Sample records for model state drug
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Mathematical modeling of drug dissolution.
Siepmann, J; Siepmann, F
2013-08-30
The dissolution of a drug administered in the solid state is a pre-requisite for efficient subsequent transport within the human body. This is because only dissolved drug molecules/ions/atoms are able to diffuse, e.g. through living tissue. Thus, generally major barriers, including the mucosa of the gastro intestinal tract, can only be crossed after dissolution. Consequently, the process of dissolution is of fundamental importance for the bioavailability and, hence, therapeutic efficacy of various pharmaco-treatments. Poor aqueous solubility and/or very low dissolution rates potentially lead to insufficient availability at the site of action and, hence, failure of the treatment in vivo, despite a potentially ideal chemical structure of the drug to interact with its target site. Different physical phenomena are involved in the process of drug dissolution in an aqueous body fluid, namely the wetting of the particle's surface, breakdown of solid state bonds, solvation, diffusion through the liquid unstirred boundary layer surrounding the particle as well as convection in the surrounding bulk fluid. Appropriate mathematical equations can be used to quantify these mass transport steps, and more or less complex theories can be developed to describe the resulting drug dissolution kinetics. This article gives an overview on the current state of the art of modeling drug dissolution and points out the assumptions the different theories are based on. Various practical examples are given in order to illustrate the benefits of such models. This review is not restricted to mathematical theories considering drugs exhibiting poor aqueous solubility and/or low dissolution rates, but also addresses models quantifying drug release from controlled release dosage forms, in which the process of drug dissolution plays a major role. Copyright © 2013 Elsevier B.V. All rights reserved.
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State Drug Utilization Data 2017
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2016
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2011
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2003
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2008
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1992
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1995
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1998
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2014
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2005
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2002
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2004
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1993
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2006
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2012
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1999
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2015
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1997
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1991
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2001
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2007
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2013
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 2009
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1996
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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State Drug Utilization Data 1994
U.S. Department of Health & Human Services — Drug utilization data are reported by states for covered outpatient drugs that are paid for by state Medicaid agencies since the start of the Medicaid Drug Rebate...
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The Food and Drug Administration and Drug Legalization: A Brief Model of Regulation
Kalam, Murad
2002-01-01
This paper offers a brief model of FDA regulation of currently illegal narcotics in the United States. Given that nearly three out of four Americans believe that the drug war has failed, recent calls from prominent liberal and conservative thinkers to legalize drugs, and state “compassionate use†ballot initiatives, future drug legalization is at least conceivable in the United States. Yet, how would the FDA regulate NLD’s under its current st...
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Drug-model membrane interactions
International Nuclear Information System (INIS)
Deniz, Usha K.
1994-01-01
In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab
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Heisig, M; Lieckfeldt, R; Wittum, G; Mazurkevich, G; Lee, G
1996-03-01
The diffusion equation should be solved for the non-steady-state problem of drug diffusion within a two-dimensional, biphasic stratum corneum membrane having homogeneous lipid and corneocyte phases. A numerical method was developed for a brick-and-mortar SC-geometry, enabling an explicit solution for time-dependent drug concentration within both phases. The lag time and permeability were calculated. It is shown how the barrier property of this model membrane depends on relative phase permeability, corneocyte alignment, and corneocyte-lipid partition coefficient. Additionally, the time-dependent drug concentration profiles within the membrane can be observed during the lag and steady-state phases. The model SC-membrane predicts, from purely morphological principles, lag times and permeabilities that are in good agreement with experimental values. The long lag times and very small permeabilities reported for human SC can only be predicted for a highly-staggered corneocyte geometry and corneocytes that are 1000 times less permeable than the lipid phase. Although the former conclusion is reasonable, the latter is questionable. The elongated, flattened corneocyte shape renders lag time and permeability insensitive to large changes in their alignment within the SC. Corneocyte/lipid partitioning is found to be fundamentally different to SC/donor partitioning, since increasing drug lipophilicity always reduces both lag time and permeability.
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Drug Poisoning Mortality by State: United States
U.S. Department of Health & Human Services — This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug...
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NCHS - Drug Poisoning Mortality by State: United States
U.S. Department of Health & Human Services — This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug...
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A two-dimensional mathematical model of percutaneous drug absorption
Directory of Open Access Journals (Sweden)
Kubota K
2004-06-01
Full Text Available Abstract Background When a drug is applied on the skin surface, the concentration of the drug accumulated in the skin and the amount of the drug eliminated into the blood vessel depend on the value of a parameter, r. The values of r depend on the amount of diffusion and the normalized skin-capillary clearence. It is defined as the ratio of the steady-state drug concentration at the skin-capillary boundary to that at the skin-surface in one-dimensional models. The present paper studies the effect of the parameter values, when the region of contact of the skin with the drug, is a line segment on the skin surface. Methods Though a simple one-dimensional model is often useful to describe percutaneous drug absorption, it may be better represented by multi-dimensional models. A two-dimensional mathematical model is developed for percutaneous absorption of a drug, which may be used when the diffusion of the drug in the direction parallel to the skin surface must be examined, as well as in the direction into the skin, examined in one-dimensional models. This model consists of a linear second-order parabolic equation with appropriate initial conditions and boundary conditions. These boundary conditions are of Dirichlet type, Neumann type or Robin type. A finite-difference method which maintains second-order accuracy in space along the boundary, is developed to solve the parabolic equation. Extrapolation in time is applied to improve the accuracy in time. Solution of the parabolic equation gives the concentration of the drug in the skin at a given time. Results Simulation of the numerical methods described is carried out with various values of the parameter r. The illustrations are given in the form of figures. Conclusion Based on the values of r, conclusions are drawn about (1 the flow rate of the drug, (2 the flux and the cumulative amount of drug eliminated into the receptor cell, (3 the steady-state value of the flux, (4 the time to reach the steady-state
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Darwish, Kinda A; Mrestani, Yahya; Rüttinger, Hans-Hermann; Neubert, Reinhard H H
2016-05-01
Is to characterize the drug release from the ß-cyclodextrin (ß-CD) cavity and the drug transfer into model membranes by affinity capillary electrophoresis. Phospholipid liposomes with and without cholesterol were used to mimic the natural biological membrane. The interaction of cationic and anionic drugs with ß-CD and the interaction of the drugs with liposomes were detected separately by measuring the drug mobility in ß-CD containing buffer and liposome containing buffer; respectively. Moreover, the kinetics of drug release from ß-CD and its transfer into liposomes with or without cholesterol was studied by investigation of changes in the migration behaviours of the drugs in samples, contained drug, ß-CD and liposome, at 1:1:1 molar ratio at different time intervals; zero time, 30 min, 1, 2, 4, 6, 8, 10 and 24 h. Lipophilic drugs such as propranolol and ibuprofen were chosen for this study, because they form complexes with ß-CD. The mobility of the both drug liposome mixtures changed with time to a final state. For samples of liposomal membranes with cholesterol the final state was faster reached than without cholesterol. The study confirmed that the drug release from the CD cavity and its transfer into the model membrane was more enhanced by the competitive displacement of the drug from the ß-CD cavity by cholesterol, the membrane component. The ACE method here developed can be used to optimize the drug release from CD complexes and the drug transfer into model membranes.
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Multiscale Modeling in the Clinic: Drug Design and Development
Energy Technology Data Exchange (ETDEWEB)
Clancy, Colleen E.; An, Gary; Cannon, William R.; Liu, Yaling; May, Elebeoba E.; Ortoleva, Peter; Popel, Aleksander S.; Sluka, James P.; Su, Jing; Vicini, Paolo; Zhou, Xiaobo; Eckmann, David M.
2016-02-17
A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.
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Energy Technology Data Exchange (ETDEWEB)
Slikker, William; Young, John F.; Corley, Rick A.; Dorman, David C.; Conolly, Rory B.; Knudsen, Thomas; Erstad, Brian L.; Luecke, Richard H.; Faustman, Elaine M.; Timchalk, Chuck; Mattison, Donald R.
2005-07-26
A workshop was conducted on November 18?19, 2004, to address the issue of improving predictive models for drug delivery to developing humans. Although considerable progress has been made for adult humans, large gaps remain for predicting pharmacokinetic/pharmacodynamic (PK/PD) outcome in children because most adult models have not been tested during development. The goals of the meeting included a description of when, during development, infants/children become adultlike in handling drugs. The issue of incorporating the most recent advances into the predictive models was also addressed: both the use of imaging approaches and genomic information were considered. Disease state, as exemplified by obesity, was addressed as a modifier of drug pharmacokinetics and pharmacodynamics during development. Issues addressed in this workshop should be considered in the development of new predictive and mechanistic models of drug kinetics and dynamics in the developing human.
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Target-mediated drug disposition model and its approximations for antibody-drug conjugates.
Gibiansky, Leonid; Gibiansky, Ekaterina
2014-02-01
Antibody-drug conjugate (ADC) is a complex structure composed of an antibody linked to several molecules of a biologically active cytotoxic drug. The number of ADC compounds in clinical development now exceeds 30, with two of them already on the market. However, there is no rigorous mechanistic model that describes pharmacokinetic (PK) properties of these compounds. PK modeling of ADCs is even more complicated than that of other biologics as the model should describe distribution, binding, and elimination of antibodies with different toxin load, and also the deconjugation process and PK of the released toxin. This work extends the target-mediated drug disposition (TMDD) model to describe ADCs, derives the rapid binding (quasi-equilibrium), quasi-steady-state, and Michaelis-Menten approximations of the TMDD model as applied to ADCs, derives the TMDD model and its approximations for ADCs with load-independent properties, and discusses further simplifications of the system under various assumptions. The developed models are shown to describe data simulated from the available clinical population PK models of trastuzumab emtansine (T-DM1), one of the two currently approved ADCs. Identifiability of model parameters is also discussed and illustrated on the simulated T-DM1 examples.
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Vaginal drug distribution modeling.
Katz, David F; Yuan, Andrew; Gao, Yajing
2015-09-15
This review presents and applies fundamental mass transport theory describing the diffusion and convection driven mass transport of drugs to the vaginal environment. It considers sources of variability in the predictions of the models. It illustrates use of model predictions of microbicide drug concentration distribution (pharmacokinetics) to gain insights about drug effectiveness in preventing HIV infection (pharmacodynamics). The modeling compares vaginal drug distributions after different gel dosage regimens, and it evaluates consequences of changes in gel viscosity due to aging. It compares vaginal mucosal concentration distributions of drugs delivered by gels vs. intravaginal rings. Finally, the modeling approach is used to compare vaginal drug distributions across species with differing vaginal dimensions. Deterministic models of drug mass transport into and throughout the vaginal environment can provide critical insights about the mechanisms and determinants of such transport. This knowledge, and the methodology that obtains it, can be applied and translated to multiple applications, involving the scientific underpinnings of vaginal drug distribution and the performance evaluation and design of products, and their dosage regimens, that achieve it. Copyright © 2015 Elsevier B.V. All rights reserved.
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López-Moreno, Sergio; Martínez-Ojeda, Rosa Haydeé; López-Arellano, Oliva; Jarillo-Soto, Edgar; Castro-Albarrán, Juan Manuel
2011-01-01
To assess the consequences of private outsourcing on the overall supply and filling of prescriptions in state health services. The research was conducted using quantitative and qualitative techniques in 13 states. The information was collected through interviews and direct observation. The interviews were carried on staff of state health services related to the drug supply chain and users of health services. The quantitative approach examined the percentage of stocked full recipes in a sample of users. States that have opted for the fully outsourced model, and properly monitored this choice, have increased the supply of drugs to their users and guaranteed the supply in the care units in charge. Other states with the outsourced model have multiple problems: direct purchase of drugs not included in the basic drugs catalogue, failure of suppliers and shortage of supplies in the laboratories that provide the company. The main disadvantages identified in all models were: the subordination of the medical criteria to administrative criteria, insufficient planning based on local care needs, heterogeneous procedures, insufficient knowledge of regulations and lack of normativity. The results indicate that the incorporation of private providers in the drug supply chain may not be the solution to bring down the shortage faced by health services, especially at the hospital level. The shift to outsourcing models has developed without incorporating evaluation mechanisms and the consequences that this transition can have on state health systems must be investigated more deeply.
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Multiscale modeling of transdermal drug delivery
Rim, Jee Eun
2006-04-01
This study addresses the modeling of transdermal diffusion of drugs, to better understand the permeation of molecules through the skin, and especially the stratum corneum, which forms the main permeation barrier of the skin. In transdermal delivery of systemic drugs, the drugs diffuse from a patch placed on the skin through the epidermis to the underlying blood vessels. The epidermis is the outermost layer of the skin and can be further divided into the stratum corneum (SC) and the viable epidermis layers. The SC consists of keratinous cells (corneocytes) embedded in the lipid multi-bilayers of the intercellular space. It is widely accepted that the barrier properties of the skin mostly arises from the ordered structure of the lipid bilayers. The diffusion path, at least for lipophilic molecules, seems to be mainly through the lipid bilayers. Despite the advantages of transdermal drug delivery compared to other drug delivery routes such as oral dosing and injections, the low percutaneous permeability of most compounds is a major difficulty in the wide application of transdermal drug delivery. In fact, many transdermal drug formulations include one or more permeation enhancers that increase the permeation of the drug significantly. During the last two decades, many researchers have studied percutaneous absorption of drugs both experimentally and theoretically. However, many are based on pharmacokinetic compartmental models, in which steady or pseudo-steady state conditions are assumed, with constant diffusivity and partitioning for single component systems. This study presents a framework for studying the multi-component diffusion of drugs coupled with enhancers through the skin by considering the microstructure of the stratum corneum (SC). A multiscale framework of modeling the transdermal diffusion of molecules is presented, by first calculating the microscopic diffusion coefficient in the lipid bilayers of the SC using molecular dynamics (MD). Then a
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QSAR Modeling and Prediction of Drug-Drug Interactions.
Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C
2016-02-01
Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.
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Drug Poisoning Mortality by County: United States
U.S. Department of Health & Human Services — This dataset describes drug poisoning deaths at the U.S. and state level by selected demographic characteristics, and includes age-adjusted death rates for drug...
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Ellinwood, Nicholas; Dobrev, Dobromir; Morotti, Stefano; Grandi, Eleonora
2017-09-01
The KV1.5 potassium channel, which underlies the ultra-rapid delayed-rectifier current (IKur) and is predominantly expressed in atria vs. ventricles, has emerged as a promising target to treat atrial fibrillation (AF). However, while numerous KV1.5-selective compounds have been screened, characterized, and tested in various animal models of AF, evidence of antiarrhythmic efficacy in humans is still lacking. Moreover, current guidelines for pre-clinical assessment of candidate drugs heavily rely on steady-state concentration-response curves or IC50 values, which can overlook adverse cardiotoxic effects. We sought to investigate the effects of kinetics and state-dependent binding of IKur-targeting drugs on atrial electrophysiology in silico and reveal the ideal properties of IKur blockers that maximize anti-AF efficacy and minimize pro-arrhythmic risk. To this aim, we developed a new Markov model of IKur that describes KV1.5 gating based on experimental voltage-clamp data in atrial myocytes from patient right-atrial samples in normal sinus rhythm. We extended the IKur formulation to account for state-specificity and kinetics of KV1.5-drug interactions and incorporated it into our human atrial cell model. We simulated 1- and 3-Hz pacing protocols in drug-free conditions and with a [drug] equal to the IC50 value. The effects of binding and unbinding kinetics were determined by examining permutations of the forward (kon) and reverse (koff) binding rates to the closed, open, and inactivated states of the KV1.5 channel. We identified a subset of ideal drugs exhibiting anti-AF electrophysiological parameter changes at fast pacing rates (effective refractory period prolongation), while having little effect on normal sinus rhythm (limited action potential prolongation). Our results highlight that accurately accounting for channel interactions with drugs, including kinetics and state-dependent binding, is critical for developing safer and more effective pharmacological anti
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Market power and state costs of HIV/AIDS drugs.
Leibowitz, Arleen A; Sood, Neeraj
2007-03-01
We examine whether U.S. states can use their market power to reduce the costs of supplying prescription drugs to uninsured and underinsured persons with HIV through a public program, the AIDS Drug Assistance Program (ADAP). Among states that purchase drugs from manufacturers and distribute them directly to clients, those that purchase a greater volume pay lower average costs per prescription. Among states depending on retail pharmacies to distribute drugs and then claiming rebates from manufacturers, those that contract with smaller numbers of pharmacy networks have lower average costs. Average costs per prescription do not differ between the two purchase methods.
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Mathematical modeling and computational prediction of cancer drug resistance.
Sun, Xiaoqiang; Hu, Bin
2017-06-23
Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of
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Drug-Excipient Interactions in the Solid State: The Role of Different Stress Factors.
Gressl, Corinna; Brunsteiner, Michael; Davis, Adrian; Landis, Margaret; Pencheva, Klimentina; Scrivens, Garry; Sluggett, Gregory W; Wood, Geoffrey P F; Gruber-Woelfler, Heidrun; Khinast, Johannes G; Paudel, Amrit
2017-12-04
Understanding properties and mechanisms that govern drug degradation in the solid state is of high importance to ensure drug stability and safety of solid dosage forms. In this study, we attempt to understand drug-excipient interactions in the solid state using both theoretical and experimental approaches. The model active pharmaceutical ingredients (APIs) under study are carvedilol (CAR) and codeine phosphate (COP), which are known to undergo esterification with citric acid (CA) in the solid state. Starting from the crystal structures of two different polymorphs of each compound, we calculated the exposure and accessibility of reactive hydroxyl groups for a number of relevant crystal surfaces, as well as descriptors that could be associated with surface stabilities using molecular simulations. Accelerated degradation experiments at elevated temperature and controlled humidity were conducted to assess the propensity of different solid forms of the model APIs to undergo chemical reactions with anhydrous CA or CA monohydrate. In addition, for CAR, we studied the solid state degradation at varying humidity levels and also under mechano-activation. Regarding the relative degradation propensities, we found that variations in the exposure and accessibility of molecules on the crystal surface play a minor role compared to the impact of molecular mobility due to different levels of moisture. We further studied drug-excipient interactions under mechano-activation (comilling of API and CA) and found that the reaction proceeded even faster than in physical powder mixtures kept at accelerated storage conditions.
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A State-by-State Analysis of Laws Dealing With Driving Under the Influence of Drugs
2009-12-01
This study reviewed each State statute regarding drug-impaired driving as of December 2008. There : is a high degree of variability across the States in the ways they approach drug-impaired driving. : Current laws in many States contain provisions ma...
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Salmas, Ramin Ekhteiari; Yurtsever, Mine; Stein, Matthias; Durdagi, Serdar
2015-05-01
Homology model structures of the dopamine D2 receptor (D2R) were generated starting from the active and inactive states of β2-adrenergic crystal structure templates. To the best of our knowledge, the active conformation of D2R was modeled for the first time in this study. The homology models are built and refined using MODELLER and ROSETTA programs. Top-ranked models have been validated with ligand docking simulations and in silico Alanine-scanning mutagenesis studies. The derived extra-cellular loop region of the protein models is directed toward the binding site cavity which is often involved in ligand binding. The binding sites of protein models were refined using induced fit docking to enable the side-chain refinement during ligand docking simulations. The derived models were then tested using molecular modeling techniques on several marketed drugs for schizophrenia. Alanine-scanning mutagenesis and molecular docking studies gave similar results for marketed drugs tested. We believe that these new D2 receptor models will be very useful for a better understanding of the mechanisms of action of drugs to be targeted to the binding sites of D2Rs and they will contribute significantly to drug design studies involving G-protein-coupled receptors in the future.
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Modeling Drug-Carrier Interaction in the Drug Release from Nanocarriers
Directory of Open Access Journals (Sweden)
Like Zeng
2011-01-01
Full Text Available Numerous nanocarriers of various compositions and geometries have been developed for the delivery and release of therapeutic and imaging agents. Due to the high specific surface areas of nanocarriers, different mechanisms such as ion pairing and hydrophobic interaction need to be explored for achieving sustained release. Recently, we developed a three-parameter model that considers reversible drug-carrier interaction and first-order drug release from liposomes. A closed-form analytical solution was obtained. Here, we further explore the ability of the model to capture the release of bioactive molecules such as drugs and growth factors from various nanocarriers. A parameter study demonstrates that the model is capable of resembling major categories of drug release kinetics. We further fit the model to 60 sets of experimental data from various drug release systems, including nanoparticles, hollow particles, fibers, and hollow fibers. Additionally, bootstrapping is used to evaluate the accuracy of parameter determination and validate the model in selected cases. The simplicity and universality of the model and the clear physical meanings of each model parameter render the model useful for the design and development of new drug delivery systems.
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Koch, Gilbert; Jusko, William J; Schropp, Johannes
2017-02-01
Target-mediated drug disposition (TMDD) describes drug binding with high affinity to a target such as a receptor. In application TMDD models are often over-parameterized and quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are essential to reduce the number of parameters. However, implementation of such approximations becomes difficult for TMDD models with drug-drug interaction (DDI) mechanisms. Hence, alternative but equivalent formulations are necessary for QE or QSS approximations. To introduce and develop such formulations, the single drug case is reanalyzed. This work opens the route for straightforward implementation of QE or QSS approximations of DDI TMDD models. The manuscript is the first part to introduce DDI TMDD models with QE or QSS approximations.
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Shaparin, Naum; Mehta, Neel; Kunkel, Frank; Stripp, Richard; Borg, Damon; Kolb, Elizabeth
2017-11-01
Interpretation limitations of urine drug testing and the invasiveness of blood toxicology have motivated the desire for the development of simpler methods to assess biologically active drug levels on an individualized patient basis. Oral fluid is a matrix well-suited for the challenge because collections are based on simple noninvasive procedures and drug concentrations better correlate to blood drug levels as oral fluid is a filtrate of the blood. Well-established pharmacokinetic models were utilized to generate oral fluid steady state concentration ranges to assess the interpretive value of the alternative matrix to monitor steady state plasma oxycodone levels. Paired oral fluid and plasma samples were collected from patients chronically prescribed oxycodone and quantitatively analyzed by liquid chromatography tandem mass spectrometry. Steady state plasma concentration ranges were calculated for each donor and converted to an equivalent range in oral fluid. Measured plasma and oral fluid oxycodone concentrations were compared with respective matrix-matched steady state ranges, using each plasma steady state classification as the control. A high degree of correlation was observed between matrices when classifying donors according to expected steady state oxycodone concentration. Agreement between plasma and oral fluid steady state classifications was observed in 75.6% of paired samples. This study supports novel application of basic pharmacokinetic knowledge to the pain management industry, simplifying and improving individualized drug monitoring and risk assessment through the use of oral fluid drug testing. Many benefits of established therapeutic drug monitoring in plasma can be realized in oral fluid for patients chronically prescribed oxycodone at steady state. © 2017 American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
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A Profile of Substance Abuse, Gender, Crime, and Drug Policy in the United States and Canada
Grant, Judith
2009-01-01
The climate of domestic drug policy in the United States as it pertains to both women and men at the beginning of the 21st century is the criminalization mode of regulation--a mode that is based on the model of addiction as a crime and one that is used to prohibit the use of illegal drugs. In Canada, drug policy is based mainly on the harm…
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An attention-based effective neural model for drug-drug interactions extraction.
Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian
2017-10-10
Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.
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Light, Michael T; Miller, Ty; Kelly, Brian C
2017-09-01
To examine the influence of undocumented immigration in the United States on 4 different metrics of drug and alcohol problems: drug arrests, drug overdose fatalities, driving under the influence (DUI) arrests, and DUI deaths. We combined newly developed state-level estimates of the undocumented population between 1990 and 2014 from the Center for Migration Studies with arrest data from the Federal Bureau of Investigation Uniform Crime Reports and fatality information from the Fatality Analysis Reporting System and the Centers for Disease Control and Prevention Underlying Cause of Death database. We used fixed-effects regression models to examine the longitudinal association between increased undocumented immigration and drug problems and drunk driving. Increased undocumented immigration was significantly associated with reductions in drug arrests, drug overdose deaths, and DUI arrests, net of other factors. There was no significant relationship between increased undocumented immigration and DUI deaths. This study provides evidence that undocumented immigration has not increased the prevalence of drug or alcohol problems, but may be associated with reductions in these public health concerns.
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Investigating drug repositioning opportunities in FDA drug labels through topic modeling.
Bisgin, Halil; Liu, Zhichao; Kelly, Reagan; Fang, Hong; Xu, Xiaowei; Tong, Weida
2012-01-01
Drug repositioning offers an opportunity to revitalize the slowing drug discovery pipeline by finding new uses for currently existing drugs. Our hypothesis is that drugs sharing similar side effect profiles are likely to be effective for the same disease, and thus repositioning opportunities can be identified by finding drug pairs with similar side effects documented in U.S. Food and Drug Administration (FDA) approved drug labels. The safety information in the drug labels is usually obtained in the clinical trial and augmented with the observations in the post-market use of the drug. Therefore, our drug repositioning approach can take the advantage of more comprehensive safety information comparing with conventional de novo approach. A probabilistic topic model was constructed based on the terms in the Medical Dictionary for Regulatory Activities (MedDRA) that appeared in the Boxed Warning, Warnings and Precautions, and Adverse Reactions sections of the labels of 870 drugs. Fifty-two unique topics, each containing a set of terms, were identified by using topic modeling. The resulting probabilistic topic associations were used to measure the distance (similarity) between drugs. The success of the proposed model was evaluated by comparing a drug and its nearest neighbor (i.e., a drug pair) for common indications found in the Indications and Usage Section of the drug labels. Given a drug with more than three indications, the model yielded a 75% recall, meaning 75% of drug pairs shared one or more common indications. This is significantly higher than the 22% recall rate achieved by random selection. Additionally, the recall rate grows rapidly as the number of drug indications increases and reaches 84% for drugs with 11 indications. The analysis also demonstrated that 65 drugs with a Boxed Warning, which indicates significant risk of serious and possibly life-threatening adverse effects, might be replaced with safer alternatives that do not have a Boxed Warning. In
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Beyond the drug-terror nexus: drug trafficking and state-crime relations in Central Asia.
De Danieli, Filippo
2014-11-01
In the wake of collapse of the Soviet Union, Central Asia has transformed into a key hub along the Afghan opiates trafficking routes. Around 30 percent of the heroin manufactured in Afghanistan is estimated to be smuggled through Central Asian republics in its way to booming drug markets in Russia and Eastern Europe. Building upon available evidence and extensive fieldwork research, the article seeks to confute mainstream analyses which emphasize connections between criminal and terrorist networks. The focus is on conducive factors for the establishment of drug routes in Central Asia, the characteristics of drug related networks, and the nature of political-criminal relations across the region. It is argued that in all five Central Asia republics strategic partnerships have formed between drug traffickers and state actors around the exploitation of drug rents and that mafias' influence on politics is stronger in Tajikistan and Kyrgyzstan, the region's poorest countries. By moving the focus from narco-terror to the state-crime connections, the article provides a critical insight into political economy issues surrounding a complex and multifaceted phenomenon such as the drug trade. Copyright © 2014. Published by Elsevier B.V.
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State and Community Responses to Drug-related Violence in Mexico
International Development Research Centre (IDRC) Digital Library (Canada)
Extrants. Études. State and community responses to drug-related violence in Mexico. Rapports. Respuestas estatales y comunitarias a la violencia asociada al narcotráfico en México : informe técnico. Rapports. State and community responses to drug-related violence in Mexico ...
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Denatured protein-coated docetaxel nanoparticles: Alterable drug state and cytosolic delivery.
Zhang, Li; Xiao, Qingqing; Wang, Yiran; Zhang, Chenshuang; He, Wei; Yin, Lifang
2017-05-15
Many lead compounds have a low solubility in water, which substantially hinders their clinical application. Nanosuspensions have been considered a promising strategy for the delivery of water-insoluble drugs. Here, denatured soy protein isolate (SPI)-coated docetaxel nanosuspensions (DTX-NS) were developed using an anti-solvent precipitation-ultrasonication method to improve the water-solubility of DTX, thus improving its intracellular delivery. DTX-NS, with a diameter of 150-250nm and drug-loading up to 18.18%, were successfully prepared by coating drug particles with SPI. Interestingly, the drug state of DTX-NS was alterable. Amorphous drug nanoparticles were obtained at low drug-loading, whereas at a high drug-loading, the DTX-NS drug was mainly present in the crystalline state. Moreover, DTX-NS could be internalized at high levels by cancer cells and enter the cytosol by lysosomal escape, enhancing cell cytotoxicity and apoptosis compared with free DTX. Taken together, denatured SPI has a strong stabilization effect on nanosuspensions, and the drug state in SPI-coated nanosuspensions is alterable by changing the drug-loading. Moreover, DTX-NS could achieve cytosolic delivery, generating enhanced cell cytotoxicity against cancer cells. Copyright © 2017 Elsevier B.V. All rights reserved.
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Mathematical modeling of drug release from lipid dosage forms.
Siepmann, J; Siepmann, F
2011-10-10
Lipid dosage forms provide an interesting potential for controlled drug delivery. In contrast to frequently used poly(ester) based devices for parenteral administration, they do not lead to acidification upon degradation and potential drug inactivation, especially in the case of protein drugs and other acid-labile active agents. The aim of this article is to give an overview on the current state of the art of mathematical modeling of drug release from this type of advanced drug delivery systems. Empirical and semi-empirical models are described as well as mechanistic theories, considering diffusional mass transport, potentially limited drug solubility and the leaching of other, water-soluble excipients into the surrounding bulk fluid. Various practical examples are given, including lipid microparticles, beads and implants, which can successfully be used to control the release of an incorporated drug during periods ranging from a few hours up to several years. The great benefit of mechanistic mathematical theories is the possibility to quantitatively predict the effects of different formulation parameters and device dimensions on the resulting drug release kinetics. Thus, in silico simulations can significantly speed up product optimization. This is particularly useful if long release periods (e.g., several months) are targeted, since experimental trial-and-error studies are highly time-consuming in these cases. In the future it would be highly desirable to combine mechanistic theories with the quantitative description of the drug fate in vivo, ideally including the pharmacodynamic efficacy of the treatments. Copyright © 2011 Elsevier B.V. All rights reserved.
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Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.
Kim, Munju; Gillies, Robert J; Rejniak, Katarzyna A
2013-11-18
Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.
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A state-of-the-art multi-criteria model for drug benefit-risk analysis
Tervonen, T.; Hillege, H.L.; Buskens, E.; Postmus, D.
2010-01-01
Drug benefit-risk analysis is based on firm clinical evidence related to various safety and efficacy outcomes, such as tolerability, treatment response, and adverse events. In this paper, we propose a new approach for constructing a supporting multi-criteria model that fully takes into account this
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Animal models of drug addiction.
García Pardo, María Pilar; Roger Sánchez, Concepción; De la Rubia Ortí, José Enrique; Aguilar Calpe, María Asunción
2017-09-29
The development of animal models of drug reward and addiction is an essential factor for progress in understanding the biological basis of this disorder and for the identification of new therapeutic targets. Depending on the component of reward to be studied, one type of animal model or another may be used. There are models of reinforcement based on the primary hedonic effect produced by the consumption of the addictive substance, such as the self-administration (SA) and intracranial self-stimulation (ICSS) paradigms, and there are models based on the component of reward related to associative learning and cognitive ability to make predictions about obtaining reward in the future, such as the conditioned place preference (CPP) paradigm. In recent years these models have incorporated methodological modifications to study extinction, reinstatement and reconsolidation processes, or to model specific aspects of addictive behavior such as motivation to consume drugs, compulsive consumption or drug seeking under punishment situations. There are also models that link different reinforcement components or model voluntary motivation to consume (two-bottle choice, or drinking in the dark tests). In short, innovations in these models allow progress in scientific knowledge regarding the different aspects that lead individuals to consume a drug and develop compulsive consumption, providing a target for future treatments of addiction.
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Ahuja, Naveen; Katare, Om Prakash; Singh, Bhupinder
2007-01-01
Role of various water-soluble carriers was studied for dissolution enhancement of a poorly soluble model drug, rofecoxib, using solid dispersion approach. Diverse carriers viz. polyethylene glycols (PEG 4000 and 6000), polyglycolized fatty acid ester (Gelucire 44/14), polyvinylpyrollidone K25 (PVP), poloxamers (Lutrol F127 and F68), polyols (mannitol, sorbitol), organic acid (citric acid) and hydrotropes (urea, nicotinamide) were investigated for the purpose. Phase-solubility studies revealed AL type of curves for each carrier, indicating linear increase in drug solubility with carrier concentration. The sign and magnitude of the thermodynamic parameter, Gibbs free energy of transfer, indicated spontaneity of solubilization process. All the solid dispersions showed dissolution improvement vis-à-vis pure drug to varying degrees, with citric acid, PVP and poloxamers as the most promising carriers. Mathematical modeling of in vitro dissolution data indicated the best fitting with Korsemeyer-Peppas model and the drug release kinetics primarily as Fickian diffusion. Solid state characterization of the drug-poloxamer binary system using XRD, FTIR, DSC and SEM techniques revealed distinct loss of drug crystallinity in the formulation, ostensibly accounting for enhancement in dissolution rate.
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Wing, Deborah A; Powers, Barbara; Hickok, Durlin
2010-04-01
The process for drug approval in the United States is complex and time-consuming. There are comparatively few drugs with U.S. Food and Drug Administration (FDA)-approved indications for obstetric use in this country at this time; however, several are under development. We review the process for drug approval and recount the approval histories of obstetric drugs reviewed in the recent past. We also outline the current status of two progestational agents that are under development. For a variety of reasons, including a small market compared with others such as cardiology or oncology, and the potential of being drawn into medical-legal litigation, sponsors are disinclined to pursue drug development for obstetric purposes in this country. We compare the procedures for review and approval of drugs in the United States with those in Europe, and note that recent changes within the FDA may result in not only more drugs being approved but also changes in labeling of already approved drugs. Special programs to facilitate drug development and reforms to modernize the process and improve safety are discussed. These may result in changes in labeling of already approved drugs. Obstacles such as funding and liability are also discussed.
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Mack, Karin A; Jones, Christopher M; Ballesteros, Michael F
2017-10-20
Drug overdoses are a leading cause of injury death in the United States, resulting in approximately 52,000 deaths in 2015. Understanding differences in illicit drug use, illicit drug use disorders, and overall drug overdose deaths in metropolitan and nonmetropolitan areas is important for informing public health programs, interventions, and policies. Illicit drug use and drug use disorders during 2003-2014, and drug overdose deaths during 1999-2015. The National Survey of Drug Use and Health (NSDUH) collects information through face-to-face household interviews about the use of illicit drugs, alcohol, and tobacco among the U.S. noninstitutionalized civilian population aged ≥12 years. Respondents include residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories, migratory workers' camps, and halfway houses) and civilians living on military bases. NSDUH variables include sex, age, race/ethnicity, residence (metropolitan/nonmetropolitan), annual household income, self-reported drug use, and drug use disorders. National Vital Statistics System Mortality (NVSS-M) data for U.S. residents include information from death certificates filed in the 50 states and the District of Columbia. Cases were selected with an underlying cause of death based on the ICD-10 codes for drug overdoses (X40-X44, X60-X64, X85, and Y10-Y14). NVSS-M variables include decedent characteristics (sex, age, and race/ethnicity) and information on intent (unintentional, suicide, homicide, or undetermined), location of death (medical facility, in a home, or other [including nursing homes, hospices, unknown, and other locations]) and county of residence (metropolitan/nonmetropolitan). Metropolitan/nonmetropolitan status is assigned independently in each data system. NSDUH uses a three-category system: Core Based Statistical Area (CBSA) of ≥1 million persons; CBSA of illicit drugs, the prevalence was highest for the large metropolitan areas compared with
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Directory of Open Access Journals (Sweden)
Yvonne Paulley
2010-01-01
Full Text Available Reverse iontophoresis is a relatively new technique for non-invasive drug monitoring in the body. It involves a small electrical current being passed through the skin to facilitate the movement of small charged ions and polar molecules on the skin's surface where the amount of drug can then be measured and hence an accurate estimate of the blood concentration can be made. In vivo studies for several molecules show that initially large amounts of drug are extracted from the body, which are unrelated to the magnitude of the blood concentration; over time the fluxes of extraction decrease to a level proportional to the steady state blood concentration. This suggests that, at first, the drug is being extracted from some source other than the blood; one such candidate for this source is the dead cells which form the stratum corneum. In this paper, we construct two related mathematical models; the first describes the formation of the drug reservoir in the stratum corneum as a consequence of repeated drug intake and natural death of skin cells in the body. The output from this model provides initial conditions for the model of reverse iontophoresis in which charged ions from both the blood and the stratum corneum reservoir compete for the electric current. Model parameters are estimated from data collected for lithium monitoring. Our models will improve interpretation of reverse iontophoretic data by discriminating the subdermal from the skin contribution to the fluxes of extraction. They also suggest that analysis of the skin reservoir might be a valuable tool to investigate patients' exposure to chemicals including therapeutic drugs.
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SEIIrR: Drug abuse model with rehabilitation
Sutanto, Azizah, Afina; Widyaningsih, Purnami; Saputro, Dewi Retno Sari
2017-05-01
Drug abuse in the world quite astonish and tend to increase. The increase and decrease on the number of drug abusers showed a pattern of spread that had the same characteristics with patterns of spread of infectious disease. The susceptible infected removed (SIR) and susceptible exposed infected removed (SEIR) epidemic models for infectious disease was developed to study social epidemic. In this paper, SEIR model for disease epidemic was developed to study drug abuse epidemic with rehabilitation treatment. The aims of this paper were to analogize susceptible exposed infected isolated recovered (SEIIrR) model on the drug abusers, to determine solutions of the model, to determine equilibrium point, and to do simulation on β. The solutions of SEIIrR model was determined by using fourth order of Runge-Kutta algorithm, equilibrium point obtained was free-drug equilibrium point. Solutions of SEIIrR showed that the model was able to suppress the spread of drug abuse. The increasing value of contact rate was not affect the number of infected individuals due to rehabilitation treatment.
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Spread of anti-malarial drug resistance: Mathematical model with implications for ACT drug policies
Directory of Open Access Journals (Sweden)
Dondorp Arjen M
2008-11-01
Full Text Available Abstract Background Most malaria-endemic countries are implementing a change in anti-malarial drug policy to artemisinin-based combination therapy (ACT. The impact of different drug choices and implementation strategies is uncertain. Data from many epidemiological studies in different levels of malaria endemicity and in areas with the highest prevalence of drug resistance like borders of Thailand are certainly valuable. Formulating an appropriate dynamic data-driven model is a powerful predictive tool for exploring the impact of these strategies quantitatively. Methods A comprehensive model was constructed incorporating important epidemiological and biological factors of human, mosquito, parasite and treatment. The iterative process of developing the model, identifying data needed, and parameterization has been taken to strongly link the model to the empirical evidence. The model provides quantitative measures of outcomes, such as malaria prevalence/incidence and treatment failure, and illustrates the spread of resistance in low and high transmission settings. The model was used to evaluate different anti-malarial policy options focusing on ACT deployment. Results The model predicts robustly that in low transmission settings drug resistance spreads faster than in high transmission settings, and treatment failure is the main force driving the spread of drug resistance. In low transmission settings, ACT slows the spread of drug resistance to a partner drug, especially at high coverage rates. This effect decreases exponentially with increasing delay in deploying the ACT and decreasing rates of coverage. In the high transmission settings, however, drug resistance is driven by the proportion of the human population with a residual drug level, which gives resistant parasites some survival advantage. The spread of drug resistance could be slowed down by controlling presumptive drug use and avoiding the use of combination therapies containing drugs with
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Drug Per Se Laws: A Review of their Use in States
2010-07-01
This report summarizes a study of the implementation of drug per se laws in 15 States. These laws generally make it an : impaired-driving offense to drive with a measurable amount of certain drugs in ones system. The specific prohibited : drugs va...
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Preclinical experimental models of drug metabolism and disposition in drug discovery and development
Directory of Open Access Journals (Sweden)
Donglu Zhang
2012-12-01
Full Text Available Drug discovery and development involve the utilization of in vitro and in vivo experimental models. Different models, ranging from test tube experiments to cell cultures, animals, healthy human subjects, and even small numbers of patients that are involved in clinical trials, are used at different stages of drug discovery and development for determination of efficacy and safety. The proper selection and applications of correct models, as well as appropriate data interpretation, are critically important in decision making and successful advancement of drug candidates. In this review, we discuss strategies in the applications of both in vitro and in vivo experimental models of drug metabolism and disposition.
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Abramov, Yuriy A
2015-06-01
The main purpose of this study is to define the major limiting factor in the accuracy of the quantitative structure-property relationship (QSPR) models of the thermodynamic intrinsic aqueous solubility of the drug-like compounds. For doing this, the thermodynamic intrinsic aqueous solubility property was suggested to be indirectly "measured" from the contributions of solid state, ΔGfus, and nonsolid state, ΔGmix, properties, which are estimated by the corresponding QSPR models. The QSPR models of ΔGfus and ΔGmix properties were built based on a set of drug-like compounds with available accurate measurements of fusion and thermodynamic solubility properties. For consistency ΔGfus and ΔGmix models were developed using similar algorithms and descriptor sets, and validated against the similar test compounds. Analysis of the relative performances of these two QSPR models clearly demonstrates that it is the solid state contribution which is the limiting factor in the accuracy and predictive power of the QSPR models of the thermodynamic intrinsic solubility. The performed analysis outlines a necessity of development of new descriptor sets for an accurate description of the long-range order (periodicity) phenomenon in the crystalline state. The proposed approach to the analysis of limitations and suggestions for improvement of QSPR-type models may be generalized to other applications in the pharmaceutical industry.
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Orphan diseases: state of the drug discovery art.
Volmar, Claude-Henry; Wahlestedt, Claes; Brothers, Shaun P
2017-06-01
Since 1983 more than 300 drugs have been developed and approved for orphan diseases. However, considering the development of novel diagnosis tools, the number of rare diseases vastly outpaces therapeutic discovery. Academic centers and nonprofit institutes are now at the forefront of rare disease R&D, partnering with pharmaceutical companies when academic researchers discover novel drugs or targets for specific diseases, thus reducing the failure risk and cost for pharmaceutical companies. Considerable progress has occurred in the art of orphan drug discovery, and a symbiotic relationship now exists between pharmaceutical industry, academia, and philanthropists that provides a useful framework for orphan disease therapeutic discovery. Here, the current state-of-the-art of drug discovery for orphan diseases is reviewed. Current technological approaches and challenges for drug discovery are considered, some of which can present somewhat unique challenges and opportunities in orphan diseases, including the potential for personalized medicine, gene therapy, and phenotypic screening.
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In silico modeling to predict drug-induced phospholipidosis
International Nuclear Information System (INIS)
Choi, Sydney S.; Kim, Jae S.; Valerio, Luis G.; Sadrieh, Nakissa
2013-01-01
Drug-induced phospholipidosis (DIPL) is a preclinical finding during pharmaceutical drug development that has implications on the course of drug development and regulatory safety review. A principal characteristic of drugs inducing DIPL is known to be a cationic amphiphilic structure. This provides evidence for a structure-based explanation and opportunity to analyze properties and structures of drugs with the histopathologic findings for DIPL. In previous work from the FDA, in silico quantitative structure–activity relationship (QSAR) modeling using machine learning approaches has shown promise with a large dataset of drugs but included unconfirmed data as well. In this study, we report the construction and validation of a battery of complementary in silico QSAR models using the FDA's updated database on phospholipidosis, new algorithms and predictive technologies, and in particular, we address high performance with a high-confidence dataset. The results of our modeling for DIPL include rigorous external validation tests showing 80–81% concordance. Furthermore, the predictive performance characteristics include models with high sensitivity and specificity, in most cases above ≥ 80% leading to desired high negative and positive predictivity. These models are intended to be utilized for regulatory toxicology applied science needs in screening new drugs for DIPL. - Highlights: • New in silico models for predicting drug-induced phospholipidosis (DIPL) are described. • The training set data in the models is derived from the FDA's phospholipidosis database. • We find excellent predictivity values of the models based on external validation. • The models can support drug screening and regulatory decision-making on DIPL
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DEFF Research Database (Denmark)
Svagan, Anna Justina; Müllertz, Anette; Löbmann, Korbinian
2017-01-01
OBJECTIVES: This study aimed to prepare a furosemide-loaded sustained release cellulose nanofibre (CNF)-based nanofoams with buoyancy. METHODS: Dry foams consisting of CNF and the model drug furosemide at concentrations of 21% and 50% (w/w) have been prepared by simply foaming a CNF-drug suspension...... followed by drying. The resulting foams were characterized towards their morphology, solid state properties and dissolution kinetics. KEY FINDINGS: Solid state analysis of the resulting drug-loaded foams revealed that the drug was present as an amorphous sodium furosemide salt and in form of furosemide...... form I crystals embedded in the CNF foam cell walls. The foams could easily be shaped and were flexible, and during the drug release study, the foam pieces remained intact and were floating on the surface due to their positive buoyancy. Both foams showed a sustained furosemide release compared...
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State-of-the-Art Materials for Ultrasound-Triggered Drug Delivery
Sirsi, Shashank; Borden, Mark
2014-01-01
Ultrasound is a unique and exciting theranostic modality that can be used to track drug carriers, trigger drug release and improve drug deposition with high spatial precision. In this review, we briefly describe the mechanisms of interaction between drug carriers and ultrasound waves, including cavitation, streaming and hyperthermia, and how those interactions can promote drug release and tissue uptake. We then discuss the rational design of some state-of-the-art materials for ultrasound-triggered drug delivery and review recent progress for each drug carrier, focusing on the delivery of chemotherapeutic agents such as doxorubicin. These materials include nanocarrier formulations, such as liposomes and micelles, designed specifically for ultrasound-triggered drug release, as well as microbubbles, microbubble-nanocarrier hybrids, microbubble-seeded hydrogels and phase-change agents. PMID:24389162
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Comparing Generic Drug Markets in Europe and the United States: Prices, Volumes, and Spending.
Wouters, Olivier J; Kanavos, Panos G; McKEE, Martin
2017-09-01
Policy Points: Our study indicates that there are opportunities for cost savings in generic drug markets in Europe and the United States. Regulators should make it easier for generic drugs to reach the market. Regulators and payers should apply measures to stimulate price competition among generic drugmakers and to increase generic drug use. To meaningfully evaluate policy options, it is important to analyze historical context and understand why similar initiatives failed previously. Rising drug prices are putting pressure on health care budgets. Policymakers are assessing how they can save money through generic drugs. We compared generic drug prices and market shares in 13 European countries, using data from 2013, to assess the amount of variation that exists between countries. To place these results in context, we reviewed evidence from recent studies on the prices and use of generics in Europe and the United States. We also surveyed peer-reviewed studies, gray literature, and books published since 2000 to (1) outline existing generic drug policies in European countries and the United States; (2) identify ways to increase generic drug use and to promote price competition among generic drug companies; and (3) explore barriers to implementing reform of generic drug policies, using a historical example from the United States as a case study. The prices and market shares of generics vary widely across Europe. For example, prices charged by manufacturers in Switzerland are, on average, more than 2.5 times those in Germany and more than 6 times those in the United Kingdom, based on the results of a commonly used price index. The proportion of prescriptions filled with generics ranges from 17% in Switzerland to 83% in the United Kingdom. By comparison, the United States has historically had low generic drug prices and high rates of generic drug use (84% in 2013), but has in recent years experienced sharp price increases for some off-patent products. There are policy
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A hidden Markov model to assess drug-induced sleep fragmentation in the telemetered rat.
Diack, C; Ackaert, O; Ploeger, B A; van der Graaf, P H; Gurrell, R; Ivarsson, M; Fairman, D
2011-12-01
Drug-induced sleep fragmentation can cause sleep disturbances either via their intended pharmacological action or as a side effect. Examples of disturbances include excessive daytime sleepiness, insomnia and nightmares. Developing drugs without these side effects requires insight into the mechanisms leading to sleep disturbance. The characterization of the circadian sleep pattern by EEG following drug exposure has improved our understanding of these mechanisms and their translatability across species. The EEG shows frequent transitions between specific sleep states leading to multiple correlated sojourns in these states. We have developed a Markov model to consider the high correlation in the data and quantitatively compared sleep disturbance in telemetered rats induced by methylphenidate, which is known to disturb sleep, and of a new chemical entity (NCE). It was assumed that these drugs could either accelerate or decelerate the transitions between the sleep states. The difference in sleep disturbance of methylphenidate and the NCE were quantitated and different mechanisms of action on rebound sleep were identified. The estimated effect showed that both compounds induce sleep fragmentation with methylphenidate being fivefold more potent compared to the NCE.
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Directory of Open Access Journals (Sweden)
Lisa Corina Barros de Andrade e Sousa1
2016-01-01
Full Text Available The fungus Candida albicans is the most common causative agent of human fungal infections and better drugs or drug combination strategies are urgently needed. Here, we present an agent-based model of the interplay of C. albicans with the host immune system and with the microflora of the host. We took into account the morphological change of C. albicans from the yeast to hyphae form and its dynamics during infection. The model allowed us to follow the dynamics of fungal growth and morphology, of the immune cells and of microflora in different perturbing situations. We specifically focused on the consequences of microflora reduction following antibiotic treatment. Using the agent-based model, different drug types have been tested for their effectiveness, namely drugs that inhibit cell division and drugs that constrain the yeast-to-hyphae transition. Applied individually, the division drug turned out to successfully decrease hyphae while the transition drug leads to a burst in hyphae after the end of the treatment. To evaluate the effect of different drug combinations, doses, and schedules, we introduced a measure for the return to a healthy state, the infection score. Using this measure, we found that the addition of a transition drug to a division drug treatment can improve the treatment reliability while minimizing treatment duration and drug dosage. In this work we present a theoretical study. Although our model has not been calibrated to quantitative experimental data, the technique of computationally identifying synergistic treatment combinations in an agent based model exemplifies the importance of computational techniques in translational research.
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Context Sensitive Modeling of Cancer Drug Sensitivity.
Directory of Open Access Journals (Sweden)
Bo-Juen Chen
Full Text Available Recent screening of drug sensitivity in large panels of cancer cell lines provides a valuable resource towards developing algorithms that predict drug response. Since more samples provide increased statistical power, most approaches to prediction of drug sensitivity pool multiple cancer types together without distinction. However, pan-cancer results can be misleading due to the confounding effects of tissues or cancer subtypes. On the other hand, independent analysis for each cancer-type is hampered by small sample size. To balance this trade-off, we present CHER (Contextual Heterogeneity Enabled Regression, an algorithm that builds predictive models for drug sensitivity by selecting predictive genomic features and deciding which ones should-and should not-be shared across different cancers, tissues and drugs. CHER provides significantly more accurate models of drug sensitivity than comparable elastic-net-based models. Moreover, CHER provides better insight into the underlying biological processes by finding a sparse set of shared and type-specific genomic features.
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Modeling the modified drug release from curved shape drug delivery systems - Dome Matrix®.
Caccavo, D; Barba, A A; d'Amore, M; De Piano, R; Lamberti, G; Rossi, A; Colombo, P
2017-12-01
The controlled drug release from hydrogel-based drug delivery systems is a topic of large interest for research in pharmacology. The mathematical modeling of the behavior of these systems is a tool of emerging relevance, since the simulations can be of use in the design of novel systems, in particular for complex shaped tablets. In this work a model, previously developed, was applied to complex-shaped oral drug delivery systems based on hydrogels (Dome Matrix®). Furthermore, the model was successfully adopted in the description of drug release from partially accessible Dome Matrix® systems (systems with some surfaces coated). In these simulations, the erosion rate was used asa fitting parameter, and its dependence upon the surface area/volume ratio and upon the local fluid dynamics was discussed. The model parameters were determined by comparison with the drug release profile from a cylindrical tablet, then the model was successfully used for the prediction of the drug release from a Dome Matrix® system, for simple module configuration and for module assembled (void and piled) configurations. It was also demonstrated that, given the same initial S/V ratio, the drug release is independent upon the shape of the tablets but it is only influenced by the S/V evolution. The model reveals itself able to describe the observed phenomena, and thus it can be of use for the design of oral drug delivery systems, even if complex shaped. Copyright © 2017 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
samira yavari
2015-06-01
Full Text Available Objective: This study was an attempt to explore the structural relationship between religious activity, religious struggle, attitude to drugs, social modeling, spiritual well-being, and cigarette and tobacco smoking among students. Method: For this purpose, 504 male and female students from Kharazmi University, Agricultural Paradise, and Azad University of Karaj were selected by cluster sampling and they were asked to complete spiritual well-being scale, religious activity scale, religious struggle scale, social modeling scale, negative beliefs about drugs, and the tobacco section of the high-risk behavior questionnaire. Results: The results showed that the effect of religious activity on cigarette and tobacco smoking was mediated by negative beliefs about drugs, social modeling, spiritual well-being, and incentives for drug use. Similarly, the effect of religious struggle on cigarette and tobacco smoking was mediated by spiritual well-being. Conclusion: It seems that religion prevents people joining the unhealthy peer groups by the establishment of moral discipline, internal and external rules, and healthy coping styles therefore, people get less attracted to cigarette and tobacco smoking. Accordingly, these factors should be paid more attention in prevention programs for drug use, particularly cigarette and tobacco that are considered as the gateway to other drugs.
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Wang, Wei; Cao, Siqin; Zhu, Lizhe; Huang, Xuhui
2017-01-01
bioengineering applications and rational drug design. Constructing Markov State Models (MSMs) based on large-scale molecular dynamics simulations has emerged as a powerful approach to model functional conformational changes of the biomolecular system
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Dening, Tahnee J; Rao, Shasha; Thomas, Nicky; Prestidge, Clive A
2016-01-01
Lipid-based drug delivery systems (LBDDS) have gained significant attention in recent times, owing to their ability to overcome the challenges limiting the oral delivery of poorly water-soluble drugs. Despite the successful commercialization of several LBDDS products over the years, a large discrepancy exists between the number of poorly water-soluble drugs displaying suboptimal in vivo performances and the application of LBDDS to mitigate their various delivery challenges. Conventional LBDDS, including lipid solutions and suspensions, emulsions, and self-emulsifying formulations, suffer from various drawbacks limiting their widespread use and commercialization. Accordingly, solid-state LBDDS, fabricated by adsorbing LBDDS onto a chemically inert solid carrier material, have attracted substantial interest as a viable means of stabilizing LBDDS whilst eliminating some of the various limitations. This review describes the impact of solid carrier choice on LBDDS performance and highlights the importance of appropriate solid carrier material selection when designing hybrid solid-state LBDDS. Specifically, emphasis is placed on discussing the ability of the specific solid carrier to modulate drug release, control lipase action and lipid digestion, and enhance biopharmaceutical performance above the original liquid-state LBDDS. To encourage the interested reader to consider their solid carrier choice on a higher level, various novel materials with the potential for future use as solid carriers for LBDDS are described. This review is highly significant in guiding future research directions in the solid-state LBDDS field and fostering the translation of these delivery systems to the pharmaceutical marketplace.
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Characteristics of Suicides Caused by Drug Overdose in the State of Maryland
Directory of Open Access Journals (Sweden)
Ling Li
2015-01-01
Full Text Available Suicidal drug overdose is a major public health issue. In the United States, every year more than 33,000 people commit suicides. Our study focused on the characteristics of suicide victims in the state of Maryland. Material and methods: This study was a retrospective review of autopsy cases of all suicide deaths caused by drug (s or drug (s with alcohol intoxication investigated by the OCME in Maryland over a 7-year period from January 2004 to December 2011. All deaths investigated by the OCME that require autopsy examination are subject to comprehensive toxicology testing for drugs and alcohol. The screen tests were performed using gas chromatography (GC and radioimmunoassay techniques. All detected drugs and/or metabolites were confirmed using GC-mass spectrometry (GC-MS. Results: From 2004 to 2011, 434 deaths were certified as suicide. Of the 434 suicidal overdose deaths, 84% were white, 11% were African-American, and about 5% were either Hispanic or Asian. The male and female ratio was almost equal. Their ages ranged 15-82 years. Of the 434 suicidal drug overdose deaths, 277 victims (63.8% consumed a single drug type and 157 (36.2% consumed more than one type of drug. Of the 277 single-drug overdose cases, 71.1% suicides were due to prescription drugs, 23.5% due to over-the-counter drugs, and 5.4% due to street/recreational drugs. Among single-type prescription drugs, analgesic (N = 76, antidepressant (N = 45, and neuroleptic (N = 35 classes were the three leading type of drugs used in suicidal deaths. Oxycodone, morphine, quetiapine, and amitriptyline were the most common prescription drugs in suicidal overdose. Diphenhydramine was the leading over-the-counter drug. Of the 157 victims who consumed more than one drug, combined prescription drugs were present in 54.1%, mixed prescription and over-the-counter drugs in 29.3%, and prescription drugs/over-the-counter drugs and street drugs in 16.6% of cases. Of the multiple-drug overdose suicides
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Taepaiboon, Pattama; Rungsardthong, Uracha; Supaphol, Pitt
2006-05-01
Mats of PVA nanofibres were successfully prepared by the electrospinning process and were developed as carriers of drugs for a transdermal drug delivery system. Four types of non-steroidal anti-inflammatory drug with varying water solubility property, i.e. sodium salicylate (freely soluble in water), diclofenac sodium (sparingly soluble in water), naproxen (NAP), and indomethacin (IND) (both insoluble in water), were selected as model drugs. The morphological appearance of the drug-loaded electrospun PVA mats depended on the nature of the model drugs. The 1H-nuclear magnetic resonance results confirmed that the electrospinning process did not affect the chemical integrity of the drugs. Thermal properties of the drug-loaded electrospun PVA mats were analysed by differential scanning calorimetry and thermogravimetric analysis. The molecular weight of the model drugs played a major role on both the rate and the total amount of drugs released from the as-prepared drug-loaded electrospun PVA mats, with the rate and the total amount of the drugs released decreasing with increasing molecular weight of the drugs. Lastly, the drug-loaded electrospun PVA mats exhibited much better release characteristics of the model drugs than drug-loaded as-cast films.
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An invertebrate model for CNS drug discovery
DEFF Research Database (Denmark)
Al-Qadi, Sonia; Schiøtt, Morten; Hansen, Steen Honoré
2015-01-01
BACKGROUND: ABC efflux transporters at the blood brain barrier (BBB), namely the P-glycoprotein (P-gp), restrain the development of central nervous system (CNS) drugs. Consequently, early screening of CNS drug candidates is pivotal to identify those affected by efflux activity. Therefore, simple,...... barriers. CONCLUSION: Findings suggest a conserved mechanism of brain efflux activity between insects and vertebrates, confirming that this model holds promise for inexpensive and high-throughput screening relative to in vivo models, for CNS drug discovery....
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Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism
DEFF Research Database (Denmark)
Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik
2016-01-01
)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers......The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R...... indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site...
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Modelling drug flux through microporated skin.
Rzhevskiy, Alexey S; Guy, Richard H; Anissimov, Yuri G
2016-11-10
A simple mathematical equation has been developed to predict drug flux through microporated skin. The theoretical model is based on an approach applied previously to water evaporation through leaf stomata. Pore density, pore radius and drug molecular weight are key model parameters. The predictions of the model were compared with results derived from a simple, intuitive method using porated area alone to estimate the flux enhancement. It is shown that the new approach predicts significantly higher fluxes than the intuitive analysis, with transport being proportional to the total pore perimeter rather than area as intuitively anticipated. Predicted fluxes were in good general agreement with experimental data on drug delivery from the literature, and were quantitatively closer to the measured values than those derived from the intuitive, area-based approach. Copyright © 2016 Elsevier B.V. All rights reserved.
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Application of PK/PD Modeling in Veterinary Field: Dose Optimization and Drug Resistance Prediction
Directory of Open Access Journals (Sweden)
Ijaz Ahmad
2016-01-01
Full Text Available Among veterinary drugs, antibiotics are frequently used. The true mean of antibiotic treatment is to administer dose of drug that will have enough high possibility of attaining the preferred curative effect, with adequately low chance of concentration associated toxicity. Rising of antibacterial resistance and lack of novel antibiotic is a global crisis; therefore there is an urgent need to overcome this problem. Inappropriate antibiotic selection, group treatment, and suboptimal dosing are mostly responsible for the mentioned problem. One approach to minimizing the antibacterial resistance is to optimize the dosage regimen. PK/PD model is important realm to be used for that purpose from several years. PK/PD model describes the relationship between drug potency, microorganism exposed to drug, and the effect observed. Proper use of the most modern PK/PD modeling approaches in veterinary medicine can optimize the dosage for patient, which in turn reduce toxicity and reduce the emergence of resistance. The aim of this review is to look at the existing state and application of PK/PD in veterinary medicine based on in vitro, in vivo, healthy, and disease model.
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Koch, Gilbert; Jusko, William J; Schropp, Johannes
2017-02-01
We present competitive and uncompetitive drug-drug interaction (DDI) with target mediated drug disposition (TMDD) equations and investigate their pharmacokinetic DDI properties. For application of TMDD models, quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are necessary to reduce the number of parameters. To realize those approximations of DDI TMDD models, we derive an ordinary differential equation (ODE) representation formulated in free concentration and free receptor variables. This ODE formulation can be straightforward implemented in typical PKPD software without solving any non-linear equation system arising from the QE or QSS approximation of the rapid binding assumptions. This manuscript is the second in a series to introduce and investigate DDI TMDD models and to apply the QE or QSS approximation.
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Gibiansky, Leonid; Gibiansky, Ekaterina
2017-10-01
The paper extended the TMDD model to drugs with two identical binding sites (2-1 TMDD). The quasi-steady-state (2-1 QSS), quasi-equilibrium (2-1 QE), irreversible binding (2-1 IB), and Michaelis-Menten (2-1 MM) approximations of the model were derived. Using simulations, the 2-1 QSS approximation was compared with the full 2-1 TMDD model. As expected and similarly to the standard TMDD for monoclonal antibodies (mAb), 2-1 QSS predictions were nearly identical to 2-1 TMDD predictions, except for times of fast changes following initiation of dosing, when equilibrium has not yet been reached. To illustrate properties of new equations and approximations, several variations of population PK data for mAbs with soluble (slow elimination of the complex) or membrane-bound (fast elimination of the complex) targets were simulated from a full 2-1 TMDD model and fitted to 2-1 TMDD models, to its approximations, and to the standard (1-1) QSS model. For a mAb with a soluble target, it was demonstrated that the 2-1 QSS model provided nearly identical description of the observed (simulated) free drug and total target concentrations, although there was some minor bias in predictions of unobserved free target concentrations. The standard QSS approximation also provided a good description of the observed data, but was not able to distinguish between free drug concentrations (with no target attached and both binding site free) and partially bound drug concentrations (with one of the binding sites occupied by the target). For a mAb with a membrane-bound target, the 2-1 MM approximation adequately described the data. The 2-1 QSS approximation converged 10 times faster than the full 2-1 TMDD, and its run time was comparable with the standard QSS model.
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Mathematical modeling for novel cancer drug discovery and development.
Zhang, Ping; Brusic, Vladimir
2014-10-01
Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.
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Rhodamine/Nanodiamond as a System Model for Drug Carrier.
Reina, G; Orlanducci, S; Cairone, C; Tamburri, E; Lenti, S; Cianchetta, I; Rossi, M; Terranova, M L
2015-02-01
In this paper we present some strategies that are being developed in our labs towards enabling nanodiamond-based applications for drug delivery. Rhodamine B (RhB) has been choosen as model molecule to study the loading of nanodiamonds with active moieties and the conditions for their controlled release. In order to test the chemical/physical interactions between functionalized detonation nanodiamond (DND) and complex molecules, we prepared and tested different RhB@DND systems, with RhB adsorbed or linked by ionic bonding to the DND surface. The chemical state of the DND surfaces before conjugation with the RhB molecules, and the chemical features of the DND-RhB interactions have been deeply analysed by coupling DND with Au nanoparticles and taking advantage of surface enhanced Raman spectroscopy SERS. The effects due to temperature and pH variations on the process of RhB release from the DND carrier have been also investigated. The amounts of released molecules are consistent with those required for effective drug action in conventional therapeutic applications, and this makes the DND promising nanostructured cargos for drug delivery applications.
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Drug use and AIDS: estimating injection prevalence in a rural state.
Leukefeld, Carl G; Logan, T K; Farabee, David; Clayton, Richard
2002-01-01
This paper presents approaches used in one rural U.S. state to describe the level of injecting drug use and to estimate the number of injectors not receiving drug-user treatment. The focus is on two broad areas of estimation that were used to present the prevalence of injecting drug use in Kentucky. The first estimation approach uses available data from secondary data sources. The second approach involves three small community studies.
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Zebrafish models in neuropsychopharmacology and CNS drug discovery.
Khan, Kanza M; Collier, Adam D; Meshalkina, Darya A; Kysil, Elana V; Khatsko, Sergey L; Kolesnikova, Tatyana; Morzherin, Yury Yu; Warnick, Jason E; Kalueff, Allan V; Echevarria, David J
2017-07-01
Despite the high prevalence of neuropsychiatric disorders, their aetiology and molecular mechanisms remain poorly understood. The zebrafish (Danio rerio) is increasingly utilized as a powerful animal model in neuropharmacology research and in vivo drug screening. Collectively, this makes zebrafish a useful tool for drug discovery and the identification of disordered molecular pathways. Here, we discuss zebrafish models of selected human neuropsychiatric disorders and drug-induced phenotypes. As well as covering a broad range of brain disorders (from anxiety and psychoses to neurodegeneration), we also summarize recent developments in zebrafish genetics and small molecule screening, which markedly enhance the disease modelling and the discovery of novel drug targets. © 2017 The British Pharmacological Society.
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Ochalek, M; Podhaisky, H; Ruettinger, H-H; Wohlrab, J; Neubert, R H H
2012-10-01
The barrier function of two quaternary stratum corneum (SC) lipid model membranes, which were previously characterized with regard to the lipid organization, was investigated based on diffusion studies of model drugs with varying lipophilicities. Diffusion experiments of a hydrophilic drug, urea, and more lipophilic drugs than urea (i.e. caffeine, diclofenac sodium) were conducted using Franz-type diffusion cells. The amount of permeated drug was analyzed using either HPLC or CE technique. The subjects of interest in the present study were the investigation of the influence of physicochemical properties of model drugs on their diffusion and permeation through SC lipid model membranes, as well as the study of the impact of the constituents of these artificial systems (particularly ceramide species) on their barrier properties. The diffusion through both SC lipid model membranes and the human SC of the most hydrophilic model drug, urea, was faster than the permeation of the more lipophilic drugs. The slowest rate of permeation through SC lipid systems occurred in the case of caffeine. The composition of SC lipid model membranes has a significant impact on their barrier function. Model drugs diffused and permeated faster through Membrane II (presence of Cer [EOS]). In terms of the barrier properties, Membrane II is much more similar to the human SC than Membrane I. Copyright © 2012 Elsevier B.V. All rights reserved.
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Prada, Sergio I
2017-12-01
The Medicaid Drug Utilization Review (DUR) program is a 2-phase process conducted by Medicaid state agencies. The first phase is a prospective DUR and involves electronically monitoring prescription drug claims to identify prescription-related problems, such as therapeutic duplication, contraindications, incorrect dosage, or duration of treatment. The second phase is a retrospective DUR and involves ongoing and periodic examinations of claims data to identify patterns of fraud, abuse, underutilization, drug-drug interaction, or medically unnecessary care, implementing corrective actions when needed. The Centers for Medicare & Medicaid Services requires each state to measure prescription drug cost-savings generated from its DUR programs on an annual basis, but it provides no guidance or unified methodology for doing so. To describe and synthesize the methodologies used by states to measure cost-savings using their Medicaid retrospective DUR program in federal fiscal years 2014 and 2015. For each state, the cost-savings methodologies included in the Medicaid DUR 2014 and 2015 reports were downloaded from Medicaid's website. The reports were then reviewed and synthesized. Methods described by the states were classified according to research designs often described in evaluation textbooks. In 2014, the most often used prescription drugs cost-savings estimation methodology for the Medicaid retrospective DUR program was a simple pre-post intervention method, without a comparison group (ie, 12 states). In 2015, the most common methodology used was a pre-post intervention method, with a comparison group (ie, 14 states). Comparisons of savings attributed to the program among states are still unreliable, because of a lack of a common methodology available for measuring cost-savings. There is great variation among states in the methods used to measure prescription drug utilization cost-savings. This analysis suggests that there is still room for improvement in terms of
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A theory of drug tolerance and dependence II: the mathematical model.
Peper, Abraham
2004-08-21
The preceding paper presented a model of drug tolerance and dependence. The model assumes the development of tolerance to a repeatedly administered drug to be the result of a regulated adaptive process. The oral detection and analysis of exogenous substances is proposed to be the primary stimulus for the mechanism of drug tolerance. Anticipation and environmental cues are in the model considered secondary stimuli, becoming primary in dependence and addiction or when the drug administration bypasses the natural-oral-route, as is the case when drugs are administered intravenously. The model considers adaptation to the effect of a drug and adaptation to the interval between drug taking autonomous tolerance processes. Simulations with the mathematical model demonstrate the model's behaviour to be consistent with important characteristics of the development of tolerance to repeatedly administered drugs: the gradual decrease in drug effect when tolerance develops, the high sensitivity to small changes in drug dose, the rebound phenomenon and the large reactions following withdrawal in dependence. The present paper discusses the mathematical model in terms of its design. The model is a nonlinear, learning feedback system, fully satisfying control theoretical principles. It accepts any form of the stimulus-the drug intake-and describes how the physiological processes involved affect the distribution of the drug through the body and the stability of the regulation loop. The mathematical model verifies the proposed theory and provides a basis for the implementation of mathematical models of specific physiological processes.
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The Impact of an Indiana (United States Drug Court on Criminal Recidivism
Directory of Open Access Journals (Sweden)
John R. Gallagher
2014-07-01
Full Text Available This study evaluated a drug court located in a metropolitan area of Indiana (United States, focusing specifically on identifying variables that predicted recidivism among drug court participants and comparing criminal recidivism patterns among drug court and probation participants. Drug court participants were most likely to recidivate if they were younger, had a violation within the first 30 days of the program, had a previous criminal record, and were terminated unsuccessfully from the program. Furthermore, drug court participants were less likely to recidivate than probationers who had similar offense and demographic characteristics. Implications for drug court practice, policy advocacy, and future research are discussed.
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New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.
Peletier, Lambertus A; Gabrielsson, Johan
2018-05-14
In vivo analyses of pharmacological data are traditionally based on a closed system approach not incorporating turnover of target and ligand-target kinetics, but mainly focussing on ligand-target binding properties. This study incorporates information about target and ligand-target kinetics parallel to binding. In a previous paper, steady-state relationships between target- and ligand-target complex versus ligand exposure were derived and a new expression of in vivo potency was derived for a circulating target. This communication is extending the equilibrium relationships and in vivo potency expression for (i) two separate targets competing for one ligand, (ii) two different ligands competing for a single target and (iii) a single ligand-target interaction located in tissue. The derived expressions of the in vivo potencies will be useful both in drug-related discovery projects and mechanistic studies. The equilibrium states of two targets and one ligand may have implications in safety assessment, whilst the equilibrium states of two competing ligands for one target may cast light on when pharmacodynamic drug-drug interactions are important. The proposed equilibrium expressions for a peripherally located target may also be useful for small molecule interactions with extravascularly located targets. Including target turnover, ligand-target complex kinetics and binding properties in expressions of potency and efficacy will improve our understanding of within and between-individual (and across species) variability. The new expressions of potencies highlight the fact that the level of drug-induced target suppression is very much governed by target turnover properties rather than by the target expression level as such.
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Singh, Prabal Vikram; Tatambhotla, Anand; Kalvakuntla, Rohini; Chokshi, Maulik
2013-01-01
To perform an initial qualitative comparison of the different procurement models in India to frame questions for future research in this area; to capture the finer differences between the state models through 53 process and price parameters to determine their functional efficiencies. Qualitative analysis is performed for the study. Five states: Tamil Nadu, Kerala, Odisha, Punjab and Maharashtra were chosen to ensure heterogeneity in a number of factors such as procurement type (centralised, decentralised or mixed); autonomy of the procurement organisation; state of public health infrastructure; geography and availability of data through Right to Information Act (RTI). Data on procurement processes were collected through key informant analysis by way of semistructured interviews with leadership teams of procuring organisations. These process data were validated through interviews with field staff (stakeholders of district hospitals, taluk hospitals, community health centres and primary health centres) in each state. A total of 30 actors were interviewed in all five states. The data collected are analysed against 52 process and price parameters to determine the functional efficiency of the model. The analysis indicated that autonomous procurement organisations were more efficient in relation to payments to suppliers, had relatively lower drug procurement prices and managed their inventory more scientifically. The authors highlight critical success factors that significantly influence the outcome of any procurement model. In a way, this study raises more questions and seeks the need for further research in this arena to aid policy makers.
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Optimization of Drug Delivery by Drug-Eluting Stents.
Directory of Open Access Journals (Sweden)
Franz Bozsak
Full Text Available Drug-eluting stents (DES, which release anti-proliferative drugs into the arterial wall in a controlled manner, have drastically reduced the rate of in-stent restenosis and revolutionized the treatment of atherosclerosis. However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation. We present a framework to optimize DES design such that restenosis is inhibited without affecting the endothelial healing process. To this end, we have developed a computational model of fluid flow and drug transport in stented arteries and have used this model to establish a metric for quantifying DES performance. The model takes into account the multi-layered structure of the arterial wall and incorporates a reversible binding model to describe drug interaction with the cells of the arterial wall. The model is coupled to a novel optimization algorithm that allows identification of optimal DES designs. We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance. Paclitaxel-eluting stents perform optimally by releasing their drug either very rapidly (within a few hours or very slowly (over periods of several months up to one year at concentrations considerably lower than current DES. In contrast, sirolimus-eluting stents perform optimally only when drug release is slow. The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.
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Fed-state gastric media and drug analysis techniques: Current status and points to consider.
Baxevanis, Fotios; Kuiper, Jesse; Fotaki, Nikoletta
2016-10-01
Gastric fed state conditions can have a significant effect on drug dissolution and absorption. In vitro dissolution tests with simple aqueous media cannot usually predict drugs' in vivo response, as several factors such as the meal content, the gastric emptying and possible interactions between food and drug formulations can affect drug's pharmacokinetics. Good understanding of the effect of the in vivo fed gastric conditions on the drug is essential for the development of biorelevant dissolution media simulating the gastric environment after the administration of the standard high fat meal proposed by the FDA and the EMA in bioavailability/bioequivalence (BA/BE) studies. The analysis of drugs in fed state media can be quite challenging as most analytical protocols currently employed are time consuming and labour intensive. In this review, an overview of the in vivo gastric conditions and the biorelevant media used for their in vitro simulation are described. Furthermore an analysis of the physicochemical properties of the drugs and the formulations related to food effect is given. In terms of drug analysis, the protocols currently used for the fed state media sample treatment and analysis and the analytical challenges and needs emerging for more efficient and time saving techniques for a broad spectrum of compounds are being discussed. Copyright © 2016 Elsevier B.V. All rights reserved.
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Racism in United States: Drug Legislation and the Trade-Off Behind It
Heiligman, Avron C.
1978-01-01
This paper attempts to show that drug legislation in the United States has been the result of racial discrimination as rationalized by labeling specific target populations deviant. The author suggests that organized medicine can also be linked to the controlling measures of drug legislation. (Author)
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Wang, Daniel Wei L; Ferraz, Octavio Luiz Motta
2012-01-01
This paper discusses the post-trial access to drugs for patients who participated in clinical trials in Brazil. The ethical guidance for clinical trials in Brazil is arguably one of the clearest in the world in attributing to research sponsors the responsibility for providing post-trial drugs to patients who participated in their experiments. The Federal Constitution recognizes health as a fundamental right to be fulfilled by the State. Based on the Brazilian constitution and on the National Health Council resolutions, courts have been accepting patients' claims and ordering the State and the pharmaceutical companies to provide these patients with the tested treatment in the quantity and duration they need it. This generous interpretation of the duties of the pharmaceutical companies and the State makes the Brazilian model for post-trial access unique when compared to the experience of other countries and thus should be followed with attention by future research in order to assess its consequences for patients, research sponsors, and the public health system. © 2012 American Society of Law, Medicine & Ethics, Inc.
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Cyclodextrins as drug carriers in Pharmaceutical Technology: The state of the art.
Conceição, Jaime; Adeoye, Oluwatomide; Cabral-Marques, Helena Maria; Lobo, Jose Manuel Sousa
2017-12-18
Cyclodextrins (CDs) are versatile excipients with an essential role in drug delivery, as they can form non-covalently bonded inclusion complexes (host-guest complexes) with several drugs either in solution or in the solid state. The main purpose of this publication was to carry out a state of the art of CDs as complexing agents in drug carrier systems. In this way, the history, properties and pharmaceutical applications of the CDs were highlighted with typical examples. The methods to enhance the complexation efficiency (CE) and the CDs applications in solid dosage forms were emphasized in more detail. The main advantages of using these cyclic oligosaccharides are as follows: (1) to enhance solubility/dissolution/ bioavailability of poorly soluble drugs; (2) to enhance drug stability; (3) to modify the drug release site and/or time profile; and (4) to reduce drug side effects (for example, gastric or ocular irritation). These compounds present favorable toxicological profile for human use and therefore there are various medicines containing CDs approved by regulatory authorities worldwide. On the other hand, the major drawback of CDs is the increase in formulation bulk, once the CE is, in general, very low. This aspect is particularly relevant in solid dosage forms and limits the use of CDs to potent drugs. CDs have great potential as drug carriers in Pharmaceutical Technology and can be used by the formulator in order to improve the drug properties such as solubility, bioavailability and stability. Additionally, recent studies have shown that these compounds can be applied as active pharmaceutical ingredients. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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[A model list of high risk drugs].
Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L
2013-12-01
«High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.
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Animal models of pancreatic cancer for drug research.
Kapischke, Matthias; Pries, Alexandra
2008-10-01
The operative and conservative results of therapy in pancreatic ductal adenocarcinoma remain appallingly poor. This underlines the demand for further research for effective anticancer drugs. The various animal models remain the essential method for the determination of efficacy of substances during preclinical phase. Unfortunately, most of these tested substances showed a good efficacy in pancreatic carcinoma in the animal model but were not confirmed during the clinical phase. The available literature in PubMed, Medline, Ovid and secondary literature was searched regarding the available animal models for drug testing against pancreatic cancer. The models were analyzed regarding their pros and cons in anticancer drug testing. The different modifications of the orthotopic model (especially in mice) seem at present to be the best model for anticancer testing in pancreatic carcinoma. The value of genetically engineered animal model (GEM) and syngeneic models is on debate. A good selection of the model concerning the questions supposed to be clarified may improve the comparability of the results of animal experiments compared to clinical trials.
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Low temperature fused deposition modeling (FDM) 3D printing of thermolabile drugs.
Kollamaram, Gayathri; Croker, Denise M; Walker, Gavin M; Goyanes, Alvaro; Basit, Abdul W; Gaisford, Simon
2018-07-10
Fused deposition modelling (FDM) is the most commonly investigated 3D printing technology for the manufacture of personalized medicines, however, the high temperatures used in the process limit its wider application. The objective of this study was to print low-melting and thermolabile drugs by reducing the FDM printing temperature. Two immediate release polymers, Kollidon VA64 and Kollidon 12PF were investigated as potential candidates for low-temperature FDM printing. Ramipril was used as the model low melting temperature drug (109 °C); to the authors' knowledge this is the lowest melting point drug investigated to date by FDM printing. Filaments loaded with 3% drug were obtained by hot melt extrusion at 70 °C and ramipril printlets with a dose equivalent of 8.8 mg were printed at 90 °C. HPLC analysis confirmed that the drug was stable with no signs of degradation and dissolution studies revealed that drug release from the printlets reached 100% within 20-30 min. Variable temperature Raman and solid state nuclear magnetic resonance (SSNMR) spectroscopy techniques were used to evaluate drug stability over the processing temperature range. These data indicated that ramipril did not undergo degradation below its melting point (which is above the processing temperature range: 70-90 °C) but it was transformed into the impurity diketopiperazine upon exposure to temperatures higher than its melting point. The use of the excipients Kollidon VA64 and Kollidon 12PF in FDM was further validated by printing with the drug 4-aminosalicylic acid (4-ASA), which in previous work was reported to undergo degradation in FDM printing, but here it was found to be stable. This work demonstrates that the selection and use of new excipients can overcome one of the major disadvantages in FDM printing, drug degradation due to thermal heating, making this technology suitable for drugs with lower melting temperatures. Copyright © 2018 Elsevier B.V. All rights reserved.
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Shen, Lin; Rabi, S. Alireza; Sedaghat, Ahmad R.; Shan, Liang; Lai, Jun; Xing, Sifei; Siliciano, Robert F.
2012-01-01
Control of HIV-1 replication was first achieved with regimens that included a nonnucleoside reverse transcriptase inhibitor (NNRTI) or a protease inhibitor (PI); however, an explanation for the high antiviral activity of these drugs has been lacking. Indeed, conventional pharmacodynamic measures like IC50 (drug concentration causing 50% inhibition) do not differentiate NNRTIs and PIs from less active nucleoside reverse transcriptase inhibitors (NRTIs). Drug inhibitory potential depends on the slope of the dose-response curve (m), which represents how inhibition increases as a function of increasing drug concentration and is related to the Hill coefficient, a measure of intramolecular cooperativity in ligand binding to a multivalent receptor. Although NNRTIs and PIs bind univalent targets, they unexpectedly exhibit cooperative dose-response curves (m > 1). We show that this cooperative inhibition can be explained by a model in which infectivity requires participation of multiple copies of a drug target in an individual life cycle stage. A critical subset of these target molecules must be in the unbound state. Consistent with experimental observations, this model predicts m > 1 for NNRTIs and PIs and m = 1 in situations where a single drug target/virus mediates a step in the life cycle, as is the case with NRTIs and integrase strand transfer inhibitors. This model was tested experimentally by modulating the number of functional drug targets per virus, and dose-response curves for modulated virus populations fit model predictions. This model explains the high antiviral activity of two drug classes important for successful HIV-1 treatment and defines a characteristic of good targets for antiviral drugs in general, namely, intermolecular cooperativity. PMID:21753122
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Munshi, Kiraat D; Mager, Douglas; Ward, Krista M; Mischel, Brian; Henderson, Rochelle R
2018-02-01
Formulary or preferred drug list (PDL) management is an effective strategy to ensure clinically efficient prescription drug management by managed care organizations (MCOs). Medicaid MCOs participating in Florida's Medicaid program were required to use a state-mandated PDL between May and August 2014. To examine differences in prescription drug use and plan costs between a single Florida Medicaid managed care (MMC) health plan that implemented a state-mandated PDL policy on July 1, 2014, and a comparable MMC health plan in another state without a state-mandated PDL, controlling for sociodemographic confounders. A retrospective analysis with a pre-post design was conducted using deidentified administrative claims data from a large pharmacy benefit manager. The prepolicy evaluation period was January 1 through June 30, 2014, and the postpolicy period was January 1 through June 30, 2015. Continuously eligible Florida MMC plan members were matched on sociodemographic and health characteristics to their counterparts enrolled in a comparable MMC health plan in another state without a state-mandated formulary. Outcomes were drug use, measured as the number of 30-day adjusted nonspecialty drug prescriptions per member per period, and total drug plan costs per member per period for all drugs, with separate measures for generic and brand drugs. Bivariate comparisons were conducted using t-tests. Employing a difference-in-differences (DID) analytic approach, multivariate negative binomial regression and generalized estimating equation models were used to analyze prescription drug use and costs. The final analytical sample consisted of 18,372 enrollees, evenly divided between the 2 groups. In the postpolicy evaluation period, overall and generic use declined, while brand use increased for members in the Florida health plan. Drug costs, especially for brands, significantly increased for Florida health plan members. No significant changes were observed over the same time period
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Mathematical modeling of efficacy and safety for anticancer drugs clinical development.
Lavezzi, Silvia Maria; Borella, Elisa; Carrara, Letizia; De Nicolao, Giuseppe; Magni, Paolo; Poggesi, Italo
2018-01-01
Drug attrition in oncology clinical development is higher than in other therapeutic areas. In this context, pharmacometric modeling represents a useful tool to explore drug efficacy in earlier phases of clinical development, anticipating overall survival using quantitative model-based metrics. Furthermore, modeling approaches can be used to characterize earlier the safety and tolerability profile of drug candidates, and, thus, the risk-benefit ratio and the therapeutic index, supporting the design of optimal treatment regimens and accelerating the whole process of clinical drug development. Areas covered: Herein, the most relevant mathematical models used in clinical anticancer drug development during the last decade are described. Less recent models were considered in the review if they represent a standard for the analysis of certain types of efficacy or safety measures. Expert opinion: Several mathematical models have been proposed to predict overall survival from earlier endpoints and validate their surrogacy in demonstrating drug efficacy in place of overall survival. An increasing number of mathematical models have also been developed to describe the safety findings. Modeling has been extensively used in anticancer drug development to individualize dosing strategies based on patient characteristics, and design optimal dosing regimens balancing efficacy and safety.
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Bardhan, Munmun; Majumdar, Anupa; Jana, Sayantan; Ghosh, Tapas; Pal, Uttam; Swarnakar, Snehasikta; Senapati, Dulal
2018-01-01
Formulated mesoporous silica nanoparticle (MSN) systems offer the best possible drug delivery system through the release of drug molecules from the accessible pores. In the present investigation, steady state and time resolved fluorescence techniques along with the fluorescence imaging were applied to investigate the interactions of dye loaded MSN with fluorescent unilamellar vesicles and live cells. Here 1,2-dimyristoyl-sn-glycero-3-phospocholine (DMPC) was used to prepare Small Unilamellar Vesicles (SUVs) as the model membrane with fluorescent 1,6-diphenyl-1,3,5-hexatriene (DPH) molecule incorporated inside the lipid bilayer. The interaction of DPH incorporated DMPC membrane with Fluorescein loaded MSN lead to the release of Fluorescein (Fl) dye from the interior pores of MSN systems. The extent of release of Fl and spatial distribution of the DPH molecule has been explored by monitoring steady-state fluorescence intensity and fluorescence lifetime at physiological condition. To investigate the fate of drug molecule released from MSN, fluorescence anisotropy has been used. The drug delivery efficiency of the MSN as a carrier for doxorubicin (DOX), a fluorescent chemotherapeutic drug, has also been investigated at physiological conditions. The study gives a definite confirmation for high uptake and steady release of DOX in primary oral mucosal non-keratinized squamous cells in comparison to naked DOX treatment. Copyright © 2017 Elsevier B.V. All rights reserved.
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Drug use trajectory patterns among older drug users
Directory of Open Access Journals (Sweden)
Tyndall B
2011-05-01
Full Text Available Miriam Boeri, Thor Whalen, Benjamin Tyndall, Ellen BallardKennesaw State University, Department of Sociology and Criminal Justice, Kennesaw GA, USAAbstract: To better understand patterns of drug use trajectories over time, it is essential to have standard measures of change. Our goal here is to introduce measures we developed to quantify change in drug use behaviors. A secondary goal is to provide effective visualizations of these trajectories for applied use. We analyzed data from a sample of 92 older drug users (ages 45 to 65 to identify transition patterns in drug use trajectories across the life course. Data were collected for every year since birth using a mixed methods design. The community-drawn sample of active and former users were 40% female, 50% African American, and 60% reporting some college or greater. Their life histories provided retrospective longitudinal data on the diversity of paths taken throughout the life course and changes in drug use patterns that occurred over time. Bayesian analysis was used to model drug trajectories displayed by innovative computer graphics. The mathematical techniques and visualizations presented here provide the foundation for future models using Bayesian analysis. In this paper we introduce the concepts of transition counts, transition rates and relapse/remission rates, and we describe how these measures can help us better understand drug use trajectories. Depicted through these visual tools, measurements of discontinuous patterns provide a succinct view of individual drug use trajectories. The measures we use on drug use data will be further developed to incorporate contextual influences on the drug trajectory and build predictive models that inform rehabilitation efforts for drug users. Although the measures developed here were conceived to better examine drug use trajectories, the applications of these measures can be used with other longitudinal datasets.Keywords: drug use, trajectory patterns
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Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations
Hethey, Christoph Philipp
2017-01-01
Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. In...
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Poulin, Patrick
2015-07-01
A basic assumption in pharmacokinetics-pharmacodynamics research is that the free drug concentration is similar in plasma and tissue, and, hence, in vitro plasma data can be used to estimate the in vivo condition in tissue. However, in a companion manuscript, it has been demonstrated that this assumption is violated for the ionized drugs. Nonetheless, these observations focus on in vitro static environments and do not challenge data with an in vivo dynamic system. Therefore, an extension from an in vitro to an in vivo system becomes the necessary next step. The objective of this study was to perform theoretical simulations of the free drug concentration in tissue and plasma by using a physiologically based pharmacokinetics (PBPK) model reproducing the in vivo conditions in human. Therefore, the effects of drug ionization, lipophilicity, and clearance have been taken into account in a dynamic system. This modeling exercise was performed as a proof of concept to demonstrate that free drug concentration in tissue and plasma may also differ in a dynamic system for passively permeable drugs that are ionized at the physiological pH. The PBPK model simulations indicated that free drug concentrations in tissue cells and plasma significantly differ for the ionized drugs because of the pH gradient effect between cells and interstitial space. Hence, a rule of thumb for potentially performing more accurate PBPK/PD modeling is suggested, which states that the free drug concentration in tissue and plasma will differ for the ionizable drugs in contrast to the neutral drugs. In addition to the pH gradient effect for the ionizable drugs, lipophilicity and clearance effects will increase or decrease the free drug concentration in tissue and plasma for each class of drugs; thus, higher will be the drug lipophilicity and clearance, lower would be the free drug concentration in plasma, and, hence, in tissue, in a dynamic in vivo system. Therefore, only considering the value of free
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Prediction of adverse drug reactions using decision tree modeling.
Hammann, F; Gutmann, H; Vogt, N; Helma, C; Drewe, J
2010-07-01
Drug safety is of great importance to public health. The detrimental effects of drugs not only limit their application but also cause suffering in individual patients and evoke distrust of pharmacotherapy. For the purpose of identifying drugs that could be suspected of causing adverse reactions, we present a structure-activity relationship analysis of adverse drug reactions (ADRs) in the central nervous system (CNS), liver, and kidney, and also of allergic reactions, for a broad variety of drugs (n = 507) from the Swiss drug registry. Using decision tree induction, a machine learning method, we determined the chemical, physical, and structural properties of compounds that predispose them to causing ADRs. The models had high predictive accuracies (78.9-90.2%) for allergic, renal, CNS, and hepatic ADRs. We show the feasibility of predicting complex end-organ effects using simple models that involve no expensive computations and that can be used (i) in the selection of the compound during the drug discovery stage, (ii) to understand how drugs interact with the target organ systems, and (iii) for generating alerts in postmarketing drug surveillance and pharmacovigilance.
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Srinivas, Nuggehally R
2016-01-20
Digoxin, a narrow therapeutic index drug, is widely used in congestive heart failure. However, the digitalization therapy involves dose titration and can exhibit drug-drug interaction. Ctrough versus area under the plasma concentration versus time curve in a dosing interval of 24 hours (AUC0-24h) and Cmax versus AUC0-24h for digoxin were established by linear regression. The predictions of digoxin AUC0-24h values were performed using published Ctrough or Cmax with appropriate regression lines. The fold difference, defined as the quotient of the observed/predicted AUC0-24h values, was evaluated. The mean square error and root mean square error, correlation coefficient (r), and goodness of the fold prediction were used to evaluate the models. Both Ctrough versus AUC0-24h (r = 0.9215) and Cmax versus AUC0-24h models for digoxin (r = 0.7781) showed strong correlations. Approximately 93.8% of the predicted digoxin AUC0-24h values were within 0.76-fold to 1.25-fold difference for Ctrough model. In sharp contrast, the Cmax model showed larger variability with only 51.6% of AUC0-24h predictions within 0.76-1.25-fold difference. The r value for observed versus predicted AUC0-24h for Ctrough (r = 0.9551; n = 177; P < 0.001) was superior to the Cmax (r = 0.6134; n = 275; P < 0.001) model. The mean square error and root mean square error (%) for the Ctrough model were 11.95% and 16.2% as compared to 67.17% and 42.3% obtained for the Cmax model. Simple linear regression models for Ctrough/Cmax versus AUC0-24h were derived for digoxin. On the basis of statistical evaluation, Ctrough was superior to Cmax model for the prediction of digoxin AUC0-24h and can be potentially used in a prospective setting for predicting drug-drug interaction or lack of it.
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Cherkaoui-Rbati, Mohammed H; Paine, Stuart W; Littlewood, Peter; Rauch, Cyril
2017-01-01
All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.
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Directory of Open Access Journals (Sweden)
Mohammed H Cherkaoui-Rbati
Full Text Available All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs of new chemical entities (NCEs and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit, located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level. A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.
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Animal Migraine Models for Drug Development
DEFF Research Database (Denmark)
Jansen-Olesen, Inger; Tfelt-Hansen, Peer; Olesen, Jes
2013-01-01
Migraine is number seven in WHO's list of all diseases causing disability and the third most costly neurological disorder in Europe. Acute attacks are treatable by highly selective drugs such as the triptans but there is still a huge unmet therapeutic need. Unfortunately, drug development...... for headache has almost come to a standstill partly because of a lack of valid animal models. Here we review previous models with emphasis on optimal characteristics of a future model. In addition to selection of animal species, the method of induction of migraine-like changes and the method of recording...... responses elicited by such measures are crucial. The most naturalistic way of inducing attacks is by infusion of endogenous signaling molecules that are known to cause migraine in patients. The most valid response is recording of neural activity in the trigeminal system. The most useful headache related...
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Addressing drug adherence using an operations management model.
Nunlee, Martin; Bones, Michelle
2014-01-01
OBJECTIVE To provide a model that enables health systems and pharmacy benefit managers to provide medications reliably and test for reliability and validity in the analysis of adherence to drug therapy of chronic disease. SUMMARY The quantifiable model described here can be used in conjunction with behavioral designs of drug adherence assessments. The model identifies variables that can be reproduced and expanded across the management of chronic diseases with drug therapy. By creating a reorder point system for reordering medications, the model uses a methodology commonly seen in operations research. The design includes a safety stock of medication and current supply of medication, which increases the likelihood that patients will have a continuous supply of medications, thereby positively affecting adherence by removing barriers. CONCLUSION This method identifies an adherence model that quantifies variables related to recommendations from health care providers; it can assist health care and service delivery systems in making decisions that influence adherence based on the expected order cycle days and the expected daily quantity of medication administered. This model addresses the possession of medication as a barrier to adherence.
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Stoltman, Jonathan J K; Woodcock, Eric A; Lister, Jamey J; Lundahl, Leslie H; Greenwald, Mark K
2015-12-01
Delay discounting (DD) refers to how rapidly an individual devalues goods based on delays to receipt. DD usually is considered a trait variable but can be state dependent, yet few studies have assessed commodity valuation at short, naturalistically relevant time intervals that might enable state-dependent analysis. This study aimed to determine whether drug-use impulsivity and intelligence influence heroin DD at short (ecologically relevant) delays during two pharmacological states (heroin satiation and withdrawal). Out-of-treatment, intensive heroin users (n = 170; 53.5% African American; 66.7% male) provided complete DD data during imagined heroin satiation and withdrawal. Delays were 3, 6, 12, 24, 48, 72, and 96 hours; maximum delayed heroin amount was thirty $10 bags. Indifference points were used to calculate area under the curve (AUC). We also assessed drug-use impulsivity (subscales from the Impulsive Relapse Questionnaire [IRQ]) and estimated intelligence (Shipley IQ) as predictors of DD. Heroin discounting was greater (smaller AUC) during withdrawal than satiation. In regression analyses, lower intelligence and IRQ Capacity for Delay as well as higher IRQ Speed (to return to drug use) predicted greater heroin discounting in the satiation condition. Lower intelligence and higher IRQ Speed predicted greater discounting in the withdrawal condition. Sex, race, substance use variables, and other IRQ subscales were not significantly related to the withdrawal or satiation DD behavior. In summary, heroin discounting was temporally rapid, pharmacologically state dependent, and predicted by drug-use impulsivity and estimated intelligence. These findings highlight a novel and sensitive measure of acute DD that is easy to administer. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
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Experimental psychiatric illness and drug abuse models: from human to animal, an overview.
Edwards, Scott; Koob, George F
2012-01-01
Preclinical animal models have supported much of the recent rapid expansion of neuroscience research and have facilitated critical discoveries that undoubtedly benefit patients suffering from psychiatric disorders. This overview serves as an introduction for the following chapters describing both in vivo and in vitro preclinical models of psychiatric disease components and briefly describes models related to drug dependence and affective disorders. Although there are no perfect animal models of any psychiatric disorder, models do exist for many elements of each disease state or stage. In many cases, the development of certain models is essentially restricted to the human clinical laboratory domain for the purpose of maximizing validity, whereas the use of in vitro models may best represent an adjunctive, well-controlled means to model specific signaling mechanisms associated with psychiatric disease states. The data generated by preclinical models are only as valid as the model itself, and the development and refinement of animal models for human psychiatric disorders continues to be an important challenge. Collaborative relationships between basic neuroscience and clinical modeling could greatly benefit the development of new and better models, in addition to facilitating medications development.
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Directory of Open Access Journals (Sweden)
Valentina Galbiati
2016-07-01
Full Text Available Hypersensitivity drug reactions (HDRs are the adverse effect of pharmaceuticals that clinically resemble allergy. HDRs account for approximately 1/6 of drug-induced adverse effects, and include immune-mediated ('allergic' and non immune-mediated ('pseudo allergic' reactions. In recent years, the severe and unpredicted drug adverse events clearly indicate that the immune system can be a critical target of drugs. Enhanced prediction in preclinical safety evaluation is, therefore, crucial. Nowadays, there are no validated in vitro or in vivo methods to screen the sensitizing potential of drugs in the pre-clinical phase. The problem of non-predictability of immunologically-based hypersensitivity reactions is related to the lack of appropriate experimental models rather than to the lack of -understanding of the adverse phenomenon.We recently established experimental conditions and markers to correctly identify drug associated with in vivo hypersensitivity reactions using THP-1 cells and IL-8 production, CD86 and CD54 expression. The proposed in vitro method benefits from a rationalistic approach with the idea that allergenic drugs share with chemical allergens common mechanisms of cell activation. This assay can be easily incorporated into drug development for hazard identification of drugs, which may have the potential to cause in vivo hypersensitivity reactions. The purpose of this review is to assess the state of the art of in vitro models to assess the allergenic potential of drugs based on the activation of dendritic cells.
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Wang, Li; Zhang, Yaoyun; Jiang, Min; Wang, Jingqi; Dong, Jiancheng; Liu, Yun; Tao, Cui; Jiang, Guoqian; Zhou, Yi; Xu, Hua
2018-04-04
In recent years, electronic health record systems have been widely implemented in China, making clinical data available electronically. However, little effort has been devoted to making drug information exchangeable among these systems. This study aimed to build a Normalized Chinese Clinical Drug (NCCD) knowledge base, by applying and extending the information model of RxNorm to Chinese clinical drugs. Chinese drugs were collected from 4 major resources-China Food and Drug Administration, China Health Insurance Systems, Hospital Pharmacy Systems, and China Pharmacopoeia-for integration and normalization in NCCD. Chemical drugs were normalized using the information model in RxNorm without much change. Chinese patent drugs (i.e., Chinese herbal extracts), however, were represented using an expanded RxNorm model to incorporate the unique characteristics of these drugs. A hybrid approach combining automated natural language processing technologies and manual review by domain experts was then applied to drug attribute extraction, normalization, and further generation of drug names at different specification levels. Lastly, we reported the statistics of NCCD, as well as the evaluation results using several sets of randomly selected Chinese drugs. The current version of NCCD contains 16 976 chemical drugs and 2663 Chinese patent medicines, resulting in 19 639 clinical drugs, 250 267 unique concepts, and 2 602 760 relations. By manual review of 1700 chemical drugs and 250 Chinese patent drugs randomly selected from NCCD (about 10%), we showed that the hybrid approach could achieve an accuracy of 98.60% for drug name extraction and normalization. Using a collection of 500 chemical drugs and 500 Chinese patent drugs from other resources, we showed that NCCD achieved coverages of 97.0% and 90.0% for chemical drugs and Chinese patent drugs, respectively. Evaluation results demonstrated the potential to improve interoperability across various electronic drug systems
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Pharmacists' advancing roles in drug and disease management: a review of states' legislation.
McKnight, Alicia G; Thomason, Angela R
2009-01-01
To determine which states in the United States have provisions in place for pharmacist participation in drug and disease management programs and/or collaborative practice agreements and to provide comparison and discussion regarding such provisions. A secondary endpoint was the requirements of certification, credentialing, and registration with the specific state's rules and regulations. Information was gathered from states' statutes, rules, and regulations. Acquisition of each state's laws was achieved through various forms of electronic media. Data were accessed from January to March 2008. 19 states (38%) had specific provisions for disease management, 33 (66%) had provisions for drug therapy management, and 37 (74%) had provisions for collaborative practice. A total of 11 states (22%) specified that pharmacists receive specialized training to participate in such endeavors. Board approval or notification for collaborative practice agreements was required in 16 states (32%). With varying degrees of autonomy and restriction, pharmacists in certain states have the ability to develop disease management and/or collaborative practice programs. For pharmacists to take advantage of these new direct patient care opportunities, knowing the rules and requirements of their state's legislation is essential.
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Calderon, Silvia N; Klein, Michael
2014-12-01
In the United States of America (USA), the abuse potential assessment of a drug is performed as part of the safety evaluation of a drug under development, and to evaluate if the drug needs to be subject to controls that would minimize the abuse of the drug once on the market. The assessment of the abuse potential of new drugs consists of a scientific and medical evaluation of all data related to abuse of the drug. This paper describes the regulatory framework for evaluating the abuse potential of new drugs, in general, including novel stimulants. The role of the United States Food and Drug Administration (FDA) in the evaluation of the abuse potential of drugs, and its role in drug control are also discussed. A definition of abuse potential, an overview of the currently accepted approaches to evaluating the abuse potential of a drug, as well as a description of the criteria that applies when recommending a specific level of control (i.e., a Schedule) for a drug under the Controlled Substances Act (CSA). This article is part of the Special Issue entitled 'CNS Stimulants'. Published by Elsevier Ltd.
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Quantitative prediction of drug side effects based on drug-related features.
Niu, Yanqing; Zhang, Wen
2017-09-01
Unexpected side effects of drugs are great concern in the drug development, and the identification of side effects is an important task. Recently, machine learning methods are proposed to predict the presence or absence of interested side effects for drugs, but it is difficult to make the accurate prediction for all of them. In this paper, we transform side effect profiles of drugs as their quantitative scores, by summing up their side effects with weights. The quantitative scores may measure the dangers of drugs, and thus help to compare the risk of different drugs. Here, we attempt to predict quantitative scores of drugs, namely the quantitative prediction. Specifically, we explore a variety of drug-related features and evaluate their discriminative powers for the quantitative prediction. Then, we consider several feature combination strategies (direct combination, average scoring ensemble combination) to integrate three informative features: chemical substructures, targets, and treatment indications. Finally, the average scoring ensemble model which produces the better performances is used as the final quantitative prediction model. Since weights for side effects are empirical values, we randomly generate different weights in the simulation experiments. The experimental results show that the quantitative method is robust to different weights, and produces satisfying results. Although other state-of-the-art methods cannot make the quantitative prediction directly, the prediction results can be transformed as the quantitative scores. By indirect comparison, the proposed method produces much better results than benchmark methods in the quantitative prediction. In conclusion, the proposed method is promising for the quantitative prediction of side effects, which may work cooperatively with existing state-of-the-art methods to reveal dangers of drugs.
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Alcohol and drug policy model for the Canadian upstream petroleum industry
Energy Technology Data Exchange (ETDEWEB)
NONE
2007-09-15
This alcohol and drug policy model was developed to help employers manage and reduce the risks associated with drug and alcohol use in the workplace. The policy model outlined guidelines for establishing and implementing drug and alcohol policies, and discussed treatment programs and opportunities for re-employment. The model was developed by Enform, the upstream petroleum industry's safety and training arm, who used a previous guide developed by the Construction Owner's Association of Alberta (COAA) as a model. Enform's model provided a summary of key accountabilities across all levels of industry as well as the accepted minimum criteria for developing alcohol and drug policies. The model included guidelines and recommendations for employees, supervisors, and owners, employers, and contractors. The responsibilities of associations, organizations, and private companies were also outlined. An overview of recommended implementation plans was provided, as well as details of alcohol and drug use education programs and workplace rules. A supervisor's guide to implementation provided outlines of the causes of drug use among employees. tabs.
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Moeller, Scott J; London, Edythe D; Northoff, Georg
2016-02-01
Drug addiction is characterized by widespread abnormalities in brain function and neurochemistry, including drug-associated effects on concentrations of the excitatory and inhibitory neurotransmitters glutamate and gamma-aminobutyric acid (GABA), respectively. In healthy individuals, these neurotransmitters drive the resting state, a default condition of brain function also disrupted in addiction. Here, our primary goal was to review in vivo magnetic resonance spectroscopy and positron emission tomography studies that examined markers of glutamate and GABA abnormalities in human drug addiction. Addicted individuals tended to show decreases in these markers compared with healthy controls, but findings also varied by individual characteristics (e.g., abstinence length). Interestingly, select corticolimbic brain regions showing glutamatergic and/or GABAergic abnormalities have been similarly implicated in resting-state functional connectivity deficits in drug addiction. Thus, our secondary goals were to provide a brief review of this resting-state literature, and an initial rationale for the hypothesis that abnormalities in glutamatergic and/or GABAergic neurotransmission may underlie resting-state functional deficits in drug addiction. In doing so, we suggest future research directions and possible treatment implications. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Modeling Patient-Specific Magnetic Drug Targeting Within the Intracranial Vasculature
Directory of Open Access Journals (Sweden)
Alexander Patronis
2018-04-01
Full Text Available Drug targeting promises to substantially enhance future therapies, for example through the focussing of chemotherapeutic drugs at the site of a tumor, thus reducing the exposure of healthy tissue to unwanted damage. Promising work on the steering of medication in the human body employs magnetic fields acting on nanoparticles made of paramagnetic materials. We develop a computational tool to aid in the optimization of the physical parameters of these particles and the magnetic configuration, estimating the fraction of particles reaching a given target site in a large patient-specific vascular system for different physiological states (heart rate, cardiac output, etc.. We demonstrate the excellent computational performance of our model by its application to the simulation of paramagnetic-nanoparticle-laden flows in a circle of Willis geometry obtained from an MRI scan. The results suggest a strong dependence of the particle density at the target site on the strength of the magnetic forcing and the velocity of the background fluid flow.
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Modeling Patient-Specific Magnetic Drug Targeting Within the Intracranial Vasculature.
Patronis, Alexander; Richardson, Robin A; Schmieschek, Sebastian; Wylie, Brian J N; Nash, Rupert W; Coveney, Peter V
2018-01-01
Drug targeting promises to substantially enhance future therapies, for example through the focussing of chemotherapeutic drugs at the site of a tumor, thus reducing the exposure of healthy tissue to unwanted damage. Promising work on the steering of medication in the human body employs magnetic fields acting on nanoparticles made of paramagnetic materials. We develop a computational tool to aid in the optimization of the physical parameters of these particles and the magnetic configuration, estimating the fraction of particles reaching a given target site in a large patient-specific vascular system for different physiological states (heart rate, cardiac output, etc.). We demonstrate the excellent computational performance of our model by its application to the simulation of paramagnetic-nanoparticle-laden flows in a circle of Willis geometry obtained from an MRI scan. The results suggest a strong dependence of the particle density at the target site on the strength of the magnetic forcing and the velocity of the background fluid flow.
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“Hare Krishna vs. Shiva Shiva”: Swami Agehananda Bharati, Drugs, and the Mystical State in Hindusim
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Helton Christopher Jason
2016-12-01
Full Text Available This paper will form an overview of Swami Agehananda Bharati’s views about drugs as a catalyst for achieving the mystical state (in both a Hindu and general context, as well as his observations of the perception of drugs throughout the Hindu community, inside and outside South Asia. It will demonstrate that Bharati considered drugs a valid means toward achieving the mystical state, both as a scholar of Hinduism and as a practicing sannyasin.
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A Structural Model of the Retail Market for Illicit Drugs.
Galenianos, Manolis; Gavazza, Alessandro
2017-03-01
We estimate a model of illicit drugs markets using data on purchases of crack cocaine. Buyers are searching for high-quality drugs, but they determine drugs' quality (i.e., their purity) only after consuming them. Hence, sellers can rip off first-time buyers or can offer higher-quality drugs to induce buyers to purchase from them again. In equilibrium, a distribution of qualities persists. The estimated model implies that if drugs were legalized, in which case purity could be regulated and hence observable, the average purity of drugs would increase by approximately 20 percent and the dispersion would decrease by approximately 80 percent. Moreover, increasing penalties may raise the purity and affordability of the drugs traded by increasing sellers’ relative profitability of targeting loyal buyers versus first-time buyers.
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Modeling the drug transport in the anterior segment of the eye.
Avtar, Ram; Tandon, Deepti
2008-10-02
The aim of the present work is the development of a simple mathematical model for the time course concentration profile of topically administered drugs in the anterior chamber aqueous humor and investigation of the effects of various model parameters on the aqueous humor concentration of lipophilic and hydrophilic drugs. A simple pharmacokinetic model for the transient drug transport in the anterior segment has been developed by using the conservation of mass in the precorneal tear film, Fick's law of diffusion and Michaelis-Menten kinetics of drug metabolism in cornea, and the conservation of mass in the anterior chamber. An analytical solution describing the drug concentration in the anterior chamber has been obtained. The model predicts that an increase in the drug metabolic (consumption) rate in the corneal epithelium reduces the drug concentration in the anterior chamber for both lipophilic and hydrophilic molecules. A decrease in the clearance rate and distribution volume of the drug in the anterior chamber raises the aqueous humor concentration significantly. It is also observed that decay rate of drug concentration in the anterior chamber is higher for lipophilic molecules than that for hydrophilic molecules. The bioavailability of drugs applied topically to the eye may be improved by a rise in the precorneal tear volume, diffusion coefficient in corneal epithelium and distribution coefficient across the endothelium anterior chamber interface, and by reducing the drug metabolism, drug clearance rate and distribution volume in anterior chamber.
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Pringle, Abbie; Harmer, Catherine J
2015-12-01
Human models of emotional processing suggest that the direct effect of successful antidepressant drug treatment may be to modify biases in the processing of emotional information. Negative biases in emotional processing are documented in depression, and single or short-term dosing with conventional antidepressant drugs reverses these biases in depressed patients prior to any subjective change in mood. Antidepressant drug treatments also modulate emotional processing in healthy volunteers, which allows the consideration of the psychological effects of these drugs without the confound of changes in mood. As such, human models of emotional processing may prove to be useful for testing the efficacy of novel treatments and for matching treatments to individual patients or subgroups of patients.
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2012-01-01
Background While extensive evidence suggests that the economic recession has had far reaching effects on many economic sectors, little is known regarding its impact on prescription drug utilization. The purpose of this study is to describe the association between state-level unemployment rates and retail sales of seven therapeutic classes (statins, antidepressants, antipsychotics, angiotensin-converting enzyme [ACE] inhibitors, opiates, phosphodiesterase [PDE] inhibitors and oral contraceptives) in the United States. Methods Using a retrospective mixed ecological design, we examined retail prescription sales using IMS Health Xponent™ from September 2007 through July 2010, and we used the Bureau of Labor Statistics to derive population-based rates and mixed-effects modeling with state-level controls to examine the association between unemployment and utilization. Our main outcome measure was state-level utilization per 100,000 people for each class. Results Monthly unemployment levels and rates of use of each class varied substantially across the states. There were no statistically significant associations between use of ACE inhibitors or SSRIs/SNRIs and average unemployment in analyses across states, while for opioids and PDE inhibitors there were small statistically significant direct associations, and for the remaining classes inverse associations. Analyses using each state as its own control collectively exhibited statistically significant positive associations between increases in unemployment and prescription drug utilization for five of seven areas examined. This relationship was greatest for statins (on average, a 4% increase in utilization per 1% increased unemployment) and PDE inhibitors (3% increase in utilization per 1% increased unemployment), and lower for oral contraceptives and atypical antipsychotics. Conclusion We found no evidence of an association between increasing unemployment and decreasing prescription utilization, suggesting that any
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MODELING OF TARGETED DRUG DELIVERY PART II. MULTIPLE DRUG ADMINISTRATION
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A. V. Zaborovskiy
2017-01-01
Full Text Available In oncology practice, despite significant advances in early cancer detection, surgery, radiotherapy, laser therapy, targeted therapy, etc., chemotherapy is unlikely to lose its relevance in the near future. In this context, the development of new antitumor agents is one of the most important problems of cancer research. In spite of the importance of searching for new compounds with antitumor activity, the possibilities of the “old” agents have not been fully exhausted. Targeted delivery of antitumor agents can give them a “second life”. When developing new targeted drugs and their further introduction into clinical practice, the change in their pharmacodynamics and pharmacokinetics plays a special role. The paper describes a pharmacokinetic model of the targeted drug delivery. The conditions under which it is meaningful to search for a delivery vehicle for the active substance were described. Primary screening of antitumor agents was undertaken to modify them for the targeted delivery based on underlying assumptions of the model.
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Modern state of the assortment drugs for the treatment of vaginal candidosis
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Юлия Валентиновна Левачкова
2015-12-01
Full Text Available Today the problem of treatment of vaginal candidosis and creation of effective drugs for the treatment of this disease is actual for modern gynecology and pharmacy.Aim: to explore the structure of the assortment of drugs for the treatment of vaginal candidosis, presented in the Ukrainian pharmaceutical market.Methods: Statistical and marketing methods of investigation of electronic and paper sources of information. Implemented analysis assortment based on the materials of the State Register drugs in Ukraine and Compendium.Results: in the treatment of vaginal candidosis greatest efficiency belongs fluconazole. According to the ATC classification drugs with fluconazole includes to 2 anatomical groups, among which the main proportion of drugs for systemic use. In the pharmaceutical market of Ukraine registered 103 drugs with a fluconazole, which are mainly represented by import manufacturers. The largest share of preparations (84.8% constitute solid forms (capsules and tablets.Conclusions: vaginal medications with fluconazole are not present. Considering that the suppositories have several advantages over other pharmaceutical forms, creation of the new drugs with fluconazole is a perspective direction for modern medicine and pharmacy
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Marijuana, other drugs, and alcohol use by drivers in Washington State.
2016-07-01
In Washington State legal sales of marijuana began July 8, 2014. A voluntary, anonymous roadside study was conducted to assess the prevalence of drivers testing positive for alcohol and other drugs, including marijuana, on Washingtons roads. Data ...
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Bioresorbable polymer coated drug eluting stent: a model study.
Rossi, Filippo; Casalini, Tommaso; Raffa, Edoardo; Masi, Maurizio; Perale, Giuseppe
2012-07-02
In drug eluting stent technologies, an increased demand for better control, higher reliability, and enhanced performances of drug delivery systems emerged in the last years and thus offered the opportunity to introduce model-based approaches aimed to overcome the remarkable limits of trial-and-error methods. In this context a mathematical model was studied, based on detailed conservation equations and taking into account the main physical-chemical mechanisms involved in polymeric coating degradation, drug release, and restenosis inhibition. It allowed highlighting the interdependence between factors affecting each of these phenomena and, in particular, the influence of stent design parameters on drug antirestenotic efficacy. Therefore, the here-proposed model is aimed to simulate the diffusional release, for both in vitro and the in vivo conditions: results were verified against various literature data, confirming the reliability of the parameter estimation procedure. The hierarchical structure of this model also allows easily modifying the set of equations describing restenosis evolution to enhance model reliability and taking advantage of the deep understanding of physiological mechanisms governing the different stages of smooth muscle cell growth and proliferation. In addition, thanks to its simplicity and to the very low system requirements and central processing unit (CPU) time, our model allows obtaining immediate views of system behavior.
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Application of PBPK modelling in drug discovery and development at Pfizer.
Jones, Hannah M; Dickins, Maurice; Youdim, Kuresh; Gosset, James R; Attkins, Neil J; Hay, Tanya L; Gurrell, Ian K; Logan, Y Raj; Bungay, Peter J; Jones, Barry C; Gardner, Iain B
2012-01-01
Early prediction of human pharmacokinetics (PK) and drug-drug interactions (DDI) in drug discovery and development allows for more informed decision making. Physiologically based pharmacokinetic (PBPK) modelling can be used to answer a number of questions throughout the process of drug discovery and development and is thus becoming a very popular tool. PBPK models provide the opportunity to integrate key input parameters from different sources to not only estimate PK parameters and plasma concentration-time profiles, but also to gain mechanistic insight into compound properties. Using examples from the literature and our own company, we have shown how PBPK techniques can be utilized through the stages of drug discovery and development to increase efficiency, reduce the need for animal studies, replace clinical trials and to increase PK understanding. Given the mechanistic nature of these models, the future use of PBPK modelling in drug discovery and development is promising, however, some limitations need to be addressed to realize its application and utility more broadly.
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Computational modeling of drug transport across the in vitro cornea.
Pak, Joseph; Chen, Z J; Sun, Kay; Przekwas, Andrzej; Walenga, Ross; Fan, Jianghong
2018-01-01
A novel quasi-3D (Q3D) modeling approach was developed to model networks of one dimensional structures like tubes and vessels common in human anatomy such as vascular and lymphatic systems, neural networks, and respiratory airways. Instead of a branching network of the same tissue type, this approach was extended to model an interconnected stack of different corneal tissue layers with membrane junction conditions assigned between the tissues. The multi-laminate structure of the cornea presents a unique barrier design and opportunity for investigation using Q3D modeling. A Q3D model of an in vitro rabbit cornea was created to simulate the drug transport across the cornea, accounting for transcellular and paracellular pathways of passive and convective drug transport as well as physicochemistry of lipophilic partitioning and protein binding. Lipophilic Rhodamine B and hydrophilic fluorescein were used as drug analogs. The model predictions for both hydrophilic and lipophilic tracers were able to match the experimental measurements along with the sharp discontinuities at the epithelium-stroma and stroma-endothelium interfaces. This new modeling approach was successfully applied towards pharmacokinetic modeling for use in topical ophthalmic drug design. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Lubach, Joseph W; Hau, Jonathan
2018-02-20
To investigate the nature of drug-excipient interactions between indomethacin (IMC) and methacrylate copolymer Eudragit® E (EE) in the amorphous state, and evaluate the effects on formulation and stability of these amorphous systems. Amorphous solid dispersions containing IMC and EE were spray dried with drug loadings from 20% to 90%. PXRD was used to confirm the amorphous nature of the dispersions, and DSC was used to measure glass transition temperatures (T g ). 13 C and 15 N solid-state NMR was utilized to investigate changes in local structure and protonation state, while 1 H T 1 and T 1ρ relaxation measurements were used to probe miscibility and phase behavior of the dispersions. T g values for IMC-EE solid dispersions showed significant positive deviations from predicted values in the drug loading range of 40-90%, indicating a relatively strong drug-excipient interaction. 15 N solid-state NMR exhibited a change in protonation state of the EE basic amine, with two distinct populations for the EE amine at -360.7 ppm (unprotonated) and -344.4 ppm (protonated). Additionally, 1 H relaxation measurements showed phase separation at high drug load, indicating an amorphous ionic complex and free IMC-rich phase. PXRD data showed all ASDs up to 90% drug load remained physically stable after 2 years. 15 N solid-state NMR experiments show a change in protonation state of EE, indicating that an ionic complex indeed forms between IMC and EE in amorphous solid dispersions. Phase behavior was determined to exhibit nanoscale phase separation at high drug load between the amorphous ionic complex and excess free IMC.
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Jain, Vaibhav; Maiti, Prabal K.; Bharatam, Prasad V.
2016-09-01
Computational studies performed on dendrimer-drug complexes usually consider 1:1 stoichiometry, which is far from reality, since in experiments more number of drug molecules get encapsulated inside a dendrimer. In the present study, molecular dynamic (MD) simulations were implemented to characterize the more realistic molecular models of dendrimer-drug complexes (1:n stoichiometry) in order to understand the effect of high drug loading on the structural properties and also to unveil the atomistic level details. For this purpose, possible inclusion complexes of model drug Nateglinide (Ntg) (antidiabetic, belongs to Biopharmaceutics Classification System class II) with amine- and acetyl-terminated G4 poly(amidoamine) (G4 PAMAM(NH2) and G4 PAMAM(Ac)) dendrimers at neutral and low pH conditions are explored in this work. MD simulation analysis on dendrimer-drug complexes revealed that the drug encapsulation efficiency of G4 PAMAM(NH2) and G4 PAMAM(Ac) dendrimers at neutral pH was 6 and 5, respectively, while at low pH it was 12 and 13, respectively. Center-of-mass distance analysis showed that most of the drug molecules are located in the interior hydrophobic pockets of G4 PAMAM(NH2) at both the pH; while in the case of G4 PAMAM(Ac), most of them are distributed near to the surface at neutral pH and in the interior hydrophobic pockets at low pH. Structural properties such as radius of gyration, shape, radial density distribution, and solvent accessible surface area of dendrimer-drug complexes were also assessed and compared with that of the drug unloaded dendrimers. Further, binding energy calculations using molecular mechanics Poisson-Boltzmann surface area approach revealed that the location of drug molecules in the dendrimer is not the decisive factor for the higher and lower binding affinity of the complex, but the charged state of dendrimer and drug, intermolecular interactions, pH-induced conformational changes, and surface groups of dendrimer do play an
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Directory of Open Access Journals (Sweden)
Maciej Leszczyński
2017-01-01
Full Text Available We consider an optimal control problem for a general mathematical model of drug treatment with a single agent. The control represents the concentration of the agent and its effect (pharmacodynamics is modelled by a Hill function (i.e., Michaelis-Menten type kinetics. The aim is to minimize a cost functional consisting of a weighted average related to the state of the system (both at the end and during a fixed therapy horizon and to the total amount of drugs given. The latter is an indirect measure for the side effects of treatment. It is shown that optimal controls are continuous functions of time that change between full or no dose segments with connecting pieces that take values in the interior of the control set. Sufficient conditions for the strong local optimality of an extremal controlled trajectory in terms of the existence of a solution to a piecewise defined Riccati differential equation are given.
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Drug-induced cholestasis: mechanisms, models, and markers.
Chatterjee, Sagnik; Annaert, Pieter
2018-04-27
Drug-induced cholestasis is a risk factor in progression of drug candidates, and poses serious health hazard if not detected before going into human. Intrahepatic accumulation of bile acids (BAs) represents a characteristic phenomenon associated with drug-induced cholestasis. The major challenges in obtaining a complete understanding of drug-induced cholestasis lies in the complexity of BA-mediated toxicity mechanisms and the impact of bile acids at different 'targets' such as transporters, enzymes and nuclear receptors. At the same time, it is not trivial to have a relevant in vitro system that recapitulates these features. In addition, lack of sensitive and early preclinical biomarkers, relevant to the clinical situation, complicates proper detection of drug-induced cholestasis. Significant overlap in biomarker signatures between different mechanisms of drug-induced liver injury (DILI) precludes identification of specific mechanisms. Over the last decade the knowledge gaps in drug-induced cholestasis are closing due to growing mechanistic understanding of BA-mediated toxicity at (patho)physiologically relevant BA concentrations. Significant progress has been made in the mechanistic understanding of drug-induced cholestasis and associated toxicity, biomarkers and susceptibility factors. In addition, novel in vitro models are evolving which provide a holistic understanding of processes underlying drug-induced cholestasis. This review summarizes the challenges and recent understandings about drug-induced cholestasis with a potential path forward. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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Guerrero, Erick G; Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A; Mora, Maria Elena Medina
2014-05-01
Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and US migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N=16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans' migrant status - (1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals) - featured analysis of variance and Chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR=2.453, 95% CI=1.933, 3.113) and using more illicit drugs (IRR=2.061, 95% CI=1.626, 2.613). Women were less likely than men to report having used drugs (OR=0.187, 95% CI=0.146, 0.239) and using more illicit drugs (IRR=0.153, 95% CI=0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. Copyright © 2014 Elsevier B.V. All rights reserved.
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Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A.; Mora, Maria Elena Medina
2014-01-01
Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and U.S. migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N = 16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans’ migrant status—(1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals)—featured analysis of variance and chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR = 2.453, 95% CI = 1.933, 3.113) and using more illicit drugs (IRR = 2.061, 95% CI = 1.626, 2.613). Women were less likely than men to report having used drugs (OR = 0.187, 95% CI = 0.146, 0.239) and using more illicit drugs (IRR = 0.153, 95% CI = 0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. PMID:24816376
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Drug-Target Kinetics in Drug Discovery.
Tonge, Peter J
2018-01-17
The development of therapies for the treatment of neurological cancer faces a number of major challenges including the synthesis of small molecule agents that can penetrate the blood-brain barrier (BBB). Given the likelihood that in many cases drug exposure will be lower in the CNS than in systemic circulation, it follows that strategies should be employed that can sustain target engagement at low drug concentration. Time dependent target occupancy is a function of both the drug and target concentration as well as the thermodynamic and kinetic parameters that describe the binding reaction coordinate, and sustained target occupancy can be achieved through structural modifications that increase target (re)binding and/or that decrease the rate of drug dissociation. The discovery and deployment of compounds with optimized kinetic effects requires information on the structure-kinetic relationships that modulate the kinetics of binding, and the molecular factors that control the translation of drug-target kinetics to time-dependent drug activity in the disease state. This Review first introduces the potential benefits of drug-target kinetics, such as the ability to delineate both thermodynamic and kinetic selectivity, and then describes factors, such as target vulnerability, that impact the utility of kinetic selectivity. The Review concludes with a description of a mechanistic PK/PD model that integrates drug-target kinetics into predictions of drug activity.
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Animal models for testing anti-prion drugs.
Fernández-Borges, Natalia; Elezgarai, Saioa R; Eraña, Hasier; Castilla, Joaquín
2013-01-01
Prion diseases belong to a group of fatal infectious diseases with no effective therapies available. Throughout the last 35 years, less than 50 different drugs have been tested in different experimental animal models without hopeful results. An important limitation when searching for new drugs is the existence of appropriate models of the disease. The three different possible origins of prion diseases require the existence of different animal models for testing anti-prion compounds. Wild type, over-expressing transgenic mice and other more sophisticated animal models have been used to evaluate a diversity of compounds which some of them were previously tested in different in vitro experimental models. The complexity of prion diseases will require more pre-screening studies, reliable sporadic (or spontaneous) animal models and accurate chemical modifications of the selected compounds before having an effective therapy against human prion diseases. This review is intended to put on display the more relevant animal models that have been used in the search of new antiprion therapies and describe some possible procedures when handling chemical compounds presumed to have anti-prion activity prior to testing them in animal models.
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How Preclinical Models Evolved to Resemble the Diagnostic Criteria of Drug Addiction.
Belin-Rauscent, Aude; Fouyssac, Maxime; Bonci, Antonello; Belin, David
2016-01-01
Drug addiction is a complex neuropsychiatric disorder that affects a subset of the individuals who take drugs. It is characterized by maladaptive drug-seeking habits that are maintained despite adverse consequences and intense drug craving. The pathophysiology and etiology of addiction is only partially understood despite extensive research because of the gap between current preclinical models of addiction and the clinical criteria of the disorder. This review presents a brief overview, based on selected methodologies, of how behavioral models have evolved over the last 50 years to the development of recent preclinical models of addiction that more closely mimic diagnostic criteria of addiction. It is hoped that these new models will increase our understanding of the complex neurobiological mechanisms whereby some individuals switch from controlled drug use to compulsive drug-seeking habits and relapse to these maladaptive habits. Additionally, by paving the way to bridge the gap that exists between biobehavioral research on addiction and the human situation, these models may provide new perspectives for the development of novel and effective therapeutic strategies for drug addiction. Published by Elsevier Inc.
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A drug cost model for injuries due to road traffic accidents.
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Riewpaiboon A
2008-03-01
Full Text Available Objective: This study aimed to develop a drug cost model for injuries due to road traffic accidents for patients receiving treatment at a regional hospital in Thailand. Methods: The study was designed as a retrospective, descriptive analysis. The cases were all from road traffic accidents receiving treatment at a public regional hospital in the fiscal year 2004. Results: Three thousand seven hundred and twenty-three road accident patients were included in the study. The mean drug cost per case was USD18.20 (SD=73.49, median=2.36. The fitted drug cost model had an adjusted R2 of 0.449. The positive significant predictor variables of drug costs were prolonged length of stay, age over 30 years old, male, Universal Health Coverage Scheme, time of accident during 18:00-24:00 o’clock, and motorcycle comparing to bus. To forecast the drug budget for 2006, there were two approaches identified, the mean drug cost and the predicted average drug cost. The predicted average drug cost was calculated based on the forecasted values of statistically significant (p<0.05 predictor variables included in the fitted model; predicted total drug cost was USD44,334. Alternatively, based on the mean cost, predicted total drug cost in 2006 was USD63,408. This was 43% higher than the figure based on the predicted cost approach.Conclusions: The planned budget of drug cost based on the mean cost and predicted average cost were meaningfully different. The application of a predicted average cost model could result in a more accurate budget planning than that of a mean statistic approach.
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Hirai, Daiki; Iwao, Yasunori; Kimura, Shin-Ichiro; Noguchi, Shuji; Itai, Shigeru
2017-04-30
Metastable crystals and the amorphous state of poorly water-soluble drugs in solid dispersions (SDs), are subject to a solid-liquid interface reaction upon exposure to a solvent. The dissolution behavior during the solid-liquid interface reaction often shows that the concentration of drugs is supersaturated, with a high initial drug concentration compared with the solubility of stable crystals but finally approaching the latter solubility with time. However, a method for measuring the precipitation rate of stable crystals and/or the potential solubility of metastable crystals or amorphous drugs has not been established. In this study, a novel mathematical model that can represent the dissolution behavior of the solid-liquid interface reaction for metastable crystals or amorphous drug was developed and its validity was evaluated. The theory for this model was based on the Noyes-Whitney equation and assumes that the precipitation of stable crystals at the solid-liquid interface occurs through a first-order reaction. Moreover, two models were developed, one assuming that the surface area of the drug remains constant because of the presence of excess drug in the bulk and the other that the surface area changes in time-dependency because of agglomeration of the drug. SDs of Ibuprofen (IB)/polyvinylpyrrolidone (PVP) were prepared and their dissolution behaviors under non-sink conditions were fitted by the models to evaluate improvements in solubility. The model assuming time-dependent surface area showed good agreement with experimental values. Furthermore, by applying the model to the dissolution profile, parameters such as the precipitation rate and the potential solubility of the amorphous drug were successfully calculated. In addition, it was shown that the improvement in solubility with supersaturation was able to be evaluated quantitatively using this model. Therefore, this mathematical model would be a useful tool to quantitatively determine the supersaturation
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[Alternatives to the drug research and development model].
Velásquez, Germán
2015-03-01
One-third of the global population lacks access to medications; the situation is worse in poor countries, where up to 50% of the population lacks access. The failure of current incentive systems based in intellectual property to offer the necessary pharmaceutical products, especially in the global south, is a call to action. Problems related to drug access cannot be solved solely through improvements or modifications in the existing incentive models. The intellectual property system model does not offer sufficient innovation for developing countries; new mechanisms that effectively promote innovation and drug access simultaneously are needed. A binding international agreement on research and development, negotiated under the auspices of the World Health Organization, could provide an adequate framework for guaranteeing priority-setting, coordination, and sustainable financing of drugs at reasonable prices for developing countries.
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Edman, Johan
2016-06-01
This article examines developments in the Swedish drug treatment services in 1982-2000 and explores the ways in which political initiatives and the state administration's management have contributed to the major privatisations of institutional drug treatment during this period. The empirical basis for the textual analysis lies in official reports, parliamentary material and archived records from the Stockholm County Administrative Board's management of treatment facilities. The major privatisations of drug treatment services in the 1980s were both unintentional and unwanted and mainly arose from a lack of bureaucratic control and ideological anchorage. The privatisations were, however, reinforced by ideologically driven NPM-oriented political initiatives in the 1990s. The market-oriented treatment services have failed to fulfil the needs for diversity and availability within a publicly financed sector, which deals with unevenly informed and often socio-economically weak citizens. New management models in this field must ensure that ideological considerations are taken into account to meet politically decided goals and means. Copyright © 2016 Elsevier B.V. All rights reserved.
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Qi, Sheng; McAuley, William J; Yang, Ziyi; Tipduangta, Pratchaya
2014-07-01
Use of the amorphous state is considered to be one of the most effective approaches for improving the dissolution and subsequent oral bioavailability of poorly water-soluble drugs. However as the amorphous state has much higher physical instability in comparison with its crystalline counterpart, stabilization of amorphous drugs in a solid-dosage form presents a major challenge to formulators. The currently used approaches for stabilizing amorphous drug are discussed in this article with respect to their preparation, mechanism of stabilization and limitations. In order to realize the potential of amorphous formulations, significant efforts are required to enable the prediction of formulation performance. This will facilitate the development of computational tools that can inform a rapid and rational formulation development process for amorphous drugs.
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Xu, Yingqian; Wang, Bochu; Deng, Jia; Liu, Zerong; Zhu, Liancai
2013-01-01
The purpose of this paper was to research the potential of a dynamic cell model in drug screening by studying the influence of microvascular wall shear stress on the drug absorption of endothelial cells compared to that in the static state. The cells were grown and seeded on gelatin-coated glass slides and were pretreated with extracts of Salviae miltiorrhizae (200 μg/ml) for 1 h. Then oxidative stress damage was produced by H2O2 (300 μmol/l) for 0.5 h under the 1.5 dyn/cm2 shear stress incorporated in a parallel plate flow chamber. Morphological analysis was conducted with an inverted microscope and image analysis software, and high performance liquid chromatography-mass spectrometry was used for the detection of active compounds. We compared the drug absorption in the dynamic group with that in the static group. In the dynamic model, five compounds and two new metabolite peaks were detected. However, in the static model, four compounds were absorbed by cells, and one metabolite peak was found. This study indicated that there were some effects on the absorption and metabolism of drugs under the microvascular shear stress compared to that under stasis. We infer that shear stress in the microcirculation situation in vivo played a role in causing the differences between drug screening in vitro and in vivo.
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[Categories and characteristics of BPH drug evaluation models: a comparative study].
Huang, Dong-Yan; Wu, Jian-Hui; Sun, Zu-Yue
2014-02-01
Benign prostatic hyperplasia (BPH) is a worldwide common disease in men over 50 years old, and the exact cause of BPH remains largely unknown. In order to elucidate its pathogenesis and screen effective drugs for the treatment of BPH, many BPH models have been developed at home and abroad. This article presents a comprehensive analysis of the categories and characteristics of BPH drug evaluation models, highlighting the application value of each model, to provide a theoretical basis for the development of BPH drugs.
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Macheras, Panos; Iliadis, Athanassios; Melagraki, Georgia
2018-05-30
The aim of this work is to develop a gastrointestinal (GI) drug absorption model based on a reaction limited model of dissolution and consider its impact on the biopharmaceutic classification of drugs. Estimates for the fraction of dose absorbed as a function of dose, solubility, reaction/dissolution rate constant and the stoichiometry of drug-GI fluids reaction/dissolution were derived by numerical solution of the model equations. The undissolved drug dose and the reaction/dissolution rate constant drive the dissolution rate and determine the extent of absorption when high-constant drug permeability throughout the gastrointestinal tract is assumed. Dose is an important element of drug-GI fluids reaction/dissolution while solubility exclusively acts as an upper limit for drug concentrations in the lumen. The 3D plots of fraction of dose absorbed as a function of dose and reaction/dissolution rate constant for highly soluble and low soluble drugs for different "stoichiometries" (0.7, 1.0, 2.0) of the drug-reaction/dissolution with the GI fluids revealed that high extent of absorption was found assuming high drug- reaction/dissolution rate constant and high drug solubility. The model equations were used to simulate in vivo supersaturation and precipitation phenomena. The model developed provides the theoretical basis for the interpretation of the extent of drug's absorption on the basis of the parameters associated with the drug-GI fluids reaction/dissolution. A new paradigm emerges for the biopharmaceutic classification of drugs, namely, a model independent biopharmaceutic classification scheme of four drug categories based on either the fulfillment or not of the current dissolution criteria and the high or low % drug metabolism. Copyright © 2018. Published by Elsevier B.V.
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PBPK Modeling - A Predictive, Eco-Friendly, Bio-Waiver Tool for Drug Research.
De, Baishakhi; Bhandari, Koushik; Mukherjee, Ranjan; Katakam, Prakash; Adiki, Shanta K; Gundamaraju, Rohit; Mitra, Analava
2017-01-01
The world has witnessed growing complexities in disease scenario influenced by the drastic changes in host-pathogen- environment triadic relation. Pharmaceutical R&Ds are in constant search of novel therapeutic entities to hasten transition of drug molecules from lab bench to patient bedside. Extensive animal studies and human pharmacokinetics are still the "gold standard" in investigational new drug research and bio-equivalency studies. Apart from cost, time and ethical issues on animal experimentation, burning questions arise relating to ecological disturbances, environmental hazards and biodiversity issues. Grave concerns arises when the adverse outcomes of continued studies on one particular disease on environment gives rise to several other pathogenic agents finally complicating the total scenario. Thus Pharma R&Ds face a challenge to develop bio-waiver protocols. Lead optimization, drug candidate selection with favorable pharmacokinetics and pharmacodynamics, toxicity assessment are vital steps in drug development. Simulation tools like Gastro Plus™, PK Sim®, SimCyp find applications for the purpose. Advanced technologies like organ-on-a chip or human-on-a chip where a 3D representation of human organs and systems can mimic the related processes and activities, thereby linking them to major features of human biology can be successfully incorporated in the drug development tool box. PBPK provides the State of Art to serve as an optional of animal experimentation. PBPK models can successfully bypass bio-equivalency studies, predict bioavailability, drug interactions and on hyphenation with in vitro-in vivo correlation can be extrapolated to humans thus serving as bio-waiver. PBPK can serve as an eco-friendly bio-waiver predictive tool in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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A graph theoretical perspective of a drug abuse epidemic model
Nyabadza, F.; Mukwembi, S.; Rodrigues, B. G.
2011-05-01
A drug use epidemic can be represented by a finite number of states and transition rules that govern the dynamics of drug use in each discrete time step. This paper investigates the spread of drug use in a community where some users are in treatment and others are not in treatment, citing South Africa as an example. In our analysis, we consider the neighbourhood prevalence of each individual, i.e., the proportion of the individual’s drug user contacts who are not in treatment amongst all of his or her contacts. We introduce parameters α∗, β∗ and γ∗, depending on the neighbourhood prevalence, which govern the spread of drug use. We examine how changes in α∗, β∗ and γ∗ affect the system dynamics. Simulations presented support the theoretical results.
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Old and new therapeutics for Rheumatoid Arthritis: in vivo models and drug development
DEFF Research Database (Denmark)
Sardar, Samra; Andersson, Åsa
2016-01-01
Development of novel drugs for treatment of chronic inflammatory diseases is to a large extent dependent on the availability of good experimental in vivo models in order to perform preclinical tests of new drugs and for the identification of novel drug targets. Here, we review a number of existing...... of in vivo models during development of anti-rheumatic drugs; from Methotrexate to various antibody treatments, to novel drugs that are, or have recently been, in clinical trials. For novel drugs, we have explored websites for clinical trials. Although one Rheumatoid Arthritis in vivo model cannot mirror...
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Coomber, Kerri; Toumbourou, John W.; Miller, Peter; Staiger, Petra K.; Hemphill, Sheryl A.; Catalano, Richard F.
2011-01-01
Purpose: There are inconsistent research findings regarding the impact of rurality on adolescent alcohol, tobacco, and illicit substance use. Therefore, the current study reports on the effect of rurality on alcohol, tobacco, and illicit drug use among adolescents in 2 state representative samples in 2 countries, Washington State (WA) in the…
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Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin
2013-03-01
Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Marijuana, other drugs, and alcohol use by drivers in Washington state : appendices.
2016-07-01
In Washington State legal sales of marijuana began July 8, 2014. A voluntary, anonymous roadside study was conducted to assess the prevalence of drivers testing positive for alcohol and other drugs, including marijuana, on Washingtons roads. Data ...
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Evaluation of the whole body physiologically based pharmacokinetic (WB-PBPK) modeling of drugs.
Munir, Anum; Azam, Shumaila; Fazal, Sahar; Bhatti, A I
2018-08-14
The Physiologically based pharmacokinetic (PBPK) modeling is a supporting tool in drug discovery and improvement. Simulations produced by these models help to save time and aids in examining the effects of different variables on the pharmacokinetics of drugs. For this purpose, Sheila and Peters suggested a PBPK model capable of performing simulations to study a given drug absorption. There is a need to extend this model to the whole body entailing all another process like distribution, metabolism, and elimination, besides absorption. The aim of this scientific study is to hypothesize a WB-PBPK model through integrating absorption, distribution, metabolism, and elimination processes with the existing PBPK model.Absorption, distribution, metabolism, and elimination models are designed, integrated with PBPK model and validated. For validation purposes, clinical records of few drugs are collected from the literature. The developed WB-PBPK model is affirmed by comparing the simulations produced by the model against the searched clinical data. . It is proposed that the WB-PBPK model may be used in pharmaceutical industries to create of the pharmacokinetic profiles of drug candidates for better outcomes, as it is advance PBPK model and creates comprehensive PK profiles for drug ADME in concentration-time plots. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Modeling chemical reactions for drug design.
Gasteiger, Johann
2007-01-01
Chemical reactions are involved at many stages of the drug design process. This starts with the analysis of biochemical pathways that are controlled by enzymes that might be downregulated in certain diseases. In the lead discovery and lead optimization process compounds have to be synthesized in order to test them for their biological activity. And finally, the metabolism of a drug has to be established. A better understanding of chemical reactions could strongly help in making the drug design process more efficient. We have developed methods for quantifying the concepts an organic chemist is using in rationalizing reaction mechanisms. These methods allow a comprehensive modeling of chemical reactivity and thus are applicable to a wide variety of chemical reactions, from gas phase reactions to biochemical pathways. They are empirical in nature and therefore allow the rapid processing of large sets of structures and reactions. We will show here how methods have been developed for the prediction of acidity values and of the regioselectivity in organic reactions, for designing the synthesis of organic molecules and of combinatorial libraries, and for furthering our understanding of enzyme-catalyzed reactions and of the metabolism of drugs.
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Directory of Open Access Journals (Sweden)
Farai Nyabadza
2017-01-01
Full Text Available The complex problem of drug abuse and drug-related crimes in communities in the Western Cape province cannot be studied in isolation but through the system they are embedded in. In this paper, a theoretical model to evaluate the syndemic of substance abuse and drug-related crimes within the Western Cape province of South Africa is constructed and explored. The dynamics of drug abuse and drug-related crimes within the Western Cape are simulated using STELLA software. The simulation results are consistent with the data from SACENDU and CrimeStats SA, highlighting the usefulness of such a model in designing and planning interventions to combat substance abuse and its related problems.
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Directory of Open Access Journals (Sweden)
Richard M. Reisman
2009-01-01
Full Text Available Context The dramatic rise in the use of prescription opioids to treat non-cancer pain has been paralleled by increasing prescription opioid abuse. However, detailed analyses of these trends and programs to address them are lacking. Objective To study the association between state shipments of prescription opioids for medical use and prescription opioid abuse admissions and to assess the effects of state prescription drug monitoring programs (PDMPs on prescription opioid abuse admissions. Design and Setting A retrospective ecological cohort study comparing state prescription opioid shipments (source: Automation of Reports and Consolidated Orders Systems database and inpatient admissions for prescription opioid abuse (source: Treatment Episode Data Set in 14 states with PDMPs (intervention group and 36 states without PDMPs (control group for the period 1997–2003. Results From 1997 to 2003, oxycodone, morphine, and hydrocodone shipments increased by 479%, 100%, and 148% respectively. Increasing prescription oxycodone shipments were significantly associated with increasing prescription opioid admission rates (p < 0.001. PDMP states had significantly lower oxycodone shipments than the control group. PDMP states had less increase in prescription opioid admissions per year (p = 0.063. A patient admitted to an inpatient drug abuse rehabilitation program in a PDMP state was less likely to be admitted for prescription opioid drug abuse (Odds ratio = 0.775, 95% Confidence Interval 0.764–0.785. Conclusions PDMPs appear to decrease the quantity of oxycodone shipments and the prescription opioid admission rate for states with these programs. Overall, opioid shipments rose significantly in PDMP states during the study period indicating a negligible “chilling effect” on physician prescribing.
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Buyukozturk, Fulden; Di Maio, Selena; Budil, David E.; Carrier, Rebecca L.
2014-01-01
Purpose To mechanistically study and model the effect of lipids, either from food or self-emulsifying drug delivery systems (SEDDS), on drug transport in the intestinal lumen. Methods Simultaneous lipid digestion, dissolution/release, and drug partitioning were experimentally studied and modeled for two dosing scenarios: solid drug with a food-associated lipid (soybean oil) and drug solubilized in a model SEDDS (soybean oil and Tween 80 at 1:1 ratio). Rate constants for digestion, permeability of emulsion droplets, and partition coefficients in micellar and oil phases were measured, and used to numerically solve the developed model. Results Strong influence of lipid digestion on drug release from SEDDS and solid drug dissolution into food-associated lipid emulsion were observed and predicted by the developed model. 90 minutes after introduction of SEDDS, there was 9% and 70% drug release in the absence and presence of digestion, respectively. However, overall drug dissolution in the presence of food-associated lipids occurred over a longer period than without digestion. Conclusion A systems-based mechanistic model incorporating simultaneous dynamic processes occurring upon dosing of drug with lipids enabled prediction of aqueous drug concentration profile. This model, once incorporated with a pharmacokinetic model considering processes of drug absorption and drug lymphatic transport in the presence of lipids, could be highly useful for quantitative prediction of impact of lipids on bioavailability of drugs. PMID:24234918
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Hunnisett-Dritz, Dee
2012-08-15
The importation of cytarabine into the United States during a critical national drug shortage is described. In March 2011, the hospital pharmacy team at an acute care hospital was struggling to supply cytarabine for four specific patients, all of whom needed critical maintenance therapy after induction. Cytarabine was not available from any source in the United States, and the team had no realistic projected release dates for back orders. Idis UK, a pharmaceutical distributor, was asked to identify available drug and eventually found an unrestricted source of cytarabine in Switzerland. Once available drug was identified, a price quote for the supply amount was written for our consideration. This was inspected carefully to ensure that the drug, strength, dosage form, and any other ingredients listed were indeed what were expected. The pharmacy department worked with the hospital's department of finance and accounting to submit the necessary financial paperwork. Payment was electronically sent to the distributor before the drug was shipped. Before the order for cytarabine was placed, the associated risks and benefits were assessed. The patients provided consent to treatment with the unapproved product. Acceptance of the price quote and instructions to order the drug were e-mailed to the distributor. The necessary documentation was completed and included with the shipment. The importation process, from initial inquiries to delivery, took 21 days. The importation of cytarabine amid a drug shortage required a complex process that involved the efforts of an overseas distributor, the cooperation of multiple health professionals, and meticulous attention to detail.
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Modeling the development of drug addiction in male and female animals.
Lynch, Wendy J
2018-01-01
An increasing emphasis has been placed on the development and use of animal models of addiction that capture defining features of human drug addiction, including escalation/binge drug use, enhanced motivation for the drug, preference for the drug over other reward options, use despite negative consequences, and enhanced drug-seeking/relapse vulnerability. The need to examine behavior in both males and females has also become apparent given evidence demonstrating that the addiction process occurs differently in males and females. This review discusses the procedures that are used to model features of addiction in animals, as well as factors that influence their development. Individual differences are also discussed, with a particular focus on sex differences. While no one procedure consistently produces all characteristics, different models have been developed to focus on certain characteristics. A history of escalating/binge patterns of use appears to be critical for producing other features characteristic of addiction, including an enhanced motivation for the drug, enhanced drug seeking, and use despite negative consequences. These characteristics tend to emerge over abstinence, and appear to increase rather than decrease in magnitude over time. In females, these characteristics develop sooner during abstinence and/or following less drug exposure as compared to males, and for psychostimulant addiction, may require estradiol. Although preference for the drug over other reward options has been demonstrated in non-human primates, it has been more difficult to establish in rats. Future research is needed to define the parameters that optimally induce each of these features of addiction in the majority of animals. Such models are essential for advancing our understanding of human drug addiction and its treatment in men and women. Copyright © 2017 Elsevier Inc. All rights reserved.
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Brouwers, Joachim; Tack, Jan; Augustijns, Patrick
2007-10-01
The purpose of this study was to explore the feasibility of linking the pharmacokinetic profile of a drug with its gastrointestinal behavior by simultaneously monitoring plasma and intraluminal drug concentrations. Fosamprenavir, a phosphate ester prodrug of the poorly water-soluble HIV-inhibitor amprenavir, was selected as model compound. A single tablet of fosamprenavir (Telzir) was administered to 5 volunteers in the fasted and fed state (simulated by intake of a nutritional drink). Gastric and duodenal fluids were aspirated in function of time and characterized with respect to the concentration of (fos)amprenavir, inorganic phosphate and pH. In parallel, blood samples were collected and analyzed for amprenavir. The observed plasma concentration-time profiles suggested a food-induced delay in the absorption of amprenavir: in the fed state, mean tmax increased by more than 150 min compared to the fasted state. A similar delay was seen in the duodenal appearance of fosamprenavir (concentrations in mM-range) and, after dephosphorylation, amprenavir (concentrations below 160 microM). This observation could be related to the behavior of fosamprenavir in the stomach. In the fasted state, gastric dissolution of fosamprenavir started immediately, resulting in a Cmax of 4 +/- 2 mM after 43 +/- 15 min; however, in the fed state, the fosamprenavir concentration remained below 20 microM for the first 90 min after drug intake. The postponed gastric dissolution may be attributed to a food-induced delay in tablet disintegration. For the first time, the pharmacokinetic profile of a drug was monitored in parallel with its gastrointestinal concentrations. The observed food effect in the plasma concentration-time profile of amprenavir after intake of its phosphate ester prodrug could be related to a food-induced delay in gastric dissolution of fosamprenavir.
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Mining FDA drug labels using an unsupervised learning technique--topic modeling.
Bisgin, Halil; Liu, Zhichao; Fang, Hong; Xu, Xiaowei; Tong, Weida
2011-10-18
The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering "topics" that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that might arise from specific
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Mining FDA drug labels using an unsupervised learning technique - topic modeling
2011-01-01
Background The Food and Drug Administration (FDA) approved drug labels contain a broad array of information, ranging from adverse drug reactions (ADRs) to drug efficacy, risk-benefit consideration, and more. However, the labeling language used to describe these information is free text often containing ambiguous semantic descriptions, which poses a great challenge in retrieving useful information from the labeling text in a consistent and accurate fashion for comparative analysis across drugs. Consequently, this task has largely relied on the manual reading of the full text by experts, which is time consuming and labor intensive. Method In this study, a novel text mining method with unsupervised learning in nature, called topic modeling, was applied to the drug labeling with a goal of discovering “topics” that group drugs with similar safety concerns and/or therapeutic uses together. A total of 794 FDA-approved drug labels were used in this study. First, the three labeling sections (i.e., Boxed Warning, Warnings and Precautions, Adverse Reactions) of each drug label were processed by the Medical Dictionary for Regulatory Activities (MedDRA) to convert the free text of each label to the standard ADR terms. Next, the topic modeling approach with latent Dirichlet allocation (LDA) was applied to generate 100 topics, each associated with a set of drugs grouped together based on the probability analysis. Lastly, the efficacy of the topic modeling was evaluated based on known information about the therapeutic uses and safety data of drugs. Results The results demonstrate that drugs grouped by topics are associated with the same safety concerns and/or therapeutic uses with statistical significance (P<0.05). The identified topics have distinct context that can be directly linked to specific adverse events (e.g., liver injury or kidney injury) or therapeutic application (e.g., antiinfectives for systemic use). We were also able to identify potential adverse events that
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Computing characterizations of drugs for ion channels and receptors using Markov models
Tveito, Aslak
2016-01-01
Flow of ions through voltage gated channels can be represented theoretically using stochastic differential equations where the gating mechanism is represented by a Markov model. The flow through a channel can be manipulated using various drugs, and the effect of a given drug can be reflected by changing the Markov model. These lecture notes provide an accessible introduction to the mathematical methods needed to deal with these models. They emphasize the use of numerical methods and provide sufficient details for the reader to implement the models and thereby study the effect of various drugs. Examples in the text include stochastic calcium release from internal storage systems in cells, as well as stochastic models of the transmembrane potential. Well known Markov models are studied and a systematic approach to including the effect of mutations is presented. Lastly, the book shows how to derive the optimal properties of a theoretical model of a drug for a given mutation defined in terms of a Markov model.
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Haneef, Jamshed; Chadha, Renu
2017-08-01
The present study deals with the application of mechanochemical approach for the preparation of drug-drug multicomponent solid forms of three poorly soluble antihypertensive drugs (telmisartan, irbesartan and hydrochlorothiazide) using atenolol as a coformer. The resultant solid forms comprise of cocrystal (telmisartan-atenolol), coamorphous (irbesartan-atenolol) and eutectic (hydrochlorothiazide-atenolol). The study emphasizes that solid-state transformation of drug molecules into new forms is a result of the change in structural patterns, diminishing of dimers and creating new facile hydrogen bonding network based on structural resemblance. The propensity for heteromeric or homomeric interaction between two different drugs resulted into diverse solid forms (cocrystal/coamorphous/eutectics) and become one of the interesting aspects of this research work. Evaluation of these solid forms revealed an increase in solubility and dissolution leading to better antihypertensive activity in deoxycorticosterone acetate (DOCA) salt-induced animal model. Thus, development of these drug-drug multicomponent solid forms is a promising and viable approach to addressing the issue of poor solubility and could be of considerable interest in dual drug therapy for the treatment of hypertension.
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Consequences of adolescent use of alcohol and other drugs: Studies using rodent models
Spear, Linda Patia
2016-01-01
Studies using animal models of adolescent exposure to alcohol, nicotine, cannabinoids, and the stimulants cocaine, 3,4-Methylenedioxymethampethamine and methamphetamine have revealed a variety of persisting neural and behavioral consequences. Affected brain regions often include mesolimbic and prefrontal regions undergoing notable ontogenetic change during adolescence, although it is unclear whether this represents areas of specific vulnerability or particular scrutiny to date. Persisting alterations in forebrain systems critical for modulating reward, socioemotional processing and cognition have emerged, including apparent induction of a hyper-dopaminergic state with some drugs and/or attenuations in neurons expressing cholinergic markers. Disruptions in cognitive functions such as working memory, alterations in affect including increases in social anxiety, and mixed evidence for increases in later drug self-administration have also been reported. When consequences of adolescent and adult exposure were compared, adolescents were generally found to be more vulnerable to alcohol, nicotine, and cannabinoids, but generally not to stimulants. More work is needed to determine how adolescent drug exposure influences sculpting of the adolescent brain, and provide approaches to prevent/reverse these effects. PMID:27484868
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Application of Model Animals in the Study of Drug Toxicology
Song, Yagang; Miao, Mingsan
2018-01-01
Drug safety is a key factor in drug research and development, Drug toxicology test is the main method to evaluate the safety of drugs, The body condition of an animal has important implications for the results of the study, Previous toxicological studies of drugs were carried out in normal animals in the past, There is a great deviation from the clinical practice.The purpose of this study is to investigate the necessity of model animals as a substitute for normal animals for toxicological studies, It is expected to provide exact guidance for future drug safety evaluation.
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International Nuclear Information System (INIS)
Li Yuting; Wang Tianyi; Wang Jing; Jiang Tongying; Cheng Gang; Wang Siling
2011-01-01
The purpose of this study was to develop carboxyl multi-wall carbon nanotubes (MWNTs) and unmodified MWNTs loaded with a poorly water-soluble drug, intended to improve the drug loading capacity, dissolubility and study the drug-loading mechanism. MWNTs were modified with a carboxyl group through the acid treatment. MWNTs as well as the resulting functionalized MWNTs were investigated as scaffold for loading the model drug, Carvedilol (CAR), using three different methods (the fusion method, the incipient wetness impregnation method, and the solvent method). The effects of different pore size, specific surface area and physical state were systematically studied using scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transformation infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), nitrogen adsorption, X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). The functional MWNTs allowed a higher drug loading than the unmodified preparations. The methods used to load the drug had a marked effect on the drug-loading, dissolution, and physical state of the drug as well as its distribution. In addition, the solubility of the drug was increased when carried by both MWNTs and functional MWNTs, and this might help to improve the bioavailability.
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Statistical Agent Based Modelization of the Phenomenon of Drug Abuse
di Clemente, Riccardo; Pietronero, Luciano
2012-07-01
We introduce a statistical agent based model to describe the phenomenon of drug abuse and its dynamical evolution at the individual and global level. The agents are heterogeneous with respect to their intrinsic inclination to drugs, to their budget attitude and social environment. The various levels of drug use were inspired by the professional description of the phenomenon and this permits a direct comparison with all available data. We show that certain elements have a great importance to start the use of drugs, for example the rare events in the personal experiences which permit to overcame the barrier of drug use occasionally. The analysis of how the system reacts to perturbations is very important to understand its key elements and it provides strategies for effective policy making. The present model represents the first step of a realistic description of this phenomenon and can be easily generalized in various directions.
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Directory of Open Access Journals (Sweden)
Preston M. Luong
2017-01-01
Full Text Available Endogenous endophthalmitis is a rare but feared infectious ocular complication of injection drug use (IDU. The recent opioid epidemic in the United States threatens to increase the incidence of this disease. We report the first case of endogenous endophthalmitis in the United States caused by the emerging fungal pathogen Rhodotorula in an injection drug user which led to no light perception vision (NLP. Worldwide experience with Rhodotorula endogenous endophthalmitis is limited, but existing cases suggest infection by this particular fungal genus has a grim prognosis.
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In vitro and in vivo models for testing arrhythmogenesis in drugs.
Carlsson, L
2006-01-01
The steadily increasing list of drugs associated with prolongation of the QT interval and torsades de pointes (TdP) constitute a medical problem of major concern. Hence, there is a need at an early stage to identify drug candidates with an inherent capacity to induce repolarization-related proarrhythmias, avoiding exposure of large populations to potentially harmful drugs. Furthermore, the availability of clinically relevant and predictive animal models should reduce the risk that effective and potentially life-saving drugs never reach the market. This review will discuss the pros and cons of some in vivo and in vitro animal models for assessing proarrhythmia liability.
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Modeling HIV-1 drug resistance as episodic directional selection.
Murrell, Ben; de Oliveira, Tulio; Seebregts, Chris; Kosakovsky Pond, Sergei L; Scheffler, Konrad
2012-01-01
The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS) which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.
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Modeling HIV-1 drug resistance as episodic directional selection.
Directory of Open Access Journals (Sweden)
Ben Murrell
Full Text Available The evolution of substitutions conferring drug resistance to HIV-1 is both episodic, occurring when patients are on antiretroviral therapy, and strongly directional, with site-specific resistant residues increasing in frequency over time. While methods exist to detect episodic diversifying selection and continuous directional selection, no evolutionary model combining these two properties has been proposed. We present two models of episodic directional selection (MEDS and EDEPS which allow the a priori specification of lineages expected to have undergone directional selection. The models infer the sites and target residues that were likely subject to directional selection, using either codon or protein sequences. Compared to its null model of episodic diversifying selection, MEDS provides a superior fit to most sites known to be involved in drug resistance, and neither one test for episodic diversifying selection nor another for constant directional selection are able to detect as many true positives as MEDS and EDEPS while maintaining acceptable levels of false positives. This suggests that episodic directional selection is a better description of the process driving the evolution of drug resistance.
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Barker, David J; Simmons, Steven J; West, Mark O
2015-01-01
The present review describes ways in which ultrasonic vocalizations (USVs) have been used in studies of substance abuse. Accordingly, studies are reviewed which demonstrate roles for affective processing in response to the presentation of drug-related cues, experimenter- and self-administered drug, drug withdrawal, and during tests of relapse/reinstatement. The review focuses on data collected from studies using cocaine and amphetamine, where a large body of evidence has been collected. Data suggest that USVs capture animals' initial positive reactions to psychostimulant administration and are capable of identifying individual differences in affective responding. Moreover, USVs have been used to demonstrate that positive affect becomes sensitized to psychostimulants over acute exposure before eventually exhibiting signs of tolerance. In the drug-dependent animal, a mixture of USVs suggesting positive and negative affect is observed, illustrating mixed responses to psychostimulants. This mixture is predominantly characterized by an initial bout of positive affect followed by an opponent negative emotional state, mirroring affective responses observed in human addicts. During drug withdrawal, USVs demonstrate the presence of negative affective withdrawal symptoms. Finally, it has been shown that drug-paired cues produce a learned, positive anticipatory response during training, and that presentation of drug-paired cues following abstinence produces both positive affect and reinstatement behavior. Thus, USVs are a useful tool for obtaining an objective measurement of affective states in animal models of substance abuse and can increase the information extracted from drug administration studies. USVs enable detection of subtle differences in a behavioral response that might otherwise be missed using traditional measures.
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Wang, Bo; Studdert, David M; Sarpatwari, Ameet; Franklin, Jessica M; Landon, Joan; Kesselheim, Aaron S
2017-01-01
In the past decade, the federal government has frequently investigated and prosecuted pharmaceutical manufacturers for illegal promotion of drugs for indications not approved by the Food and Drug Administration (FDA) ("off-label" uses). State governments can choose to coordinate with the federal investigation, or pursue their own independent state investigations. One of the largest-ever off-label prosecutions relates to the atypical antipsychotic drug olanzapine (Zyprexa). In a series of settlements between 2008 and 2010, Eli Lilly paid $1.4 billion to the federal government and over $290 million to state governments. We examined the effect of these settlements on off-label prescribing of this medication, taking advantage of geographical differences in states' involvement in the investigations and the timing of the settlements. However, we did not find a reduction in off-label prescribing; rather, there were no prescribing changes among states that joined the federal investigation, those that pursued independent state investigations, and states that pursued no investigations at all. Since the settlements of state investigations of off-label prescribing do not appear to significantly impact prescribing rates, policymakers should consider alternate ways of reducing the prevalence of non-evidence-based off-label use to complement their ongoing investigations.
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Directory of Open Access Journals (Sweden)
R Pignatello
2011-01-01
Full Text Available Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy.
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Bayesian state space models for dynamic genetic network construction across multiple tissues.
Liang, Yulan; Kelemen, Arpad
2016-08-01
Construction of gene-gene interaction networks and potential pathways is a challenging and important problem in genomic research for complex diseases while estimating the dynamic changes of the temporal correlations and non-stationarity are the keys in this process. In this paper, we develop dynamic state space models with hierarchical Bayesian settings to tackle this challenge for inferring the dynamic profiles and genetic networks associated with disease treatments. We treat both the stochastic transition matrix and the observation matrix time-variant and include temporal correlation structures in the covariance matrix estimations in the multivariate Bayesian state space models. The unevenly spaced short time courses with unseen time points are treated as hidden state variables. Hierarchical Bayesian approaches with various prior and hyper-prior models with Monte Carlo Markov Chain and Gibbs sampling algorithms are used to estimate the model parameters and the hidden state variables. We apply the proposed Hierarchical Bayesian state space models to multiple tissues (liver, skeletal muscle, and kidney) Affymetrix time course data sets following corticosteroid (CS) drug administration. Both simulation and real data analysis results show that the genomic changes over time and gene-gene interaction in response to CS treatment can be well captured by the proposed models. The proposed dynamic Hierarchical Bayesian state space modeling approaches could be expanded and applied to other large scale genomic data, such as next generation sequence (NGS) combined with real time and time varying electronic health record (EHR) for more comprehensive and robust systematic and network based analysis in order to transform big biomedical data into predictions and diagnostics for precision medicine and personalized healthcare with better decision making and patient outcomes.
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Hossain, Shaolie S.
2011-08-20
The majority of heart attacks occur when there is a sudden rupture of atherosclerotic plaque, exposing prothrombotic emboli to coronary blood flow, forming clots that can cause blockages of the arterial lumen. Diseased arteries can be treated with drugs delivered locally to vulnerable plaques. The objective of this work was to develop a computational tool-set to support the design and analysis of a catheter-based nanoparticulate drug delivery system to treat vulnerable plaques and diffuse atherosclerosis. A threedimensional mathematical model of coupled mass transport of drug and drug-encapsulated nanoparticles was developed and solved numerically utilizing isogeometric finite element analysis. Simulations were run on a patient-specific multilayered coronary artery wall segment with a vulnerable plaque and the effect of artery and plaque inhomogeneity was analyzed. The method captured trends observed in local drug delivery and demonstrated potential for optimizing drug design parameters, including delivery location, nanoparticle surface properties, and drug release rate. © Springer-Verlag 2011.
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Sovereignty Under Siege: Drug Trafficking and State Capacity in the Caribbean and Central America
2016-06-01
million people consume illicit drugs (of the cannabis , opioid, cocaine, or amphetamine classifications), which corresponds to 3.5–7 percent of the world...prevalent.28 Last, failed states have flawed institutions, lack infrastructural capacity (potholes), have poor, privatized education and medical ...drug assaults.149 Colombian DTOs moved into the Caribbean like a cancerous growth, taking root, and then malignantly spreading to destabilize or
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Sharifi, N; Ozgoli, S; Ramezani, A
2017-06-01
Mixed immunotherapy and chemotherapy of tumours is one of the most efficient ways to improve cancer treatment strategies. However, it is important to 'design' an effective treatment programme which can optimize the ways of combining immunotherapy and chemotherapy to diminish their imminent side effects. Control engineering techniques could be used for this. The method of multiple model predictive controller (MMPC) is applied to the modified Stepanova model to induce the best combination of drugs scheduling under a better health criteria profile. The proposed MMPC is a feedback scheme that can perform global optimization for both tumour volume and immune competent cell density by performing multiple constraints. Although current studies usually assume that immunotherapy has no side effect, this paper presents a new method of mixed drug administration by employing MMPC, which implements several constraints for chemotherapy and immunotherapy by considering both drug toxicity and autoimmune. With designed controller we need maximum 57% and 28% of full dosage of drugs for chemotherapy and immunotherapy in some instances, respectively. Therefore, through the proposed controller less dosage of drugs are needed, which contribute to suitable results with a perceptible reduction in medicine side effects. It is observed that in the presence of MMPC, the amount of required drugs is minimized, while the tumour volume is reduced. The efficiency of the presented method has been illustrated through simulations, as the system from an initial condition in the malignant region of the state space (macroscopic tumour volume) transfers into the benign region (microscopic tumour volume) in which the immune system can control tumour growth. Copyright © 2017 Elsevier B.V. All rights reserved.
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Popilski, Hen; Stepensky, David
2015-05-01
Solid tumors are characterized by complex morphology. Numerous factors relating to the composition of the cells and tumor stroma, vascularization and drainage of fluids affect the local microenvironment within a specific location inside the tumor. As a result, the intratumoral drug/drug delivery system (DDS) disposition following systemic or local administration is non-homogeneous and its complexity reflects the differences in the local microenvironment. Mathematical models can be used to analyze the intratumoral drug/DDS disposition and pharmacological effects and to assist in choice of optimal anticancer treatment strategies. The mathematical models that have been applied by different research groups to describe the intratumoral disposition of anticancer drugs/DDSs are summarized in this article. The properties of these models and of their suitability for prediction of the drug/DDS intratumoral disposition and pharmacological effects are reviewed. Currently available mathematical models appear to neglect some of the major factors that govern the drug/DDS intratumoral disposition, and apparently possess limited prediction capabilities. More sophisticated and detailed mathematical models and their extensive validation are needed for reliable prediction of different treatment scenarios and for optimization of drug treatment in the individual cancer patients.
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Reliability of a Novel Model for Drug Release from 2D HPMC-Matrices
Directory of Open Access Journals (Sweden)
Rumiana Blagoeva
2010-04-01
Full Text Available A novel model of drug release from 2D-HPMC matrices is considered. Detailed mathematical description of matrix swelling and the effect of the initial drug loading are introduced. A numerical approach to solution of the posed nonlinear 2D problem is used on the basis of finite element domain approximation and time difference method. The reliability of the model is investigated in two steps: numerical evaluation of the water uptake parameters; evaluation of drug release parameters under available experimental data. The proposed numerical procedure for fitting the model is validated performing different numerical examples of drug release in two cases (with and without taking into account initial drug loading. The goodness of fit evaluated by the coefficient of determination is presented to be very good with few exceptions. The obtained results show better model fitting when accounting the effect of initial drug loading (especially for larger values.
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Modelling Illicit Drug Fate in Sewers for Wastewater-Based Epidemiology
DEFF Research Database (Denmark)
Ramin, Pedram
was found during festival period as compared to normal weekdays. Wastewater-based epidemiology is a truly interdisciplinary approach in which engineering tools, including models developed and tested in this thesis, can be beneficial for the accurate estimation of drug consumption in urban areas........ Sewer systems can be considered as biological reactors, in which the concentration of organic chemicals present in wastewater can be impacted by in-sewer processes during hydraulic residence time. Illicit drug biomarkers, as trace organic chemicals in the range of nanograms to micrograms per liter...... on sorption and transformation of drug biomarkers in raw wastewater and sewer biofilms; and (ii) developing modelling tools – by combining and extending existing modelling frameworks – to predict such processes. To achieve this goal, a substantial part of this thesis was dedicated to the experimental...
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Belackova, Vendula; Ritter, Alison; Shanahan, Marian; Hughes, Caitlin E
2017-03-01
Variations in drug laws, as well as variations in enforcement practice, exist across jurisdictions. This study explored the feasibility of categorising drug laws "on the books" in terms of their punitiveness, and the extent of their concordance with "laws in practice" in a cross-national comparison. "Law on the books", classified with respect to both cannabis and other drug offences in the Czech Republic, NSW (AU) and Florida (USA) were analysed in order to establish an ordinal relationship between the three states. Indicators to assess the "laws in practice" covered both police (arrests) and court (sentencing) activity between 2002 and 2013. Parametric and non-parametric tests of equality of means, tests of stationarity and correlation analysis were used to examine the concordance between the ordinal categorisation of "laws on the books" and "laws in practice", as well as trends over time. The Czech Republic had the most lenient drug laws; Florida had the most punitive and NSW was in-between. Examining the indicators of "laws in practice", we found that the population adjusted number of individuals sentenced to prison ranked across the three states was concordant with categorisation of "laws on the books", but the average sentence length and percentage of court cases sentenced to prison were not. Also, the de jure decriminalisation of drug possession in the Czech Republic yielded a far greater share of administrative offenses than the de facto decriminalisation of cannabis use / possession in NSW. Finally, the mean value of most "laws in practice" indicators changed significantly over time although the "laws on the books" didn't change. While some indicators of "laws in practice" were concordant with the ordinal categorisation of drug laws, several indicators of "laws in practice" appeared to operate independently from the drug laws as stated. This has significant implications for drug policy analysis and means that research should not assume they are
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From Product Models to Product State Models
DEFF Research Database (Denmark)
Larsen, Michael Holm
1999-01-01
A well-known technology designed to handle product data is Product Models. Product Models are in their current form not able to handle all types of product state information. Hence, the concept of a Product State Model (PSM) is proposed. The PSM and in particular how to model a PSM is the Research...
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The paradigm shift to an “open” model in drug development
Directory of Open Access Journals (Sweden)
Regina Au
2014-12-01
Full Text Available The rising cost of healthcare, the rising cost for drug development, the patent cliff for Big pharma, shorter patent protection, decrease reimbursement, and the recession have made it more difficult for the pharmaceutical and biotechnology industry to develop drugs. Due to the unsustainable amount of time and money in developing a drug that will have a significant return on investment (ROI it has become hard to sustain a robust pipeline. The industry is transforming its business model to meet these challenges. In essence a paradigm shift is occurring; the old “closed” model is giving way to a new “open” business model.
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Bowen, Elizabeth A.; Redmond, Helen
2016-01-01
The United States' War on Drugs encompasses a body of legislation characterized by punitive approaches to drug control. These policies have resulted in escalating incarceration rates and have extracted a particularly harsh toll on low-income people of color. This article argues that education on the War on Drugs is essential for effective practice…
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Canet, Mark J.; Hardwick, Rhiannon N.; Lake, April D.; Dzierlenga, Anika L.; Clarke, John D.; Cherrington, Nathan J.
2014-01-01
Nonalcoholic fatty liver disease is a prevalent form of chronic liver disease that can progress to the more advanced stage of nonalcoholic steatohepatitis (NASH). NASH has been shown to alter drug transporter regulation and may have implications in the development of adverse drug reactions. Several experimental rodent models have been proposed for the study of NASH, but no single model fully recapitulates all aspects of the human disease. The purpose of the current study was to determine whic...
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Lin, Wen; Ji, Tao; Einolf, Heidi; Ayalasomayajula, Surya; Lin, Tsu-Han; Hanna, Imad; Heimbach, Tycho; Breen, Christopher; Jarugula, Venkateswar; He, Handan
2017-05-01
Sacubitril/valsartan (LCZ696) has been approved for the treatment of heart failure. Sacubitril is an in vitro inhibitor of organic anion-transporting polypeptides (OATPs). In clinical studies, LCZ696 increased atorvastatin C max by 1.7-fold and area under the plasma concentration-time curve by 1.3-fold, but had little or no effect on simvastatin or simvastatin acid exposure. A physiologically based pharmacokinetics modeling approach was applied to explore the underlying mechanisms behind the statin-specific LCZ696 drug interaction observations. The model incorporated OATP-mediated clearance (CL int,T ) for simvastatin and simvastatin acid to successfully describe the pharmacokinetic profiles of either analyte in the absence or presence of LCZ696. Moreover, the model successfully described the clinically observed drug effect with atorvastatin. The simulations clarified the critical parameters responsible for the observation of a low, yet clinically relevant, drug-drug interaction DDI between sacubitril and atorvastatin and the lack of effect with simvastatin acid. Atorvastatin is administered in its active form and rapidly achieves C max that coincide with the low C max of sacubitril. In contrast, simvastatin requires a hydrolysis step to the acid form and therefore is not present at the site of interactions at sacubitril concentrations that are inhibitory. Similar models were used to evaluate the drug-drug interaction risk for additional OATP-transported statins which predicted to maximally result in a 1.5-fold exposure increase. Copyright © 2017. Published by Elsevier Inc.
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Phukan, Sanjib Kumar; Medhi, Gajendra Kumar; Mahanta, Jagadish; Adhikary, Rajatashuvra; Thongamba, Gay; Paranjape, Ramesh S; Akoijam, Brogen S
2017-07-03
Personal networks are significant social spaces to spread of HIV or other blood-borne infections among hard-to-reach population, viz., injecting drug users, female sex workers, etc. Sharing of infected needles or syringes among drug users is one of the major routes of HIV transmission in Manipur, a high HIV prevalence state in India. This study was carried out to describe the network characteristics and recruitment patterns of injecting drug users and to assess the association of personal network with injecting risky behaviors in Manipur. A total of 821 injecting drug users were recruited into the study using respondent-driven sampling (RDS) from Bishnupur and Churachandpur districts of Manipur; data on demographic characteristics, HIV risk behaviors, and network size were collected from them. Transition probability matrices and homophily indices were used to describe the network characteristics, and recruitment patterns of injecting drug users. Univariate and multivariate binary logistic regression models were performed to analyze the association between the personal networks and sharing of needles or syringes. The average network size was similar in both the districts. Recruitment analysis indicates injecting drug users were mostly engaged in mixed age group setting for injecting practice. Ever married and new injectors showed lack of in-group ties. Younger injecting drug users had mainly recruited older injecting drug users from their personal network. In logistic regression analysis, higher personal network was found to be significantly associated with increased likelihood of injecting risky behaviors. Because of mixed personal network of new injectors and higher network density associated with HIV exposure, older injecting drug users may act as a link for HIV transmission or other blood-borne infections to new injectors and also to their sexual partners. The information from this study may be useful to understanding the network pattern of injecting drug users
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State Space Modeling Using SAS
Directory of Open Access Journals (Sweden)
Rajesh Selukar
2011-05-01
Full Text Available This article provides a brief introduction to the state space modeling capabilities in SAS, a well-known statistical software system. SAS provides state space modeling in a few different settings. SAS/ETS, the econometric and time series analysis module of the SAS system, contains many procedures that use state space models to analyze univariate and multivariate time series data. In addition, SAS/IML, an interactive matrix language in the SAS system, provides Kalman filtering and smoothing routines for stationary and nonstationary state space models. SAS/IML also provides support for linear algebra and nonlinear function optimization, which makes it a convenient environment for general-purpose state space modeling.
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Modeling volatility using state space models.
Timmer, J; Weigend, A S
1997-08-01
In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).
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Cell and small animal models for phenotypic drug discovery
Directory of Open Access Journals (Sweden)
Szabo M
2017-06-01
Full Text Available Mihaly Szabo,1 Sara Svensson Akusjärvi,1 Ankur Saxena,1 Jianping Liu,2 Gayathri Chandrasekar,1 Satish S Kitambi1 1Department of Microbiology Tumor, and Cell Biology, 2Department of Biochemistry and Biophysics, Karolinska Institutet, Solna, Sweden Abstract: The phenotype-based drug discovery (PDD approach is re-emerging as an alternative platform for drug discovery. This review provides an overview of the various model systems and technical advances in imaging and image analyses that strengthen the PDD platform. In PDD screens, compounds of therapeutic value are identified based on the phenotypic perturbations produced irrespective of target(s or mechanism of action. In this article, examples of phenotypic changes that can be detected and quantified with relative ease in a cell-based setup are discussed. In addition, a higher order of PDD screening setup using small animal models is also explored. As PDD screens integrate physiology and multiple signaling mechanisms during the screening process, the identified hits have higher biomedical applicability. Taken together, this review highlights the advantages gained by adopting a PDD approach in drug discovery. Such a PDD platform can complement target-based systems that are currently in practice to accelerate drug discovery. Keywords: phenotype, screening, PDD, discovery, zebrafish, drug
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Kadakia, Ekta; Shah, Lipa; Amiji, Mansoor M
2017-07-01
Nanoemulsions have shown potential in delivering drug across epithelial and endothelial cell barriers, which express efflux transporters. However, their transport mechanisms are not entirely understood. Our goal was to investigate the cellular permeability of nanoemulsion-encapsulated drugs and apply mathematical modeling to elucidate transport mechanisms and sensitive nanoemulsion attributes. Transport studies were performed in Caco-2 cells, using fish oil nanoemulsions and a model substrate, rhodamine-123. Permeability data was modeled using a semi-mechanistic approach, capturing the following cellular processes: endocytotic uptake of the nanoemulsion, release of rhodamine-123 from the nanoemulsion, efflux and passive permeability of rhodamine-123 in aqueous solution. Nanoemulsions not only improved the permeability of rhodamine-123, but were also less sensitive to efflux transporters. The model captured bidirectional permeability results and identified sensitive processes, such as the release of the nanoemulsion-encapsulated drug and cellular uptake of the nanoemulsion. Mathematical description of cellular processes, improved our understanding of transport mechanisms, such as nanoemulsions don't inhibit efflux to improve drug permeability. Instead, their endocytotic uptake, results in higher intracellular drug concentrations, thereby increasing the concentration gradient and transcellular permeability across biological barriers. Modeling results indicated optimizing nanoemulsion attributes like the droplet size and intracellular drug release rate, may further improve drug permeability.
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Modeling of transdermal drug delivery with a microneedle array
Lv, Y.-G.; Liu, J.; Gao, Y.-H.; Xu, B.
2006-11-01
Transdermal drug delivery is generally limited by the extraordinary barrier properties of the stratum corneum, the outer 10-15 µm layer of skin. A conventional needle inserted across this barrier and into deeper tissues could effectively deliver drugs. However, it would lead to infection and cause pain, thereby reducing patient compliance. In order to administer a frequent injection of insulin and other therapeutic agents more efficiently, integrated arrays with very short microneedles were recently proposed as very good candidates for painless injection or extraction. A variety of microneedle designs have thus been made available by employing the fabrication tools of the microelectronics industry and using materials such as silicon, metals, polymers and glass with feature sizes ranging from sub-micron to nanometers. At the same time, experiments were also made to test the capability of the microneedles to inject drugs into tissues. However, due to the difficulty encountered in measurement, a detailed understanding of the spatial and transient drug delivery process still remains unclear up to now. To better grasp the mechanisms involved, quantitative theoretical models were developed in this paper to simultaneously characterize the flow and drug transport, and numerical solutions were performed to predict the kinetics of dispersed drugs injected into the skin from a microneedle array. Calculations indicated that increasing the initial injection velocity and accelerating the blood circulation in skin tissue with high porosity are helpful to enhance the transdermal drug delivery. This study provides the first quantitative simulation of fluid injection through a microneedle array and drug species transport inside the skin. The modeling strategy can also possibly be extended to deal with a wider range of clinical issues such as targeted nanoparticle delivery for therapeutics or molecular imaging.
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Deb, Partha; Trivedi, Pravin K; Zimmer, David M
2014-10-01
In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.
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Blundell, Cassidy; Yi, Yoon-Suk; Ma, Lin; Tess, Emily R; Farrell, Megan J; Georgescu, Andrei; Aleksunes, Lauren M; Huh, Dongeun
2018-01-01
The current lack of knowledge about the effect of maternally administered drugs on the developing fetus is a major public health concern worldwide. The first critical step toward predicting the safety of medications in pregnancy is to screen drug compounds for their ability to cross the placenta. However, this type of preclinical study has been hampered by the limited capacity of existing in vitro and ex vivo models to mimic physiological drug transport across the maternal-fetal interface in the human placenta. Here the proof-of-principle for utilizing a microengineered model of the human placental barrier to simulate and investigate drug transfer from the maternal to the fetal circulation is demonstrated. Using the gestational diabetes drug glyburide as a model compound, it is shown that the microphysiological system is capable of reconstituting efflux transporter-mediated active transport function of the human placental barrier to limit fetal exposure to maternally administered drugs. The data provide evidence that the placenta-on-a-chip may serve as a new screening platform to enable more accurate prediction of drug transport in the human placenta. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Functional State Modelling of Cultivation Processes: Dissolved Oxygen Limitation State
Directory of Open Access Journals (Sweden)
Olympia Roeva
2015-04-01
Full Text Available A new functional state, namely dissolved oxygen limitation state for both bacteria Escherichia coli and yeast Saccharomyces cerevisiae fed-batch cultivation processes is presented in this study. Functional state modelling approach is applied to cultivation processes in order to overcome the main disadvantages of using global process model, namely complex model structure and a big number of model parameters. Alongwith the newly introduced dissolved oxygen limitation state, second acetate production state and first acetate production state are recognized during the fed-batch cultivation of E. coli, while mixed oxidative state and first ethanol production state are recognized during the fed-batch cultivation of S. cerevisiae. For all mentioned above functional states both structural and parameter identification is here performed based on experimental data of E. coli and S. cerevisiae fed-batch cultivations.
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Data-driven prediction of adverse drug reactions induced by drug-drug interactions.
Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Kumar, Kamal; Yu, Xueping; Wallqvist, Anders; Reifman, Jaques
2017-06-08
The expanded use of multiple drugs has increased the occurrence of adverse drug reactions (ADRs) induced by drug-drug interactions (DDIs). However, such reactions are typically not observed in clinical drug-development studies because most of them focus on single-drug therapies. ADR reporting systems collect information on adverse health effects caused by both single drugs and DDIs. A major challenge is to unambiguously identify the effects caused by DDIs and to attribute them to specific drug interactions. A computational method that provides prospective predictions of potential DDI-induced ADRs will help to identify and mitigate these adverse health effects. We hypothesize that drug-protein interactions can be used as independent variables in predicting ADRs. We constructed drug pair-protein interaction profiles for ~800 drugs using drug-protein interaction information in the public domain. We then constructed statistical models to score drug pairs for their potential to induce ADRs based on drug pair-protein interaction profiles. We used extensive clinical database information to construct categorical prediction models for drug pairs that are likely to induce ADRs via synergistic DDIs and showed that model performance deteriorated only slightly, with a moderate amount of false positives and false negatives in the training samples, as evaluated by our cross-validation analysis. The cross validation calculations showed an average prediction accuracy of 89% across 1,096 ADR models that captured the deleterious effects of synergistic DDIs. Because the models rely on drug-protein interactions, we made predictions for pairwise combinations of 764 drugs that are currently on the market and for which drug-protein interaction information is available. These predictions are publicly accessible at http://avoid-db.bhsai.org . We used the predictive models to analyze broader aspects of DDI-induced ADRs, showing that ~10% of all combinations have the potential to induce ADRs
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Ye, Min; Nagar, Swati; Korzekwa, Ken
2015-01-01
Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057
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Directory of Open Access Journals (Sweden)
Millard M
2017-10-01
Full Text Available Marie Millard,1,2 Ilya Yakavets,1–3 Vladimir Zorin,3,4 Aigul Kulmukhamedova,1,2,5 Sophie Marchal,1,2 Lina Bezdetnaya1,2 1Centre de Recherche en Automatique de Nancy, Centre National de la Recherche Scientifique UMR 7039, Université de Lorraine, 2Research Department, Institut de Cancérologie de Lorraine, Vandœuvre-lès-Nancy, France; 3Laboratory of Biophysics and Biotechnology, 4International Sakharov Environmental Institute, Belarusian State University, Minsk, Belarus; 5Department of Radiology, Medical Company Sunkar, Almaty, Kazakhstan Abstract: The increasing number of publications on the subject shows that nanomedicine is an attractive field for investigations aiming to considerably improve anticancer chemotherapy. Based on selective tumor targeting while sparing healthy tissue, carrier-mediated drug delivery has been expected to provide significant benefits to patients. However, despite reduced systemic toxicity, most nanodrugs approved for clinical use have been less effective than previously anticipated. The gap between experimental results and clinical outcomes demonstrates the necessity to perform comprehensive drug screening by using powerful preclinical models. In this context, in vitro three-dimensional models can provide key information on drug behavior inside the tumor tissue. The multicellular tumor spheroid (MCTS model closely mimics a small avascular tumor with the presence of proliferative cells surrounding quiescent cells and a necrotic core. Oxygen, pH and nutrient gradients are similar to those of solid tumor. Furthermore, extracellular matrix (ECM components and stromal cells can be embedded in the most sophisticated spheroid design. All these elements together with the physicochemical properties of nanoparticles (NPs play a key role in drug transport, and therefore, the MCTS model is appropriate to assess the ability of NP to penetrate the tumor tissue. This review presents recent developments in MCTS models for a
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Calvo, Natalia L; Arias, Juan M; Altabef, Aída Ben; Maggio, Rubén M; Kaufman, Teodoro S
2016-09-10
Albendazole (ALB) is a broad-spectrum anthelmintic, which exhibits two solid-state forms (Forms I and II). The Form I is the metastable crystal at room temperature, while Form II is the stable one. Because the drug has poor aqueous solubility and Form II is less soluble than Form I, it is desirable to have a method to assess the solid-state form of the drug employed for manufacturing purposes. Therefore, a Partial Least Squares (PLS) model was developed for the determination of Form I of ALB in its mixtures with Form II. For model development, both solid-state forms of ALB were prepared and characterized by microscopic (optical and with normal and polarized light), thermal (DSC) and spectroscopic (ATR-FTIR, Raman) techniques. Mixtures of solids in different ratios were prepared by weighing and mechanical mixing of the components. Their Raman spectra were acquired, and subjected to peak smoothing, normalization, standard normal variate correction and de-trending, before performing the PLS calculations. The optimal spectral region (1396-1280cm(-1)) and number of latent variables (LV=3) were obtained employing a moving window of variable size strategy. The method was internally validated by means of the leave one out procedure, providing satisfactory statistics (r(2)=0.9729 and RMSD=5.6%) and figures of merit (LOD=9.4% and MDDC=1.4). Furthermore, the method's performance was also evaluated by analysis of two validation sets. Validation set I was used for assessment of linearity and range and Validation set II, to demonstrate accuracy and precision (Recovery=101.4% and RSD=2.8%). Additionally, a third set of spiked commercial samples was evaluated, exhibiting excellent recoveries (94.2±6.4%). The results suggest that the combination of Raman spectroscopy with multivariate analysis could be applied to the assessment of the main crystal form and its quantitation in samples of ALB bulk drug, in the routine quality control laboratory. Copyright © 2016 Elsevier B.V. All
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Modeling and implementing a database on drugs into a hospital intranet.
François, M; Joubert, M; Fieschi, D; Fieschi, M
1998-09-01
Our objective was to develop a drug information service, implementing a database on drugs in our university hospitals information system. Thériaque is a database, maintained by a group of pharmacists and physicians, on all the drugs available in France. Before its implementation we modeled its content (chemical classes, active components, excipients, indications, contra-indications, side effects, and so on) according to an object-oriented method. Then we designed HTML pages whose appearance translates the structure of classes of objects of the model. Fields in pages are dynamically fulfilled by the results of queries to a relational database in which information on drugs is stored. This allowed a fast implementation and did not imply to port a client application on the thousands of workstations over the network. The interface provides end-users with an easy-to-use and natural way to access information related to drugs in an internet environment.
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Firm- and drug-specific patterns of generic drug payments by US medicaid programs: 1991-2008.
Kelton, Christina M L; Chang, Lenisa V; Guo, Jeff J; Yu, Yan; Berry, Edmund A; Bian, Boyang; Heaton, Pamela C
2014-04-01
The entry of generic drugs into markets previously monopolized by patented, branded drugs often represents large potential savings for healthcare payers in the USA. Our objectives were to describe and explain the trends in drug reimbursement by public Medicaid programmes post-generic entry for as many drug markets and for as long a time period as possible. The data were the Medicaid State Drug Utilization Data maintained by the Centers for Medicare and Medicaid Services. Quarterly utilization and expenditure data from 1991 to 2008 were extracted for 83 drugs, produced by 229 firms, that experienced initial generic entry between 1992 and 2004. A relative 'price' for a specific drug, firm and quarter was constructed as Medicaid reimbursement per unit (e.g. tablet, capsule or vial) divided by average reimbursement per unit for the branded drug the year before entry. Fixed-effects models controlling for time-, firm- and drug-specific differences were estimated to explain reimbursement. Twelve quarters after generic entry, 18 % of drugs had average per-unit reimbursement less than 50 % of the original branded-drug reimbursement. For each additional firm manufacturing the drug, reimbursement per unit, relative to the pre-generic-entry branded-drug reimbursement, was estimated to fall by 17 (p < 0.01) and 3 (p < 0.01) percentage points for generic and branded-drug companies, respectively. Each additional quarter post-generic entry brought a 2 (p < 0.01) percentage point drop in relative reimbursement. State Medicaid programmes generally have been able to obtain relief from high drug prices following patent expirations for many branded-drug medications by adjusting reimbursement following the expanded competition in the pharmaceutical market.
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Pomey, Marie-Pascale; Forest, Pierre-Gerlier; Palley, Howard A; Martin, Elisabeth
2007-09-01
In January 1997, the government of Quebec, Canada, implemented a public/private prescription drug program that covered the entire population of the province. Under this program, the public sector collaborates with private insurers to protect all Quebecers from the high cost of drugs. This article outlines the principal features and history of the Quebec plan and draws parallels between the factors that led to its emergence and those that led to the passage of the Medicare Prescription Drug, Improvement and Modernization Act (MMA) in the United States. It also discusses the challenges and similarities of both programs and analyzes Quebec's ten years of experience to identify adjustments that may help U.S. policymakers optimize the MMA.
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Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches
Directory of Open Access Journals (Sweden)
Sudin eBhattacharya
2012-12-01
Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.
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Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.
Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram
2017-02-01
In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.
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Latkin, Carl A; Edwards, Catie; Davey-Rothwell, Melissa A; Yang, Cui; Tobin, Karin E
2018-02-12
There has been a dramatic increase in drug overdose deaths in the United States. In the current study, the authors examined factors associated with witnessing a drug overdose. A sample of 450 substance users in Baltimore, Maryland, were recruited for a behavioral intervention and were administered a survey. Multinomial logistic regression models were used to compare participants who never witnessed a drug overdose with those who witnessed one in the prior 6 months and those who witnessed an overdose over 6 months ago. Most (58%) participants were male, 40% experienced homelessness in the prior 6 months, 63% reported a history of heroin injecting, 84% had snorted heroin, 75% reported witnessing a drug overdose, and 38% experienced an overdose. In multinomial logistic regression models, witnessing an overdose in the past 6 months was associated with number of different types of places where drugs were used (adjusted odds ratio [aOR] = 1.34), history of experiencing an overdose (aOR = 1.80), injecting heroin and/or speedball (aOR = 1.78), and snorting heroin (aOR = 1.54). Witnessing an overdose more than 6 months ago was associated with number of different places where drugs were used (aOR = 1.25), history of experiencing an overdose (aOR = 1.61), snorting heroin (aOR = 1.42), and injecting heroin or speedball (aOR = 1.47). These data suggest that people who engage in more public and frequent drug use, and hence are more likely to witness an overdose, should be targeted for interventions to prevent and treat drug overdose.
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Directory of Open Access Journals (Sweden)
Aleksander Mendyk
2015-01-01
Full Text Available The purpose of this work was to develop a mathematical model of the drug dissolution (Q from the solid lipid extrudates based on the empirical approach. Artificial neural networks (ANNs and genetic programming (GP tools were used. Sensitivity analysis of ANNs provided reduction of the original input vector. GP allowed creation of the mathematical equation in two major approaches: (1 direct modeling of Q versus extrudate diameter (d and the time variable (t and (2 indirect modeling through Weibull equation. ANNs provided also information about minimum achievable generalization error and the way to enhance the original dataset used for adjustment of the equations’ parameters. Two inputs were found important for the drug dissolution: d and t. The extrudates length (L was found not important. Both GP modeling approaches allowed creation of relatively simple equations with their predictive performance comparable to the ANNs (root mean squared error (RMSE from 2.19 to 2.33. The direct mode of GP modeling of Q versus d and t resulted in the most robust model. The idea of how to combine ANNs and GP in order to escape ANNs’ black-box drawback without losing their superior predictive performance was demonstrated. Open Source software was used to deliver the state-of-the-art models and modeling strategies.
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Lacey, John H.; Kelley-Baker, Tara; Voas, Robert B.; Romano, Eduardo; Furr-Holden, C. Debra; Torres, Pedro; Berning, Amy
2011-01-01
This article describes the methodology used in the 2007 U.S. National Roadside Survey to estimate the prevalence of alcohol- and drug-impaired driving and alcohol- and drug-involved driving. This study involved randomly stopping drivers at 300 locations across the 48 continental U.S. states at sites selected through a stratified random sampling…
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A Comparative Study of Successful Central Nervous System Drugs Using Molecular Modeling
Kim, Hyosub; Sulaimon, Segun; Menezes, Sandra; Son, Anne; Menezes, Warren J. C.
2011-01-01
Molecular modeling is a powerful tool used for three-dimensional visualization and for exploring electrostatic forces involved in drug transport. This tool enhances student understanding of structure-property relationships, as well as actively engaging them in class. Molecular modeling of several central nervous system (CNS) drugs is used to…
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Novel films for drug delivery via the buccal mucosa using model soluble and insoluble drugs.
Kianfar, Farnoosh; Chowdhry, Babur Z; Antonijevic, Milan D; Boateng, Joshua S
2012-10-01
Bioadhesive buccal films are innovative dosage forms with the ability to adhere to the mucosal surface and subsequently hydrate to release and deliver drugs across the buccal membrane. This study aims to formulate and characterize stable carrageenan (CAR) based buccal films with desirable drug loading capacity. The films were prepared using CAR, poloxamer (POL) 407, various grades of PEG (plasticizer) and loaded with paracetamol (PM) and indomethacin (IND) as model soluble and insoluble drugs, respectively. The films were characterized by texture analysis, thermogravimetric analysis (TGA), DSC, scanning electron microscopy, X-ray powder diffraction (XRPD), and in vitro drug release studies. Optimized films were obtained from aqueous gels comprising 2.5% w/w κ-CAR 911, 4% w/w POL 407 and 6% w/w (PM) and 6.5% w/w (IND) of PEG 600 with maximum drug loading of 1.6% w/w and 0.8 % w/w for PM and IND, respectively. TGA showed residual water content of approximately 5% of films dry weight. DSC revealed a T(g) at 22.25 and 30.77°C for PM and IND, respectively, implying the presence of amorphous forms of both drugs which was confirmed by XRPD. Drug dissolution profiles in simulated saliva showed cumulative percent release of up to 45 and 57% of PM and IND, respectively, within 40 min of contact with dissolution medium simulating saliva.
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THE MODELING OF DRUG ADDICTION PREVALENCE AND ITS CONSEQUENCES IN RUSSIAN REGIONS
Directory of Open Access Journals (Sweden)
V.P. Sirotin
2009-12-01
Full Text Available The narcotization prevalence in Russia as whole and its regions is described. In order to provide the adequate models the clusters of regions on the level of their economic development are defined. For every group the regression model of drug addiction social distress is constructed. Modeling results allow to find the features of regions and the most significant factors determining the drug addiction prevalence.
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Drug development costs when financial risk is measured using the Fama-French three-factor model.
Vernon, John A; Golec, Joseph H; Dimasi, Joseph A
2010-08-01
In a widely cited article, DiMasi, Hansen, and Grabowski (2003) estimate the average pre-tax cost of bringing a new molecular entity to market. Their base case estimate, excluding post-marketing studies, was $802 million (in $US 2000). Strikingly, almost half of this cost (or $399 million) is the cost of capital (COC) used to fund clinical development expenses to the point of FDA marketing approval. The authors used an 11% real COC computed using the capital asset pricing model (CAPM). But the CAPM is a single factor risk model, and multi-factor risk models are the current state of the art in finance. Using the Fama-French three factor model we find that the cost of drug development to be higher than the earlier estimate. Copyright (c) 2009 John Wiley & Sons, Ltd.
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Terry-McElrath, Yvonne M.; Emery, Sherry; Szczypka, Glen; Johnston, Lloyd D.
2010-01-01
Using nationally representative data from the Monitoring the Future Study on United States middle and high school students, we related exposure to anti-drug television advertising as measured by Nielsen Media Research ratings points to student self-reported drug-related outcomes from 1995-2006. Multivariate analyses controlling for key socio-demographics and accounting for the complex survey design included 337,918 cases. Results indicated that attitudes, beliefs, and behaviors regarding substance use were significantly related to such advertising exposure over the six months prior to the date youth were surveyed. However, the observed relationships varied by grade level, over time and by advertising tagline and marijuana focus. Findings differed markedly between middle and high school students across the study interval. One factor that may partially explain observed differences may be variation in the degree to which the ads focused on marijuana. Putting a concerted effort into increasing anti-drug advertising will likely increase the exposure to and recall of such ads among youth. However, the likelihood that such advertising will result in youth being less likely to use drugs seems to depend heavily on the type of advertising utilized and how it relates to different ages and characteristics of targeted youth. PMID:20961691
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A data-driven predictive approach for drug delivery using machine learning techniques.
Directory of Open Access Journals (Sweden)
Yuanyuan Li
Full Text Available In drug delivery, there is often a trade-off between effective killing of the pathogen, and harmful side effects associated with the treatment. Due to the difficulty in testing every dosing scenario experimentally, a computational approach will be helpful to assist with the prediction of effective drug delivery methods. In this paper, we have developed a data-driven predictive system, using machine learning techniques, to determine, in silico, the effectiveness of drug dosing. The system framework is scalable, autonomous, robust, and has the ability to predict the effectiveness of the current drug treatment and the subsequent drug-pathogen dynamics. The system consists of a dynamic model incorporating both the drug concentration and pathogen population into distinct states. These states are then analyzed using a temporal model to describe the drug-cell interactions over time. The dynamic drug-cell interactions are learned in an adaptive fashion and used to make sequential predictions on the effectiveness of the dosing strategy. Incorporated into the system is the ability to adjust the sensitivity and specificity of the learned models based on a threshold level determined by the operator for the specific application. As a proof-of-concept, the system was validated experimentally using the pathogen Giardia lamblia and the drug metronidazole in vitro.
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DEFF Research Database (Denmark)
Christophersen, Philip C; Vaghela, Dimple; Müllertz, Anette
2014-01-01
The effect of food intake on the release and degradation of peptide drugs from solid lipid particles is unknown and was therefore investigated in vitro using different fed state media in a lipolysis model. Desmopressin was used as a model peptide and incorporated into solid lipid particles...... and the protease or desmopressin. Addition of a medium chain triglyceride, trilaurin, in combination with drug-loaded lipid particles diminished the food effect on the TG18 particles, and trilaurin is therefore proposed to be a suitable excipient for reduction of the food effect. Overall, the present study shows...... that strategies to reduce food effect, such as adding trilaurin, for lipid particle formulations should be considered as drug release from such formulations might be influenced by the presence of food in the gastrointestinal tract....
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Li, Ming; de Graaf, Inge A M; Groothuis, Geny M M
2016-01-01
The absorption, distribution, metabolism, excretion and toxicity (ADME-tox) processes of drugs are of importance and require preclinical investigation intestine in addition to the liver. Various models have been developed for prediction of ADME-tox in the intestine. In this review, precision-cut intestinal slices (PCIS) are discussed and highlighted as model for ADME-tox studies. This review provides an overview of the applications and an update of the most recent research on PCIS as an ex vivo model to study the transport, metabolism and toxicology of drugs and other xenobiotics. The unique features of PCIS and the differences with other models as well as the translational aspects are also discussed. PCIS are a simple, fast, and reliable ex vivo model for drug ADME-tox research. Therefore, PCIS are expected to become an indispensable link in the in vitro-ex vivo-in vivo extrapolation, and a bridge in translation of animal data to the human situation. In the future, this model may be helpful to study the effects of interorgan interactions, intestinal bacteria, excipients and drug formulations on the ADME-tox properties of drugs. The optimization of culture medium and the development of a (cryo)preservation technique require more research.
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Zhou, Shu; Li, Guo-Bo; Huang, Lu-Yi; Xie, Huan-Zhang; Zhao, Ying-Lan; Chen, Yu-Zong; Li, Lin-Li; Yang, Sheng-Yong
2014-08-01
Drug-induced ototoxicity, as a toxic side effect, is an important issue needed to be considered in drug discovery. Nevertheless, current experimental methods used to evaluate drug-induced ototoxicity are often time-consuming and expensive, indicating that they are not suitable for a large-scale evaluation of drug-induced ototoxicity in the early stage of drug discovery. We thus, in this investigation, established an effective computational prediction model of drug-induced ototoxicity using an optimal support vector machine (SVM) method, GA-CG-SVM. Three GA-CG-SVM models were developed based on three training sets containing agents bearing different risk levels of drug-induced ototoxicity. For comparison, models based on naïve Bayesian (NB) and recursive partitioning (RP) methods were also used on the same training sets. Among all the prediction models, the GA-CG-SVM model II showed the best performance, which offered prediction accuracies of 85.33% and 83.05% for two independent test sets, respectively. Overall, the good performance of the GA-CG-SVM model II indicates that it could be used for the prediction of drug-induced ototoxicity in the early stage of drug discovery. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Drug and Vaccine evaluation in the Human Aotus Plasmodium falciparum Model
2011-05-01
and phenyl ring systems is anticipated to yield a valuable new antimalarial drug (33). The antimalarial activity and pharmacology of a series of...remains essentially unchanged since 1976, viz. to ascertain the antimalarial activity of drugs against P. falciparum and P. vivax in Aotus. The...Present data on the evaluation of potential antimalarial activity of drugs in the pre-clinical model of Aotus l. lemurinus (Panamanian night
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Martino, Piera Di; Magnoni, Federico; Peregrina, Dolores Vargas; Gigliobianco, Maria Rosa; Censi, Roberta; Malaj, Ledjan
2016-01-01
Drugs and excipients used for pharmaceutical applications generally exist in the solid (crystalline or amorphous) state, more rarely as liquid materials. In some cases, according to the physicochemical nature of the molecule, or as a consequence of specific technological processes, a compound may exist exclusively in the amorphous state. In other cases, as a consequence of specific treatments (freezing and spray drying, melting and co-melting, grinding and compression), the crystalline form may convert into a completely or partially amorphous form. An amorphous material shows physical and thermodynamic properties different from the corresponding crystalline form, with profound repercussions on its technological performance and biopharmaceutical properties. Several physicochemical techniques such as X-ray powder diffraction, thermal methods of analysis, spectroscopic techniques, gravimetric techniques, and inverse gas chromatography can be applied to characterize the amorphous form of a compound (drug or excipient), and to evaluate its thermodynamic stability. This review offers a survey of the technologies used to convert a crystalline solid into an amorphous form, and describes the most important techniques for characterizing the amorphous state of compounds of pharmaceutical interest.
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Gupta, Ravi; Dhruva, Sanket S; Fox, Erin R; Ross, Joseph S
2017-10-01
Hundreds of drug products are currently marketed in the United States without approval from the FDA. The 2006 Unapproved Drugs Initiative (UDI) requires manufacturers to remove these drug products from the market or obtain FDA approval by demonstrating evidence of safety and efficacy. Once the FDA acts against an unapproved drug, fewer manufacturers remain in the market, potentially enabling drug price increases and greater susceptibility to drug shortages. There is a need for systematic study of the UDI's effect on prices and shortages of all targeted drugs. To examine the clinical evidence for approval and association with prices and shortages of previously unapproved prescription drugs after being addressed by the UDI. Previously unapproved prescription drugs that faced UDI regulatory action or with at least 1 product that received FDA approval through manufacturers' voluntary compliance with the UDI between 2006 and 2015 were identified. The clinical evidence was categorized as either newly conducted clinical trials or use of previously published literature and/or bioequivalence studies to demonstrate safety and efficacy. We determined the change in average wholesale price, presence of shortage, and duration of shortage for each drug during the 2 years before and after UDI regulatory action or approval through voluntary compliance. Between 2006 and 2015, 34 previously unapproved prescription drugs were addressed by the UDI. Nearly 90% of those with a drug product that received FDA approval were supported by literature reviews or bioequivalence studies, not new clinical trial evidence. Among the 26 drugs with available pricing data, average wholesale price during the 2 years before and after voluntary approval or UDI action increased by a median of 37% (interquartile range [IQR] = 23%-204%; P Innovation; from the Blue Cross Blue Shield Association to better understand medical technology evidence generation; from the Centers for Medicare & Medicaid Services to
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Modelling of drug release from ensembles of aspirin microcapsules ...
African Journals Online (AJOL)
Purpose: In order to determine the drug release profile of an ensemble of aspirin crystals or microcapsules from its particle distribution a mathematical model that considered the individual release characteristics of the component single particles was developed. The model assumed that under sink conditions the release ...
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Animal models of pain and migraine in drug discovery
DEFF Research Database (Denmark)
Munro, Gordon; Jansen-Olesen, Inger; Olesen, Jes
2017-01-01
of the most commonly used models and methods employed within 'pain and migraine' drug development will be presented. Recent advances within these disciplines suggest that, with the addition of a few extra carefully chosen ancillary models and/or endpoints, the relative value in terms of resources used...
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Hepatocyte-based in vitro model for assessment of drug-induced cholestasis
Energy Technology Data Exchange (ETDEWEB)
Chatterjee, Sagnik, E-mail: Sagnik.Chatterjee@pharm.kuleuven.be [Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, O and N2, Herestraat 49 — bus 921, 3000 Leuven (Belgium); Richert, Lysiane, E-mail: l.richert@kaly-cell.com [KaLy-Cell, 20A rue du Général Leclerc, 67115 Plobsheim (France); Augustijns, Patrick, E-mail: Patrick.Augustijns@pharm.kuleuven.be [Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, O and N2, Herestraat 49 — bus 921, 3000 Leuven (Belgium); Annaert, Pieter, E-mail: Pieter.Annaert@pharm.kuleuven.be [Drug Delivery and Disposition, KU Leuven Department of Pharmaceutical and Pharmacological Sciences, O and N2, Herestraat 49 — bus 921, 3000 Leuven (Belgium)
2014-01-01
Early detection of drug-induced cholestasis remains a challenge during drug development. We have developed and validated a biorelevant sandwich-cultured hepatocytes- (SCH) based model that can identify compounds causing cholestasis by altering bile acid disposition. Human and rat SCH were exposed (24–48 h) to known cholestatic and/or hepatotoxic compounds, in the presence or in the absence of a concentrated mixture of bile acids (BAs). Urea assay was used to assess (compromised) hepatocyte functionality at the end of the incubations. The cholestatic potential of the compounds was expressed by calculating a drug-induced cholestasis index (DICI), reflecting the relative residual urea formation by hepatocytes co-incubated with BAs and test compound as compared to hepatocytes treated with test compound alone. Compounds with clinical reports of cholestasis, including cyclosporin A, troglitazone, chlorpromazine, bosentan, ticlopidine, ritonavir, and midecamycin showed enhanced toxicity in the presence of BAs (DICI ≤ 0.8) for at least one of the tested concentrations. In contrast, the in vitro toxicity of compounds causing hepatotoxicity by other mechanisms (including diclofenac, valproic acid, amiodarone and acetaminophen), remained unchanged in the presence of BAs. A safety margin (SM) for drug-induced cholestasis was calculated as the ratio of lowest in vitro concentration for which was DICI ≤ 0.8, to the reported mean peak therapeutic plasma concentration. SM values obtained in human SCH correlated well with reported % incidence of clinical drug-induced cholestasis, while no correlation was observed in rat SCH. This in vitro model enables early identification of drug candidates causing cholestasis by disturbed BA handling. - Highlights: • Novel in vitro assay to detect drug-induced cholestasis • Rat and human sandwich-cultured hepatocytes (SCH) as in vitro models • Cholestatic compounds sensitize SCH to toxic effects of accumulating bile acids • Drug
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Hepatocyte-based in vitro model for assessment of drug-induced cholestasis
International Nuclear Information System (INIS)
Chatterjee, Sagnik; Richert, Lysiane; Augustijns, Patrick; Annaert, Pieter
2014-01-01
Early detection of drug-induced cholestasis remains a challenge during drug development. We have developed and validated a biorelevant sandwich-cultured hepatocytes- (SCH) based model that can identify compounds causing cholestasis by altering bile acid disposition. Human and rat SCH were exposed (24–48 h) to known cholestatic and/or hepatotoxic compounds, in the presence or in the absence of a concentrated mixture of bile acids (BAs). Urea assay was used to assess (compromised) hepatocyte functionality at the end of the incubations. The cholestatic potential of the compounds was expressed by calculating a drug-induced cholestasis index (DICI), reflecting the relative residual urea formation by hepatocytes co-incubated with BAs and test compound as compared to hepatocytes treated with test compound alone. Compounds with clinical reports of cholestasis, including cyclosporin A, troglitazone, chlorpromazine, bosentan, ticlopidine, ritonavir, and midecamycin showed enhanced toxicity in the presence of BAs (DICI ≤ 0.8) for at least one of the tested concentrations. In contrast, the in vitro toxicity of compounds causing hepatotoxicity by other mechanisms (including diclofenac, valproic acid, amiodarone and acetaminophen), remained unchanged in the presence of BAs. A safety margin (SM) for drug-induced cholestasis was calculated as the ratio of lowest in vitro concentration for which was DICI ≤ 0.8, to the reported mean peak therapeutic plasma concentration. SM values obtained in human SCH correlated well with reported % incidence of clinical drug-induced cholestasis, while no correlation was observed in rat SCH. This in vitro model enables early identification of drug candidates causing cholestasis by disturbed BA handling. - Highlights: • Novel in vitro assay to detect drug-induced cholestasis • Rat and human sandwich-cultured hepatocytes (SCH) as in vitro models • Cholestatic compounds sensitize SCH to toxic effects of accumulating bile acids • Drug
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How modeling and simulation have enhanced decision making in new drug development.
Miller, Raymond; Ewy, Wayne; Corrigan, Brian W; Ouellet, Daniele; Hermann, David; Kowalski, Kenneth G; Lockwood, Peter; Koup, Jeffrey R; Donevan, Sean; El-Kattan, Ayman; Li, Cheryl S W; Werth, John L; Feltner, Douglas E; Lalonde, Richard L
2005-04-01
The idea of model-based drug development championed by Lewis Sheiner, in which pharmacostatistical models of drug efficacy and safety are developed from preclinical and available clinical data, offers a quantitative approach to improving drug development and development decision-making. Examples are presented that support this paradigm. The first example describes a preclinical model of behavioral activity to predict potency and time-course of response in humans and assess the potential for differentiation between compounds. This example illustrates how modeling procedures expounded by Lewis Sheiner provided the means to differentiate potency and the lag time between drug exposure and response and allow for rapid decision making and dose selection. The second example involves planning a Phase 2a dose-ranging and proof of concept trial in Alzheimer's disease (AD). The issue was how to proceed with the study and what criteria to use for a go/no go decision. The combined knowledge of AD disease progression, and preclinical and clinical information about the drug were used to simulate various clinical trial scenarios to identify an efficient and effective Phase 2 study. A design was selected and carried out resulting in a number of important learning experiences as well as extensive financial savings. The motivation for this case in point was the "Learn-Confirm" paradigm described by Lewis Sheiner. The final example describes the use of Pharmacokinetic and Pharmacodynamic (PK/PD) modeling and simulation to confirm efficacy across doses. In the New Drug Application for gabapentin, data from two adequate and well-controlled clinical trials was submitted to the Food and Drug Administration (FDA) in support of the approval of the indication for the treatment of post-herpetic neuralgia. The clinical trial data was not replicated for each of the sought dose levels in the drug application presenting a regulatory dilemma. Exposure response analysis submitted in the New Drug
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Bioengineered Liver Models for Drug Testing and Cell Differentiation Studies
Directory of Open Access Journals (Sweden)
Gregory H. Underhill
2018-01-01
Full Text Available In vitro models of the human liver are important for the following: (1 mitigating the risk of drug-induced liver injury to human beings, (2 modeling human liver diseases, (3 elucidating the role of single and combinatorial microenvironmental cues on liver cell function, and (4 enabling cell-based therapies in the clinic. Methods to isolate and culture primary human hepatocytes (PHHs, the gold standard for building human liver models, were developed several decades ago; however, PHHs show a precipitous decline in phenotypic functions in 2-dimensional extracellular matrix–coated conventional culture formats, which does not allow chronic treatment with drugs and other stimuli. The development of several engineering tools, such as cellular microarrays, protein micropatterning, microfluidics, biomaterial scaffolds, and bioprinting, now allow precise control over the cellular microenvironment for enhancing the function of both PHHs and induced pluripotent stem cell–derived human hepatocyte-like cells; long-term (4+ weeks stabilization of hepatocellular function typically requires co-cultivation with liver-derived or non–liver-derived nonparenchymal cell types. In addition, the recent development of liver organoid culture systems can provide a strategy for the enhanced expansion of therapeutically relevant cell types. Here, we discuss advances in engineering approaches for constructing in vitro human liver models that have utility in drug screening and for determining microenvironmental determinants of liver cell differentiation/function. Design features and validation data of representative models are presented to highlight major trends followed by the discussion of pending issues that need to be addressed. Overall, bioengineered liver models have significantly advanced our understanding of liver function and injury, which will prove useful for drug development and ultimately cell-based therapies.
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Sovereignty under siege: drug trafficking and state capacity in the Caribbean and Central America
King, Ryan Thomas
2016-01-01
Approved for public release; distribution is unlimited Drug trafficking organizations have increased their prominence throughout the Caribbean and Central America. These organizations undermine the rule of law, increase levels of violence and corruption, and hamper development, all of which can weaken a state. Weak or failing states become domestic and regional burdens that spill over into neighboring countries and cause secondary and tertiary problems. This thesis examines causes for diff...
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[Modeling asthma evolution by a multi-state model].
Boudemaghe, T; Daurès, J P
2000-06-01
There are many scores for the evaluation of asthma. However, most do not take into account the evolutionary aspects of this illness. We propose a model for the clinical course of asthma by a homogeneous Markov model process based on data provided by the A.R.I.A. (Association de Recherche en Intelligence Artificielle dans le cadre de l'asthme et des maladies respiratoires). The criterion used is the activity of the illness during the month before consultation. The activity is divided into three levels: light (state 1), mild (state 2) and severe (state 3). The model allows the evaluation of the strength of transition between states. We found that strong intensities were implicated towards state 2 (lambda(12) and lambda(32)), less towards state 1 (lambda(21) and lambda(31)), and minimum towards state 3 (lambda(23)). This results in an equilibrium distribution essentially divided between state 1 and 2 (44.6% and 51.0% respectively) with a small proportion in state 3 (4.4%). In the future, the increasing amount of available data should permit the introduction of covariables, the distinction of subgroups and the implementation of clinical studies. The interest of this model falls within the domain of the quantification of the illness as well as the representation allowed thereof, while offering a formal framework for the clinical notion of time and evolution.
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Systematic synergy modeling: understanding drug synergy from a systems biology perspective.
Chen, Di; Liu, Xi; Yang, Yiping; Yang, Hongjun; Lu, Peng
2015-09-16
Owing to drug synergy effects, drug combinations have become a new trend in combating complex diseases like cancer, HIV and cardiovascular diseases. However, conventional synergy quantification methods often depend on experimental dose-response data which are quite resource-demanding. In addition, these methods are unable to interpret the explicit synergy mechanism. In this review, we give representative examples of how systems biology modeling offers strategies toward better understanding of drug synergy, including the protein-protein interaction (PPI) network-based methods, pathway dynamic simulations, synergy network motif recognitions, integrative drug feature calculations, and "omic"-supported analyses. Although partially successful in drug synergy exploration and interpretation, more efforts should be put on a holistic understanding of drug-disease interactions, considering integrative pharmacology and toxicology factors. With a comprehensive and deep insight into the mechanism of drug synergy, systems biology opens a novel avenue for rational design of effective drug combinations.
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Qi, Z; Kikuchi, S; Tretter, F; Voit, E O
2011-05-01
Major depressive disorder (MDD) affects about 16% of the general population and is a leading cause of death in the United States and around the world. Aggravating the situation is the fact that "drug use disorders" are highly comorbid in MDD patients, and VICE VERSA. Drug use and MDD share a common component, the dopamine system, which is critical in many motivation and reward processes, as well as in the regulation of stress responses in MDD. A potentiating mechanism in drug use disorders appears to be synaptic plasticity, which is regulated by dopamine transmission. In this article, we describe a computational model of the synaptic plasticity of GABAergic medium spiny neurons in the nucleus accumbens, which is critical in the reward system. The model accounts for effects of both dopamine and glutamate transmission. Model simulations show that GABAergic medium spiny neurons tend to respond to dopamine stimuli with synaptic potentiation and to glutamate signals with synaptic depression. Concurrent dopamine and glutamate signals cause various types of synaptic plasticity, depending on input scenarios. Interestingly, the model shows that a single 0.5 mg/kg dose of amphetamine can cause synaptic potentiation for over 2 h, a phenomenon that makes synaptic plasticity of medium spiny neurons behave quasi as a bistable system. The model also identifies mechanisms that could potentially be critical to correcting modifications of synaptic plasticity caused by drugs in MDD patients. An example is the feedback loop between protein kinase A, phosphodiesterase, and the second messenger cAMP in the postsynapse. Since reward mechanisms activated by psychostimulants could be crucial in establishing addiction comorbidity in patients with MDD, this model might become an aid for identifying and targeting specific modules within the reward system and lead to a better understanding and potential treatment of comorbid drug use disorders in MDD. © Georg Thieme Verlag KG Stuttgart · New
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Challenges in modelling nanoparticles for drug delivery
International Nuclear Information System (INIS)
Barnard, Amanda S
2016-01-01
Although there have been significant advances in the fields of theoretical condensed matter and computational physics, when confronted with the complexity and diversity of nanoparticles available in conventional laboratories a number of modeling challenges remain. These challenges are generally shared among application domains, but the impacts of the limitations and approximations we make to overcome them (or circumvent them) can be more significant one area than another. In the case of nanoparticles for drug delivery applications some immediate challenges include the incompatibility of length-scales, our ability to model weak interactions and solvation, the complexity of the thermochemical environment surrounding the nanoparticles, and the role of polydispersivity in determining properties and performance. Some of these challenges can be met with existing technologies, others with emerging technologies including the data-driven sciences; some others require new methods to be developed. In this article we will briefly review some simple methods and techniques that can be applied to these (and other) challenges, and demonstrate some results using nanodiamond-based drug delivery platforms as an exemplar. (topical review)
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Drug policy in United States of America
Stahl, Edmundo G.; Médico internista, President and Chief Executive Officer, LatAmScience. Florida, USA.
2009-01-01
The USA federal prescription drug policies are inconsistent. The federal government regulates the development, production, marketing and safety of prescription drugs in the country through various legal mechanisms as well as private and governmental institutions. Patent laws also play an important role in this process protecting the pharmaceutical industry. The government has no direct mechanism to control prices of prescription drugs nor does it have a policy to cover the whole US popula...
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Baird, Jared A; Taylor, Lynne S
2011-06-01
The purpose of this study was to gain a better understanding of which factors contribute to the eutectic composition of drug-polyethylene glycol (PEG) blends and to compare experimental values with predictions from the semi-empirical model developed by Lacoulonche et al. Eutectic compositions of various drug-PEG 3350 solid dispersions were predicted, assuming athermal mixing, and compared to experimentally determined eutectic points. The presence or absence of specific interactions between the drug and PEG 3350 were investigated using Fourier transform infrared (FT-IR) spectroscopy. The eutectic composition for haloperidol-PEG and loratadine-PEG solid dispersions was accurately predicted using the model, while predictions for aceclofenac-PEG and chlorpropamide-PEG were very different from those experimentally observed. Deviations in the model prediction from ideal behavior for the systems evaluated were confirmed to be due to the presence of specific interactions between the drug and polymer, as demonstrated by IR spectroscopy. Detailed analysis showed that the eutectic composition prediction from the model is interdependent on the crystal lattice energy of the drug compound (evaluated from the melting temperature and the heat of fusion) as well as the nature of the drug-polymer interactions. In conclusion, for compounds with melting points less than 200°C, the model is ideally suited for predicting the eutectic composition of systems where there is an absence of drug-polymer interactions.
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Oláh, Julianna; Mulholland, Adrian J.; Harvey, Jeremy N.
2011-01-01
Cytochrome P450 enzymes play key roles in the metabolism of the majority of drugs. Improved models for prediction of likely metabolites will contribute to drug development. In this work, two possible metabolic routes (aromatic carbon oxidation and O-demethylation) of dextromethorphan are compared using molecular dynamics (MD) simulations and density functional theory (DFT). The DFT results on a small active site model suggest that both reactions might occur competitively. Docking and MD studies of dextromethorphan in the active site of P450 2D6 show that the dextromethorphan is located close to heme oxygen in a geometry apparently consistent with competitive metabolism. In contrast, calculations of the reaction path in a large protein model [using a hybrid quantum mechanical–molecular mechanics (QM/MM) method] show a very strong preference for O-demethylation, in accordance with experimental results. The aromatic carbon oxidation reaction is predicted to have a high activation energy, due to the active site preventing formation of a favorable transition-state structure. Hence, the QM/MM calculations demonstrate a crucial role of many active site residues in determining reactivity of dextromethorphan in P450 2D6. Beyond substrate binding orientation and reactivity of Compound I, successful metabolite predictions must take into account the detailed mechanism of oxidation in the protein. These results demonstrate the potential of QM/MM methods to investigate specificity in drug metabolism. PMID:21444768
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Sjögren, Erik; Thörn, Helena; Tannergren, Christer
2016-06-06
Gastrointestinal (GI) drug absorption is a complex process determined by formulation, physicochemical and biopharmaceutical factors, and GI physiology. Physiologically based in silico absorption models have emerged as a widely used and promising supplement to traditional in vitro assays and preclinical in vivo studies. However, there remains a lack of comparative studies between different models. The aim of this study was to explore the strengths and limitations of the in silico absorption models Simcyp 13.1, GastroPlus 8.0, and GI-Sim 4.1, with respect to their performance in predicting human intestinal drug absorption. This was achieved by adopting an a priori modeling approach and using well-defined input data for 12 drugs associated with incomplete GI absorption and related challenges in predicting the extent of absorption. This approach better mimics the real situation during formulation development where predictive in silico models would be beneficial. Plasma concentration-time profiles for 44 oral drug administrations were calculated by convolution of model-predicted absorption-time profiles and reported pharmacokinetic parameters. Model performance was evaluated by comparing the predicted plasma concentration-time profiles, Cmax, tmax, and exposure (AUC) with observations from clinical studies. The overall prediction accuracies for AUC, given as the absolute average fold error (AAFE) values, were 2.2, 1.6, and 1.3 for Simcyp, GastroPlus, and GI-Sim, respectively. The corresponding AAFE values for Cmax were 2.2, 1.6, and 1.3, respectively, and those for tmax were 1.7, 1.5, and 1.4, respectively. Simcyp was associated with underprediction of AUC and Cmax; the accuracy decreased with decreasing predicted fabs. A tendency for underprediction was also observed for GastroPlus, but there was no correlation with predicted fabs. There were no obvious trends for over- or underprediction for GI-Sim. The models performed similarly in capturing dependencies on dose and
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Hobbs, Michael J; Bloomer, Jackie; Dear, Gordon
2017-08-01
1. In a clinical trial, a strong drug-drug interaction (DDI) was observed between dextromethorphan (DM, the object or victim drug) and GSK1034702 (the precipitant or perpetrator drug), following single and repeat doses. This study determined the inhibition parameters of GSK1034702 in vitro and applied PBPK modelling approaches to simulate the clinical observations and provide mechanistic hypotheses to understand the DDI. 2. In vitro assays were conducted to determine the inhibition parameters of human CYP2D6 by GSK1034702. PBPK models were populated with the in vitro parameters and DDI simulations conducted and compared to the observed data from a clinical study with DM and GSK1034702. 3. GSK1034702 was a potent direct and metabolism-dependent inhibitor of human CYP2D6, with inhibition parameters of: IC 50 = 1.6 μM, K inact = 3.7 h -1 and K I = 0.8 μM. Incorporating these data into PBPK models predicted a DDI after repeat, but not single, 5 mg doses of GSK1034702. 4. The DDI observed with repeat administration of GSK1034702 (5 mg) can be attributed to metabolism-dependent inhibition of CYP2D6. Further, in vitro data were generated and several potential mechanisms proposed to explain the interaction observed following a single dose of GSK1034702.
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Bertoni, Neilane; Bastos, Francisco I; Mello, Maeve Brito de; Makuch, Maria Yolanda; Sousa, Maria Helena de; Osis, Maria José; Faúndes, Anibal
2009-06-01
This article summarizes the findings of a survey including 5,981 students from public schools in Minas Gerais State, Brazil. The analysis assessed the influence of drug use on sexual practices. Among the boys engaged in relationships with casual partners who stated having used illicit drugs, 55.7% reported consistent condom use, as compared to 65.4% among those not reporting such habits. Among boys engaged in relationships with stable partners who reported illicit drug use, consistent condom use was reported by 42.7%, versus 64.1% among those not reporting such habits. In the subgroup of boys engaged in stable relationships who did not report illicit drug use, consistent condom use was less frequent among those that used alcohol/cigarettes, compared to those who did not drink or smoke (60.7% vs. 71.1%). Girls were less likely than boys to use condoms consistently, regardless of the nature of their relationships, without a noticeable influence of drug use. Policies to prevent drug abuse, sexually transmitted diseases, and unplanned pregnancy should be fully integrated.
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Zhou, Hui-yun; Chen, Xi-guang
2008-12-01
In this study, chitosan/cellulose acetate microspheres (CCAM) were prepared by W/O/W emulsification and solvent evaporation as a drug delivery system. The microspheres were spherical, free-flowing and non-aggregated. The CCAM had good flow and suspension ability. The loading efficiency of different model drugs increased with the increasing hydrophobicity of the drug. The loading efficiency of 6-mercaptopurine (6-MP) was more than 30% whereas that of ranitidine hydrochloride (RT) or acetaminophen (ACP) was only 10%. The pH values of solution affected the swelling ability of CCAM and the relative humidity had little effect on the characteristics of CCAM when it was not more than 75%. The CCAM system had a good effect on the controlled release of different model drugs. However, the release rate became slower with the increase of the hydrophobicity of drugs. The release rate of CCAM loaded with hydrophilic RT was almost 60% during 48 h and the release rate of CCAM loaded with hydrophobic drug of 6-MP was not more than 30%. In the meantime, the CCAM system was degradable in vitro and the degradation rate was faster in lysozyme solution than that in the medium of PBS. So the CCAM system was a degradable promising drug delivery system especially for hydrophobic drugs.
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Drugs as instruments: a new framework for non-addictive psychoactive drug use.
Müller, Christian P; Schumann, Gunter
2011-12-01
Most people who are regular consumers of psychoactive drugs are not drug addicts, nor will they ever become addicts. In neurobiological theories, non-addictive drug consumption is acknowledged only as a "necessary" prerequisite for addiction, but not as a stable and widespread behavior in its own right. This target article proposes a new neurobiological framework theory for non-addictive psychoactive drug consumption, introducing the concept of "drug instrumentalization." Psychoactive drugs are consumed for their effects on mental states. Humans are able to learn that mental states can be changed on purpose by drugs, in order to facilitate other, non-drug-related behaviors. We discuss specific "instrumentalization goals" and outline neurobiological mechanisms of how major classes of psychoactive drugs change mental states and serve non-drug-related behaviors. We argue that drug instrumentalization behavior may provide a functional adaptation to modern environments based on a historical selection for learning mechanisms that allow the dynamic modification of consummatory behavior. It is assumed that in order to effectively instrumentalize psychoactive drugs, the establishment of and retrieval from a drug memory is required. Here, we propose a new classification of different drug memory subtypes and discuss how they interact during drug instrumentalization learning and retrieval. Understanding the everyday utility and the learning mechanisms of non-addictive psychotropic drug use may help to prevent abuse and the transition to drug addiction in the future.
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Illicit drug use and abuse/dependence: modeling of two-stage variables using the CCC approach.
Agrawal, A; Neale, M C; Jacobson, K C; Prescott, C A; Kendler, K S
2005-06-01
Drug use and abuse/dependence are stages of a complex drug habit. Most genetically informative models that are fit to twin data examine drug use and abuse/dependence independent of each other. This poses an interesting question: for a multistage process, how can we partition the factors influencing each stage specifically from the factors that are common to both stages? We used a causal-common-contingent (CCC) model to partition the common and specific influences on drug use and abuse/dependence. Data on use and abuse/dependence of cannabis, cocaine, sedatives, stimulants and any illicit drug was obtained from male and female twin pairs. CCC models were tested individually for each sex and in a sex-equal model. Our results suggest that there is evidence for additive genetic, shared environmental and unique environmental influences that are common to illicit drug use and abuse/dependence. Furthermore, we found substantial evidence for factors that were specific to abuse/dependence. Finally, sexes could be equated for all illicit drugs. The findings of this study emphasize the need for models that can partition the sources of individual differences into common and stage-specific influences.
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Ye, Min; Nagar, Swati; Korzekwa, Ken
2016-04-01
Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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Morgen, Michael; Bloom, Corey; Beyerinck, Ron; Bello, Akintunde; Song, Wei; Wilkinson, Karen; Steenwyk, Rick; Shamblin, Sheri
2012-02-01
To demonstrate drug/polymer nanoparticles can increase the rate and extent of oral absorption of a low-solubility, high-permeability drug. Amorphous drug/polymer nanoparticles containing celecoxib were prepared using ethyl cellulose and either sodium caseinate or bile salt. Nanoparticles were characterized using dynamic light scattering, transmission and scanning electron microscopy, and differential scanning calorimetry. Drug release and resuspension studies were performed using high-performance liquid chromatography. Pharmacokinetic studies were performed in dogs and humans. A physical model is presented describing the nanoparticle state of matter and release performance. Nanoparticles dosed orally in aqueous suspensions provided higher systemic exposure and faster attainment of peak plasma concentrations than commercial capsules, with median time to maximum drug concentration (Tmax) of 0.75 h in humans for nanoparticles vs. 3 h for commercial capsules. Nanoparticles released celecoxib rapidly and provided higher dissolved-drug concentrations than micronized crystalline drug. Nanoparticle suspensions are stable for several days and can be spray-dried to form dry powders that resuspend in water. Drug/polymer nanoparticles are well suited for providing rapid oral absorption and increased bioavailability of BCS Class II drugs.
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Directory of Open Access Journals (Sweden)
Caridad Ivette Fernandez
2017-12-01
Full Text Available In 2016, 19.8% of the Cuban population was aged 60 or over. As a result, age-associated degenerative diseases and other diseases have become priority targets from a prophylactic, diagnostic and therapeutic perspective. As a result, the Cuban biomedical scientific community has addressed its basic, preclinical and epidemiological research in order to rise up to the challenge. A firm step in this direction has been the international congress “State of the art in non-clinical models for neurodegenerative diseases” which has brought together preclinical and clinical researchers, technicians and regulatory staff members from different countries to review the state of the art in neurodegenerations, find unifying ideas, objectives and collaborations or partnership. The objective is to expose the perspectives of new biotechnological products from Cuba and other countries from the diagnostic, therapeutic and neuroprotective point of view. It is crucial, therefore, that the irreplaceable role of laboratory animals in achieving these objectives is understood but they must be used in rational, adequate and ethical manner. We expose the current development trends in this field, being of common interest to the work directed to the search for potential drugs, diagnostic tools and the promotion of changes in lifestyle as a preventive projection.
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Some Remarks on Prediction of Drug-Target Interaction with Network Models.
Zhang, Shao-Wu; Yan, Xiao-Ying
2017-01-01
System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Thus, it is highly desired to develop computational methods for efficiently and effectively analyzing and detecting new drug-target interaction pairs. With the explosive growth of different types of omics data, such as genome, pharmacology, phenotypic, and other kinds of molecular networks, numerous computational approaches have been developed to predict Drug-Target Interactions (DTI). In this review, we make a survey on the recent advances in predicting drug-target interaction with network-based models from the following aspects: i) Available public data sources and benchmark datasets; ii) Drug/target similarity metrics; iii) Network construction; iv) Common network algorithms; v) Performance comparison of existing network-based DTI predictors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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Pearlstein, Robert A; McKay, Daniel J J; Hornak, Viktor; Dickson, Callum; Golosov, Andrei; Harrison, Tyler; Velez-Vega, Camilo; Duca, José
2017-01-01
Cellular drug targets exist within networked function-generating systems whose constituent molecular species undergo dynamic interdependent non-equilibrium state transitions in response to specific perturbations (i.e.. inputs). Cellular phenotypic behaviors are manifested through the integrated behaviors of such networks. However, in vitro data are frequently measured and/or interpreted with empirical equilibrium or steady state models (e.g. Hill, Michaelis-Menten, Briggs-Haldane) relevant to isolated target populations. We propose that cells act as analog computers, "solving" sets of coupled "molecular differential equations" (i.e. represented by populations of interacting species)via "integration" of the dynamic state probability distributions among those populations. Disconnects between biochemical and functional/phenotypic assays (cellular/in vivo) may arise with targetcontaining systems that operate far from equilibrium, and/or when coupled contributions (including target-cognate partner binding and drug pharmacokinetics) are neglected in the analysis of biochemical results. The transformation of drug discovery from a trial-and-error endeavor to one based on reliable design criteria depends on improved understanding of the dynamic mechanisms powering cellular function/dysfunction at the systems level. Here, we address the general mechanisms of molecular and cellular function and pharmacological modulation thereof. We outline a first principles theory on the mechanisms by which free energy is stored and transduced into biological function, and by which biological function is modulated by drug-target binding. We propose that cellular function depends on dynamic counter-balanced molecular systems necessitated by the exponential behavior of molecular state transitions under non-equilibrium conditions, including positive versus negative mass action kinetics and solute-induced perturbations to the hydrogen bonds of solvating water versus kT. Copyright© Bentham
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Taipale, Heidi; Tanskanen, Antti; Koponen, Marjaana; Tolppanen, Anna-Maija; Tiihonen, Jari; Hartikainen, Sirpa
2016-01-01
Background PRE2DUP is a modeling method that generates drug use periods (ie, when drug use started and ended) from drug purchases recorded in dispensing-based register data. It is based on the evaluation of personal drug purchasing patterns and considers hospital stays, possible stockpiling of drugs, and package information. Objective The objective of this study was to investigate person-level agreement between self-reported drug use in the interview and drug use modeled from dispensing data with PRE2DUP method for various drug classes used by older persons. Methods Self-reported drug use was assessed from the GeMS Study including a random sample of persons aged ≥75 years from the city of Kuopio, Finland, in 2006. Drug purchases recorded in the Prescription register data of these persons were modeled to determine drug use periods with PRE2DUP modeling method. Agreement between self-reported drug use on the interview date and drug use calculated from register-based data was compared in order to find the frequently used drugs and drug classes, which was evaluated by Cohen’s kappa. Kappa values 0.61–0.80 were considered to represent good and 0.81–1.00 as very good agreement. Results Among 569 participants with mean age of 82 years, the agreement between interview and register data was very good for 75% and very good or good for 93% of the studied drugs or drug classes. Good or very good agreement was observed for drugs that are typically used on regular bases, whereas “as needed” drugs represented poorer results. Conclusion PRE2DUP modeling method validly describes regular drug use among older persons. For most of drug classes investigated, PRE2DUP-modeled register data described drug use as well as interview-based data which are more time-consuming to collect. Further studies should be conducted by comparing it with other methods and in different drug user populations. PMID:27785101
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Directory of Open Access Journals (Sweden)
Tatyana Dyakonov
2012-01-01
Full Text Available The objective of this proof-of-concept study was to develop a platform for controlled drug delivery based on silk fibroin (SF and to explore the feasibility of using SF in oral drug delivery. The SF-containing matrixes were prepared via spray-drying and film casting, and the release profile of the model drug naproxen sodium was evaluated. Attenuated total reflectance Fourier transform infrared spectroscopy (FTIR has been used to observe conformational changes in SF- and drug-containing compositions. SF-based films, spray-dried microparticles, and matrixes loaded with naproxen were prepared. Both FTIR spectra and in vitro dissolution data demonstrated that SF β-sheet conformation regulates the release profile of naproxen. The controlled release characteristics of the SF-containing compositions were evaluated as a function of SF concentration, temperature, and exposure to dehydrating solvents. The results suggest that SF may be an attractive polymer for use in controlled drug delivery systems.
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Drug perfusion enhancement in tissue model by steady streaming induced by oscillating microbubbles.
Oh, Jin Sun; Kwon, Yong Seok; Lee, Kyung Ho; Jeong, Woowon; Chung, Sang Kug; Rhee, Kyehan
2014-01-01
Drug delivery into neurological tissue is challenging because of the low tissue permeability. Ultrasound incorporating microbubbles has been applied to enhance drug delivery into these tissues, but the effects of a streaming flow by microbubble oscillation on drug perfusion have not been elucidated. In order to clarify the physical effects of steady streaming on drug delivery, an experimental study on dye perfusion into a tissue model was performed using microbubbles excited by acoustic waves. The surface concentration and penetration length of the drug were increased by 12% and 13%, respectively, with streaming flow. The mass of dye perfused into a tissue phantom for 30s was increased by about 20% in the phantom with oscillating bubbles. A computational model that considers fluid structure interaction for streaming flow fields induced by oscillating bubbles was developed, and mass transfer of the drug into the porous tissue model was analyzed. The computed flow fields agreed with the theoretical solutions, and the dye concentration distribution in the tissue agreed well with the experimental data. The computational results showed that steady streaming with a streaming velocity of a few millimeters per second promotes mass transfer into a tissue. © 2013 Published by Elsevier Ltd.
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Directory of Open Access Journals (Sweden)
S.M. Taghizadeh
2009-12-01
Full Text Available Some formulations of drug in adhesive transdermal drug delivery systems (TDDSs( with different functional and non-functional acrylic pressure sensitive adhesives PSAs( were prepared. For this purpose fentanyl was used as a drug component. The effects of PSAs type on skin permeation and in vitro drug release from devices were evaluated using hydrodynamically well-characterized Chien permeation system fitted with excised rat abdominal skin. The adhesion properties of devices (peel strength and tack values( were obtained. It was found that TDDS with –COOH functional PSA had the lowest steady state flux. Drug release was followed by Higuchi's kinetic model. Adhesion properties of the samples were improved by addition of functional PSA in the formulations.
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Financial Effect of a Drug Distribution Model Change on a Health System.
Turingan, Erin M; Mekoba, Bijan C; Eberwein, Samuel M; Roberts, Patricia A; Pappas, Ashley L; Cruz, Jennifer L; Amerine, Lindsey B
2017-06-01
Background: Drug manufacturers change distribution models based on patient safety and product integrity needs. These model changes can limit health-system access to medications, and the financial impact on health systems can be significant. Objective: The primary aim of this study was to determine the health-system financial impact of a manufacturer's change from open to limited distribution for bevacizumab (Avastin), rituximab (Rituxan), and trastuzumab (Herceptin). The secondary aim was to identify opportunities to shift administration to outpatient settings to support formulary change. Methods: To assess the financial impact on the health system, the cost minus discount was applied to total drug expenditure during a 1-year period after the distribution model change. The opportunity analysis was conducted for three institutions within the health system through chart review of each inpatient administration. Opportunity cost was the sum of the inpatient administration cost and outpatient administration margin. Results: The total drug expenditure for the study period was $26 427 263. By applying the cost minus discount, the financial effect of the distribution model change was $1 393 606. A total of 387 administrations were determined to be opportunities to be shifted to the outpatient setting. During the study period, the total opportunity cost was $1 766 049. Conclusion: Drug expenditure increased for the health system due to the drug distribution model change and loss of cost minus discount. The opportunity cost of shifting inpatient administrations could offset the increase in expenditure. It is recommended to restrict bevacizumab, rituximab, and trastuzumab through Pharmacy & Therapeutics Committees to outpatient use where clinically appropriate.
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Zhu, Xiaoxiang; Braatz, Richard D.
2015-01-01
Biodegradable poly(D,L-lactic-co-glycolic acid) (PLGA) coating for applications in drug-eluting stents has been receiving increasing interest as a result of its unique properties compared with biodurable polymers in delivering drug for reducing stents-related side effects. In this work, a mathematical model for describing the PLGA degradation and erosion and coupled drug release from PLGA stent coating is developed and validated. An analytical expression is derived for PLGA mass loss that predicts multiple experimental studies in the literature. An analytical model for the change of the number-average degree of polymerization (or molecular weight) is also derived. The drug transport model incorporates simultaneous drug diffusion through both the polymer solid and the liquid-filled pores in the coating, where an effective drug diffusivity model is derived taking into account factors including polymer molecular weight change, stent coating porosity change, and drug partitioning between solid and aqueous phases. The model is used to describe in vitro sirolimus release from PLGA stent coating, and demonstrates the significance of simultaneous sirolimus release via diffusion through both polymer solid and pore space. The proposed model is compared to existing drug transport models, and the impact of model parameters, limitations and possible extensions of the model are also discussed. PMID:25345656
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Drug repurposing for aging research using model organisms.
Ziehm, Matthias; Kaur, Satwant; Ivanov, Dobril K; Ballester, Pedro J; Marcus, David; Partridge, Linda; Thornton, Janet M
2017-10-01
Many increasingly prevalent diseases share a common risk factor: age. However, little is known about pharmaceutical interventions against aging, despite many genes and pathways shown to be important in the aging process and numerous studies demonstrating that genetic interventions can lead to a healthier aging phenotype. An important challenge is to assess the potential to repurpose existing drugs for initial testing on model organisms, where such experiments are possible. To this end, we present a new approach to rank drug-like compounds with known mammalian targets according to their likelihood to modulate aging in the invertebrates Caenorhabditis elegans and Drosophila. Our approach combines information on genetic effects on aging, orthology relationships and sequence conservation, 3D protein structures, drug binding and bioavailability. Overall, we rank 743 different drug-like compounds for their likelihood to modulate aging. We provide various lines of evidence for the successful enrichment of our ranking for compounds modulating aging, despite sparse public data suitable for validation. The top ranked compounds are thus prime candidates for in vivo testing of their effects on lifespan in C. elegans or Drosophila. As such, these compounds are promising as research tools and ultimately a step towards identifying drugs for a healthier human aging. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
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Racialized risk environments in a large sample of people who inject drugs in the United States.
Cooper, Hannah L F; Linton, Sabriya; Kelley, Mary E; Ross, Zev; Wolfe, Mary E; Chen, Yen-Tyng; Zlotorzynska, Maria; Hunter-Jones, Josalin; Friedman, Samuel R; Des Jarlais, Don; Semaan, Salaam; Tempalski, Barbara; DiNenno, Elizabeth; Broz, Dita; Wejnert, Cyprian; Paz-Bailey, Gabriela
2016-01-01
Substantial racial/ethnic disparities exist in HIV infection among people who inject drugs (PWID) in many countries. To strengthen efforts to understand the causes of disparities in HIV-related outcomes and eliminate them, we expand the "Risk Environment Model" to encompass the construct "racialized risk environments," and investigate whether PWID risk environments in the United States are racialized. Specifically, we investigate whether black and Latino PWID are more likely than white PWID to live in places that create vulnerability to adverse HIV-related outcomes. As part of the Centers for Disease Control and Prevention's National HIV Behavioral Surveillance, 9170 PWID were sampled from 19 metropolitan statistical areas (MSAs) in 2009. Self-reported data were used to ascertain PWID race/ethnicity. Using Census data and other administrative sources, we characterized features of PWID risk environments at four geographic scales (i.e., ZIP codes, counties, MSAs, and states). Means for each feature of the risk environment were computed for each racial/ethnic group of PWID, and were compared across racial/ethnic groups. Almost universally across measures, black PWID were more likely than white PWID to live in environments associated with vulnerability to adverse HIV-related outcomes. Compared to white PWID, black PWID lived in ZIP codes with higher poverty rates and worse spatial access to substance abuse treatment and in counties with higher violent crime rates. Black PWID were less likely to live in states with laws facilitating sterile syringe access (e.g., laws permitting over-the-counter syringe sales). Latino/white differences in risk environments emerged at the MSA level (e.g., Latino PWID lived in MSAs with higher drug-related arrest rates). PWID risk environments in the US are racialized. Future research should explore the implications of this racialization for racial/ethnic disparities in HIV-related outcomes, using appropriate methods. Copyright © 2015
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Energy Technology Data Exchange (ETDEWEB)
Hu, Liang [Department of Pharmaceutics, Shenyang Pharmaceutical University, P.O. Box 32, Liaoning Province, Shenyang 110016 (China); Sun, Hongrui [English Teaching Department, School of Basic Courses, Shenyang Pharmaceutical University, Wenhua Road 103, Shenyang 110016 (China); Zhao, Qinfu; Han, Ning; Bai, Ling; Wang, Ying; Jiang, Tongying [Department of Pharmaceutics, Shenyang Pharmaceutical University, P.O. Box 32, Liaoning Province, Shenyang 110016 (China); Wang, Siling, E-mail: silingwang@syphu.edu.cn [Department of Pharmaceutics, Shenyang Pharmaceutical University, P.O. Box 32, Liaoning Province, Shenyang 110016 (China)
2015-02-01
We used a combination of mesoporous silica nanospheres (MSN) and layer-by-layer (LBL) self-assembly technology to establish a new oral sustained drug delivery system for the poorly water-soluble drug felodipine. Firstly, the model drug was loaded into MSN, and then the loaded MSN were repeatedly encapsulated by chitosan (CHI) and acacia (ACA) via LBL self-assembly method. The structural features of the samples were studied using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and nitrogen adsorption. The encapsulating process was monitored by zeta-potential and surface tension measurements. The physical state of the drug in the samples was characterized by differential scanning calorimetry (DSC) and X-ray diffractometry (XRD). The influence of the multilayer with different number of layers on the drug release rate was studied using thermal gravimetric analysis (TGA) and surface tension measurement. The swelling effect and the structure changes of the multilayer were investigated to explore the relationship between the drug release behavior and the state of the multilayer under different pH conditions. The stability and mucosa adhesive ability of the prepared nanoparticles were also explored. After multilayer coating, the drug release rate was effectively controlled. The differences in drug release behavior under different pH conditions could be attributed to the different states of the multilayer. And the nanoparticles possessed good stability and strong mucosa adhesive ability. We believe that this combination offers a simple strategy for regulating the release rate of poorly water-soluble drugs and extends the pharmaceutical applications of inorganic materials and polymers. - Highlights: • A combination of inorganic and organic materials was applied. • Mesoporous silica nanospheres (MSN) were used as drug carriers. • Chitosan and acacia were encapsulated through layer-by-layer self-assembly. • The release rate of the poorly
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International Nuclear Information System (INIS)
Hu, Liang; Sun, Hongrui; Zhao, Qinfu; Han, Ning; Bai, Ling; Wang, Ying; Jiang, Tongying; Wang, Siling
2015-01-01
We used a combination of mesoporous silica nanospheres (MSN) and layer-by-layer (LBL) self-assembly technology to establish a new oral sustained drug delivery system for the poorly water-soluble drug felodipine. Firstly, the model drug was loaded into MSN, and then the loaded MSN were repeatedly encapsulated by chitosan (CHI) and acacia (ACA) via LBL self-assembly method. The structural features of the samples were studied using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and nitrogen adsorption. The encapsulating process was monitored by zeta-potential and surface tension measurements. The physical state of the drug in the samples was characterized by differential scanning calorimetry (DSC) and X-ray diffractometry (XRD). The influence of the multilayer with different number of layers on the drug release rate was studied using thermal gravimetric analysis (TGA) and surface tension measurement. The swelling effect and the structure changes of the multilayer were investigated to explore the relationship between the drug release behavior and the state of the multilayer under different pH conditions. The stability and mucosa adhesive ability of the prepared nanoparticles were also explored. After multilayer coating, the drug release rate was effectively controlled. The differences in drug release behavior under different pH conditions could be attributed to the different states of the multilayer. And the nanoparticles possessed good stability and strong mucosa adhesive ability. We believe that this combination offers a simple strategy for regulating the release rate of poorly water-soluble drugs and extends the pharmaceutical applications of inorganic materials and polymers. - Highlights: • A combination of inorganic and organic materials was applied. • Mesoporous silica nanospheres (MSN) were used as drug carriers. • Chitosan and acacia were encapsulated through layer-by-layer self-assembly. • The release rate of the poorly
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Computational and experimental model of transdermal iontophorethic drug delivery system.
Filipovic, Nenad; Saveljic, Igor; Rac, Vladislav; Graells, Beatriz Olalde; Bijelic, Goran
2017-11-30
The concept of iontophoresis is often applied to increase the transdermal transport of drugs and other bioactive agents into the skin or other tissues. It is a non-invasive drug delivery method which involves electromigration and electroosmosis in addition to diffusion and is shown to be a viable alternative to conventional administration routs such as oral, hypodermic and intravenous injection. In this study we investigated, experimentally and numerically, in vitro drug delivery of dexamethasone sodium phosphate to porcine skin. Different current densities, delivery durations and drug loads were investigated experimentally and introduced as boundary conditions for numerical simulations. Nernst-Planck equation was used for calculation of active substance flux through equivalent model of homogeneous hydrogel and skin layers. The obtained numerical results were in good agreement with experimental observations. A comprehensive in-silico platform, which includes appropriate numerical tools for fitting, could contribute to iontophoretic drug-delivery devices design and correct dosage and drug clearance profiles as well as to perform much faster in-silico experiments to better determine parameters and performance criteria of iontophoretic drug delivery. Copyright © 2017 Elsevier B.V. All rights reserved.
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Computational prediction of drug-drug interactions based on drugs functional similarities.
Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah
2017-06-01
Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.
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Solanki, Nayan G; Tahsin, Md; Shah, Ankita V; Serajuddin, Abu T M
2018-01-01
The primary aim of this study was to identify pharmaceutically acceptable amorphous polymers for producing 3D printed tablets of a model drug, haloperidol, for rapid release by fused deposition modeling. Filaments for 3D printing were prepared by hot melt extrusion at 150°C with 10% and 20% w/w of haloperidol using Kollidon ® VA64, Kollicoat ® IR, Affinsiol ™ 15 cP, and HPMCAS either individually or as binary blends (Kollidon ® VA64 + Affinisol ™ 15 cP, 1:1; Kollidon ® VA64 + HPMCAS, 1:1). Dissolution of crushed extrudates was studied at pH 2 and 6.8, and formulations demonstrating rapid dissolution rates were then analyzed for drug-polymer, polymer-polymer and drug-polymer-polymer miscibility by film casting. Polymer-polymer (1:1) and drug-polymer-polymer (1:5:5 and 2:5:5) mixtures were found to be miscible. Tablets with 100% and 60% infill were printed using MakerBot printer at 210°C, and dissolution tests of tablets were conducted at pH 2 and 6.8. Extruded filaments of Kollidon ® VA64-Affinisol ™ 15 cP mixtures were flexible and had optimum mechanical strength for 3D printing. Tablets containing 10% drug with 60% and 100% infill showed complete drug release at pH 2 in 45 and 120 min, respectively. Relatively high dissolution rates were also observed at pH 6.8. The 1:1-mixture of Kollidon ® VA64 and Affinisol ™ 15 cP was thus identified as a suitable polymer system for 3D printing and rapid drug release. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
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Green, David
2016-01-01
Objectives: To test the “Trump Hypothesis”: whether immigrants are responsible for higher levels of violent and drug-related crime in the United States, as asserted by Donald Trump in his 2015 presidential campaign announcement. This is achieved using recent crime and immigration data, thus testing the common public perception linking immigrants to crime, and providing an updated assessment of the immigrant-crime nexus. Methods: Rates of violent crime and drug arrests by state are pooled for ...
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DEFF Research Database (Denmark)
Khan, Jamal; Hawley, Adrian; Rades, Thomas
2016-01-01
In situ lipolysis and synchrotron small-angle X-ray scattering (SAXS) were used to directly detect and elucidate the solid-state form of precipitated fenofibrate from the digestion of a model lipid-based formulation (LBF). This method was developed in light of recent findings that indicate variab...... on drugs, and experimental conditions, which are anticipated to produce altered solid-state forms upon the precipitation of drug (i.e., polymorphs, amorphous forms, and salts). © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci....
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Germovsek, Eva; Barker, Charlotte I S; Sharland, Mike; Standing, Joseph F
2018-04-19
Pharmacokinetic/pharmacodynamic (PKPD) modeling is important in the design and conduct of clinical pharmacology research in children. During drug development, PKPD modeling and simulation should underpin rational trial design and facilitate extrapolation to investigate efficacy and safety. The application of PKPD modeling to optimize dosing recommendations and therapeutic drug monitoring is also increasing, and PKPD model-based dose individualization will become a core feature of personalized medicine. Following extensive progress on pediatric PK modeling, a greater emphasis now needs to be placed on PD modeling to understand age-related changes in drug effects. This paper discusses the principles of PKPD modeling in the context of pediatric drug development, summarizing how important PK parameters, such as clearance (CL), are scaled with size and age, and highlights a standardized method for CL scaling in children. One standard scaling method would facilitate comparison of PK parameters across multiple studies, thus increasing the utility of existing PK models and facilitating optimal design of new studies.
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Multimodality imaging and mathematical modelling of drug delivery to glioblastomas.
Boujelben, Ahmed; Watson, Michael; McDougall, Steven; Yen, Yi-Fen; Gerstner, Elizabeth R; Catana, Ciprian; Deisboeck, Thomas; Batchelor, Tracy T; Boas, David; Rosen, Bruce; Kalpathy-Cramer, Jayashree; Chaplain, Mark A J
2016-10-06
Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood-brain barrier (BBB). Although it has been hypothesized that the 'normalization' of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated-flow rate, vessel permeability and tissue diffusion coefficient-interact nonlinearly to produce the observed average drug concentration in the microenvironment.
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Modeling the Release Kinetics of Poorly Water-Soluble Drug Molecules from Liposomal Nanocarriers
Directory of Open Access Journals (Sweden)
Stephan Loew
2011-01-01
Full Text Available Liposomes are frequently used as pharmaceutical nanocarriers to deliver poorly water-soluble drugs such as temoporfin, cyclosporine A, amphotericin B, and paclitaxel to their target site. Optimal drug delivery depends on understanding the release kinetics of the drug molecules from the host liposomes during the journey to the target site and at the target site. Transfer of drugs in model systems consisting of donor liposomes and acceptor liposomes is known from experimental work to typically exhibit a first-order kinetics with a simple exponential behavior. In some cases, a fast component in the initial transfer is present, in other cases the transfer is sigmoidal. We present and analyze a theoretical model for the transfer that accounts for two physical mechanisms, collisions between liposomes and diffusion of the drug molecules through the aqueous phase. Starting with the detailed distribution of drug molecules among the individual liposomes, we specify the conditions that lead to an apparent first-order kinetic behavior. We also discuss possible implications on the transfer kinetics of (1 high drug loading of donor liposomes, (2 attractive interactions between drug molecules within the liposomes, and (3 slow transfer of drugs between the inner and outer leaflets of the liposomes.
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Neuhaus, W; Mandikova, J; Pawlowitsch, R; Linz, B; Bennani-Baiti, B; Lauer, R; Lachmann, B; Noe, C R
2012-05-01
In the course of our validation program testing blood-brain barrier (BBB) in vitro models for their usability as tools in drug discovery it was evaluated whether an established Transwell model based on porcine cell line PBMEC/C1-2 was able to differentiate between the transport properties of first and second generation antihistaminic drugs. First generation antihistamines can permeate the BBB and act in the central nervous system (CNS), whereas entry to the CNS of second generation antihistamines is restricted by efflux pumps such as P-glycoprotein (P-gP) located in brain endothelial cells. P-gP functionality of PBMEC/C1-2 cells grown on Transwell filter inserts was proven by transport studies with P-gP substrate rhodamine 123 and P-gP blocker verapamil. Subsequent drug transport studies with the first generation antihistamines promethazine, diphenhydramine and pheniramine and the second generation antihistamines astemizole, ceterizine, fexofenadine and loratadine were accomplished in single substance as well as in group studies. Results were normalised to diazepam, an internal standard for the transcellular transport route. Moreover, effects after addition of P-gP inhibitor verapamil were investigated. First generation antihistamine pheniramine permeated as fastest followed by diphenhydramine, diazepam, promethazine and second generation antihistaminic drugs ceterizine, fexofenadine, astemizole and loratadine reflecting the BBB in vivo permeability ranking well. Verapamil increased the transport rates of all second generation antihistamines, which suggested involvement of P-gP during their permeation across the BBB model. The ranking after addition of verapamil was significantly changed, only fexofenadine and ceterizine penetrated slower than internal standard diazepam in the presence of verapamil. In summary, permeability data showed that the BBB model based on porcine cell line PBMEC/C1-2 was able to reflect the BBB in vivo situation for the transport of
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A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).
Kuang, Qifan; Wang, MinQi; Li, Rong; Dong, YongCheng; Li, Yizhou; Li, Menglong
2014-01-01
Early and accurate identification of adverse drug reactions (ADRs) is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs. In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper. Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.
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Birru, Woldeamanuel A; Warren, Dallas B; Han, Sifei; Benameur, Hassan; Porter, Christopher J H; Pouton, Colin W; Chalmers, David K
2017-03-06
Lipid-based drug formulations can greatly enhance the bioavailability of poorly water-soluble drugs. Following the oral administration of formulations containing tri- or diglycerides, the digestive processes occurring within the gastrointestinal (GI) tract hydrolyze the glycerides to mixtures of free fatty acids and monoglycerides that are, in turn, solubilized by bile. The behavior of drugs within the resulting colloidal mixtures is currently not well characterized. This work presents matched in vitro experimental and molecular dynamics (MD) theoretical models of the GI microenvironment containing a digested triglyceride-based (Type I) drug formulation. Both the experimental and theoretical models consist of molecular species representing bile (glycodeoxycholic acid), digested triglyceride (1:2 glyceryl-1-monooleate and oleic acid), and water. We have characterized the phase behavior of the physical system using nephelometry, dynamic light scattering, and polarizing light microscopy and compared these measurements to phase behavior observed in multiple MD simulations. Using this model microenvironment, we have investigated the dissolution of the poorly water-soluble drug danazol experimentally using LC-MS and theoretically by MD simulation. The results show how the formulation lipids alter the environment of the GI tract and improve the solubility of danazol. The MD simulations successfully reproduce the experimental results showing the utility of MD in modeling the fate of drugs after digestion of lipid-based formulations within the intestinal lumen.
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Weaver, Richard J; Betts, Catherine; Blomme, Eric A G; Gerets, Helga H J; Gjervig Jensen, Klaus; Hewitt, Philip G; Juhila, Satu; Labbe, Gilles; Liguori, Michael J; Mesens, Natalie; Ogese, Monday O; Persson, Mikael; Snoeys, Jan; Stevens, James L; Walker, Tracy; Park, B Kevin
2017-07-01
The liver is an important target for drug-induced toxicities. Early detection of hepatotoxic drugs requires use of well-characterized test systems, yet current knowledge, gaps and limitations of tests employed remains an important issue for drug development. Areas Covered: The current state of the science, understanding and application of test systems in use for the detection of drug-induced cytotoxicity, mitochondrial toxicity, cholestasis and inflammation is summarized. The test systems highlighted herein cover mostly in vitro and some in vivo models and endpoint measurements used in the assessment of small molecule toxic liabilities. Opportunities for research efforts in areas necessitating the development of specific tests and improved mechanistic understanding are highlighted. Expert Opinion: Use of in vitro test systems for safety optimization will remain a core activity in drug discovery. Substantial inroads have been made with a number of assays established for human Drug-induced Liver Injury. There nevertheless remain significant gaps with a need for improved in vitro tools and novel tests to address specific mechanisms of human Drug-Induced Liver Injury. Progress in these areas will necessitate not only models fit for application, but also mechanistic understanding of how chemical insult on the liver occurs in order to identify translational and quantifiable readouts for decision-making.
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Clifford, Anton; Shakeshaft, Anthony
2017-07-01
Indigenous peoples of Australia, New Zealand, Canada and the United States experience a disproportionately high burden of harms from substance misuse. Research is therefore required to improve our understanding of substance use in Indigenous populations and provide evidence on strategies effective for reducing harmful use. A search of 13 electronic databases for peer-reviewed articles published between 1993 and 2014 focusing on substance use and Indigenous peoples of Australia, New Zealand, Canada and the United States. Relevant abstracts were classified as data or non-data based research. Data-based studies were further classified as measurement, descriptive or intervention and their trends examined by country and drug type. Intervention studies were classified by type and their evaluation designs classified using the Cochrane Effective Practice and Organisation of Care (EPOC) data collection checklist. There was a statistically significant increase from 1993 to 2014 in the percentage of total publications that were data-based (P Indigenous drug and alcohol field are required. The dominance of descriptive research in the Indigenous drug and alcohol field is less than optimal for generating evidence to inform Indigenous drug and alcohol policy and programs. [Clifford A, Shakeshaft A. A bibliometric review of drug and alcohol research focused on Indigenous peoples of Australia, New Zealand, Canada and the United States. Drug Alcohol Rev 2017;36:509-522]. © 2017 Australasian Professional Society on Alcohol and other Drugs.
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My Life with State Space Models
DEFF Research Database (Denmark)
Lundbye-Christensen, Søren
2007-01-01
. The conceptual idea behind the state space model is that the evolution over time in the object we are observing and the measurement process itself are modelled separately. My very first serious analysis of a data set was done using a state space model, and since then I seem to have been "haunted" by state space...
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Mathematical models for drug diffusion through the compartments of ...
African Journals Online (AJOL)
M.A. Khanday
2016-07-26
Jul 26, 2016 ... partments have both favourable and adverse effects on human body. The researchers ... absorption, distribution and elimination process of the drug within the body ... models can be used to understand the transport processes.
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PockDrug: A Model for Predicting Pocket Druggability That Overcomes Pocket Estimation Uncertainties.
Borrel, Alexandre; Regad, Leslie; Xhaard, Henri; Petitjean, Michel; Camproux, Anne-Claude
2015-04-27
Predicting protein druggability is a key interest in the target identification phase of drug discovery. Here, we assess the pocket estimation methods' influence on druggability predictions by comparing statistical models constructed from pockets estimated using different pocket estimation methods: a proximity of either 4 or 5.5 Å to a cocrystallized ligand or DoGSite and fpocket estimation methods. We developed PockDrug, a robust pocket druggability model that copes with uncertainties in pocket boundaries. It is based on a linear discriminant analysis from a pool of 52 descriptors combined with a selection of the most stable and efficient models using different pocket estimation methods. PockDrug retains the best combinations of three pocket properties which impact druggability: geometry, hydrophobicity, and aromaticity. It results in an average accuracy of 87.9% ± 4.7% using a test set and exhibits higher accuracy (∼5-10%) than previous studies that used an identical apo set. In conclusion, this study confirms the influence of pocket estimation on pocket druggability prediction and proposes PockDrug as a new model that overcomes pocket estimation variability.
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METHODOLOGY OF THE DRUGS MARKET VOLUME MODELING ON THE EXAMPLE OF HEMOPHILIA A
N. B. Molchanova
2015-01-01
Hemophilia A is a serious genetic disease, which may lead to disability of a patient even in early ages without a required therapy. The only one therapeutic approach is a replacement therapy with drugs of bloodcoagulation factor VIII (FVIII). The modeling of coagulation drugs market volume will allow evaluation of the level of patients’ provision with a necessary therapy. Modeling of a “perfect” market of drugs and its comparison with the real one was the purpose of the study. During the mode...
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METHODOLOGY OF THE DRUGS MARKET VOLUME MODELING ON THE EXAMPLE OF HEMOPHILIA A
Directory of Open Access Journals (Sweden)
N. B. Molchanova
2015-01-01
Full Text Available Hemophilia A is a serious genetic disease, which may lead to disability of a patient even in early ages without a required therapy. The only one therapeutic approach is a replacement therapy with drugs of bloodcoagulation factor VIII (FVIII. The modeling of coagulation drugs market volume will allow evaluation of the level of patients’ provision with a necessary therapy. Modeling of a “perfect” market of drugs and its comparison with the real one was the purpose of the study. During the modeling of market volume we have used the data about the number of hamophilia A patients on the basis of the federal registry, Russian and international morbidity indices, and the data of a real practice about average consumption of drugs of bloodcoagulation factors and data about the drugs prescription according to the standards and protocols of assistance rendering. According to the standards of care delivery, average annual volume of FVIII drugs consumption amounted to 406 325 244 IU for children and 964 578 678 IU for adults, i.e. an average volume of a “perfect” market is equal to 1 370 903 922 IU for all patients. The market volume is 1.8 times bigger than a real volume of FVIII drugs which, according to the data of IMS marketing agency, amounted to 765 000 000 IU in 2013. The modeling conducted has shown that despite a relatively high patients’ coverage there is a potential for almost double growth.
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Polar drug residues in sewage and natural waters in the state of Rio de Janeiro, Brazil.
Stumpf, M; Ternes, T A; Wilken, R D; Rodrigues, S V; Baumann, W
1999-01-12
The drug residues of lipid regulators, anti-inflammatories and some drug metabolites have been detected in raw sewage, treated waste water and river water in the state of Rio de Janeiro, Brazil. These residues are mainly derived from humans via excretion. The median concentrations in the effluents of sewage treatment plants (STPs) of most drugs investigated in this study ranged from 0.1 to 1 microgram/l. The removal rates of individual drugs during passage through a Brazilian STP varied from 12 to 90%. As a consequence of the incomplete removal of these residues during passage through a STP, rivers were also found to be contaminated. Median concentrations ranged from between 0.02 and 0.04 microgram/l in river water, whereas the maximum values were observed to be up to 0.5 microgram/l.
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Energy Technology Data Exchange (ETDEWEB)
ChiBin, Zhang; XiaoHui, Lin, E-mail: lxh60@seu.edu.cn; ZhaoMin, Wang; ChangBao, Wang
2017-03-15
In experiments and theoretical analyses, this study examines the capture efficiency (CE) of magnetic drug carrier particles (MDCPs) for implant-assisted magnetic drug targeting (IA-MDT) in microvessels. It also proposes a three-dimensional statistical transport model of MDCPs for IA-MDT in permeable microvessels, which describes blood flow by the two-fluid (Casson and Newtonian) model. The model accounts for the permeable effect of the microvessel wall and the coupling effect between the blood flow and tissue fluid flow. The MDCPs move randomly through the microvessel, and their transport state is described by the Boltzmann equation. The regulated changes and factors affecting the CE of the MDCPs in the assisted magnetic targeting were obtained by solving the theoretical model and by experimental testing. The CE was negatively correlated with the blood flow velocity, and positively correlated with the external magnetic field intensity and microvessel permeability. The predicted CEs of the MDCPs were consistent with the experimental results. Additionally, under the same external magnetic field, the predicted CE was 5–8% higher in the IA-MDT model than in the model ignoring the permeability effect of the microvessel wall. - Highlights: • A model of MDCPs for IA-MDT in permeable microvessels was established. • An experimental device was established, the CE of MDCPs was measured. • The predicted CE of MDCPs was 5–8% higher in the IA-MDT model.
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Quantitative modeling of selective lysosomal targeting for drug design
DEFF Research Database (Denmark)
Trapp, Stefan; Rosania, G.; Horobin, R.W.
2008-01-01
log K ow. These findings were validated with experimental results and by a comparison to the properties of antimalarial drugs in clinical use. For ten active compounds, nine were predicted to accumulate to a greater extent in lysosomes than in other organelles, six of these were in the optimum range...... predicted by the model and three were close. Five of the antimalarial drugs were lipophilic weak dibasic compounds. The predicted optimum properties for a selective accumulation of weak bivalent bases in lysosomes are consistent with experimental values and are more accurate than any prior calculation...
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Gause, Samuel; Hsu, Kuan-Hui; Shafor, Chancellor; Dixon, Phillip; Powell, Kristin Conrad; Chauhan, Anuj
2016-07-01
Ophthalmic drug for the anterior chamber diseases are delivered into tears by either eye drops or by extended release devices placed in the eyes. The instilled drug exits the eye through various routes including tear drainage into the nose through the canaliculi and transport across various ocular membranes. Understanding the mechanisms relevant to each route can be useful in predicting the dependency of ocular bioavailability on various formulation parameters, such as drug concentration, salinity, viscosity, etc. Mathematical modeling has been developed for each of the routes and validated by comparison with experiments. The individual models can be combined into a system model to predict the fraction of the instilled drug that reaches the target. This review summarizes the individual models for the transport of drugs across the cornea and conjunctiva and the canaliculi tear drainage. It also summarizes the combined tear dynamics model that can predict the ocular bioavailability of drugs instilled as eye drops. The predictions from the individual models and the combined model are in good agreement with experimental data. Both experiments and models predict that the corneal bioavailability for drugs delivered through eye drops is less than 5% due to the small area of the cornea in comparison to the conjunctiva, and the rapid clearance of the instilled solution by tear drainage. A contact lens is a natural choice for delivering drugs to the cornea due to the placement of the contact in the immediate vicinity of the cornea. The drug released by the contact towards the cornea surface is trapped in the post lens tear film for extended duration of at least 30min allowing transport of a large portion into the cornea. The model predictions backed by in vivo animal and clinical data show that the bioavailability increases to about 50% with contact lenses. This realization has encouraged considerable research towards delivering ocular drugs by contact lenses. Commercial
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Determinants of U.S. Prescription Drug Utilization using County Level Data.
Nianogo, Thierry; Okunade, Albert; Fofana, Demba; Chen, Weiwei
2016-05-01
Prescription drugs are the third largest component of U.S. healthcare expenditures. The 2006 Medicare Part D and the 2010 Affordable Care Act are catalysts for further growths in utilization becuase of insurance expansion effects. This research investigating the determinants of prescription drug utilization is timely, methodologically novel, and policy relevant. Differences in population health status, access to care, socioeconomics, demographics, and variations in per capita number of scripts filled at retail pharmacies across the U.S.A. justify fitting separate econometric models to county data of the states partitioned into low, medium, and high prescription drug users. Given the skewed distribution of per capita number of filled prescriptions (response variable), we fit the variance stabilizing Box-Cox power transformation regression models to 2011 county level data for investigating the correlates of prescription drug utilization separately for low, medium, and high utilization states. Maximum likelihood regression parameter estimates, including the optimal Box-Cox λ power transformations, differ across high (λ = 0.214), medium (λ = 0.942), and low (λ = 0.302) prescription drug utilization models. The estimated income elasticities of -0.634, 0.031, and -0.532 in high, medium, and low utilization models suggest that the economic behavior of prescriptions is not invariant across different utilization levels. Copyright © 2015 John Wiley & Sons, Ltd.
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Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng
2016-05-01
Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.
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Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng
2016-05-01
Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .
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A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs.
Directory of Open Access Journals (Sweden)
Qifan Kuang
Full Text Available Early and accurate identification of adverse drug reactions (ADRs is critically important for drug development and clinical safety. Computer-aided prediction of ADRs has attracted increasing attention in recent years, and many computational models have been proposed. However, because of the lack of systematic analysis and comparison of the different computational models, there remain limitations in designing more effective algorithms and selecting more useful features. There is therefore an urgent need to review and analyze previous computation models to obtain general conclusions that can provide useful guidance to construct more effective computational models to predict ADRs.In the current study, the main work is to compare and analyze the performance of existing computational methods to predict ADRs, by implementing and evaluating additional algorithms that have been earlier used for predicting drug targets. Our results indicated that topological and intrinsic features were complementary to an extent and the Jaccard coefficient had an important and general effect on the prediction of drug-ADR associations. By comparing the structure of each algorithm, final formulas of these algorithms were all converted to linear model in form, based on this finding we propose a new algorithm called the general weighted profile method and it yielded the best overall performance among the algorithms investigated in this paper.Several meaningful conclusions and useful findings regarding the prediction of ADRs are provided for selecting optimal features and algorithms.
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Sex differences and ovarian hormones in animal models of drug dependence.
Carroll, Marilyn E; Anker, Justin J
2010-06-01
Increasing evidence indicates the presence of sex differences in many aspects of drug abuse. Most studies reveal that females exceed males during the initiation, escalation, extinction, and reinstatement (relapse) of drug-seeking behavior, but males are more sensitive than females to the aversive effects of drugs such as drug withdrawal. Findings from human and animal research indicate that circulating levels of ovarian steroid hormones account for these sex differences. Estrogen (E) facilitates drug-seeking behavior, while progesterone (P) and its metabolite, allopregnanalone (ALLO), counteract the effects of E and reduce drug seeking. Estrogen and P influence other behaviors that are affiliated with drug abuse such as drug-induced locomotor sensitization and conditioned place preference. The enhanced vulnerability to drug seeking in females vs. males is also additive with the other risk factors for drug abuse (e.g., adolescence, sweet preference, novelty reactivity, and impulsivity). Finally, treatment studies using behavioral or pharmacological interventions, including P and ALLO, also indicate that females show greater treatment effectiveness during several phases of the addiction process. The neurobiological basis of sex differences in drug abuse appears to be genetic and involves the influence of ovarian hormones and their metabolites, the hypothalamic pituitary adrenal (HPA) axis, dopamine (DA), and gamma-hydroxy-butyric acid (GABA). Overall, sex and hormonal status along with other biological risk factors account for a continuum of addiction-prone and -resistant animal models that are valuable for studying drug abuse prevention and treatment strategies. Copyright 2009. Published by Elsevier Inc.
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Naritomi, Yoichi; Sanoh, Seigo; Ohta, Shigeru
2018-02-01
Predicting human drug metabolism and pharmacokinetics (PK) is key to drug discovery. In particular, it is important to predict human PK, metabolite profiles and drug-drug interactions (DDIs). Various methods have been used for such predictions, including in vitro metabolic studies using human biological samples, such as hepatic microsomes and hepatocytes, and in vivo studies using experimental animals. However, prediction studies using these methods are often inconclusive due to discrepancies between in vitro and in vivo results, and interspecies differences in drug metabolism. Further, the prediction methods have changed from qualitative to quantitative to solve these issues. Chimeric mice with humanized liver have been developed, in which mouse liver cells are mostly replaced with human hepatocytes. Since human drug metabolizing enzymes are expressed in the liver of these mice, they are regarded as suitable models for mimicking the drug metabolism and PK observed in humans; therefore, these mice are useful for predicting human drug metabolism and PK. In this review, we discuss the current state, issues, and future directions of predicting human drug metabolism and PK using chimeric mice with humanized liver in drug discovery. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.
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Patient access to new cancer drugs in the United States and Australia.
Wilson, Andrew; Cohen, Joshua
2011-01-01
In light of the current debate on the use value and potential impact of comparative effectiveness research on patient access, it may prove insightful to compare a health-care system that systematically bases its reimbursement decisions on comparative effectiveness evidence with the United States (US) system that hitherto has only been informed by such evidence on an ad hoc basis. For a set of 2000-2009 approved new molecular entities and biologics indicated for cancer, we compared patient access between US Medicare and Australian Pharmaceutical Benefits Scheme (PBS) beneficiaries. Here, access is defined in terms of marketing availability, payer coverage, and patient out-of-pocket costs. Although 34 drugs and biologics were approved for cancer in the US, just more than one-third (35%) were ultimately covered by the Australian PBS. The PBS also placed more restrictions on use. On the other hand, prices and patient out-of-pocket costs were greater for the US Medicare population. Our analysis points to a possible trade-off in market access to oncology drugs. Although more oncology drugs are available in the US and a higher percentage of available drugs are covered, the evidence-based approach adopted by Australia has contributed to reduced prices, thereby improving affordability for payers and patients for those medications deemed cost-effective by the reimbursement authority. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Directory of Open Access Journals (Sweden)
Iris Chen
Full Text Available Antiretroviral (ARV drug use was analyzed in HIV-uninfected women in an observational cohort study conducted in 10 urban and periurban communities in the United States with high rates of poverty and HIV infection. Plasma samples collected in 2009-2010 were tested for the presence of 16 ARV drugs. ARV drugs were detected in samples from 39 (2% of 1,806 participants: 27/181 (15% in Baltimore, MD and 12/179 (7% in Bronx, NY. The ARV drugs detected included different combinations of non-nucleoside reverse transcriptase inhibitors and protease inhibitors (1-4 drugs/sample. These data were analyzed in the context of self-reported data on ARV drug use. None of the 39 women who had ARV drugs detected reported ARV drug use at any study visit. Further research is needed to evaluate ARV drug use by HIV-uninfected individuals.
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Energy Technology Data Exchange (ETDEWEB)
Valerio, Luis G., E-mail: luis.valerio@fda.hhs.gov [Science and Research Staff, Office of Pharmaceutical Science, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, MD 20993–0002 (United States); Cross, Kevin P. [Leadscope, Inc., 1393 Dublin Road, Columbus, OH, 43215–1084 (United States)
2012-05-01
Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive
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International Nuclear Information System (INIS)
Valerio, Luis G.; Cross, Kevin P.
2012-01-01
Control and minimization of human exposure to potential genotoxic impurities found in drug substances and products is an important part of preclinical safety assessments of new drug products. The FDA's 2008 draft guidance on genotoxic and carcinogenic impurities in drug substances and products allows use of computational quantitative structure–activity relationships (QSAR) to identify structural alerts for known and expected impurities present at levels below qualified thresholds. This study provides the information necessary to establish the practical use of a new in silico toxicology model for predicting Salmonella t. mutagenicity (Ames assay outcome) of drug impurities and other chemicals. We describe the model's chemical content and toxicity fingerprint in terms of compound space, molecular and structural toxicophores, and have rigorously tested its predictive power using both cross-validation and external validation experiments, as well as case studies. Consistent with desired regulatory use, the model performs with high sensitivity (81%) and high negative predictivity (81%) based on external validation with 2368 compounds foreign to the model and having known mutagenicity. A database of drug impurities was created from proprietary FDA submissions and the public literature which found significant overlap between the structural features of drug impurities and training set chemicals in the QSAR model. Overall, the model's predictive performance was found to be acceptable for screening drug impurities for Salmonella mutagenicity. -- Highlights: ► We characterize a new in silico model to predict mutagenicity of drug impurities. ► The model predicts Salmonella mutagenicity and will be useful for safety assessment. ► We examine toxicity fingerprints and toxicophores of this Ames assay model. ► We compare these attributes to those found in drug impurities known to FDA/CDER. ► We validate the model and find it has a desired predictive performance.
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Directory of Open Access Journals (Sweden)
E Soleimani
2016-02-01
Full Text Available Objective: This study was an attempt to investigate the effect of music therapy on addicts’ state-trait anxiety rate in the stage of drug-free rehabilitation. Method: A quasi-experimental research design, along with pretest-posttest and control group was employed for the conduct of this study. The statistical population of the study included the addicts in the rehabilitation stage who had referred to the clean collaborators rehabilitation camp in Ardebil province in November 2014. From this population, the number of 32 addicts in 16-50-year-old age range was selected as the participants of the study by convenience sampling method. State-Trait Anxiety Inventory was used for data collection. Results: The results of multivariate covariant analysis showed that there is a significant difference between control and experimental groups in state and trait anxiety. In other words, the state and trait anxiety of addicts in the experimental group had been reduced after music therapy. Conclusion: Considering the obtained results, it can be concluded that music therapy alone or along other psychological interventions can be an effective method for reducing addicts’ anxiety in drug-free rehabilitation stage.
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Human Drug Discrimination: Elucidating the Neuropharmacology of Commonly Abused Illicit Drugs.
Bolin, B Levi; Alcorn, Joseph L; Reynolds, Anna R; Lile, Joshua A; Stoops, William W; Rush, Craig R
2016-06-07
Drug-discrimination procedures empirically evaluate the control that internal drug states have over behavior. They provide a highly selective method to investigate the neuropharmacological underpinnings of the interoceptive effects of drugs in vivo. As a result, drug discrimination has been one of the most widely used assays in the field of behavioral pharmacology. Drug-discrimination procedures have been adapted for use with humans and are conceptually similar to preclinical drug-discrimination techniques in that a behavior is differentially reinforced contingent on the presence or absence of a specific interoceptive drug stimulus. This chapter provides a basic overview of human drug-discrimination procedures and reviews the extant literature concerning the use of these procedures to elucidate the underlying neuropharmacological mechanisms of commonly abused illicit drugs (i.e., stimulants, opioids, and cannabis) in humans. This chapter is not intended to review every available study that used drug-discrimination procedures in humans. Instead, when possible, exemplary studies that used a stimulant, opioid, or Δ 9 -tetrahydrocannabinol (the primary psychoactive constituent of cannabis) to assess the discriminative-stimulus effects of drugs in humans are reviewed for illustrative purposes. We conclude by commenting on the current state and future of human drug-discrimination research.
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Secondary Prevention Services for Clients Who Are Low Risk in Drug Court: A Conceptual Model
DeMatteo, David S.; Marlowe, Douglas B.; Festinger, David S.
2006-01-01
The drug court model assumes that most drug offenders are addicts, and that drug use fuels other criminal activity. As a result, drug court clients must satisfy an intensive regimen of treatment and supervisory obligations. However, research suggests that roughly one third of drug court clients do not have a clinically significant substance use…
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Pharmacokinetic properties and in silico ADME modeling in drug discovery.
Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D
2013-03-01
The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.
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Maeda, Hideki; Kurokawa, Tatsuo
2015-12-01
This study exhaustively and historically investigated the status of drug lag for oncology drugs approved in Japan. We comprehensively investigated oncology drugs approved in Japan between April 2001 and July 2014, using publicly available information. We also examined changes in the status of drug lag between Japan and the United States, as well as factors influencing drug lag. This study included 120 applications for approval of oncology drugs in Japan. The median difference over a 13-year period in the approval date between the United States and Japan was 875 days (29.2 months). This figure peaked in 2002, and showed a tendency to decline gradually each year thereafter. In 2014, the median approval lag was 281 days (9.4 months). Multiple regression analysis identified the following potential factors that reduce drug lag: "Japan's participation in global clinical trials"; "bridging strategies"; "designation of priority review in Japan"; and "molecularly targeted drugs". From 2001 to 2014, molecularly targeted drugs emerged as the predominant oncology drug, and the method of development has changed from full development in Japan or bridging strategy to global simultaneous development by Japan's taking part in global clinical trials. In line with these changes, the drug lag between the United States and Japan has significantly reduced to less than 1 year.
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United States National Library of Medicine Drug Information Portal.
Hochstein, Colette; Goshorn, Jeanne; Chang, Florence
2009-01-01
The Drug Information Portal is a free Web resource from the National Library of Medicine (NLM) that provides a user-friendly gateway to current information for more than 15,000 drugs. The site guides users to related resources of NLM, the National Institutes of Health (NIH), and other government agencies. Current drug-related information regarding consumer health, clinical trials, AIDS, MeSH pharmacological actions, MEDLINE/PubMed biomedical literature, and physical properties and structure is easily retrieved by searching on a drug name. A varied selection of focused topics in medicine and drugs is also available from displayed subject headings. This column provides background information about the Drug Information Portal, as well as search basics.
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Deep-Learning-Based Drug-Target Interaction Prediction.
Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei
2017-04-07
Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.
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Dual process interaction model of HIV-risk behaviors among drug offenders.
Ames, Susan L; Grenard, Jerry L; Stacy, Alan W
2013-03-01
This study evaluated dual process interaction models of HIV-risk behavior among drug offenders. A dual process approach suggests that decisions to engage in appetitive behaviors result from a dynamic interplay between a relatively automatic associative system and an executive control system. One synergistic type of interplay suggests that executive functions may dampen or block effects of spontaneously activated associations. Consistent with this model, latent variable interaction analyses revealed that drug offenders scoring higher in affective decision making were relatively protected from predictive effects of spontaneous sex associations promoting risky sex. Among drug offenders with lower levels of affective decision making ability, spontaneous sexually-related associations more strongly predicted risky sex (lack of condom use and greater number of sex partners). These findings help elucidate associative and control process effects on appetitive behaviors and are important for explaining why some individuals engage in risky sex, while others are relatively protected.
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Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities.
Huang, Boshi; Kang, Dongwei; Zhan, Peng; Liu, Xinyong
2015-12-01
The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery. In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress. Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.
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Non-alcoholic fatty liver disease (NAFLD) models in drug discovery.
Cole, Banumathi K; Feaver, Ryan E; Wamhoff, Brian R; Dash, Ajit
2018-02-01
The progressive disease spectrum of non-alcoholic fatty liver disease (NAFLD), which includes non-alcoholic steatohepatitis (NASH), is a rapidly emerging public health crisis with no approved therapy. The diversity of various therapies under development highlights the lack of consensus around the most effective target, underscoring the need for better translatable preclinical models to study the complex progressive disease and effective therapies. Areas covered: This article reviews published literature of various mouse models of NASH used in preclinical studies, as well as complex organotypic in vitro and ex vivo liver models being developed. It discusses translational challenges associated with both kinds of models, and describes some of the studies that validate their application in NAFLD. Expert opinion: Animal models offer advantages of understanding drug distribution and effects in a whole body context, but are limited by important species differences. Human organotypic in vitro and ex vivo models with physiological relevance and translatability need to be used in a tiered manner with simpler screens. Leveraging newer technologies, like metabolomics, proteomics, and transcriptomics, and the future development of validated disease biomarkers will allow us to fully utilize the value of these models to understand disease and evaluate novel drugs in isolation or combination.
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Opportunities for AIDS prevention in a rural state in criminal justice and drug treatment settings.
Farabee, D; Leukefeld, C G
1999-01-01
This study examined the likelihood that drug users would receive HIV/ AIDS prevention information and supplies (e.g., condoms and bleach) in the rural state of Kentucky. Despite evidence of high HIV risk among criminal justice and substance-using populations, incarceration and substance-user treatment were only minimally associated with prior HIV prevention exposure or HIV testing. These data strongly support the use of criminal justice and treatment settings to provide AIDS prevention interventions for the high-risk drug-using populations they serve, and to target HIV prevention services in rural as well as urban areas.
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Directory of Open Access Journals (Sweden)
Medhi Gajendra
2012-04-01
Full Text Available Abstract Background The intersection between illicit drug use and female commercial sex work has been identified as an important factor responsible for rising HIV prevalence among female sex workers (FSW in several northeastern states of India. But, little is know about the factors associated with the use of drugs among FSWs in this region. The objective of the paper was to describe the factors associated with history of drug use among FSWs in Dimapur, an important commercial hub of Nagaland, which is a high HIV prevalence state of India. Methods FSWs were recruited using respondent driven sampling (RDS, and were interviewed to collect data on socio-demographic characteristics and HIV risk behaviours. Biological samples were tested for HIV, syphilis gonorrhea and Chlamydia. Logistic regression analysis was performed to identify factors associated with drug use. Results Among the 426 FSWs in the study, about 25% (n = 107 reported having ever used illicit drugs. Among 107 illicit drug users, 83 (77.6% were non-injecting and 24 (22.4% were injecting drug users. Drug-using FSWs were significantly more likely to test positive for one or more STIs (59% vs. 33.5%, active syphilis (27.1% vs. 11.4% and Chlamydia infection (30% vs. 19.9% compared to their non-drug using peers. Drug-using FSWs were also significantly more likely to be currently married, widowed or separated compared with non-drug-using FSWs. In multiple logistic regression analysis, being an alcohol user, being married, having a larger volume of clients, and having sexual partners who have ever used or shared injecting drugs were found to be independently associated with illicit drug use. Conclusions Drug-using FSWs were more vulnerable to STIs including HIV compared to their non-drug using peers. Several important factors associated with being an FSW who uses drugs were identified in this study and this knowledge can be used to plan more effectively targeted harm reduction strategies
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State-to-state models of vibrational relaxation in Direct Simulation Monte Carlo (DSMC)
Oblapenko, G. P.; Kashkovsky, A. V.; Bondar, Ye A.
2017-02-01
In the present work, the application of state-to-state models of vibrational energy exchanges to the Direct Simulation Monte Carlo (DSMC) is considered. A state-to-state model for VT transitions of vibrational energy in nitrogen and oxygen, based on the application of the inverse Laplace transform to results of quasiclassical trajectory calculations (QCT) of vibrational energy transitions, along with the Forced Harmonic Oscillator (FHO) state-to-state model is implemented in DSMC code and applied to flows around blunt bodies. Comparisons are made with the widely used Larsen-Borgnakke model and the in uence of multi-quantum VT transitions is assessed.
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NCHS - Drug Poisoning Mortality by County: United States
U.S. Department of Health & Human Services — This dataset describes drug poisoning deaths at the county level by selected demographic characteristics and includes age-adjusted death rates for drug poisoning...
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Modeling of corneal and retinal pharmacokinetics after periocular drug administration.
Amrite, Aniruddha C; Edelhauser, Henry F; Kompella, Uday B
2008-01-01
the SD rat corneas. Similar pharmacokinetics models explain drug delivery to the cornea in rat and rabbit animal models. Retinal pharmacokinetics after periocular drug administration can be explained with a four-compartment (periocular space, choroid-containing transfer compartment, retina, and distribution compartment) model with elimination from the periocular space, retina, and choroid compartment. Inclusion of a dissolution-release step before the drug is available for absorption or elimination better explains retinal t(max). Good fits were obtained in both the BN (r = 0.99) and SD (r = 0.99) rats for retinal celecoxib using the same model; however, the parameter estimates differed. Corneal and retinal pharmacokinetics of small lipophilic molecules after periocular administration can be described by compartment models. The modeling analysis shows that (1) leak-back from the site of administration most likely contributes to the apparent lack of an increase phase in corneal concentrations; (2) elimination via the conjunctival or periocular blood and lymphatic systems contributes significantly to drug clearance after periocular injection; (3) corneal pharmacokinetics of small lipophilic molecules can be explained by using similar models in rats and rabbits; and (4) although there are differences in some retinal pharmacokinetics parameters between the pigmented and nonpigmented rats, the physiological basis of these differences has yet to be ascertained.
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Zebrafish as a potential model organism for drug test against hepatitis C virus.
Directory of Open Access Journals (Sweden)
Cun-Bao Ding
Full Text Available Screening and evaluating anti- hepatitis C virus (HCV drugs in vivo is difficult worldwide, mainly because of the lack of suitable small animal models. We investigate whether zebrafish could be a model organism for HCV replication. To achieve NS5B-dependent replication an HCV sub-replicon was designed and created with two vectors, one with HCV ns5b and fluorescent rfp genes, and the other containing HCV's 5'UTR, core, 3'UTR and fluorescent gfp genes. The vectors containing sub-replicons were co-injected into zebrafish zygotes. The sub-replicon amplified in liver showing a significant expression of HCV core RNA and protein. The sub-replicon amplification caused no abnormality in development and growth of zebrafish larvae, but induced gene expression change similar to that in human hepatocytes. As the amplified core fluorescence in live zebrafish was detectable microscopically, it rendered us an advantage to select those with replicating sub-replicon for drug experiments. Ribavirin and oxymatrine, two known anti-HCV drugs, inhibited sub-replicon amplification in this model showing reduced levels of HCV core RNA and protein. Technically, this method had a good reproducibility and is easy to operate. Thus, zebrafish might be a model organism to host HCV, and this zebrafish/HCV (sub-replicon system could be an animal model for anti-HCV drug screening and evaluation.
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Namouchi, Amine; Cimino, Mena; Favre-Rochex, Sandrine; Charles, Patricia; Gicquel, Brigitte
2017-07-13
Tuberculosis (TB) is caused by Mycobacterium tuberculosis and represents one of the major challenges facing drug discovery initiatives worldwide. The considerable rise in bacterial drug resistance in recent years has led to the need of new drugs and drug regimens. Model systems are regularly used to speed-up the drug discovery process and circumvent biosafety issues associated with manipulating M. tuberculosis. These include the use of strains such as Mycobacterium smegmatis and Mycobacterium marinum that can be handled in biosafety level 2 facilities, making high-throughput screening feasible. However, each of these model species have their own limitations. We report and describe the first complete genome sequence of Mycobacterium aurum ATCC23366, an environmental mycobacterium that can also grow in the gut of humans and animals as part of the microbiota. This species shows a comparable resistance profile to that of M. tuberculosis for several anti-TB drugs. The aims of this study were to (i) determine the drug resistance profile of a recently proposed model species, Mycobacterium aurum, strain ATCC23366, for anti-TB drug discovery as well as Mycobacterium smegmatis and Mycobacterium marinum (ii) sequence and annotate the complete genome sequence of this species obtained using Pacific Bioscience technology (iii) perform comparative genomics analyses of the various surrogate strains with M. tuberculosis (iv) discuss how the choice of the surrogate model used for drug screening can affect the drug discovery process. We describe the complete genome sequence of M. aurum, a surrogate model for anti-tuberculosis drug discovery. Most of the genes already reported to be associated with drug resistance are shared between all the surrogate strains and M. tuberculosis. We consider that M. aurum might be used in high-throughput screening for tuberculosis drug discovery. We also highly recommend the use of different model species during the drug discovery screening process.
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Modeling per capita state health expenditure variation: state-level characteristics matter.
Cuckler, Gigi; Sisko, Andrea
2013-01-01
In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.
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International Nuclear Information System (INIS)
Wang, Feng; Calvayrac, Florent; Montembault, Véronique; Fontaine, Laurent
2015-01-01
Thermal transport in the environment close to the periphery of the nanoparticle, from a few angstroms to less than a nanometer scale, is becoming increasingly important with the advent of several biomedical applications of multifunctional magnetic nanoparticles, including drug delivery, magnetic resonance imaging, and hyperthermia therapy. We present a multiscale and multiphysics model of the irradiation by electromagnetic waves of radiofrequency of iron oxide nanoparticles functionalized by drug-releasing polymers used as new multifunctional therapeutic compounds against tumors. We compute ab initio the thermal conductivity of the polymer chains as a function of the length, model the unfolding of the polymer after heat transfer from the nanoparticle by molecular mechanics, and develop a multiscale thermodynamic and heat transfer model including the surrounding medium (water) in order to model the drug release. (paper)
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Directory of Open Access Journals (Sweden)
Fatma E. El-Khouly
2017-10-01
Full Text Available Despite decades of clinical trials for diffuse intrinsic pontine glioma (DIPG, patient survival does not exceed 10% at two years post-diagnosis. Lack of benefit from systemic chemotherapy may be attributed to an intact bloodbrain barrier (BBB. We aim to develop a theoretical model including relevant physicochemical properties in order to review whether applied chemotherapeutics are suitable for passive diffusion through an intact BBB or whether local administration via convection-enhanced delivery (CED may increase their therapeutic potential. Physicochemical properties (lipophilicity, molecular weight, and charge in physiological environment of anticancer drugs historically and currently administered to DIPG patients, that affect passive diffusion over the BBB, were included in the model. Subsequently, the likelihood of BBB passage of these drugs was ascertained, as well as their potential for intratumoral administration via CED. As only non-molecularly charged, lipophilic, and relatively small sized drugs are likely to passively diffuse through the BBB, out of 51 drugs modeled, only 8 (15%—carmustine, lomustine, erlotinib, vismodegib, lenalomide, thalidomide, vorinostat, and mebendazole—are theoretically qualified for systemic administration in DIPG. Local administration via CED might create more therapeutic options, excluding only positively charged drugs and drugs that are either prodrugs and/or only available as oral formulation. A wide variety of drugs have been administered systemically to DIPG patients. Our model shows that only few are likely to penetrate the BBB via passive diffusion, which may partly explain the lack of efficacy. Drug distribution via CED is less dependent on physicochemical properties and may increase the therapeutic options for DIPG.
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In silico modeling predicts drug sensitivity of patient-derived cancer cells.
Pingle, Sandeep C; Sultana, Zeba; Pastorino, Sandra; Jiang, Pengfei; Mukthavaram, Rajesh; Chao, Ying; Bharati, Ila Sri; Nomura, Natsuko; Makale, Milan; Abbasi, Taher; Kapoor, Shweta; Kumar, Ansu; Usmani, Shahabuddin; Agrawal, Ashish; Vali, Shireen; Kesari, Santosh
2014-05-21
Glioblastoma (GBM) is an aggressive disease associated with poor survival. It is essential to account for the complexity of GBM biology to improve diagnostic and therapeutic strategies. This complexity is best represented by the increasing amounts of profiling ("omics") data available due to advances in biotechnology. The challenge of integrating these vast genomic and proteomic data can be addressed by a comprehensive systems modeling approach. Here, we present an in silico model, where we simulate GBM tumor cells using genomic profiling data. We use this in silico tumor model to predict responses of cancer cells to targeted drugs. Initially, we probed the results from a recent hypothesis-independent, empirical study by Garnett and co-workers that analyzed the sensitivity of hundreds of profiled cancer cell lines to 130 different anticancer agents. We then used the tumor model to predict sensitivity of patient-derived GBM cell lines to different targeted therapeutic agents. Among the drug-mutation associations reported in the Garnett study, our in silico model accurately predicted ~85% of the associations. While testing the model in a prospective manner using simulations of patient-derived GBM cell lines, we compared our simulation predictions with experimental data using the same cells in vitro. This analysis yielded a ~75% agreement of in silico drug sensitivity with in vitro experimental findings. These results demonstrate a strong predictability of our simulation approach using the in silico tumor model presented here. Our ultimate goal is to use this model to stratify patients for clinical trials. By accurately predicting responses of cancer cells to targeted agents a priori, this in silico tumor model provides an innovative approach to personalizing therapy and promises to improve clinical management of cancer.
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Berezhkovskiy, Leonid M
2013-02-01
The steady state, V(ss), terminal volume of distribution, V(β), and the terminal half-life, t(1/2), are commonly obtained from the drug plasma concentration-time profile, C(p)(t), following intravenous dosing. Unlike V(ss) that can be calculated based on the physicochemical properties of drugs considering the equilibrium partitioning between plasma and organ tissues, t(1/2) and V(β) cannot be calculated that way because they depend on the rates of drug transfer between blood and tissues. Considering the physiological pharmacokinetic model pertinent to the terminal phase of drug elimination, a novel equation that calculates t(1/2) (and consequently V(β)) was derived. It turns out that V(ss), the total body clearance, Cl, equilibrium blood-plasma concentration ratio, r; and the physiological parameters of the body such as cardiac output, and blood and tissue volumes are sufficient for determination of terminal kinetics. Calculation of t(1/2) by the obtained equation appears to be in good agreement with the experimentally observed vales of this parameter in pharmacokinetic studies in rat, monkey, dog, and human. The equation for the determination of the pre-exponent of the terminal phase of C(p)(t) is also found. The obtained equation allows to predict t(1/2) in human assuming that V(ss) and Cl were either obtained by allometric scaling or, respectively, calculated in silico or based on in vitro drug stability measurements. For compounds that have high clearance, the derived equation may be applied to calculate r just using the routine data on Cl, V(ss), and t(1/2), rather than doing the in vitro assay to measure this parameter. Copyright © 2012 Wiley Periodicals, Inc.
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Tracking Ecstasy Trends in the United States with Data from Three National Drug Surveillance Systems
Yacoubian, George S., Jr.
2003-01-01
Anecdotal reports have suggested that the use of 3,4-methylenedioxymeth-amphetamine (MDMA or "ecstasy") is a prodigious problem across the United States. Unfortunately, no longitudinal evidence exists to support this contention. In the current study, data from the Drug Abuse Warning Network (DAWN), Monitoring the Future (MTF), and…
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THE JUST DRUG DISTRIBUTION IN THE PERSPECTIVE OF WELFARE STATE
Directory of Open Access Journals (Sweden)
Aktieva Tri Tjitrawati
2014-03-01
Full Text Available States have obligations to improve equitability of welfare and prosperity of the community. Pharmaceutical is one of the important and strategic industries because of its vital role to support the development of health sector. Lack of regulation on pricing-products, and diversion of social aspects in the drugs trade, either by government or industry, are associated with the paradigm that underlies regulation of the distributions. Prospective policy analysis and functional approach of law are used to find a level of balance of various interest related to the subject, and to find concepts as a basis to construct new paradigm on drugs distribution. Negara berkewajiban untuk meningkatkan kesejahteraan dan kemakmuran masyarakat secara berkeadilan. Industri farmasi merupakan salah satu industri penting dan strategis karena perannya yang vital menunjang pembangunan bidang kesehatan.Terdapat kecenderungan kurangnya peran Pemerintah dalam pricing policy obat, serta diabaikannya aspek sosial dalam perdagangan produk farmasi, baik oleh Pemerintah maupun industri farmasi. Carut marut ini berkaitan dengan ketidakjelasan paradigma yang berujung pada ketidakjelasan kebijakan yang melandasi tatanan distribusi obat. Makalah ini menggunakan analisis kebijakan prospektif dan pendekatan fungsional hukum untuk mengkaji kebijakan distribusi obat yang bersifat multi disiplin dan menemukan konsep baru untuk menemukan titik keseimbangan dari berbagai kepentingan terkait.
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Mucus as a Barrier to Drug Delivery
DEFF Research Database (Denmark)
Bøgh, Marie; Nielsen, Hanne Mørck
2015-01-01
Viscoelastic mucus lines all mucosal surfaces of the body and forms a potential barrier to mucosal drug delivery. Mucus is mainly composed of water and mucins; high-molecular weight glycoproteins forming an entangled network. Consequently, mucus forms a steric barrier and due to its negative charge...... barrier to drug delivery. Current knowledge of mucus characteristics and barrier properties, as achieved by state-of-the-art methodologies, is the topic of this MiniReview emphasizing the gastrointestinal mucus and an overall focus on oral drug delivery. Cell culture-based in vitro models are well......, studies of peptide and protein drug diffusion in and through mucus and studies of mucus-penetrating nanoparticles are included to illustrate the mucus as a potentially important barrier to obtain sufficient bioavailability of orally administered drugs, and thus an important parameter to address...
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Functional State Modelling of Saccharomyces cerevisiae Cultivations
Directory of Open Access Journals (Sweden)
Iasen Hristozov
2004-10-01
Full Text Available The implementation of functional state approach for modelling of yeast cultivation is considered in this paper. This concept helps in monitoring and control of complex processes such as bioprocesses. Using of functional state modelling approach for fermentation processes aims to overcome the main disadvantage of using global process model, namely complex model structure and big number of model parameters. The main advantage of functional state modelling is that the parameters of each local model can be separately estimated from other local models parameters. The results achieved from batch, as well as from fed-batch, cultivations are presented.
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International Nuclear Information System (INIS)
Wen, Z.; Liao, Q.; Hu, Y.; You, L.; Zhou, L.; Zhao, Y.
2013-01-01
Current therapy for pancreatic cancer is multimodal, involving surgery and chemotherapy. However, development of pancreatic cancer therapies requires a thorough evaluation of drug efficacy in vitro before animal testing and subsequent clinical trials. Compared to two-dimensional culture of cell monolayer, three-dimensional (3-D) models more closely mimic native tissues, since the tumor microenvironment established in 3-D models often plays a significant role in cancer progression and cellular responses to the drugs. Accumulating evidence has highlighted the benefits of 3-D in vitro models of various cancers. In the present study, we have developed a spheroid-based, 3-D culture of pancreatic cancer cell lines MIAPaCa-2 and PANC-1 for pancreatic drug testing, using the acid phosphatase assay. Drug efficacy testing showed that spheroids had much higher drug resistance than monolayers. This model, which is characteristically reproducible and easy and offers rapid handling, is the preferred choice for filling the gap between monolayer cell cultures and in vivo models in the process of drug development and testing for pancreatic cancer
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Directory of Open Access Journals (Sweden)
Z. Wen
2013-08-01
Full Text Available Current therapy for pancreatic cancer is multimodal, involving surgery and chemotherapy. However, development of pancreatic cancer therapies requires a thorough evaluation of drug efficacy in vitro before animal testing and subsequent clinical trials. Compared to two-dimensional culture of cell monolayer, three-dimensional (3-D models more closely mimic native tissues, since the tumor microenvironment established in 3-D models often plays a significant role in cancer progression and cellular responses to the drugs. Accumulating evidence has highlighted the benefits of 3-D in vitro models of various cancers. In the present study, we have developed a spheroid-based, 3-D culture of pancreatic cancer cell lines MIAPaCa-2 and PANC-1 for pancreatic drug testing, using the acid phosphatase assay. Drug efficacy testing showed that spheroids had much higher drug resistance than monolayers. This model, which is characteristically reproducible and easy and offers rapid handling, is the preferred choice for filling the gap between monolayer cell cultures and in vivo models in the process of drug development and testing for pancreatic cancer.
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The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence.
El Rawas, Rana; Saria, Alois
2016-03-01
Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug's effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or "agonistic" versus the hostile or "antagonistic" social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence.
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Hindered disulfide bonds to regulate release rate of model drug from mesoporous silica.
Nadrah, Peter; Maver, Uroš; Jemec, Anita; Tišler, Tatjana; Bele, Marjan; Dražić, Goran; Benčina, Mojca; Pintar, Albin; Planinšek, Odon; Gaberšček, Miran
2013-05-01
With the advancement of drug delivery systems based on mesoporous silica nanoparticles (MSNs), a simple and efficient method regulating the drug release kinetics is needed. We developed redox-responsive release systems with three levels of hindrance around the disulfide bond. A model drug (rhodamine B dye) was loaded into MSNs' mesoporous voids. The pore opening was capped with β-cyclodextrin in order to prevent leakage of drug. Indeed, in absence of a reducing agent the systems exhibited little leakage, while the addition of dithiothreitol cleaved the disulfide bonds and enabled the release of cargo. The release rate and the amount of released dye were tuned by the level of hindrance around disulfide bonds, with the increased hindrance causing a decrease in the release rate as well as in the amount of released drug. Thus, we demonstrated the ability of the present mesoporous systems to intrinsically control the release rate and the amount of the released cargo by only minor structural variations. Furthermore, an in vivo experiment on zebrafish confirmed that the present model delivery system is nonteratogenic.
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Multi-state modeling of biomolecules.
Directory of Open Access Journals (Sweden)
Melanie I Stefan
2014-09-01
Full Text Available Multi-state modeling of biomolecules refers to a series of techniques used to represent and compute the behavior of biological molecules or complexes that can adopt a large number of possible functional states. Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: the problem of how to describe and specify a multi-state system (the "specification problem" and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem". To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler, and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators fall into two further categories: nonspatial simulators, such as StochSim, DYNSTOC, RuleMonkey, and the Network-Free Stochastic Simulator (NFSim, and spatial simulators, including Meredys, SRSim, and MCell. Modelers can thus choose from a variety of tools, the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.
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Dressler, J; Müller, E
1997-09-01
Germany was divided into two parts after World War II. The closed border and a nonconvertible currency in the Eastern part were the factors that did not allow a drug market to develop. Alcohol and medicaments were used as substitute drugs. Since Germany was reunified 5 years ago, there are now the same conditions prevailing for the procurement and sale of drugs in East Germany as there are in the Western German states. This report describes the current state of drug traffic, especially in Saxony, under the new social conditions.
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Fogel, Joshua; Shlivko, Alexander
2016-01-02
Reality television watching and social media use are popular activities. Reality television can include mention of illegal drug use and prescription drug misuse. To determine if reality television and social media use of Twitter are associated with either illegal drug use or prescription drug misuse. Survey of 576 college students in 2011. Independent variables included watching reality television (social cognitive theory), parasocial interaction (parasocial interaction theory), television hours watched (cultivation theory), following a reality television character on Twitter, and demographics. Outcome variables were illegal drug use and prescription drug misuse. Watching reality television and also identifying with reality TV program characters were each associated with greater odds for illegal drug use. Also, following a reality TV character on Twitter had greater odds for illegal drug use and also in one analytical model for prescription drug misuse. No support was seen for cultivation theory. Those born in the United States had greater odds for illegal drug use and prescription drug misuse. Women and Asians had lower odds for illegal drug use. African Americans and Asians had lower odds for prescription drug misuse. Physicians, psychologists, and other healthcare practitioners may find it useful to include questions in their clinical interview about reality television watching and Twitter use. Physician and psychology groups, public health practitioners, and government health agencies should consider discussing with television broadcasting companies the potential negative impact of including content with illegal drugs and prescription drug misuse on reality television programs.
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Hughes, Caitlin E; Ritter, Alison; Cowdery, Nicholas; Sindicich, Natasha
2014-11-01
Legal thresholds for drug trafficking, over which possession of an illicit drug is deemed 'trafficking' as opposed to 'personal use', are employed in all Australian states and territories excepting Queensland. In this paper, we explore the extent to which people who regularly inject drugs understand such laws. Participants from the seven affected states/territories in the 2012 Illicit Drug Reporting System (n = 823) were asked about their legal knowledge of trafficking thresholds: whether, if arrested, quantity possessed would affect legal action taken; and the quantities of heroin, methamphetamine, cocaine and cannabis that would constitute an offence of supply. Data were compared against the actual laws to identify the accuracy of knowledge by drug type and state, and sociodemographics, use and purchasing patterns related to knowledge. Most Illicit Drug Reporting System participants (77%) correctly said that quantity possessed would affect charge received. However, only 55.8% nominated any specific quantity that would constitute an offence of supply, and of those 22.6% nominated a wrong quantity, namely a quantity that was larger than the actual quantity for supply (this varied by state and drug). People who regularly inject drugs have significant gaps in knowledge about Australian legal thresholds for drug trafficking, particularly regarding the actual threshold quantities. This suggests that there may be a need to improve education for this population. Necessity for accurate knowledge would also be lessened by better design of Australian drug trafficking laws. © 2014 Australasian Professional Society on Alcohol and other Drugs.
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Carbon nanotubes buckypapers for potential transdermal drug delivery
International Nuclear Information System (INIS)
Schwengber, Alex; Prado, Héctor J.; Zilli, Darío A.; Bonelli, Pablo R.
2015-01-01
Drug loaded buckypapers based on different types of carbon nanotubes (CNTs) were prepared and characterized in order to evaluate their potentialities for the design of novel transdermal drug delivery systems. Lab-synthesized CNTs as well as commercial samples were employed. Clonidine hydrochloride was used as model drug, and the influence of composition of the drug loaded buckypapers and processing variables on in vitro release profiles was investigated. To examine the influence of the drug nature the evaluation was further extended to buckypapers prepared with flurbiprofen and one type of CNTs, their selection being based on the results obtained with the former drug. Scanning electronic microscopy images indicated that the model drugs were finely dispersed on the CNTs. Differential scanning calorimetry, and X-ray diffraction pointed to an amorphous state of both drugs in the buckypapers. A higher degree of CNT–drug superficial interactions resulted in a slower release of the drug. These interactions were in turn affected by the type of CNTs employed (single wall or multiwall CNTs), their functionalization with hydroxyl or carboxyl groups, the chemical structure of the drug, and the CNT:drug mass ratio. Furthermore, the application of a second layer of drug free CNTs on the loaded buckypaper, led to decelerate the drug release and to reduce the burst effect. - Highlights: • Drug loaded buckypapers from carbon nanotubes were prepared and characterized. • Their potentialities for transdermal drug delivery applications were evaluated. • Characteristics of carbon nanotubes and the structure of the drug affected release • A higher carbon nanotube:drug mass ratio decelerated release • Up to one week controlled release profiles were obtained for the drug flurbiprofen
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Carbon nanotubes buckypapers for potential transdermal drug delivery
Energy Technology Data Exchange (ETDEWEB)
Schwengber, Alex [PINMATE-Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA Buenos Aires (Argentina); Prado, Héctor J. [PINMATE-Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA Buenos Aires (Argentina); Cátedra de Tecnología Farmacéutica II, Departamento de Tecnología Farmacéutica, Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Junín 956, C1113AAD Buenos Aires (Argentina); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); Zilli, Darío A. [PINMATE-Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA Buenos Aires (Argentina); Bonelli, Pablo R. [PINMATE-Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA Buenos Aires (Argentina); Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Av. Rivadavia 1917, C1033AAJ Buenos Aires (Argentina); and others
2015-12-01
Drug loaded buckypapers based on different types of carbon nanotubes (CNTs) were prepared and characterized in order to evaluate their potentialities for the design of novel transdermal drug delivery systems. Lab-synthesized CNTs as well as commercial samples were employed. Clonidine hydrochloride was used as model drug, and the influence of composition of the drug loaded buckypapers and processing variables on in vitro release profiles was investigated. To examine the influence of the drug nature the evaluation was further extended to buckypapers prepared with flurbiprofen and one type of CNTs, their selection being based on the results obtained with the former drug. Scanning electronic microscopy images indicated that the model drugs were finely dispersed on the CNTs. Differential scanning calorimetry, and X-ray diffraction pointed to an amorphous state of both drugs in the buckypapers. A higher degree of CNT–drug superficial interactions resulted in a slower release of the drug. These interactions were in turn affected by the type of CNTs employed (single wall or multiwall CNTs), their functionalization with hydroxyl or carboxyl groups, the chemical structure of the drug, and the CNT:drug mass ratio. Furthermore, the application of a second layer of drug free CNTs on the loaded buckypaper, led to decelerate the drug release and to reduce the burst effect. - Highlights: • Drug loaded buckypapers from carbon nanotubes were prepared and characterized. • Their potentialities for transdermal drug delivery applications were evaluated. • Characteristics of carbon nanotubes and the structure of the drug affected release • A higher carbon nanotube:drug mass ratio decelerated release • Up to one week controlled release profiles were obtained for the drug flurbiprofen.
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Xue, Caifu; Zhang, Xunjie; Cai, Weimin
2017-12-21
The potential of inhibitory metabolites of perpetrator drugs to contribute to drug-drug interactions (DDIs) is uncommon and underestimated. However, the occurrence of unexpected DDI suggests the potential contribution of metabolites to the observed DDI. The aim of this study was to develop a physiologically-based pharmacokinetic (PBPK) model for bupropion and its three primary metabolites-hydroxybupropion, threohydrobupropion and erythrohydrobupropion-based on a mixed "bottom-up" and "top-down" approach and to contribute to the understanding of the involvement and impact of inhibitory metabolites for DDIs observed in the clinic. PK profiles from clinical researches of different dosages were used to verify the bupropion model. Reasonable PK profiles of bupropion and its metabolites were captured in the PBPK model. Confidence in the DDI prediction involving bupropion and co-administered CYP2D6 substrates could be maximized. The predicted maximum concentration (C max ) area under the concentration-time curve (AUC) values and C max and AUC ratios were consistent with clinically observed data. The addition of the inhibitory metabolites into the PBPK model resulted in a more accurate prediction of DDIs (AUC and C max ratio) than that which only considered parent drug (bupropion) P450 inhibition. The simulation suggests that bupropion and its metabolites contribute to the DDI between bupropion and CYP2D6 substrates. The inhibitory potency from strong to weak is hydroxybupropion, threohydrobupropion, erythrohydrobupropion, and bupropion, respectively. The present bupropion PBPK model can be useful for predicting inhibition from bupropion in other clinical studies. This study highlights the need for caution and dosage adjustment when combining bupropion with medications metabolized by CYP2D6. It also demonstrates the feasibility of applying the PBPK approach to predict the DDI potential of drugs undergoing complex metabolism, especially in the DDI involving inhibitory
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Predictive modeling of structured electronic health records for adverse drug event detection.
Zhao, Jing; Henriksson, Aron; Asker, Lars; Boström, Henrik
2015-01-01
The digitization of healthcare data, resulting from the increasingly widespread adoption of electronic health records, has greatly facilitated its analysis by computational methods and thereby enabled large-scale secondary use thereof. This can be exploited to support public health activities such as pharmacovigilance, wherein the safety of drugs is monitored to inform regulatory decisions about sustained use. To that end, electronic health records have emerged as a potentially valuable data source, providing access to longitudinal observations of patient treatment and drug use. A nascent line of research concerns predictive modeling of healthcare data for the automatic detection of adverse drug events, which presents its own set of challenges: it is not yet clear how to represent the heterogeneous data types in a manner conducive to learning high-performing machine learning models. Datasets from an electronic health record database are used for learning predictive models with the purpose of detecting adverse drug events. The use and representation of two data types, as well as their combination, are studied: clinical codes, describing prescribed drugs and assigned diagnoses, and measurements. Feature selection is conducted on the various types of data to reduce dimensionality and sparsity, while allowing for an in-depth feature analysis of the usefulness of each data type and representation. Within each data type, combining multiple representations yields better predictive performance compared to using any single representation. The use of clinical codes for adverse drug event detection significantly outperforms the use of measurements; however, there is no significant difference over datasets between using only clinical codes and their combination with measurements. For certain adverse drug events, the combination does, however, outperform using only clinical codes. Feature selection leads to increased predictive performance for both data types, in isolation and
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Stability Analysis of an HIV/AIDS Dynamics Model with Drug Resistance
Directory of Open Access Journals (Sweden)
Qianqian Li
2012-01-01
Full Text Available A mathematical model of HIV/AIDS transmission incorporating treatment and drug resistance was built in this study. We firstly calculated the threshold value of the basic reproductive number (R0 by the next generation matrix and then analyzed stability of two equilibriums by constructing Lyapunov function. When R0<1, the system was globally asymptotically stable and converged to the disease-free equilibrium. Otherwise, the system had a unique endemic equilibrium which was also globally asymptotically stable. While an antiretroviral drug tried to reduce the infection rate and prolong the patients’ survival, drug resistance was neutralizing the effects of treatment in fact.
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Cognitive Enhancers for Facilitating Drug Cue Extinction: Insights from Animal Models
Nic Dhonnchadha, Bríd Áine; Kantak, Kathleen M.
2011-01-01
Given the success of cue exposure (extinction) therapy combined with a cognitive enhancer for reducing anxiety, it is anticipated that this approach will prove more efficacious than exposure therapy alone in preventing relapse in individuals with substance use disorders. Several factors may undermine the efficacy of exposure therapy for substance use disorders, but we suspect that neurocognitive impairments associated with chronic drug use are an important contributing factor. Numerous insights on these issues are gained from research using animal models of addiction. In this review, the relationship between brain sites whose learning, memory and executive functions are impaired by chronic drug use and brain sites that are important for effective drug cue extinction learning is explored first. This is followed by an overview of animal research showing improved treatment outcome for drug addiction (e.g. alcohol, amphetamine, cocaine, heroin) when explicit extinction training is conducted in combination with acute dosing of a cognitive-enhancing drug. The mechanism by which cognitive enhancers are thought to exert their benefits is by facilitating consolidation of drug cue extinction memory after activation of glutamatergic receptors. Based on the encouraging work in animals, factors that may be important for the treatment of drug addiction are considered. PMID:21295059
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Five-Factor Model personality profiles of drug users
Directory of Open Access Journals (Sweden)
Crum Rosa M
2008-04-01
Full Text Available Abstract Background Personality traits are considered risk factors for drug use, and, in turn, the psychoactive substances impact individuals' traits. Furthermore, there is increasing interest in developing treatment approaches that match an individual's personality profile. To advance our knowledge of the role of individual differences in drug use, the present study compares the personality profile of tobacco, marijuana, cocaine, and heroin users and non-users using the wide spectrum Five-Factor Model (FFM of personality in a diverse community sample. Method Participants (N = 1,102; mean age = 57 were part of the Epidemiologic Catchment Area (ECA program in Baltimore, MD, USA. The sample was drawn from a community with a wide range of socio-economic conditions. Personality traits were assessed with the Revised NEO Personality Inventory (NEO-PI-R, and psychoactive substance use was assessed with systematic interview. Results Compared to never smokers, current cigarette smokers score lower on Conscientiousness and higher on Neuroticism. Similar, but more extreme, is the profile of cocaine/heroin users, which score very high on Neuroticism, especially Vulnerability, and very low on Conscientiousness, particularly Competence, Achievement-Striving, and Deliberation. By contrast, marijuana users score high on Openness to Experience, average on Neuroticism, but low on Agreeableness and Conscientiousness. Conclusion In addition to confirming high levels of negative affect and impulsive traits, this study highlights the links between drug use and low Conscientiousness. These links provide insight into the etiology of drug use and have implications for public health interventions.
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Barreto, Maria Nelly Sobreira de Carvalho; Cesse, Eduarda Ângela Pessoa; Lima, Rodrigo Fonseca; Marinho, Michelly Geórgia da Silva; Specht, Yuri da Silva; de Carvalho, Eduardo Maia Freese; Fontbonne, Annick
2015-01-01
To evaluate the access to drugs for hypertension and diabetes and the direct cost of buying them among users of the Family Health Strategy (FHS) in the state of Pernambuco, Brazil. Population-based, cross-sectional study of a systematic random sample of 785 patients with hypertension and 823 patients with diabetes mellitus who were registered in 208 randomly selected FHS teams in 35 municipalities of the state of Pernambuco. The selected municipalities were classified into three levels with probability proportional to municipality size (LS, large-sized; MS, medium-sized; SS, small-sized). To verify differences between the cities, we used the χ2 test. Pharmacological treatment was used by 91.2% patients with hypertension whereas 85.6% patients with diabetes mellitus used oral antidiabetic drugs (OADs), and 15.4% used insulin. The FHS team itself provided antihypertensive medications to 69.0% patients with hypertension, OADs to 75.0% patients with diabetes mellitus, and insulin treatment to 65.4%. The 36.9% patients with hypertension and 29.8% with diabetes mellitus that had to buy all or part of their medications reported median monthly cost of R$ 18.30, R$ 14.00, and R$ 27.61 for antihypertensive drugs, OADs, and insulin, respectively. It is necessary to increase efforts to ensure access to these drugs in the primary health care network.
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Directory of Open Access Journals (Sweden)
Maria Nelly Sobreira de Carvalho Barreto
2015-06-01
Full Text Available OBJECTIVE: To evaluate the access to drugs for hypertension and diabetes and the direct cost of buying them among users of the Family Health Strategy (FHS in the state of Pernambuco, Brazil.METHODS: Population-based, cross-sectional study of a systematic random sample of 785 patients with hypertension and 823 patients with diabetes mellitus who were registered in 208 randomly selected FHS teams in 35 municipalities of the state of Pernambuco. The selected municipalities were classified into three levels with probability proportional to municipality size (LS, large-sized; MS, medium-sized; SS, small-sized. To verify differences between the cities, we used the χ2 test.RESULTS: Pharmacological treatment was used by 91.2% patients with hypertension whereas 85.6% patients with diabetes mellitus used oral antidiabetic drugs (OADs, and 15.4% used insulin. The FHS team itself provided antihypertensive medications to 69.0% patients with hypertension, OADs to 75.0% patients with diabetes mellitus, and insulin treatment to 65.4%. The 36.9% patients with hypertension and 29.8% with diabetes mellitus that had to buy all or part of their medications reported median monthly cost of R$ 18.30, R$ 14.00, and R$ 27.61 for antihypertensive drugs, OADs, and insulin, respectively.CONCLUSION: It is necessary to increase efforts to ensure access to these drugs in the primary health care network.
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The History of MDMA as an Underground Drug in the United States, 1960-1979.
Passie, Torsten; Benzenhöfer, Udo
2016-01-01
MDMA (3,4-methylenedioxy-methylamphetamine, a.k.a. "ecstasy") was first synthesized in 1912 and resynthesized more than once for pharmaceutical reasons before it became a popular recreational drug. Partially based on previously overlooked U.S. government documentation, this article reconstructs the early history of MDMA as a recreational drug in the U.S. from 1960 to 1979. According to the literature, MDMA was introduced as a street drug at the end of the 1960s. The first forensic detection of MDMA "on the street" was reported in 1970 in Chicago. It appears that MDMA was first synthesized by underground chemists in search of "legal alternatives" for the closely related and highly sought-after drug MDA, which was scheduled under the Controlled Substances Act (CSA) in 1970. Until 1974, nearly all MDMA street samples seized came from the U.S. Midwest, the first "hot region" of MDMA use. In Canada, MDMA was first detected in 1974 and scheduled in 1976. From 1975 to 1979, MDMA was found in street samples in more than 10 U.S. states, the West Coast becoming the major "hot region" of MDMA use. Recreational use of MDMA spread across the U.S. in the early 1980s, and in 1985 it was scheduled under the CSA.
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Huber, Robert; Panksepp, Jules B; Nathaniel, Thomas; Alcaro, Antonio; Panksepp, Jaak
2011-10-01
In mammals, rewarding properties of drugs depend on their capacity to activate appetitive motivational states. With the underlying mechanisms strongly conserved in evolution, invertebrates have recently emerged as a powerful new model in addiction research. In crayfish natural reward has proven surprisingly sensitive to human drugs of abuse, opening an unlikely avenue of research into the basic biological mechanisms of drug addiction. In a series of studies we first examined the presence of natural reward systems in crayfish, then characterized its sensitivity to a wide range of human drugs of abuse. A conditioned place preference (CPP) paradigm was used to demonstrate that crayfish seek out those environments that had previously been paired with the psychostimulants cocaine and amphetamine, and the opioid morphine. The administration of amphetamine exerted its effects at a number of sites, including the stimulation of circuits for active exploratory behaviors (i.e., SEEKING). A further study examined morphine-induced reward, extinction and reinstatement in crayfish. Repeated intra-circulatory infusions of morphine served as a reward when paired with distinct visual or tactile cues. Morphine-induced CPP was extinguished after repeated saline injections. Following this extinction phase, morphine-experienced crayfish were once again challenged with the drug. The priming injections of morphine reinstated CPP at all tested doses, suggesting that morphine-induced CPP is unrelenting. In an exploration of drug-associated behavioral sensitization in crayfish we concurrently mapped measures of locomotion and rewarding properties of morphine. Single and repeated intra-circulatory infusions of morphine resulted in persistent locomotory sensitization, even 5 days following the infusion. Moreover, a single dose of morphine was sufficient to induce long-term behavioral sensitization. CPP for morphine and context-dependent cues could not be disrupted over a drug free period of 5
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Drug Policy: the "Dutch Model"
van Ooijen-Houben, M.M.J.; Kleemans, E.R.
2015-01-01
Dutch drug policy, once considered pragmatic and lenient and rooted in a generally tolerant attitude toward drug use, has slowly but surely shifted from a primarily public health focus to an increasing focus on law enforcement. The "coffee shop" policy and the policy toward MDMA/ecstasy are
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Updating of states in operational hydrological models
Bruland, O.; Kolberg, S.; Engeland, K.; Gragne, A. S.; Liston, G.; Sand, K.; Tøfte, L.; Alfredsen, K.
2012-04-01
Operationally the main purpose of hydrological models is to provide runoff forecasts. The quality of the model state and the accuracy of the weather forecast together with the model quality define the runoff forecast quality. Input and model errors accumulate over time and may leave the model in a poor state. Usually model states can be related to observable conditions in the catchment. Updating of these states, knowing their relation to observable catchment conditions, influence directly the forecast quality. Norway is internationally in the forefront in hydropower scheduling both on short and long terms. The inflow forecasts are fundamental to this scheduling. Their quality directly influence the producers profit as they optimize hydropower production to market demand and at the same time minimize spill of water and maximize available hydraulic head. The quality of the inflow forecasts strongly depends on the quality of the models applied and the quality of the information they use. In this project the focus has been to improve the quality of the model states which the forecast is based upon. Runoff and snow storage are two observable quantities that reflect the model state and are used in this project for updating. Generally the methods used can be divided in three groups: The first re-estimates the forcing data in the updating period; the second alters the weights in the forecast ensemble; and the third directly changes the model states. The uncertainty related to the forcing data through the updating period is due to both uncertainty in the actual observation and to how well the gauging stations represent the catchment both in respect to temperatures and precipitation. The project looks at methodologies that automatically re-estimates the forcing data and tests the result against observed response. Model uncertainty is reflected in a joint distribution of model parameters estimated using the Dream algorithm.
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Passini, Elisa; Britton, Oliver J; Lu, Hua Rong; Rohrbacher, Jutta; Hermans, An N; Gallacher, David J; Greig, Robert J H; Bueno-Orovio, Alfonso; Rodriguez, Blanca
2017-01-01
Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC 50 /Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca 2+ -transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca 2+ /late Na + currents and Na + /Ca 2+ -exchanger, reduced Na + /K + -pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density
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Directory of Open Access Journals (Sweden)
Elisa Passini
2017-09-01
Full Text Available Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient. Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs. Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density
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College Student Drug Usage in a State System as a Function of Type of Institution
Schoenfeldt, Lyle F.; Strimbu, Jerry L.
1975-01-01
Over 4,500 students from 28 universities, colleges, and junior colleges constituting a state system of higher education were compared on extent of drug use. The largest differences were between universities and junior colleges on alcohol and marihuana. Differences in terms of actual numbers of users were small. Implications are discussed.…
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Advanced surface chemical analysis of continuously manufactured drug loaded composite pellets.
Hossain, Akter; Nandi, Uttom; Fule, Ritesh; Nokhodchi, Ali; Maniruzzaman, Mohammed
2017-04-15
The aim of the present study was to develop and characterise polymeric composite pellets by means of continuous melt extrusion techniques. Powder blends of a steroid hormone (SH) as a model drug and either ethyl cellulose (EC N10 and EC P7 grades) or hydroxypropyl methylcellulose (HPMC AS grade) as polymeric carrier were extruded using a Pharma 11mm twin screw extruder in a continuous mode of operation to manufacture extruded composite pellets of 1mm length. Molecular modelling study using commercial Gaussian 09 software outlined a possible drug-polymer interaction in the molecular level to develop solid dispersions of the drug in the pellets. Solid-state analysis conducted via a differential scanning calorimetry (DSC), hot stage microscopy (HSM) and X-ray powder diffraction (XRPD) analyses revealed the amorphous state of the drug in the polymer matrices. Surface analysis using SEM/energy dispersive X-ray (EDX) of the produced pellets arguably showed a homogenous distribution of the C and O atoms in the pellet matrices. Moreover, advanced chemical surface analysis conducted via atomic force microscopy (AFM) showed a homogenous phase system having the drug molecule dispersed onto the amorphous matrices while Raman mapping confirmed the homogenous single-phase drug distribution in the manufactured composite pellets. Such composite pellets are expected to deliver multidisciplinary applications in drug delivery and medical sciences by e.g. modifying drug solubility/dissolutions or stabilizing the unstable drug (e.g. hormone, protein) in the composite network. Copyright © 2016. Published by Elsevier Inc.
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Artificial emotional model based on finite state machine
Institute of Scientific and Technical Information of China (English)
MENG Qing-mei; WU Wei-guo
2008-01-01
According to the basic emotional theory, the artificial emotional model based on the finite state machine(FSM) was presented. In finite state machine model of emotion, the emotional space included the basic emotional space and the multiple emotional spaces. The emotion-switching diagram was defined and transition function was developed using Markov chain and linear interpolation algorithm. The simulation model was built using Stateflow toolbox and Simulink toolbox based on the Matlab platform.And the model included three subsystems: the input one, the emotion one and the behavior one. In the emotional subsystem, the responses of different personalities to the external stimuli were described by defining personal space. This model takes states from an emotional space and updates its state depending on its current state and a state of its input (also a state-emotion). The simulation model realizes the process of switching the emotion from the neutral state to other basic emotions. The simulation result is proved to correspond to emotion-switching law of human beings.
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Alves, Vânia Sampaio
2009-11-01
This article aims to characterize health care models for users of alcohol and other drugs in the Brazilian context. Discourse analysis was performed on public drug policy in Brazil from the 1970s. This analysis was contextualized by a brief digression on the main political positions identified in several countries of the world in relation to drug use problems. Beginning in the current decade, drug policies in Brazil have been receptive to harm reduction approaches, resulting in reorientation of the health care model. In conclusion, the structuring and strengthening of a network of care for users of alcohol and other drugs and their families, based on community care and the harm reduction approach and combined with other social and health services, is now a key public health challenge for the country.
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State and Community Responses to Drug-related Violence in Mexico
International Development Research Centre (IDRC) Digital Library (Canada)
Violent conflict related to drug trafficking in Mexico has had a profound impact on the ... mostly due to illegal drug trafficking and the government's response to it, ... security forces and drug traffickers or in executions related to the drug trade.
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Formulating state space models in R with focus on longitudinal regression models
DEFF Research Database (Denmark)
Dethlefsen, Claus; Lundbye-Christensen, Søren
We provide a language for formulating a range of state space models. The described methodology is implemented in the R -package sspir available from cran.r-project.org . A state space model is specified similarly to a generalized linear model in R , by marking the time-varying terms in the form...... We provide a language for formulating a range of state space models. The described methodology is implemented in the R -package sspir available from cran.r-project.org . A state space model is specified similarly to a generalized linear model in R , by marking the time-varying terms...
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Energy Technology Data Exchange (ETDEWEB)
Yamini, Yadollah, E-mail: yyamini@modares.ac.ir [Department of Chemistry, Faculty of Sciences, Tarbiat Modares University, P.O. Box 14115-175, Tehran (Iran, Islamic Republic of); Moradi, Morteza [Department of Chemistry, Faculty of Sciences, Tarbiat Modares University, P.O. Box 14115-175, Tehran (Iran, Islamic Republic of)
2011-07-15
Highlights: > Ketoconazole (KZ) and clotrimazole (CZ) are two antifungal drugs. > The solubilities of KZ and CZ were measured in supercritical CO{sub 2}. > The experimental results were correlated using five density based models. > The heats' of drug-CO{sub 2} solvation and drug vaporization were estimated. - Abstract: In the present study the solubilities of two antifungal drugs of ketoconazole and clotrimazole in supercritical carbon dioxide were measured using a simple static method. The experimental data were measured at (308 to 348) K, over the pressure range of (12.2 to 35.5) MPa. The mole fraction solubilities ranged from 0.2 . 10{sup -6} to 17.45 . 10{sup -5}. In this study five density based models were used to calculate the solubility of drugs in supercritical carbon dioxide. The density based models are Chrastil, modified Chrastil, Bartle, modified Bartle and Mendez-Santiago and Teja (M-T). Interaction parameters for the studied models were obtained and the percentage of average absolute relative deviation (AARD%) in each calculation was displayed. The correlation results showed good agreement with the experimental data. A comparison among the five models revealed that the Bartle and its modified models gave much better correlations of the solubility data with an average absolute relative deviation (AARD%) ranging from 4.8% to 6.2% and from 4.5% to 6.3% for ketoconazole and clotrimazole, respectively. Using the correlation results, the heat of drug-CO{sub 2} solvation and that of drug vaporization was separately approximated in the range of (-22.1 to -26.4 and 88.3 to 125.9) kJ . mol{sup -1}.
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Mechanistic systems modeling to guide drug discovery and development.
Schmidt, Brian J; Papin, Jason A; Musante, Cynthia J
2013-02-01
A crucial question that must be addressed in the drug development process is whether the proposed therapeutic target will yield the desired effect in the clinical population. Pharmaceutical and biotechnology companies place a large investment on research and development, long before confirmatory data are available from human trials. Basic science has greatly expanded the computable knowledge of disease processes, both through the generation of large omics data sets and a compendium of studies assessing cellular and systemic responses to physiologic and pathophysiologic stimuli. Given inherent uncertainties in drug development, mechanistic systems models can better inform target selection and the decision process for advancing compounds through preclinical and clinical research. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Lin, Shan-Yang; Wang, Shun-Li
2012-04-01
The solid-state chemistry of drugs has seen growing importance in the pharmaceutical industry for the development of useful API (active pharmaceutical ingredients) of drugs and stable dosage forms. The stability of drugs in various solid dosage forms is an important issue because solid dosage forms are the most common pharmaceutical formulation in clinical use. In solid-state stability studies of drugs, an ideal accelerated method must not only be selected by different complicated methods, but must also detect the formation of degraded product. In this review article, an analytical technique combining differential scanning calorimetry and Fourier-transform infrared (DSC-FTIR) microspectroscopy simulates the accelerated stability test, and simultaneously detects the decomposed products in real time. The pharmaceutical dipeptides aspartame hemihydrate, lisinopril dihydrate, and enalapril maleate either with or without Eudragit E were used as testing examples. This one-step simultaneous DSC-FTIR technique for real-time detection of diketopiperazine (DKP) directly evidenced the dehydration process and DKP formation as an impurity common in pharmaceutical dipeptides. DKP formation in various dipeptides determined by different analytical methods had been collected and compiled. Although many analytical methods have been applied, the combined DSC-FTIR technique is an easy and fast analytical method which not only can simulate the accelerated drug stability testing but also at the same time enable to explore phase transformation as well as degradation due to thermal-related reactions. This technique offers quick and proper interpretations. Copyright © 2012 Elsevier B.V. All rights reserved.
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Model Checking Infinite-State Markov Chains
Remke, Anne Katharina Ingrid; Haverkort, Boudewijn R.H.M.; Cloth, L.
2004-01-01
In this paper algorithms for model checking CSL (continuous stochastic logic) against infinite-state continuous-time Markov chains of so-called quasi birth-death type are developed. In doing so we extend the applicability of CSL model checking beyond the recently proposed case for finite-state
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Photokinetic Drug Delivery: Light-Enhanced Permeation in an In Vitro Eye Model.
Godley, Bernard F; Kraft, Edward R; Giannos, Steven A; Zhao, Zhen-Yang; Haag, Anthony M; Wen, Julie W
2015-12-01
To investigate light-enhanced molecular movement as a potential technology for drug delivery. To do this, we developed an in vitro eye model while representing similar concentration gradient conditions and compositions found in the eye. The eye model unit was fabricated by inserting a cross-linked type I collagen membrane in a spectrophotometer cuvette with 1% hyaluronic acid as the drug recipient medium. Photokinetic delivery was studied by illuminating 1 mg/mL methotrexate (MTX) placed in the drug donor compartment on top of the membrane, with noncoherent 450 nm light at 8.2 mW from an LED source pulsed at 25 cycles per second, placed in contact with the solution. A modified UV-visual spectrophotometer was employed to rapidly determine the concentration of MTX, at progressive 1 mm distances away from the membrane, within the viscous recipient medium of the model eye after 1 h. A defined, progressive concentration gradient was observed within the nonagitated drug recipient media, diminishing with greater distances from the membrane. Transport of MTX through the membrane was significantly enhanced (ranging from 2 to 3 times, P < 0.05 to P ≤ 0.001) by photokinetic methods compared with control conditions by determining drug concentrations at 4 defined distances from the membrane. According to scanning electron microscopy images, no structural damage or shunts were created on the surface of the cross-linked gelatin membrane. The application of pulsed noncoherent visible light significantly enhances the permeation of MTX through a cross-linked collagen membrane and hyaluronic acid recipient medium without causing structural damage to the membrane.
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Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.
Zhang, Wen; Chen, Yanlin; Li, Dingfang
2017-11-25
Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.
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Stem cells: a model for screening, discovery and development of drugs
Directory of Open Access Journals (Sweden)
Kitambi SS
2011-09-01
Full Text Available Satish Srinivas Kitambi1, Gayathri Chandrasekar21Department of Medical Biochemistry and Biophysics; 2Department of Biosciences, Karolinska Institutet, Stockholm, SwedenAbstract: The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficacy studies using stem cells offers a reliable platform for the drug discovery process. Advances made in the generation of induced pluripotent stem cells from normal or diseased tissue serves as a platform to perform drug screens aimed at developing cell-based therapies against conditions like Parkinson's disease and diabetes. This review discusses the application of stem cells and cancer stem cells in drug screening and their role in complementing, reducing, and replacing animal testing. In addition to this, target identification and major advances in the field of personalized medicine using induced pluripotent cells are also discussed.Keywords: therapeutics, stem cells, cancer stem cells, screening models, drug development, high throughput screening
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Drug accumulation by means of noninvasive magnetic drug delivery system
International Nuclear Information System (INIS)
Chuzawa, M.; Mishima, F.; Akiyama, Y.; Nishijima, S.
2011-01-01
The medication is one of the most general treatment methods, but drugs diffuse in the normal tissues other than the target part by the blood circulation. Therefore, side effect in the medication, particularly for a drug with strong effect such as anti-cancer drug, are a serious issue. Drug Delivery System (DDS) which accumulates the drug locally in the human body is one of the techniques to solve the side-effects. Magnetic Drug Delivery System (MDDS) is one of the active DDSs, which uses the magnetic force. The objective of this study is to accumulate the ferromagnetic drugs noninvasively in the deep part of the body by using MDDS. It is necessary to generate high magnetic field and magnetic gradient at the target part to reduce the side-effects to the tissues with no diseases. The biomimetic model was composed, which consists of multiple model organs connected with diverged blood vessel model. The arrangement of magnetic field was examined to accumulate ferromagnetic drug particles in the target model organ by using a superconducting bulk magnet which can generate high magnetic fields. The arrangement of magnet was designed to generate high and stable magnetic field at the target model organ. The accumulation experiment of ferromagnetic particles has been conducted. In this study, rotating HTS bulk magnet around the axis of blood vessels by centering on the target part was suggested, and the model experiment for magnet rotation was conducted. As a result, the accumulation of the ferromagnetic particles to the target model organ in the deep part was confirmed.
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Optimal Control of Drug Therapy in a Hepatitis B Model
Directory of Open Access Journals (Sweden)
Jonathan E. Forde
2016-08-01
Full Text Available Combination antiviral drug therapy improves the survival rates of patients chronically infected with hepatitis B virus by controlling viral replication and enhancing immune responses. Some of these drugs have side effects that make them unsuitable for long-term administration. To address the trade-off between the positive and negative effects of the combination therapy, we investigated an optimal control problem for a delay differential equation model of immune responses to hepatitis virus B infection. Our optimal control problem investigates the interplay between virological and immunomodulatory effects of therapy, the control of viremia and the administration of the minimal dosage over a short period of time. Our numerical results show that the high drug levels that induce immune modulation rather than suppression of virological factors are essential for the clearance of hepatitis B virus.
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Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction
Engleman, Eric A.; Katner, Simon N.; Neal-Beliveau, Bethany S.
2016-01-01
Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH’s effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system–dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine
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Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction.
Engleman, Eric A; Katner, Simon N; Neal-Beliveau, Bethany S
2016-01-01
Drug addiction takes a massive toll on society. Novel animal models are needed to test new treatments and understand the basic mechanisms underlying addiction. Rodent models have identified the neurocircuitry involved in addictive behavior and indicate that rodents possess some of the same neurobiologic mechanisms that mediate addiction in humans. Recent studies indicate that addiction is mechanistically and phylogenetically ancient and many mechanisms that underlie human addiction are also present in invertebrates. The nematode Caenorhabditis elegans has conserved neurobiologic systems with powerful molecular and genetic tools and a rapid rate of development that enables cost-effective translational discovery. Emerging evidence suggests that C. elegans is an excellent model to identify molecular mechanisms that mediate drug-induced behavior and potential targets for medications development for various addictive compounds. C. elegans emit many behaviors that can be easily quantitated including some that involve interactions with the environment. Ethanol (EtOH) is the best-studied drug-of-abuse in C. elegans and at least 50 different genes/targets have been identified as mediating EtOH's effects and polymorphisms in some orthologs in humans are associated with alcohol use disorders. C. elegans has also been shown to display dopamine and cholinergic system-dependent attraction to nicotine and demonstrate preference for cues previously associated with nicotine. Cocaine and methamphetamine have been found to produce dopamine-dependent reward-like behaviors in C. elegans. These behavioral tests in combination with genetic/molecular manipulations have led to the identification of dozens of target genes/systems in C. elegans that mediate drug effects. The one target/gene identified as essential for drug-induced behavioral responses across all drugs of abuse was the cat-2 gene coding for tyrosine hydroxylase, which is consistent with the role of dopamine neurotransmission
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Modelling the encapsulation of the anticancer drug cisplatin into carbon nanotubes
International Nuclear Information System (INIS)
Hilder, Tamsyn A; Hill, James M
2007-01-01
The proposed use of nanocapsules in drug delivery systems promises many advantages over current procedures. The major advantage is the potential for patients to have significantly reduced side effects from taking the drug, especially for highly toxic drugs such as those used for cancer treatments. Nanotubes have been suggested as one such carrier to deliver a drug to a specific site, giving rise to the notion of the 'magic bullet'. The aim of this paper is to determine whether a particular nanotube would accept a particular drug, and to determine the radius of the nanotube that provides the maximum uptake of the drug molecule. In particular, this paper looks at the drug cisplatin, a platinum based anticancer drug widely used in the treatment of tumours. Three orientations of cisplatin, a polar molecule, are investigated as it enters the nanotube. It is shown that, for all three orientations of cisplatin to be accepted into the carbon nanotube, the minimum radius must be at least 4.785 A, which is slightly smaller than a (9, 5) nanotube and that the maximum suction energy occurs when the carbon nanotube radius is approximately 5.3 A, which is approximately equivalent to a (11, 4) nanotube. This paper presents for the first time a calculation of this nature, and although the model represents only a first approximation, it constitutes a necessary preliminary calculation which might provide medical scientists with some overall guidelines
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Dynamics of synthetic drugs transmission model with psychological addicts and general incidence rate
Ma, Mingju; Liu, Sanyang; Xiang, Hong; Li, Jun
2018-02-01
Synthetic drugs are replacing traditional ones and becoming the main popular ones gradually, which have given rise to serious social issues in recent years. In this paper, a synthetic drugs transmission model with psychological addicts and general contact rate is proposed. The local and global stabilities are decided by the basic reproduction number R0. By analyzing the sensitivity of parameters, we obtain that controlling psychological addiction is better than drugs treatment. These results are verified by numerical simulations.
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Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik; Harvey, Jeremy N; Mulholland, Adrian J
2016-06-20
The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site, but this is not a prerequisite for reaction via either mechanism. Several active site residues play a role in the binding of mexiletine in the active site, including Thr124 and Phe226. This work reveals key details of the N-hydroxylation of mexiletine and further demonstrates that mechanistic studies using QM/MM methods are useful for understanding drug metabolism.
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Directory of Open Access Journals (Sweden)
Liu Cong
2011-12-01
Full Text Available Abstract Background Elucidating the effects of drugs on solid tumours is a highly challenging multi-level problem, since this involves many complexities associated with transport and cellular response, which in turn is characterized by highly non-linear chemical signal transduction. Appropriate systems frameworks are needed to seriously address the sources of these complexities, especially from the cellular side. Results We develop a skeletal modelling framework incorporating interstitial drug transport, intracellular signal processing and cell population descriptions. The descriptions aim to appropriately capture the nature of information flow. The model is deliberately formulated to start with simple intracellular descriptions so that additional features can be incorporated in a modular fashion. Two kinds of intracellular signalling modules which describe the drug effect were considered, one a monostable switch and the other a bistable switch. Analysis of our model revealed how different drug stimuli can lead to cell killing in the tumour. Interestingly both modules considered exhibited similar trends. The effects of important parameters were also studied. Conclusions We have created a predictive systems platform integrating drug transport and cellular response which can be systematically augmented to include additional layers of cellular complexity. Our results indicate that intracellular signalling models which are qualitatively different can give rise to similar behaviour to simple (and typical stimuli, and that validating intracellular descriptions must be performed with care by considering a variety of drug stimuli.
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Full Text Available ... HIV infection in the United States. Drugs can change the way the brain works, disrupting the parts ... HIV infection in the United States. Drugs can change the way the brain works, disrupting the parts ...
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Full Text Available ... States. Drugs can change the way the brain works, disrupting the parts of the brain that people ... States. Drugs can change the way the brain works, disrupting the parts of the brain that people ...
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Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies.
Williamson, Beth; Riley, Robert J
2017-12-01
Drug-drug interactions (DDIs) continue to account for 5% of hospital admissions and therefore remain a major regulatory concern. Effective, quantitative prediction of DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations rather than concentrating on risk management ('manage the baggage') later in drug development. A key challenge in DDI prediction is the discrepancies between reported models. Areas covered: The current synopsis focuses on four recent influential publications on hepatic drug transporter DDIs using static models that tackle interactions with individual transporters and in combination with other drug transporters and metabolising enzymes. These models vary in their assumptions (including input parameters), transparency, reproducibility and complexity. In this review, these facets are compared and contrasted with recommendations made as to their application. Expert opinion: Over the past decade, static models have evolved from simple [I]/k i models to incorporate victim and perpetrator disposition mechanisms including the absorption rate constant, the fraction of the drug metabolised/eliminated and/or clearance concepts. Nonetheless, models that comprise additional parameters and complexity do not necessarily out-perform simpler models with fewer inputs. Further, consideration of the property space to exploit some drug target classes has also highlighted the fine balance required between frontloading and back-loading studies to design out or 'manage the baggage'.
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Gupta, Himanshu R; Patil, Yogesh; Singh, Dipty; Thakur, Mansee
2016-12-01
model is recommended as a well-established method for rapidly assessing the toxicity of homeopathic drugs.
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Kue, Chin Siang; Tan, Kae Yi; Lam, May Lynn; Lee, Hong Boon
2015-01-01
The chick embryo chorioallantoic membrane (CAM) is a preclinical model widely used for vascular and anti-vascular effects of therapeutic agents in vivo. In this study, we examine the suitability of CAM as a predictive model for acute toxicology studies of drugs by comparing it to conventional mouse and rat models for 10 FDA-approved anticancer drugs (paclitaxel, carmustine, camptothecin, cyclophosphamide, vincristine, cisplatin, aloin, mitomycin C, actinomycin-D, melphalan). Suitable formulations for intravenous administration were determined before the average of median lethal dose (LD50) and median survival dose (SD(50)) in the CAM were measured and calculated for these drugs. The resultant ideal LD(50) values were correlated to those reported in the literature using Pearson's correlation test for both intravenous and intraperitoneal routes of injection in rodents. Our results showed moderate correlations (r(2)=0.42 - 0.68, PLD(50) values obtained using the CAM model with LD(50) values from mice and rats models for both intravenous and intraperitoneal administrations, suggesting that the chick embryo may be a suitable alternative model for acute drug toxicity screening before embarking on full toxicological investigations in rodents in development of anticancer drugs.
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Drug Enforcement Administration
... de informacin confidencial --> DEA NEWS The Drug Enforcement Administration and Discovery Education name grand winner of Operation ... JUN 15 (Washington) The United States Drug Enforcement Administration, DEA Educational Foundation and Discovery Education awarded Porter ...
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DEFF Research Database (Denmark)
Khan, Jamal; Rades, Thomas; Boyd, Ben J
2016-01-01
The tendency for poorly water-soluble weakly basic drugs to precipitate in a noncrystalline form during the in vitro digestion of lipid-based formulations (LBFs) was linked to an ionic interaction between drug and fatty acid molecules produced upon lipid digestion. Cinnarizine was chosen as a model...... from the starting free base crystalline material to the hydrochloride salt, thus supporting the case that ionic interactions between weak bases and fatty acid molecules during digestion are responsible for producing amorphous-salts upon precipitation. The conclusion has wide implications...... weakly basic drug and was dissolved in a medium-chain (MC) LBF, which was subject to in vitro lipolysis experiments at various pH levels above and below the reported pKa value of cinnarizine (7.47). The solid-state form of the precipitated drug was analyzed using X-ray diffraction (XRD), Fourier...
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Assmus, Frauke; Houston, J Brian; Galetin, Aleksandra
2017-11-15
The prediction of tissue-to-plasma water partition coefficients (Kpu) from in vitro and in silico data using the tissue-composition based model (Rodgers & Rowland, J Pharm Sci. 2005, 94(6):1237-48.) is well established. However, distribution of basic drugs, in particular into lysosome-rich lung tissue, tends to be under-predicted by this approach. The aim of this study was to develop an extended mechanistic model for the prediction of Kpu which accounts for lysosomal sequestration and the contribution of different cell types in the tissue of interest. The extended model is based on compound-specific physicochemical properties and tissue composition data to describe drug ionization, distribution into tissue water and drug binding to neutral lipids, neutral phospholipids and acidic phospholipids in tissues, including lysosomes. Physiological data on the types of cells contributing to lung, kidney and liver, their lysosomal content and lysosomal pH were collated from the literature. The predictive power of the extended mechanistic model was evaluated using a dataset of 28 basic drugs (pK a ≥7.8, 17 β-blockers, 11 structurally diverse drugs) for which experimentally determined Kpu data in rat tissue have been reported. Accounting for the lysosomal sequestration in the extended mechanistic model improved the accuracy of Kpu predictions in lung compared to the original Rodgers model (56% drugs within 2-fold or 88% within 3-fold of observed values). Reduction in the extent of Kpu under-prediction was also evident in liver and kidney. However, consideration of lysosomal sequestration increased the occurrence of over-predictions, yielding overall comparable model performances for kidney and liver, with 68% and 54% of Kpu values within 2-fold error, respectively. High lysosomal concentration ratios relative to cytosol (>1000-fold) were predicted for the drugs investigated; the extent differed depending on the lysosomal pH and concentration of acidic phospholipids among
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Computational Studies of Drug Release, Transport and Absorption in the Human Intestines
Behafarid, Farhad; Brasseur, J. G.; Vijayakumar, G.; Jayaraman, B.; Wang, Y.
2016-11-01
Following disintegration of a drug tablet, a cloud of particles 10-200 μm in diameter enters the small intestine where drug molecules are absorbed into the blood. Drug release rate depends on particle size, solubility and hydrodynamic enhancements driven by gut motility. To quantify the interrelationships among dissolution, transport and wall permeability, we apply lattice Boltzmann method to simulate the drug concentration field in the 3D gut released from polydisperse distributions of drug particles in the "fasting" vs. "fed" motility states. Generalized boundary conditions allow for both solubility and gut wall permeability to be systematically varied. We apply a local 'quasi-steady state' approximation for drug dissolution using a mathematical model generalized for hydrodynamic enhancements and heterogeneity in drug release rate. We observe fundamental differences resulting from the interplay among release, transport and absorption in relationship to particle size distribution, luminal volume, motility, solubility and permeability. For example, whereas smaller volume encourages higher bulk concentrations and reduced release rate, it also encourages higher absorption rate, making it difficult to generalize predictions. Supported by FDA.
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Karchava, Marine; Pulver, Wendy; Smith, Lou; Philpott, Sean; Sullivan, Timothy J.; Wethers, Judith; Parker, Monica M.
2006-01-01
Prevalence studies indicate that transmission of drug-resistant HIV has been rising in the adult population, but data from the perinatally infected pediatric population are limited. In this retrospective study, we sequenced the pol region of HIV from perinatally infected infants diagnosed in New York State in 2001–2002. Analyses of drug resistance, subtype diversity, and perinatal antiretroviral exposure were conducted, and the results were compared with those from a previous study of HIV-inf...
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Drug Release Mechanism of Slightly Soluble Drug from ...
African Journals Online (AJOL)
theophylline (THP) as drug in drug to clay ratios of 1:2, 3:4 and 1:1. The formulations were characterized for drug release and loading. Dependent and independent kinetic models were employed to analyze the drug release data. Fourier transform infrared spectroscopy (FTIR) was used for the structural characterization of ...
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Mathematical Model to Predict Skin Concentration after Topical Application of Drugs
Directory of Open Access Journals (Sweden)
Hiroaki Todo
2013-12-01
Full Text Available Skin permeation experiments have been broadly done since 1970s to 1980s as an evaluation method for transdermal drug delivery systems. In topically applied drug and cosmetic formulations, skin concentration of chemical compounds is more important than their skin permeations, because primary target site of the chemical compounds is skin surface or skin tissues. Furthermore, the direct pharmacological reaction of a metabolically stable drug that binds with specific receptors of known expression levels in an organ can be determined by Hill’s equation. Nevertheless, little investigation was carried out on the test method of skin concentration after topically application of chemical compounds. Recently we investigated an estimating method of skin concentration of the chemical compounds from their skin permeation profiles. In the study, we took care of “3Rs” issues for animal experiments. We have proposed an equation which was capable to estimate animal skin concentration from permeation profile through the artificial membrane (silicone membrane and animal skin. This new approach may allow the skin concentration of a drug to be predicted using Fick’s second law of diffusion. The silicone membrane was found to be useful as an alternative membrane to animal skin for predicting skin concentration of chemical compounds, because an extremely excellent extrapolation to animal skin concentration was attained by calculation using the silicone membrane permeation data. In this chapter, we aimed to establish an accurate and convenient method for predicting the concentration profiles of drugs in the skin based on the skin permeation parameters of topically active drugs derived from steady-state skin permeation experiments.
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A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.
Directory of Open Access Journals (Sweden)
Jessica M Conway
2014-08-01
Full Text Available Simple models of therapy for viral diseases such as hepatitis C virus (HCV or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.
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Hernández-Alava, Mónica; Pudney, Stephen
2017-09-01
EQ-5D is used in cost-effectiveness studies underlying many important health policy decisions. It comprises a survey instrument describing health states across five domains, and a system of utility values for each state. The original 3-level version of EQ-5D is being replaced with a more sensitive 5-level version but the consequences of this change are uncertain. We develop a multi-equation ordinal response model incorporating a copula specification with normal mixture marginals to analyse joint responses to EQ-5D-3L and EQ-5D-5L in a survey of people with rheumatic disease, and use it to generate mappings between the alternative descriptive systems. We revisit a major cost-effectiveness study of drug therapies for rheumatoid arthritis, mapping the original EQ-5D-3L measure onto a 5L valuation basis. Working within a comprehensive, flexible econometric framework, we find that use of simpler restricted specifications can make very large changes to cost-effectiveness estimates with serious implications for decision-making. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
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Löscher, Wolfgang
2017-07-01
The identification of potential therapeutic agents for the treatment of epilepsy requires the use of seizure models. Except for some early treatments, including bromides and phenobarbital, the antiseizure activity of all clinically used drugs was, for the most part, defined by acute seizure models in rodents using the maximal electroshock and subcutaneous pentylenetetrazole seizure tests and the electrically kindled rat. Unfortunately, the clinical evidence to date would suggest that none of these models, albeit useful, are likely to identify those therapeutics that will effectively manage patients with drug resistant seizures. Over the last 30 years, a number of animal models have been developed that display varying degrees of pharmacoresistance, such as the phenytoin- or lamotrigine-resistant kindled rat, the 6-Hz mouse model of partial seizures, the intrahippocampal kainate model in mice, or rats in which spontaneous recurrent seizures develops after inducing status epilepticus by chemical or electrical stimulation. As such, these models can be used to study mechanisms of drug resistance and may provide a unique opportunity for identifying a truly novel antiseizure drug (ASD), but thus far clinical evidence for this hope is lacking. Although animal models of drug resistant seizures are now included in ASD discovery approaches such as the ETSP (epilepsy therapy screening program), it is important to note that no single model has been validated for use to identify potential compounds for as yet drug resistant seizures, but rather a battery of such models should be employed, thus enhancing the sensitivity to discover novel, highly effective ASDs. The present review describes the previous and current approaches used in the search for new ASDs and offers some insight into future directions incorporating new and emerging animal models of therapy resistance.
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Gibson, E J; Begum, N; Koblbauer, I; Dranitsaris, G; Liew, D; McEwan, P; Tahami Monfared, A A; Yuan, Y; Juarez-Garcia, A; Tyas, D; Lees, M
2018-01-01
Economic models in oncology are commonly based on the three-state partitioned survival model (PSM) distinguishing between progression-free and progressive states. However, the heterogeneity of responses observed in immuno-oncology (I-O) suggests that new approaches may be appropriate to reflect disease dynamics meaningfully. This study explored the impact of incorporating immune-specific health states into economic models of I-O therapy. Two variants of the PSM and a Markov model were populated with data from one clinical trial in metastatic melanoma patients. Short-term modeled outcomes were benchmarked to the clinical trial data and a lifetime model horizon provided estimates of life years and quality adjusted life years (QALYs). The PSM-based models produced short-term outcomes closely matching the trial outcomes. Adding health states generated increased QALYs while providing a more granular representation of outcomes for decision making. The Markov model gave the greatest level of detail on outcomes but gave short-term results which diverged from those of the trial (overstating year 1 progression-free survival by around 60%). Increased sophistication in the representation of disease dynamics in economic models is desirable when attempting to model treatment response in I-O. However, the assumptions underlying different model structures and the availability of data for health state mapping may be important limiting factors.
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Directory of Open Access Journals (Sweden)
Trine Krogh-Madsen
2017-12-01
Full Text Available In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity.
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Sugamura, Yuka; Fujii, Makiko; Nakanishi, Sayaka; Suzuki, Ayako; Shibata, Yusuke; Koizumi, Naoya; Watanabe, Yoshiteru
2011-01-01
The effect of particle size on amorphization of drugs in a solid dispersion (SD) was investigated for two drugs, indomethacin (IM) and nifedipine (NP). The SD of drugs were prepared in a mixture with crospovidone by a variety of mechanical methods, and their properties investigated by particle sizing, thermal analysis, and powder X-ray diffraction. IM, which had an initial particle size of 1 µm and tends to aggregate, was forced through a sieve to break up the particles. NP, which had a large initial particle size, was jet-milled. In both cases, reduction of the particle size of the drugs enabled transition to an amorphous state below the melting point of the drug. The reduction in particle size is considered to enable increased contact between the crospovidone and drug particles, increasing interactions between the two compounds. © 2011 Pharmaceutical Society of Japan
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Influence of pH on Drug Absorption from the Gastrointestinal Tract: A Simple Chemical Model
Hickman, Raymond J. S.; Neill, Jane
1997-07-01
A simple model of the gastrointestinal tract is obtained by placing ethyl acetate in contact with water at pH 2 and pH 8 in separate test tubes. The ethyl acetate corresponds to the lipid material lining the tract while the water corresponds to the aqueous contents of the stomach (pH 2) and intestine (pH 8). The compounds aspirin, paracetamol and 3-aminophenol are used as exemplars of acidic, neutral and basic drugs respectively to illustrate the influence which pH has on the distribution of each class of drug between the aqueous and organic phases of the model. The relative concentration of drug in the ethyl acetate is judged by applying microlitre-sized samples of ethyl acetate to a layer of fluorescent silica which, after evaporation of the ethyl acetate, is viewed under an ultraviolet lamp. Each of the three drugs, if present in the ethyl acetate, becomes visible as a dark spot on the silica layer. The observations made in the model system correspond well to the patterns of drug absorption from the gastrointestinal tract described in pharmacology texts and these observations are convincingly explained in terms of simple acid-base chemistry.
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Kellams, Joni R; Maye, John P
Nurse practitioners (NPs) now have prescriptive authority for controlled substances in all 50 states in the United States. Florida, the last state to grant NPs DEA licensure, has been wrought with prescription diversion practices for a number of years as pill mills, doctor shopping, and overprescribing proliferated. Prescription Drug Monitoring Programs (PDMPs) help curb drug diversion activity and play a key role in reducing the abuse of controlled substances. The primary objective of this education improvement initiative was to increase knowledge of actively licensed NPs in the state of Florida regarding the state's PDMP. The main themes included the drug abuse problem, description and progression of the PDMP, and how to use the Florida PDMP. Upon approval from the institutional review board, this education improvement initiative gauged NP knowledge of the PDMP and main themes before and after an educational PowerPoint intervention. A pretest/posttest questionnaire was administered for assessment of all knowledge questions. One hundred forty-five NPs with active advanced registered NP licenses in Florida completed both the pretest and posttest questionnaires. Descriptive statistics and paired t tests were used for statistical significance testing. Knowledge of the PDMP and the main themes of the education improvement initiative significantly increased (p < .001) from pretest to posttest results. This education improvement initiative had positive effects for NPs on the knowledge of the Florida PDMP and the main themes. This indicated that Florida NPs are able to acquire greater comprehension of the PDMP by an education intervention.
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Position-aware deep multi-task learning for drug-drug interaction extraction.
Zhou, Deyu; Miao, Lei; He, Yulan
2018-05-01
A drug-drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed. In this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework. The proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.
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Ground states of a spin-boson model
International Nuclear Information System (INIS)
Amann, A.
1991-01-01
Phase transition with respect to ground states of a spin-boson Hamiltonian are investigated. The spin-boson model under discussion consists of one spin and infinitely many bosons with a dipole-type coupling. It is shown that the order parameter of the model vanishes with respect to arbitrary ground states if it vanishes with respect to ground states obtained as (biased) temperature to zero limits of thermic equilibrium states. The ground states of the latter special type have been investigated by H. Spohn. Spohn's respective phase diagrams are therefore valid for arbitrary ground states. Furthermore, disjointness of ground states in the broken symmetry regime is examined
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DEFF Research Database (Denmark)
Andersen, Per Kragh; Klein, John P.; Rosthøj, Susanne
2003-01-01
Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model......Generalised estimating equation; Generalised linear model; Jackknife pseudo-value; Logistic regression; Markov Model; Multi-state model...
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Macrophage models of Gaucher disease for evaluating disease pathogenesis and candidate drugs.
Aflaki, Elma; Stubblefield, Barbara K; Maniwang, Emerson; Lopez, Grisel; Moaven, Nima; Goldin, Ehud; Marugan, Juan; Patnaik, Samarjit; Dutra, Amalia; Southall, Noel; Zheng, Wei; Tayebi, Nahid; Sidransky, Ellen
2014-06-11
Gaucher disease is caused by an inherited deficiency of glucocerebrosidase that manifests with storage of glycolipids in lysosomes, particularly in macrophages. Available cell lines modeling Gaucher disease do not demonstrate lysosomal storage of glycolipids; therefore, we set out to develop two macrophage models of Gaucher disease that exhibit appropriate substrate accumulation. We used these cellular models both to investigate altered macrophage biology in Gaucher disease and to evaluate candidate drugs for its treatment. We generated and characterized monocyte-derived macrophages from 20 patients carrying different Gaucher disease mutations. In addition, we created induced pluripotent stem cell (iPSC)-derived macrophages from five fibroblast lines taken from patients with type 1 or type 2 Gaucher disease. Macrophages derived from patient monocytes or iPSCs showed reduced glucocerebrosidase activity and increased storage of glucocerebroside and glucosylsphingosine in lysosomes. These macrophages showed efficient phagocytosis of bacteria but reduced production of intracellular reactive oxygen species and impaired chemotaxis. The disease phenotype was reversed with a noninhibitory small-molecule chaperone drug that enhanced glucocerebrosidase activity in the macrophages, reduced glycolipid storage, and normalized chemotaxis and production of reactive oxygen species. Macrophages differentiated from patient monocytes or patient-derived iPSCs provide cellular models that can be used to investigate disease pathogenesis and facilitate drug development. Copyright © 2014, American Association for the Advancement of Science.
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Kaunisto, Erik; Marucci, Mariagrazia; Borgquist, Per; Axelsson, Anders
2011-10-10
The time required for the design of a new delivery device can be sensibly reduced if the release mechanism is understood and an appropriate mathematical model is used to characterize the system. Once all the model parameters are obtained, in silico experiments can be performed, to provide estimates of the release from devices with different geometries and compositions. In this review coated and matrix systems are considered. For coated formulations, models describing the diffusional drug release, the osmotic pumping drug release, and the lag phase of pellets undergoing cracking in the coating due to the build-up of a hydrostatic pressure are reviewed. For matrix systems, models describing pure polymer dissolution, diffusion in the polymer and drug release from swelling and eroding polymer matrix formulations are reviewed. Importantly, the experiments used to characterize the processes occurring during the release and to validate the models are presented and discussed. Copyright © 2011 Elsevier B.V. All rights reserved.
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Models of policy-making and their relevance for drug research.
Ritter, Alison; Bammer, Gabriele
2010-07-01
Researchers are often frustrated by their inability to influence policy. We describe models of policy-making to provide new insights and a more realistic assessment of research impacts on policy. We describe five prominent models of policy-making and illustrate them with examples from the alcohol and drugs field, before drawing lessons for researchers. Policy-making is a complex and messy process, with different models describing different elements. We start with the incrementalist model, which highlights small amendments to policy, as occurs in school-based drug education. A technical/rational approach then outlines the key steps in a policy process from identification of problems and their causes, through to examination and choice of response options, and subsequent implementation and evaluation. There is a clear role for research, as we illustrate with the introduction of new medications, but this model largely ignores the dominant political aspects of policy-making. Such political aspects include the influence of interest groups, and we describe models about power and pressure groups, as well as advocacy coalitions, and the challenges they pose for researchers. These are illustrated with reference to the alcohol industry, and interest group conflicts in establishing a Medically Supervised Injecting Centre. Finally, we describe the multiple streams framework, which alerts researchers to 'windows of opportunity', and we show how these were effectively exploited in policy for cannabis law reform in Western Australia. Understanding models of policy-making can help researchers maximise the uptake of their work and advance evidence-informed policy.
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Mathematical model of transmission network static state estimation
Directory of Open Access Journals (Sweden)
Ivanov Aleksandar
2012-01-01
Full Text Available In this paper the characteristics and capabilities of the power transmission network static state estimator are presented. The solving process of the mathematical model containing the measurement errors and their processing is developed. To evaluate difference between the general model of state estimation and the fast decoupled state estimation model, the both models are applied to an example, and so derived results are compared.
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Effect of drugs of abuse on social behaviour: a review of animal models.
Blanco-Gandía, Maria C; Mateos-García, Ana; García-Pardo, Maria P; Montagud-Romero, Sandra; Rodríguez-Arias, Marta; Miñarro, José; Aguilar, María A
2015-09-01
Social behaviour is disturbed in many substance abuse and psychiatric disorders. Given the consensus that social behaviours of lower mammals may help to understand some human emotional reactions, the aim of the present work was to provide an up-to-date review of studies on the changes in social behaviour induced by drugs of abuse. Various animal models have been used to study the relationship between drugs of abuse and social behaviour. Herein, we describe the effects of different substances of abuse on the three most commonly used animal models of social behaviour: the social play test, the social interaction test and the resident-intruder paradigm. The first is the most widely used test to assess adolescent behaviour in rodents, the second is generally used to evaluate a wide repertoire of behaviours in adulthood and the latter is specific to aggressive behaviour. Throughout the review we will explore the most relevant studies carried out to date to evaluate the effects of alcohol, cocaine, opioids, 3,4-methylenedioxymethamphetamine (MDMA), cannabinoids, nicotine and other drugs of abuse on these three paradigms, taking into account the influence of different variables, such as social history, age and type of exposure. Drugs of diverse pharmacological classes induce alterations in social behaviour, although they can be contrasting depending on several factors (drug, individual differences and environmental conditions). Ethanol and nicotine increase social interaction at low doses but reduce it at high doses. Psychostimulants, MDMA and cannabinoids reduce social interaction, whereas opiates increase it. Ethanol and psychostimulants enhance aggression, whereas MDMA, opiates, cannabinoids and nicotine reduce it. Prenatal drug exposure alters social behaviour, whereas drug withdrawal decreases sociability and enhances aggression. As a whole, this evidence has improved our understanding of the social dimension of drug addiction.
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Competing States in the t-J Model: Uniform d-Wave State versus Stripe State versus Stripe State
Corboz, P.R.; Rice, T.M.; Troyer, M.
2014-01-01
Variational studies of the t-J model on the square lattice based on infinite projected-entangled pair states confirm an extremely close competition between a uniform d-wave superconducting state and different stripe states. The site-centered stripe with an in-phase d-wave order has an equal or only
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A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe
2011-05-30
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.
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Moura, Maria Edileuza Soares; da Guarda Reis, Mônica Nogueira; Lima, Yanna Andressa Ramos; Eulálio, Kelsen Dantas; Cardoso, Ludimila Paula Vaz; Stefani, Mariane Martins Araújo
2015-05-01
HIV-1 transmitted-drug-resistance and genetic diversity are dynamic and may differ in distinct locations/risk groups. In Brazil, increased AIDS incidence and related mortality have been detected in the Northeast region, differently from the epicenter in the Southeast. This cross-sectional study describes transmitted-dru- resistance and HIV-1 subtypes in protease/PR and reverse transcriptase/RT regions among antiretroviral naïve patients from Piauí State, Northeast Brazil. Among 96 patients recruited 89 (92.7%) had HIV-1 PR/RT regions sequenced: 44 females and 45 males, 22 self-declared as men who have sex with men. Transmitted-drug-resistance was investigated by CPR tool (Stanford HIV-1 Drug Resistance/SDRM). HIV-1 subtypes were assigned by REGA and phylogenetic inference. Overall, transmitted-drug-resistance rate was 11.2% (10/89; CI 95%: 5.8-19.1%); 22.7% among men who have sex with men (5/22; CI 95%: 8.8-43.4%), 10% in heterosexual men (2/20; CI 95%: 1.7-29.3%) and 6.8% in women (3/44; CI 95%: 1.8-17.4%). Singleton mutations to protease-inhibitor/PI, nucleoside-reverse-transcriptase-inhibitor/NRTI or non-nucleoside-reverse-transcriptase-inhibitor/NNRTI predominated (8/10): PI mutations (M46L, V82F, L90M); NRTI mutations (M41L, D67N) and NNRTI mutations (K103N/S). Dual class resistance mutations to NRTI and NNRTI were observed: T215L (NRTI), Y188L (NNRTI) and T215N (NRTI), F227L (NNRTI). Subtype B prevailed (86.6%; 77/89), followed by subtype F1 (1.1%, 1/89) and subtype C (1.1%, 1/89). B/F1 and B/C intersubtype recombinants represented 11.2% (10/89). In Piauí State extensive testing of incidence and transmitted-drug-resistance in all populations with risk behaviors may help control AIDS epidemic locally. © 2015 Wiley Periodicals, Inc.
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The two-state dimer receptor model: a general model for receptor dimers.
Franco, Rafael; Casadó, Vicent; Mallol, Josefa; Ferrada, Carla; Ferré, Sergi; Fuxe, Kjell; Cortés, Antoni; Ciruela, Francisco; Lluis, Carmen; Canela, Enric I
2006-06-01
Nonlinear Scatchard plots are often found for agonist binding to G-protein-coupled receptors. Because there is clear evidence of receptor dimerization, these nonlinear Scatchard plots can reflect cooperativity on agonist binding to the two binding sites in the dimer. According to this, the "two-state dimer receptor model" has been recently derived. In this article, the performance of the model has been analyzed in fitting data of agonist binding to A(1) adenosine receptors, which are an example of receptor displaying concave downward Scatchard plots. Analysis of agonist/antagonist competition data for dopamine D(1) receptors using the two-state dimer receptor model has also been performed. Although fitting to the two-state dimer receptor model was similar to the fitting to the "two-independent-site receptor model", the former is simpler, and a discrimination test selects the two-state dimer receptor model as the best. This model was also very robust in fitting data of estrogen binding to the estrogen receptor, for which Scatchard plots are concave upward. On the one hand, the model would predict the already demonstrated existence of estrogen receptor dimers. On the other hand, the model would predict that concave upward Scatchard plots reflect positive cooperativity, which can be neither predicted nor explained by assuming the existence of two different affinity states. In summary, the two-state dimer receptor model is good for fitting data of binding to dimeric receptors displaying either linear, concave upward, or concave downward Scatchard plots.
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An examination of the Sport Drug Control Model with elite Australian athletes.
Gucciardi, Daniel F; Jalleh, Geoffrey; Donovan, Robert J
2011-11-01
This study presents an opportunistic examination of the theoretical tenets outlined in the Sport Drug Control Model(1) using questionnaire items from a survey of 643 elite Australian athletes. Items in the questionnaire that related to the concepts in the model were identified and structural equation modelling was employed to test the hypothesised model. Morality (cheating), benefit appraisal (performance), and threat appraisal (enforcement) evidenced the strongest relationships with attitude to doping, which in turn was positively associated with doping susceptibility. Self-esteem, perceptions of legitimacy and reference group opinions showed small non-significant associations with attitude to doping. The hypothesised model accounted for 30% and 11% of the variance in attitudes to doping and doping susceptibility, respectively. These present findings provide support for the model even though the questionnaire items were not constructed to specifically measure concepts contained in it. Thus, the model appears useful for understanding influences on doping. Nevertheless, there is a need to further explore individual and social factors that may influence athletes' use of performance enhancing drugs. Copyright © 2011 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
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Animal models to guide clinical drug development in ADHD: lost in translation?
Wickens, Jeffery R; Hyland, Brian I; Tripp, Gail
2011-01-01
We review strategies for developing animal models for examining and selecting compounds with potential therapeutic benefit in attention-deficit hyperactivity disorder (ADHD). ADHD is a behavioural disorder of unknown aetiology and pathophysiology. Current understanding suggests that genetic factors play an important role in the aetiology of ADHD. The involvement of dopaminergic and noradrenergic systems in the pathophysiology of ADHD is probable. We review the clinical features of ADHD including inattention, hyperactivity and impulsivity and how these are operationalized for laboratory study. Measures of temporal discounting (but not premature responding) appear to predict known drug effects well (treatment validity). Open-field measures of overactivity commonly used do not have treatment validity in human populations. A number of animal models have been proposed that simulate the symptoms of ADHD. The most commonly used are the spontaneously hypertensive rat (SHR) and the 6-hydroxydopamine-lesioned (6-OHDA) animals. To date, however, the SHR lacks treatment validity, and the effects of drugs on symptoms of impulsivity and inattention have not been studied extensively in 6-OHDA-lesioned animals. At the present stage of development, there are no in vivo models of proven effectiveness for examining and selecting compounds with potential therapeutic benefit in ADHD. However, temporal discounting is an emerging theme in theories of ADHD, and there is good evidence of increased value of delayed reward following treatment with stimulant drugs. Therefore, operant behaviour paradigms that measure the effects of drugs in situations of delayed reinforcement, whether in normal rats or selected models, show promise for the future. LINKED ARTICLES This article is part of a themed issue on Translational Neuropharmacology. To view the other articles in this issue visit http://dx.doi.org/10.1111/bph.2011.164.issue-4 PMID:21480864
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Regulation of chromatin states by drugs of abuse.
Walker, Deena M; Cates, Hannah M; Heller, Elizabeth A; Nestler, Eric J
2015-02-01
Drug addiction involves long-term behavioral abnormalities and gene expression changes throughout the mesolimbic dopamine system. Epigenetic mechanisms establish/maintain alterations in gene expression in the brain, providing the impetus for investigations characterizing how epigenetic processes mediate the effects of drugs of abuse. This review focuses on evidence that epigenetic events, specifically histone modifications, regulate gene expression changes throughout the reward circuitry. Drugs of abuse induce changes in histone modifications throughout the reward circuitry by altering histone-modifying enzymes, manipulation of which reveals a role for histone modification in addiction-related behaviors. There is a complex interplay between these enzymes, resulting in a histone signature of the addicted phenotype. Insights gained from these studies are key to identifying novel targets for diagnosis and therapy. Copyright © 2014 Elsevier Ltd. All rights reserved.
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Directory of Open Access Journals (Sweden)
Feras Khalil
2011-01-01
Full Text Available The concept of physiologically based pharmacokinetic (PBPK modeling was introduced years ago, but it has not been practiced significantly. However, interest in and implementation of this modeling technique have grown, as evidenced by the increased number of publications in this field. This paper demonstrates briefly the methodology, applications, and limitations of PBPK modeling with special attention given to discuss the use of PBPK models in pediatric drug development and some examples described in detail. Although PBPK models do have some limitations, the potential benefit from PBPK modeling technique is huge. PBPK models can be applied to investigate drug pharmacokinetics under different physiological and pathological conditions or in different age groups, to support decision-making during drug discovery, to provide, perhaps most important, data that can save time and resources, especially in early drug development phases and in pediatric clinical trials, and potentially to help clinical trials become more “confirmatory” rather than “exploratory”.
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Fed and fasted state gastro-intestinal in vitro lipolysis
DEFF Research Database (Denmark)
Christophersen, Philip Carsten B; Christiansen, Martin Lau; Holm, Rene
2014-01-01
The present study aims at evaluating the ability of a gastro-intestinal in vitro lipolysis model to predict the performance of two lipid formulations and a conventional tablet containing a poorly soluble drug, cinnarizine, in dogs, both in the fasted and fed state. A self-nano-emulsifying drug de...
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Thermodynamic state ensemble models of cis-regulation.
Directory of Open Access Journals (Sweden)
Marc S Sherman
Full Text Available A major goal in computational biology is to develop models that accurately predict a gene's expression from its surrounding regulatory DNA. Here we present one class of such models, thermodynamic state ensemble models. We describe the biochemical derivation of the thermodynamic framework in simple terms, and lay out the mathematical components that comprise each model. These components include (1 the possible states of a promoter, where a state is defined as a particular arrangement of transcription factors bound to a DNA promoter, (2 the binding constants that describe the affinity of the protein-protein and protein-DNA interactions that occur in each state, and (3 whether each state is capable of transcribing. Using these components, we demonstrate how to compute a cis-regulatory function that encodes the probability of a promoter being active. Our intention is to provide enough detail so that readers with little background in thermodynamics can compose their own cis-regulatory functions. To facilitate this goal, we also describe a matrix form of the model that can be easily coded in any programming language. This formalism has great flexibility, which we show by illustrating how phenomena such as competition between transcription factors and cooperativity are readily incorporated into these models. Using this framework, we also demonstrate that Michaelis-like functions, another class of cis-regulatory models, are a subset of the thermodynamic framework with specific assumptions. By recasting Michaelis-like functions as thermodynamic functions, we emphasize the relationship between these models and delineate the specific circumstances representable by each approach. Application of thermodynamic state ensemble models is likely to be an important tool in unraveling the physical basis of combinatorial cis-regulation and in generating formalisms that accurately predict gene expression from DNA sequence.
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A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis
Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L.; Postmus, Douwe
2011-01-01
Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multicriteria model that fully takes into account the evidence on efficacy and adverse drug
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Smith, Alec S T; Macadangdang, Jesse; Leung, Winnie; Laflamme, Michael A; Kim, Deok-Ho
Improved methodologies for modeling cardiac disease phenotypes and accurately screening the efficacy and toxicity of potential therapeutic compounds are actively being sought to advance drug development and improve disease modeling capabilities. To that end, much recent effort has been devoted to the development of novel engineered biomimetic cardiac tissue platforms that accurately recapitulate the structure and function of the human myocardium. Within the field of cardiac engineering, induced pluripotent stem cells (iPSCs) are an exciting tool that offer the potential to advance the current state of the art, as they are derived from somatic cells, enabling the development of personalized medical strategies and patient specific disease models. Here we review different aspects of iPSC-based cardiac engineering technologies. We highlight methods for producing iPSC-derived cardiomyocytes (iPSC-CMs) and discuss their application to compound efficacy/toxicity screening and in vitro modeling of prevalent cardiac diseases. Special attention is paid to the application of micro- and nano-engineering techniques for the development of novel iPSC-CM based platforms and their potential to advance current preclinical screening modalities. Published by Elsevier Inc.
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Yonamine, Mauricio; Sanches, Livia Rentas; Paranhos, Beatriz Aparecida Passos Bismara; de Almeida, Rafael Menck; Andreuccetti, Gabriel; Leyton, Vilma
2013-01-01
Alcohol and drug use by truck drivers is a current problem in Brazil. Though there is evidence that alcohol consumption is occurring in higher proportions, the use of stimulant drugs to avoid fatigue and to maintain the work schedule has also been reported. The purpose of this study was to estimate the incidence of alcohol and illicit drug use among truck drivers on São Paulo state roads. São Paulo is the most populous state in Brazil and has the largest industrial park and economic production in the country. Data were assessed not only using a questionnaire but also, and more reliably, through toxicological analysis of oral fluid samples. Between the years 2002 and 2008, 1250 oral fluid samples were collected from truck drivers on the roads during morning hours. The samples were tested for the presence of alcohol, cocaine, tetrahydrocannabinol (THC), and amphetamine/methamphetamine. A previously published, validated gas chromatographic (gas chromatography-flame ionization detection and gas chromatography-mass spectrometry) method was applied to the samples for alcohol and drug detection. Of the total analyzed samples, 3.1 percent (n = 39) were positive: 1.44 percent (n = 18) were positive for alcohol, 0.64 percent (n = 8) for amphetamines, 0.56 percent (n = 7) for cocaine, and 0.40 percent (n = 5) for THC. In one case, cocaine and THC were detected. The results are indicative of the extent of alcohol and drug use by truck drivers in the state of São Paulo, Brazil. This research provides evidence that not only alcohol but also illicit drug use is a real problem among professional drivers. The use of these substances should be controlled to better promote safe driving conditions on Brazilian roads.
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Collins, John
2017-01-24
Much international drug policy debate centres on, what policies are permissible under the international drug treaties, whether member states are openly 'breaching' these treaties by changing national regulatory frameworks and shifting priorities away from a 'war on drugs' approach, and what 'flexibility' exists for policy reform and experimentation at national and local levels. Orthodox interpretations hold that the current system is a US-led 'prohibition regime' that was constructed in an extremely repressive and restrictive manner with almost no flexibility for significant national deviations. This paper challenges these orthodox interpretive frameworks and suggests no absolute and clear dichotomy between strict adherence and 'breaches' of the international treaties. This paper uses historical analysis to highlight the flaws in orthodox policy analyses, which assume a uniform interpretation, implementation and set of policy trajectories towards a 'prohibition regime' in the 20th century. It challenges some existing legal interpretations of the treaties through recourse to historical precedents of flexible interpretation and policy prioritisation. It then examines the legal justifications currently being formulated by member states to explain a shift towards policies which, until recently, have been viewed as outside the permissible scope of the conventions. It then examines a functionalist framework for understanding the likely contours of drug diplomacy in the post-UN General Assembly Special Session (UNGASS) 2016 era. The paper highlights that, contrary to current policy discourses, the international control system has always been implemented in a 'flexible' manner. It demonstrates that drug control goals were repeatedly subsumed to security, development, political stability and population welfare imperatives, or what we might now refer to under the umbrella of 'development issues.' The paper further demonstrates that policy prioritisation, inherent treaty
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Thermosensitive liposomal drug delivery systems: state of the art review
Directory of Open Access Journals (Sweden)
Kneidl B
2014-09-01
Full Text Available Barbara Kneidl,1,2 Michael Peller,3 Gerhard Winter,2 Lars H Lindner,1 Martin Hossann11Department of Internal Medicine III, University Hospital Munich, 2Department of Pharmacy, Pharmaceutical Technology and Biopharmaceutics, 3Institute for Clinical Radiology, University Hospital Munich, Ludwig-Maximilians University, Munich, GermanyAbstract: Thermosensitive liposomes are a promising tool for external targeting of drugs to solid tumors when used in combination with local hyperthermia or high intensity focused ultrasound. In vivo results have demonstrated strong evidence that external targeting is superior over passive targeting achieved by highly stable long-circulating drug formulations like PEGylated liposomal doxorubicin. Up to March 2014, the Web of Science listed 371 original papers in this field, with 45 in 2013 alone. Several formulations have been developed since 1978, with lysolipid-containing, low temperature-sensitive liposomes currently under clinical investigation. This review summarizes the historical development and effects of particular phospholipids and surfactants on the biophysical properties and in vivo efficacy of thermosensitive liposome formulations. Further, treatment strategies for solid tumors are discussed. Here we focus on temperature-triggered intravascular and interstitial drug release. Drug delivery guided by magnetic resonance imaging further adds the possibility of performing online monitoring of a heating focus to calculate locally released drug concentrations and to externally control drug release by steering the heating volume and power. The combination of external targeting with thermosensitive liposomes and magnetic resonance-guided drug delivery will be the unique characteristic of this nanotechnology approach in medicine.Keywords: thermosensitive liposomes, phosphatidyloligoglycerol, hyperthermia, high intensity focused ultrasound, drug delivery, drug targeting
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Analyzing research trends on drug safety using topic modeling.
Zou, Chen
2018-04-06
Published drug safety data has evolved in the past decade due to scientific and technological advances in the relevant research fields. Considering that a vast amount of scientific literature has been published in this area, it is not easy to identify the key information. Topic modeling has emerged as a powerful tool to extract meaningful information from a large volume of unstructured texts. Areas covered: We analyzed the titles and abstracts of 4347 articles in four journals dedicated to drug safety from 2007 to 2016. We applied Latent Dirichlet allocation (LDA) model to extract 50 main topics, and conducted trend analysis to explore the temporal popularity of these topics over years. Expert Opinion/Commentary: We found that 'benefit-risk assessment and communication', 'diabetes' and 'biologic therapy for autoimmune diseases' are the top 3 most published topics. The topics relevant to the use of electronic health records/observational data for safety surveillance are becoming increasingly popular over time. Meanwhile, there is a slight decrease in research on signal detection based on spontaneous reporting, although spontaneous reporting still plays an important role in benefit-risk assessment. The topics related to medical conditions and treatment showed highly dynamic patterns over time.
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DFT application for chlorin derivatives photosensitizer drugs modeling
Machado, Neila; Carvalho, B. G.; Téllez Soto, C. A.; Martin, A. A.; Favero, P. P.
2018-04-01
Photodynamic therapy is an alternative form of cancer treatment that meets the desire for a less aggressive approach to the body. It is based on the interaction between a photosensitizer, activating light, and molecular oxygen. This interaction results in a cascade of reactions that leads to localized cell death. Many studies have been conducted to discover an ideal photosensitizer, which aggregates all the desirable characteristics of a potent cell killer and generates minimal side effects. Using Density Functional Theory (DFT) implemented in the program Vienna Ab-initio Simulation Package, new chlorin derivatives with different functional groups were simulated to evaluate the different absorption wavelengths to permit resonant absorption with the incident laser. Gaussian 09 program was used to determine vibrational wave numbers and Natural Bond Orbitals. The chosen drug with the best characteristics for the photosensitizer was a modified model of the original chlorin, which was called as Thiol chlorin. According to our calculations it is stable and is 19.6% more efficient at optical absorption in 708 nm in comparison to the conventional chlorin e6. Vibrational modes, optical and electronic properties were predicted. In conclusion, this study is an attempt to improve the development of new photosensitizer drugs through computational methods that save time and contribute to decrease the numbers of animals for model application.
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DEFF Research Database (Denmark)
Spina, Alexander; Eramova, Irina; Lazarus, Jeffrey V
2014-01-01
BACKGROUND: Unsafe injections, through infectious bodily fluids, are a major route of transmission for hepatitis B and C. Viral hepatitis burden among people who inject drugs is particularly high in many Member States of central and Eastern Europe while national capacity and willingness to address......, with less than one-third reportedly conducting regular serosurveys among people who inject drugs. CONCLUSIONS: Findings highlight key gaps requiring attention in order to improve national policies and programmes in the region and ensure an adequate response to injection drug use-associated viral hepatitis...... of a national policy for hepatitis prevention and control; however less than one-third (27%) reported having written national strategies. Under half of the responding Member States reported holding events for World Hepatitis Day 2012. One-fifth reported offering hepatitis B and C testing free of charge...
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Wang, Wei
2017-10-06
The function of complex biomolecular machines relies heavily on their conformational changes. Investigating these functional conformational changes is therefore essential for understanding the corresponding biological processes and promoting bioengineering applications and rational drug design. Constructing Markov State Models (MSMs) based on large-scale molecular dynamics simulations has emerged as a powerful approach to model functional conformational changes of the biomolecular system with sufficient resolution in both time and space. However, the rapid development of theory and algorithms for constructing MSMs has made it difficult for nonexperts to understand and apply the MSM framework, necessitating a comprehensive guidance toward its theory and practical usage. In this study, we introduce the MSM theory of conformational dynamics based on the projection operator scheme. We further propose a general protocol of constructing MSM to investigate functional conformational changes, which integrates the state-of-the-art techniques for building and optimizing initial pathways, performing adaptive sampling and constructing MSMs. We anticipate this protocol to be widely applied and useful in guiding nonexperts to study the functional conformational changes of large biomolecular systems via the MSM framework. We also discuss the current limitations of MSMs and some alternative methods to alleviate them.
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Sachs-Barrable, Kristina; Conway, Jocelyn; Gershkovich, Pavel; Ibrahim, Fady; Wasan, Kishor M
2014-11-01
Neglected tropical diseases (NTDs) are infections which are endemic in poor populations in lower- and middle-income countries (LMIC). Approximately one billion people have now or are at risk of getting an NTD and yet less than 5% of research dollars are focused on providing treatments and prevention of these highly debilitating and deadly conditions. The United States Food and Drug Administration (FDA) Orphan Drug Designation program (ODDP) provides orphan status to drugs and biologics, defined as those intended for the safe and effective treatment, diagnosis or prevention of rare diseases and/or disorders that affect fewer than 200 000 people in the United States, or that affect more than 200 000 persons but are not expected to recover the costs of developing and marketing a treatment drug. These regulations have led to the translation of rare disease knowledge into innovative rare disease therapies. The FDA Guidance for Industry on developing drugs for the treatment and prevention of NTDs describes the following regulatory strategies: Orphan Product Designation, Fast Track Designation, Priority Review Designation, Accelerated Approval and Tropical Disease Priority Review Voucher. This paper will discuss how these regulations and especially the ODDP can improve the clinical development and accessibility of drug products for NTDs.
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Astashkina, Anna; Grainger, David W
2014-04-01
Drug failure due to toxicity indicators remains among the primary reasons for staggering drug attrition rates during clinical studies and post-marketing surveillance. Broader validation and use of next-generation 3-D improved cell culture models are expected to improve predictive power and effectiveness of drug toxicological predictions. However, after decades of promising research significant gaps remain in our collective ability to extract quality human toxicity information from in vitro data using 3-D cell and tissue models. Issues, challenges and future directions for the field to improve drug assay predictive power and reliability of 3-D models are reviewed. Copyright © 2014 Elsevier B.V. All rights reserved.
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Frueh, Felix W
2008-11-01
It is 10 years since the introduction of trastuzumab into the US market, and we are still waiting for a validation of the business case for biomarker-driven drug development. While many reasons for the lack of duplication of this model may exist, the need for accelerated innovation in drug development paired with the opportunity of integrating biomarker-driven research into drug development programs may lead to new and creative ways of fostering the cooperation between drug developers and test manufacturers. The rapid increase in knowledge about biomarkers and our understanding of disease and disease mechanisms open unprecedented prospects to make not only better, more informed decisions regarding patient care, but also strategic decisions during drug development. This requires that a biomarker strategy becomes an integral part of (early) drug development and that new, innovative paths are tried towards a model that combines the scientific approach with an economically feasible implementation strategy. Collaborative research, the use of new communication tools, the exploration of alternative ways to position a product in the market, and other considerations are part of such a strategy. This perspective article illustrates the current landscape and takes a look at some of these new ways for more effectively integrating biomarkers into drug development.
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A developmental etiological model for drug abuse in men.
Kendler, Kenneth S; Ohlsson, Henrik; Edwards, Alexis C; Sundquist, Jan; Sundquist, Kristina
2017-10-01
We attempt to develop a relatively comprehensive structural model of risk factors for drug abuse (DA) in Swedish men that illustrates developmental and mediational processes. We examined 20 risk factors for DA in 48,369 men undergoing conscription examinations in 1969-70 followed until 2011 when 2.34% (n=1134) of them had DA ascertained in medical, criminal and pharmacy registries. Risk factors were organized into four developmental tiers reflecting i) birth, ii) childhood/early adolescence, iii) late adolescence, and iv) young adulthood. Structural equational model fitting was performed using Mplus. The best fitting model explained 47.8% of the variance in DA. The most prominent predictors, in order, were: early adolescent externalizing behavior, early adult criminal behavior, early adolescent internalizing behavior, early adult unemployment, early adult alcohol use disorder, and late adolescent drug use. Two major inter-connecting pathways emerged reflecting i) genetic/familial risk and ii) family dysfunction and psychosocial adversity. Generated on a first and tested on a second random half of the sample, a model from these variables predicted DA with an ROC area under the curve of 83.6%. Fifty-nine percent of DA cases arose from subjects in the top decile of risk. DA in men is a highly multifactorial syndrome with risk arising from familial-genetic, psychosocial, behavioral and psychological factors acting and interacting over development. Among the multiple predisposing factors for DA, a range of psychosocial adversities, externalizing psychopathology and lack of social constraints in early adulthood are predominant. Copyright © 2017 Elsevier B.V. All rights reserved.
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Dahan, Arik; Markovic, Milica; Keinan, Shahar; Kurnikov, Igor; Aponick, Aaron; Zimmermann, Ellen M.; Ben-Shabat, Shimon
2017-11-01
Targeting drugs to the inflamed intestinal tissue(s) represents a major advancement in the treatment of inflammatory bowel disease (IBD). In this work we present a powerful in-silico modeling approach to guide the molecular design of novel prodrugs targeting the enzyme PLA2, which is overexpressed in the inflamed tissues of IBD patients. The prodrug consists of the drug moiety bound to the sn-2 position of phospholipid (PL) through a carbonic linker, aiming to allow PLA2 to release the free drug. The linker length dictates the affinity of the PL-drug conjugate to PLA2, and the optimal linker will enable maximal PLA2-mediated activation. Thermodynamic integration and Weighted Histogram Analysis Method (WHAM)/Umbrella Sampling method were used to compute the changes in PLA2 transition state binding free energy of the prodrug molecule (ΔΔGtr) associated with decreasing/increasing linker length. The simulations revealed that 6-carbons linker is the optimal one, whereas shorter or longer linkers resulted in decreased PLA2-mediated activation. These in-silico results were shown to be in excellent correlation with experimental in-vitro data. Overall, this modern computational approach enables optimization of the molecular design of novel prodrugs, which may allow targeting the free drug specifically to the diseased intestinal tissue of IBD patients.
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Directory of Open Access Journals (Sweden)
Himanshu R Gupta
2016-12-01
exposure times used in this study. The embryonic zebrafish model is recommended as a well-established method for rapidly assessing the toxicity of homeopathic drugs.
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Interstitial fluid flow and drug delivery in vascularized tumors: a computational model.
Directory of Open Access Journals (Sweden)
Michael Welter
Full Text Available Interstitial fluid is a solution that bathes and surrounds the human cells and provides them with nutrients and a way of waste removal. It is generally believed that elevated tumor interstitial fluid pressure (IFP is partly responsible for the poor penetration and distribution of therapeutic agents in solid tumors, but the complex interplay of extravasation, permeabilities, vascular heterogeneities and diffusive and convective drug transport remains poorly understood. Here we consider-with the help of a theoretical model-the tumor IFP, interstitial fluid flow (IFF and its impact upon drug delivery within tumor depending on biophysical determinants such as vessel network morphology, permeabilities and diffusive vs. convective transport. We developed a vascular tumor growth model, including vessel co-option, regression, and angiogenesis, that we extend here by the interstitium (represented by a porous medium obeying Darcy's law and sources (vessels and sinks (lymphatics for IFF. With it we compute the spatial variation of the IFP and IFF and determine its correlation with the vascular network morphology and physiological parameters like vessel wall permeability, tissue conductivity, distribution of lymphatics etc. We find that an increased vascular wall conductivity together with a reduction of lymph function leads to increased tumor IFP, but also that the latter does not necessarily imply a decreased extravasation rate: Generally the IF flow rate is positively correlated with the various conductivities in the system. The IFF field is then used to determine the drug distribution after an injection via a convection diffusion reaction equation for intra- and extracellular concentrations with parameters guided by experimental data for the drug Doxorubicin. We observe that the interplay of convective and diffusive drug transport can lead to quite unexpected effects in the presence of a heterogeneous, compartmentalized vasculature. Finally we discuss
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Interstitial fluid flow and drug delivery in vascularized tumors: a computational model.
Welter, Michael; Rieger, Heiko
2013-01-01
Interstitial fluid is a solution that bathes and surrounds the human cells and provides them with nutrients and a way of waste removal. It is generally believed that elevated tumor interstitial fluid pressure (IFP) is partly responsible for the poor penetration and distribution of therapeutic agents in solid tumors, but the complex interplay of extravasation, permeabilities, vascular heterogeneities and diffusive and convective drug transport remains poorly understood. Here we consider-with the help of a theoretical model-the tumor IFP, interstitial fluid flow (IFF) and its impact upon drug delivery within tumor depending on biophysical determinants such as vessel network morphology, permeabilities and diffusive vs. convective transport. We developed a vascular tumor growth model, including vessel co-option, regression, and angiogenesis, that we extend here by the interstitium (represented by a porous medium obeying Darcy's law) and sources (vessels) and sinks (lymphatics) for IFF. With it we compute the spatial variation of the IFP and IFF and determine its correlation with the vascular network morphology and physiological parameters like vessel wall permeability, tissue conductivity, distribution of lymphatics etc. We find that an increased vascular wall conductivity together with a reduction of lymph function leads to increased tumor IFP, but also that the latter does not necessarily imply a decreased extravasation rate: Generally the IF flow rate is positively correlated with the various conductivities in the system. The IFF field is then used to determine the drug distribution after an injection via a convection diffusion reaction equation for intra- and extracellular concentrations with parameters guided by experimental data for the drug Doxorubicin. We observe that the interplay of convective and diffusive drug transport can lead to quite unexpected effects in the presence of a heterogeneous, compartmentalized vasculature. Finally we discuss various
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Balancing the benefits and costs of antibiotic drugs: the TREAT model.
Leibovici, L; Paul, M; Andreassen, S
2010-12-01
TREAT is a computerized decision support system aimed at improving empirical antibiotic treatment of inpatients with suspected bacterial infections. It contains a model that balances, for each antibiotic choice (including 'no antibiotics'), expected benefit and expected costs. The main benefit afforded by appropriate, empirical, early antibiotic treatment in moderate to severe infections is a better chance of survival. Each antibiotic drug was consigned three cost components: cost of the drug and administration; cost of side effects; and costs of future resistance. 'No treatment' incurs no costs. The model worked well for decision support. Its analysis showed, yet again, that for moderate to severe infections, a model that does not include costs of resistance to future patients will always return maximum antibiotic treatment. Two major moral decisions are hidden in the model: how to take into account the limited life-expectancy and limited quality of life of old or very sick patients; and how to assign a value for a life-year of a future, unnamed patient vs. the present, individual patient. © 2010 The Authors. Clinical Microbiology and Infection © 2010 European Society of Clinical Microbiology and Infectious Diseases.
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Evered, Kyle T; Evered, Emine Ö
2016-07-01
In the 1970s, Turkey ceased to be a significant producer state of illicit drugs, but it continued to serve as a key route for the trade of drugs between East and West. Over the past decade, however, authorities identified two concerns beyond its continued transit state status. These reported problems entail both new modes of production and a rising incidence of drug abuse within the nation-state - particularly among its youth. Amid these developments, new law enforcement institutions emerged and acquired European sponsorship, leading to the establishment of TUBİM (the Turkish Monitoring Center for Drugs and Drug Addiction). Coordinating with and reporting to the European Union agency EMCDDA (the European Monitoring Center for Drugs and Drug Addiction), TUBİM's primary assigned duties entail the collection and analysis of data on drug abuse, trafficking, and prevention, the geographic identification of sites of concern (e.g. consumption, drug-related crimes, and peoples undergoing treatment), and the production of annual national reports. In this article, we examine the geopolitical origins of TUBİM as Turkey's central apparatus for confronting drug problems and its role as a vehicle for policy development, interpretation, and enforcement. In doing so, we emphasize the political and spatial dimensions inherent to the country's institutional and policy-driven approaches to contend with drug-related problems, and we assess how this line of attack reveals particular ambiguities in mission when evaluated from scales at world regional, national, and local levels. In sum, we assess how Turkey's new institutional and legislative landscapes condition the state's engagements with drug use, matters of user's health, and policy implementation at local scales and amid ongoing political developments. Copyright © 2016 Elsevier B.V. All rights reserved.
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Predictive tools for the evaluation of microbial effects on drugs during gastrointestinal passage.
Pieper, Ines A; Bertau, Martin
2010-06-01
Predicting drug metabolism after oral administration is highly complex, yet indispensable. Hitherto, drug metabolism mainly focuses on hepatic processes. In the intestine, drug molecules encounter the metabolic activity of microorganisms prior to absorption through the gut wall. Drug biotransformation through the gastrointestinal microflora has the potential to evoke serious problems because the metabolites formed may cause unexpected and undesired side effects in patients. Hence, in the course of drug development, the question has to be addressed if microbially formed metabolites are physiologically active, pharmaceutically active or even toxic. In order to provide answers to these questions and to keep the number of laboratory tests needed low, predictive tools - in vivo as well as in silico - are invaluable. This review gives an outline of the current state of the art in the field of predicting the drug biotransformation through the gastrointestinal microflora on several levels of modelling. A comprehensive review of the literature with a thorough discussion on assets and drawbacks of the different modelling approaches. The impact of the gastrointestinal drug biotransformation on patients' health will grow with increasing complexity of drug entities. Predicting metabolic fates of drugs by combining in vitro and in silico models provides invaluable information which will be suitable to particularly reduce in vivo studies.
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Experimental methods and transport models for drug delivery across the blood-brain barrier.
Fu, Bingmei M
2012-06-01
The blood-brain barrier (BBB) is a dynamic barrier essential for maintaining the micro-environment of the brain. Although the special anatomical features of the BBB determine its protective role for the central nervous system (CNS) from blood-born neurotoxins, however, the BBB extremely limits the therapeutic efficacy of drugs into the CNS, which greatly hinders the treatment of major brain diseases. This review summarized the unique structures of the BBB, described a variety of in vivo and in vitro experimental methods for determining the transport properties of the BBB, e.g., the permeability of the BBB to water, ions, and solutes including nutrients, therapeutic agents and drug carriers, and presented newly developed mathematical models which quantitatively correlate the anatomical structures of the BBB with its barrier functions. Finally, on the basis of the experimental observations and the quantitative models, several strategies for drug delivery through the BBB were proposed.
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Garcia, Victor
2011-01-01
To help in understanding the manner in which community, individual, and other factors in the United States and Mexico contribute to drug use among transnational migrants, this paper introduces a binational social ecology model of substance abuse in this population. We draw on our 2 NIH-funded ethnographic studies—1 on problem drinking and the other on drug abuse—among transnational Mexican workers in the mushroom industry of southeastern Pennsylvania. Our model demonstrates that major reasons for substance abuse among transnational migrants include nontraditional living arrangements in labor camps and overcrowded apartments, the absence of kin and community deterrents to drug use, social isolation, the presence of drug use and binge drinking subcultures, the availability of drugs, family history of drugs, previous drug use or witnessing of drug use in Mexico, and drug use norms and drug availability in Mexico. It suggests the need for US and Mexican researchers to collaborate in binational teams and address factors on both sides of the border. Our binational social ecology model, together with our research recommendations, will assist alcohol and drug researchers to discover how community and individual factors in both the United States and abroad fit and interact beyond mere association and provide a more comprehensive research approach to substance abuse research among transnational migrants. PMID:18237326
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Towards a pragmatic human migraine model for drug testing
DEFF Research Database (Denmark)
Hansen, Emma Katrine; Olesen, Jes
2017-01-01
Background A model for the testing of novel anti-migraine drugs should preferably use healthy volunteers for ease of recruiting. Isosorbide-5-mononitrate (5-ISMN) provokes headache in healthy volunteers with some migraine features such as pulsating pain quality and aggravation by physical activity.......003). Difference in area under the headache score curve (AUC) 0-4 hours between sumatriptan and placebo was not significant ( p = 0.30). Conclusion 5-ISMN is a very powerful inducer of migraine-like headache in healthy individuals but the headache does not respond to sumatriptan. The model is not useful for future...
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A model of directional selection applied to the evolution of drug resistance in HIV-1.
Seoighe, Cathal; Ketwaroo, Farahnaz; Pillay, Visva; Scheffler, Konrad; Wood, Natasha; Duffet, Rodger; Zvelebil, Marketa; Martinson, Neil; McIntyre, James; Morris, Lynn; Hide, Winston
2007-04-01
Understanding how pathogens acquire resistance to drugs is important for the design of treatment strategies, particularly for rapidly evolving viruses such as HIV-1. Drug treatment can exert strong selective pressures and sites within targeted genes that confer resistance frequently evolve far more rapidly than the neutral rate. Rapid evolution at sites that confer resistance to drugs can be used to help elucidate the mechanisms of evolution of drug resistance and to discover or corroborate novel resistance mutations. We have implemented standard maximum likelihood methods that are used to detect diversifying selection and adapted them for use with serially sampled reverse transcriptase (RT) coding sequences isolated from a group of 300 HIV-1 subtype C-infected women before and after single-dose nevirapine (sdNVP) to prevent mother-to-child transmission. We have also extended the standard models of codon evolution for application to the detection of directional selection. Through simulation, we show that the directional selection model can provide a substantial improvement in sensitivity over models of diversifying selection. Five of the sites within the RT gene that are known to harbor mutations that confer resistance to nevirapine (NVP) strongly supported the directional selection model. There was no evidence that other mutations that are known to confer NVP resistance were selected in this cohort. The directional selection model, applied to serially sampled sequences, also had more power than the diversifying selection model to detect selection resulting from factors other than drug resistance. Because inference of selection from serial samples is unlikely to be adversely affected by recombination, the methods we describe may have general applicability to the analysis of positive selection affecting recombining coding sequences when serially sampled data are available.
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A drug's life: the pathway to drug approval.
Keng, Michael K; Wenzell, Candice M; Sekeres, Mikkael A
2013-10-01
In the United States, drugs and medical devices are regulated by the US Food and Drug Administration (FDA). A drug must undergo rigorous testing prior to marketing to and medical use by the general public. The FDA grants marketing approval for drug products based on a comprehensive review of safety and efficacy data. This review article explains the history behind the establishment of the FDA and examines the historical legislation and approval processes for drugs, specifically in the fields of medical oncology and hematology. The agents imatinib (Gleevec, Novartis) and decitabine (Dacogen, Eisai) are used to illustrate both the current FDA regulatory process-specifically the orphan drug designation and accelerated approval process-and why decitabine failed to gain an indication for acute myeloid leukemia. The purpose and construct of the Oncologic Drugs Advisory Committee are also discussed, along with examples of 2 renal cell cancer drugs-axitinib (Inlyta, Pfizer) and tivozanib-that used progression-free survival as an endpoint. Regulatory approval of oncology drugs is the cornerstone of the development of new treatment agents and modalities, which lead to improvements in the standard of cancer care. The future landscape of drug development and regulatory approval will be influenced by the new breakthrough therapy designation, and choice of drug will be guided by genomic insights.
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Modelling applied to PET-studies ont blood-brain transfer of 11-C-labelled drugs in the dog
International Nuclear Information System (INIS)
Agon, P.; Kaufman, J.M.
1989-01-01
Positron emission tomograph (PET) allows the 'in vivo' monitoring of changes in tissue concentrations of a labelled compounds. In order to validate the technique for the study of the early distribution of drugs into the braiin occuring following intravenous administration. The distribution in anaesthetized dogs of several 11-C-labelled drugs with known physicochemical and pharmacokinetic properties was studied. Twenty five sequential scans of a single slice of the head were performed using a Neuro-ECAT positron camera over 90 minutes following intravenous administration. Arterial blood samples were obtained for monitoring of blood and plasma radioactivity. Blood-brain transfer of the drugs was also studied after blood-brain barrier disruption by intracarotid infusion of a hyperosmolar mannitol solution. A qualitative evaluation of drug distribution can be done by visual inspection of the radioactivity concentration-time curves obtained for blood and tissues; for a quantitative evaluation a mathematical approach was required. A four compartment unit-membrane model can be suggested as a generally applicable model. For all the drugs studied, a model with 2 compartments described the course of the radioactivity quite well. In experiments with blood-brain barrier disruption the conditions for blood-brain exchange are changed and a 4 compartment model was required to describe adequately the course of the radioactivity. The results obtained when applying these models to sets of data for different drugs, were in good agreement with their known properties. (author). 4 refs.; 4 figs
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Baheti, Kirtee; Kale, Mayura Ajay
2018-04-17
Since last two decades, there has been more focus on the development strategies related to Anti-Alzheimer's drug research. This may be attributed to the fact that most of the Alzheimer's cases are still mostly unknown except for a few cases, where genetic differences have been identified. With the progress of the disease, the symptoms involve intellectual deterioration, memory impairment, abnormal personality and behavioural patterns, confusion, aggression, mood swings, irritability Current therapies available for this disease give only symptomatic relief and do not focus on manipulations of biololecular processes. Nearly all the therapies to treat Alzheimer's disease, target to change the amyloid cascade which is considered to be an important in AD pathogenesis. New drug regimens are not able to keep pace with the ever-increasing understanding about dementia at molecular level. Looking into these aggravated problems, we though to put forth molecular modeling as a drug discovery approach for developing novel drugs to treat Alzheimer disease. The disease is incurable and it gets worst as it advances and finally causes death. Due to this, the design of drugs to treat this disease has become an utmost priority for research. One of the most important emerging technologies applied for this has been Computer-assisted drug design (CADD). It is a research tool that employs large scale computing strategies in an attempt to develop a model receptor site which can be used for designing of an anti-Alzheimer drug. The various models of amyloid-based calcium channels have been computationally optimized. Docking and De novo evolution are used to design the compounds. These are further subjected to absorption, distribution, metabolism, excretion and toxicity (ADMET) studies to finally bring about active compounds that are able to cross BBB. Many novel compounds have been designed which might be promising ones for the treatment of AD. The present review describes the research
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Advisory Board on Alcoholism and Drug Abuse
State Employees Advisory Board on Alcoholism and Drug Abuse DHSS State of Alaska Home Divisions and ; Advisory Board on Alcoholism and Drug Abuse Page Content Alison Kulas Executive Director If you, a family Kulas Begins Tenure as Executive Director The Advisory Board on Alcoholism and Drug Abuse, The Alaska
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Lacey, John H.; Kelley-Baker, Tara; Voas, Robert B.; Romano, Eduardo; Furr-Holden, C. Debra; Torres, Pedro; Berning, Amy
2013-01-01
This article describes the methodology used in the 2007 U.S. National Roadside Survey to estimate the prevalence of alcohol- and drug-impaired driving and alcohol- and drug-involved driving. This study involved randomly stopping drivers at 300 locations across the 48 continental U.S. states at sites selected through a stratified random sampling procedure. Data were collected during a 2-hour Friday daytime session at 60 locations and during 2-hour nighttime weekend periods at 240 locations. Both self-report and biological measures were taken. Biological measures included breath alcohol measurements from 9,413 respondents, oral fluid samples from 7,719 respondents, and blood samples from 3,276 respondents. PMID:21997324
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Targeting Antibacterial Agents by Using Drug-Carrying Filamentous Bacteriophages
Yacoby, Iftach; Shamis, Marina; Bar, Hagit; Shabat, Doron; Benhar, Itai
2006-01-01
Bacteriophages have been used for more than a century for (unconventional) therapy of bacterial infections, for half a century as tools in genetic research, for 2 decades as tools for discovery of specific target-binding proteins, and for nearly a decade as tools for vaccination or as gene delivery vehicles. Here we present a novel application of filamentous bacteriophages (phages) as targeted drug carriers for the eradication of (pathogenic) bacteria. The phages are genetically modified to display a targeting moiety on their surface and are used to deliver a large payload of a cytotoxic drug to the target bacteria. The drug is linked to the phages by means of chemical conjugation through a labile linker subject to controlled release. In the conjugated state, the drug is in fact a prodrug devoid of cytotoxic activity and is activated following its dissociation from the phage at the target site in a temporally and spatially controlled manner. Our model target was Staphylococcus aureus, and the model drug was the antibiotic chloramphenicol. We demonstrated the potential of using filamentous phages as universal drug carriers for targetable cells involved in disease. Our approach replaces the selectivity of the drug itself with target selectivity borne by the targeting moiety, which may allow the reintroduction of nonspecific drugs that have thus far been excluded from antibacterial use (because of toxicity or low selectivity). Reintroduction of such drugs into the arsenal of useful tools may help to combat emerging bacterial antibiotic resistance. PMID:16723570
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Drug detection by terahertz time-domain spectroscopy
International Nuclear Information System (INIS)
Duan Ruixin; Zhu Yiming; Zhao Hongwei
2013-01-01
Due to unique spectral region, functional imaging ability, excellent penetration and safety characteristics of terahertz radiation, the terahertz technology rapidly becomes a vital method to detect and analyze drugs. In this paper, firstly, we identify the functional groups of anti-diabetic drugs by density functional theory (DFT), HIPHOP models and experimental results from terahertz time-domain spectroscopy measurements. Secondly, we identify four kinds of herbs of radix curcumae by using the support vector machine (SVM) analysis. Besides, we analyze the absorption of anhydrous and hydrous glucose, and determine the state of water in the crystalized D-glucose·H 2 O through the results of differential scanning calorimetry measurement. Finally, we summarize the advantages and disadvantages of terahertz time-domain spectroscopy method in drug detection and analyzing. (authors)
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Reynoso-Vallejo, Humberto; Chassler, Deborah; Witas, Julie; Lundgren, Lena M
2008-02-01
This study examined patterns of treatment entry by Puerto Rican, Central American, Dominican, and other Latino male injection drug users (IDUs) in the state of Massachusetts over the time period 1996-2002. Specifically, it explored whether these populations had different patterns relative to three paths: entry into detoxification only, entry into residential treatment, or entry into methadone maintenance. Using a state-level MIS dataset on all substance abuse treatment entries to all licensed treatment programs, bi-variate and logistic regression methods were employed to examine patterns of drug treatment utilization among Latino men residing in Massachusetts. Three logistic regression models, which controlled for age, education, homelessness, employment, history of mental health treatment, health insurance, criminal justice involvement, having injected drugs in the past month, and number of treatment entries, indicated that Puerto Rican men were significantly less likely to only use detoxification services and residential treatment services, and significantly more likely to enter methadone maintenance compared to Latino men from Central American, Dominican, or other Latino backgrounds. For example, Central American men were 2.4 times more likely to enter only detoxification programs and 54% less likely to enter methadone maintenance programs than Puerto Rican male IDUs. For program planning, include the need to (a) develop varied drug treatment services to meet the needs of non-homogenous Latino groups within the population, (b) tailor outreach efforts to effectively reach all Latino groups, and (c) increase awareness among practitioners of differential patterns of treatment utilization.
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Directory of Open Access Journals (Sweden)
Zaloumis Sophie
2012-08-01
Full Text Available Abstract Background Mechanistic within-host models relating blood anti-malarial drug concentrations with the parasite-time profile help in assessing dosing schedules and partner drugs for new anti-malarial treatments. A comprehensive simulation study to assess the utility of a stage-specific pharmacokinetic-pharmacodynamic (PK-PD model for predicting within-host parasite response was performed. Methods Three anti-malarial combination therapies were selected: artesunate-mefloquine, dihydroartemisinin-piperaquine, and artemether-lumefantrine. The PK-PD model included parameters to represent the concentration-time profiles of both drugs, the initial parasite burden and distribution across the parasite life cycle, and the parasite multiplication factor due to asexual reproduction. The model also included the maximal killing rate of each drug, and the blood drug concentration associated with half of that killing effect (in vivo EC50, derived from the in vitro IC50, the extent of binding to 0.5% Albumax present in the in vitro testing media, and the drugs plasma protein binding and whole blood to plasma partitioning ratio. All stochastic simulations were performed using a Latin-Hypercube-Sampling approach. Results The simulations demonstrated that the proportion of patients cured was highly sensitive to the in vivo EC50 and the maximal killing rate of the partner drug co-administered with the artemisinin derivative. The in vivo EC50 values that corresponded to on average 95% of patients cured were much higher than the adjusted values derived from the in vitro IC50. The proportion clinically cured was not strongly influenced by changes in the parameters defining the age distribution of the initial parasite burden (mean age of 4 to 16 hours and the parasite multiplication factor every life cycle (ranging from 8 to 12 fold/cycle. The median parasite clearance times, however, lengthened as the standard deviation of the initial parasite burden increased (i
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Intestinal Oxidative State Can Alter Nutrient and Drug Bioavailability
Directory of Open Access Journals (Sweden)
Faria Ana
2009-01-01
Full Text Available Organic cations (OCs are substances of endogenous (e.g., dopamine, choline or exogenous (e.g., drugs like cimetidine origin that are positively charged at physiological ph. since many of these compounds can not pass the cell membrane freely, their transport in or out of cells must be mediated by specific transport systems. Transport by organic cation transporters (OCTs can be regulated rapidly by altering their trafficking and/or affinities in response to stimuli. However, for example, a specific disease could lead to modifications in the expression of OCTs. Chronic exposure to oxidative stress has been suggested to alter regulation and functional activity of proteins through several pathways. According to results from a previous work, oxidation-reduction pathways were thought to be involved in intestinal organic cation uptake modulation. The present work was performed in order to evaluate the influence of oxidative stressors, especially glutathione, on the intestinal organic cation absorption. For this purpose, the effect of compounds with different redox potential (glutathione, an endogenous antioxidant, and procyanidins, diet antioxidants was assessed on MPP+ (1-methyl-4-phenylpyridinium iodide uptake in an enterocyte cell line (Caco-2. Caco-2 cells were subcultured with two different media conditions (physiological: 5 mM glucose, referred as control cells; and high-glucose: 25 mM glucose, referred as HG cells. In HG cells, the uptake was significantly lower than in control cells. Redox changing interventions affected Mpp+ uptake, both in control and in high-glucose Caco-2 cells. Cellular glutathione levels could have an important impact on membrane transporter activity. The results indicate that modifications in the cellular oxidative state modulate MPP+ uptake by Caco-2 cells. Such modifications may reflect in changes of nutrient and drug bioavailability.
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Microfluidic-Based Multi-Organ Platforms for Drug Discovery
Directory of Open Access Journals (Sweden)
Ahmad Rezaei Kolahchi
2016-09-01
Full Text Available Development of predictive multi-organ models before implementing costly clinical trials is central for screening the toxicity, efficacy, and side effects of new therapeutic agents. Despite significant efforts that have been recently made to develop biomimetic in vitro tissue models, the clinical application of such platforms is still far from reality. Recent advances in physiologically-based pharmacokinetic and pharmacodynamic (PBPK-PD modeling, micro- and nanotechnology, and in silico modeling have enabled single- and multi-organ platforms for investigation of new chemical agents and tissue-tissue interactions. This review provides an overview of the principles of designing microfluidic-based organ-on-chip models for drug testing and highlights current state-of-the-art in developing predictive multi-organ models for studying the cross-talk of interconnected organs. We further discuss the challenges associated with establishing a predictive body-on-chip (BOC model such as the scaling, cell types, the common medium, and principles of the study design for characterizing the interaction of drugs with multiple targets.
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African Journals Online (AJOL)
Background: The Drug Revolving Fund (DRF) was instituted in 1996 in Oyo State to ensure sustainable drug availability at primary health care level with a seed stock of drugs supplied by the Petroleum Trust Fund. This was discontinued in 1999 and replaced in January 2000, with free health service, which involves ...
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Biomarkers of adverse drug reactions.
Carr, Daniel F; Pirmohamed, Munir
2018-02-01
Adverse drug reactions can be caused by a wide range of therapeutics. Adverse drug reactions affect many bodily organ systems and vary widely in severity. Milder adverse drug reactions often resolve quickly following withdrawal of the casual drug or sometimes after dose reduction. Some adverse drug reactions are severe and lead to significant organ/tissue injury which can be fatal. Adverse drug reactions also represent a financial burden to both healthcare providers and the pharmaceutical industry. Thus, a number of stakeholders would benefit from development of new, robust biomarkers for the prediction, diagnosis, and prognostication of adverse drug reactions. There has been significant recent progress in identifying predictive genomic biomarkers with the potential to be used in clinical settings to reduce the burden of adverse drug reactions. These have included biomarkers that can be used to alter drug dose (for example, Thiopurine methyltransferase (TPMT) and azathioprine dose) and drug choice. The latter have in particular included human leukocyte antigen (HLA) biomarkers which identify susceptibility to immune-mediated injuries to major organs such as skin, liver, and bone marrow from a variety of drugs. This review covers both the current state of the art with regard to genomic adverse drug reaction biomarkers. We also review circulating biomarkers that have the potential to be used for both diagnosis and prognosis, and have the added advantage of providing mechanistic information. In the future, we will not be relying on single biomarkers (genomic/non-genomic), but on multiple biomarker panels, integrated through the application of different omics technologies, which will provide information on predisposition, early diagnosis, prognosis, and mechanisms. Impact statement • Genetic and circulating biomarkers present significant opportunities to personalize patient therapy to minimize the risk of adverse drug reactions. ADRs are a significant heath issue
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The liberal state and the rogue agency: FDA's regulation of drugs for mood disorders, 1950s-1970s.
Shorter, Edward
2008-01-01
The theory of the liberal state does not generally contemplate the possibility that regulatory agencies will turn into "rogues," regulating against the interests of their clients and, indeed, the public interest. In the years between circa 1955 and 1975 this seems to have happened to one of the prime regulatory agencies of the US federal government: the Food and Drug Administration (FDA). Intent upon transforming itself from a traditional "cop" agency to a regulatory giant, the FDA campaigned systematically to bring down some safe and effective drugs. This article concentrates on hearings in the area of psychopharmacology regarding several antianxiety drugs, namely meprobamate (Miltown), chlordiazepoxide (Librium) and diazepam (Valium). In addition, from 1967 to 1973 this regulatory vengefulness occurred on a broad scale in the Drug Efficacy Study Implementation (DESI), an administrative exercise that removed from the market almost half of the psychopharmacopoeia. The article explores possible bureaucratic motives for these actions.
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Evaluation of radiation doses from radioactive drugs
International Nuclear Information System (INIS)
Halperin, J.A.; Grove, G.R.
1977-01-01
Radioactive new drugs are regulated by the Food and Drug Administration (FDA) in the United States. Before a new drug can be marketed it must have an approved New Drug Application (NDA). Clinical investigations of a radioactive new drug are carried out under a Notice of Claimed Investigational Exemption for a New Drug (IND), submitted to the FDA. In the review of the IND, radiation doses are projected on the basis of experimental data from animal models and from calculations based upon radiation characteristics, predicted biodistribution of the drug in humans, and activity to be administered. FDA physicians review anticipated doses and prevent clinical investigations in humans when the potential risk of the use of a radioactive substance outweighs the prospect of achieving beneficial results from the administration of the drug. In the evaluation of an NDA, FDA staff attempt to assure that the intended diagnostic or therapeutic effect is achievable with the lowest practicable radiation dose. Radiation doses from radioactive new drugs are evaluated by physicians within the FDA. Important radioactive new drugs are also evaluated by the Radiopharmaceuticals Advisory Committee. FDA also supports the Center for Internal Radiation Dosimetry at Oak Ridge, to provide information regarding in vivo distribution and dosimetry to critical organs and the whole body from radioactive new drugs. The process for evaluation of radiation doses from radioactive new drugs for protection against use of unnecessary radiation exposure by patients in nuclear medicine procedures, a
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Directory of Open Access Journals (Sweden)
Jorge Delva
1998-11-01
Full Text Available This study examines nonmedical injecting drug use (IDU among Latinas aged 12 years and older in a nationally representative sample of U.S. households. Data from the 1990-1995 National Household Surveys on Drug Abuse disclosed 154 Latinas with self-reported histories of IDU out of 18 335 Latinas who responded. Hypotheses about correlates of IDU were tested by using the conditional form of multiple logistic regression to compare the characteristics of these IDUs with those of 602 noninjecting Latinas matched on neighborhood of residence. In the USA, an estimated 1% of Latinas age 12 years and older have injected drugs for non-medical purposes on at least one occasion. IDU was 4.6 to 6.5 times greater for adult Latinas (18-44 years old when compared to Latinas aged either 12 through 17 years (P < 0.05 or older than 44 years. IDU was an estimated 7.1 times greater for Latinas who reported marijuana use and 5.4 times greater for Latinas who reported inhalant use when compared to Latinas not using these drugs (P < 0.01. In light of recent studies indicating that IDU is a serious public health problem for Latinas in the United States, the observed associations represent first steps in an effort to understand the Latina subgroups most affected by IDU and the underlying risk factors or causes of this behavior.
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A Model for Random Student Drug Testing
Nelson, Judith A.; Rose, Nancy L.; Lutz, Danielle
2011-01-01
The purpose of this case study was to examine random student drug testing in one school district relevant to: (a) the perceptions of students participating in competitive extracurricular activities regarding drug use and abuse; (b) the attitudes and perceptions of parents, school staff, and community members regarding student drug involvement; (c)…
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Thermal safety of ultrasound-enhanced ocular drug delivery: A modeling study
Energy Technology Data Exchange (ETDEWEB)
Nabili, Marjan, E-mail: mnabili@gwmail.gwu.edu [Department of Electrical and Computer Engineering, The George Washington University, 800 22nd Street NW, Room 5000, Washington, DC 20052 (United States); Geist, Craig, E-mail: cgeist@mfa.gwu.edu, E-mail: zderic@gwu.edu [Department of Ophthalmology, The George Washington University, 2150 Pennsylvania Avenue NW, Floor 2A, Washington, DC 20037 (United States); Zderic, Vesna, E-mail: cgeist@mfa.gwu.edu, E-mail: zderic@gwu.edu [Department of Biomedical Engineering, The George Washington University, 800 22nd Street NW, Room 6670, Washington, DC 20052 (United States)
2015-10-15
Purpose: Delivery of sufficient amounts of therapeutic drugs into the eye for treatment of various ocular diseases is often a challenging task. Ultrasound was shown to be effective in enhancing ocular drug delivery in the authors’ previous in vitro and in vivo studies. Methods: The study reported here was designed to investigate the safety of ultrasound application and its potential thermal effects in the eye using PZFlex modeling software. The safety limit in this study was set as a temperature increase of no more than 1.5 °C based on regulatory recommendations and previous experimental safety studies. Acoustic and thermal specifications of different human eye tissues were obtained from the published literature. The tissues of particular interest in this modeling safety study were cornea, lens, and the location of optic nerve in the posterior eye. Ultrasound application was modeled at frequencies of 400 kHz–1 MHz, intensities of 0.3–1 W/cm{sup 2}, and exposure duration of 5 min, which were the parameters used in the authors’ previous drug delivery experiments. The baseline eye temperature was 37 °C. Results: The authors’ results showed that the maximal tissue temperatures after 5 min of ultrasound application were 38, 39, 39.5, and 40 °C in the cornea, 39.5, 40, 42, and 43 °C in the center of the lens, and 37.5, 38.5, and 39 °C in the back of the eye (at the optic nerve location) at frequencies of 400, 600, 800 kHz, and 1 MHz, respectively. Conclusions: The ocular temperatures reached at higher frequencies were considered unsafe based on current recommendations. At a frequency of 400 kHz and intensity of 0.8 W/cm{sup 2} (parameters shown in the authors’ previous in vivo studies to be optimal for ocular drug delivery), the temperature increase was small enough to be considered safe inside different ocular tissues. However, the impact of orbital bone and tissue perfusion should be included in future modeling efforts to determine the safety
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Thermal safety of ultrasound-enhanced ocular drug delivery: A modeling study
International Nuclear Information System (INIS)
Nabili, Marjan; Geist, Craig; Zderic, Vesna
2015-01-01
Purpose: Delivery of sufficient amounts of therapeutic drugs into the eye for treatment of various ocular diseases is often a challenging task. Ultrasound was shown to be effective in enhancing ocular drug delivery in the authors’ previous in vitro and in vivo studies. Methods: The study reported here was designed to investigate the safety of ultrasound application and its potential thermal effects in the eye using PZFlex modeling software. The safety limit in this study was set as a temperature increase of no more than 1.5 °C based on regulatory recommendations and previous experimental safety studies. Acoustic and thermal specifications of different human eye tissues were obtained from the published literature. The tissues of particular interest in this modeling safety study were cornea, lens, and the location of optic nerve in the posterior eye. Ultrasound application was modeled at frequencies of 400 kHz–1 MHz, intensities of 0.3–1 W/cm 2 , and exposure duration of 5 min, which were the parameters used in the authors’ previous drug delivery experiments. The baseline eye temperature was 37 °C. Results: The authors’ results showed that the maximal tissue temperatures after 5 min of ultrasound application were 38, 39, 39.5, and 40 °C in the cornea, 39.5, 40, 42, and 43 °C in the center of the lens, and 37.5, 38.5, and 39 °C in the back of the eye (at the optic nerve location) at frequencies of 400, 600, 800 kHz, and 1 MHz, respectively. Conclusions: The ocular temperatures reached at higher frequencies were considered unsafe based on current recommendations. At a frequency of 400 kHz and intensity of 0.8 W/cm 2 (parameters shown in the authors’ previous in vivo studies to be optimal for ocular drug delivery), the temperature increase was small enough to be considered safe inside different ocular tissues. However, the impact of orbital bone and tissue perfusion should be included in future modeling efforts to determine the safety of this
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Multi-Step Usage of in Vivo Models During Rational Drug Design and Discovery
Directory of Open Access Journals (Sweden)
Charles H. Williams
2011-04-01
Full Text Available In this article we propose a systematic development method for rational drug design while reviewing paradigms in industry, emerging techniques and technologies in the field. Although the process of drug development today has been accelerated by emergence of computational methodologies, it is a herculean challenge requiring exorbitant resources; and often fails to yield clinically viable results. The current paradigm of target based drug design is often misguided and tends to yield compounds that have poor absorption, distribution, metabolism, and excretion, toxicology (ADMET properties. Therefore, an in vivo organism based approach allowing for a multidisciplinary inquiry into potent and selective molecules is an excellent place to begin rational drug design. We will review how organisms like the zebrafish and Caenorhabditis elegans can not only be starting points, but can be used at various steps of the drug development process from target identification to pre-clinical trial models. This systems biology based approach paired with the power of computational biology; genetics and developmental biology provide a methodological framework to avoid the pitfalls of traditional target based drug design.
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International Nuclear Information System (INIS)
Lipkin, H.J.
1986-01-01
The success of simple constituent quark models in single-hardon physics and their failure in multiquark physics is discussed, emphasizing the relation between meson and baryon spectra, hidden color and the color matrix, breakup decay modes, coupled channels, and hadron-hadron interactions via flipping and tunneling of flux tubes. Model-independent predictions for possible multiquark bound states are considered and the most promising candidates suggested. A quark approach to baryon-baryon interactions is discussed
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Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor
2012-01-01
High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a
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What is a new drug worth? An innovative model for performance-based pricing.
Dranitsaris, G; Dorward, K; Owens, R C; Schipper, H
2015-05-01
This article focuses on a novel method to derive prices for new pharmaceuticals by making price a function of drug performance. We briefly review current models for determining price for a new product and discuss alternatives that have historically been favoured by various funding bodies. The progressive approach to drug pricing, proposed herein, may better address the views and concerns of multiple stakeholders in a developed healthcare system by acknowledging and incorporating input from disparate parties via comprehensive and successive negotiation stages. In proposing a valid construct for performance-based pricing, the following model seeks to achieve several crucial objectives: earlier and wider access to new treatments; improved transparency in drug pricing; multi-stakeholder involvement through phased pricing negotiations; recognition of innovative product performance and latent changes in value; an earlier and more predictable return for developers without sacrificing total return on investment (ROI); more involved and informed risk sharing by the end-user. © 2014 John Wiley & Sons Ltd.
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Brady, Oliver J; Slater, Hannah C; Pemberton-Ross, Peter; Wenger, Edward; Maude, Richard J; Ghani, Azra C; Penny, Melissa A; Gerardin, Jaline; White, Lisa J; Chitnis, Nakul; Aguas, Ricardo; Hay, Simon I; Smith, David L; Stuckey, Erin M; Okiro, Emelda A; Smith, Thomas A; Okell, Lucy C
2017-07-01
Mass drug administration for elimination of Plasmodium falciparum malaria is recommended by WHO in some settings. We used consensus modelling to understand how to optimise the effects of mass drug administration in areas with low malaria transmission. We collaborated with researchers doing field trials to establish a standard intervention scenario and standard transmission setting, and we input these parameters into four previously published models. We then varied the number of rounds of mass drug administration, coverage, duration, timing, importation of infection, and pre-administration transmission levels. The outcome of interest was the percentage reduction in annual mean prevalence of P falciparum parasite rate as measured by PCR in the third year after the final round of mass drug administration. The models predicted differing magnitude of the effects of mass drug administration, but consensus answers were reached for several factors. Mass drug administration was predicted to reduce transmission over a longer timescale than accounted for by the prophylactic effect alone. Percentage reduction in transmission was predicted to be higher and last longer at lower baseline transmission levels. Reduction in transmission resulting from mass drug administration was predicted to be temporary, and in the absence of scale-up of other interventions, such as vector control, transmission would return to pre-administration levels. The proportion of the population treated in a year was a key determinant of simulated effectiveness, irrespective of whether people are treated through high coverage in a single round or new individuals are reached by implementation of several rounds. Mass drug administration was predicted to be more effective if continued over 2 years rather than 1 year, and if done at the time of year when transmission is lowest. Mass drug administration has the potential to reduce transmission for a limited time, but is not an effective replacement for existing
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Chen, Yuejie; Wang, Shujing; Wang, Shan; Liu, Chengyu; Su, Ching; Hageman, Michael; Hussain, Munir; Haskell, Roy; Stefanski, Kevin; Qian, Feng
2016-10-01
To identify the key formulation factors controlling the initial drug and polymer dissolution rates from an amorphous solid dispersion (ASD). Ketoconazole (KTZ) ASDs using PVP, PVP-VA, HMPC, or HPMC-AS as polymeric matrix were prepared. For each drug-polymer system, two types of formulations with the same composition were prepared: 1. Spray dried dispersion (SDD) that is homogenous at molecular level, 2. Physical blend of SDD (80% drug loading) and pure polymer (SDD-PB) that is homogenous only at powder level. Flory-Huggins interaction parameters (χ) between KTZ and the four polymers were obtained by Flory-Huggins model fitting. Solution (13)C NMR and FT-IR were conducted to investigate the specific drug-polymer interaction in the solution and solid state, respectively. Intrinsic dissolution of both the drug and the polymer from ASDs were studied using a Higuchi style intrinsic dissolution apparatus. PXRD and confocal Raman microscopy were used to confirm the absence of drug crystallinity on the tablet surface before and after dissolution study. In solid state, KTZ is completely miscible with PVP, PVP-VA, or HPMC-AS, demonstrated by the negative χ values of -0.36, -0.46, -1.68, respectively; while is poorly miscible with HPMC shown by a positive χ value of 0.23. According to solution (13)C NMR and FT-IR studies, KTZ interacts with HPMC-AS strongly through H-bonding and dipole induced interaction; with PVPs and PVP-VA moderately through dipole-induced interactions; and with HPMC weakly without detectable attractive interaction. Furthermore, the "apparent" strength of drug-polymer interaction, measured by the extent of peak shift on NMR or FT-IR spectra, increases with the increasing number of interacting drug-polymer pairs. For ASDs with the presence of considerable drug-polymer interactions, such as KTZ/PVPs, KTZ/PVP-VA, or KTZ /HPMC-AS systems, drug released at the same rate as the polymer when intimate drug-polymer mixing was ensured (i.e., the SDD systems
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Formulating state space models in R with focus on longitudinal regression models
DEFF Research Database (Denmark)
Dethlefsen, Claus; Lundbye-Christensen, Søren
2006-01-01
We provide a language for formulating a range of state space models with response densities within the exponential family. The described methodology is implemented in the R-package sspir. A state space model is specified similarly to a generalized linear model in R, and then the time-varying terms...
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Lam, P L; Gambari, R
2014-03-28
This review provides an overall discussion of microencapsulation systems for both oral and transdermal drug deliveries. Clinically, many drugs, especially proteins and peptides, are susceptible to the gastrointestinal tract and the first-pass metabolism after oral administration while some drugs exhibit low skin permeability through transdermal delivery route. Medicated microcapsules as oral and transdermal drug delivery vehicles are believed to offer an extended drug effect at a relatively low dose and provide a better patient compliance. The polymeric microcapsules can be produced by different microencapsulation methods and the drug microencapsulation technology provides the quality preservation for drug stabilization. The release of the entrapped drug is controlled and prolonged for specific usages. Some recent studies have focused on the evaluation of drug containing microcapsules on potential biological and therapeutic applications. For the oral delivery, in vivo animal models were used for evaluating possible treatment effects of drug containing microcapsules. For the transdermal drug delivery, skin delivery models were introduced to investigate the potential skin delivery of medicated microcapsules. Finally, the challenges and limitations of drug microencapsulation in real life are discussed and the commercially available drug formulations using microencapsulation technology for oral and transdermal applications are shown. Copyright © 2014 Elsevier B.V. All rights reserved.
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State-Space Modelling in Marine Science
DEFF Research Database (Denmark)
Albertsen, Christoffer Moesgaard
State-space models provide a natural framework for analysing time series that cannot be observed without error. This is the case for fisheries stock assessments and movement data from marine animals. In fisheries stock assessments, the aim is to estimate the stock size; however, the only data...... available is the number of fish removed from the population and samples on a small fraction of the population. In marine animal movement, accurate position systems such as GPS cannot be used. Instead, inaccurate alternative must be used yielding observations with large errors. Both assessment and individual...... animal movement models are important for management and conservation of marine animals. Consequently, models should be developed to be operational in a management context while adequately evaluating uncertainties in the models. This thesis develops state-space models using the Laplace approximation...
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On rate-state and Coulomb failure models
Gomberg, J.; Beeler, N.; Blanpied, M.
2000-01-01
We examine the predictions of Coulomb failure stress and rate-state frictional models. We study the change in failure time (clock advance) Δt due to stress step perturbations (i.e., coseismic static stress increases) added to "background" stressing at a constant rate (i.e., tectonic loading) at time t0. The predictability of Δt implies a predictable change in seismicity rate r(t)/r0, testable using earthquake catalogs, where r0 is the constant rate resulting from tectonic stressing. Models of r(t)/r0, consistent with general properties of aftershock sequences, must predict an Omori law seismicity decay rate, a sequence duration that is less than a few percent of the mainshock cycle time and a return directly to the background rate. A Coulomb model requires that a fault remains locked during loading, that failure occur instantaneously, and that Δt is independent of t0. These characteristics imply an instantaneous infinite seismicity rate increase of zero duration. Numerical calculations of r(t)/r0 for different state evolution laws show that aftershocks occur on faults extremely close to failure at the mainshock origin time, that these faults must be "Coulomb-like," and that the slip evolution law can be precluded. Real aftershock population characteristics also may constrain rate-state constitutive parameters; a may be lower than laboratory values, the stiffness may be high, and/or normal stress may be lower than lithostatic. We also compare Coulomb and rate-state models theoretically. Rate-state model fault behavior becomes more Coulomb-like as constitutive parameter a decreases relative to parameter b. This is because the slip initially decelerates, representing an initial healing of fault contacts. The deceleration is more pronounced for smaller a, more closely simulating a locked fault. Even when the rate-state Δt has Coulomb characteristics, its magnitude may differ by some constant dependent on b. In this case, a rate-state model behaves like a modified
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International Nuclear Information System (INIS)
Mardinoglu, Adil; Cregg, P.J.; Murphy, Kieran; Curtin, Maurice; Prina-Mello, Adriele
2011-01-01
The magnetisable stent assisted magnetic targeted drug delivery system in a physiologically stretched vessel is considered theoretically. The changes in the mechanical behaviour of the vessel are analysed under the influence of mechanical forces generated by blood pressure. In this 2D mathematical model a ferromagnetic, coiled wire stent is implanted to aid collection of magnetic drug carrier particles in an elastic tube, which has similar mechanical properties to the blood vessel. A cyclic mechanical force is applied to the elastic tube to mimic the mechanical stress and strain of both the stent and vessel while in the body due to pulsatile blood circulation. The magnetic dipole-dipole and hydrodynamic interactions for multiple particles are included and agglomeration of particles is also modelled. The resulting collection efficiency of the mathematical model shows that the system performance can decrease by as much as 10% due to the effects of the pulsatile blood circulation. - Research highlights: →Theoretical modelling of magnetic drug targeting on a physiologically stretched stent-vessel system. →Cyclic mechanical force applied to mimic the mechanical stress and strain of both stent and vessel. →The magnetic dipole-dipole and hydrodynamic interactions for multiple particles is modelled. →Collection efficiency of the mathematical model is calculated for different physiological blood flow and magnetic field strength.
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Modelling of Functional States during Saccharomyces cerevisiae Fed-batch Cultivation
Directory of Open Access Journals (Sweden)
Stoyan Tzonkov
2005-04-01
Full Text Available An implementation of functional state approach for modelling of yeast fed-batch cultivation is presented in this paper. Using of functional state modelling approach aims to overcome the main disadvantage of using global process model, namely complex model structure and big number of model parameters, which complicate the model simulation and parameter estimation. This approach has computational advantages, such as the possibility to use the estimated values from the previous state as starting values for estimation of parameters of a new state. The functional state modelling approach is applied here for fedbatch cultivation of Saccharomyces cerevisiae. Four functional states are recognised and parameter estimation of local models is presented as well.
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Drug lag for cardiovascular drug approvals in India compared with the US and EU approvals
Directory of Open Access Journals (Sweden)
Bhaven C. Kataria
2013-01-01
Conclusion: This study confirms that there is a substantial drug lag in approval of new cardiovascular drugs in India compared with the United States and European Union. The impact of drug lag on health outcomes remains to be established.
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Mining adverse drug reactions from online healthcare forums using hidden Markov model.
Sampathkumar, Hariprasad; Chen, Xue-wen; Luo, Bo
2014-10-23
Adverse Drug Reactions are one of the leading causes of injury or death among patients undergoing medical treatments. Not all Adverse Drug Reactions are identified before a drug is made available in the market. Current post-marketing drug surveillance methods, which are based purely on voluntary spontaneous reports, are unable to provide the early indications necessary to prevent the occurrence of such injuries or fatalities. The objective of this research is to extract reports of adverse drug side-effects from messages in online healthcare forums and use them as early indicators to assist in post-marketing drug surveillance. We treat the task of extracting adverse side-effects of drugs from healthcare forum messages as a sequence labeling problem and present a Hidden Markov Model(HMM) based Text Mining system that can be used to classify a message as containing drug side-effect information and then extract the adverse side-effect mentions from it. A manually annotated dataset from http://www.medications.com is used in the training and validation of the HMM based Text Mining system. A 10-fold cross-validation on the manually annotated dataset yielded on average an F-Score of 0.76 from the HMM Classifier, in comparison to 0.575 from the Baseline classifier. Without the Plain Text Filter component as a part of the Text Processing module, the F-Score of the HMM Classifier was reduced to 0.378 on average, while absence of the HTML Filter component was found to have no impact. Reducing the Drug names dictionary size by half, on average reduced the F-Score of the HMM Classifier to 0.359, while a similar reduction to the side-effects dictionary yielded an F-Score of 0.651 on average. Adverse side-effects mined from http://www.medications.com and http://www.steadyhealth.com were found to match the Adverse Drug Reactions on the Drug Package Labels of several drugs. In addition, some novel adverse side-effects, which can be potential Adverse Drug Reactions, were also
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Drug overdose surveillance using hospital discharge data.
Slavova, Svetla; Bunn, Terry L; Talbert, Jeffery
2014-01-01
We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000-2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison.
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Drug Overdose Surveillance Using Hospital Discharge Data
Bunn, Terry L.; Talbert, Jeffery
2014-01-01
Objectives We compared three methods for identifying drug overdose cases in inpatient hospital discharge data on their ability to classify drug overdoses by intent and drug type(s) involved. Methods We compared three International Classification of Diseases, Ninth Revision, Clinical Modification code-based case definitions using Kentucky hospital discharge data for 2000–2011. The first definition (Definition 1) was based on the external-cause-of-injury (E-code) matrix. The other two definitions were based on the Injury Surveillance Workgroup on Poisoning (ISW7) consensus recommendations for national and state poisoning surveillance using the principal diagnosis or first E-code (Definition 2) or any diagnosis/E-code (Definition 3). Results Definition 3 identified almost 50% more drug overdose cases than did Definition 1. The increase was largely due to cases with a first-listed E-code describing a drug overdose but a principal diagnosis that was different from drug overdose (e.g., mental disorders, or respiratory or circulatory system failure). Regardless of the definition, more than 53% of the hospitalizations were self-inflicted drug overdoses; benzodiazepines were involved in about 30% of the hospitalizations. The 2011 age-adjusted drug overdose hospitalization rate in Kentucky was 146/100,000 population using Definition 3 and 107/100,000 population using Definition 1. Conclusion The ISW7 drug overdose definition using any drug poisoning diagnosis/E-code (Definition 3) is potentially the highest sensitivity definition for counting drug overdose hospitalizations, including by intent and drug type(s) involved. As the states enact policies and plan for adequate treatment resources, standardized drug overdose definitions are critical for accurate reporting, trend analysis, policy evaluation, and state-to-state comparison. PMID:25177055
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Tasman, H.; Supali, T.; Supriatna, A. K.; Nuraini, N.; Soewono, E.
2015-03-01
In this paper we discuss a mathematical model for the transmission of lymphatic filariasis disease. The human population is divided into susceptible, latent, acute and chronic subpopulations. Treatment is carried out within the scheme of mass drug administration (MDA) by giving the diethylcarbamazine (DEC) and albendazole (ALB) to all individuals. In the model, we assume that the treatments have direct killing effect to microfilariae, increase of immune-mediated effect. The treated individuals are assumed to remain susceptible to the disease. This is due to the fact that the treatment is only partially effective against macrofilaria. Simulations of the model reveals that DEC-ALB treatment does give significant reduction of acute and chronic compartments at the end of the treatment period and slow down the growth after the treatment before eventually tend to the endemic state. It showed that repeated treatment during MDA is effective to decrease the transmission. This suggests that terminating MDA program after a long period of its application may still effective in controlling the disease.
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Guo, Wenbin; Xiao, Changqing; Liu, Guiying; Wooderson, Sarah C; Zhang, Zhikun; Zhang, Jian; Yu, Liuyu; Liu, Jianrong
2014-01-03
Dysconnectivity hypothesis posits that schizophrenia relates to abnormalities in neuronal connectivity. However, little is known about the alterations of the interhemispheric resting-state functional connectivity (FC) in patients with paranoid schizophrenia. In the present study, we used a newly developed voxel-mirrored homotopic connectivity (VMHC) method to investigate the interhemispheric FC of the whole brain in patients with paranoid schizophrenia at rest. Forty-nine first-episode, drug-naive patients with paranoid schizophrenia and 50 age-, gender-, and education-matched healthy subjects underwent a resting-state functional magnetic resonance imaging (fMRI) scans. An automated VMHC approach was used to analyze the data. Patients exhibited lower VMHC than healthy subjects in the precuneus (PCu), the precentral gyrus, the superior temporal gyrus (STG), the middle occipital gyrus (MOG), and the fusiform gyrus/cerebellum lobule VI. No region showed greater VMHC in the patient group than in the control group. Significantly negative correlation was observed between VMHC in the precentral gyrus and the PANSS positive/total scores, and between VMHC in the STG and the PANSS positive/negative/total scores. Our results suggest that interhemispheric resting-state FC of VMHC is reduced in paranoid schizophrenia with clinical implications for psychiatric symptomatology thus further contribute to the dysconnectivity hypothesis of schizophrenia. © 2013.
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Caenorhabditis elegans as a Model System for Studying Drug Induced Mitochondrial Toxicity.
Directory of Open Access Journals (Sweden)
Richard de Boer
Full Text Available Today HIV-1 infection is recognized as a chronic disease with obligatory lifelong treatment to keep viral titers below detectable levels. The continuous intake of antiretroviral drugs however, leads to severe and even life-threatening side effects, supposedly by the deleterious impact of nucleoside-analogue type compounds on the functioning of the mitochondrial DNA polymerase. For detailed investigation of the yet partially understood underlying mechanisms, the availability of a versatile model system is crucial. We therefore set out to develop the use of Caenorhabditis elegans to study drug induced mitochondrial toxicity. Using a combination of molecular-biological and functional assays, combined with a quantitative analysis of mitochondrial network morphology, we conclude that anti-retroviral drugs with similar working mechanisms can be classified into distinct groups based on their effects on mitochondrial morphology and biochemistry. Additionally we show that mitochondrial toxicity of antiretroviral drugs cannot be exclusively attributed to interference with the mitochondrial DNA polymerase.
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Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict
Ismail, Mohd Tahir; Alias, Siti Nor Shadila
2014-07-01
For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..
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Gou, Yi; Zhang, Zhenlei; Li, Dongyang; Zhao, Lei; Cai, Meiling; Sun, Zhewen; Li, Yongping; Zhang, Yao; Khan, Hamid; Sun, Hongbing; Wang, Tao; Liang, Hong; Yang, Feng
2018-11-01
Multi-drug delivery systems, which may be promising solution to overcome obstacles, have limited the clinical success of multi-drug combination therapies to treat cancer. To this end, we used three different anticancer agents, Cu(BpT)Br, NAMI-A, and doxorubicin (DOX), to build human serum albumin (HSA)-based multi-drug delivery systems in a breast cancer model to investigate the therapeutic efficacy of overcoming single drug (DOX) resistance to cancer cells in vivo, and to regulate the drugs' release from HSA. The HSA complex structure revealed that NAMI-A and Cu(BpT)Br bind to the IB and IIA sub-domain of HSA by N-donor residue replacing a leaving group and coordinating to their metal centers, respectively. The MALDI-TOF mass spectra demonstrated that one DOX molecule is conjugated with lysine of HSA by a pH-sensitive linker. Furthermore, the release behavior of three agents form HSA can be regulated at different pH levels. Importantly, in vivo results revealed that the HSA-NAMI-A-Cu(BpT)Br-DOX complex not only increases the targeting ability compared with a combination of the three agents (the NAMI-A/Cu(BpT)Br/DOX mixture), but it also overcomes DOX resistance to drug-resistant breast cancer cell lines.
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DEFF Research Database (Denmark)
Mosgaard, Mette D; Sassene, Philip; Mu, Huiling
2015-01-01
: The HTP model is able to predict drug distribution during digestion of LbDDS containing poorly water soluble drugs in the same manner as the DIVL model. Thus the HTP model might prove applicable for high-throughput evaluation of LbDDS in e.g. 96 well plates or small scale dissolution equipment....... (DIVL) model with regard to the extent of lipid digestion and drug distribution of two poorly soluble model drugs (cinnarizine and danazol), during digestion of three LbDDS (LbDDS I-III). RESULT: The HTP model was able to maintain pH around 6.5 during digestion, without the addition of Na...
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Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok
2015-01-01
No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure–response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure–response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects’ sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure–response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs. PMID:26392753
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Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok
2015-01-01
No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure-response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure-response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects' sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure-response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs.
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Full Text Available ... Drugs and HIV Email Facebook Twitter 2005 –Ongoing Behaviors associated with drug misuse are among the main factors in the spread of HIV infection in the United States. Drugs can change the way the brain works, disrupting the parts ...
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Fultz, Elissa K; Martin, Douglas L; Hudson, Courtney N; Kippin, Tod E; Szumlinski, Karen K
2017-08-01
A high degree of co-morbidity exists between methamphetamine (MA) addiction and alcohol use disorders and both sequential and simultaneous MA-alcohol mixing increases risk for co-abuse. As little preclinical work has focused on the biobehavioral interactions between MA and alcohol within the context of drug-taking behavior, we employed simple murine models of voluntary oral drug consumption to examine how prior histories of either MA- or alcohol-taking influence the intake of the other drug. In one study, mice with a 10-day history of binge alcohol-drinking [5,10, 20 and 40% (v/v); 2h/day] were trained to self-administer oral MA in an operant-conditioning paradigm (10-40mg/L). In a second study, mice with a 10-day history of limited-access oral MA-drinking (5, 10, 20 and 40mg/L; 2h/day) were presented with alcohol (5-40% v/v; 2h/day) and then a choice between solutions of 20% alcohol, 10mg/L MA or their mix. Under operant-conditioning procedures, alcohol-drinking mice exhibited less MA reinforcement overall, than water controls. However, when drug availability was not behaviorally-contingent, alcohol-drinking mice consumed more MA and exhibited greater preference for the 10mg/L MA solution than drug-naïve and combination drug-experienced mice. Conversely, prior MA-drinking history increased alcohol intake across a range of alcohol concentrations. These exploratory studies indicate the feasibility of employing procedurally simple murine models of sequential and simultaneous oral MA-alcohol mixing of relevance to advancing our biobehavioral understanding of MA-alcohol co-abuse. Copyright © 2017 Elsevier B.V. All rights reserved.
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Verkhivker, Gennady M
2016-01-01
The human protein kinome presents one of the largest protein families that orchestrate functional processes in complex cellular networks, and when perturbed, can cause various cancers. The abundance and diversity of genetic, structural, and biochemical data underlies the complexity of mechanisms by which targeted and personalized drugs can combat mutational profiles in protein kinases. Coupled with the evolution of system biology approaches, genomic and proteomic technologies are rapidly identifying and charactering novel resistance mechanisms with the goal to inform rationale design of personalized kinase drugs. Integration of experimental and computational approaches can help to bring these data into a unified conceptual framework and develop robust models for predicting the clinical drug resistance. In the current study, we employ a battery of synergistic computational approaches that integrate genetic, evolutionary, biochemical, and structural data to characterize the effect of cancer mutations in protein kinases. We provide a detailed structural classification and analysis of genetic signatures associated with oncogenic mutations. By integrating genetic and structural data, we employ network modeling to dissect mechanisms of kinase drug sensitivities to oncogenic EGFR mutations. Using biophysical simulations and analysis of protein structure networks, we show that conformational-specific drug binding of Lapatinib may elicit resistant mutations in the EGFR kinase that are linked with the ligand-mediated changes in the residue interaction networks and global network properties of key residues that are responsible for structural stability of specific functional states. A strong network dependency on high centrality residues in the conformation-specific Lapatinib-EGFR complex may explain vulnerability of drug binding to a broad spectrum of mutations and the emergence of drug resistance. Our study offers a systems-based perspective on drug design by unravelling
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An ETP model (exclusion-tolerance-progression for multi drug resistance
Directory of Open Access Journals (Sweden)
Kannan Subburaj
2005-04-01
Full Text Available Abstract Background It is known that sensitivity or resistance of tumor cells to a given chemotherapeutic agent is an acquired characteristic(s, depending on the heterogeneity of the tumor mass subjected to the treatment. The clinical success of a chemotherapeutic regimen depends on the ratio of sensitive to resistant cell populations. Results Based on findings from clinical and experimental studies, a unifying model is proposed to delineate the potential mechanism by which tumor cells progress towards multi drug resistance, resulting in failure of chemotherapy. Conclusion It is suggested that the evolution of multi drug resistance is a developmentally orchestrated event. Identifying stage-specific time windows during this process would help to identify valid therapeutic targets for the effective elimination of malignancy.
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Huh, Jisu; Delorme, Denise E; Reid, Leonard N
2016-01-01
Given the importance of over-the-counter (OTC) drugs in the health care marketplace and lack of systematic research on OTC drug advertising (OTCA) effects, this study tested a theory-based, product category-specific OTCA effects model. Structural equation modeling analysis of data for 1 OTC drug category, analgesics, supported the proposed model, explaining the OTCA effect process from key consumer antecedents to ad involvement, from ad involvement to ad attention, from ad attention to cognitive responses, then to affective/evaluative responses, leading to the final behavioral outcome. Several noteworthy patterns also emerged: (a) Product involvement was directly linked to ad attention, rather than exerting an indirect influence through ad involvement; (b) ad attention was significantly related to both cognitive and affective/evaluative responses to different degrees, with stronger links to cognitive responses; and (c) ad-prompted actions were influenced by both ad trust and ad attitude.
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Availability and usage of new antibacterial drugs in Europe.
Ziv, G
1980-05-15
The present-day availability and usage of established and new antibacterial drugs approved for clinical and therapeutic purposes in food-producing animals and poultry in the United States and Europe were compared. Presently, 42 such drugs are approved in Europe, 13 of which were approved since Dec 31, 1974. In the United States, 17 such drugs are currently approved, only four were approved since Dec 31, 1974. Most drug products approved in Europe contain two or more antibacterial agents, whereas most of the products approved in the United States are single drug entities. Drugs approved in Europe but not in the United States include sulfonamide and trimethoprim combinations, nafcillin, oxacillin, metampicillin, cephoxazole, cephalonium, cephacetrile, cephalexin, gentamicin, rifamycin SV, nifuroquine, tiamulin, chloramphenicol, colistin, and polymyxin B. Pharmacologic and clinical features of several of these drugs are briefly described.
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Assessment of anti-arrhythmic activity of antipsychotic drugs in an animal model
DEFF Research Database (Denmark)
Mow, Tomas; Frederiksen, Kristen; Thomsen, Morten B.
2015-01-01
limited experimental information exists about the effects of α1-adrenergic receptor activity of antipsychotic drugs in pro-arrhythmic models, we have decided to investigate this. In this study we show that four antipsychotic drugs all have high affinity for α1-adrenergic receptor (sertindole>risperidone>haloperidol......>olanzapine) and all block IKr (sertindole>haloperidol>risperidone>olanzapine). In canine Purkinje fibres, α1-adrenergic stimulation prolonged action potential duration; however, the stimulation does not cause afterdepolarizations, even in the presence of dofetilide-induced delayed repolarization. We showed...
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Verma, Sanjay; Rudraraju, Varma S
2015-02-01
The objective of this study was to develop a solid dispersion based controlled release system for drug substances that are poorly soluble in water. A wax-based disintegration mediated controlled release system was designed based on the fact that an amorphous drug can crystallize out from hydrophilic matrices. For this study, cilostazol (CIL) was selected as the model drug, as it exhibits poor aqueous solubility. An amorphous solid dispersion was prepared to assist the drug to attain a supersaturated state. Povidone was used as carrier for solid dispersion (spray drying technique), hydrogenated vegetable oil (HVO) as wax matrix former, and sodium carboxymethyl cellulose (NaCMC) as a disintegrant. The extreme vertices mixture design (EVMD) was applied to optimize the designed and developed composition. The optimized formulation provided a dissolution pattern which was equivalent to the predicted curve, ascertaining that the optimal formulation could be accomplished with EVMD. The release profile of CIL was described by the Higuchi's model better than zero-order, first-order, and Hixson-Crowell's model, which indicated that the supersaturation state of CIL dominated to allow drug release by diffusion rather than disintegration regulated release as is generally observed by Hixson-Crowell's model. The optimized composition was evaluated for disintegration, dissolution, XRD, and stability studies. It was found that the amorphous state as well as the dissolution profile of CIL was maintained under the accelerated conditions of 40°C/75% RH for 6 months.
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War on Drugs Policing and Police Brutality.
Cooper, Hannah L F
2015-01-01
War on Drugs policing has failed to reduce domestic street-level drug activity: the cost of drugs remains low and drugs remain widely available. In light of growing attention to police brutality in the United States, this paper explores interconnections between specific War on Drugs policing strategies and police-related violence against Black adolescents and adults in the United States. This paper reviews literature about (1) historical connections between race/ethnicity and policing in the United States; (2) the ways that the War on Drugs eroded specific legal protections originally designed to curtail police powers; and (3) the implications of these erosions for police brutality targeting Black communities. Policing and racism have been mutually constitutive in the United States. Erosions to the 4th Amendment to the Constitution and to the Posse Comitatus Act set the foundations for two War on Drugs policing strategies: stop and frisk and Special Weapons and Tactics (SWAT) teams. These strategies have created specific conditions conducive to police brutality targeting Black communities. Conclusions/Importance: War on Drugs policing strategies appear to increase police brutality targeting Black communities, even as they make little progress in reducing street-level drug activity. Several jurisdictions are retreating from the War on Drugs; this retreat should include restoring rights originally protected by the 4th Amendment and Posse Comitatus. While these legal changes occur, police chiefs should discontinue the use of SWAT teams to deal with low-level nonviolent drug offenses and should direct officers to cease engaging in stop and frisk.
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The finite state projection approach to analyze dynamics of heterogeneous populations
Johnson, Rob; Munsky, Brian
2017-06-01
Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.
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HIV Prevention and Rehabilitation Models for Women Who Inject Drugs in Russia and Ukraine
Directory of Open Access Journals (Sweden)
Roman Yorick
2012-01-01
Full Text Available Women who inject drugs require gender-specific approaches to drug rehabilitation, modification of risk behaviors, and psychosocial adaptation. Improved outcomes have been demonstrated when the specific needs of women’s subpopulations have been addressed. Special services for women include prenatal care, child care, women-only programs, supplemental workshops on women-focused topics, mental health services, and comprehensive programs that include several of the above components. To address the special needs of women injecting drug user (IDU subpopulations, such as HIV-positive pregnant women and women with young children, recently released female prisoners, and street-involved girls and young women, HealthRight International and its local partners in Russia and Ukraine have developed innovative service models. This paper presents each of these models and discusses their effectiveness and implementation challenges specific to local contexts in Russia and Ukraine.
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DeLuna, Frank; Zhang, Yu Shrike; Bustamante, Gilbert; Li, Le; Lauderdale, Matthew; Dokmeci, Mehmet R.; Khademhosseini, Ali; Ye, Jing Yong
2018-02-01
Efficient methods for the accurate analysis of drug toxicities are in urgent demand as failures of newly discovered drug candidates due to toxic side effects have resulted in about 30% of clinical attrition. The high failure rate is partly due to current inadequate models to study drug side effects, i.e., common animal models may fail due to its misrepresentation of human physiology. Therefore, much effort has been allocated in the development of organ-on-a-chip models which offer a variety of human organ models mimicking a multitude of human physiological conditions. However, it is extremely challenging to analyze the transient and long-term response of the organ models to drug treatments during drug toxicity tests, as the proteins secreted from the organ-on-a-chip model are minute due to its volumetric size, and current methods for detecting said biomolecules are not suitable for real-time monitoring. As protein biomolecules are being continuously secreted from the human organ model, fluorescence techniques are practically impossible to achieve real-time fluorescence labeling in the dynamically changing environment, thus making a label-free approach highly desirable for the organ-on-achip applications. In this paper, we report the use of a photonic-crystal biosensor integrated with a microfluidic system for sensitive label-free bioassays of secreted protein biomolecules from a heart-on-the-chip model created with cardiomyocytes derived from human induced pluripotent stem cells.
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Ager, Alastair K; Lembani, Martina; Mohammed, Abdulaziz; Mohammed Ashir, Garba; Abdulwahab, Ahmad; de Pinho, Helen; Delobelle, Peter; Zarowsky, Christina
2015-01-01
Yobe State has faced severe disruption of its health service as a result of the Boko Haram insurgency. A systems dynamics analysis was conducted to identify key pathways of threat to provision and emerging pathways of response and adaptation. Structured interviews were conducted with 39 stakeholders from three local government areas selected to represent the diversity of conflict experience across the state: Damaturu, Fune and Nguru, and with four officers of the PRRINN-MNCH program providing technical assistance for primary care development in the state. A group model building session was convened with 11 senior stakeholders, which used participatory scripts to review thematic analysis of interviews and develop a preliminary systems model linking identified variables. Population migration and transport restrictions have substantially impacted access to health provision. The human resource for health capability of the state has been severely diminished through the outward migration of (especially non-indigenous) health workers and the suspension of programmes providing external technical assistance. The political will of the Yobe State government to strengthen health provision - through lifting a moratorium on recruitment and providing incentives for retention and support of staff - has supported a recovery of health systems functioning. Policies of free-drug provision and decentralized drug supply appear to have been protective of the operation of the health system. Community resources and cohesion have been significant assets in combatting the impacts of the insurgency on service utilization and quality. Staff commitment and motivation - particularly amongst staff indigenous to the state - has protected health care quality and enabled flexibility of human resource deployment. A systems analysis using participatory group model building provided a mechanism to identify key pathways of threat and adaptation with regard to health service functioning. Generalizable
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The impact of pharmacophore modeling in drug design.
Guner, Osman F
2005-07-01
With the reliable use of computer simulations in scientific research, it is possible to achieve significant increases in productivity as well as a reduction in research costs compared with experimental approaches. For example, computer-simulation can substantially enchance productivity by focusing the scientist to better, more informed choices, while also driving the 'fail-early' concept to result in a significant reduction in cost. Pharmacophore modeling is a reliable computer-aided design tool used in the discovery of new classes of compounds for a given therapeutic category. This commentary will briefly review the benefits and applications of this technology in drug discovery and design, and will also highlight its historical evolution. The two most commonly used approaches for pharmacophore model development will be discussed, and several examples of how this technology was successfully applied to identify new potent leads will be provided. The article concludes with a brief outline of the controversial issue of patentability of pharmacophore models.
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A Methodological Review of US Budget-Impact Models for New Drugs.
Mauskopf, Josephine; Earnshaw, Stephanie
2016-11-01
A budget-impact analysis is required by many jurisdictions when adding a new drug to the formulary. However, previous reviews have indicated that adherence to methodological guidelines is variable. In this methodological review, we assess the extent to which US budget-impact analyses for new drugs use recommended practices. We describe recommended practice for seven key elements in the design of a budget-impact analysis. Targeted literature searches for US studies reporting estimates of the budget impact of a new drug were performed and we prepared a summary of how each study addressed the seven key elements. The primary finding from this review is that recommended practice is not followed in many budget-impact analyses. For example, we found that growth in the treated population size and/or changes in disease-related costs expected during the model time horizon for more effective treatments was not included in several analyses for chronic conditions. In addition, all drug-related costs were not captured in the majority of the models. Finally, for most studies, one-way sensitivity and scenario analyses were very limited, and the ranges used in one-way sensitivity analyses were frequently arbitrary percentages rather than being data driven. The conclusions from our review are that changes in population size, disease severity mix, and/or disease-related costs should be properly accounted for to avoid over- or underestimating the budget impact. Since each budget holder might have different perspectives and different values for many of the input parameters, it is also critical for published budget-impact analyses to include extensive sensitivity and scenario analyses based on realistic input values.
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Yang, Kun; Weng, Liang; Cheng, Yiyun; Zhang, Hongfeng; Zhang, Jiahai; Wu, Qinglin; Xu, Tongwen
2011-03-17
Fully acetylated poly(amidoamine) (PAMAM) dendrimer was proposed as a biocompatible drug vehicle using dexamethasone 21-phosphate (Dp21) as a model drug. NMR techniques including (1)H NMR and 2D NOE NMR were used to characterize the host-guest chemistry of acetylated dendrimer/Dp21 and cationic dendrimer/Dp21 complexes. The pH-dependent micellization, complexation, and inclusion behaviors of Dp21 were observed in the presence of acetylated and cationic PAMAM dendrimers. Acetylated dendrimer only encapsulates Dp21 at acidic conditions, while cationic dendrimer can host Dp21 at both acidic and neutral conditions. The orientation of Dp21 molecules in the dendrimer cavities depends on the quaternization degree of tertiary amine groups of dendrimer and the protonation ratio of phosphate group of Dp21. A distinctive pH-dependent release behavior of Dp21 from the acetylated and nonacetylated dendritic matrix was observed: Dp21 exhibits a much slower release rate from acetylated dendrimer at lower pH conditions and a much faster release rate from nonacetylated dendrimer with decreasing pH values. Cytotoxicity studies further confirmed the biocompatibility of acetylated dendrimers, which are much safer in the delivery of therapeutics for the treatment of various diseases than nonacetylated dendrimers. The dendrimer-drug binding and release mechanisms provide a new insight for the design and optimization of biocompatible dendrimer-based drug delivery systems. © 2011 American Chemical Society
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Hydrogel-based 3D model of patient-derived prostate xenograft tumors suitable for drug screening.
Fong, Eliza L S; Martinez, Mariane; Yang, Jun; Mikos, Antonios G; Navone, Nora M; Harrington, Daniel A; Farach-Carson, Mary C
2014-07-07
The lack of effective therapies for bone metastatic prostate cancer (PCa) underscores the need for accurate models of the disease to enable the discovery of new therapeutic targets and to test drug sensitivities of individual tumors. To this end, the patient-derived xenograft (PDX) PCa model using immunocompromised mice was established to model the disease with greater fidelity than is possible with currently employed cell lines grown on tissue culture plastic. However, poorly adherent PDX tumor cells exhibit low viability in standard culture, making it difficult to manipulate these cells for subsequent controlled mechanistic studies. To overcome this challenge, we encapsulated PDX tumor cells within a three-dimensional hyaluronan-based hydrogel and demonstrated that the hydrogel maintains PDX cell viability with continued native androgen receptor expression. Furthermore, a differential sensitivity to docetaxel, a chemotherapeutic drug, was observed as compared to a traditional PCa cell line. These findings underscore the potential impact of this novel 3D PDX PCa model as a diagnostic platform for rapid drug evaluation and ultimately push personalized medicine toward clinical reality.
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Kiyatkin, Eugene A; Ren, Suelynn E
2017-01-01
Psychomotor stimulants are frequently used by humans to intensify the subjective experience of different types of social interactions. Since psychomotor stimulants enhance metabolism and increase body temperatures, their use under conditions of physiological activation and in warm humid environments could result in pathological hyperthermia, a life-threatening symptom of acute drug intoxication. Here, we will describe the brain hyperthermic effects of MDMA, MDPV, and methylone, three structurally related recreational drugs commonly used by young adults during raves and other forms of social gatherings. After a short introduction on brain temperature and basic mechanisms underlying its physiological fluctuations, we will consider how MDMA, MDPV, and methylone affect brain and body temperatures in awake freely moving rats. Here, we will discuss the role of drug-induced heat production in the brain due to metabolic brain activation and diminished heat dissipation due to peripheral vasoconstriction as two primary contributors to the hyperthermic effects of these drugs. Then, we will consider how the hyperthermic effects of these drugs are modulated under conditions that model human drug use (social interaction and warm ambient temperature). Since social interaction results in brain and body heat production, coupled with skin vasoconstriction that impairs heat loss to the external environment, these physiological changes interact with drug-induced changes in heat production and loss, resulting in distinct changes in the hyperthermic effects of each tested drug. Finally, we present our recent data, in which we compared the efficacy of different pharmacological strategies for reversing MDMA-induced hyperthermia in both the brain and body. Specifically, we demonstrate increased efficacy of the centrally acting atypical neuroleptic compound clozapine over the peripherally acting vasodilator drug, carvedilol. These data could be important for understanding the potential
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Transfer kinetics from colloidal drug carriers and liposomes to biomembrane models: DSC studies
Directory of Open Access Journals (Sweden)
Maria Grazia Sarpietro
2011-01-01
Full Text Available The release of bioactive molecules by different delivery systems has been studied. We have proposed a protocol that takes into account a system that is able to carry out the uptake of a bioactive molecule released during the time, resembling an in vivo-like system, and for this reason we have used biomembrane models represented by multi-lamellar and unilamellar vesicles. The bioactive molecule loaded delivery system has been put in contact with the biomembrane model and the release has been evaluated, to consider the effect of the bioactive molecule on the biomembrane model thermotropic behavior, and to compare the results with those obtained when a pure drug interacts with the biomembrane model. The differential scanning calorimetry technique has been employed. Depending on the delivery system used, our research permits to evaluate the effect of different parameters on the bioactive molecule release, such as pH, drug loading degree, delivery system swelling, crosslinking agent, degree of cross-linking, and delivery system side chains.
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Nagar, Vittal R; Springer, Joe E; Salles, Sara
2015-10-01
To investigate the incidence of spinal abscess and substance abuse in a tertiary care hospital after state legislation titled "House Bill 1" (HB1) mandated stricter regulation of prescription drugs of abuse in Kentucky in 2012. A retrospective case series study design was used to review the incidence of spinal abscess and drug abuse diagnoses admissions from 2010 to 2014. Variances in the incidence of spinal abscess and substance abuse were plotted across this time frame. The incidence of intraspinal abscess increased 1.56-fold in 2011 (n = 26) and 2012 (n = 25) relative to 2010 (n = 16). However, in 2013, the year following implementation of HB1 legislation, the incidence of intraspinal abscess increased 2.38-fold (n = 38) and then 4.19-fold (n = 67) in 2014. The incidence of intraspinal abscess in subjects with drug abuse diagnosis remained constant between 2010 (n = 3) and 2012 (n = 3). However, it increased twofold (n = 7) in 2013 and then ninefold (n = 27) in 2014. A correlation coefficient (rSAD ) of 0.775 revealed a strong association between the increase incidence of intraspinal abscess and diagnosis of drug abuse. The results of this retrospective study demonstrate an increased incidence of intraspinal abscess associated with drug abuse after passage of HB1 legislation regulating prescriptions of controlled medications in Kentucky. This increased incidence may be related to individuals relying on nonprescription drugs of abuse due to more highly regulated access to controlled prescription medications. However, additional factors unrelated to HB1 legislation must be taken into account. Wiley Periodicals, Inc.
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Microfluidic Devices for Drug Delivery Systems and Drug Screening
Kompella, Uday B.; Damiati, Safa A.
2018-01-01
Microfluidic devices present unique advantages for the development of efficient drug carrier particles, cell-free protein synthesis systems, and rapid techniques for direct drug screening. Compared to bulk methods, by efficiently controlling the geometries of the fabricated chip and the flow rates of multiphase fluids, microfluidic technology enables the generation of highly stable, uniform, monodispersed particles with higher encapsulation efficiency. Since the existing preclinical models are inefficient drug screens for predicting clinical outcomes, microfluidic platforms might offer a more rapid and cost-effective alternative. Compared to 2D cell culture systems and in vivo animal models, microfluidic 3D platforms mimic the in vivo cell systems in a simple, inexpensive manner, which allows high throughput and multiplexed drug screening at the cell, organ, and whole-body levels. In this review, the generation of appropriate drug or gene carriers including different particle types using different configurations of microfluidic devices is highlighted. Additionally, this paper discusses the emergence of fabricated microfluidic cell-free protein synthesis systems for potential use at point of care as well as cell-, organ-, and human-on-a-chip models as smart, sensitive, and reproducible platforms, allowing the investigation of the effects of drugs under conditions imitating the biological system. PMID:29462948
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International Nuclear Information System (INIS)
Rondeau, D.B.; Jolicoeur, F.B.; Merkel, A.D.; Wayner, M.J.
1981-01-01
The literature on the effects of drugs on the acquisition and the magnitude of taste aversion is reviewed and discussed. Then, the results of a series of experiments on the effects of phenobarbital and related drugs on taste aversion are reported. A standard taste aversion model was used in all experiments; test drugs were injected prior to drinking in a one bottle situation on the first test day following the taste aversion treatment. Phenobarbital in doses ranging from 20 to 80 mg/kg significantly attenuated taste aversion induced by lithium chloride (LiCl) and x-radiation, the maximal effect occurred with the 60 mg/kg dose. The attenuating effect was found to be dependent upon the magnitude of the aversion to the sapid solution. Phenobarbital completely abolished aversion produced by 0.375 mEq LiCl while the attenuation effect decreased linearly with higher doses of LiCl. Results also indicate that phenobarbital's attenuating effect cannot be solely attributed to its dipsogenic characteristic or to its state dependent learning effect. Attenuation of LiCl aversion to a saccharin solution was also observed following single doses of amobarbital, 30 mg/kg, pentobarbital, 15 mg/kg, and chloropromazine, 0.75 mg/kg. Taste aversion was not affected by other doses of those drugs or by hexobarbital, barbital, and chlordiazepoxide. Phenobarbital's attenuating effect on taste aversion is discussed in relation to other known behavioral and neurophysiological effects of the drug
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Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars
2018-01-01
Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.