WorldWideScience

Sample records for model state drug

  1. State Drug Utilization Data 2013

    Data.gov (United States)

    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...

  2. State Drug Utilization Data 1996

    Data.gov (United States)

    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...

  3. State Drug Utilization Data 1993

    Data.gov (United States)

    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...

  4. State Drug Utilization Data 1995

    Data.gov (United States)

    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...

  5. State Drug Utilization Data 1997

    Data.gov (United States)

    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...

  6. State Drug Utilization Data 2015

    Data.gov (United States)

    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...

  7. State Drug Utilization Data 1998

    Data.gov (United States)

    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...

  8. State Drug Utilization Data 1991

    Data.gov (United States)

    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...

  9. State Drug Utilization Data 1992

    Data.gov (United States)

    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...

  10. State Drug Utilization Data 1994

    Data.gov (United States)

    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...

  11. State Drug Utilization Data 2001

    Data.gov (United States)

    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...

  12. State Drug Utilization Data 2005

    Data.gov (United States)

    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...

  13. State Drug Utilization Data 2011

    Data.gov (United States)

    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...

  14. State Drug Utilization Data 2006

    Data.gov (United States)

    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...

  15. State Drug Utilization Data 2014

    Data.gov (United States)

    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...

  16. State Drug Utilization Data 2012

    Data.gov (United States)

    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...

  17. State Drug Utilization Data 2009

    Data.gov (United States)

    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...

  18. State Drug Utilization Data 2004

    Data.gov (United States)

    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...

  19. State Drug Utilization Data 2008

    Data.gov (United States)

    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...

  20. State Drug Utilization Data 2002

    Data.gov (United States)

    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...

  1. State Drug Utilization Data 2017

    Data.gov (United States)

    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...

  2. State Drug Utilization Data 2016

    Data.gov (United States)

    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...

  3. State Drug Utilization Data 2000

    Data.gov (United States)

    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...

  4. State Drug Utilization Data 2007

    Data.gov (United States)

    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...

  5. A state-of-the-art multi-criteria model for drug benefit-risk analysis

    NARCIS (Netherlands)

    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

  6. Drug Poisoning Mortality by State: United States

    Data.gov (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...

  7. In vitro blood-brain barrier models for drug research: state-of-the-art and new perspectives on reconstituting these models on artificial basement membrane platforms.

    Science.gov (United States)

    Banerjee, Jayati; Shi, Yejiao; Azevedo, Helena S

    2016-09-01

    In vitro blood-brain barrier (BBB) models are indispensable screening tools for obtaining early information about the brain-penetrating behaviour of promising drug candidates. Until now, in vitro BBB models have focused on investigating the interplay among cellular components of neurovascular units and the effect of fluidic sheer stress in sustaining normal BBB phenotype and functions. However, an area that has received less recognition is the role of the noncellular basement membrane (BM) in modulating BBB physiology. This review describes the state-of-the-art on in vitro BBB models relevant in drug discovery research and highlights their strengths, weaknesses and the utility potential of some of these models in testing the permeability of nanocarriers as vectors for delivering therapeutics to the brain. Importantly, our review also introduces a new concept of engineering artificial BM platforms for reconstituting BBB models in vitro. Copyright © 2016 Elsevier Ltd. All rights reserved.

  8. Mathematical modeling of drug dissolution.

    Science.gov (United States)

    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.

  9. 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

  10. Mathematical modeling of drug delivery.

    Science.gov (United States)

    Siepmann, J; Siepmann, F

    2008-12-08

    Due to the significant advances in information technology mathematical modeling of drug delivery is a field of steadily increasing academic and industrial importance with an enormous future potential. The in silico optimization of novel drug delivery systems can be expected to significantly increase in accuracy and easiness of application. Analogous to other scientific disciplines, computer simulations are likely to become an integral part of future research and development in pharmaceutical technology. Mathematical programs can be expected to be routinely used to help optimizing the design of novel dosage forms. Good estimates for the required composition, geometry, dimensions and preparation procedure of various types of delivery systems will be available, taking into account the desired administration route, drug dose and release profile. Thus, the number of required experimental studies during product development can be significantly reduced, saving time and reducing costs. In addition, the quantitative analysis of the physical, chemical and potentially biological phenomena, which are involved in the control of drug release, offers another fundamental advantage: The underlying drug release mechanisms can be elucidated, which is not only of academic interest, but a pre-requisite for an efficient improvement of the safety of the pharmaco-treatments and for effective trouble-shooting during production. This article gives an overview on the current state of the art of mathematical modeling of drug delivery, including empirical/semi-empirical and mechanistic realistic models. Analytical as well as numerical solutions are described and various practical examples are given. One of the major challenges to be addressed in the future is the combination of mechanistic theories describing drug release out of the delivery systems with mathematical models quantifying the subsequent drug transport within the human body in a realistic way. Ideally, the effects of the design

  11. Drug Poisoning Mortality by County: United States

    Data.gov (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...

  12. NCHS - Drug Poisoning Mortality by State: United States

    Data.gov (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...

  13. Drug reimportation practices in the United States

    OpenAIRE

    Bhosle, Monali J; Balkrishnan, Rajesh

    2007-01-01

    Background Drug reimportation is perceived as a costs-cutting strategy by Americans. Nonetheless, issues such as drug safety and efficacy prevent legalization of the practice. With the contradictory views from supporters and opponents, debate on drug reimportation continues to snowball. The objective of this commentary is to discuss issues regarding drug reimportation practices in the United States (US). It also examines policy implications and potential solutions of the controversy. Findings...

  14. Biorelevant media for transport experiments in the Caco-2 model to evaluate drug absorption in the fasted and the fed state and their usefulness.

    Science.gov (United States)

    Markopoulos, C; Thoenen, F; Preisig, D; Symillides, M; Vertzoni, M; Parrott, N; Reppas, C; Imanidis, G

    2014-04-01

    In this work we developed and characterized transport media that simulate the composition of micellar phase of intestinal fluids in the fasted and, especially, in the fed state and are appropriate for evaluating intestinal drug permeability characteristics using the Caco-2 model (FaSSIF-TM(Caco) and FeSSIF-TM(Caco), respectively). Media composition was based on FaSSIF-V2 and FeSSIF-V2 and recently reported data on total lipid concentrations in the micellar phase of contents of the upper small intestine in the fasted and the fed state and was adapted for cell culture compatibility. Permeation data were evaluated by compartmental kinetic modeling. Permeability coefficients, P, of hydrophilic drugs were not affected by media composition. In contrast, P values of a series of lipophilic compounds measured with FaSSIF-TM(Caco) and FeSSIF-TM(Caco), and reflecting transport by diffusion were smaller than those obtained with a purely aqueous reference transport medium, aq-TM(Caco), following the rank order aq-TM(Caco)>FaSSIF-TM(Caco)>FeSSIF-TM(Caco). The decline of permeability values was stronger as lipophilicity of the compounds increased. Compared with values estimated using aq-TM(Caco), permeability was reduced, depending on the compound, by more than 20- to 100-fold when measured with FeSSIF-TM(Caco) whereas compound ranking in regard to the permeability characteristics was also affected. The impact of reduced P value on flux through the mucosa, hence on drug absorption, in combination with the drug amount loaded on colloidal particles needs to be taken into consideration in PBPK modeling especially when the food effect is evaluated. Copyright © 2013 Elsevier B.V. All rights reserved.

  15. Animal models of drug addiction.

    Science.gov (United States)

    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.

  16. Drug reimportation practices in the United States.

    Science.gov (United States)

    Bhosle, Monali J; Balkrishnan, Rajesh

    2007-03-01

    Drug reimportation is perceived as a costs-cutting strategy by Americans. Nonetheless, issues such as drug safety and efficacy prevent legalization of the practice. With the contradictory views from supporters and opponents, debate on drug reimportation continues to snowball. The objective of this commentary is to discuss issues regarding drug reimportation practices in the United States (US). It also examines policy implications and potential solutions of the controversy. Comparatively inexpensive drugs available across the border help Americans relieve the burden of medication costs. Consequently, the volume of reimported drugs entering the US has considerably increased. However, these practices are illegal and legalization of drug reimportation is a political debate. While safety is the most important barrier for legalization, this concern does not seem to affect growing number of Americans who are getting their prescriptions filled from across the border. Canadians oppose legalization of reimportation in the US as it could exacerbate the problem of medication shortage in Canada. Currently, legalization of dug reimportation has wedged between the arguments by different groups. Until the US government finds a solution to reduce medication costs, it seems to be impossible to stop Americans from buying the comparatively inexpensive medications available across the border.

  17. The Food and Drug Administration and Drug Legalization: A Brief Model of Regulation

    OpenAIRE

    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...

  18. Moisture and drug solid-state monitoring during a continuous drying process using empirical and mass balance models

    DEFF Research Database (Denmark)

    Fonteyne, Margot; Gildemyn, Delphine; Peeters, Elisabeth

    2014-01-01

    of Process Analytical Technology (PAT) tools (Raman and NIR spectroscopy) and a mass balance approach. The six-segmented fluid bed drying system being part of a fully continuous from-powder-to-tablet production line (ConsiGma™-25) was used for this study. A theophylline:lactose:PVP (30:67.5:2.5) blend......, the different size fractions of the dried granules obtained during different experiments (fines, yield and oversized granules) were compared separately, revealing differences in both solid state of theophylline and moisture content between the different granule size fractions. © 2014 Elsevier B.V. All rights...... reserved...

  19. A Multilevel Ecological Model of HIV Risk for People Who Are Homeless or Unstably Housed and Who Use Drugs in the Urban United States.

    Science.gov (United States)

    Bowen, Elizabeth A

    2016-07-01

    Elevated HIV prevalence has been observed among urban U.S. individuals who use drugs and who lack stable housing. This article synthesizes extant research on this population and situates it in a multilevel, ecologically based model of HIV risk. Based on a multidisciplinary review of the literature, the model applies social-ecological theory on human development to identify factors shaping the HIV risk context for individuals who use drugs and who are unstably housed at global, societal, neighborhood, household, and individual levels of influence. At the global level, the model includes neoliberal ideologies contributing to the social inequalities that frame the HIV epidemic. U.S. housing and drug policy, including urban renewal, HOPE VI, and the War on Drugs, is the focus of the societal level. At the neighborhood level, mechanisms of the built environment and psychosocial mechanisms are explored for their salience to HIV risk. Research on the association between housing instability and HIV risk is reviewed at the household level. At the last level, relevant individual differences in biology, psychology, and cognition are discussed. Modeling risk at multiple levels of the environment underscores the need to expand the focus of research, treatment, and prevention interventions for HIV/AIDS and addictions beyond individuals and their risk behaviors to address facets of structural violence and incorporate the broader social, political, and economic contexts of risk and health.

  20. 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.

  1. Drug Prohibition in the United States: Costs, Consequences, and Alternatives

    Science.gov (United States)

    Nadelmann, Ethan A.

    1989-09-01

    ``Drug legalization'' increasingly merits serious consideration as both an analytical model and a policy option for addressing the ``drug problem.'' Criminal justice approaches to the drug problem have proven limited in their capacity to curtail drug abuse. They also have proven increasingly costly and counterproductive. Drug legalization policies that are wisely implemented can minimize the risks of legalization, dramatically reduce the costs of current policies, and directly address the problems of drug abuse.

  2. Estimation of the cost-effectiveness of HIV prevention portfolios for people who inject drugs in the United States: A model-based analysis.

    Directory of Open Access Journals (Sweden)

    Cora L Bernard

    2017-05-01

    Full Text Available The risks of HIV transmission associated with the opioid epidemic make cost-effective programs for people who inject drugs (PWID a public health priority. Some of these programs have benefits beyond prevention of HIV-a critical consideration given that injection drug use is increasing across most United States demographic groups. To identify high-value HIV prevention program portfolios for US PWID, we consider combinations of four interventions with demonstrated efficacy: opioid agonist therapy (OAT, needle and syringe programs (NSPs, HIV testing and treatment (Test & Treat, and oral HIV pre-exposure prophylaxis (PrEP.We adapted an empirically calibrated dynamic compartmental model and used it to assess the discounted costs (in 2015 US dollars, health outcomes (HIV infections averted, change in HIV prevalence, and discounted quality-adjusted life years [QALYs], and incremental cost-effectiveness ratios (ICERs of the four prevention programs, considered singly and in combination over a 20-y time horizon. We obtained epidemiologic, economic, and health utility parameter estimates from the literature, previously published models, and expert opinion. We estimate that expansions of OAT, NSPs, and Test & Treat implemented singly up to 50% coverage levels can be cost-effective relative to the next highest coverage level (low, medium, and high at 40%, 45%, and 50%, respectively and that OAT, which we assume to have immediate and direct health benefits for the individual, has the potential to be the highest value investment, even under scenarios where it prevents fewer infections than other programs. Although a model-based analysis can provide only estimates of health outcomes, we project that, over 20 y, 50% coverage with OAT could avert up to 22,000 (95% CI: 5,200, 46,000 infections and cost US$18,000 (95% CI: US$14,000, US$24,000 per QALY gained, 50% NSP coverage could avert up to 35,000 (95% CI: 8,900, 43,000 infections and cost US$25,000 (95% CI: US

  3. Estimation of the cost-effectiveness of HIV prevention portfolios for people who inject drugs in the United States: A model-based analysis

    Science.gov (United States)

    Owens, Douglas K.; Goldhaber-Fiebert, Jeremy D.; Brandeau, Margaret L.

    2017-01-01

    Background The risks of HIV transmission associated with the opioid epidemic make cost-effective programs for people who inject drugs (PWID) a public health priority. Some of these programs have benefits beyond prevention of HIV—a critical consideration given that injection drug use is increasing across most United States demographic groups. To identify high-value HIV prevention program portfolios for US PWID, we consider combinations of four interventions with demonstrated efficacy: opioid agonist therapy (OAT), needle and syringe programs (NSPs), HIV testing and treatment (Test & Treat), and oral HIV pre-exposure prophylaxis (PrEP). Methods and findings We adapted an empirically calibrated dynamic compartmental model and used it to assess the discounted costs (in 2015 US dollars), health outcomes (HIV infections averted, change in HIV prevalence, and discounted quality-adjusted life years [QALYs]), and incremental cost-effectiveness ratios (ICERs) of the four prevention programs, considered singly and in combination over a 20-y time horizon. We obtained epidemiologic, economic, and health utility parameter estimates from the literature, previously published models, and expert opinion. We estimate that expansions of OAT, NSPs, and Test & Treat implemented singly up to 50% coverage levels can be cost-effective relative to the next highest coverage level (low, medium, and high at 40%, 45%, and 50%, respectively) and that OAT, which we assume to have immediate and direct health benefits for the individual, has the potential to be the highest value investment, even under scenarios where it prevents fewer infections than other programs. Although a model-based analysis can provide only estimates of health outcomes, we project that, over 20 y, 50% coverage with OAT could avert up to 22,000 (95% CI: 5,200, 46,000) infections and cost US$18,000 (95% CI: US$14,000, US$24,000) per QALY gained, 50% NSP coverage could avert up to 35,000 (95% CI: 8,900, 43,000) infections and

  4. Estimation of the cost-effectiveness of HIV prevention portfolios for people who inject drugs in the United States: A model-based analysis.

    Science.gov (United States)

    Bernard, Cora L; Owens, Douglas K; Goldhaber-Fiebert, Jeremy D; Brandeau, Margaret L

    2017-05-01

    The risks of HIV transmission associated with the opioid epidemic make cost-effective programs for people who inject drugs (PWID) a public health priority. Some of these programs have benefits beyond prevention of HIV-a critical consideration given that injection drug use is increasing across most United States demographic groups. To identify high-value HIV prevention program portfolios for US PWID, we consider combinations of four interventions with demonstrated efficacy: opioid agonist therapy (OAT), needle and syringe programs (NSPs), HIV testing and treatment (Test & Treat), and oral HIV pre-exposure prophylaxis (PrEP). We adapted an empirically calibrated dynamic compartmental model and used it to assess the discounted costs (in 2015 US dollars), health outcomes (HIV infections averted, change in HIV prevalence, and discounted quality-adjusted life years [QALYs]), and incremental cost-effectiveness ratios (ICERs) of the four prevention programs, considered singly and in combination over a 20-y time horizon. We obtained epidemiologic, economic, and health utility parameter estimates from the literature, previously published models, and expert opinion. We estimate that expansions of OAT, NSPs, and Test & Treat implemented singly up to 50% coverage levels can be cost-effective relative to the next highest coverage level (low, medium, and high at 40%, 45%, and 50%, respectively) and that OAT, which we assume to have immediate and direct health benefits for the individual, has the potential to be the highest value investment, even under scenarios where it prevents fewer infections than other programs. Although a model-based analysis can provide only estimates of health outcomes, we project that, over 20 y, 50% coverage with OAT could avert up to 22,000 (95% CI: 5,200, 46,000) infections and cost US$18,000 (95% CI: US$14,000, US$24,000) per QALY gained, 50% NSP coverage could avert up to 35,000 (95% CI: 8,900, 43,000) infections and cost US$25,000 (95% CI: US$7

  5. Models of multiquark states

    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

  6. Strategic drug analysis in fed-state gastric biorelevant media based on drug physicochemical properties.

    Science.gov (United States)

    Baxevanis, Fotios; Kuiper, Jesse; Fotaki, Nikoletta

    2018-03-03

    Milk-based media such as the Fed State Simulated Gastric Fluid (FeSSGF) are commonly used in order to simulate the in vivo properties of the fed state stomach. Due to the lack of a specific guideline for standardised sample clean-up in these media, the aim of the current study was to develop an optimum protocol for the extraction and quantification of drugs from the fed state gastric medium based on the APIs' physicochemical properties (lipophilicity, ionisation, aqueous solubility and protein binding). Two different extraction techniques, protein precipitation (PP) and solid phase extraction (SPE) were assessed. A pilot study in six model drugs was performed, with tests using seven different protein precipitation reagents at four different medium:reagent ratios and two drug concentrations as well as different solid phase extraction cartridges and elution protocols. % recovery was analysed using partial least squares (PLS) regression so as to determine the physicochemical parameters affecting the drug percentage recovered. For protein precipitation protocols, drug concentration, selection of protein precipitation reagent and ratio added to the medium significantly affected drug % recovery from FeSSGF (p < 0.05). The same applied for the selection of elution solvent and cartridge type for solid phase extraction. Optimum protocols using MeOH, ΑCN and 10% w/v TCA at a 1:2 FeSSGF:reagent ratio were effective to a larger group of drugs of a wide range of lipophilicity and ionisation, with ΑCN being the most effective in the whole range of log P values (-0.56-8.81). Solid phase extraction was proven to be effective for compounds of poor to moderate lipophilicity (log P < 4), with extremely hydrophobic compounds demonstrating lower % recovery values (down to 10% recovery). PLS demonstrated that only for 10% w/v TCA (protein precipitation) and HLB (solid phase extraction) can the effect of key drug physicochemical properties on the final amount of drug recovered be

  7. 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

  8. Changes in antioxidant capacity of blood due to mutual action of electromagnetic field (1800 MHz) and opioid drug (tramadol) in animal model of persistent inflammatory state.

    Science.gov (United States)

    Bodera, Paweł; Stankiewicz, Wanda; Zawada, Katarzyna; Antkowiak, Bożena; Paluch, Małgorzata; Kieliszek, Jarosław; Kalicki, Bolesław; Bartosiński, Andrzej; Wawer, Iwona

    2013-01-01

    The biological effects and health implications of electromagnetic field (EMF) associated with cellular mobile telephones and related wireless systems and devices have become a focus of international scientific interest and world-wide public concern. It has also been proved that EMF influences the production of reactive oxygen species (ROS) in different tissues. Experiments were performed in healthy rats and in rats with persistent inflammatory state induced by Complete Freund's Adjuvant (CFA) injection, which was given 24 h before EMF exposure and drug application. Rats were injected with CFA or the same volume of paraffin oil into the plantar surface of the left hind paw. Animals were exposed to the far-field range of an antenna at 1800 MHz with the additional modulation which was identical to that generated by mobile phone GSM 1800. Rats were given 15 min exposure, or were sham-exposed with no voltage applied to the field generator in control groups. Immediately before EMF exposure, rats were injected intraperitoneally with tramadol in the 20 mg/kg dose or vehicle in the 1 ml/kg volume. Our study revealed that single EMF exposure in 1800 MHz frequency significantly reduced antioxidant capacity both in healthy animals and those with paw inflammation. A certain synergic mode of action between applied electromagnetic fields and administered tramadol in rats treated with CFA was observed. The aim of the study was to examine the possible, parallel/combined effects of electromagnetic radiation, artificially induced inflammation and a centrally-acting synthetic opioid analgesic drug, tramadol, (used in the treatment of severe pain) on the antioxidant capacity of blood of rats. The antioxidant capacity of blood of healthy rats was higher than that of rats which received only tramadol and were exposed to electromagnetic fields.

  9. MODELING OF TARGETED DRUG DELIVERY PART II. MULTIPLE DRUG ADMINISTRATION

    Directory of Open Access Journals (Sweden)

    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.

  10. A Profile of Substance Abuse, Gender, Crime, and Drug Policy in the United States and Canada

    Science.gov (United States)

    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…

  11. A State-by-State Analysis of Laws Dealing With Driving Under the Influence of Drugs

    Science.gov (United States)

    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...

  12. "War on drugs" continues in United States under new leadership.

    OpenAIRE

    Gorman, D M

    1993-01-01

    Criticism of the "war on drugs" pursued under Republican administrations has grown in the United States. With the election of Bill Clinton many experts expected a shift from law enforcement policies to an approach favouring treatment and prevention. The budget announced in April, however, revealed no such shift in allocation of resources. Although the war on drugs has apparently failed to reduce the supply of cheap heroin and cocaine to the United States, the prevention strategy favoured by i...

  13. Mathematical modeling and computational prediction of cancer drug resistance.

    Science.gov (United States)

    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

  14. 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.

  15. Modelling drug flux through microporated skin.

    Science.gov (United States)

    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.

  16. Orphan diseases: state of the drug discovery art.

    Science.gov (United States)

    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.

  17. Dengue human infection models supporting drug development.

    Science.gov (United States)

    Whitehorn, James; Van, Vinh Chau Nguyen; Simmons, Cameron P

    2014-06-15

    Dengue is a arboviral infection that represents a major global health burden. There is an unmet need for effective dengue therapeutics to reduce symptoms, duration of illness and incidence of severe complications. Here, we consider the merits of a dengue human infection model (DHIM) for drug development. A DHIM could allow experimentally controlled studies of candidate therapeutics in preselected susceptible volunteers, potentially using smaller sample sizes than trials that recruited patients with dengue in an endemic country. In addition, the DHIM would assist the conduct of intensive pharmacokinetic and basic research investigations and aid in determining optimal drug dosage. Furthermore, a DHIM could help establish proof of concept that chemoprophylaxis against dengue is feasible. The key challenge in developing the DHIM for drug development is to ensure the model reliably replicates the typical clinical and laboratory features of naturally acquired, symptomatic dengue. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America.

  18. Target-mediated drug disposition model and its approximations for antibody-drug conjugates.

    Science.gov (United States)

    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.

  19. Drug screening using model systems: some basics

    Directory of Open Access Journals (Sweden)

    Ross Cagan

    2016-11-01

    Full Text Available An increasing number of laboratories that focus on model systems are considering drug screening. Executing a drug screen is complicated enough. But the path for moving initial hits towards the clinic requires a different knowledge base and even a different mindset. In this Editorial I discuss the importance of doing some homework before you start screening. 'Lead hits', 'patentable chemical space' and 'druggability' are all concepts worth exploring when deciding which screening path to take. I discuss some of the lessons I learned that may be useful as you navigate the screening matrix.

  20. Mathematical modeling of drug release from lipid dosage forms.

    Science.gov (United States)

    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.

  1. Variable Classification of Drug-Intoxication Suicides across US States: A Partial Artifact of Forensics?

    Directory of Open Access Journals (Sweden)

    Ian R H Rockett

    Full Text Available The 21st-century epidemic of pharmaceutical and other drug-intoxication deaths in the United States (US has likely precipitated an increase in misclassified, undercounted suicides. Drug-intoxication suicides are highly prone to be misclassified as accident or undetermined. Misclassification adversely impacts suicide and other injury mortality surveillance, etiologic understanding, prevention, and hence clinical and public health policy formation and practice.To evaluate whether observed variation in the relative magnitude of drug-intoxication suicides across US states is a partial artifact of the scope and quality of toxicological testing and type of medicolegal death investigation system.This was a national, state-based, ecological study of 111,583 drug-intoxication fatalities, whose manner of death was suicide, accident, or undetermined. The proportion of (nonhomicide drug-intoxication deaths classified by medical examiners and coroners as suicide was analyzed relative to the proportion of death certificates citing one or more specific drugs and two types of state death investigation systems. Our model incorporated five sociodemographic covariates. Data covered the period 2008-2010, and derived from NCHS's Multiple Cause-of-Death public use files.Across states, the proportion of drug-intoxication suicides ranged from 0.058 in Louisiana to 0.286 in South Dakota and the rate from 1 per 100,000 population in North Dakota to 4 in New Mexico. There was a low correlation between combined accident and undetermined drug-intoxication death rates and corresponding suicide rates (Spearman's rho = 0.38; p<0.01. Citation of 1 or more specific drugs on the death certificate was positively associated with the relative odds of a state classifying a nonhomicide drug-intoxication death as suicide rather than accident or undetermined, adjusting for region and type of state death investigation system (odds ratio, 1.062; 95% CI,1.016-1.110. Region, too, was a

  2. Beyond the drug-terror nexus: drug trafficking and state-crime relations in Central Asia.

    Science.gov (United States)

    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.

  3. Improving Predictive Modeling in Pediatric Drug Development: Pharmacokinetics, Pharmacodynamics, and Mechanistic Modeling

    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.

  4. A Novel Chronic Opioid Monitoring Tool to Assess Prescription Drug Steady State Levels in Oral Fluid.

    Science.gov (United States)

    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

  5. Inventory of state energy models

    Energy Technology Data Exchange (ETDEWEB)

    Melcher, A.G.; Gist, R.L.; Underwood, R.G.; Weber, J.C.

    1980-03-31

    These models address a variety of purposes, such as supply or demand of energy or of certain types of energy, emergency management of energy, conservation in end uses of energy, and economic factors. Fifty-one models are briefly described as to: purpose; energy system; applications;status; validation; outputs by sector, energy type, economic and physical units, geographic area, and time frame; structure and modeling techniques; submodels; working assumptions; inputs; data sources; related models; costs; references; and contacts. Discussions in the report include: project purposes and methods of research, state energy modeling in general, model types and terminology, and Federal legislation to which state modeling is relevant. Also, a state-by-state listing of modeling efforts is provided and other model inventories are identified. The report includes a brief encylopedia of terms used in energy models. It is assumed that many readers of the report will not be experienced in the technical aspects of modeling. The project was accomplished by telephone conversations and document review by a team from the Colorado School of Mines Research Institute and the faculty of the Colorado School of Mines. A Technical Committee (listed in the report) provided advice during the course of the project.

  6. Econometric modelling of multiple self-reports of health states: The switch from EQ-5D-3L to EQ-5D-5L in evaluating drug therapies for rheumatoid arthritis.

    Science.gov (United States)

    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.

  7. Computational modeling of tetrahydroimidazo-[4,5,1-jk][1,4]-benzodiazepinone derivatives: an atomistic drug design approach using Kier-Hall electrotopological state (E-state) indices.

    Science.gov (United States)

    Sapre, Nitin S; Pancholi, Nilanjana; Gupta, Swagata; Sapre, Neelima

    2008-08-01

    Quantitative structure-activity relationships (QSAR), based on E-state indices have been developed for a series of tetrahydroimidazo-[4,5,1-jk]-benzodiazepinone derivatives against HIV-1 reverse transcriptase (HIV-1 RT). Statistical modeling using multiple linear regression technique in predicting the anti-HIV activity yielded a good correlation for the training set (R(2) = 0.913, R(2)(adj) = 0.897, Q(2) = 0.849, MSE = 0.190, F-ratio = 59.97, PRESS = 18.05, SSE = 0.926, and p value = 0.00). Leave-one-out cross-validation also reaffirmed the predictions (R(2) = 0.850, R(2)(adj) = 0.824, Q(2) = 0.849, MSE = 0.328, and PRESS = 18.05). The predictive ability of the training set was also cross-validated by a test set (R(2) = 0.812, R(2)(adj) = 0.799, Q(2) = 0.765, MSE = 0.347, F-ratio = 64.69, PRESS = 7.37, SSE = 0.975, and p value = 0.00), which ascertained a satisfactory quality of fit. The results reflect the substitution pattern and suggest that the presence of a bulky and electropositive group in the five-member ring and electron withdrawing groups in the seven-member ring will have a positive impact on the antiviral activity of the derivatives. Bulky groups in the six-member ring do not show an activity-enhancing impact. Outlier analysis too reconfirms our findings. The E-state descriptors indicate their importance in quantifying the electronic characteristics of a molecule and thus can be used in chemical interpretation of electronic and steric factors affecting the biological activity of compounds. 2008 Wiley Periodicals, Inc.

  8. Developmental History of U.S. State Department Office of Drug Demand Reduction's International Training

    Science.gov (United States)

    Deitch, David; Koutsenok, Igor

    2005-01-01

    The development of the drug overuse and addiction treatment models in the United States has an enormous impact on the adoption of similar activities throughout the world. The increased globalization of substance abuse attracted treatment practitioners from Europe to the U.S. to examine the implementation of therapeutic community and other models…

  9. Variable Classification of Drug-Intoxication Suicides across US States: A Partial Artifact of Forensics?

    Science.gov (United States)

    Rockett, Ian R H; Hobbs, Gerald R; Wu, Dan; Jia, Haomiao; Nolte, Kurt B; Smith, Gordon S; Putnam, Sandra L; Caine, Eric D

    2015-01-01

    The 21st-century epidemic of pharmaceutical and other drug-intoxication deaths in the United States (US) has likely precipitated an increase in misclassified, undercounted suicides. Drug-intoxication suicides are highly prone to be misclassified as accident or undetermined. Misclassification adversely impacts suicide and other injury mortality surveillance, etiologic understanding, prevention, and hence clinical and public health policy formation and practice. To evaluate whether observed variation in the relative magnitude of drug-intoxication suicides across US states is a partial artifact of the scope and quality of toxicological testing and type of medicolegal death investigation system. This was a national, state-based, ecological study of 111,583 drug-intoxication fatalities, whose manner of death was suicide, accident, or undetermined. The proportion of (nonhomicide) drug-intoxication deaths classified by medical examiners and coroners as suicide was analyzed relative to the proportion of death certificates citing one or more specific drugs and two types of state death investigation systems. Our model incorporated five sociodemographic covariates. Data covered the period 2008-2010, and derived from NCHS's Multiple Cause-of-Death public use files. Across states, the proportion of drug-intoxication suicides ranged from 0.058 in Louisiana to 0.286 in South Dakota and the rate from 1 per 100,000 population in North Dakota to 4 in New Mexico. There was a low correlation between combined accident and undetermined drug-intoxication death rates and corresponding suicide rates (Spearman's rho = 0.38; psuicide rather than accident or undetermined, adjusting for region and type of state death investigation system (odds ratio, 1.062; 95% CI,1.016-1.110). Region, too, was a significant predictor. Relative to the South, a 10% increase in drug citation was associated with 43% (95% CI,11%-83%), 41% (95% CI,7%-85%), and 33% (95% CI,1%-76%) higher odds of a suicide

  10. Modeling volatility using state space models.

    Science.gov (United States)

    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).

  11. Undocumented Immigration, Drug Problems, and Driving Under the Influence in the United States, 1990-2014.

    Science.gov (United States)

    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.

  12. Markov state models and molecular alchemy

    Science.gov (United States)

    Schütte, Christof; Nielsen, Adam; Weber, Marcus

    2015-01-01

    In recent years, Markov state models (MSMs) have attracted a considerable amount of attention with regard to modelling conformation changes and associated function of biomolecular systems. They have been used successfully, e.g. for peptides including time-resolved spectroscopic experiments, protein function and protein folding , DNA and RNA, and ligand-receptor interaction in drug design and more complicated multivalent scenarios. In this article, a novel reweighting scheme is introduced that allows to construct an MSM for certain molecular system out of an MSM for a similar system. This permits studying how molecular properties on long timescales differ between similar molecular systems without performing full molecular dynamics simulations for each system under consideration. The performance of the reweighting scheme is illustrated for simple test cases, including one where the main wells of the respective energy landscapes are located differently and an alchemical transformation of butane to pentane where the dimension of the state space is changed.

  13. 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)

  14. Mathematical models of tumor heterogeneity and drug resistance

    Science.gov (United States)

    Greene, James

    In this dissertation we develop mathematical models of tumor heterogeneity and drug resistance in cancer chemotherapy. Resistance to chemotherapy is one of the major causes of the failure of cancer treatment. Furthermore, recent experimental evidence suggests that drug resistance is a complex biological phenomena, with many influences that interact nonlinearly. Here we study the influence of such heterogeneity on treatment outcomes, both in general frameworks and under specific mechanisms. We begin by developing a mathematical framework for describing multi-drug resistance to cancer. Heterogeneity is reflected by a continuous parameter, which can either describe a single resistance mechanism (such as the expression of P-gp in the cellular membrane) or can account for the cumulative effect of several mechanisms and factors. The model is written as a system of integro-differential equations, structured by the continuous "trait," and includes density effects as well as mutations. We study the limiting behavior of the model, both analytically and numerically, and apply it to study treatment protocols. We next study a specific mechanism of tumor heterogeneity and its influence on cell growth: the cell-cycle. We derive two novel mathematical models, a stochastic agent-based model and an integro-differential equation model, each of which describes the growth of cancer cells as a dynamic transition between proliferative and quiescent states. By examining the role all parameters play in the evolution of intrinsic tumor heterogeneity, and the sensitivity of the population growth to parameter values, we show that the cell-cycle length has the most significant effect on the growth dynamics. In addition, we demonstrate that the agent-based model can be approximated well by the more computationally efficient integro-differential equations, when the number of cells is large. The model is closely tied to experimental data of cell growth, and includes a novel implementation of

  15. Drug-Excipient Interactions in the Solid State: The Role of Different Stress Factors.

    Science.gov (United States)

    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.

  16. Investigating drug repositioning opportunities in FDA drug labels through topic modeling.

    Science.gov (United States)

    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

  17. A Model for Random Student Drug Testing

    Science.gov (United States)

    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)…

  18. Application of Model Animals in the Study of Drug Toxicology

    Science.gov (United States)

    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.

  19. [Organization of the drug supply chain in state health services: potential consequences of the public-private mix].

    Science.gov (United States)

    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.

  20. Drug discrimination models in anxiety and depression.

    Science.gov (United States)

    Andrews, J S; Stephens, D N

    1990-01-01

    Drug discrimination is a technique for investigating the stimulus properties of centrally active drugs. Although many studies have employed animals to investigate the stimulus properties of substances used clinically for the treatment of anxiety and depression, it would be a mistake to consider the internal discriminative stimuli as being related specifically to the anxiolytic or antidepressant properties of these drugs. Rather drug cues are better considered as relating to the pharmacological action of classes of compounds. Thus, benzodiazepine cues generalize to other compounds acting at benzodiazepine receptors, but not to substances (anxiolytic or otherwise) acting at 5-HT1A receptors. Similarly, antidepressants with different pharmacological properties, for example the tricyclic imipramine, or the phenylaminoketone buproprion produce distinct, unrelated discriminative stimuli. For this reason, the limits of drug discrimination techniques for investigating novel anxiolytic or antidepressant drugs should be clearly recognized. Attempts to identify an anxiogenic discriminative stimulus using pentylenetetrazole have also been misguided. In this technique it has proven difficult to separate unequivocally the pharmacological proconvulsant effects of the drug from the psychological construct anxiety. Nevertheless, drug discrimination remains a valuable technique for investigating pharmacological interactions in animals and man.

  1. U.S. Food and Drug Administration drug approval: slow advances in obstetric care in the United States.

    Science.gov (United States)

    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.

  2. 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.

  3. Modeling the modified drug release from curved shape drug delivery systems - Dome Matrix®.

    Science.gov (United States)

    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.

  4. Anti-Cancer Drug Validation: the Contribution of Tissue Engineered Models.

    Science.gov (United States)

    Carvalho, Mariana R; Lima, Daniela; Reis, Rui L; Oliveira, Joaquim M; Correlo, Vitor M

    2017-06-01

    Drug toxicity frequently goes concealed until clinical trials stage, which is the most challenging, dangerous and expensive stage of drug development. Both the cultures of cancer cells in traditional 2D assays and animal studies have limitations that cannot ever be unraveled by improvements in drug-testing protocols. A new generation of bioengineered tumors is now emerging in response to these limitations, with potential to transform drug screening by providing predictive models of tumors within their tissue context, for studies of drug safety and efficacy. Considering the NCI60, a panel of 60 cancer cell lines representative of 9 different cancer types: leukemia, lung, colorectal, central nervous system (CNS), melanoma, ovarian, renal, prostate and breast, we propose to review current "state of art" on the 9 cancer types specifically addressing the 3D tissue models that have been developed and used in drug discovery processes as an alternative to complement their study.

  5. Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism

    DEFF Research Database (Denmark)

    Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik

    2016-01-01

    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...... are useful for understanding drug metabolism....

  6. Drugs and Crime: An Empirically Based, Interdisciplinary Model

    Science.gov (United States)

    Quinn, James F.; Sneed, Zach

    2008-01-01

    This article synthesizes neuroscience findings with long-standing criminological models and data into a comprehensive explanation of the relationship between drug use and crime. The innate factors that make some people vulnerable to drug use are conceptually similar to those that predict criminality, supporting a spurious reciprocal model of the…

  7. NCHS - Drug Poisoning Mortality by County: United States

    Data.gov (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...

  8. A Qualitative View of Drug Use Behaviors of Mexican Male Injection Drug Users Deported from the United States

    OpenAIRE

    Ojeda, Victoria D.; Robertson, Angela M.; Hiller, Sarah P.; Lozada, Remedios; Cornelius, Wayne; Palinkas, Lawrence A.; Magis-Rodriguez, Carlos; Strathdee, Steffanie A.

    2011-01-01

    Deportees are a hidden yet highly vulnerable and numerous population. Significantly, little data exists about the substance use and deportation experiences of Mexicans deported from the United States. This pilot qualitative study describes illicit drug use behaviors among 24 Mexico-born male injection drug users (IDUs), ≥18 years old, residing in Tijuana, Mexico who self-identified as deportees from the United States. In-person interviews were conducted in Tijuana, Mexico in 2008. Content ana...

  9. Evaluation of drug permeation under fed state conditions using mucus-covered Caco-2 cell epithelium.

    Science.gov (United States)

    Birch, Ditlev; Diedrichsen, Ragna G; Christophersen, Philip C; Mu, Huiling; Nielsen, Hanne M

    2018-03-07

    The absence of a surface-lining mucus layer is a major pitfall for the Caco-2 epithelial model. However, this can be alleviated by applying biosimilar mucus (BM) to the apical surface of the cell monolayer, thereby constructing a mucosa mimicking in vivo conditions. This study aims to elucidate the influence of BM as a barrier towards exogenic compounds such as permeation enhancers, and components of fed state simulated intestinal fluid (FeSSIF). Caco-2 cell monolayers surface-lined with BM were exposed to several compounds with distinct physicochemical properties, and the cell viability and permeability of the cell monolayer was compared to that of cell monolayers without BM and well-established mucus-secreting epithelial models (HT29 monolayers and HT29/Caco-2 co-culture monolayers). Exposure of BM-covered cells to constituents from FeSSIF revealed that it comprised a strong, hydrophilic barrier effect as 90% of BM-covered cells remained viable for >4 h, and the permeation rate of hydrophobic drugs was reduced. In contrast, the permeation rate of hydrophilic drugs was largely unaffected. Control monolayers displayed a loss of barrier function and Caco-2 cell monolayers surface-lined with BM constitute a valuable in vitro model that makes it possible to mimic intestinal fed state conditions when studying drug permeation. Copyright © 2017. Published by Elsevier B.V.

  10. Modelling Formation of a Drug Reservoir in the Stratum Corneum and Its Impact on Drug Monitoring Using Reverse Iontophoresis

    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.

  11. Personalized drug administration for cancer treatment using Model Reference Adaptive Control.

    Science.gov (United States)

    Babaei, Naser; Salamci, Metin U

    2015-04-21

    A new Model Reference Adaptive Control (MRAC) approach is proposed for the nonlinear regulation problem of cancer treatment via chemotherapy. We suggest an approach for determining an optimal anticancer drug delivery scenario for cancer patients without prior knowledge of nonlinear model structure and parameters by compounding State Dependent Riccati Equation (SDRE) and MRAC which will lead to personalized drug administration. Several approaches have been proposed for eradicating cancerous cells in nonlinear tumor growth model. The main difficulty in these approaches is the requirement of nonlinear model parameters, which are unknown to physicians in reality. To cope with this shortage, we first determine the drug delivery scenario for a reference patient with known mathematical model and parameters via SDRE technique, and by using the proposed approach we adapt the drug administration scenario for another cancer patient despite unknown nonlinear model structure and model parameters. We propose an efficient approach to determine drug administration which will help physicians for prescribing a chemotherapy protocol for a cancer patient by regulating the drug delivery scenario of the reference patient. Stabilizing the tumor growth nonlinear model has been achieved via full state feedback techniques and yields a near optimal solution to cancer treatment problem. Numerical simulations show the effectiveness of the proposed algorithm for eradicating tumor lumps with different sizes in different patients. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Effects of drug solubility, state and loading on controlled release in bicomponent electrospun fibers

    OpenAIRE

    Natu, Mădălina V.; Sousa, Hermínio C. de; Gil, M. H.

    2010-01-01

    Bicomponent fibers of two semi-crystalline (co)polymers, poly(ɛ-caprolactone), and poly(oxyethylene-b-oxypropylene-b-oxyethylene), were obtained by electrospinning. Acetazolamide and timolol maleate were loaded in the fibers in different concentrations (below and above the drug solubility limit in polymer) in order to determine the effect of drug solubility in polymer, drug state, drug loading and fiber composition on fiber morphology, drug distribution and release kinetics. The high loadings...

  13. 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

  14. Social and legal factors related to drug abuse in the United States and Japan.

    OpenAIRE

    Greberman, S B; Wada, K

    1994-01-01

    This article is an overview of social and legal differences in the United States and in Japan that are related to patterns of current drug abuse epidemics in these countries. These two nations have drug abuse problems with different histories and take different approaches currently to handling illicit drug marketing and use. Histories of opiate and cocaine abuse in the United States and of stimulant and inhalant abuse in Japan are discussed. The United States has experienced three heroin epid...

  15. A pharmacokinetic drug-drug interaction model of simvastatin and clarithromycin in humans.

    Science.gov (United States)

    Methaneethorn, Janthima; Chaiwong, Krissanapong; Pongpanich, Komwut; Sonsingh, Phakawat; Lohitnavy, Manupat

    2014-01-01

    Simvastatin is a HMG-CoA reductase Inhibitor and a substrate of CYP3A4. Clarithromycin is a commonly used macrolide antibiotics and a potent inhibitor of CYP3A4. When co-administered with simvastatin, clarithromycin can significantly increase simvastatin plasma concentration levels, thereby, increase the risk of rhabdomyolysis. At present, pharmacokinetic data of the interaction between both drugs are available. However, they are being used for semi-quantitative application only, not for quantitative prediction. We aimed to develop a mathematical model describing a drug-drug interaction between simvastatin and clarithromycin in humans. Selected pharmacokinetic interaction study was obtained from PubMed search. Concentration-time course data were subsequently extracted and used for model development. Compartmental pharmacokinetic interaction model was developed using Advanced Continuous Simulating Language Extreme (ACSLX), a FORTRAN language-based computer program. The drug-drug interaction between simvastatin and clarithromycin was modeled simultaneously with a parent-metabolite model for clarithromycin and a one-compartment model for simvastatin linked to its active form, simvastatin hydroxy acid. The simulated simvastatin concentrations obtained from the final model displayed satisfactory goodness of fit to the data from the literature. Our model could successfully describe concentration-time course of simvastatin-clarithromycin interaction. The resulting interaction model can be able to use for further development of a quantitative model predicting rhabdomyolysis occurrence in patients concurrently receiving simvastatin and clarithromycin.

  16. Floating solid cellulose nanofibre nanofoams for sustained release of the poorly soluble model drug furosemide

    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...

  17. Mathematical modeling for novel cancer drug discovery and development.

    Science.gov (United States)

    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.

  18. 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

  19. hiv prevention among drug and alcohol users: models of ...

    African Journals Online (AJOL)

    Administrator

    HIV PREVENTION AMONG DRUG AND ALCOHOL USERS: MODELS. OF INTERVENTION IN KENYA. Clement S. Deveau. Academy for Educational Development (AED). Capable Partners Program (CAP). Nairobi, Kenya. ABSTRACT. The spread of HIV among drug and alcohol users, as a high-risk group, is a significant ...

  20. Drug Per Se Laws: A Review of their Use in States

    Science.gov (United 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...

  1. Revealing kinetics and state-dependent binding properties of IKur-targeting drugs that maximize atrial fibrillation selectivity

    Science.gov (United States)

    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

  2. Drug-induced cholestasis: mechanisms, models, and markers.

    Science.gov (United States)

    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.

  3. 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.

  4. Teratogenic potential of antiepileptic drugs in the zebrafish model.

    Science.gov (United States)

    Lee, Sung Hak; Kang, Jung Won; Lin, Tao; Lee, Jae Eun; Jin, Dong Il

    2013-01-01

    The zebrafish model is an attractive candidate for screening of developmental toxicity during early drug development. Antiepileptic drugs (AEDs) arouse concern for the risk of teratogenicity, but the data are limited. In this study, we evaluated the teratogenic potential of seven AEDs (carbamazepine (CBZ), ethosuximide (ETX), valproic acid (VPN), lamotrigine (LMT), lacosamide (LCM), levetiracetam (LVT), and topiramate (TPM)) in the zebrafish model. Zebrafish embryos were exposed to AEDs from initiation of gastrula (5.25 hours post-fertilization (hpf)) to termination of hatching (72 hpf) which mimic the mammalian teratogenic experimental design. The lethality and teratogenic index (TI) of AEDs were determined and the TI values of each drug were compared with the US FDA human pregnancy categories. Zebrafish model was useful screening model for teratogenic potential of antiepilepsy drugs and was in concordance with in vivo mammalian data and human clinical data.

  5. The model of drugs distribution dynamics in biological tissue

    Science.gov (United States)

    Ginevskij, D. A.; Izhevskij, P. V.; Sheino, I. N.

    2017-09-01

    The dose distribution by Neutron Capture Therapy follows the distribution of 10B in the tissue. The modern models of pharmacokinetics of drugs describe the processes occurring in conditioned "chambers" (blood-organ-tumor), but fail to describe the spatial distribution of the drug in the tumor and in normal tissue. The mathematical model of the spatial distribution dynamics of drugs in the tissue, depending on the concentration of the drug in the blood, was developed. The modeling method is the representation of the biological structure in the form of a randomly inhomogeneous medium in which the 10B distribution occurs. The parameters of the model, which cannot be determined rigorously in the experiment, are taken as the quantities subject to the laws of the unconnected random processes. The estimates of 10B distribution preparations in the tumor and healthy tissue, inside/outside the cells, are obtained.

  6. My Life with State Space Models

    DEFF Research Database (Denmark)

    Lundbye-Christensen, Søren

    2007-01-01

    State space models have had a tremendous impact on the analysis of time series. Even though the models and ideas are much older the work that Mike West and others started in the 1980ies brought the attention to the statisticians and the models and inferential possibilities have developed enormously....... 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...... models. I will not try to give a thorough exposition of the development from simple linear Gaussian state space models to the highly non-linear models analysed with computer intensive methods. Instead I will give examples of some health related applications, that I have been involved in, and relate...

  7. "The Attila the Hun law": New York's Rockefeller drug laws and the making of a punitive state.

    Science.gov (United States)

    Kohler-Hausmann, Julilly

    2010-01-01

    In 1973, New York's Governor Nelson Rockefeller responded to panic about soaring heroin use by renouncing his aggressive treatment programs and enacting the most punitive drug policy in the United States. His "Rockefeller Drug Laws" mandated sentences up to life in prison for selling any narcotics. These punishments, comparable to the penalties for murder, served as models for subsequent "War on Drugs" policies enacted across the nation.This article explores the ideological and political work accomplished by this high profile legislation—for policy makers, for members of the general public who clamored for "get tough" strategies, and for the drug users targeted by the statutes. The laws were a repudiation of liberal treatment programs and specialists' expertise, and provided a forum to remake the much-maligned welfare state into a stern, macho vehicle for establishing order in society. Increasingly punitive policies constricted the rights of drug users by rhetorically constructing "addicts" and "pushers" as outside of the polity and as the antithesis of full citizens. Therefore, the Rockefeller Drug Laws not only had devastating effects on drug offenders, but also were instrumental in the profound renegotiation of the state's role and responsibilities.

  8. Statistical Agent Based Modelization of the Phenomenon of Drug Abuse

    Science.gov (United States)

    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.

  9. A graph theoretical perspective of a drug abuse epidemic model

    Science.gov (United States)

    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.

  10. 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

  11. State and Community Responses to Drug-related Violence in Mexico

    International Development Research Centre (IDRC) Digital Library (Canada)

    Studies. State and community responses to drug-related violence in Mexico. Download PDF. Reports. State and community responses to drug-related violence in Mexico. Download PDF. Reports. Respuestas estatales y comunitarias a la violencia asociada al narcotráfico en México : informe técnico. Download PDF ...

  12. State and Community Responses to Drug-related Violence in Mexico

    International Development Research Centre (IDRC) Digital Library (Canada)

    State and Community Responses to Drug-related Violence in Mexico. Violent conflict related to drug trafficking in Mexico has had a profound impact on the quality of life and health of affected communities. Nevertheless, there is very little evidence about who these victims are, how they are victimized, and what the state's ...

  13. 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

  14. An invertebrate model for CNS drug discovery

    DEFF Research Database (Denmark)

    Al-Qadi, Sonia; Schiøtt, Morten; Hansen, Steen Honoré

    2015-01-01

    , high-throughput and predictive screening models are required. The grasshopper (locust) has been developed as an invertebrate in situ model for BBB permeability assessment, as it has shown similarities to vertebrate models. METHODS: Transcriptome profiling of ABC efflux transporters in the locust brain...

  15. Forecasting state-level premature deaths from alcohol, drugs, and suicides using Google Trends data.

    Science.gov (United States)

    Parker, Jason; Cuthbertson, Courtney; Loveridge, Scott; Skidmore, Mark; Dyar, Will

    2017-04-15

    Vital statistics on the number of, alcohol-induced death (AICD) drug-induced death (DICD), and suicides at the local-level are only available after a substantial lag of up to two years after the events occur. We (1) investigate how well Google Trends search data explain variation in state-level rates in the US, and (2) use this method to forecast these rates of death for 2015 as official data are not yet available. We tested the degree to which Google Trends data on 27 terms can be fit to CDC data using L 1 -regularization on AICD, DICD, and suicide. Using Google Trends data, we forecast 2015 AICD, DICD, and suicide rates. L 1 -regularization fit the pre-2015 data much better than the alternative model using state-level unemployment and income variables. Google Trends data account for substantial variation in growth of state-level rates of death: 30.9% for AICD, 23.9% for DICD, and 21.8% for suicide rates. Every state except Hawaii is forecasted to increase in all three of these rates in 2015. The model predicts state, not local or individual behavior, and is dependent on continued availability of Google Trends data. The method predicts state-level AICD, DICD, and suicide rates better than the alternative model. The study findings suggest that this methodology can be developed into a public health surveillance system for behavioral health-related causes of death. State-level predictions could be used to inform state interventions aimed at reducing AICD, DICD, and suicide. Copyright © 2017. Published by Elsevier B.V.

  16. Prospects for United States-Mexican cooperation in the war on drug trafficking

    OpenAIRE

    Murphy, Thomas A.

    1990-01-01

    Approved for public release; distribution is unlimited. Drug control policy on the Southwest U.S. border requires an exceptional level of cooperation between Mexico and the United States. This thesis examines the formulation and evolution of drug control policies in both countries, and analyzes the mutual interests and the unique constraints facing them. The thesis recommends eight proposals for improving cooperation between Mexico and the United States in the war on drugs, which include: ...

  17. Association between unemployment rates and prescription drug utilization in the United States, 2007–2010

    Science.gov (United States)

    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

  18. Modeling of drug release from matrix systems involving moving boundaries: approximate analytical solutions.

    Science.gov (United States)

    Lee, Ping I

    2011-10-10

    The purpose of this review is to provide an overview of approximate analytical solutions to the general moving boundary diffusion problems encountered during the release of a dispersed drug from matrix systems. Starting from the theoretical basis of the Higuchi equation and its subsequent improvement and refinement, available approximate analytical solutions for the more complicated cases involving heterogeneous matrix, boundary layer effect, finite release medium, surface erosion, and finite dissolution rate are also discussed. Among various modeling approaches, the pseudo-steady state assumption employed in deriving the Higuchi equation and related approximate analytical solutions appears to yield reasonably accurate results in describing the early stage release of a dispersed drug from matrices of different geometries whenever the initial drug loading (A) is much larger than the drug solubility (C(s)) in the matrix (or A≫C(s)). However, when the drug loading is not in great excess of the drug solubility (i.e. low A/C(s) values) or when the drug loading approaches the drug solubility (A→C(s)) which occurs often with drugs of high aqueous solubility, approximate analytical solutions based on the pseudo-steady state assumption tend to fail, with the Higuchi equation for planar geometry exhibiting a 11.38% error as compared with the exact solution. In contrast, approximate analytical solutions to this problem without making the pseudo-steady state assumption, based on either the double-integration refinement of the heat balance integral method or the direct simplification of available exact analytical solutions, show close agreement with the exact solutions in different geometries, particularly in the case of low A/C(s) values or drug loading approaching the drug solubility (A→C(s)). However, the double-integration heat balance integral approach is generally more useful in obtaining approximate analytical solutions especially when exact solutions are not

  19. SEIIrR: Drug abuse model with rehabilitation

    Science.gov (United States)

    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.

  20. Developing an Agent-Based Drug Model to Investigate the Synergistic Effects of Drug Combinations.

    Science.gov (United States)

    Gao, Hongjie; Yin, Zuojing; Cao, Zhiwei; Zhang, Le

    2017-12-14

    The growth and survival of cancer cells are greatly related to their surrounding microenvironment. To understand the regulation under the impact of anti-cancer drugs and their synergistic effects, we have developed a multiscale agent-based model that can investigate the synergistic effects of drug combinations with three innovations. First, it explores the synergistic effects of drug combinations in a huge dose combinational space at the cell line level. Second, it can simulate the interaction between cells and their microenvironment. Third, it employs both local and global optimization algorithms to train the key parameters and validate the predictive power of the model by using experimental data. The research results indicate that our multicellular system can not only describe the interactions between the microenvironment and cells in detail, but also predict the synergistic effects of drug combinations.

  1. Model Checking Multivariate State Rewards

    DEFF Research Database (Denmark)

    Nielsen, Bo Friis; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    We consider continuous stochastic logics with state rewards that are interpreted over continuous time Markov chains. We show how results from multivariate phase type distributions can be used to obtain higher-order moments for multivariate state rewards (including covariance). We also generalise...

  2. Modeling Per Capita State Health Expenditure Variat...

    Data.gov (United States)

    U.S. Department of Health & Human Services — Modeling Per Capita State Health Expenditure Variation State-Level Characteristics Matter, published in Volume 3, Issue 4, of the Medicare and Medicaid Research...

  3. Animal Migraine Models for Drug Development

    DEFF Research Database (Denmark)

    Jansen-Olesen, Inger; Tfelt-Hansen, Peer; Olesen, Jes

    2013-01-01

    responses are likely to be behavioral, allowing multiple experiments in each individual animal. Distinction is made between acute and prophylactic models and how to validate each of them. Modern insight into neurobiological mechanisms of migraine is so good that it is only a question of resources...... 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...

  4. Drug poisoning deaths in the United States, 1980-2008.

    Science.gov (United States)

    Warner, Margaret; Chen, Li Hui; Makuc, Diane M; Anderson, Robert N; Miniño, Arialdi M

    2011-12-01

    In 2008, the number of poisoning deaths exceeded the number of motor vehicle traffic deaths and was the leading cause of injury death for the fi rst time since at least 1980. During the past three decades, the poisoning death rate nearly tripled, while the motor vehicle traffic death rate decreased by one-half. During this period, the percentage of poisoning deaths that were caused by drugs increased from about 60% to about 90%. The population groups with the highest drug poisoning death rates in 2008 were males, people aged 45–54 years, and non-Hispanic white and American Indian or Alaska Native persons. The vast majority of drug poisoning deaths are unintentional (see Appendix table). Opioid analgesics were involved in more drug poisoning deaths than other specified drugs, including heroin and cocaine. Opioid analgesics were involved in nearly 15,000 deaths in 2008, while cocaine was involved in about 5,100 deaths and heroin was involved in about 3,000 deaths (data not shown). Deaths involving opioid analgesics may involve other drugs as well, including benzodiazepines (2). In addition to an increase in the number of deaths caused by drug poisoning, increases in drug use, abuse, misuse, and nonfatal health outcomes have been observed. In the past two decades, there has been an increase in the distribution and medical use of prescription drugs, including opioid analgesics (3). From 1999 to 2008, the use of prescription medications increased (4). In 2007–2008, 48% of Americans used at least one prescription drug in the past month and 11% of Americans used five or more prescriptions in the past month. Analgesics for pain relief were among the common drugs taken by adults aged 20–59 years (4). In 2009–2010, over 5 million Americans reported using prescription pain relievers nonmedically in the past month (that is, without a doctor’s prescription or only for the experience or feeling they caused), and the majority of people using prescription pain relievers

  5. Cellular automata model for drug release from binary matrix and reservoir polymeric devices.

    Science.gov (United States)

    Johannes Laaksonen, Timo; Mikael Laaksonen, Hannu; Tapio Hirvonen, Jouni; Murtomäki, Lasse

    2009-04-01

    Kinetics of drug release from polymeric tablets, inserts and implants is an important and widely studied area. Here we present a new and widely applicable cellular automata model for diffusion and erosion processes occurring during drug release from polymeric drug release devices. The model divides a 2D representation of the release device into an array of cells. Each cell contains information about the material, drug, polymer or solvent that the domain contains. Cells are then allowed to rearrange according to statistical rules designed to match realistic drug release. Diffusion is modeled by a random walk of mobile cells and kinetics of chemical or physical processes by probabilities of conversion from one state to another. This is according to the basis of diffusion coefficients and kinetic rate constants, which are on fundamental level just probabilities for certain occurrences. The model is applied to three kinds of devices with different release mechanisms: erodable matrices, diffusion through channels or pores and membrane controlled release. The dissolution curves obtained are compared to analytical models from literature and the validity of the model is considered. The model is shown to be compatible with all three release devices, highlighting easy adaptability of the model to virtually any release system and geometry. Further extension and applications of the model are envisioned.

  6. The High Cost of Prescription Drugs in the United States: Origins and Prospects for Reform.

    Science.gov (United States)

    Kesselheim, Aaron S; Avorn, Jerry; Sarpatwari, Ameet

    The increasing cost of prescription drugs in the United States has become a source of concern for patients, prescribers, payers, and policy makers. To review the origins and effects of high drug prices in the US market and to consider policy options that could contain the cost of prescription drugs. We reviewed the peer-reviewed medical and health policy literature from January 2005 to July 2016 for articles addressing the sources of drug prices in the United States, the justifications and consequences of high prices, and possible solutions. Per capita prescription drug spending in the United States exceeds that in all other countries, largely driven by brand-name drug prices that have been increasing in recent years at rates far beyond the consumer price index. In 2013, per capita spending on prescription drugs was $858 compared with an average of $400 for 19 other industrialized nations. In the United States, prescription medications now comprise an estimated 17% of overall personal health care services. The most important factor that allows manufacturers to set high drug prices is market exclusivity, protected by monopoly rights awarded upon Food and Drug Administration approval and by patents. The availability of generic drugs after this exclusivity period is the main means of reducing prices in the United States, but access to them may be delayed by numerous business and legal strategies. The primary counterweight against excessive pricing during market exclusivity is the negotiating power of the payer, which is currently constrained by several factors, including the requirement that most government drug payment plans cover nearly all products. Another key contributor to drug spending is physician prescribing choices when comparable alternatives are available at different costs. Although prices are often justified by the high cost of drug development, there is no evidence of an association between research and development costs and prices; rather, prescription

  7. Assessment of different polymers and drug loads for fused deposition modeling of drug loaded implants.

    Science.gov (United States)

    Kempin, Wiebke; Franz, Christian; Koster, Lynn-Christine; Schneider, Felix; Bogdahn, Malte; Weitschies, Werner; Seidlitz, Anne

    2017-06-01

    The 3D printing technique of fused deposition modeling® (FDM) has lately come into focus as a potential fabrication technique for pharmaceutical dosage forms and medical devices that allows the preparation of delivery systems with nearly any shape. This is particular promising for implants administered at application sites with a high anatomical variability where an individual shape adaption appears reasonable. In this work different polymers (Eudragit®RS, polycaprolactone (PCL), poly(l-lactide) (PLLA) and ethyl cellulose (EC)) were evaluated with respect to their suitability for FDM of drug loaded implants and their drug release behaviour was evaluated. The fluorescent dye quinine was used as a model drug to visualize drug distribution in filaments and implants. Quinine loaded filaments were produced by solvent casting and subsequent hot melt extrusion (HME) and model implants were printed as hollow cylinders using a standard FDM printer. Parameters were found at which model implants (hollow cylinders, outer diameter 4-5mm, height 3mm) could be produced from all tested polymers. The drug release which was examined by incubation of the printed implants in phosphate buffered saline solution (PBS) pH 7.4 was highly dependent on the used polymer. The fastest relative drug release of approximately 76% in 51days was observed for PCL and the lowest for Eudragit®RS and EC with less than 5% of quinine release in 78 and 100days, respectively. For PCL further filaments were prepared with different quinine loads ranging from 2.5% to 25% and thermal analysis proved the presence of a solid dispersion of quinine in the polymer for all tested concentrations. Increasing the drug load also increased the overall percentage of drug released to the medium since nearly the same absolute amount of quinine remained trapped in PCL at the end of drug release studies. This knowledge is valuable for future developments of printed implants with a desired drug release profile that might be

  8. Drug-loaded electrospun mats of poly(vinyl alcohol) fibres and their release characteristics of four model drugs

    Science.gov (United States)

    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.

  9. Regulation of chromatin states by drugs of abuse.

    Science.gov (United States)

    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.

  10. A regulatory perspective on the abuse potential evaluation of novel stimulant drugs in the United States.

    Science.gov (United States)

    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.

  11. Novel films for drug delivery via the buccal mucosa using model soluble and insoluble drugs.

    Science.gov (United States)

    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.

  12. Relapse Model among Iranian Drug Users: A Qualitative Study.

    Science.gov (United States)

    Jalali, Amir; Seyedfatemi, Naiemeh; Peyrovi, Hamid

    2015-01-01

    Relapse is a common problem in drug user's rehabilitation program and reported in all over the country. An in-depth study on patients' experiences can be used for exploring the relapse process among drug users. Therefore, this study suggests a model for relapse process among Iranian drug users. In this qualitative study with grounded theory approach, 22 participants with rich information about the phenomenon under the study were selected using purposive, snowball and theoretical sampling methods. After obtaining the informed consent, data were collected based on face-to-face, in-depth, semi-structured interviews. All interviews were analyzed in three stages of axial, selective and open coding methods. Nine main categories emerged, including avoiding of drugs, concerns about being accepted, family atmosphere, social conditions, mental challenge, self-management, self-deception, use and remorse and a main category, feeling of loss as the core variable. Mental challenge has two subcategories, evoking pleasure and craving. Relapse model is a dynamic and systematic process including from cycles of drug avoidance to remorse with a core variable as feeling of loss.  Relapse process is a dynamic and systematic process that needs an effective control. Determining a relapse model as a clear process could be helpful in clinical sessions. RESULTS of this research have depicted relapse process among Iranian drugs user by conceptual model.

  13. Comparing Generic Drug Markets in Europe and the United States: Prices, Volumes, and Spending.

    Science.gov (United States)

    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

  14. Fitting State Space Models with EViews

    Directory of Open Access Journals (Sweden)

    Filip A. M. Van den Bossche

    2011-05-01

    Full Text Available This paper demonstrates how state space models can be fitted in EViews. We first briefly introduce EViews as an econometric software package. Next we fit a local level model to the Nile data. We then show how a multivariate “latent risk” model can be developed, making use of the EViews programming environment. We conclude by summarizing the possibilities and limitations of the software package when it comes to state space modeling.

  15. Steady-State Process Modelling

    DEFF Research Database (Denmark)

    Cameron, Ian; Gani, Rafiqul

    2011-01-01

    illustrate the “equation oriented” approach as well as the “sequential modular” approach to solving complex flowsheets for steady state applications. The applications include the Williams-Otto plant, the hydrodealkylation (HDA) of toluene, conversion of ethylene to ethanol and a bio-ethanol process....

  16. Search for Active-State Conformation of Drug Target GPCR Using Real-Coded Genetic Algorithm

    Science.gov (United States)

    Ishino, Yoko; Harada, Takanori; Aida, Misako

    G-Protein coupled receptors (GPCRs) comprise a large superfamily of proteins and are a target for nearly 50% of drugs in clinical use today. GPCRs have a unique structural motif, seven transmembrane helices, and it is known that agonists and antagonists dock with a GPCR in its ``active'' and ``inactive'' condition, respectively. Knowing conformations of both states is eagerly anticipated for elucidation of drug action mechanism. Since GPCRs are difficult to crystallize, the 3D structures of these receptors have not yet been determined by X-ray crystallography, except the inactive-state conformation of two proteins. The conformation of them enabled the inactive form of other GPCRs to be modeled by computer-aided homology modeling. However, to date, the active form of GPCRs has not been solved. This paper describes a novel method to predict the 3D structure of an active-state GPCR aiming at molecular docking-based virtual screening using real-coded genetic algorithm (real-coded GA), receptor-ligand docking simulations, and molecular dynamics (MD) simulations. The basic idea of the method is that the MD is first used to calculate an average 3D coordinates of all atoms of a GPCR protein against heat fluctuation on the pico- or nano- second time scale, and then real-coded GA involving receptor-ligand docking simulations functions to determine the rotation angle of each helix as a movement on wider time scale. The method was validated using human leukotriene B4 receptor BLT1 as a sample GPCR. Our study demonstrated that the established evolutionary search for the active state of the leukotriene receptor provided the appropriate 3D structure of the receptor to dock with its agonists.

  17. Modeling Illicit Drug Use Dynamics and Its Optimal Control Analysis

    Directory of Open Access Journals (Sweden)

    Steady Mushayabasa

    2015-01-01

    Full Text Available The global burden of death and disability attributable to illicit drug use, remains a significant threat to public health for both developed and developing nations. This paper presents a new mathematical modeling framework to investigate the effects of illicit drug use in the community. In our model the transmission process is captured as a social “contact” process between the susceptible individuals and illicit drug users. We conduct both epidemic and endemic analysis, with a focus on the threshold dynamics characterized by the basic reproduction number. Using our model, we present illustrative numerical results with a case study in Cape Town, Gauteng, Mpumalanga and Durban communities of South Africa. In addition, the basic model is extended to incorporate time dependent intervention strategies.

  18. The United States Military and the War on Drugs

    National Research Council Canada - National Science Library

    Randolph, David E

    1992-01-01

    The end of the Cold War has brought wrenching changes to the U.S. Armed Forces. At a time when declining budgets and building down are the order of the day, there is one area where the military's role is actually growing: the war on drugs...

  19. Computational modeling of drug transport across the in vitro cornea.

    Science.gov (United States)

    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.

  20. 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 ...

  1. Molecular Modeling: A Powerful Tool for Drug Design and Molecular ...

    Indian Academy of Sciences (India)

    Molecular modeling has become a valuable and essential tool to medicinal chemists in the drug design process. Molecular modeling describes the generation, manipula- tion or representation of three-dimensional structures of molecules and associated physico-chemical properties. It involves a range of computerized ...

  2. Model Checking Dynamic States in GROOVE

    NARCIS (Netherlands)

    Kastenberg, H.; Rensink, Arend; Valmari, A.

    2006-01-01

    Much research has been done in the field of model-checking complex systems (either hardware or software). Approaches that use explicit state modelling mostly use bit vectors to represent the states of such systems. Unfortunately, that kind of representation does not extend smoothly to systems in

  3. Modeling of activity landscapes for drug discovery.

    Science.gov (United States)

    Bajorath, Jürgen

    2012-06-01

    Activity landscapes (ALs) are graphical representations that integrate compound structure and potency relationships. These computer-generated models enable the interactive large-scale analysis of structure-activity relationships (SARs) and complement traditional approaches to study SARs of individual compound series in a qualitative or quantitative manner. A variety of AL designs have been reported. The concept of activity landscapes is introduced and different methodologies to represent 2D or 3D AL representations of large compound data sets are described on the basis of original literature references. Several AL variants and extensions have been generated for special applications in medicinal chemistry. These include, for example, AL views of evolving data sets with constant topology, selectivity landscapes and multi-target ALs, or molecular mechanism and multi-property maps. Furthermore, the applicability domain of the AL concept is discussed including specific requirements for practical utility in medicinal chemistry opportunities for further developments. AL modeling has substantially extended conventional ways to study SARs. The AL concept is inseparable from the notion of activity cliffs that are of high interest in SAR analysis. AL design is an area of active research at the interface between chemoinformatics and medicinal chemistry with potential for further growth. Special emphasis must be put on increasing the usability of AL models for practicing medicinal chemists.

  4. Depoliticising the political: Market solutions and the retreat of Swedish institutional drug treatment from state management.

    Science.gov (United States)

    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.

  5. Toward a normalized clinical drug knowledge base in China-applying the RxNorm model to Chinese clinical drugs.

    Science.gov (United States)

    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

  6. Steady state HNG combustion modeling

    Energy Technology Data Exchange (ETDEWEB)

    Louwers, J.; Gadiot, G.M.H.J.L. [TNO Prins Maurits Lab., Rijswijk (Netherlands); Brewster, M.Q. [Univ. of Illinois, Urbana, IL (United States); Son, S.F. [Los Alamos National Lab., NM (United States); Parr, T.; Hanson-Parr, D. [Naval Air Warfare Center, China Lake, CA (United States)

    1998-04-01

    Two simplified modeling approaches are used to model the combustion of Hydrazinium Nitroformate (HNF, N{sub 2}H{sub 5}-C(NO{sub 2}){sub 3}). The condensed phase is treated by high activation energy asymptotics. The gas phase is treated by two limit cases: the classical high activation energy, and the recently introduced low activation energy approach. This results in simplification of the gas phase energy equation, making an (approximate) analytical solution possible. The results of both models are compared with experimental results of HNF combustion. It is shown that the low activation energy approach yields better agreement with experimental observations (e.g. regression rate and temperature sensitivity), than the high activation energy approach.

  7. Drug use and AIDS: estimating injection prevalence in a rural state.

    Science.gov (United States)

    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.

  8. Atomic level insights into realistic molecular models of dendrimer-drug complexes through MD simulations.

    Science.gov (United States)

    Jain, Vaibhav; Maiti, Prabal K; Bharatam, Prasad V

    2016-09-28

    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(NH 2 ) 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(NH 2 ) 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(NH 2 ) 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

  9. Atomic level insights into realistic molecular models of dendrimer-drug complexes through MD simulations

    Science.gov (United States)

    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

  10. Current advances in mathematical modeling of anti-cancer drug penetration into tumor tissues.

    Science.gov (United States)

    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.

  11. Computational and experimental model of transdermal iontophorethic drug delivery system.

    Science.gov (United States)

    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.

  12. Racism in United States: Drug Legislation and the Trade-Off Behind It

    Science.gov (United States)

    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)

  13. 75 FR 17423 - Memorandum of Understanding Between the Food and Drug Administration, United States Department of...

    Science.gov (United States)

    2010-04-06

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2010-N-0004] [FDA 225-10-0007] Memorandum of Understanding Between the Food and Drug Administration, United States Department of Health and Human Services and the Association of Minority Health Profession Schools, Inc...

  14. Animal models of pancreatic cancer for drug research.

    Science.gov (United States)

    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.

  15. Marijuana, other drugs, and alcohol use by drivers in Washington state : appendices.

    Science.gov (United States)

    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 ...

  16. Marijuana, other drugs, and alcohol use by drivers in Washington State.

    Science.gov (United States)

    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 ...

  17. Modeling of transdermal drug delivery with a microneedle array

    Science.gov (United States)

    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.

  18. Comparing the Medicaid Retrospective Drug Utilization Review Program Cost-Savings Methods Used by State Agencies.

    Science.gov (United States)

    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

  19. Mathematical modeling of multi-drugs therapy: a challenge for determining the optimal combinations of antiviral drugs.

    Science.gov (United States)

    Koizumi, Yoshiki; Iwami, Shingo

    2014-09-25

    In the current era of antiviral drug therapy, combining multiple drugs is a primary approach for improving antiviral effects, reducing the doses of individual drugs, relieving the side effects of strong antiviral drugs, and preventing the emergence of drug-resistant viruses. Although a variety of new drugs have been developed for HIV, HCV and influenza virus, the optimal combinations of multiple drugs are incompletely understood. To optimize the benefits of multi-drugs combinations, we must investigate the interactions between the combined drugs and their target viruses. Mathematical models of viral infection dynamics provide an ideal tool for this purpose. Additionally, whether drug combinations computed by these models are synergistic can be assessed by two prominent drug combination theories, Loewe additivity and Bliss independence. By combining the mathematical modeling of virus dynamics with drug combination theories, we could show the principles by which drug combinations yield a synergistic effect. Here, we describe the theoretical aspects of multi-drugs therapy and discuss their application to antiviral research.

  20. Low temperature fused deposition modeling (FDM) 3D printing of thermolabile drugs.

    Science.gov (United States)

    Kollamaram, Gayathri; Croker, Denise M; Walker, Gavin M; Goyanes, Alvaro; Basit, Abdul W; Gaisford, Simon

    2018-04-26

    Fused deposition modelling (FDM) is the most commonly investigated 3D printing technology for the manufacture of personalized medicines, however, high temperatures associated with 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 8.9 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 to 30 mins. 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 thermal heating, making this technology suitable for drugs with lower melting temperatures. Copyright © 2018. Published by Elsevier B.V.

  1. Understanding anti-tuberculosis drug efficacy: rethinking bacterial populations and how we model them

    Directory of Open Access Journals (Sweden)

    Dimitrios Evangelopoulos

    2015-03-01

    Full Text Available Tuberculosis still remains a global health emergency, claiming 1.5 million lives in 2013. The bacterium responsible for this disease, Mycobacterium tuberculosis (M.tb, has successfully survived within hostile host environments, adapting to immune defence mechanisms, for centuries. This has resulted in a disease that is challenging to treat, requiring lengthy chemotherapy with multi-drug regimens. One explanation for this difficulty in eliminating M.tb bacilli in vivo is the disparate action of antimicrobials on heterogeneous populations of M.tb, where mycobacterial physiological state may influence drug efficacy. In order to develop improved drug combinations that effectively target diverse mycobacterial phenotypes, it is important to understand how such subpopulations of M.tb are formed during human infection. We review here the in vitro and in vivo systems used to model M.tb subpopulations that may persist during drug therapy, and offer aspirations for future research in this field.

  2. Markov State Model of Ion Assembling Process.

    Science.gov (United States)

    Shevchuk, Roman

    2016-05-12

    We study the process of ion assembling in aqueous solution by means of molecular dynamics. In this article, we present a method to study many-particle assembly using the Markov state model formalism. We observed that at NaCl concentration higher than 1.49 mol/kg, the system tends to form a big ionic cluster composed of roughly 70-90% of the total number of ions. Using Markov state models, we estimated the average time needed for the system to make a transition from discorded state to a state with big ionic cluster. Our results suggest that the characteristic time to form an ionic cluster is a negative exponential function of the salt concentration. Moreover, we defined and analyzed three different kinetic states of a single ion particle. These states correspond to a different particle location during nucleation process.

  3. Fed-state gastric media and drug analysis techniques: Current status and points to consider.

    Science.gov (United States)

    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.

  4. The additive damage model: a mathematical model for cellular responses to drug combinations.

    Science.gov (United States)

    Jones, Leslie Braziel; Secomb, Timothy W; Dewhirst, Mark W; El-Kareh, Ardith W

    2014-09-21

    Mathematical models to describe dose-dependent cellular responses to drug combinations are an essential component of computational simulations for predicting therapeutic responses. Here, a new model, the additive damage model, is introduced and tested in cases where varying concentrations of two drugs are applied with a fixed exposure schedule. In the model, cell survival is determined by whether cellular damage, which depends on the concentrations of the drugs, exceeds a lethal threshold, which varies randomly in the cell population with a prescribed statistical distribution. Cellular damage is assumed to be additive, and is expressed as a sum of separate terms for each drug. Each term has a saturable dependence on drug concentration. The model has appropriate behavior over the entire range of drug concentrations, and is predictive, given single-agent dose-response data for each drug. The proposed model is compared with several other models, by testing their ability to fit 24 data sets for platinum-taxane combinations and 21 data sets for various other combinations. The Akaike Information Criterion is used to assess goodness of fit, taking into account the number of unknown parameters in each model. Overall, the additive damage model provides a better fit to the data sets than any previous model. The proposed model provides a basis for computational simulations of therapeutic responses. It predicts responses to drug combinations based on data for each drug acting as a single agent, and can be used as an improved null reference model for assessing synergy in the action of drug combinations. Copyright © 2014 Elsevier Ltd. All rights reserved.

  5. Mathematical models for drug diffusion through the compartments of ...

    African Journals Online (AJOL)

    M.A. Khanday

    2016-07-26

    Jul 26, 2016 ... quadratic shape function.10. Moreover, Khanday and. Najar11,12 established the mathematical models on oxygen transport in biological tissues through capillary bed using both analytical and numerical methods. In this study, we extended the diffusion of drug in blood and tissue using three mathemat-.

  6. Toward a pragmatic migraine model for drug testing

    DEFF Research Database (Denmark)

    Hansen, Emma Katrine; Guo, Song; Ashina, Messoud

    2016-01-01

    BACKGROUND: A model for the testing of novel antimigraine drugs should ideally use healthy volunteers for ease of recruiting. Cilostazol provokes headache in healthy volunteers with some migraine features such as pulsating pain quality and aggravation by physical activity. Therefore, this headach...

  7. Molecular Modeling: A Powerful Tool for Drug Design and Molecular ...

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

  8. Antipsychotic drugs rapidly induce dopamine neuron depolarization block in a developmental rat model of schizophrenia.

    Science.gov (United States)

    Valenti, Ornella; Cifelli, Pierangelo; Gill, Kathryn M; Grace, Anthony A

    2011-08-24

    Repeated administration of antipsychotic drugs to normal rats has been shown to induce a state of dopamine neuron inactivation known as depolarization block, which correlates with the ability of the drugs to exhibit antipsychotic efficacy and extrapyramidal side effects in schizophrenia patients. Nonetheless, in normal rats depolarization block requires weeks of antipsychotic drug administration, whereas schizophrenia patients exhibit initial effects soon after initiating antipsychotic drug treatment. We now report that, in a developmental disruption rat model of schizophrenia [methyl-azoxymethanol acetate (20 mg/kg, i.p.) injected into G17 pregnant female rats, with offspring tested as adults], the extant hyperdopaminergic state combines with the excitatory actions of a first- (haloperidol; 0.6 mg/kg, i.p.) and a second- (sertindole; 2.5 mg/kg, i.p.) generation antipsychotic drug to rapidly induce depolarization block in ventral tegmental area dopamine neurons. Acute injection of either antipsychotic drug induced an immediate reduction in the number of spontaneously active dopamine neurons (cells per electrode track; termed population activity). Repeated administration of either antipsychotic drug for 1, 3, 7, 15, and 21 d continued to reduce dopamine neuron population activity. Both acute and repeated effects on population activity were reversed by acute apomorphine injections, which is consistent with the reversal of dopamine neuron depolarization block. Although this action may account for the effects of D2 antagonist drugs on alleviating psychosis and the lack of development of tolerance in humans, the drugs appear to do so by inducing an offsetting deficit rather than attacking the primary pathology present in schizophrenia.

  9. 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.

  10. The STAMP Software for State Space Models

    Directory of Open Access Journals (Sweden)

    Roy Mendelssohn

    2011-05-01

    Full Text Available This paper reviews the use of STAMP (Structural Time Series Analyser, Modeler and Predictor for modeling time series data using state-space methods with unobserved components. STAMP is a commercial, GUI-based program that runs on Windows, Linux and Macintosh computers as part of the larger OxMetrics System. STAMP can estimate a wide-variety of both univariate and multivariate state-space models, provides a wide array of diagnostics, and has a batch mode capability. The use of STAMP is illustrated for the Nile river data which is analyzed throughout this issue, as well as by modeling a variety of oceanographic and climate related data sets. The analyses of the oceanographic and climate data illustrate the breadth of models available in STAMP, and that state-space methods produce results that provide new insights into important scientific problems.

  11. Steady state modeling of desiccant wheels

    DEFF Research Database (Denmark)

    Bellemo, Lorenzo; Elmegaard, Brian; Kærn, Martin Ryhl

    2014-01-01

    systems. A steady state two-dimensional model is formulated and implemented aiming to obtain good accuracy and short computational times. Comparison with experimental data from the literature shows that the model reproduces the physical behavior of desiccant wheels. Mass diffusion in the desiccant should...

  12. Modeling in the Common Core State Standards

    Science.gov (United States)

    Tam, Kai Chung

    2011-01-01

    The inclusion of modeling and applications into the mathematics curriculum has proven to be a challenging task over the last fifty years. The Common Core State Standards (CCSS) has made mathematical modeling both one of its Standards for Mathematical Practice and one of its Conceptual Categories. This article discusses the need for mathematical…

  13. Multivariable Wind Modeling in State Space

    DEFF Research Database (Denmark)

    Sichani, Mahdi Teimouri; Pedersen, B. J.

    2011-01-01

    -spectral density matrix a frequency response matrix is constructed which determines the turbulence vector as a linear filtration of Gaussian white noise. Finally, an accurate state space modeling method is proposed which allows selection of an appropriate model order, and estimation of a state space model......Turbulence of the incoming wind field is of paramount importance to the dynamic response of wind turbines. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the paper an empirical...... cross-spectral density function for the along-wind turbulence component over the rotor plane is taken as the starting point. The spectrum is spatially discretized in terms of a Hermitian cross-spectral density matrix for the turbulence state vector which turns out not to be positive definite. Since...

  14. Animal models for testing anti-prion drugs.

    Science.gov (United States)

    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.

  15. A Two-Layer Mathematical Modelling of Drug Delivery to Biological Tissues

    Science.gov (United States)

    Chakravarty, Koyel; Dalal, D. C.

    2016-10-01

    Local drug delivery has received much recognition in recent years, yet it is still unpredictable how drug efficacy depends on physicochemical properties and delivery kinetics. The purpose of the current study is to provide a useful mathematical model for drug release from a drug delivery device and consecutive drug transport in biological tissue, thereby aiding the development of new therapeutic drug by a systemic approach. In order to study the complete process, a two-layer spatio-temporal model depicting drug transport between the coupled media is presented. Drug release is described by considering solubilisation dynamics of drug particle, diffusion of the solubilised drug through porous matrix and also some other processes like reversible dissociation / recrystallization, drug particle-receptor binding and internalization phenomena. The model has led to a system of partial differential equations describing the important properties of drug kinetics. This model contributes towards the perception of the roles played by diffusion, mass-transfer, particle binding and internalization parameters.

  16. Impact of Drug Shortages on Health System Pharmacies in the Southeastern United States.

    Science.gov (United States)

    Caulder, Celeste R; Mehta, Brenna; Bookstaver, P Brandon; Sims, LaVetra D; Stevenson, Bill

    2015-04-01

    Drug shortages have become all too common and affect all aspects of the health care delivery system. The increased number of drug shortages has had a negative impact on patient care as well as costly financial implications. This article identifies the current problems and negative outcomes drug shortages have caused and provides a framework for how to best prepare for and combat future shortages. It highlights specific problems faced by health care system pharmacies in the Southeastern United States and the managerial responses to address these shortage situations. A 34-question, multiple-choice survey was distributed to pharmacy directors in North Carolina, South Carolina, Georgia, and Florida. Of 549 surveys distributed, 219 (40%) responses were received. Respondents reported that drug shortages cause 1% to 5% error rates in hospitals and that 60% of the time drug shortages create unsafe conditions for patients and staff. Many of the respondents reported a 300% to 500% markup on medications on the shortage list. Seventy-six percent of institutions have autosubstitutions for drug shortages that have been preapproved by Pharmacy & Therapeutics Committees. The causes of drug shortages are multifaceted, and the safety and financial implications can be costly. In the short term, health care institutions can utilize pharmacists to assist in circumventing the drug shortage problem. The combined efforts of all health care professionals, the US government, manufacturers, and the lay public are necessary to bring awareness and plausible solutions to the drug shortage problems in the long term.

  17. 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.

  18. Zebrafish xenograft models of cancer and metastasis for drug discovery.

    Science.gov (United States)

    Brown, Hannah K; Schiavone, Kristina; Tazzyman, Simon; Heymann, Dominique; Chico, Timothy Ja

    2017-04-01

    Patients with metastatic cancer suffer the highest rate of cancer-related death, but existing animal models of metastasis have disadvantages that limit our ability to understand this process. The zebrafish is increasingly used for cancer modelling, particularly xenografting of human cancer cell lines, and drug discovery, and may provide novel scientific and therapeutic insights. However, this model system remains underexploited. Areas covered: The authors discuss the advantages and disadvantages of the zebrafish xenograft model for the study of cancer, metastasis and drug discovery. They summarise previous work investigating the metastatic cascade, such as tumour-induced angiogenesis, intravasation, extravasation, dissemination and homing, invasion at secondary sites, assessing metastatic potential and evaluation of cancer stem cells in zebrafish. Expert opinion: The practical advantages of zebrafish for basic biological study and drug discovery are indisputable. However, their ability to sufficiently reproduce and predict the behaviour of human cancer and metastasis remains unproven. For this to be resolved, novel mechanisms must to be discovered in zebrafish that are subsequently validated in humans, and for therapeutic interventions that modulate cancer favourably in zebrafish to successfully translate to human clinical studies. In the meantime, more work is required to establish the most informative methods in zebrafish.

  19. Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

    Science.gov (United States)

    Pignatello, R.; Musumeci, T.; Basile, L.; Carbone, C.; Puglisi, G.

    2011-01-01

    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. PMID:21430952

  20. Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development.

    Science.gov (United States)

    Pignatello, R; Musumeci, T; Basile, L; Carbone, C; Puglisi, G

    2011-01-01

    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.

  1. Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

    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.

  2. [Modeling asthma evolution by a multi-state model].

    Science.gov (United States)

    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.

  3. 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...

  4. Tissue Chips to aid drug development and modeling for rare diseases.

    Science.gov (United States)

    Low, Lucie A; Tagle, Danilo A

    2016-01-01

    The technologies used to design, create and use microphysiological systems (MPS, "tissue chips" or "organs-on-chips") have progressed rapidly in the last 5 years, and validation studies of the functional relevance of these platforms to human physiology, and response to drugs for individual model organ systems, are well underway. These studies are paving the way for integrated multi-organ systems that can model diseases and predict drug efficacy and toxicology of multiple organs in real-time, improving the potential for diagnostics and development of novel treatments of rare diseases in the future. This review will briefly summarize the current state of tissue chip research and highlight model systems where these microfabricated (or bioengineered) devices are already being used to screen therapeutics, model disease states, and provide potential treatments in addition to helping elucidate the basic molecular and cellular phenotypes of rare diseases. Microphysiological systems hold great promise and potential for modeling rare disorders, as well as for their potential use to enhance the predictive power of new drug therapeutics, plus potentially increase the statistical power of clinical trials while removing the inherent risks of these trials in rare disease populations.

  5. Cyclodextrins as drug carriers in Pharmaceutical Technology: The state of the art.

    Science.gov (United States)

    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.

  6. An Assessment of Alcohol and Drug Education/Prevention Programs in the United States Army

    Science.gov (United States)

    1973-12-01

    paraphernalia such as exotic pipes, black lights, psychedelic posters, and the like. These elements of the drug culture must be considered when one...methods used were successf-il in curbing hard drug use, and that the benefits outweigh the costs, we recommend that the Army implemeni the program on a...Research ProbI~t • KI•773-3 ,’AN_ ASSESSMENIT OF ALCOHOL AND DRUG - EDUCATIONP/ EVENTIOON PROGRAMS IN THE UNITED STATES ARMY. 0t -.. -’. "--,’- D D

  7. Successful importation of cytarabine into the United States during a critical national drug shortage.

    Science.gov (United States)

    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.

  8. A Systems Dynamic Model for Drug Abuse and Drug-Related Crime in the Western Cape Province of South Africa

    OpenAIRE

    Nyabadza, Farai; Coetzee, Lezanie

    2017-01-01

    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...

  9. COGNITIVE MODELING OF EPISTEMIC MENTAL STATES

    Directory of Open Access Journals (Sweden)

    Yurovitskaya, L.N.

    2017-03-01

    Full Text Available Epistemic states of mind, connected with the cognitive activity of a man, are aimed not only at apprehending the world around us, but also at the process of this apprehension. A very important step on this way is an attempt to model these states and processes in terms of formal logics and semantics, irrespective of the language of cognition. The article presents the idea of how formal logical and linguistic modeling of the process of thinking shows the correlation and the interdependence of semantic units connected with mental activities of human brain. The basic notions of the conceptual field of cognition are presented in the article

  10. A Model of Mental State Transition Network

    Science.gov (United States)

    Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

    Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

  11. 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.

  12. Five-Factor Model personality profiles of drug users.

    Science.gov (United States)

    Terracciano, Antonio; Löckenhoff, Corinna E; Crum, Rosa M; Bienvenu, O Joseph; Costa, Paul T

    2008-04-11

    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. 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. 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. 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.

  13. Modeling of corneal and retinal pharmacokinetics after periocular drug administration.

    Science.gov (United States)

    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.

  14. 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.

  15. Modelling human drug abuse and addiction with dedicated small animal positron emission tomography.

    Science.gov (United States)

    Dalley, Jeffrey W; Fryer, Tim D; Aigbirhio, Franklin I; Brichard, Laurent; Richards, Hugh K; Hong, Young T; Baron, Jean-Claude; Everitt, Barry J; Robbins, Trevor W

    2009-01-01

    Drug addiction is a chronically relapsing brain disorder, which causes substantial harm to the addicted individual and society as a whole. Despite considerable research we still do not understand why some people appear particularly disposed to drug abuse and addiction, nor do we understand how frequently co-morbid brain disorders such as depression and attention-deficit hyperactivity disorder (ADHD) contribute causally to the emergence of addiction-like behaviour. In recent years positron emission tomography (PET) has come of age as a translational neuroimaging technique in the study of drug addiction, ADHD and other psychopathological states in humans. PET provides unparalleled quantitative assessment of the spatial distribution of radiolabelled molecules in the brain and because it is non-invasive permits longitudinal assessment of physiological parameters such as binding potential in the same subject over extended periods of time. However, whilst there are a burgeoning number of human PET experiments in ADHD and drug addiction there is presently a paucity of PET imaging studies in animals despite enormous advances in our understanding of the neurobiology of these disorders based on sophisticated animal models. This article highlights recent examples of successful cross-species convergence of findings from PET studies in the context of drug addiction and ADHD and identifies how small animal PET can more effectively be used to model complex psychiatric disorders involving at their core impaired behavioural self-control.

  16. Pharmacokinetic properties and in silico ADME modeling in drug discovery.

    Science.gov (United States)

    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.

  17. Modeling Human Nonalcoholic Steatohepatitis-Associated Changes in Drug Transporter Expression Using Experimental Rodent Models

    OpenAIRE

    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...

  18. Multimedia Mapping using Continuous State Space Models

    DEFF Research Database (Denmark)

    Lehn-Schiøler, Tue

    2004-01-01

    In this paper a system that transforms speech waveforms to animated faces are proposed. The system relies on continuous state space models to perform the mapping, this makes it possible to ensure video with no sudden jumps and allows continuous control of the parameters in 'face space'. Simulatio...

  19. What Characterise the Nordic Welfare State Model

    DEFF Research Database (Denmark)

    Greve, Bent

    2007-01-01

    The main distinctive characteristics of the Nordic welfare states are presented. These include full employment, high degree of equality, a high level of taxes and public sector spending. The Nordic countries are compared to other European countries. The conclusion being that the Nordic Model...

  20. Pharmacists' advancing roles in drug and disease management: a review of states' legislation.

    Science.gov (United States)

    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.

  1. Mathematical modeling of coupled drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls

    KAUST Repository

    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.

  2. Computational models for predicting drug responses in cancer research.

    Science.gov (United States)

    Azuaje, Francisco

    2017-09-01

    The computational prediction of drug responses based on the analysis of multiple types of genome-wide molecular data is vital for accomplishing the promise of precision medicine in oncology. This will benefit cancer patients by matching their tumor characteristics to the most effective therapy available. As larger and more diverse layers of patient-related data become available, further demands for new bioinformatics approaches and expertise will arise. This article reviews key strategies, resources and techniques for the prediction of drug sensitivity in cell lines and patient-derived samples. It discusses major advances and challenges associated with the different model development steps. This review highlights major trends in this area, and will assist researchers in the assessment of recent progress and in the selection of approaches to emerging applications in oncology. © The Author 2016. Published by Oxford University Press.

  3. Commercial importation of prescription drugs in the United States: short-run implications.

    Science.gov (United States)

    Danzon, Patricia M; Johnson, Scott J; Long, Genia; Furukawa, Michael F

    2011-04-01

    The option of legalizing the commercial importation of prescription drugs is of continued policy interest as a way to reduce U.S. drug spending. Using IMS data, we estimate potential savings from commercial drug importation under assumptions about percentage of drugs likely to attract imports; potential supply from foreign countries; and share of savings passed on to payers. Our base case estimate is that $1.7 billion per year, or 0.6 percent of total drug spending, would be saved by payers; sensitivity analyses range from 0.2 to 2.5 percent under plausible assumptions and up to 17.4 percent under unrealistic assumptions about unlimited foreign supply, costless trade, and zero profits for intermediaries. Estimated savings to payers are less than the average price differentials between the United States and foreign countries because proposed legislation exempts certain drugs from importation; foreign markets are small relative to the United States; regulatory and other constraints may limit the volume of exports; trade is costly; and intermediaries will retain some savings. Although savings to U.S. payers/consumers would likely be small and have minimal impact on total U.S. health care spending, costs to other countries could be significant, due to reduced access and possibly higher prices. In the long run, reduced investment in R&D could adversely affect consumers globally.

  4. Drug use and service utilization among Hispanics in the United States.

    Science.gov (United States)

    Mancini, Michael A; Salas-Wright, Christopher P; Vaughn, Michael G

    2015-11-01

    To examine illicit drug use and service utilization patterns of US-born and foreign-born Hispanics in the United States. Hispanic respondents 18 years and older in the NESARC were categorized as being of Mexican (n = 3,556), Puerto Rican (n = 785), Cuban (n = 346), Central American (n = 513), or South American (n = 381) origin. We examined lifetime prevalence of drug use and substance abuse treatment utilization patterns for US-born and Hispanic immigrants across subgroups. Lifetime prevalence of drug use was greater among US-born Hispanics than Hispanic immigrants after controlling for age, gender, income, education, urbanicity, parental history of drug use problems and lifetime DSM-IV mood/anxiety disorders. Both US-born and immigrant Hispanic drug users were less likely than non-Hispanic white drug users to have utilized any form of substance abuse treatment (US-born AOR = 0.89, immigrant AOR = 0.64) and more likely to have utilized family or social services (US-born AOR = 1.17, immigrant AOR = 1.19). Compared to US-born Hispanic drug users, Hispanic immigrant drug users were less likely to have used any form of substance abuse treatment (AOR = 0.81) and were more likely to have utilized family or social services (AOR = 1.22). Strategies to increase engagement and retention of Hispanic drug users in substance abuse treatment include increasing access to linguistically and culturally competent programs that address unmet family and social needs. Further studies examining differences in drug use and service utilization patterns within Hispanic subgroups are needed.

  5. Drug Release Modeling from a Novel Temperature-responsive Polymeric System

    Directory of Open Access Journals (Sweden)

    M. Siroos Azar

    2007-08-01

    Full Text Available Nowadays, environment-sensitive smart drug delivery systems have found diverse applications in pharmaceutical science and technology. These systems can respond to the environment stimuli such as temperature, pressure, pH, light, electrical and magnetical fields and etc. They can release the proper amount of drug in human body. Among these systems, special attention and much research works have been devoted to temperature responsive systems. Smart polymeric materials and hydrogels are widely used in production of temperature responsive systems. The temperatureresponsive polymeric materials and their based smart drug delivery systems are not just responsive to temperature, as other stimuli may induce them as well. Therefore, in practical cases, their performances may be disordered and the drug release may not occur in an anticipated manner. Furthermore, the mathematical relations of drug release in these systems are very complicated. Therefore, in this work, a novel temperature responsive smart drug deliverysystem is introduced in which the drug release would only be a function of temperature and its mathematical relations are also considerably simple. This system is composed of three individual layers. The modeling of this systemis performed by analyzing the heat and mass transfer equations at pseudo-steady state and the effects of system parameters on the performance of the system are investigated. The obtained results show that the performance of the system is drastically related to the types of materials of the system and also their physical and chemical properties. By using the obtained results in this work, we can design the temperature responsive smart drug delivery systems and optimize their performance in practical cases.

  6. State-of-the-art technology in modern computer-aided drug design.

    Science.gov (United States)

    Dalkas, Georgios A; Vlachakis, Dimitrios; Tsagkrasoulis, Dimosthenis; Kastania, Anastasia; Kossida, Sophia

    2013-11-01

    The quest for small drug-like compounds that selectively inhibit the function of biological targets has always been a major focus in the pharmaceutical industry and in academia as well. High-throughput screening of compound libraries requires time, cost and resources. Therefore, the use of alternative methods is necessary for facilitating lead discovery. Computational techniques that dock small molecules into macromolecular targets and predict the affinity and activity of the small molecule are widely used in drug design and discovery, and have become an integral part of the industrial and academic research. In this review, we present an overview of some state-of-the-art technologies in modern drug design that have been developed for expediting the search for novel drug candidates.

  7. Modern state of the assortment drugs for the treatment of vaginal candidosis

    Directory of Open Access Journals (Sweden)

    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

  8. Primary drug resistance among pulmonary treatment-naïve tuberculosis patients in Amazonas State, Brazil.

    Science.gov (United States)

    da Silva Garrido, M; Ramasawmy, R; Perez-Porcuna, T M; Zaranza, E; Chrusciak Talhari, A; Martinez-Espinosa, F E; Bührer-Sékula, S

    2014-05-01

    Multidrug-resistant tuberculosis (MDR-TB) is the main indicator of previous treatment in tuberculosis (TB) patients. MDR-TB among treatment-naïve patients indicates infection with drug-resistant Mycobacterium tuberculosis strains, and such cases are considered primary drug-resistant cases. To estimate the prevalence of drug resistance in pulmonary TB (PTB) treatment-naïve patients and to identify the socio-demographic and clinical characteristics of the resistant population. A total of 205 treatment-naïve PTB patients from Manaus, Amazonas State, Brazil, were enrolled. Drug susceptibility testing (DST) was performed on all positive mycobacterial cultures using the 1% proportion method. Positive M. tuberculosis cultures were obtained from only 175 patients for DST. The prevalence of primary MDR-TB was 1.7% (3/175); 14.3% (25/175) of the cultures presented resistance to at least one of the drugs. Resistance to streptomycin, isoniazid, rifampicin and ethambutol was respectively 8.6%, 6.9%, 3.4% and 2.3%. An association between TB patients with resistance to more than one drug and known previous household contact with a TB patient was observed (P= 0.008, OR 6.7, 95%CI 1.2-67.3). Although the prevalence of primary MDR-TB currently is relatively low, it may become a major public health problem if tailored treatment is not provided, as resistance to more than one drug is significantly associated with household contact.

  9. Prescription Opioid Usage and Abuse Relationships: An Evaluation of State Prescription Drug Monitoring Program Efficacy

    OpenAIRE

    Richard M. Reisman; Pareen J. Shenoy; Adam J. Atherly; Christopher R. Flowers

    2009-01-01

    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.Des...

  10. Analysis of West African Drug Trafficking: The Dynamics of Interdiction and State Capacity

    Science.gov (United States)

    2011-03-01

    Fowler, “The International Narcotics Trade: Can It Be Stopped By Interdiction,” Journal of Policy Modeling, 18, no. 3, (1996): 262; Van de Velde ...2005): 429-447. For the roots of cocaine and heroin trafficking see: Henry Bernstein, “Ghana’s Drug Economy: Some Preliminary Data.” Review of...Bernstein, Henry . “Ghana’s Drug Economy: Some Preliminary Data.” Review of African Political Economy 26, no. 79, Africa and the Drugs Trade (March 1999

  11. Competing States in the t-J Model: Uniform d-Wave State versus Stripe State versus Stripe State

    NARCIS (Netherlands)

    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

  12. Scaling predictive modeling in drug development with cloud computing.

    Science.gov (United States)

    Moghadam, Behrooz Torabi; Alvarsson, Jonathan; Holm, Marcus; Eklund, Martin; Carlsson, Lars; Spjuth, Ola

    2015-01-26

    Growing data sets with increased time for analysis is hampering predictive modeling in drug discovery. Model building can be carried out on high-performance computer clusters, but these can be expensive to purchase and maintain. We have evaluated ligand-based modeling on cloud computing resources where computations are parallelized and run on the Amazon Elastic Cloud. We trained models on open data sets of varying sizes for the end points logP and Ames mutagenicity and compare with model building parallelized on a traditional high-performance computing cluster. We show that while high-performance computing results in faster model building, the use of cloud computing resources is feasible for large data sets and scales well within cloud instances. An additional advantage of cloud computing is that the costs of predictive models can be easily quantified, and a choice can be made between speed and economy. The easy access to computational resources with no up-front investments makes cloud computing an attractive alternative for scientists, especially for those without access to a supercomputer, and our study shows that it enables cost-efficient modeling of large data sets on demand within reasonable time.

  13. Physiologically Based Absorption Modeling to Impact Biopharmaceutics and Formulation Strategies in Drug Development-Industry Case Studies.

    Science.gov (United States)

    Kesisoglou, Filippos; Chung, John; van Asperen, Judith; Heimbach, Tycho

    2016-09-01

    In recent years, there has been a significant increase in use of physiologically based pharmacokinetic models in drug development and regulatory applications. Although most of the published examples have focused on aspects such as first-in-human (FIH) dose predictions or drug-drug interactions, several publications have highlighted the application of these models in the biopharmaceutics field and their use to inform formulation development. In this report, we present 5 case studies of use of such models in this biopharmaceutics/formulation space across different pharmaceutical companies. The case studies cover different aspects of biopharmaceutics or formulation questions including (1) prediction of absorption prior to FIH studies; (2) optimization of formulation and dissolution method post-FIH data; (3) early exploration of a modified-release formulation; (4) addressing bridging questions for late-stage formulation changes; and (5) prediction of pharmacokinetics in the fed state for a Biopharmaceutics Classification System class I drug with fasted state data. The discussion of the case studies focuses on how such models can facilitate decisions and biopharmaceutic understanding of drug candidates and the opportunities for increased use and acceptance of such models in drug development and regulatory interactions. Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

  14. Anti-Drug Abuse Strategy Report. State of New York. 1990 Update.

    Science.gov (United States)

    New York Governor's Office, Albany. Statewide Anti-Drug Abuse Council.

    This annual report from the Statewide Anti-Drug Abuse Council of New York proposes strategies for the coming year. Ongoing support for the state and local law enforcement efforts is reaffirmed as a vital component of the strategy. The council promotes a strengthening of their commitment and focus on severely impacted populations, integration of…

  15. Alcohol involvement in opioid pain reliever and benzodiazepine drug abuse-related emergency department visits and drug-related deaths - United States, 2010.

    Science.gov (United States)

    Jones, Christopher M; Paulozzi, Leonard J; Mack, Karin A

    2014-10-10

    The abuse of prescription drugs has led to a significant increase in emergency department (ED) visits and drug-related deaths over the past decade. Opioid pain relievers (OPRs) and benzodiazepines are the prescription drugs most commonly involved in these events. Excessive alcohol consumption also accounts for a significant health burden and is common among groups that report high rates of prescription drug abuse. When taken with OPRs or benzodiazepines, alcohol increases central nervous system depression and the risk for overdose. Data describing alcohol involvement in OPR or benzodiazepine abuse are limited. To quantify alcohol involvement in OPR and benzodiazepine abuse and drug-related deaths and to inform prevention efforts, the Food and Drug Administration (FDA) and CDC analyzed 2010 data for drug abuse-related ED visits in the United States and drug-related deaths that involved OPRs and alcohol or benzodiazepines and alcohol in 13 states. The analyses showed alcohol was involved in 18.5% of OPR and 27.2% of benzodiazepine drug abuse-related ED visits and 22.1% of OPR and 21.4% of benzodiazepine drug-related deaths. These findings indicate that alcohol plays a significant role in OPR and benzodiazepine abuse. Interventions to reduce the abuse of alcohol and these drugs alone and in combination are needed.

  16. Prescription Opioid Usage and Abuse Relationships: An Evaluation of State Prescription Drug Monitoring Program Efficacy

    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.

  17. Prescription Opioid Usage and Abuse Relationships: An Evaluation of State Prescription Drug Monitoring Program Efficacy

    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.

  18. Effect of ingested lipids on drug dissolution and release with concurrent digestion: a modeling approach

    Science.gov (United States)

    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

  19. MR imaging of model drug distribution in simulated vitreous

    Directory of Open Access Journals (Sweden)

    Stein Sandra

    2015-09-01

    Full Text Available The in vitro and in vivo characterization of intravitreal injections plays an important role in developing innovative therapy approaches. Using the established vitreous model (VM and eye movement system (EyeMoS the distribution of contrast agents with different molecular weight was studied in vitro. The impact of the simulated age-related vitreal liquefaction (VL on drug distribution in VM was examined either with injection through the gel phase or through the liquid phase. For comparison the distribution was studied ex vivo in the porcine vitreous. The studies were performed in a magnetic resonance (MR scanner. As expected, with increasing molecular weight the diffusion velocity and the visual distribution of the injected substances decreased. Similar drug distribution was observed in VM and in porcine eye. VL causes enhanced convective flow and faster distribution in VM. Confirming the importance of the injection technique in progress of VL, injection through gelatinous phase caused faster distribution into peripheral regions of the VM than following injection through liquefied phase. VM and MR scanner in combination present a new approach for the in vitro characterization of drug release and distribution of intravitreal dosage forms.

  20. Stigma, sexual risks, and the war on drugs: Examining drug policy and HIV/AIDS inequities among African Americans using the Drug War HIV/AIDS Inequities Model.

    Science.gov (United States)

    Kerr, Jelani; Jackson, Trinidad

    2016-11-01

    The relationship between drug policy and HIV vulnerability is well documented. However, little research examines the links between racial/ethnic HIV disparities via the Drug War, sexual risk, and stigma. The Drug War HIV/AIDS Inequities Model has been developed to address this dearth. This model contends that inequitable policing and sentencing promotes sexual risks, resource deprivation, and ultimately greater HIV risk for African-Americans. The Drug War also socially marginalizes African Americans and compounds stigma for incarcerated and formerly incarcerated persons living with HIV/AIDS. This marginalization has implications for sexual risk-taking, access to health-promoting resources, and continuum of care participation. The Drug War HIV/AIDS Inequities Model may help illuminate mechanisms that promote increased HIV vulnerability as well as inform structural intervention development and targeting to address racial/ethnic disparities. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. Sufficient conditions for optimality for a mathematical model of drug treatment with pharmacodynamics

    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.

  2. Architecture of the Product State Model Environment

    DEFF Research Database (Denmark)

    Holm Larsen, Michael; Lynggaard, Hans Jørgen B.

    2003-01-01

    This paper addresses the issue of using product models to support product lifecycle activities withparticular focus on the production phase. The motivation of the research is that products are producedmore costly and with longer lead-time than necessary.The paper provides a review of product...... modelling technologies and approaches, and the overallarchitecture for the Product State Model (PSM) Environment as a basis for quality monitoring.Especially, the paper focuses on the circumstances prevailing in a one-of-a-kind manufacturingenvironment like the shipbuilding industry, where product modelling...... technologies already haveproved their worth in the design and engineering phases of shipbuilding and in the operation phase.However, the handling of product information on the shop floor is not yet equally developed.The paper reports from the Brite-Euram project (No. BE97-4510) QualiGlobe focusing...

  3. A Dual-Process Discrete-Time Survival Analysis Model: Application to the Gateway Drug Hypothesis

    Science.gov (United States)

    Malone, Patrick S.; Lamis, Dorian A.; Masyn, Katherine E.; Northrup, Thomas F.

    2010-01-01

    The gateway drug model is a popular conceptualization of a progression most substance users are hypothesized to follow as they try different legal and illegal drugs. Most forms of the gateway hypothesis are that "softer" drugs lead to "harder," illicit drugs. However, the gateway hypothesis has been notably difficult to…

  4. Teaching Note--No Peace without Justice: Addressing the United States' War on Drugs in Social Work Education

    Science.gov (United States)

    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…

  5. Martingale models for quantum state reduction

    Energy Technology Data Exchange (ETDEWEB)

    Adler, S.L.; Brun, T.A. [Institute for Advanced Study, Princeton, NJ (United States)]. E-mails: adler@ias.edu; tbrun@ias.edu; Brody, D.C. [Blackett Laboratory, Imperial College, London (United Kingdom)]. E-mail: dorje@ic.ac.uk; Hughston, L.P. [Department of Mathematics, King' s College, Strand, London (United Kingdom)]. E-mail: lane.hughston@kcl.ac.uk

    2001-10-26

    Stochastic models for quantum state reduction give rise to statistical laws that are in most respects in agreement with those of quantum measurement theory. Here we examine the correspondence of the two theories in detail, making a systematic use of the methods of martingale theory. An analysis is carried out to determine the magnitude of the fluctuations experienced by the expectation of the observable during the course of the reduction process and an upper bound is established for the ensemble average of the greatest fluctuations incurred. We consider the general projection postulate of Lueders applicable in the case of a possibly degenerate eigenvalue spectrum, and derive this result rigorously from the underlying stochastic dynamics for state reduction in the case of both a pure and a mixed initial state. We also analyse the associated Lindblad equation for the evolution of the density matrix, and obtain an exact time-dependent solution for the state reduction that explicitly exhibits the transition from a general initial density matrix to the Lueders density matrix. Finally, we apply Girsanov's theorem to derive a set of simple formulae for the dynamics of the state in terms of a family of geometric Brownian motions, thereby constructing an explicit unravelling of the Lindblad equation. (author)

  6. Prescription Drug Utilization and Reimbursement Increased Following State Medicaid Expansion in 2014.

    Science.gov (United States)

    Mahendraratnam, Nirosha; Dusetzina, Stacie B; Farley, Joel F

    2017-03-01

    The Affordable Care Act (ACA) expanded health care and medication insurance coverage through Medicaid expansion in select states. Expansion has the potential to increase the availability of health services to patients, including prescription medications. However, limited studies have examined how expansion affected prescription drug utilization and reimbursement. To compare prescription drug utilization (number of prescriptions filled) and reimbursement trends between states that did and did not expand Medicaid coverage in 2014, while accounting for known effects of expansion on Medicaid enrollment. We conducted a comparative interrupted time series using retrospective Medicaid state drug utilization data from 2011 to 2014. After inclusion/exclusion criteria, 8 states that expanded Medicaid in 2014 and 10 states that did not expand Medicaid were studied. Primary outcomes were changes in quarterly prescription drug utilization and quarterly total prescription drug reimbursement before and after expansion. To account for increases in enrollment in expansion states, secondary outcomes were per-member-per-quarter (PMPQ) utilization and reimbursement before and after expansion. Expansion states experienced a 1.4 million prescriptions per quarter and $163 million per quarter increase in utilization and reimbursement above the change in rates observed in nonexpansion states after expansion (P quarter preceding expansion. Expansion and nonexpansion states experienced significant drops in PMPQ prescriptions immediately after expansion (P Economics and Outcomes Research Pre-doctoral Fellow at Bristol-Myers Squibb and previously provided advisory services to public and private sector clients while employed at Avalere Health, an Inovalon Company, as well as completed an internship at Genentech, a member of the Roche Group. Farley and Dusetzina have no conflicts of interest to report. Preliminary results of this study were presented at the 2016 International Society for

  7. A theory of drug tolerance and dependence II: the mathematical model.

    Science.gov (United States)

    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.

  8. Opportunities for AIDS prevention in a rural state in criminal justice and drug treatment settings.

    Science.gov (United States)

    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.

  9. DFT application for chlorin derivatives photosensitizer drugs modeling

    Science.gov (United States)

    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.

  10. A Systems Dynamic Model for Drug Abuse and Drug-Related Crime in the Western Cape Province of South Africa

    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.

  11. Multiple model predictive control for optimal drug administration of mixed immunotherapy and chemotherapy of tumours.

    Science.gov (United States)

    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.

  12. Quantitative modeling of selective lysosomal targeting for drug design

    DEFF Research Database (Denmark)

    Trapp, Stefan; Rosania, G.; Horobin, R.W.

    2008-01-01

    Lysosomes are acidic organelles and are involved in various diseases, the most prominent is malaria. Accumulation of molecules in the cell by diffusion from the external solution into cytosol, lysosome and mitochondrium was calculated with the Fick–Nernst–Planck equation. The cell model considers...... the diffusion of neutral and ionic molecules across biomembranes, protonation to mono- or bivalent ions, adsorption to lipids, and electrical attraction or repulsion. Based on simulation results, high and selective accumulation in lysosomes was found for weak mono- and bivalent bases with intermediate to high...... 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...

  13. A developmental etiological model for drug abuse in men.

    Science.gov (United States)

    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.

  14. Potential drug-drug interactions among elderly patients on anti-hypertensive medications in two tertiary healthcare facilities in Ekiti State, South-West Nigeria

    Directory of Open Access Journals (Sweden)

    Joseph Olusesan Fadare

    2016-01-01

    Full Text Available Introduction: Drug-drug interactions remain a major cause of adverse drug reactions with great consequences such as increased morbidity and increased healthcare cost. In elderly patients with systemic hypertension, there is a tendency for them to be prescribed multiple medications and this may expose them to some drug-drug interactions (DDIs especially in the context of physiological changes of ageing. The objective of this study was to evaluate potential drug-drug interaction among some Nigerian elderly hypertension. Methods: A cross-sectional study involving elderly hypertensive patients attending the general outpatient clinic of two tertiary healthcare facilities located in Ekiti State, South-West Nigeria. The information collected from the patients′ medical records included their ages, gender, diagnosis and list of prescribed anti-hypertensive medications. Potential drug-drug interactions were checked for using the Multi-Drug Interaction Checker (Medscape Reference and Epocrates Drug Interaction Checker (San Mateo CA, USA. Results: A total of 350 elderly patients attended the clinics during the study period of which 208 (59.4% hypertensive patients were identified and their records used for analysis. The fixed-dose combination drug Moduretic® (Amiloride /Hydrochlorothiazide-25.7% was the most commonly prescribed antihypertensive followed by Lisinopril (16.6%, Amlodipine (13.2% and Nifedipine (12.6%. The anti-platelet Acetyl-salicylic acid (ASA was prescribed for 100 (48.1% patients and represented 19.8% of all prescribed medications. A total of 231 potential DDIs were found among the patients giving a mean of 1.3 interactions per patient. The most common identified drug pairs with potential interactions were ACE inhibitors - Amiloride, followed by ACE inhibitors - Hydrochlorothiazide, ACE inhibitors - ASA and ARB - Amiloride. Conclusion: Potential drug-drug interactions, though common in this study comprised mainly of minor and moderate

  15. States With Prescription Drug Monitoring Mandates Saw A Reduction In Opioids Prescribed To Medicaid Enrollees.

    Science.gov (United States)

    Wen, Hefei; Schackman, Bruce R; Aden, Brandon; Bao, Yuhua

    2017-04-01

    Prescription drug monitoring programs are promising tools to use in addressing the prescription opioid epidemic, yet prescribers' participation in these state-run programs remained low as of 2014. Statutory mandates for prescribers to register with their state's program, use it, or both are believed to be effective tools to realize the programs' full potential. Our analysis of aggregate Medicaid drug utilization data indicates that state mandates for prescriber registration or use adopted in 2011-14 were associated with a reduction of 9-10 percent in population-adjusted numbers of Schedule II opioid prescriptions received by Medicaid enrollees and amounts of Medicaid spending on these prescriptions. This effect was largely associated with mandates of registration, which were comprehensive in all adopting states, and not with mandates of use, which were largely limited in scope or strength before 2015. Our findings support the use of mandates of registration in prescription drug monitoring programs as an effective and relatively low-cost policy. Future research should further assess the value of strong mandates of use to ensure safer and more appropriate prescribing of opioids. Project HOPE—The People-to-People Health Foundation, Inc.

  16. Parameter and State Estimator for State Space Models

    Directory of Open Access Journals (Sweden)

    Ruifeng Ding

    2014-01-01

    Full Text Available This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

  17. Parameter and state estimator for state space models.

    Science.gov (United States)

    Ding, Ruifeng; Zhuang, Linfan

    2014-01-01

    This paper proposes a parameter and state estimator for canonical state space systems from measured input-output data. The key is to solve the system state from the state equation and to substitute it into the output equation, eliminating the state variables, and the resulting equation contains only the system inputs and outputs, and to derive a least squares parameter identification algorithm. Furthermore, the system states are computed from the estimated parameters and the input-output data. Convergence analysis using the martingale convergence theorem indicates that the parameter estimates converge to their true values. Finally, an illustrative example is provided to show that the proposed algorithm is effective.

  18. A three states sleep-waking model

    Energy Technology Data Exchange (ETDEWEB)

    Comte, J.C. [Laboratoire de Physiopathologie des Reseaux Neuronaux du Cycle Veille-Sommeil, UMR 5167, CNRS/Universite Claude Bernard Lyon1, Faculte de Medecine RTH Laennec 7, Rue Guillaume Paradin 69372 Lyon Cedex 08 (France)]. E-mail: comtejc@gmail.com; Schatzman, M. [MAPLY, Laboratoire de Mathematiques appliquees de Lyon, UMR5585, CNRS/Universite Claude Bernard Lyon1, 21, Avenue Claude Bernard, 69622 Villeurbanne Cedex (France); Ravassard, P. [Laboratoire de Physiopathologie des Reseaux Neuronaux du Cycle Veille-Sommeil, UMR 5167, CNRS/Universite Claude Bernard Lyon1, Faculte de Medecine RTH Laennec 7, Rue Guillaume Paradin 69372 Lyon Cedex 08 (France); Luppi, P.H. [Laboratoire de Physiopathologie des Reseaux Neuronaux du Cycle Veille-Sommeil, UMR 5167, CNRS/Universite Claude Bernard Lyon1, Faculte de Medecine RTH Laennec 7, Rue Guillaume Paradin 69372 Lyon Cedex 08 (France); Salin, P.A. [Laboratoire de Physiopathologie des Reseaux Neuronaux du Cycle Veille-Sommeil, UMR 5167, CNRS/Universite Claude Bernard Lyon1, Faculte de Medecine RTH Laennec 7, Rue Guillaume Paradin 69372 Lyon Cedex 08 (France)

    2006-08-15

    The mechanisms underlying the sleep-states periodicity in animals are a mystery of biology. Recent studies identified a new neuronal population activated during the slow wave sleep (SWS) in the ventral lateral preoptic area of the hypothalamus. Interactions between this neuronal population and the others populations implicated in the vigilance states (paradoxical sleep (PS) and wake (W)) dynamics are not determined. Thus, we propose here a sleep-waking theoretical model that depicts the potential interactions between the neuronal populations responsible for the three vigilance states. First, we pooled data from previous papers regarding the neuronal populations firing rate time course and characterized statistically the experimental hypnograms. Then, we constructed a nonlinear differential equations system describing the neuronal populations activity time course. A simple rule playing the firing threshold role applied to the model allows to construct a theoretical hypnogram. A random modulation of the neuronal activity, shows that theoretical hypnograms present a dynamics close to the experimental observations. Furthermore, we show that the wake promoting neurons activity can predict the next SWS episode duration.

  19. A three states sleep-waking model

    International Nuclear Information System (INIS)

    Comte, J.C.; Schatzman, M.; Ravassard, P.; Luppi, P.H.; Salin, P.A.

    2006-01-01

    The mechanisms underlying the sleep-states periodicity in animals are a mystery of biology. Recent studies identified a new neuronal population activated during the slow wave sleep (SWS) in the ventral lateral preoptic area of the hypothalamus. Interactions between this neuronal population and the others populations implicated in the vigilance states (paradoxical sleep (PS) and wake (W)) dynamics are not determined. Thus, we propose here a sleep-waking theoretical model that depicts the potential interactions between the neuronal populations responsible for the three vigilance states. First, we pooled data from previous papers regarding the neuronal populations firing rate time course and characterized statistically the experimental hypnograms. Then, we constructed a nonlinear differential equations system describing the neuronal populations activity time course. A simple rule playing the firing threshold role applied to the model allows to construct a theoretical hypnogram. A random modulation of the neuronal activity, shows that theoretical hypnograms present a dynamics close to the experimental observations. Furthermore, we show that the wake promoting neurons activity can predict the next SWS episode duration

  20. “Hare Krishna vs. Shiva Shiva”: Swami Agehananda Bharati, Drugs, and the Mystical State in Hindusim

    Directory of Open Access Journals (Sweden)

    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.

  1. Old and new therapeutics for Rheumatoid Arthritis: in vivo models and drug development

    DEFF Research Database (Denmark)

    Sardar, Samra; Andersson, Åsa

    2016-01-01

    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...

  2. Cost-effectiveness of Drugs to Treat Relapsed/Refractory Multiple Myeloma in the United States.

    Science.gov (United States)

    Carlson, Josh J; Guzauskas, Gregory F; Chapman, Richard H; Synnott, Patricia G; Liu, Shanshan; Russo, Elizabeth T; Pearson, Steven D; Brouwer, Elizabeth D; Ollendorf, Daniel A

    2018-01-01

    New 3-drug regimens have been developed and approved to treat multiple myeloma (MM). The absence of direct comparative data and the high cost of treatment support the need to assess the relative clinical and economic outcomes across all approved regimens. To evaluate the cost-effectiveness of treatments for relapsed and/or refractory MM from a U.S. health system perspective. We developed a partition survival model with 3 health states (progression-free, progression, and death) to evaluate the following regimens: carfilzomib (CFZ), elotuzumab (ELO), ixazomib (IX), daratumumab (DAR), and panobinostat (PAN) in combination with lenalidomide (LEN) or bortezomib (BOR) plus dexamethasone (DEX) in the second and/or third line of therapy. To estimate relative treatment effects, we developed a network meta-analysis and applied progression-free survival hazard ratios to baseline parametric progression-free survival functions derived from pooled data on LEN+DEX. We estimated overall survival using data on the relationship between progression-free survival and overall survival from a large meta-analysis of MM patients. Modeled costs included those related to drug treatment, administration, monitoring, adverse events, and progression. Utilities were from publicly available data and manufacturer data, if published sources were unavailable. Model results showed that regimens containing DAR yielded the highest expected life years (DAR range: 6.71-7.38 vs. non-DAR range: 3.25-5.27) and quality-adjusted life-years (QALY; DAR range: 4.38-5.44 vs. non-DAR range: 2.04-3.46), with DAR+BOR+DEX (second line) and PAN+BOR+DEX (third line) as the most cost-effective options (incremental cost-effectiveness ratio: $50,700 and cost saving, respectively). The applicability of the PAN+BOR+DEX result may be challenging, however, because of ongoing toxicity concerns. In the probabilistic sensitivity analysis, second-line DAR+BOR+DEX and third-line PAN+BOR+DEX had an 89% and 87% probability of being

  3. Generalised linear models for correlated pseudo-observations, with applications to multi-state models

    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...

  4. Heroin delay discounting: Modulation by pharmacological state, drug-use impulsivity, and intelligence.

    Science.gov (United States)

    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).

  5. A Critical Subset Model Provides a Conceptual Basis for the High Antiviral Activity of Major HIV Drugs**

    Science.gov (United States)

    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

  6. The continuum shell-model neutron states of Pb

    Indian Academy of Sciences (India)

    model states with the collective vibrational states from giant resonances. The particle-vibration coupling model can be applied to understand the spreading pattern of the shell-model states lying in continuum region. The single-particle states are ...

  7. Design and Characterization of a Silk-Fibroin-Based Drug Delivery Platform Using Naproxen as a Model Drug

    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.

  8. Skin models for the testing of transdermal drugs

    Directory of Open Access Journals (Sweden)

    Abd E

    2016-10-01

    Full Text Available Eman Abd,1 Shereen A Yousef,1 Michael N Pastore,2 Krishna Telaprolu,1 Yousuf H Mohammed,1 Sarika Namjoshi,1 Jeffrey E Grice,1 Michael S Roberts1,2 1Translational Research Institute, School of Medicine, University of Queensland, Brisbane, 2School of Pharmacy and Medical Sciences, University of South Australia, Adelaide, Australia Abstract: The assessment of percutaneous permeation of molecules is a key step in the evaluation of dermal or transdermal delivery systems. If the drugs are intended for delivery to humans, the most appropriate setting in which to do the assessment is the in vivo human. However, this may not be possible for ethical, practical, or economic reasons, particularly in the early phases of development. It is thus necessary to find alternative methods using accessible and reproducible surrogates for in vivo human skin. A range of models has been developed, including ex vivo human skin, usually obtained from cadavers or plastic surgery patients, ex vivo animal skin, and artificial or reconstructed skin models. Increasingly, largely driven by regulatory authorities and industry, there is a focus on developing standardized techniques and protocols. With this comes the need to demonstrate that the surrogate models produce results that correlate with those from in vivo human studies and that they can be used to show bioequivalence of different topical products. This review discusses the alternative skin models that have been developed as surrogates for normal and diseased skin and examines the concepts of using model systems for in vitro–in vivo correlation and the demonstration of bioequivalence. Keywords: percutaneous permeation, dermal delivery, transdermal, bioequivalence, ex vivo skin models, reconstructed skin

  9. Drug-Related Violence and Forced Migration from Mexico to the United States

    OpenAIRE

    Arceo-Gómez, Eva Olimpia

    2012-01-01

    When President Felipe Calderón took office he declared a war on drug lords, thus initiating a war of attrition which has claimed more than 40,000 lives in the last 5 years. In this chapter I document how this escalation of violence has led Mexicans living close to the northern border to migrate to the United States. Using data from the American Community Survey to estimate migration, and administrative death records to estimate murder rates, I present evidence that the United States southern ...

  10. A Triaxial Characteristic State Model for Sand

    DEFF Research Database (Denmark)

    Krenk, S.; Borup, M.; Hedegaard, J.

    A non-associated plasticity model for sand is presented. The loading surface is a closed two-parameter surface in the principal stress space, determined by a size and a shape parameter. The shape parameter is determined explicitly from the slope of the characteristic line. For small mean stress t...... that permit ultimate stress states beyond the characteristic line have been proposed. Results from drained triaxial tests show good agreement with the model, usi ng a weighted work hardening rule....... the loading surfaces approach the zero-tension planes asymptotically, generating a nearly triangular contour in the deviator ic stress plane. The gradient of the flow potential is generated directly from the gradient of the loading potential by scaling of the mean stress component. Two hardening rules...

  11. States With Prescription Drug Monitoring Mandates Saw Reduction In Opioids Prescribed To Medicaid Enrollees

    Science.gov (United States)

    Wen, Hefei; Schackman, Bruce R.; Aden, Brandon; Bao, Yuhua

    2017-01-01

    Prescription drug monitoring programs are promising tools to use in addressing the prescription opioid epidemic, yet prescribers’ participation in these state-run programs remains low as of 2014. Statutory mandates for prescribers to register with their state’s program, use it, or both are believed to be effective tools to realize the programs’ full potential. Our analysis of aggregate Medicaid drug utilization data indicates that state mandates for prescriber registration or use adopted in 2011–14 were associated with a reduction of 9–10 percent in population-adjusted numbers of Schedule II opioid prescriptions received by Medicaid enrollees and amounts of Medicaid spending on these prescriptions. This effect was largely associated with mandates of registration, which were comprehensive in all adopting states, and not with mandates of use, which were largely limited in scope or strength before 2015. Our findings support the use of mandates of registration in prescription drug monitoring programs as an effective and relatively low-cost policy. Future research should further assess the value of strong mandates of use to ensure safer and more appropriate prescribing of opioids. PMID:28373340

  12. Antipsychotic drugs rapidly induce dopamine neuron depolarization block in a developmental rat model of schizophrenia

    OpenAIRE

    Valenti, Ornella; Cifelli, Pierangelo; Gill, Kathryn M.; Grace, Anthony A.

    2011-01-01

    Repeated administration of antipsychotic drugs to normal rats has been shown to induce a state of dopamine neuron inactivation known as depolarization block, which correlates with the ability of the drugs to exhibit antipsychotic efficacy and extrapyramidal side-effects in schizophrenia patients. Nonetheless, in normal rats depolarization block requires weeks of antipsychotic drug administration, whereas schizophrenia patients exhibit initial effects soon after initiating antipsychotic drug t...

  13. New Hepatitis C Drugs Are Very Costly And Unavailable To Many State Prisoners.

    Science.gov (United States)

    Beckman, Adam L; Bilinski, Alyssa; Boyko, Ryan; Camp, George M; Wall, A T; Lim, Joseph K; Wang, Emily A; Bruce, R Douglas; Gonsalves, Gregg S

    2016-10-01

    Prisoners bear much of the burden of the hepatitis C epidemic in the United States. Yet little is known about the scope and cost of treating hepatitis C in state prisons-particularly since the release of direct-acting antiviral medications. In the forty-one states whose departments of corrections reported data, 106,266 inmates (10 percent of their prisoners) were known to have hepatitis C on or about January 1, 2015. Only 949 (0.89 percent) of those inmates were being treated. Prices for a twelve-week course of direct-acting antivirals such as sofosbuvir and the combination drug ledipasvir/sofosbuvir varied widely as of September 30, 2015 ($43,418-$84,000 and $44,421-$94,500, respectively). Numerous corrections departments received smaller discounts than other government agencies did. To reduce the hepatitis C epidemic, state governments should increase funding for treating infected inmates. State departments of corrections should consider collaborating with other government agencies to negotiate discounts with pharmaceutical companies and with qualified health care facilities to provide medications through the federal 340B Drug Discount Program. Helping inmates transition to providers in the community upon release can enhance the gains achieved by treating hepatitis C in prison. Project HOPE—The People-to-People Health Foundation, Inc.

  14. Driving forces behind the increasing cardiovascular treatment intensity.A dynamic epidemiologic model of trends in Danish cardiovascular drug utilization.

    DEFF Research Database (Denmark)

    Kildemoes, Helle Wallach; Andersen, Morten

    -state (untreated, treated, dead) semi-Markov model to analyse the dynamics of drug use. Transitions were from untreated to treated (incidence), the reverse (discontinuation), and from either untreated or treated to dead. Stratified by sex and age categories, prevalence trends of "growth driving" drug categories...

  15. Pharmaceutical companies vs. the State: who is responsible for post-trial provision of drugs in Brazil?

    Science.gov (United States)

    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.

  16. Drug penetration model of vinblastine-treated Caco-2 cultures.

    Science.gov (United States)

    Hellinger, Eva; Bakk, Mónika Laura; Pócza, Péter; Tihanyi, Károly; Vastag, Monika

    2010-09-11

    The penetrability of new chemical entities (NCE) is routinely screened in preclinical drug research. Although Caco-2 is a well-established model for human absorption, the identification of P-glycoprotein (P-gp) substrates and therefore the predictive accuracy of this model is not always satisfactory. Vinblastine has been reported to affect P-gp expression in Caco-2 cells. Therefore, this study was intended to assess the effect of sustained vinblastine treatment on the expression of P-gp, using RT-PCR and Western blot techniques. The P-gp functionality was monitored in transport assay, and metabolic enzyme activities were studied using probe substrates. Completion of culture medium with vinblastine (10nM during both the growing and the differentiation period) increased the P-gp mRNA and the expression at protein level. These changes were associated with the sensitive and steady identification of P-gp substrates in the bidirectional transport assay. While the vinblastine-treated Caco-2 (VB-Caco-2) based model reliably identified the P-gp substrates, the native Caco-2 model failed to recognize 7 out of the 11 reference substrates. The penetrability of passively permeating compounds correlated strongly (r(2)=0.9830) in the two models as expected. Omitting vinblastine from established VB-Caco-2 cultures did not affect either the protein level or the functionality of P-gp. Vinblastine did not alter the CYP mediated activities of the cells either. The higher sensitivity of VB-Caco-2 culture is also supported by the test results of NCEs, where 37% of NCEs were found to be P-gp substrate in VB-Caco-2 verified by verapamil, but only 9% by native Caco-2. Copyright (c) 2010 Elsevier B.V. All rights reserved.

  17. The entropic brain: a theory of conscious states informed by neuroimaging research with psychedelic drugs

    Science.gov (United States)

    Carhart-Harris, Robin L.; Leech, Robert; Hellyer, Peter J.; Shanahan, Murray; Feilding, Amanda; Tagliazucchi, Enzo; Chialvo, Dante R.; Nutt, David

    2014-01-01

    Entropy is a dimensionless quantity that is used for measuring uncertainty about the state of a system but it can also imply physical qualities, where high entropy is synonymous with high disorder. Entropy is applied here in the context of states of consciousness and their associated neurodynamics, with a particular focus on the psychedelic state. The psychedelic state is considered an exemplar of a primitive or primary state of consciousness that preceded the development of modern, adult, human, normal waking consciousness. Based on neuroimaging data with psilocybin, a classic psychedelic drug, it is argued that the defining feature of “primary states” is elevated entropy in certain aspects of brain function, such as the repertoire of functional connectivity motifs that form and fragment across time. Indeed, since there is a greater repertoire of connectivity motifs in the psychedelic state than in normal waking consciousness, this implies that primary states may exhibit “criticality,” i.e., the property of being poised at a “critical” point in a transition zone between order and disorder where certain phenomena such as power-law scaling appear. Moreover, if primary states are critical, then this suggests that entropy is suppressed in normal waking consciousness, meaning that the brain operates just below criticality. It is argued that this entropy suppression furnishes normal waking consciousness with a constrained quality and associated metacognitive functions, including reality-testing and self-awareness. It is also proposed that entry into primary states depends on a collapse of the normally highly organized activity within the default-mode network (DMN) and a decoupling between the DMN and the medial temporal lobes (which are normally significantly coupled). These hypotheses can be tested by examining brain activity and associated cognition in other candidate primary states such as rapid eye movement (REM) sleep and early psychosis and comparing

  18. Increased Incidence of Spinal Abscess and Substance Abuse after Implementation of State Mandated Prescription Drug Legislation.

    Science.gov (United States)

    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.

  19. Psychotropic drug use among preschool children in the Medicaid program from 36 states.

    Science.gov (United States)

    Garfield, Lauren D; Brown, Derek S; Allaire, Benjamin T; Ross, Raven E; Nicol, Ginger E; Raghavan, Ramesh

    2015-03-01

    We determined the prevalence of and indications for psychotropic medication among preschool children in Medicaid. We obtained 2000 to 2003 Medicaid Analytic Extract data from 36 states. We followed children in 2 cohorts, born in 1999 and 2000, up to age 4 years. We used logistic regression to model odds of receiving medications for (1) attention-deficit disorder/attention-deficit hyperactivity disorder, (2) depression or anxiety, and (3) psychotic illness or bipolar. Overall, 1.19% of children received at least 1 psychotropic drug. Medications for attention-deficit disorder/attention-deficit hyperactivity disorder treatment were most common (0.61% of all children), followed by depression or anxiety (0.59%) and psychotic illness or bipolar (0.24%). Among children, boys, those of other or unknown race compared with White, and those with other insurance compared with fee for service-only had higher odds of receiving a prescription (odds ratio [OR]=1.80 [95% confidence interval (CI)=1.74, 1.86], 1.75 [corrected] [1.66, 1.85], and 1.14 [1.01, 1.28], respectively), whereas Black and Hispanic children had lower odds (OR=0.51 [95% CI=0.48, 0.53] and 0.37 [0.34, 0.39], respectively). Preschoolers are receiving psychotropic medications despite limited evidence supporting safety or efficacy. Future research should focus on implementing medication use practice parameters in infant and toddler clinics, and expanding psychosocial interventions for young children with behavioral problems.

  20. Active State Model for Autonomous Systems

    Science.gov (United States)

    Park, Han; Chien, Steve; Zak, Michail; James, Mark; Mackey, Ryan; Fisher, Forest

    2003-01-01

    The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

  1. Annual Report on the State of the Drugs Problem in the European Union, 2000.

    Science.gov (United States)

    European Monitoring Centre for Drugs and Drug Addiction, Lisbon (Portugal).

    This report presents an overview of the drug phenomenon in Europe at the start of the new millennium. The first chapter begins with a discussion of overall drug trends. Specifically, it examines trends in drug use and the consequences including multiple drug use; problem drug use and demand for treatment; drug-related deaths; drug-related…

  2. Personal characteristics associated with injecting drug use among Latinas in the United States of America

    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.

  3. The History of MDMA as an Underground Drug in the United States, 1960-1979.

    Science.gov (United States)

    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.

  4. Generalized plasma skimming model for cells and drug carriers in the microvasculature.

    Science.gov (United States)

    Lee, Tae-Rin; Yoo, Sung Sic; Yang, Jiho

    2017-04-01

    In microvascular transport, where both blood and drug carriers are involved, plasma skimming has a key role on changing hematocrit level and drug carrier concentration in capillary beds after continuous vessel bifurcation in the microvasculature. While there have been numerous studies on modeling the plasma skimming of blood, previous works lacked in consideration of its interaction with drug carriers. In this paper, a generalized plasma skimming model is suggested to predict the redistributions of both the cells and drug carriers at each bifurcation. In order to examine its applicability, this new model was applied on a single bifurcation system to predict the redistribution of red blood cells and drug carriers. Furthermore, this model was tested at microvascular network level under different plasma skimming conditions for predicting the concentration of drug carriers. Based on these results, the applicability of this generalized plasma skimming model is fully discussed and future works along with the model's limitations are summarized.

  5. In Silico Modeling of Gastrointestinal Drug Absorption: Predictive Performance of Three Physiologically Based Absorption Models.

    Science.gov (United States)

    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

  6. Examining a Causal Model of Early Drug Involvement Among Inner City Junior High School Youths.

    Science.gov (United States)

    Dembo, Richard; And Others

    Reflecting the need to construct more inclusive, socially and culturally relevant conceptions of drug use than currently exist, the determinants of drug involvement among inner-city youths within the context of a causal model were investigated. The drug involvement of the Black and Puerto Rican junior high school girls and boys was hypothesized to…

  7. The Effect of Florida Medicaid's State-Mandated Formulary Provision on Prescription Drug Use and Health Plan Costs in a Medicaid Managed Care Plan.

    Science.gov (United States)

    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

  8. Binding of the anticonvulsant drug lamotrigine and the neurotoxin batrachotoxin to voltage-gated sodium channels induces conformational changes associated with block and steady-state activation.

    Science.gov (United States)

    Cronin, Nora B; O'Reilly, Andrias; Duclohier, Hervé; Wallace, B A

    2003-03-21

    Voltage-gated sodium channels are dynamic membrane proteins characterized by rapid conformational changes that switch the molecule between closed resting, activated, and inactivated states. Sodium channels are specifically blocked by the anticonvulsant drug lamotrigine, which preferentially binds to the channel pore in the inactivated open state. Batrachotoxin is a lipid-soluble alkaloid that causes steady-state activation and binds in the inner pore of the sodium channel with overlapping but distinct molecular determinants from those of lamotrigine. Using circular dichroism spectroscopy on purified voltage-gated sodium channels from Electrophorus electricus, the secondary structures associated with the mixture of states present at equilibrium in the absence of these ligands were compared with specific stabilized states in their presence. As the channel shifts to open states, there appears to be a significant change in secondary structure to a more alpha-helical conformation. The observed changes are consistent with increased order involving the S6 segments that form the pore, the domain III-IV linker, and the P-loops that form the outer pore and selectivity filter. A molecular model has been constructed for the sodium channel based on its homology with the pore-forming regions of bacterial potassium channels, and automated docking of the crystal structure of lamotrigine with this model produces a structure in which the close contacts of the drug are with the residues previously identified by mutational studies as forming the binding site for this drug.

  9. Biomembrane models and drug-biomembrane interaction studies: Involvement in drug design and development

    OpenAIRE

    Pignatello, R.; Musumeci, T.; Basile, L.; Carbone, C.; Puglisi, G.

    2011-01-01

    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 physi...

  10. Characterizing the relationship between steady state and response using analytical expressions for the steady states of mass action models.

    Science.gov (United States)

    Loriaux, Paul Michael; Tesler, Glenn; Hoffmann, Alexander

    2013-01-01

    The steady states of cells affect their response to perturbation. Indeed, diagnostic markers for predicting the response to therapeutic perturbation are often based on steady state measurements. In spite of this, no method exists to systematically characterize the relationship between steady state and response. Mathematical models are established tools for studying cellular responses, but characterizing their relationship to the steady state requires that it have a parametric, or analytical, expression. For some models, this expression can be derived by the King-Altman method. However, King-Altman requires that no substrate act as an enzyme, and is therefore not applicable to most models of signal transduction. For this reason we developed py-substitution, a simple but general method for deriving analytical expressions for the steady states of mass action models. Where the King-Altman method is applicable, we show that py-substitution yields an equivalent expression, and at comparable efficiency. We use py-substitution to study the relationship between steady state and sensitivity to the anti-cancer drug candidate, dulanermin (recombinant human TRAIL). First, we use py-substitution to derive an analytical expression for the steady state of a published model of TRAIL-induced apoptosis. Next, we show that the amount of TRAIL required for cell death is sensitive to the steady state concentrations of procaspase 8 and its negative regulator, Bar, but not the other procaspase molecules. This suggests that activation of caspase 8 is a critical point in the death decision process. Finally, we show that changes in the threshold at which TRAIL results in cell death is not always equivalent to changes in the time of death, as is commonly assumed. Our work demonstrates that an analytical expression is a powerful tool for identifying steady state determinants of the cellular response to perturbation. All code is available at http://signalingsystems.ucsd.edu/models-and-code/ or

  11. Mouse Models of Type 2 Diabetes Mellitus in Drug Discovery.

    Science.gov (United States)

    Baribault, Helene

    2016-01-01

    Type 2 diabetes is a fast-growing epidemic in industrialized countries, associated with obesity, lack of physical exercise, aging, family history, and ethnic background. Diagnostic criteria are elevated fasting or postprandial blood glucose levels, a consequence of insulin resistance. Early intervention can help patients to revert the progression of the disease together with lifestyle changes or monotherapy. Systemic glucose toxicity can have devastating effects leading to pancreatic beta cell failure, blindness, nephropathy, and neuropathy, progressing to limb ulceration or even amputation. Existing treatments have numerous side effects and demonstrate variability in individual patient responsiveness. However, several emerging areas of discovery research are showing promises with the development of novel classes of antidiabetic drugs.The mouse has proven to be a reliable model for discovering and validating new treatments for type 2 diabetes mellitus. We review here commonly used methods to measure endpoints relevant to glucose metabolism which show good translatability to the diagnostic of type 2 diabetes in humans: baseline fasting glucose and insulin, glucose tolerance test, insulin sensitivity index, and body type composition. Improvements on these clinical values are essential for the progression of a novel potential therapeutic molecule through a preclinical and clinical pipeline.

  12. Alcohol- and Drug-Involved Driving in the United States: Methodology for the 2007 National Roadside Survey

    Science.gov (United States)

    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…

  13. Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

    Science.gov (United States)

    Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

    2017-05-01

    To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

  14. Are adolescents more vulnerable to drug addiction than adults? Evidence from animal models.

    Science.gov (United States)

    Schramm-Sapyta, Nicole L; Walker, Q David; Caster, Joseph M; Levin, Edward D; Kuhn, Cynthia M

    2009-09-01

    Epidemiological evidence suggests that people who begin experimenting with drugs of abuse during early adolescence are more likely to develop substance use disorders (SUDs), but this correlation does not guarantee causation. Animal models, in which age of onset can be tightly controlled, offer a platform for testing causality. Many animal models address drug effects that might promote or discourage drug intake and drug-induced neuroplasticity. We have reviewed the preclinical literature to investigate whether adolescent rodents are differentially sensitive to rewarding, reinforcing, aversive, locomotor, and withdrawal-induced effects of drugs of abuse. The rodent model literature consistently suggests that the balance of rewarding and aversive effects of drugs of abuse is tipped toward reward in adolescence. However, increased reward does not consistently lead to increased voluntary intake: age effects on voluntary intake are drug and method specific. On the other hand, adolescents are consistently less sensitive to withdrawal effects, which could protect against compulsive drug seeking. Studies examining neuronal function have revealed several age-related effects but have yet to link these effects to vulnerability to SUDs. Taken together, the findings suggest factors which may promote recreational drug use in adolescents, but evidence relating to pathological drug-seeking behavior is lacking. A call is made for future studies to address this gap using behavioral models of pathological drug seeking and for neurobiologic studies to more directly link age effects to SUD vulnerability.

  15. Recent Advances of Computational Modeling for Predicting Drug Metabolism: A Perspective.

    Science.gov (United States)

    Kar, Supratik; Leszczynski, Jerzy

    2017-01-01

    Absorption, Distribution, Metabolism, Excretion (ADME) properties along with drug induced adverse effects are the major reasons for the late stage failure of drug candidates as well as the cause for the expensive withdrawal of many approved drugs from the market. Considering the adverse effects of drugs, metabolism factor has great importance in medicinal chemistry and clinical pharmacology because it influences the deactivation, activation, detoxification and toxification of drugs. Computational methods are effective approaches to reduce the number of safety issues by analyzing possible links between chemical structures and metabolism followed by adverse effects, as they serve the integration of information on several levels to enhance the reliability of outcomes. In silico profiling of drug metabolism can help progress only those molecules along the discovery chain that is less likely to fail later in the drug discovery process. This positively impacts the very high costs of drug discovery and development. Understanding the science behind computational tools, their opportunities, and limitations is essential to make a true influence on drug discovery at different levels. If applied in a scientifically consequential way, computational tools may improve the capability to identify and evaluate potential drug molecules considering pharmacokinetic properties of drugs. Herein, current trends in computational modeling for predicting drug metabolism are reviewed highlighting new computational tools for drug metabolism prediction followed by reporting large and integrated databases of approved drugs associated with diverse metabolism issues. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  16. Consequences of adolescent use of alcohol and other drugs: Studies using rodent models

    Science.gov (United States)

    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

  17. Statistical modeling of the drug load distribution on trastuzumab emtansine (Kadcyla), a lysine-linked antibody drug conjugate.

    Science.gov (United States)

    Kim, Michael T; Chen, Yan; Marhoul, Joseph; Jacobson, Fred

    2014-07-16

    Trastuzumab emtansine (Kadcyla) is a recently approved antibody-drug conjugate produced by attachment of the anti-tubulin drug, DM1, to lysine amines via the SMCC linker. The resulting product exhibits a drug load distribution from 0 to 8 drugs per antibody that can be quantified using mass spectrometry. Different statistical models were tested against the experimental data derived from samples produced during process characterization studies to determine best fit. The Poisson distribution gives the best correlation for samples manufactured using the target process conditions (yielding the target average drug to antibody ratio (DAR) of 3.5) as well as those produced under conditions that exceed the allowed manufacturing ranges and yield products with average DAR values that are significantly different from the target (i.e., ≤3.0 or ≥4.0). The Poisson distribution establishes a link between average DAR values and drug load distributions, implying that measurement and control of the former (i.e., via a simple UV spectrophotometric method) could be used to indirectly control the latter in trastuzumab emtansine.

  18. 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.

  19. UAV State Estimation Modeling Techniques in AHRS

    Science.gov (United States)

    Razali, Shikin; Zhahir, Amzari

    2017-11-01

    Autonomous unmanned aerial vehicle (UAV) system is depending on state estimation feedback to control flight operation. Estimation on the correct state improves navigation accuracy and achieves flight mission safely. One of the sensors configuration used in UAV state is Attitude Heading and Reference System (AHRS) with application of Extended Kalman Filter (EKF) or feedback controller. The results of these two different techniques in estimating UAV states in AHRS configuration are displayed through position and attitude graphs.

  20. Formulating a poorly water soluble drug into an oral solution suitable for paediatric patients; lorazepam as a model drug.

    Science.gov (United States)

    van der Vossen, A C; van der Velde, I; Smeets, O S N M; Postma, D J; Eckhardt, M; Vermes, A; Koch, B C P; Vulto, A G; Hanff, L M

    2017-03-30

    Many drugs are unavailable in suitable oral paediatric dosage forms, and pharmacists often have to compound drugs to provide paediatric patients with an acceptable formulation in the right dose. Liquid formulations offer the advantage of dosing flexibility and ease of administration to young patients, but drug substances often show poor aqueous solubility. The objective of this work was to study different solvents and matrices to design a liquid formulation for poorly water soluble drugs, using lorazepam as model drug. Three different formulation strategies were explored to improve the solubility. Firstly, water-soluble organic solvents were used to improve the aqueous solubility directly, secondly, ionic surfactants were used to solubilise the model drug, and thirdly, complexation of lorazepam with cyclodextrin was studied. Specific attention was paid to excipients, adequate taste correction and palatability. For the final formulation, physical and chemical stability and microbiological quality were assessed for 12months. An organic solvent based formulation, containing a mixture of polyethylene glycol and glycerol 85%, with a minimum amount of propylene glycol, proved to be physically and chemically stable. Development of the non-ionic surfactants formulation was discontinued due to taste problems. The cyclodextrin formulations were physically stable, but lorazepam content declined to 90% within five months. The final formulation contained in volume concentration (%v/v) 87% glycerol, 10% polyethylene glycol 400 and 3% propylene glycol. Orange essence was the preferred taste corrector. The formulation remained stable for 12months at 4°C, with lorazepam content remaining >95%. Related substances increased during the study period but remained below 2%. In-use stability was proven up to 4weeks. An organic solvent based oral formulation was shown to be superior to a non-ionic surfactant based formulation or a cyclodextrin formulation. These results may help to

  1. Model Reference Adaptive Scheme for Multi-drug Infusion for Blood Pressure Control

    OpenAIRE

    Enbiya, Saleh; Mahieddine, Fatima; Hossain, Alamgir

    2011-01-01

    Using multiple interacting drugs to control both the mean arterial pressure (MAP) and cardiac output (CO) of patients with different sensitivity to drugs is a challenging task which this paper attempts to address. A multivariable model reference adaptive control (MRAC) algorithm is developed using a two-input, two-output patient model. The control objective is to maintain the homodynamic variables MAP and CO at the normal values by simultaneously administering two drugs; sodium nitroprusside ...

  2. Food, gastrointestinal pH, and models of oral drug absorption.

    Science.gov (United States)

    Abuhelwa, Ahmad Y; Williams, Desmond B; Upton, Richard N; Foster, David J R

    2017-03-01

    This article reviews the major physiological and physicochemical principles of the effect of food and gastrointestinal (GI) pH on the absorption and bioavailability of oral drugs, and the various absorption models that are used to describe/predict oral drug absorption. The rate and extent of oral drug absorption is determined by a complex interaction between a drug's physicochemical properties, GI physiologic factors, and the nature of the formulation administered. GI pH is an important factor that can markedly affect oral drug absorption and bioavailability as it may have significant influence on drug dissolution & solubility, drug release, drug stability, and intestinal permeability. Different regions of the GI tract have different drug absorptive properties. Thus, the transit time in each GI region and its variability between subjects may contribute to the variability in the rate and/or extent of drug absorption. Food-drug interactions can result in delayed, decreased, increased, and sometimes un-altered drug absorption. Food effects on oral absorption can be achieved by direct and indirect mechanisms. Various models have been proposed to describe oral absorption ranging from empirical models to the more sophisticated "mechanism-based" models. Through understanding of the physicochemical and physiological rate-limiting factors affecting oral absorption, modellers can implement simplified population-based modelling approaches that are less complex than whole-body physiologically-based models but still capture the essential elements in a physiological way and hence will be more suited for population modelling of large clinical data sets. It will also help formulation scientists to better predict formulation performance and to develop formulations that maximize oral bioavailability. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. A Probabilistic Model of Illegal Drug Trafficking Operations in the Eastern Pacific and Caribbean Sea

    Science.gov (United States)

    2013-09-01

    cocoa production in these three countries at 187,500 hectares in 2010. This is down from a peak in 2007 of 232,500 hectares. Combining the Andean...Their efforts, while productive , are not able to stop a large majority of the drugs from reaching the United States. They battle Mexican and... production , drug-trafficking, and drug consumption. The South American countries in the Andean region, particularly Colombia, Peru, and Bolivia, are

  4. Formulation of 3D Printed Tablet for Rapid Drug Release by Fused Deposition Modeling: Screening Polymers for Drug Release, Drug-Polymer Miscibility and Printability.

    Science.gov (United States)

    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.

  5. Systematic synergy modeling: understanding drug synergy from a systems biology perspective.

    Science.gov (United States)

    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.

  6. Characteristics of drug use among pregnant women in the United States: Opioid and non-opioid illegal drug use.

    Science.gov (United States)

    Metz, Verena E; Brown, Qiana L; Martins, Silvia S; Palamar, Joseph J

    2018-02-01

    The opioid epidemic in the US is affecting pregnant women and their offspring, with rising numbers of maternal and neonatal treatment episodes. The aim of this study was to characterize pregnant drug users in order to inform intervention strategies based on sociodemographic, mental health, and substance use characteristics. Data on pregnant women aged 18-44 reporting past-year, nonmedical opioid use or use of non-opioid illegal drugs (other than marijuana) were analyzed from the National Survey on Drug Use and Health (2005-2014). Women (N = 818) were categorized into 3 groups: 1) use of opioids only (n = 281), 2) opioid-polydrug users (n = 241), and 3) other (non-opioid) illegal drug users (n = 296). Characteristics between the 3 groups of women were compared using bivariable analyses. Most women were non-Hispanic White (67.6%), had a high school diploma or less education (61.0%), a household income illegal drug users (27.6%) (P drug/alcohol treatment was less prevalent among opioid-only users (6.3%) compared to opioid-polydrug users (20.3%) and other illegal drug users (8.3%) (P = 0.002). Opioid-only users also reported lower prevalence of past-year depression (P drug-using women were often of low socioeconomic status, with mental health and substance use patterns suggesting the need for targeted mental health/substance use screening and interventions before and during pregnancy, particularly for opioid-polydrug users. Copyright © 2017. Published by Elsevier B.V.

  7. A Comparative Study of Successful Central Nervous System Drugs Using Molecular Modeling

    Science.gov (United States)

    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…

  8. Polycaprolactone thin-film drug delivery systems: Empirical and predictive models for device design.

    Science.gov (United States)

    Schlesinger, Erica; Ciaccio, Natalie; Desai, Tejal A

    2015-12-01

    To define empirical models and parameters based on theoretical equations to describe drug release profiles from two polycaprolactone thin-film drug delivery systems. Additionally, to develop a predictive model for empirical parameters based on drugs' physicochemical properties. Release profiles from a selection of drugs representing the standard pharmaceutical space in both polycaprolactone matrix and reservoir systems were determined experimentally. The proposed models were used to calculate empirical parameters describing drug diffusion and release. Observed correlations between empirical parameters and drug properties were used to develop equations to predict parameters based on drug properties. Predictive and empirical models were evaluated in the design of three prototype devices: a levonorgestrel matrix system for on-demand locally administered contraception, a timolol-maleate reservoir system for glaucoma treatment, and a primaquine-bisphosphate reservoir system for malaria prophylaxis. Proposed empirical equations accurately fit experimental data. Experimentally derived empirical parameters show significant correlations with LogP, molecular weight, and solubility. Empirical models based on predicted parameters accurately predict experimental release data for three prototype systems, demonstrating the accuracy and utility of these models. The proposed empirical models can be used to design polycaprolactone thin-film devices for target geometries and release rates. Empirical parameters can be predicted based on drug properties. Together, these models provide tools for preliminary evaluation and design of controlled-release delivery systems. Copyright © 2015. Published by Elsevier B.V.

  9. Mining FDA drug labels using an unsupervised learning technique - topic modeling

    Directory of Open Access Journals (Sweden)

    Xu Xiaowei

    2011-10-01

    Full Text Available Abstract 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 Conclusions The successful application of topic modeling on the FDA drug labeling demonstrates its potential utility as a hypothesis generation means to infer hidden relationships of concepts such as, in this study, drug safety and therapeutic use

  10. THE EUROPEAN MODEL OF STATE REGULATION OF TOURISM ACTIVITIES

    OpenAIRE

    О. Davydova

    2013-01-01

    In the article the existing model of state regulation of the development of tourism. Expediency of the European model of state regulation of tourism development in Ukraine. It is noted that the European model of state regulation of tourism activities based on the coordination of marketing activities and the development of cooperation between the public and private sectors. The basic forms of public-private partnerships and the advantages of using cluster model of development of tourism, namel...

  11. 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.

  12. Simple variational ground state and pure-cat-state generation in the quantum Rabi model

    Science.gov (United States)

    Leroux, C.; Govia, L. C. G.; Clerk, A. A.

    2017-10-01

    We introduce a simple, physically motivated variational ground state for the quantum Rabi model and demonstrate that it provides a high-fidelity approximation of the true ground state in all parameter regimes (including intermediate- and strong-coupling regimes). Our variational state is constructed using Gaussian cavity states and nonorthogonal qubit pointer states and contains only three variational parameters. We use our state to develop a heuristic understanding of how the ground state evolves with increasing coupling and find a parameter regime where the ground state corresponds to the cavity being in a nearly pure Schrödinger cat state.

  13. Computing characterizations of drugs for ion channels and receptors using Markov models

    CERN Document Server

    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.

  14. Predicting Drug Concentration-Time Profiles in Multiple CNS Compartments Using a Comprehensive Physiologically-Based Pharmacokinetic Model

    NARCIS (Netherlands)

    Yamamoto, Yumi; Välitalo, Pyry A; Huntjens, Dymphy R; Proost, Johannes H; Vermeulen, An; Krauwinkel, Walter; Beukers, Margot W; van den Berg, Dirk-Jan; Hartman, Robin; Wong, Yin Cheong; Danhof, Meindert; van Hasselt, John G C; de Lange, Elizabeth C M

    2017-01-01

    Drug development targeting the central nervous system (CNS) is challenging due to poor predictability of drug concentrations in various CNS compartments. We developed a generic physiologically based pharmacokinetic (PBPK) model for prediction of drug concentrations in physiologically relevant CNS

  15. Ultrasonic Vocalizations as a Measure of Affect in Preclinical Models of Drug Abuse: A Review of Current Findings.

    Science.gov (United States)

    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.

  16. Retrospective use of PBPK modelling to understand a clinical drug-drug interaction between dextromethorphan and GSK1034702.

    Science.gov (United States)

    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.

  17. Blood-brain barrier in vitro models as tools in drug discovery: assessment of the transport ranking of antihistaminic drugs.

    Science.gov (United States)

    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

  18. [Case reports of drug-induced liver injury in a reference hospital of Zulia state, Venezuela].

    Science.gov (United States)

    Mengual-Moreno, Edgardo; Lizarzábal-García, Maribel; Ruiz-Soler, María; Silva-Suarez, Niniveth; Andrade-Bellido, Raúl; Lucena-González, Maribel; Bessone, Fernando; Hernández, Nelia; Sánchez, Adriana; Medina-Cáliz, Inmaculada

    2015-03-01

    Drug-induced liver injury (DILI) is an important cause of morbidity and mortality worldwide, with varied geographical differences. The aim of this prospective, descriptive, cross-sectional study was to identify and characterize cases of DILI in a hospital of Zulia state, Venezuela. Thirteen patients with a presumptive diagnosis of DILI attended by the Department of Gastroenterology, Hospital Universitario, Zulia state, Venezuela, from December-2012 to December-2013 were studied. Ibuprofen (n = 3; 23.1%), acetaminophen (n = 3; 23.1), isoniazid (n = 2; 15.4%) and Herbalife products (n = 2; 15.4%) were the main drugs involved with DILI. Acetaminophen and ibuprofen showed a mixed pattern of liver injury (n = 3; 23.1%) and isoniazid presented a hepatocellular pattern (n = 2; 15.4%). The CIOMS/RUCAMS allowed the identification of possible (n = 7; 53.9%), probable (n = 4; 30.8%) and highly-probable cases (n = 2; 15.4%) of DILI. Amoxicillin/clavulanate, isoniazid, isotretinoin, methotrexate and Herbalife nutritional products were implicated as highly-probable and probable agents. The highest percentage of DILI corresponded to mild cases that recovered after the discontinuation of the agent involved (n = 9; 69.3%). The consumption of Herbalife botanical products is associated with probable causality and fatality (n = 1; 7.7%). In conclusion, the frequency of DILI cases controlled by the Department of Gastroenterology of the Hospital Universitario of Maracaibo was low, being ibuprofen, acetaminophen, isoniazid and products Herbalife the products most commonly involved. It is recommended to continue with the prospective registration of cases, with an extended follow up monitoring period and to facilitate the incorporation of other hospitals in the Zulia State and Venezuela.

  19. Prediction of drug distribution in subcutaneous xenografts of human tumor cell lines and healthy tissues in mouse: application of the tissue composition-based model to antineoplastic drugs.

    Science.gov (United States)

    Poulin, Patrick; Chen, Yung-Hsiang; Ding, Xiao; Gould, Stephen E; Hop, Cornelis Eca; Messick, Kirsten; Oeh, Jason; Liederer, Bianca M

    2015-04-01

    Advanced tissue composition-based models can predict the tissue-plasma partition coefficient (Kp ) values of drugs under in vivo conditions on the basis of in vitro and physiological input data. These models, however, focus on healthy tissues and do not incorporate data from tumors. The objective of this study was to apply a tissue composition-based model to six marketed antineoplastic drugs (docetaxel, DOC; doxorubicin, DOX; gemcitabine, GEM; methotrexate, MTX; topotecan, TOP; and fluorouracil, 5-FU) to predict their Kp values in three human tumor xenografts (HCT-116, H2122, and PC3) as well as in healthy tissues (brain, muscle, lung, and liver) under steady-state in vivo conditions in female NCR nude mice. The mechanisms considered in the tissue/tumor composition-based model are the binding to lipids and to plasma proteins, but the transporter effect was also investigated. The method consisted of analyzing tissue composition, performing the pharmacokinetics studies in mice, and calculating the corresponding in vivo Kp values. Analyses of tumor composition indicated that the tumor xenografts contained no or low amounts of common transporters by contrast to lipids. The predicted Kp values were within twofold and threefold of the measured values in 77% and 93% of cases, respectively. However, predictions for brain for each drug, for liver for MTX, and for each tumor xenograft for GEM were disparate from the observed values, and, therefore, not well served by the model. Overall, this study is the first step toward the mechanism-based prediction of Kp values of small molecules in healthy and tumor tissues in mouse when no transporter and permeation limitation effect is evident. This approach will be useful in selecting compounds based on their abilities to penetrate human cancer xenografts with a physiologically based pharmacokinetic (PBPK) model, thereby increasing therapeutic index for chemotherapy in oncology study. © 2015 Wiley Periodicals, Inc. and the American

  20. A pharmacoepidemiological network model for drug safety surveillance: statins and rhabdomyolysis.

    Science.gov (United States)

    Reis, Ben Y; Olson, Karen L; Tian, Lu; Bohn, Rhonda L; Brownstein, John S; Park, Peter J; Cziraky, Mark J; Wilson, Marcus D; Mandl, Kenneth D

    2012-05-01

    Recent withdrawals of major drugs have highlighted the critical importance of drug safety surveillance in the postmarketing phase. Limitations of spontaneous report data have led drug safety professionals to pursue alternative postmarketing surveillance approaches based on healthcare administrative claims data. These data are typically analysed by comparing the adverse event rates associated with a drug of interest to those of a single comparable reference drug. The aim of this study was to determine whether adverse event detection can be improved by incorporating information from multiple reference drugs. We developed a pharmacological network model that implemented this approach and evaluated its performance. We studied whether adverse event detection can be improved by incorporating information from multiple reference drugs, and describe two approaches for doing so. The first, reported previously, combines a set of related drugs into a single reference cohort. The second is a novel pharmacoepidemiological network model, which integrates multiple pair-wise comparisons across an entire set of related drugs into a unified consensus safety score for each drug. We also implemented a single reference drug approach for comparison with both multi-drug approaches. All approaches were applied within a sequential analysis framework, incorporating new information as it became available and addressing the issue of multiple testing over time. We evaluated all these approaches using statin (HMG-CoA reductase inhibitors) safety data from a large healthcare insurer in the US covering April 2000 through March 2005. We found that both multiple reference drug approaches offer earlier detection (6-13 months) than the single reference drug approach, without triggering additional false positives. Such combined approaches have the potential to be used with existing healthcare databases to improve the surveillance of therapeutics in the postmarketing phase over single-comparator methods

  1. Macroscopic modelling of solid-state fermentation

    NARCIS (Netherlands)

    Hoogschagen, M.J.

    2007-01-01

    Solid-state fermentation is different from the more well known process of liquid fermentation because no free flowing water is present. The technique is primarily used in Asia. Well-known products are the foods tempe, soy sauce and saké. In industrial solid-state fermentation, the substrate usually

  2. In vitro and in vivo models for testing arrhythmogenesis in drugs.

    Science.gov (United States)

    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.

  3. Nonclassical states of the Jaynes - Cummings model and its excitation

    International Nuclear Information System (INIS)

    Verlan, E.M.; Razumova, M.A.

    2002-01-01

    The nonclassical squeezed states of the Jaynes -Cummings (JC) model are built,and the problem of their excitation in parametric processes is considered.The statistical properties of a field oscillator are analyzed in these states

  4. Sex differences and ovarian hormones in animal models of drug dependence.

    Science.gov (United States)

    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.

  5. Quantum-Dot Semiconductor Optical Amplifiers: State Space Model versus Rate Equation Model

    Directory of Open Access Journals (Sweden)

    Hussein Taleb

    2013-01-01

    Full Text Available A simple and accurate dynamic model for QD-SOAs is proposed. The proposed model is based on the state space theory, where by eliminating the distance dependence of the rate equation model of the QD-SOA; we derive a state space model for the device. A comparison is made between the rate equation model and the state space model under both steady state and transient regimes. Simulation results demonstrate that the derived state space model not only is much simpler and faster than the rate equation model, but also it is as accurate as the rate equation model.

  6. Modeling state entropy of the EEG and auditory evoked potentials: hypnotic and analgesic interactions.

    Science.gov (United States)

    Castro, Ana; Amorim, Pedro; Nunes, Catarina S

    2007-01-01

    Because of the complexity of raw electroencephalogram (EEG), for the anesthesiologist it is very difficult to evaluate the patient's hypnosis state. Because of this, several depth of anesthesia monitors have been developed, and are in current use at the operating room (OR). These monitors convert the information supplied by the EEG or derived signals into a simple, easy to understand index. Nowadays, general anesthesia is controlled only by the clinician, which decides what is the best drug combination for the patient, regarding all information given by monitors and sensors in the OR. In this work, we collected data from two study groups with auditory evoked potentials (AEP) monitoring, and Entropy (SE) monitoring. A model was fitted to the signals and the Hill equation parameters adjusted, in both study groups. The objective was to predict hypnosis indices, regarding only the drugs administered to a patient, and capture the initial individual patient characteristics that might influence the drugs interaction in the human body. Hypnotic and analgesic drugs interact in different ways throughout the anaesthesia stages. The models obtained captured the different dynamic interaction of drugs, during the induction and maintenance phases, demonstrating that the model must have incorporated all this information in order to perform satisfactorily. Other information like haemodynamic variables might be included in the search for the optimum model.

  7. Facilitating prediction of adverse drug reactions by using knowledge graphs and multi-label learning models.

    Science.gov (United States)

    Muñoz, Emir; Novácek, Vít; Vandenbussche, Pierre-Yves

    2017-08-18

    Timely identification of adverse drug reactions (ADRs) is highly important in the domains of public health and pharmacology. Early discovery of potential ADRs can limit their effect on patient lives and also make drug development pipelines more robust and efficient. Reliable in silico prediction of ADRs can be helpful in this context, and thus, it has been intensely studied. Recent works achieved promising results using machine learning. The presented work focuses on machine learning methods that use drug profiles for making predictions and use features from multiple data sources. We argue that despite promising results, existing works have limitations, especially regarding flexibility in experimenting with different data sets and/or predictive models. We suggest to address these limitations by generalization of the key principles used by the state of the art. Namely, we explore effects of: (1) using knowledge graphs-machine-readable interlinked representations of biomedical knowledge-as a convenient uniform representation of heterogeneous data; and (2) casting ADR prediction as a multi-label ranking problem. We present a specific way of using knowledge graphs to generate different feature sets and demonstrate favourable performance of selected off-the-shelf multi-label learning models in comparison with existing works. Our experiments suggest better suitability of certain multi-label learning methods for applications where ranking is preferred. The presented approach can be easily extended to other feature sources or machine learning methods, making it flexible for experiments tuned toward specific requirements of end users. Our work also provides a clearly defined and reproducible baseline for any future related experiments. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  8. Mathematical modeling of efficacy and safety for anticancer drugs clinical development.

    Science.gov (United States)

    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.

  9. Modeling software with finite state machines a practical approach

    CERN Document Server

    Wagner, Ferdinand; Wagner, Thomas; Wolstenholme, Peter

    2006-01-01

    Modeling Software with Finite State Machines: A Practical Approach explains how to apply finite state machines to software development. It provides a critical analysis of using finite state machines as a foundation for executable specifications to reduce software development effort and improve quality. This book discusses the design of a state machine and of a system of state machines. It also presents a detailed analysis of development issues relating to behavior modeling with design examples and design rules for using finite state machines. This volume describes a coherent and well-tested fr

  10. Wave Modelling - The State of the Art

    National Research Council Canada - National Science Library

    Cavaleri, L; Rogers, Erick; Tolman, Hendrik L; Ardhuin, Fabrice; Lavrenov, Igor V; Alves, J-H. G; Babanin, A; Banner, M; Belibassakis, K; Benoit, M

    2007-01-01

    .... The many faces of the subject imply separate discussions. This is reflected into the single sections, seven of them, each dealing with a specific topic, the whole providing a broad and solid overview of the present state of the art...

  11. Factors associated with history of drug use among female sex workers (FSW in a high HIV prevalence state of India

    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

  12. [Susceptibility of M. tuberculosis to antituberculosis drugs as determined by two methods, in Sucre state, Venezuela].

    Science.gov (United States)

    Mendoza, Rosmy; De Donato, Marcos; de Waard, Jacobus H; Takiff, Howard; Bello, Teresita; Chirinos, Gladys

    2010-12-01

    The objective of this study was to evaluate the resistance to isoniazid (INH), rifampicin (RIF), streptomycin (STR) and ethambutol (EMB), with the Canetti's proportions method (PM) and the nitrate reductase assay (NRA) of 59 clinical strains of Mycobacterium tuberculosis, isolated in the period of august 2005 to december 2006, in Sucre state, Venezuela. Primary and acquired drug resistance was 6.3% and 14.3%, respectively. Only one strain was found to be multidrug resistant (MDR). The overall agreement between the NRA and PM was 100% for INH, RIF and EMB, and 96% for STR. The time to obtain results was 10 to 14 days for the NRA, compared to 42 days for the PM. The NRA was easy to perform and therefore represents a useful tool for rapid and accurate determination of drug-resistant M. tuberculosis. The sequence of the rpoB gene of the RIF resistant strain demonstrated a never described mutation (change in the codon 456; TCG > CAG) in the hypervariable region of 81 base pairs where most of the mutations of the RIF resistant strains have been reported. Comparison of our results with those of the last resistance prevalence study carried out in the years 1998-1999, shows a decrease in the studied area.

  13. Fundamental State Space Time Series Models for JEPX Electricity Prices

    Science.gov (United States)

    Ofuji, Kenta; Kanemoto, Shigeru

    Time series models are popular in attempts to model and forecast price dynamics in various markets. In this paper, we have formulated two state space models and tested them for its applicability to power price modeling and forecasting using JEPX (Japan Electric Power eXchange) data. The state space models generally have a high degree of flexibility with its time-dependent state transition matrix and system equation configurations. Based on empirical data analysis and past literatures, we used calculation assumptions to a) extract stochastic trend component to capture non-stationarity, and b) detect structural changes underlying in the market. The stepwise calculation algorithm followed that of Kalman Filter. We then evaluated the two models' forecasting capabilities, in comparison with ordinary AR (autoregressive) and ARCH (autoregressive conditional heteroskedasticity) models. By choosing proper explanatory variables, the latter state space model yielded as good a forecasting capability as that of the AR and the ARCH models for a short forecasting horizon.

  14. Text mining for adverse drug events: the promise, challenges, and state of the art.

    Science.gov (United States)

    Harpaz, Rave; Callahan, Alison; Tamang, Suzanne; Low, Yen; Odgers, David; Finlayson, Sam; Jung, Kenneth; LePendu, Paea; Shah, Nigam H

    2014-10-01

    Text mining is the computational process of extracting meaningful information from large amounts of unstructured text. It is emerging as a tool to leverage underutilized data sources that can improve pharmacovigilance, including the objective of adverse drug event (ADE) detection and assessment. This article provides an overview of recent advances in pharmacovigilance driven by the application of text mining, and discusses several data sources-such as biomedical literature, clinical narratives, product labeling, social media, and Web search logs-that are amenable to text mining for pharmacovigilance. Given the state of the art, it appears text mining can be applied to extract useful ADE-related information from multiple textual sources. Nonetheless, further research is required to address remaining technical challenges associated with the text mining methodologies, and to conclusively determine the relative contribution of each textual source to improving pharmacovigilance.

  15. HIV prevention among drug and alcohol users: models of ...

    African Journals Online (AJOL)

    The spread of HIV among drug and alcohol users, as a high-risk group, is a significant problem in Africa, as in other parts of the world. Few programs have been implemented in Africa to deal specifically with this issue. Since November 2006, the AED Capable Partners Program in Kenya project has provided technical ...

  16. Alcohol and Other Drug Prevention on College Campuses: Model Programs

    Science.gov (United States)

    US Department of Education, 2008

    2008-01-01

    In response to recent alcohol-related tragedies and to ongoing concern about unacceptable levels of alcohol and other drug use on college campuses, Congress authorized the U.S. Department of Education to identify and promote effective campus-based prevention programs. Since 1999, the U.S. Department of Education has awarded approximately $3.5…

  17. Mathematical models for drug diffusion through the compartments of ...

    African Journals Online (AJOL)

    The Laplace transform and eigenvalue methods were used to obtain the solution of the ordinary differential equations concerning the rate of change of concentration in different compartments viz. blood and tissue medium. The drug concentration in the different compartments has been computed using numerical parameters ...

  18. Cell cultures from animal models of Alzheimer's disease as a tool for faster screening and testing of drug efficacy.

    Science.gov (United States)

    Trinchese, Fabrizio; Liu, Shumin; Ninan, Ipe; Puzzo, Daniela; Jacob, Joel P; Arancio, Ottavio

    2004-01-01

    Approximately 2 million people in the United States suffer from Alzheimer's disease (AD), which is the most common cause of chronic dementia among the aging population. During the last 7 yr, excellent opportunities to screen drugs against AD have been provided by animal models of the disease. Because even in the fastest model, AD pathology does not start before the end of the second month, it has been necessary to wait at least until that age to inject drugs into the animal to assess whether they prevent, reduce, or revert synaptic impairment, plaque formation, and increase of beta-amyloid (Abeta) levels, the main features of the disease. A solution to the problems mentioned above is achieved by the present fast, efficient, and reproducible cultured cell system from animal models of AD or Abeta-associated diseases, for the screening and testing of compounds for the treatment and therapy of AD or Abeta-associated diseases. Copyright 2004 Humana Press Inc.

  19. Dynamics of synthetic drugs transmission model with psychological addicts and general incidence rate

    Science.gov (United States)

    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.

  20. Prediction models for drug-induced hepatotoxicity by using weighted molecular fingerprints

    OpenAIRE

    Kim, Eunyoung; Nam, Hojung

    2017-01-01

    Background Drug-induced liver injury (DILI) is a critical issue in drug development because DILI causes failures in clinical trials and the withdrawal of approved drugs from the market. There have been many attempts to predict the risk of DILI based on in vivo and in silico identification of hepatotoxic compounds. In the current study, we propose the in silico prediction model predicting DILI using weighted molecular fingerprints. Results In this study, we used 881 bits of molecular fingerpri...

  1. 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.

  2. Mathematical model to analyze the dissolution behavior of metastable crystals or amorphous drug accompanied with a solid-liquid interface reaction.

    Science.gov (United States)

    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

  3. A Multiquantum State-to-State Model for the Fundamental States of Air: The Stellar Database

    Science.gov (United States)

    Lino da Silva, M.; Lopez, B.; Guerra, V.; Loureiro, J.

    2012-12-01

    We present a detailed database of vibrationally specific heavy-impact multiquantum rates for transitions between the fundamental states of neutral air species (N2 , O2 , NO, N and O). The most up-to-date datasets for atom- diatom collisions are firstly selected from the literature, scaled to accurate vibrational levels manifolds obtained using realistic intramolecular potentials, and extrapolated to high temperatures when necessary. For diatom-diatom collisions, vibrationally specific rates are produced using the Forced Harmonic Oscillator theory. An adequate manifold of vibrational levels is obtained from an accurate intermolecular potential, and available intermolecular potentials are approximated by a simplified Morse isotropic potential, or assumed through scaling of similar potentials otherwise. The database state-specific rates are valid for a large temperature range of low to very high temperatures, making it suitable for applications such as the modeling of high-enthalpy plasma sources or atmospheric entry applications. As experimentally determined state-specific rates are scarce, specially at high temperatures, emphasis has rather been put into verifying that the obtained rates are physically consistent, and verifying that they scale within the bounds of equilibrium rates available in the literature. The STELLAR database provides a complete and adequate set of heavy-impact rates for vibrational excitation, exchange, dissociation and recombination rates which can then be coupled to more detailed datasets for the simulation of physical-chemical processes in high-temperature plasmas. An application to the dissociation and exchange processes occurring behind an hypersonic shock wave are also presented in this work.

  4. Why European and United States drug regulators are not speaking with one voice on anti-influenza drugs: regulatory review methodologies and the importance of 'deep' product reviews.

    Science.gov (United States)

    Mulinari, Shai; Davis, Courtney

    2017-11-09

    Relenza represents the first neuraminidase inhibitor (NI), a class of drugs that also includes the drug Tamiflu. Although heralded as breakthrough treatments in influenza, NI efficacy has remained highly controversial. A key unsettled question is why the United States Food and Drug Administration (FDA) has approved more cautious efficacy statements in labelling than European regulators for both drugs. We conducted a qualitative analysis of United States and European Union regulatory appraisals for Relenza to investigate the reasons for divergent regulatory interpretations, pertaining to Relenza's capacity to alleviate symptoms and reduce frequency of complications of influenza. In Europe, Relenza was evaluated via the so-called national procedure with Sweden as the reference country. We show that FDA reviewers, unlike their European (i.e. Swedish) counterpart, (1) rejected the manufacturer's insistence on pooling efficacy data, (2) remained wary of subgroup analyses, and (3) insisted on stringent statistical analyses. These differences meant that the FDA was less likely to depart from prevailing regulatory and scientific standards in interpreting trial results. We argue that the differences are explained largely by divergent institutionalised review methodologies, i.e. the European regulator's reliance on manufacturer-compiled summaries compared to the FDA's examination of original data and documentation from trials. The FDA's more probing and meticulous evaluative methodology allowed its reviewers to develop 'deep' knowledge concerning the clinical and statistical facets of trials, and more informed opinions regarding suitable methods for analysing trial results. These findings challenge the current emphasis on evaluating regulatory performance mainly in terms of speed of review. We propose that persistent uncertainty and knowledge deficits regarding NIs could have been ameliorated had regulators engaged in the public debates over the drugs' efficacy and

  5. 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.

  6. Predicting Drug Response in Human Prostate Cancer from Preclinical Analysis of In Vivo Mouse Models.

    Science.gov (United States)

    Mitrofanova, Antonina; Aytes, Alvaro; Zou, Min; Shen, Michael M; Abate-Shen, Cory; Califano, Andrea

    2015-09-29

    Although genetically engineered mouse (GEM) models are often used to evaluate cancer therapies, extrapolation of such preclinical data to human cancer can be challenging. Here, we introduce an approach that uses drug perturbation data from GEM models to predict drug efficacy in human cancer. Network-based analysis of expression profiles from in vivo treatment of GEM models identified drugs and drug combinations that inhibit the activity of FOXM1 and CENPF, which are master regulators of prostate cancer malignancy. Validation of mouse and human prostate cancer models confirmed the specificity and synergy of a predicted drug combination to abrogate FOXM1/CENPF activity and inhibit tumorigenicity. Network-based analysis of treatment signatures from GEM models identified treatment-responsive genes in human prostate cancer that are potential biomarkers of patient response. More generally, this approach allows systematic identification of drugs that inhibit tumor dependencies, thereby improving the utility of GEM models for prioritizing drugs for clinical evaluation. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

  7. EPR studies of intermolecular interactions and competitive binding of drugs in a drug-BSA binding model.

    Science.gov (United States)

    Akdogan, Y; Emrullahoglu, M; Tatlidil, D; Ucuncu, M; Cakan-Akdogan, G

    2016-08-10

    Understanding intermolecular interactions between drugs and proteins is very important in drug delivery studies. Here, we studied different binding interactions between salicylic acid and bovine serum albumin (BSA) using electron paramagnetic resonance (EPR) spectroscopy. Salicylic acid was labeled with a stable radical (spin label) in order to monitor its mobilized (free) or immobilized (bound to BSA) states. In addition to spin labeled salicylic acid (SL-salicylic acid), its derivatives including SL-benzoic acid, SL-phenol, SL-benzene, SL-cyclohexane and SL-hexane were synthesized to reveal the effects of various drug binding interactions. EPR results of these SL-molecules showed that hydrophobic interaction is the main driving force. Whereas each of the two functional groups (-COOH and -OH) on the benzene ring has a minute but detectable effect on the drug-protein complex formation. In order to investigate the effect of electrostatic interaction on drug binding, cationic BSA (cBSA) was synthesized, altering the negative net charge of BSA to positive. The salicylic acid loading capacity of cBSA is significantly higher compared to that of BSA, indicating the importance of electrostatic interaction in drug binding. Moreover, the competitive binding properties of salicylic acid, ibuprofen and aspirin to BSA were studied. The combined EPR results of SL-salicylic acid/ibuprofen and SL-ibuprofen/salicylic acid showed that ibuprofen is able to replace up to ∼83% of bound SL-salicylic acid, and salicylic acid can replace only ∼14% of the bound SL-ibuprofen. This indicates that ∼97% of all salicylic acid and ibuprofen binding sites are shared. On the other hand, aspirin replaces only ∼23% of bound SL-salicylic acid, and salicylic acid replaces ∼50% of bound SL-aspirin, indicating that ∼73% of all salicylic acid and aspirin binding sites are shared. These results show that EPR spectroscopy in combination with the spin labeling technique is a very powerful

  8. A pharmacokinetic model of drug-drug interaction between clopidogrel and omeprazole at CYP2C19 in humans.

    Science.gov (United States)

    Tangamornsuksan, Wimonchat; Thiansupornpong, Pongpak; Morasuk, Thirawut; Lohitnavy, Ornrat; Lohitnavy, Manupat

    2017-07-01

    Clopidogrel is a thienopryridine antiplatelet agent commonly used in the management of cardiovascular diseases. Clopidogrel is metabolized by hepatic CYP2C19 and CYP2B6, therefore, co-administration of clopidogrel and CYP2C19 inhibitors can alter pharmacokinetics of clopidogrel. Omeprazole is a proton pump inhibitor used for decreasing gastric acid production. Omeprazole is known to be a potent inhibitor of CYP2C19. Thus when the drugs are simultaneously administered, clopidogrel plasma concentration levels can be increased. However, plasma levels of the active metabolite of clopidogrel can be significantly decreased, thereby, its antiplatelet activity is reduced. We aimed to develop a mathematical model describing a drug-drug interaction between clopidogrel and omeprazole in humans. Searching for pharmacokinetic interaction studies between clopidogrel and omeprazole in humans was performed in PubMed. Six studies were selected into our modeling purposes to develop 3 mathematical models (i.e. 4 studies for clopidogrel alone, 1 study for omeprazole alone and 1 study for clopidogrel-omeprazole interaction). Subsequently, concentration-time course data from the selected studies were extracted. Computer codes and simulations were performed using the Advanced Continuous Simulating Language Extreme (ACSLX) program. We successfully developed 3 mathematical models which are able to describe all of the datasets. Our clopidogrel-omeprazole pharmacokinetic interaction model with a description of competitive inhibition at CYP2C19 could successfully describe concentration-time courses from the selected datasets. Our interaction model may be useful in predicting plasma levels of clopidogrel and its active metabolite.

  9. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis

    NARCIS (Netherlands)

    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

  10. Modeling the economic outcomes of immuno-oncology drugs: alternative model frameworks to capture clinical outcomes

    Directory of Open Access Journals (Sweden)

    Gibson EJ

    2018-03-01

    Full Text Available EJ Gibson,1 N Begum,1 I Koblbauer,1 G Dranitsaris,2 D Liew,3 P McEwan,4 AA Tahami Monfared,5,6 Y Yuan,7 A Juarez-Garcia,7 D Tyas,8 M Lees9 1Wickenstones Ltd, Didcot, UK; 2Augmentium Pharma Consulting Inc, Toronto, ON, Canada; 3Department of Epidemiology and Preventive Medicine, Alfred Hospital, Monash University, Melbourne, VIC, Australia; 4Health Economics and Outcomes Research Ltd, Cardiff, UK; 5Bristol-Myers Squibb Canada, Saint-Laurent, QC Canada; 6Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, QC, Canada; 7Bristol-Myers Squibb, Princeton, NJ, USA; 8Bristol-Myers Squibb, Uxbridge, UK; 9Bristol-Myers Squibb, Rueil-Malmaison, France Background: 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. Materials and methods: 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. Results: 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%. Conclusion: Increased sophistication in the representation of disease dynamics in economic models

  11. Searching for Drug Synergy in Complex Dose-Response Landscapes Using an Interaction Potency Model.

    Science.gov (United States)

    Yadav, Bhagwan; Wennerberg, Krister; Aittokallio, Tero; Tang, Jing

    2015-01-01

    Rational design of multi-targeted drug combinations is a promising strategy to tackle the drug resistance problem for many complex disorders. A drug combination is usually classified as synergistic or antagonistic, depending on the deviation of the observed combination response from the expected effect calculated based on a reference model of non-interaction. The existing reference models were proposed originally for low-throughput drug combination experiments, which make the model assumptions often incompatible with the complex drug interaction patterns across various dose pairs that are typically observed in large-scale dose-response matrix experiments. To address these limitations, we proposed a novel reference model, named zero interaction potency (ZIP), which captures the drug interaction relationships by comparing the change in the potency of the dose-response curves between individual drugs and their combinations. We utilized a delta score to quantify the deviation from the expectation of zero interaction, and proved that a delta score value of zero implies both probabilistic independence and dose additivity. Using data from a large-scale anticancer drug combination experiment, we demonstrated empirically how the ZIP scoring approach captures the experimentally confirmed drug synergy while keeping the false positive rate at a low level. Further, rather than relying on a single parameter to assess drug interaction, we proposed the use of an interaction landscape over the full dose-response matrix to identify and quantify synergistic and antagonistic dose regions. The interaction landscape offers an increased power to differentiate between various classes of drug combinations, and may therefore provide an improved means for understanding their mechanisms of action toward clinical translation.

  12. Searching for Drug Synergy in Complex Dose–Response Landscapes Using an Interaction Potency Model

    Science.gov (United States)

    Yadav, Bhagwan; Wennerberg, Krister; Aittokallio, Tero; Tang, Jing

    2015-01-01

    Rational design of multi-targeted drug combinations is a promising strategy to tackle the drug resistance problem for many complex disorders. A drug combination is usually classified as synergistic or antagonistic, depending on the deviation of the observed combination response from the expected effect calculated based on a reference model of non-interaction. The existing reference models were proposed originally for low-throughput drug combination experiments, which make the model assumptions often incompatible with the complex drug interaction patterns across various dose pairs that are typically observed in large-scale dose–response matrix experiments. To address these limitations, we proposed a novel reference model, named zero interaction potency (ZIP), which captures the drug interaction relationships by comparing the change in the potency of the dose–response curves between individual drugs and their combinations. We utilized a delta score to quantify the deviation from the expectation of zero interaction, and proved that a delta score value of zero implies both probabilistic independence and dose additivity. Using data from a large-scale anticancer drug combination experiment, we demonstrated empirically how the ZIP scoring approach captures the experimentally confirmed drug synergy while keeping the false positive rate at a low level. Further, rather than relying on a single parameter to assess drug interaction, we proposed the use of an interaction landscape over the full dose–response matrix to identify and quantify synergistic and antagonistic dose regions. The interaction landscape offers an increased power to differentiate between various classes of drug combinations, and may therefore provide an improved means for understanding their mechanisms of action toward clinical translation. PMID:26949479

  13. A drug cost model for injuries due to road traffic accidents.

    Directory of Open Access Journals (Sweden)

    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.

  14. A comparative legal analysis of social media advertising of drugs in Germany and the United States.

    Science.gov (United States)

    Buechner, Bianca

    2013-01-01

    Pharmaceutical companies use social media such as Facebook and Twitter more and more to advertise their products. Advertising of medicinal products especially in social media is a critical issue confronting patient protection, competition law and ethical concerns in direct-to-consumer advertising. Advertising in the World Wide Web must take into account national and international regulations, depending on which user from which country will have access to the information posted. Different legal requirements, if any, regulate the advertising of medicinal products. This paper discusses, challenges and compares the requirements and regulations of advertising medicinal products in social media, such as Facebook, in the United States on a federal level and the European Union with Germany as a reference Member State. Social media are very active and fast moving. Therefore, it is challenging and necessary at the same time to set guidelines and regulations for the use of social media in drug advertising. This paper is a first step toward promoting an international, consistent approach when talking about regulating advertising of medicinal products in social media.

  15. Comparing State SAT Scores Using a Mixture Modeling Approach

    Science.gov (United States)

    Kim, YoungKoung Rachel

    2009-01-01

    Presented at the national conference for AERA (American Educational Research Association) in April 2009. The large variability of SAT taker population across states makes state-by-state comparisons of the SAT scores challenging. Using a mixture modeling approach, therefore, the current study presents a method of identifying subpopulations in terms…

  16. Discrete versus continuous state switching models for portfolio credit risk

    NARCIS (Netherlands)

    Lucas, A.; Klaassen, P.

    2006-01-01

    Dynamic models for credit rating transitions are important ingredients for dynamic credit risk analyses. We compare the properties of two such models that have recently been put forward. The models mainly differ in their treatment of systematic risk, which can be modeled either using discrete states

  17. Bayesian variable order Markov models: Towards Bayesian predictive state representations

    NARCIS (Netherlands)

    Dimitrakakis, C.

    2009-01-01

    We present a Bayesian variable order Markov model that shares many similarities with predictive state representations. The resulting models are compact and much easier to specify and learn than classical predictive state representations. Moreover, we show that they significantly outperform a more

  18. Likelihood functions for state space models with diffuse initial conditions

    NARCIS (Netherlands)

    Koopman, S.J.; Shephard, N.; de Vos, A.F.

    2010-01-01

    State space models with non-stationary processes and/or fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time-series models with diffuse initial conditions. In this article, we consider

  19. Likelihood functions for state space models with diffuse initial conditions

    NARCIS (Netherlands)

    Francke, M.K.; Koopmans, S.J.; de Vos, A.F.

    2008-01-01

    State space models with nonstationary processes and fixed regression effects require a state vector with diffuse initial conditions. Different likelihood functions can be adopted for the estimation of parameters in time series models with diffuse initial conditions. In this paper we consider

  20. Mathematical Modeling and Experimental Validation of Nanoemulsion-Based Drug Transport across Cellular Barriers.

    Science.gov (United States)

    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.

  1. How Preclinical Models Evolved to Resemble the Diagnostic Criteria of Drug Addiction.

    Science.gov (United States)

    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.

  2. Evaluation and modeling of the eutectic composition of various drug-polyethylene glycol solid dispersions.

    Science.gov (United States)

    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.

  3. Mathematical modeling analysis of intratumoral disposition of anticancer agents and drug delivery systems.

    Science.gov (United States)

    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.

  4. Effects of chronic administration of drugs of abuse on impulsive choice (delay discounting) in animal models.

    Science.gov (United States)

    Setlow, Barry; Mendez, Ian A; Mitchell, Marci R; Simon, Nicholas W

    2009-09-01

    Drug-addicted individuals show high levels of impulsive choice, characterized by preference for small immediate over larger but delayed rewards. Although the causal relationship between chronic drug use and elevated impulsive choice in humans has been unclear, a small but growing body of literature over the past decade has shown that chronic drug administration in animal models can cause increases in impulsive choice, suggesting that a similar causal relationship may exist in human drug users. This article reviews this literature, with a particular focus on the effects of chronic cocaine administration, which have been most thoroughly characterized. The potential mechanisms of these effects are described in terms of drug-induced neural alterations in ventral striatal and prefrontal cortical brain systems. Some implications of this research for pharmacological treatment of drug-induced increases in impulsive choice are discussed, along with suggestions for future research in this area.

  5. Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

    Directory of Open Access Journals (Sweden)

    Lucianna Helene Santos

    2015-11-01

    Full Text Available Reverse transcriptase (RT is a multifunctional enzyme in the human immunodeficiency virus (HIV-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

  6. A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China.

    Science.gov (United States)

    Qi, Chang; Kelly, Brian C; Liao, Yanhui; He, Haoyu; Luo, Tao; Deng, Huiqiong; Liu, Tieqiao; Hao, Wei; Wang, Jichuan

    2015-03-01

    Although evidence exists for distinct barriers to drug abuse treatment (BDATs), investigations of their inter-relationships and the effect of individual characteristics on the barrier factors have been sparse, especially in China. A Multiple Indicators Multiple Causes (MIMIC) model is applied for this target. A sample of 262 drug users were recruited from three drug rehabilitation centers in Hunan Province, China. We applied a MIMIC approach to investigate the effect of gender, age, marital status, education, primary substance use, duration of primary drug use, and drug treatment experience on the internal barrier factors: absence of problem (AP), negative social support (NSS), fear of treatment (FT), and privacy concerns (PC). Drug users of various characteristics were found to report different internal barrier factors. Younger participants were more likely to report NSS (-0.19, p=0.038) and PC (-0.31, pdrug users, ice users were more likely to report AP (0.44, pDrug treatment experiences related to AP (0.20, p=0.012). In addition, differential item functioning (DIF) occurred in three items when participant from groups with different duration of drug use, ice use, or marital status. Individual characteristics had significant effects on internal barriers to drug treatment. On this basis, BDAT perceived by different individuals could be assessed before tactics were utilized to successfully remove perceived barriers to drug treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  7. Modeling solid-state boron carbide low energy neutron detectors

    International Nuclear Information System (INIS)

    Lundstedt, C.; Harken, A.; Day, E.; Robertson, B.W.; Adenwalla, S.

    2006-01-01

    Two independent techniques for modeling boron-based solid-state neutron detectors are presented-one using the GEANT4 Monte Carlo toolkit and the other one an analytical approach using a simplified physical model. Results of these techniques are compared for three different types of solid-state boron carbide detector. These results provide the basis for distinguishing between conversion layer and other solid-state detectors

  8. The continuum shell-model neutron states of Pb

    Indian Academy of Sciences (India)

    even magic core nucleus 208Pb. For the discrete low-lying excited states, the depletion of the shell-model ... nucleon moves. The matrix elements of K(r) has been kept fixed at 50 MeV and this has been discussed in the following section. The shell-model neutron state |j2)has been coupled with the vibrational |λπ)spin state.

  9. Solid-state NMR in the analysis of drugs and naturally occurring materials.

    Science.gov (United States)

    Paradowska, Katarzyna; Wawer, Iwona

    2014-05-01

    This article presents some of the solid-state NMR (SSNMR) techniques used in the pharmaceutical and biomedical research. Solid-state magic angle spinning (MAS) NMR provides structural information on powder amorphous solids for which single-crystal diffraction structures cannot be obtained. NMR is non-destructive; the powder sample may be used for further studies. Quantitative results can be obtained, although solid-state NMR spectra are not normally quantitative. As compared with other techniques, MAS NMR is insensitive and requires a significant amount of the powder sample (2-100mg) to fill the 1.3-7 mm ZrO2 rotor. This is its main drawback, since natural compounds isolated from plants, microorganisms or cell cultures are difficult to obtain in quantities higher than a few milligrams. Multinuclear MAS NMR routinely uses (1)H and (13)C nuclei, less frequently (15)N, (19)F, (31)P, (77)Se, (29)Si, (43)Ca or (23)Na. The article focuses on the pharmaceutical applications of SSNMR, the studies were aimed to control over manufacturing processes (e.g. crystallization and milling) investigation of chemical and physical stability of solid forms both as pure drug and in a formulated product. SSNMR is used in combination with some other analytical methods (DSC, XRD, FT-IR) and theoretical calculations of NMR parameters. Biologically active compounds, such as amino acids and small peptides, steroids and flavonoids were studied by SSNMR methods (part 4) providing valuable structural information. The SSNMR experiments performed on biopolymers and large natural products like proteins, cellulose and lipid layers are commented upon briefly in part 5. Copyright © 2013 Elsevier B.V. All rights reserved.

  10. Embedding a State Space Model Into a Markov Decision Process

    DEFF Research Database (Denmark)

    Nielsen, Lars Relund; Jørgensen, Erik; Højsgaard, Søren

    2011-01-01

    In agriculture Markov decision processes (MDPs) with finite state and action space are often used to model sequential decision making over time. For instance, states in the process represent possible levels of traits of the animal and transition probabilities are based on biological models...... estimated from data collected from the animal or herd. State space models (SSMs) are a general tool for modeling repeated measurements over time where the model parameters can evolve dynamically. In this paper we consider methods for embedding an SSM into an MDP with finite state and action space. Different...... ways of discretizing an SSM are discussed and methods for reducing the state space of the MDP are presented. An example from dairy production is given...

  11. Drug and Vaccine Evaluation in the Human Aotus Plasmodium Falciparum Model

    National Research Council Canada - National Science Library

    Obaldia

    2002-01-01

    The purpose of this report is to present data on the evaluation of drugs and vaccines in the human malaria/Aotus lemurinus lemurinus monkey model experimentally infected with Plasmodium falciparum or vivax...

  12. Dynamic Fluorescence Microscopy of Cellular Uptake of Intercalating Model Drugs by Ultrasound-Activated Microbubbles

    NARCIS (Netherlands)

    Lammertink, B.H.A.; Deckers, R.; Derieppe, M.; De Cock, I.; Lentacker, I.; Storm, G.; Moonen, C. T.W.; Bos, C.

    2017-01-01

    Purpose: The combination of ultrasound and microbubbles can facilitate cellular uptake of (model) drugs via transient permeabilization of the cell membrane. By using fluorescent molecules, this process can be studied conveniently with confocal fluorescence microscopy. This study aimed to investigate

  13. The War Against Drug Producers

    OpenAIRE

    Herschel I. Grossman; Daniel Mejia

    2005-01-01

    This paper develops a model of a war against the producers of illegal hard drugs. This war occurs on two fronts. First, to prevent the cultivation of crops that are the raw material for producing drugs the state engages the drug producers in conflict over the control of arable land. Second, to impede further the production and exportation of drugs the state attempts to eradicate crops and to interdict drug shipments. The model also includes an interested outsider who uses both a stick and a c...

  14. The evolving landscape of drug products containing nanomaterials in the United States

    Science.gov (United States)

    D'Mello, Sheetal R.; Cruz, Celia N.; Chen, Mei-Ling; Kapoor, Mamta; Lee, Sau L.; Tyner, Katherine M.

    2017-07-01

    The Center for Drug Evaluation and Research (CDER) within the US Food and Drug Administration (FDA) is tracking the use of nanotechnology in drug products by building and interrogating a technical profile of products containing nanomaterials submitted to CDER. In this Analysis, data from more than 350 products show an increase in the submissions of drug products containing nanomaterials over the last two decades. Of these, 65% are investigational new drugs, 17% are new drug applications and 18% are abbreviated new drug applications, with the largest class of products being liposomal formulations intended for cancer treatments. Approximately 80% of products have average particle sizes of 300 nm or lower. This analysis identifies several trends in the development of drug products containing nanomaterials, including the relative rate of approvals of these products, and provides a comprehensive overview on the landscape of nanotechnology application in medicine.

  15. Modeling and implementing a database on drugs into a hospital intranet.

    Science.gov (United States)

    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.

  16. [Health care models for users of alcohol and other drugs: political discourse, knowledge, and practices].

    Science.gov (United States)

    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.

  17. Modeling of drug delivery into tissues with a microneedle array using mixture theory.

    Science.gov (United States)

    Zhang, Rumi; Zhang, Peiyu; Dalton, Colin; Jullien, Graham A

    2010-02-01

    In this paper, we apply mixture theory to quantitatively predict the transient behavior of drug delivery by using a microneedle array inserted into tissue. In the framework of mixture theory, biological tissue is treated as a multi-phase fluid saturated porous medium, where the mathematical behavior of the tissue is characterized by the conservation equations of multi-phase models. Drug delivery by microneedle array imposes additional requirements on the simulation procedures, including drug absorption by the blood capillaries and tissue cells, as well as a moving interface along its flowing pathway. The contribution of this paper is to combine mixture theory with the moving mesh methods in modeling the transient behavior of drug delivery into tissue. Numerical simulations are provided to obtain drug concentration distributions into tissues and capillaries.

  18. Adaptive Landscape by Environment Interactions Dictate Evolutionary Dynamics in Models of Drug Resistance

    Science.gov (United States)

    Ogbunugafor, C. Brandon; Wylie, C. Scott; Diakite, Ibrahim; Weinreich, Daniel M.; Hartl, Daniel L.

    2016-01-01

    regards to their basic contribution to the study of empirical adaptive landscapes, and in terms of how they inform new models for the evolution of drug resistance. PMID:26808374

  19. 75 FR 17418 - Memorandum of Understanding Between the Food and Drug Administration, United States Department of...

    Science.gov (United States)

    2010-04-06

    ... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2010-N-0004... Human Services and the National Alliance for Hispanic Health AGENCY: Food and Drug Administration, HHS... understanding (MOU) between the Food and Drug Administration, U.S. Department of Health and Human Services and...

  20. Parallel monitoring of plasma and intraluminal drug concentrations in man after oral administration of fosamprenavir in the fasted and fed state.

    Science.gov (United States)

    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.

  1. Minimal model for spoof acoustoelastic surface states

    DEFF Research Database (Denmark)

    Christensen, Johan; Liang, Z.; Willatzen, Morten

    2014-01-01

    Similar to textured perfect electric conductors for electromagnetic waves sustaining artificial or spoof surface plasmons we present an equivalent phenomena for the case of sound. Aided by a minimal model that is able to capture the complex wave interaction of elastic cavity modes and airborne...... sound radiation in perfect rigid panels, we construct designer acoustoelastic surface waves that are entirely controlled by the geometrical environment. Comparisons to results obtained by full-wave simu- lations confirm the feasibility of the model and we demonstrate illustrative examples...

  2. Four-quark states in potential model

    International Nuclear Information System (INIS)

    Badalyan, A.M.; Kitoroage, D.I.

    1987-01-01

    The mass spectrum of S-wave q 2 q -2 mesons of u, d, s quarks is calculated in the framework of the nonrelativistic potential model and compared with the bag model predictions. The spin-spin splittings of almost all four-quark mesons with J PC = 0 ++ , 2 ++ , 1 +- are shown to coincide with an accuracy of ∼ 50 MeV in both approaches. Two exceptions are O S (9), C π S (9) mesons for which the discrepancy is ∼ 300 MeV. Calculated centers of gravity of the multiplets are systematically ∼ 120 MeV higher than the MIT bag predictions

  3. Modeling new XYZ states at JPAC

    Energy Technology Data Exchange (ETDEWEB)

    Pilloni, Alessandro [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2016-12-01

    The observation of the unexpected XYZP resonances has challenged the usual heavy quarkonium framework. One of the most studied exotic states, the X(3872), happens to be copiously produced in high-energy hadron collisions. We discuss how this large prompt production cross-section, together with the comparison with light nuclei production data, disfavors a loosely-bound molecule interpretation, and calls for a new interpretation for the exotic hadron resonances. We also present the research of the Joint Physics Analysis Center in Hadron Spectroscopy.

  4. A mechanism-based pharmacokinetic model of fenofibrate for explaining increased drug absorption after food consumption.

    Science.gov (United States)

    Back, Hyun-Moon; Song, Byungjeong; Pradhan, Sudeep; Chae, Jung-Woo; Han, Nayoung; Kang, Wonku; Chang, Min Jung; Zheng, Jiao; Kwon, Kwang-Il; Karlsson, Mats O; Yun, Hwi-Yeol

    2018-01-25

    Oral administration of drugs is convenient and shows good compliance but it can be affected by many factors in the gastrointestinal (GI) system. Consumption of food is one of the major factors affecting the GI system and consequently the absorption of drugs. The aim of this study was to develop a mechanistic GI absorption model for explaining the effect of food on fenofibrate pharmacokinetics (PK), focusing on the food type and calorie content. Clinical data from a fenofibrate PK study involving three different conditions (fasting, standard meals and high-fat meals) were used. The model was developed by nonlinear mixed effect modeling method. Both linear and nonlinear effects were evaluated to explain the impact of food intake on drug absorption. Similarly, to explain changes in gastric emptying time for the drug due to food effects was evaluated. The gastric emptying rate increased by 61.7% during the first 6.94 h after food consumption. Increased calories in the duodenum increased the absorption rate constant of the drug in fed conditions (standard meal = 16.5%, high-fat meal = 21.8%) compared with fasted condition. The final model displayed good prediction power and precision. A mechanistic GI absorption model for quantitatively evaluating the effects of food on fenofibrate absorption was successfully developed, and acceptable parameters were obtained. The mechanism-based PK model of fenofibrate can quantify the effects of food on drug absorption by food type and calorie content.

  5. Solid lipid particles for oral delivery of peptide and protein drugs III - the effect of fed state conditions on the in vitro release and degradation of desmopressin

    DEFF Research Database (Denmark)

    Christophersen, Philip C; Vaghela, Dimple; Müllertz, Anette

    2014-01-01

    of oleic acid glycerides accelerated the release of desmopressin significantly from all solid lipid particles both in the presence and absence of lipase. The presence of oleic acid glycerides also reduced the degradation rate of desmopressin, probably due to the interactions between the lipids......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...

  6. From Heuristic to Mathematical Modeling of Drugs Dissolution Profiles: Application of Artificial Neural Networks and Genetic Programming

    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.

  7. Implant-assisted magnetic drug targeting in permeable microvessels: Comparison of two-fluid statistical transport model with experiment

    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.

  8. Ground state configurations in two-mode quantum Rabi models

    Science.gov (United States)

    Chilingaryan, Suren; Rodríguez-Lara, B. M.

    We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal configuration. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited. S A Chilingaryan acknowledges financial support from CONACYT.

  9. Mining FDA drug labels using an unsupervised learning technique--topic modeling.

    Science.gov (United States)

    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

  10. Mining FDA drug labels using an unsupervised learning technique - topic modeling

    Science.gov (United States)

    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

  11. Comparing exponential and exponentiated models of drug demand in cocaine users.

    Science.gov (United States)

    Strickland, Justin C; Lile, Joshua A; Rush, Craig R; Stoops, William W

    2016-12-01

    Drug purchase tasks provide rapid and efficient measurement of drug demand. Zero values (i.e., prices with zero consumption) present a quantitative challenge when using exponential demand models that exponentiated models may resolve. We aimed to replicate and advance the utility of using an exponentiated model by demonstrating construct validity (i.e., association with real-world drug use) and generalizability across drug commodities. Participants (N = 40 cocaine-using adults) completed Cocaine, Alcohol, and Cigarette Purchase Tasks evaluating hypothetical consumption across changes in price. Exponentiated and exponential models were fit to these data using different treatments of zero consumption values, including retaining zeros or replacing them with 0.1, 0.01, or 0.001. Excellent model fits were observed with the exponentiated model. Means and precision fluctuated with different replacement values when using the exponential model but were consistent for the exponentiated model. The exponentiated model provided the strongest correlation between derived demand intensity (Q0) and self-reported free consumption in all instances (Cocaine r = .88; Alcohol r = .97; Cigarette r = .91). Cocaine demand elasticity was positively correlated with alcohol and cigarette elasticity. Exponentiated parameters were associated with real-world drug use (e.g., weekly cocaine use) whereas these correlations were less consistent for exponential parameters. Our findings show that selection of zero replacement values affects demand parameters and their association with drug-use outcomes when using the exponential model but not the exponentiated model. This work supports the adoption of the exponentiated demand model by replicating improved fit and consistency and demonstrating construct validity and generalizability. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  12. Reliability state space model of Power Transformer

    OpenAIRE

    REENA JHARANIYA; M.AHFAZ KHAN

    2011-01-01

    In electrical power network, transformer is one of the most important electrical equipment in power system, which running status is directly concerned with the reliability of power system. Reliability of a power system is considerably influenced by its equipments. Power transformers are one of the most critical and expensive equipments of a power system and their proper functions are vital for the substations and utilities .Therefore, reliability model of power transformer is very important i...

  13. Potential Exposure to Anti-Drug Advertising and Drug-Related Attitudes, Beliefs, and Behaviors among United States Youth, 1995-2006

    Science.gov (United States)

    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

  14. Potential exposure to anti-drug advertising and drug-related attitudes, beliefs, and behaviors among United States youth, 1995-2006.

    Science.gov (United States)

    Terry-McElrath, Yvonne M; Emery, Sherry; Szczypka, Glen; Johnston, Lloyd D

    2011-01-01

    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 to 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 the 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. Copyright © 2010 Elsevier Ltd. All rights reserved.

  15. Vibrational spectroscopy modeling of a drug in molecular solvents and enzymes

    Science.gov (United States)

    Devereux, Christian J.; Fulfer, Kristen D.; Zhang, Xiaoliu; Kuroda, Daniel G.

    2017-09-01

    Modeling of drugs in enzymes is of immensurable value to many areas of science. We present a theoretical study on the vibrational spectroscopy of Rilpivirine, a HIV reverse transcriptase inhibitor, in conventional solvents and in clinically relevant enzymes. The study is based on vibrational spectroscopy modeling of the drug using molecular dynamics simulations, DFT frequency maps, and theory. The modeling of the infrared lineshape shows good agreement with experimental data for the drug in molecular solvents where the local environment motions define the vibrational band lineshape. On the other hand, the theoretical description of the drug in the different enzymes does not match previous experimental findings indicating that the utilized methodology might not apply to heterogeneous environments. Our findings show that the lack of reproducibility might be associated with the development of the frequency map which does not contain all of the possible interactions observed in such systems.

  16. The liberal state and the rogue agency: FDA’s regulation of drugs for mood disorders, 1950s–1970s☆

    Science.gov (United States)

    Shorter, Edward

    2013-01-01

    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. PMID:18343498

  17. The liberal state and the rogue agency: FDA's regulation of drugs for mood disorders, 1950s-1970s.

    Science.gov (United States)

    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.

  18. Monitoring alert and drowsy states by modeling EEG source nonstationarity

    Science.gov (United States)

    Hsu, Sheng-Hsiou; Jung, Tzyy-Ping

    2017-10-01

    Objective. As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. Approach. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Main results. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  ‑0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. Significance. This ICA-based framework provides a new way to study changes of brain states and can be applied to

  19. A drug cost model for injuries due to road traffic accidents.

    Science.gov (United States)

    Riewpaiboon, Arthorn; Piyauthakit, Piyanuch; Srijariya, Witsanuchai; Chaikledkaew, Usa

    2008-01-01

    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. 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. 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 R (2) 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 (pcost 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. 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.

  20. Animal models of pain and migraine in drug discovery

    DEFF Research Database (Denmark)

    Munro, Gordon; Jansen-Olesen, Inger; Olesen, Jes

    2017-01-01

    Preclinical research activities in relation to pain typically involve the 'holy trinity' of nociceptive, inflammatory and neuropathic pain for purposes of target validation and defining target product profiles of novel analgesic compounds. For some reason it seems that headache or migraine...... are rarely considered as additional entities to explore. Frontline medications used in the treatment of, for example, inflammatory pain, neuropathic pain and migraine (NSAIDs versus pregabalin/duloxetine versus triptans) reveal distinct differences in pathophysiology that partially explain this approach....... Nevertheless, for many patients enduring chronic pain, regardless of aetiology, high unmet needs remain. By focusing more on commonalities shared between neuropathic pain and headache disorders such as migraine, drug discovery efforts could be spread more efficiently across a larger indication area. Here, some...

  1. Estimation methods for nonlinear state-space models in ecology

    DEFF Research Database (Denmark)

    Pedersen, Martin Wæver; Berg, Casper Willestofte; Thygesen, Uffe Høgsbro

    2011-01-01

    The use of nonlinear state-space models for analyzing ecological systems is increasing. A wide range of estimation methods for such models are available to ecologists, however it is not always clear, which is the appropriate method to choose. To this end, three approaches to estimation in the theta...... Markov model (HMM). The second method uses the mixed effects modeling and fast numerical integration framework of the AD Model Builder (ADMB) open-source software. The third alternative is to use the popular Bayesian framework of BUGS. The study showed that state and parameter estimation performance...

  2. State of the Art Review and Report of New Tool for Drug Discovery.

    Science.gov (United States)

    Martinez-Lopez, Yoan; Caballero, Yaile; Barigye, Stephen J; Marrero-Ponce, Yovani; Millan-Cabrera, Reisel; Madera, Julio; Torrens, Francisco; Castillo-Garit, Juan A

    2017-01-01

    There are a great number of tools that can be used in QSAR/QSPR studies; they are implemented in several programs that are reviewed in this report. The usefulness of new tools can be proved through comparison, with previously published approaches. In order to perform the comparison, the most usual is the use of several benchmark datasets such as DRAGON and Sutherland's datasets. Here, an exploratory study of Atomic Weighted Vectors (AWVs), a new tool useful for drug discovery using different datasets, is presented. In order to evaluate the performance of the new tool, several statistics and QSAR/QSPR experiments are performed. Variability analyses are used to quantify the information content of the AWVs obtained from the tool, by means of an information theory-based algorithm. Principal components analysis is used to analyze the orthogonality of these descriptors, for which the new MDs from AWVs provide different information from those codified by DRAGON descriptors (0-2D). The QSAR models are obtained for every Sutherland's dataset, according to the original division into training/test sets, by means of the multiple linear regression with genetic algorithm (MLR-GA). These models have been validated and compared favorably to several previously published approaches, using the same benchmark datasets. The obtained results show that this tool should be a useful strategy for the QSAR/QSPR studies, despite its simplicity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Shock state: an unrecognized and underestimated presentation of drug reaction with eosinophilia and systemic symptoms.

    Science.gov (United States)

    Kimmoun, Antoine; Dubois, Elsa; Perez, Pierre; Barbaud, Annick; Levy, Bruno

    2013-11-01

    Some patients with drug reaction with eosinophilia and systemic symptoms (DRESS) are probably admitted in intensive care unit (ICU), but data concerning their clinical features at admission are scarce. Therefore, in the present study, we used a clinical network of French intensivists to study the clinical features and evolution of DRESS patients hospitalized in ICU. A national, retrospective, multicenter study collected DRESS cases hospitalized in ICU for DRESS from 2000 to end of 2011. All files were analyzed through the RegiSCAR scoring system as "no," "possible," "probable," or "definite" DRESS. Patients were included only if they had a probable or definite DRESS. Demographic, hemodynamic, biological, and infectious data were recorded. Twenty-one patients were included. Hospital mortality was 10 (47%) of 21, and 16 of 21 patients had on admission a shock state necessitating vasopressor agents. Echocardiographic ejection fraction in shock patients was depressed (47% ± 13%). Mechanical ventilation was required in 13 of 21 cases. Hepatic failure was observed in 11 of 21 cases, acute renal failure in 18 of 20 cases, and lactic acidosis in 12 of 20 patients. Initial bacteriology was negative in all patients. Human herpesvirus reactivations were found in five of 15 cases. In conclusion, shock without bacteriological documentation associated with multiple organ failure is the most common presentation of DRESS at admission in ICU and is associated with a higher mortality than previously described.

  4. Building New Bridges between In Vitro and In Vivo in Early Drug Discovery: Where Molecular Modeling Meets Systems Biology.

    Science.gov (United States)

    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

  5. Wave Modelling - The State of the Art

    Science.gov (United States)

    2007-09-27

    conservation of wave energy, wave action and wave momentum. The coupling coefficient is given by G(k, k 2 , k 3 , k 4 ) = 97EgDZ(k, k, k3, )(3.5) 4p 2 CO, (0...applications, with a continuous push by the market forces to improve the quality of the results. Since the first order approximation of the historical SMB... market , their use in practical applications is growing and the present limitations of spectral wave modelling in this respect are beginning to be felt. It

  6. Embryonic Zebrafish Model - A Well-Established Method for Rapidly Assessing the Toxicity of Homeopathic Drugs - Toxicity Evaluation of Homeopathic Drugs Using Zebrafish Embryo Model -

    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.

  7. Predicting Oral Drug Absorption: Mini Review on Physiologically-Based Pharmacokinetic Models

    Directory of Open Access Journals (Sweden)

    Louis Lin

    2017-09-01

    Full Text Available Most marketed drugs are administered orally, despite the complex process of oral absorption that is difficult to predict. Oral bioavailability is dependent on the interplay between many processes that are dependent on both compound and physiological properties. Because of this complexity, computational oral physiologically-based pharmacokinetic (PBPK models have emerged as a tool to integrate these factors in an attempt to mechanistically capture the process of oral absorption. These models use inputs from in vitro assays to predict the pharmacokinetic behavior of drugs in the human body. The most common oral PBPK models are compartmental approaches, in which the gastrointestinal tract is characterized as a series of compartments through which the drug transits. The focus of this review is on the development of oral absorption PBPK models, followed by a brief discussion of the major applications of oral PBPK models in the pharmaceutical industry.

  8. Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict

    Science.gov (United States)

    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..

  9. MDMA, Methylone, and MDPV: Drug-Induced Brain Hyperthermia and Its Modulation by Activity State and Environment.

    Science.gov (United States)

    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

  10. Product State Modelling based on a Meta Production

    DEFF Research Database (Denmark)

    Larsen, Michael Holm; Sørensen, Christian; Langer, Gilad

    1999-01-01

    ) is a product model that contains continuously updated data regarding the outcome of the production processes. The main contribution of this paper is a definition and a description of a Production Meta Product State Model (Production Meta PSM), using the Unified Modelling Language (UML). The meta model......As products often deviate from their original design and specifications when being produced, adjustments of the product or process are required in order to meet specifications. A prerequisite for this adjustment, is appropriate and effectively collected shop floor data. The Product State Model (PSM...... incorporates a set of characteristics associated to the (1) scope or application domain of the PSM, (2) the artefact or product, and (3) the events transforming the product and trigging product state changes. Moreover, the paper provides guidelines for a specialisation of the meta model with respect...

  11. Development of a production meta Product State Model

    DEFF Research Database (Denmark)

    Larsen, Michael Holm; Sørensen, Christian; Langer, Gilad

    1999-01-01

    ) is a product model that contains continuously updated data regarding the outcome of the production processes. The main contribution of this paper is a definition and a description of a Production Meta Product State Model (Production Meta PSM), using the Unified Modelling Language (UML). The meta model......As products often deviate from their original design and specifications when being produced, adjustments of the product or process are required in order to meet specifications. A prerequisite for this adjustment, is appropriate and effectively collected shop floor data. The Product State Model (PSM...... incorporates a set of characteristics associated to the (1) scope or application domain of the PSM, (2) the artefact or product, and (3) the events transforming the product and trigging product state changes. Moreover, the paper provides guidelines for a specialisation of the meta model with respect...

  12. Application of PBPK modelling in drug discovery and development at Pfizer.

    Science.gov (United States)

    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.

  13. A systems-based mathematical modelling framework for investigating the effect of drugs on solid tumours

    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.

  14. Drug Policy and the Ultima Ratio in A Social and Democratic State, Spain

    Directory of Open Access Journals (Sweden)

    Alison Hogg

    2013-01-01

    Full Text Available As a Member State of the UN and the EU, Spain's drug policy is heavily conditioned by these external superior ‘legal personalities’. Although, the Spanish legislature has enacted amendments to legislation on illicit substances over the last ten years to attenuate excessively punitive law, their interpretation and internal application of conventions on drug legislation has by in large overlooked the ultima ratio principle i.e. minimum intervention (Arana 2012. Spain’s criminal legislation is presented as well as the consequences of the prohibition of illicit substances in this jurisdiction. Finally, alternatives that have emerged in the Basque Autonomous Community to counter the effects of its criminalisation are briefly discussed and promoted as a means of abating external legal constraints that have serious social and legal ramifications. Como miembro de ONU y UE, la política de drogas española está fuertemente condicionada por la legislación emanada de estas entidades jurídicas. A pesar de eso, los legisladores españoles han introducido reformas en la legislación sobre sustancias ilícitas en los últimos diez años para atenuar una legislación excesivamente punitiva, su interpretación y aplicación interna de convenios sobre legislación en materia de drogas en gran parte no toma en cuenta el principio del ultimo ratio (Arana 2012. Se presenta la legislación penal española en materia de sustancias ilícitas y también los efectos que ésta tiene sobre la jurisdicción. Finalmente, las alternativas surgidas en la Comunidad Autónoma Vasca para contrarrestar los efectos de la criminalización, son brevemente discutidas y promovidas como una manera para amainar las limitaciones jurídicas que tienen importantes y serias ramificaciones sociales y legales. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2200886

  15. Evaluation of drug permeation under fed state conditions using mucus-covered Caco-2 cell epithelium

    DEFF Research Database (Denmark)

    Birch, Ditlev; Diedrichsen, Ragna G; Christophersen, Philip C

    2018-01-01

    The absence of a surface-lining mucus layer is a major pitfall for the Caco-2 epithelial model. However, this can be alleviated by applying biosimilar mucus (BM) to the apical surface of the cell monolayer, thereby constructing a mucosa mimicking in vivo conditions. This study aims to elucidate...... the influence of BM as a barrier towards exogenic compounds such as permeation enhancers, and components of fed state simulated intestinal fluid (FeSSIF). Caco-2 cell monolayers surface-lined with BM were exposed to several compounds with distinct physicochemical properties, and the cell viability...... and permeability of the cell monolayer was compared to that of cell monolayers without BM and well-established mucus-secreting epithelial models (HT29 monolayers and HT29/Caco-2 co-culture monolayers). Exposure of BM-covered cells to constituents from FeSSIF revealed that it comprised a strong, hydrophilic barrier...

  16. 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...

  17. Deep-lying hole states in the optical model

    International Nuclear Information System (INIS)

    Klevansky, S.P.; Lemmer, R.H.

    1982-01-01

    The strength function for deep-lying hole states in an optical potential is studied by the method of Green's functions. The role of isospin is emphasized. It is shown that, while the main trends of the experimental data on hole states in isotopes of Sn and Pd can be described by an energy independent optical potential, intermediate structures in these data indicate the specific nuclear polarization effects have to be included. This is done by introducing doorway states of good isospin into the optical model potential. Such states consist of neutron hole plus proton core vibrations as well as more complicated excitations that are analog states of proton hole plus neutron core vibrations of the parent nuclear system. Specific calculations for 115 Sn and 103 Pd give satisfactory fits to the strength function data using optical model and doorway state parameters that are reasonable on physical grounds

  18. Computational models to assign biopharmaceutics drug disposition classification from molecular structure.

    Science.gov (United States)

    Khandelwal, Akash; Bahadduri, Praveen M; Chang, Cheng; Polli, James E; Swaan, Peter W; Ekins, Sean

    2007-12-01

    We applied in silico methods to automatically classify drugs according to the Biopharmaceutics Drug Disposition Classification System (BDDCS). Models were developed using machine learning methods including recursive partitioning (RP), random forest (RF) and support vector machine (SVM) algorithms with ChemDraw, clogP, polar surface area, VolSurf and MolConnZ descriptors. The dataset consisted of 165 training and 56 test set molecules. RF model 3, RP model 1, and SVM model 1 can correctly predict 73.1, 63.6 and 78.6% test compounds in classes 1, 2 and 3, respectively. Both RP and SVM models can be used for class 4 prediction. The inclusion of consensus analysis resulted in improved test set predictions for class 2 and 4 drugs. The models can be used to predict BDDCS class for new compounds from molecular structure using readily available molecular descriptors and software, representing an area where in silico approaches could aid the pharmaceutical industry in speeding drugs to the patient and reducing costs. This could have significant applications in drug discovery to identify molecules that may have future developability issues.

  19. 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

  20. 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

  1. A Survey of State Universal Basic Education Board (SUBEB) Model ...

    African Journals Online (AJOL)

    SUBEB) Model Nursery and Primary School Libraries in Ekiti State. How fit are the school libraries to ably play their roles as supporters of schools ' academic programmes? To what extent are the school libraries satisfying the information needs ...

  2. Race/Ethnic Disparities in the Utilization of Treatment for Drug Dependent Inmates in U.S. State Correctional Facilities

    Science.gov (United States)

    Nowotny, Kathryn M.

    2014-01-01

    This study examines race/ethnic disparities in treatment for drug dependent inmates in state correctional facilities. The data come from the 2004 Survey of Inmates in State Correctional Facilities. Fixed effects logistic regression is used to analyze treatment outcomes for 5,180 inmates housed within 286 prisons. The analysis accounts for differences in background characteristics (i.e., age, gender, marital status, foreign born status, veteran status), socioeconomic characteristics (i.e., education, employment prior to incarceration), mental health (i.e., diagnosis with a serious mental illness), and incarceration experiences (i.e., current conviction, previous incarceration episodes, time served, additional sentencing requirements, external social support, disciplinary violations). The findings identify a remarkable unmet need among drug dependent inmates in that less than one-half of drug dependent inmates had received any type of treatment in prison at the time of the interview with the most common treatment type being self-help groups. Compared to whites, drug dependent Latino inmates have significantly lower odds of utilizing treatment, yet there are no significant black-white disparities found. Implications for drug treatment within prisons are discussed. PMID:25270722

  3. A Novel Murine Model for the In Vivo Study of Transdermal Drug Penetration

    Directory of Open Access Journals (Sweden)

    Gábor Eros

    2012-01-01

    Full Text Available Enhancement of the transdermal penetration of different active agents is an important research goal. Our aim was to establish a novel in vivo experimental model which provides a possibility for exact measurement of the quantity of penetrated drug. The experiments were performed on SKH-1 hairless mice. A skin fold in the dorsal region was fixed with two fenestrated titanium plates. A circular wound was made on one side of the skin fold. A metal cylinder with phosphate buffer was fixed into the window of the titanium plate. The concentration of penetrated drug was measured in the buffer. The skin fold was morphologically intact and had a healthy microcirculation. The drug appeared in the acceptor buffer after 30 min, and its concentration exhibited a continuous increase. The presence of ibuprofen was also detected in the plasma. In conclusion, this model allows an exact in vivo study of drug penetration and absorption.

  4. Genome-scale metabolic models as platforms for identification of novel genes as antimicrobial drug targets.

    Science.gov (United States)

    Mienda, Bashir Sajo; Salihu, Rabiu; Adamu, Aliyu; Idris, Shehu

    2018-03-01

    The growing number of multidrug-resistant pathogenic bacteria is becoming a world leading challenge for the scientific community and for public health. However, advances in high-throughput technologies and whole-genome sequencing of bacterial pathogens make the construction of bacterial genome-scale metabolic models (GEMs) increasingly realistic. The use of GEMs as an alternative platforms will expedite identification of novel unconditionally essential genes and enzymes of target organisms with existing and forthcoming GEMs. This approach will follow the existing protocol for construction of high-quality GEMs, which could ultimately reduce the time, cost and labor-intensive processes involved in identification of novel antimicrobial drug targets in drug discovery pipelines. We discuss the current impact of existing GEMs of selected multidrug-resistant pathogenic bacteria for identification of novel antimicrobial drug targets and the challenges of closing the gap between genome-scale metabolic modeling and conventional experimental trial-and-error approaches in drug discovery pipelines.

  5. Some Remarks on Prediction of Drug-Target Interaction with Network Models.

    Science.gov (United States)

    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.

  6. 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

  7. Modeling systems containing alkanolamines with the CPA equation of state

    DEFF Research Database (Denmark)

    Avlund, Ane Søgaard; Kontogeorgis, Georgios; Michelsen, Michael Locht

    2008-01-01

    An association model, the cubic-plus-association (CPA) equation of state (EoS), is applied for the first time to a class of multifunctional compounds (alkanolamines). Three alkanolamines of practical and scientific significance are considered; monoethanolamine (MEA), diethanolamine (DEA...... studied using the CPA equation of state (alcohols, amines, and glycols)....

  8. The Last State to Grant Nurse Practitioners DEA Licensure: An Education Improvement Initiative on the Florida Prescription Drug Monitoring Program.

    Science.gov (United States)

    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.

  9. Modelling drug-related morbidity in Sweden using an expert panel of physicians

    OpenAIRE

    Hakkarainen, Katja M; Alström, Daniel; Hägg, Staffan; Carlsten, Anders; Gyllensten, Hanna

    2012-01-01

    PURPOSE: In modelling studies using pharmacists' opinions, drug-related morbidity (DRM) and preventable DRM have been more common than in observational studies, and the resulting costs are extensive. Modelling studies' estimates may vary depending on informants' profession. The purpose of this modelling study was to estimate the proportion of patients with DRM and preventable DRM and the cost of illness (COI) of DRM in Sweden based on physicians' expert opinions. METHOD: A conceptual model of...

  10. Application of Prognostic Mesoscale Modeling in the Southeast United States

    International Nuclear Information System (INIS)

    Buckley, R.L.

    1999-01-01

    A prognostic model is being used to provide regional forecasts for a variety of applications at the Savannah River Site (SRS). Emergency response dispersion models available at SRS use the space and time-dependent meteorological data provided by this model to supplement local and regional observations. Output from the model is also used locally to aid in forecasting at SRS, and regionally in providing forecasts of the potential time and location of hurricane landfall within the southeast United States

  11. Dynamic State Space Partitioning for External Memory Model Checking

    DEFF Research Database (Denmark)

    Evangelista, Sami; Kristensen, Lars Michael

    2009-01-01

    We describe a dynamic partitioning scheme usable by model checking techniques that divide the state space into partitions, such as most external memory and distributed model checking algorithms. The goal of the scheme is to reduce the number of transitions that link states belonging to different...... partitions, and thereby limit the amount of disk access and network communication. We report on several experiments made with our verification platform ASAP that implements the dynamic partitioning scheme proposed in this paper....

  12. Nanoporous materials modified with biodegradable polymers as models for drug delivery applications

    DEFF Research Database (Denmark)

    Gruber, Mathias F; Schulte, Lars; Ndoni, Sokol

    2013-01-01

    Polymers play a central role in the development of carriers for diagnostic and therapeutic agents. Especially the use of either degradable polymers or porous materials to encapsulate drug compounds in order to obtain steady drug release profiles has received much attention. We present here a proof...... of principle for a system combining these two encapsulation methods and consisting of a nanoporous polymer (NP) with the pores filled with a degradable polymer mixed with a drug model. Rhodamine 6G (R6G) mixed with Poly(l-Lactic Acid) (PLLA) were confined within the 14nm pores of a NP with gyroid morphology...

  13. Historical perspective on advanced drug delivery: how engineering design and mathematical modeling helped the field mature.

    Science.gov (United States)

    Peppas, Nicholas A

    2013-01-01

    We review the early developments in drug delivery from 1960 to 1990 with emphasis on the fundamental aspects of the field and how they shaped the collaboration of pharmaceutical scientists, chemists, biologists, engineers and medical scientists towards the development of advanced drug delivery systems. Emphasis is given on the advances of biomaterials as drug delivery agents and on the use of design equations and mathematical modeling to achieve a wide range of successful systems. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. Modelling irradiation by EM waves of multifunctionalized iron oxide nanoparticles and subsequent drug release

    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)

  15. Current State of Animal (Mouse Modeling in Melanoma Research

    Directory of Open Access Journals (Sweden)

    Omer F. Kuzu

    2015-01-01

    Full Text Available Despite the considerable progress in understanding the biology of human cancer and technological advancement in drug discovery, treatment failure remains an inevitable outcome for most cancer patients with advanced diseases, including melanoma. Despite FDA-approved BRAF-targeted therapies for advanced stage melanoma showed a great deal of promise, development of rapid resistance limits the success. Hence, the overall success rate of melanoma therapy still remains to be one of the worst compared to other malignancies. Advancement of next-generation sequencing technology allowed better identification of alterations that trigger melanoma development. As development of successful therapies strongly depends on clinically relevant preclinical models, together with the new findings, more advanced melanoma models have been generated. In this article, besides traditional mouse models of melanoma, we will discuss recent ones, such as patient-derived tumor xenografts, topically inducible BRAF mouse model and RCAS/TVA-based model, and their advantages as well as limitations. Although mouse models of melanoma are often criticized as poor predictors of whether an experimental drug would be an effective treatment, development of new and more relevant models could circumvent this problem in the near future.

  16. Application of partial least-squares (PLS) modeling in quantifying drug crystallinity in amorphous solid dispersions.

    Science.gov (United States)

    Rumondor, Alfred C F; Taylor, Lynne S

    2010-10-15

    Among the different experimental methods that can be used to quantify the evolution of drug crystallinity in polymer-containing amorphous solid dispersions, powder X-ray diffractometry (PXRD) is commonly considered as a frontline method. In order to achieve accurate quantification of the percent drug crystallinity in the system, calibration curves have to be constructed using appropriate calibration samples and calculation methods. This can be non-trivial in the case of partially crystalline solid dispersions where the calibration samples must capture the multiphase nature of the systems and the mathematical model must be robust enough to accommodate subtle and not so subtle changes in the diffractograms. The purpose of this study was to compare two different calculation and model-building methods to quantify the proportion of crystalline drug in amorphous solid dispersions containing different ratios of drug and amorphous polymer. The first method involves predicting the % drug crystallinity from the ratio of the area underneath the Bragg peaks to total area of the diffractogram. The second method is multivariate analysis using a Partial Least-Squares (PLS) multivariate regression method. It was found that PLS analysis provided far better accuracy and prediction of % drug crystallinity in the sample. Through the application of PLS, root-mean-squared error of estimation (RMSEE) values of 2.2%, 1.9%, and 4.7% drug crystallinity was achieved for samples containing 25%, 50%, and 75% polymer, respectively, compared to values of 11.2%, 17.0%, and 23.6% for the area model. In addition, construction of a PLS model enables further analysis of the data, including identification of outliers and non-linearity in the data, as well as insight into which factors are most important to correlate PXRD diffractograms with % crystallinity of the drug through analysis of the loadings. Copyright 2010 Elsevier B.V. All rights reserved.

  17. Effective Drug Delivery in Diffuse Intrinsic Pontine Glioma: A Theoretical Model to Identify Potential Candidates

    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.

  18. Drug development costs when financial risk is measured using the Fama-French three-factor model.

    Science.gov (United States)

    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.

  19. Joint Bayesian Analysis of Parameters and States in Nonlinear, Non-Gaussian State Space Models

    NARCIS (Netherlands)

    Barra, I.; Hoogerheide, L.F.; Koopman, S.J.; Lucas, A.

    2017-01-01

    We propose a new methodology for designing flexible proposal densities for the joint posterior density of parameters and states in a nonlinear, non-Gaussian state space model. We show that a highly efficient Bayesian procedure emerges when these proposal densities are used in an independent

  20. The New York State Bird Conservation Area (BCA) Program: A Model for the United States

    Science.gov (United States)

    M. F. Burger; D. J. Adams; T. Post; L. Sommers; B. Swift

    2005-01-01

    The New York State Bird Conservation Area (BCA) Program, modeled after the National Audubon Society?s Important Bird Areas Program, is based on legislation signed by Governor Pataki in 1997. New York is the first state in the nation to enact such a program. The BCA Program seeks to provide a comprehensive, ecosystem approach to conserving birds and their habitats on...

  1. Towards a pragmatic human migraine model for drug testing

    DEFF Research Database (Denmark)

    Hansen, Emma Katrine; Olesen, Jes

    2017-01-01

    .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...

  2. Molecular Modeling: A Powerful Tool for Drug Design and Molecular ...

    Indian Academy of Sciences (India)

    data. GENERAL I ARTICLE of programmable calculators (starting around 1956 with the introduction of Fortran), computers as visualization aids (around. 1970) .... ous applications of computer assisted molecular modeling tech- niques are .... thods are less complicated, fast, and are able to handle very large systems ...

  3. Incorporation of lysosomal sequestration in the mechanistic model for prediction of tissue distribution of basic drugs.

    Science.gov (United States)

    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

  4. Current status of mammalian and human models for predicting drug photosensitivity

    International Nuclear Information System (INIS)

    Harber, L.C.

    1981-01-01

    The status of efforts to develop experimental models for drug photosensitivity reactions in small mammals is reviewed. Tests which are practical and also have a high predictive value in determining photosensitivity hazards to man are the goal of this research. The various animal model systems which have been used are evaluated with respect to these goals

  5. A Learning State-Space Model for Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    2007-01-01

    Full Text Available This paper proposes an approach based on a state-space model for learning the user concepts in image retrieval. We first design a scheme of region-based image representation based on concept units, which are integrated with different types of feature spaces and with different region scales of image segmentation. The design of the concept units aims at describing similar characteristics at a certain perspective among relevant images. We present the details of our proposed approach based on a state-space model for interactive image retrieval, including likelihood and transition models, and we also describe some experiments that show the efficacy of our proposed model. This work demonstrates the feasibility of using a state-space model to estimate the user intuition in image retrieval.

  6. Identifying Drugs

    Science.gov (United States)

    ... and Affect Teens The Negative Health Effects of Marijuana Use State and Federal Drug Laws Treatment and Recovery Federal Student Aid and Consequences of a Drug Conviction School Failure VIDEO: Taking Prescription Drugs to Get High—A Bad Idea Drugged Driving—What You Should Know How ...

  7. Drug perfusion enhancement in tissue model by steady streaming induced by oscillating microbubbles.

    Science.gov (United States)

    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.

  8. The Association between Non-Medical Prescription Drug Use and Suicidal Behavior among United States Adolescents

    Directory of Open Access Journals (Sweden)

    Amanda L. Divin

    2014-11-01

    Full Text Available Adolescence represents a vulnerable time for the development of both drug use/abuse and mental illness. Although previous research has substantiated a relationship between drug use and suicidal behavior, little research has examined this relationship with non-medical prescription drug use. Given the growing prevalence of non-medical prescription drug use (NMPDU among adolescents, this study explored the association between NMPDU and suicidal behavior. Nationally representative data were derived from 16, 410 adolescents who completed the 2009 National Youth Risk Behavior Survey. Approximately 19.8% of participants reported lifetime NMPDU. NMPDU was associated with significantly increased odds of suicidal behavior (P < 0.01, with seriously considering attempting suicide and making a plan about attempting suicide representing the strongest correlates for males and females. Results suggest the importance of 1 continued reinforcement of drug education programs in high school begun at earlier ages and 2 mental health care and screenings among adolescents.

  9. Modified Critical State Two-Surface Plasticity Model for Sands

    DEFF Research Database (Denmark)

    Sørensen, Kris Wessel; Nielsen, Søren Kjær; Shajarati, Amir

    This article describes the outline of a numerical integration scheme for a critical state two-surface plasticity model for sands. The model is slightly modified by LeBlanc (2008) compared to the original formulation presented by Manzari and Dafalias (1997) and has the ability to correctly model...... the stress-strain response of sands. The model is versatile and can be used to simulate drained and undrained conditions, due to the fact that the model can efficiently calculate change in void ratio as well as pore pressure. The objective of the constitutive model is to investigate if the numerical...

  10. Computational modeling of drug-resistant bacteria. Final report

    International Nuclear Information System (INIS)

    2015-01-01

    Initial proposal summary: The evolution of antibiotic-resistant mutants among bacteria (superbugs) is a persistent and growing threat to public health. In many ways, we are engaged in a war with these microorganisms, where the corresponding arms race involves chemical weapons and biological targets. Just as advances in microelectronics, imaging technology and feature recognition software have turned conventional munitions into smart bombs, the long-term objectives of this proposal are to develop highly effective antibiotics using next-generation biomolecular modeling capabilities in tandem with novel subatomic feature detection software. Using model compounds and targets, our design methodology will be validated with correspondingly ultra-high resolution structure-determination methods at premier DOE facilities (single-crystal X-ray diffraction at Argonne National Laboratory, and neutron diffraction at Oak Ridge National Laboratory). The objectives and accomplishments are summarized.

  11. Computational modeling of drug-resistant bacteria. Final report

    Energy Technology Data Exchange (ETDEWEB)

    MacDougall, Preston [Middle Tennessee State Univ., Murfreesboro, TN (United States)

    2015-03-12

    Initial proposal summary: The evolution of antibiotic-resistant mutants among bacteria (superbugs) is a persistent and growing threat to public health. In many ways, we are engaged in a war with these microorganisms, where the corresponding arms race involves chemical weapons and biological targets. Just as advances in microelectronics, imaging technology and feature recognition software have turned conventional munitions into smart bombs, the long-term objectives of this proposal are to develop highly effective antibiotics using next-generation biomolecular modeling capabilities in tandem with novel subatomic feature detection software. Using model compounds and targets, our design methodology will be validated with correspondingly ultra-high resolution structure-determination methods at premier DOE facilities (single-crystal X-ray diffraction at Argonne National Laboratory, and neutron diffraction at Oak Ridge National Laboratory). The objectives and accomplishments are summarized.

  12. Breaking the Bank: Three Financing Models for Addressing the Drug Innovation Cost Crisis.

    Science.gov (United States)

    Kleinke, J D; McGee, Nancy

    2015-05-01

    The introduction of innovative specialty pharmaceuticals with high prices has renewed efforts by public and private healthcare payers to constrain their utilization, increase patient cost-sharing, and compel government intervention on pricing. These efforts, although rational for individual payers, have the potential to undermine the public health impact and overall economic value of these innovations for society. The emerging archetypal example is the outcry over the cost of sofosbuvir, a drug proved to cure hepatitis C infection at a cost of $84,000 per person for a course of treatment (or $1000 per tablet). This represents a radical medical breakthrough for public health, with great promise for the long-term costs associated with this disease, but with major short-term cost implications for the budgets of healthcare payers. To propose potential financing models to provide a workable and lasting solution that directly addresses the misalignment of incentives between healthcare payers confronted with the high upfront costs of innovative specialty drugs and the rest of the US healthcare system, and to articulate these in the context of the historic struggle over paying for innovation. We describe 3 innovative financing models to manage expensive specialty drugs that will significantly reduce the direct, immediate cost burden of these drugs to public and private healthcare payers. The 3 financing models include high-cost drug mortgages, high-cost drugs reinsurance, and high-cost drug patient rebates. These models have been proved successful in other areas and should be adopted into healthcare to mitigate the high-cost of specialty drugs. We discuss the distribution of this burden over time and across the healthcare system, and we match the financial burden of medical innovations to the healthcare stakeholders who capture their overall value. All 3 models work within or replicate the current healthcare marketplace mechanisms for distributing immediate high

  13. Pharmacokinetics and Drug Interactions Determine Optimum Combination Strategies in Computational Models of Cancer Evolution.

    Science.gov (United States)

    Chakrabarti, Shaon; Michor, Franziska

    2017-07-15

    The identification of optimal drug administration schedules to battle the emergence of resistance is a major challenge in cancer research. The existence of a multitude of resistance mechanisms necessitates administering drugs in combination, significantly complicating the endeavor of predicting the evolutionary dynamics of cancers and optimal intervention strategies. A thorough understanding of the important determinants of cancer evolution under combination therapies is therefore crucial for correctly predicting treatment outcomes. Here we developed the first computational strategy to explore pharmacokinetic and drug interaction effects in evolutionary models of cancer progression, a crucial step towards making clinically relevant predictions. We found that incorporating these phenomena into our multiscale stochastic modeling framework significantly changes the optimum drug administration schedules identified, often predicting nonintuitive strategies for combination therapies. We applied our approach to an ongoing phase Ib clinical trial (TATTON) administering AZD9291 and selumetinib to EGFR-mutant lung cancer patients. Our results suggest that the schedules used in the three trial arms have almost identical efficacies, but slight modifications in the dosing frequencies of the two drugs can significantly increase tumor cell eradication. Interestingly, we also predict that drug concentrations lower than the MTD are as efficacious, suggesting that lowering the total amount of drug administered could lower toxicities while not compromising on the effectiveness of the drugs. Our approach highlights the fact that quantitative knowledge of pharmacokinetic, drug interaction, and evolutionary processes is essential for identifying best intervention strategies. Our method is applicable to diverse cancer and treatment types and allows for a rational design of clinical trials. Cancer Res; 77(14); 3908-21. ©2017 AACR . ©2017 American Association for Cancer Research.

  14. Ising percolation in a three-state majority vote model

    International Nuclear Information System (INIS)

    Balankin, Alexander S.; Martínez-Cruz, M.A.; Gayosso Martínez, Felipe; Mena, Baltasar; Tobon, Atalo; Patiño-Ortiz, Julián; Patiño-Ortiz, Miguel; Samayoa, Didier

    2017-01-01

    Highlights: • Three-state non-consensus majority voter model is introduced. • Phase transition in the absorbing state non-consensus is revealed. • The percolation transition belongs to the universality class of Ising percolation. • The effect of an updating rule for a tie between voter neighbors is highlighted. - Abstract: In this Letter, we introduce a three-state majority vote model in which each voter adopts a state of a majority of its active neighbors, if exist, but the voter becomes uncommitted if its active neighbors are in a tie, or all neighbors are the uncommitted. Numerical simulations were performed on square lattices of different linear size with periodic boundary conditions. Starting from a random distribution of active voters, the model leads to a stable non-consensus state in which three opinions coexist. We found that the “magnetization” of the non-consensus state and the concentration of uncommitted voters in it are governed by an initial composition of system and are independent of the lattice size. Furthermore, we found that a configuration of the stable non-consensus state undergoes a second order percolation transition at a critical concentration of voters holding the same opinion. Numerical simulations suggest that this transition belongs to the same universality class as the Ising percolation. These findings highlight the effect of an updating rule for a tie between voter neighbors on the critical behavior of models obeying the majority vote rule whenever a strict majority exists.

  15. Ising percolation in a three-state majority vote model

    Energy Technology Data Exchange (ETDEWEB)

    Balankin, Alexander S., E-mail: abalankin@ipn.mx [Grupo Mecánica Fractal, ESIME, Instituto Politécnico Nacional, México D.F., 07738 (Mexico); Martínez-Cruz, M.A.; Gayosso Martínez, Felipe [Grupo Mecánica Fractal, ESIME, Instituto Politécnico Nacional, México D.F., 07738 (Mexico); Mena, Baltasar [Laboratorio de Ingeniería y Procesos Costeros, Instituto de Ingeniería, Universidad Nacional Autónoma de México, Sisal, Yucatán, 97355 (Mexico); Tobon, Atalo; Patiño-Ortiz, Julián; Patiño-Ortiz, Miguel; Samayoa, Didier [Grupo Mecánica Fractal, ESIME, Instituto Politécnico Nacional, México D.F., 07738 (Mexico)

    2017-02-05

    Highlights: • Three-state non-consensus majority voter model is introduced. • Phase transition in the absorbing state non-consensus is revealed. • The percolation transition belongs to the universality class of Ising percolation. • The effect of an updating rule for a tie between voter neighbors is highlighted. - Abstract: In this Letter, we introduce a three-state majority vote model in which each voter adopts a state of a majority of its active neighbors, if exist, but the voter becomes uncommitted if its active neighbors are in a tie, or all neighbors are the uncommitted. Numerical simulations were performed on square lattices of different linear size with periodic boundary conditions. Starting from a random distribution of active voters, the model leads to a stable non-consensus state in which three opinions coexist. We found that the “magnetization” of the non-consensus state and the concentration of uncommitted voters in it are governed by an initial composition of system and are independent of the lattice size. Furthermore, we found that a configuration of the stable non-consensus state undergoes a second order percolation transition at a critical concentration of voters holding the same opinion. Numerical simulations suggest that this transition belongs to the same universality class as the Ising percolation. These findings highlight the effect of an updating rule for a tie between voter neighbors on the critical behavior of models obeying the majority vote rule whenever a strict majority exists.

  16. Identifying co-targets to fight drug resistance based on a random walk model

    Directory of Open Access Journals (Sweden)

    Chen Liang-Chun

    2012-01-01

    Full Text Available Abstract Background Drug resistance has now posed more severe and emergent threats to human health and infectious disease treatment. However, wet-lab approaches alone to counter drug resistance have so far still achieved limited success due to less knowledge about the underlying mechanisms of drug resistance. Our approach apply a heuristic search algorithm in order to extract active network under drug treatment and use a random walk model to identify potential co-targets for effective antibacterial drugs. Results We use interactome network of Mycobacterium tuberculosis and gene expression data which are treated with two kinds of antibiotic, Isoniazid and Ethionamide as our test data. Our analysis shows that the active drug-treated networks are associated with the trigger of fatty acid metabolism and synthesis and nicotinamide adenine dinucleotide (NADH-related processes and those results are consistent with the recent experimental findings. Efflux pumps processes appear to be the major mechanisms of resistance but SOS response is significantly up-regulation under Isoniazid treatment. We also successfully identify the potential co-targets with literature confirmed evidences which are related to the glycine-rich membrane, adenosine triphosphate energy and cell wall processes. Conclusions With gene expression and interactome data supported, our study points out possible pathways leading to the emergence of drug resistance under drug treatment. We develop a computational workflow for giving new insights to bacterial drug resistance which can be gained by a systematic and global analysis of the bacterial regulation network. Our study also discovers the potential co-targets with good properties in biological and graph theory aspects to overcome the problem of drug resistance.

  17. Product State Models in Holonic shop floor control systems

    DEFF Research Database (Denmark)

    Langer, Gilad; Sørensen, Christian; Larsen, Michael Holm

    1999-01-01

    This paper reviews the concepts of the product state models as an integrated database for Holonic Shop Floor Control. One of the requirements of agility is to be able to realise real-time control of manufacturing systems based on the actual state of the system and especially the state of its...... workpieces. The Product State Model (PSM) is an integrated object oriented database, which contains the dynamic data concerning the actual state of the workpieces during the manufacturing processing. It is integrated in the HoMuCS architecture by aggregating a PSM in each order holon. The paper outlines...... this as well as the general concepts of the PSM and the important parts of the HoMuCS system architecture. Finally the integration of a PSM is illustrated in a case study based on an industrial case at the Odense Steel Shipyard Ltd....

  18. Array of translational systems pharmacodynamic models of anti-cancer drugs.

    Science.gov (United States)

    Ait-Oudhia, Sihem; Mager, Donald E

    2016-12-01

    Cancer is a complex disease that is characterized by an uncontrolled growth and spread of abnormal cells. Drug development in oncology is particularly challenging and is associated with one of the highest attrition rates of compounds despite substantial investments in resources. Pharmacokinetic and pharmacodynamic (PK/PD) modeling seeks to couple experimental data with mathematical models to provide key insights into factors controlling cytotoxic effects of chemotherapeutics and cancer progression. PK/PD modeling of anti-cancer compounds is equally challenging, partly based on the complexity of biological and pharmacological systems. However, reliable mechanistic and systems PK/PD models for anti-cancer agents have been developed and successfully applied to: (1) provide insights into fundamental mechanisms implicated in tumor growth, (2) assist in dose selection for first-in-human phase I studies (e.g., effective dose, escalating doses, and maximal tolerated doses), (3) design and optimize combination drug regimens, (4) design clinical trials, and (5) establish links between drug efficacy and safety and the concentrations of measured biomarkers. In this commentary, classes of relevant mechanism-based and systems PK/PD models of anti-cancer agents that have shown promise in translating preclinical data and enhancing stages of the drug development process are reviewed. Specific features of such models are discussed including their strengths and limitations along with a prospectus of using these models alone or in combination for cancer therapy.

  19. Ontology and modeling patterns for state-based behavior representation

    Science.gov (United States)

    Castet, Jean-Francois; Rozek, Matthew L.; Ingham, Michel D.; Rouquette, Nicolas F.; Chung, Seung H.; Kerzhner, Aleksandr A.; Donahue, Kenneth M.; Jenkins, J. Steven; Wagner, David A.; Dvorak, Daniel L.; hide

    2015-01-01

    This paper provides an approach to capture state-based behavior of elements, that is, the specification of their state evolution in time, and the interactions amongst them. Elements can be components (e.g., sensors, actuators) or environments, and are characterized by state variables that vary with time. The behaviors of these elements, as well as interactions among them are represented through constraints on state variables. This paper discusses the concepts and relationships introduced in this behavior ontology, and the modeling patterns associated with it. Two example cases are provided to illustrate their usage, as well as to demonstrate the flexibility and scalability of the behavior ontology: a simple flashlight electrical model and a more complex spacecraft model involving instruments, power and data behaviors. Finally, an implementation in a SysML profile is provided.

  20. Exactly solvable model in quadrupole-octupole coupled states

    Science.gov (United States)

    Jalili Majarshin, A.; Sabri, H.; Rezaei, M.

    2018-03-01

    Exactly solvable model in quadrupole-octupole coupled (QOC) states is an interesting nuclear structure phenomenon. For example, several transitions of the electric dipole and quadrupole (E1 and E2) values are indicative of QOC states. Various collective models as three-level and four-level pairing models were employed in order to account for the observed properties of the QOC states. We suggest a simultaneous description of low-lying collective positive and negative-parity states to use the spdf and sdf interacting boson model to reproduce the general characteristics of the QOC states. Also, quantum phase transitions are investigated based on dual algebraic structures for the sd, sdf and spdf-IBM. The low lying positive and negative parity states and the QOC properties of the stable even-even Cd isotopes are calculated in solvable extended transitional Hamiltonian of the IBM-spdf and IBM-sdf models based on the affine SU (1 , 1) ˆ Lie algebra. Some observables such as energy levels, transition rates, expectation value of boson number operators, energy differences and staggering pattern are calculated and examined for Cd isotopes. The IBM calculations indicate a nuclear structure of the electric E1, E2 and E3 strength and energy spectra in the low-lying, thus confirming the experimental results for transition region. The calculations confirm a good agreement for the energy spectra, quantum phase transitions and fragmentation of the E1, E2 and E3 strengths.

  1. Prediction of drug terminal half-life and terminal volume of distribution after intravenous dosing based on drug clearance, steady-state volume of distribution, and physiological parameters of the body.

    Science.gov (United States)

    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.

  2. 3 QP plus rotor model and high spin states

    International Nuclear Information System (INIS)

    Mathur, Tripti

    1995-01-01

    Nuclear models are approximate methods to describe certain properties of a large number of nuclei. In this paper details of 3 QP (three quasi particle) plus rotor model and high spin state are discussed. The band head energies for the 3 QP rotational bands for 157 Ho and 159 Tm are also given. 5 refs., 8 figs

  3. Microscopic model of the glass transition and the glassy state

    International Nuclear Information System (INIS)

    Shukla, P.

    1982-07-01

    A microscopic model of the glass transition and the glassy state is presented. It is exactly solvable, and offers a unified view of the equilibrium and non-equilibrium aspects of the glass transition. It also provides a statistical-mechanical justification of the irreversible thermodynamic models of the glass transition proposed earlier. (author)

  4. A Modified Microfinance Model Proposed for the United States

    Directory of Open Access Journals (Sweden)

    Eldon H Bernstein

    2014-07-01

    While the goal in the traditional model in developing markets is the elimination of poverty, we show how those critical conditions help to explain the lack of success in the United States.  We propose a modified model whose goal is the creation of an entrepreneurial venture or improving the performance of an existing small enterprise.

  5. 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.

  6. 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...

  7. Important role of proinflammatory cytokines/other endogenous substances in drug-induced hepatotoxicity: depression of drug metabolism during infections/inflammation states, and genetic polymorphisms of drug-metabolizing enzymes/cytokines may markedly contribute to this pathology.

    Science.gov (United States)

    Prandota, Joseph

    2005-01-01

    Analysis of literature data on drug-induced hepatotoxicity reveals that often upper respiratory febrile illnesses and/or inflammation states precede liver injury/diseases related to administration of drugs or hepatotoxicity associated with administration of therapeutic doses of acetaminophen in some genetically predisposed subjects. The goals of this paper are to review the potential role of alterations in the balance between TH1 cells producing cytokines associated with a cell-mediated response and TH2 cells associated with an antibody response, as well as other endogenous substances, eg, growth factors, leading to a shift in immune response to one that may participate in the liver cells injury during administration of certain drugs, especially in subjects with genetic polymorphisms in drug-metabolizing enzymes. The papers cited in this review were selected to illustrate specific issue related to how profuse and dysregulated production of cytokines, growth factors, and/or other endogenous substances during viral/bacterial infections and inflammation states play a role in the development of drug-induced liver injury. Several cases of liver injury related to administration of drugs appear to be initiated or intensified by upper respiratory febrile illnesses and/or inflammation states, which stimulate sometimes dysregulated production of interferon gamma and/or other proinflammatory cytokines/growth factors. This, in turn, results in down-regulation of various induced and constitutive isoforms of cytochromes P-450, and other enzymes involved in the metabolism of several exogenous (eg, drugs) and endogenous lipophilic (eg, steroids) substances, thus having an important impact on the alterations in bioactivation and detoxication processes in the body and on the balance between production, utilization, and elimination of endogenous bioproducts of these reactions. Activation of systemic host defense mechanisms results in down-regulation of various enzymes involved in

  8. A Model of Consumer Response to Over-the-Counter Drug Advertising: Antecedents and Influencing Factors.

    Science.gov (United States)

    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.

  9. Muscular dystrophy in a dish: engineered human skeletal muscle mimetics for disease modeling and drug discovery

    Science.gov (United States)

    Smith, Alec S.T.; Davis, Jennifer; Lee, Gabsang; Mack, David L.

    2016-01-01

    Engineered in vitro models using human cells, particularly patient-derived induced pluripotent stem cells (iPSCs), offer a potential solution to issues associated with the use of animals for studying disease pathology and drug efficacy. Given the prevalence of muscle diseases in human populations, an engineered tissue model of human skeletal muscle could provide a biologically accurate platform to study basic muscle physiology, disease progression, and drug efficacy and/or toxicity. Such platforms could be used as phenotypic drug screens to identify compounds capable of alleviating or reversing congenital myopathies, such as Duchene muscular dystrophy (DMD). Here, we review current skeletal muscle modeling technologies with a specific focus on efforts to generate biomimetic systems for investigating the pathophysiology of dystrophic muscle. PMID:27109386

  10. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

    Science.gov (United States)

    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.

  11. Cognitive Enhancers for Facilitating Drug Cue Extinction: Insights from Animal Models

    Science.gov (United States)

    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

  12. Environmental modulation of drug taking: Nonhuman primate models of cocaine abuse and PET neuroimaging.

    Science.gov (United States)

    Nader, Michael A; Banks, Matthew L

    2014-01-01

    The current review highlights the importance of environmental variables on cocaine self-administration in nonhuman primate models of drug abuse. In addition to describing the behavioral consequences, potential mechanisms of action are discussed, based on imaging results using the non-invasive and translational technique of positron emission tomography (PET). In this review, the role of three environmental variables - both positive and negative - are described: alternative non-drug reinforcers; social rank (as an independent variable) and punishment of cocaine self-administration. These environmental stimuli can profoundly influence brain function and drug self-administration. We focus on environmental manipulations involving non-drug alternatives (e.g., food reinforcement) using choice paradigms. Manipulations such as response cost and social variables (e.g., social rank, social stress) also influence the behavioral effects of drugs. Importantly, these manipulations are amenable to brain imaging studies. Taken together, these studies emphasize the profound impact environmental variables can have on drug taking, which should provide important information related to individual-subject variability in treatment responsiveness, and the imaging work may highlight pharmacological targets for medications related to treating drug abuse. This article is part of a Special Issue entitled 'NIDA 40th Anniversary Issue'. Copyright © 2013 Elsevier Ltd. All rights reserved.

  13. Standard State Space Models of Unawareness (Extended Abstract

    Directory of Open Access Journals (Sweden)

    Peter Fritz

    2016-06-01

    Full Text Available The impossibility theorem of Dekel, Lipman and Rustichini has been thought to demonstrate that standard state-space models cannot be used to represent unawareness. We first show that Dekel, Lipman and Rustichini do not establish this claim. We then distinguish three notions of awareness, and argue that although one of them may not be adequately modeled using standard state spaces, there is no reason to think that standard state spaces cannot provide models of the other two notions. In fact, standard space models of these forms of awareness are attractively simple. They allow us to prove completeness and decidability results with ease, to carry over standard techniques from decision theory, and to add propositional quantifiers straightforwardly.

  14. THE EUROPEAN MODEL OF STATE REGULATION OF TOURISM ACTIVITIES

    Directory of Open Access Journals (Sweden)

    О. Davydova

    2013-11-01

    Full Text Available In the article the existing model of state regulation of the development of tourism. Expediency of the European model of state regulation of tourism development in Ukraine. It is noted that the European model of state regulation of tourism activities based on the coordination of marketing activities and the development of cooperation between the public and private sectors. The basic forms of public-private partnerships and the advantages of using cluster model of development of tourism, namely, contracts, production sharing agreement, lease, joint venture. Promising areas of application of the PPP identified the transport sector, housing and utilities, energy and tourism sector. The features of cluster formations in the country and the prospects for tourism clusters.

  15. Bayesian state space models for dynamic genetic network construction across multiple tissues.

    Science.gov (United States)

    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.

  16. Determination of solid state characteristics of spray-congealed Ibuprofen solid lipid microparticles and their impact on sustaining drug release.

    Science.gov (United States)

    Wong, Priscilla Chui Hong; Heng, Paul Wan Sia; Chan, Lai Wah

    2015-05-04

    This study was used to find solid state characteristics of ibuprofen loaded spray-congealed solid lipid microparticles (SLMs) by employing simple lipids as matrices, with or without polymeric additives, and the impact of solid drug-matrix miscibility on sustaining drug release. Solid miscibility of ibuprofen with two lipids, cetyl alcohol (CA) and stearic acid (SA), were investigated using differential scanning calorimetry (DSC). SLMs containing 20% w/w ibuprofen with or without polymeric additives, PVP/VA and EC, were produced by spray congealing, and the resultant microparticles were subjected to visual examination by scanning electron microscopy (SEM), thermal analysis using DSC, and hot-stage microscopy. Intermolecular interactions between lipids and drug as well as additives were investigated by Fourier-transformed infrared spectroscopy (FTIR) and nuclear magnetic resonance spectroscopy (NMR). X-ray diffractometry (XRD) was utilized to study polymorphic changes of drug and matrix over the course of a year. Ibuprofen was found to depress the melting points of CA and SA in a colligative manner, reaching maximum solubility at 10% w/w and 30% w/w for CA and SA, respectively. Drug encapsulation efficiencies and yields of spray-congealed SLMs containing 20% w/w ibuprofen were consistently high for both lipid matrices. CA and SA were found to adopt their stable γ- and β-polymorphs, respectively, immediately after spray congealing. The spray congealing process resulted in ibuprofen adopting an amorphous or poorly crystalline state, with no further changes over the course of a year. SEM, DSC, and hot stage microscope studies on the SLMs confirmed the formation of a solid dispersion between ibuprofen and CA and a solid solution between ibuprofen and SA. SA was found to sustain the release of ibuprofen significantly better than CA. PVP/VA and EC showed some interactions with CA, which led to an expansion of unit cell dimensions of CA upon spray congealing, whereas they

  17. Development of an optimised application protocol for sonophoretic transdermal delivery of a model hydrophilic drug.

    Science.gov (United States)

    Sarheed, Omar; Rasool, Bazigha K Abdul

    2011-01-01

    It has now been known for over a decade that low frequency ultrasound can be used to effectively enhance transdermal drug penetration - an approach termed sonophoresis. Mechanistically, acoustic cavitation results in the creation of defects in the stratum corneum that allow accelerated absorption of topically applied molecules. The aim of this study was to develop an optimised sonophoresis protocol for studying transdermal drug delivery in vitro. To this end, caffeine was selected as a model hydrophilic drug while porcine skin was used as a model barrier. Following acoustic validation, 20kHz ultrasound was applied for different durations (range: 5 s to 10 min) using three different modes (10%, 33% or 100% duty cycles) and two distinct sonication procedures (either before or concurrent with drug deposition). Each ultrasonic protocol was assessed in terms of its heating and caffeine flux-enhancing effects. It was found that the best regimen was a concurrent 5 min, pulsed (10% duty cycle) beam of SATA intensity 0.37 W/cm(2). A key insight was that in the case of pulsed beams of 10% duty cycle, sonication concurrent with drug deposition was superior to sonication prior to drug deposition and potential mechanisms for this are discussed.

  18. Modeling structure-function relationships for diffusive drug transport in inert porous geopolymer matrices.

    Science.gov (United States)

    Jämstorp, Erik; Strømme, Maria; Frenning, Göran

    2011-10-01

    A unique structure-function relationship investigation of mechanically strong geopolymer drug delivery vehicles for sustained release of potent substances is presented. The effect of in-synthesis water content on geopolymer pore structure and diffusive drug transport is investigated. Scanning electron microscopy, N2 gas adsorption, mercury intrusion porosimetry, compression strength test, drug permeation, and release experiments are performed. Effective diffusion coefficients are measured and compared with corresponding theoretical values as derived from pore size distribution and connectivity via pore-network modeling. By solely varying the in-synthesis water content, mesoporous and mechanically strong geopolymers with porosities of 8%-45% are obtained. Effective diffusion coefficients of the model drugs Saccharin and Zolpidem are observed to span two orders of magnitude (∼1.6-120 × 10(-8) cm(2) /s), comparing very well to theoretical estimations. The ability to predict drug permeation and release from geopolymers, and materials alike, allows future formulations to be tailored on a structural and chemical level for specific applications such as controlled drug delivery of highly potent substances. Copyright © 2011 Wiley-Liss, Inc.

  19. The skill and style to model the evolution of resistance to pesticides and drugs.

    Science.gov (United States)

    2010-07-01

    Resistance to pesticides and drugs led to the development of theoretical models aimed at identifying the main factors of resistance evolution and predicting the efficiency of resistance management strategies. We investigated the various ways in which the evolution of resistance has been modelled over the last three decades, by reviewing 187 articles published on models of the evolution of resistance to all major classes of pesticides and drugs. We found that (i) the technical properties of the model were most strongly influenced by the class of pesticide or drug and the target organism, (ii) the resistance management strategies studied were quite similar for the different classes of pesticides or drugs, except that the refuge strategy was mostly used in models of the evolution of resistance to insecticidal proteins, (iii) economic criteria were rarely used to evaluate the evolution of resistance and (iv) the influence of mutation, migration and drift on the speed of resistance development has been poorly investigated. We propose guidelines for the future development of theoretical models of the evolution of resistance. For instance, we stress the potential need to give more emphasis to the three evolutionary forces migration, mutation and genetic drift rather than simply selection.

  20. Zebrafish as a Model Organism for the Development of Drugs for Skin Cancer

    Directory of Open Access Journals (Sweden)

    Fatemeh Bootorabi

    2017-07-01

    Full Text Available Skin cancer, which includes melanoma and squamous cell carcinoma, represents the most common type of cutaneous malignancy worldwide, and its incidence is expected to rise in the near future. This condition derives from acquired genetic dysregulation of signaling pathways involved in the proliferation and apoptosis of skin cells. The development of animal models has allowed a better understanding of these pathomechanisms, with the possibility of carrying out toxicological screening and drug development. In particular, the zebrafish (Danio rerio has been established as one of the most important model organisms for cancer research. This model is particularly suitable for live cell imaging and high-throughput drug screening in a large-scale fashion. Thanks to the recent advances in genome editing, such as the clustered regularly-interspaced short palindromic repeats (CRISPR/CRISPR-associated protein 9 (Cas9 methodologies, the mechanisms associated with cancer development and progression, as well as drug resistance can be investigated and comprehended. With these unique tools, the zebrafish represents a powerful platform for skin cancer research in the development of target therapies. Here, we will review the advantages of using the zebrafish model for drug discovery and toxicological and phenotypical screening. We will focus in detail on the most recent progress in the field of zebrafish model generation for the study of melanoma and squamous cell carcinoma (SCC, including cancer cell injection and transgenic animal development. Moreover, we will report the latest compounds and small molecules under investigation in melanoma zebrafish models.

  1. Adverse Selection Models with Three States of Nature

    Directory of Open Access Journals (Sweden)

    Daniela MARINESCU

    2011-02-01

    Full Text Available In the paper we analyze an adverse selection model with three states of nature, where both the Principal and the Agent are risk neutral. When solving the model, we use the informational rents and the efforts as variables. We derive the optimal contract in the situation of asymmetric information. The paper ends with the characteristics of the optimal contract and the main conclusions of the model.

  2. Transformation of Neural State Space Models into LFT Models for Robust Control Design

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, Klaus

    2000-01-01

    This paper considers the extraction of linear state space models and uncertainty models from neural networks trained as state estimators with direct application to robust control. A new method for writing a neural state space model in a linear fractional transformation form in a non-conservative ......-conservative way is proposed, and it is demonstrated how a standard robust control law can be designed for a system described by means of a multi layer perceptron....

  3. Tuberculosis drug resistance isolates from pulmonary tuberculosis patients, Kassala State, Sudan

    Directory of Open Access Journals (Sweden)

    Fatima A Khalid

    2015-01-01

    This study revealed that high resistance to rifampicin was associated with various point mutations in and out of the RRDR of the rpoB gene. Molecular methods are needed for early detection of TB disease and drug resistance.

  4. Rheumatic diseases induced by drugs and environmental factors: the state-of-the-art - part two.

    Science.gov (United States)

    Niklas, Karolina; Niklas, Arkadiusz A; Majewski, Dominik; Puszczewicz, Mariusz J

    2016-01-01

    The majority of rheumatic diseases belong to the group of autoimmune diseases and are associated with autoantibody production. Their etiology is not fully understood. Certain medications and environmental factors may have an influence on the occurrence of rheumatic diseases. Establishing a cause-effect relationship between a certain factor and disease induction is not always simple. It is important to administer the drug continuously or monitor exposure to a given factor in the period preceding the onset of symptoms. The lack of early diagnosed autoimmune disease, or finally the lack of symptoms within a few weeks/months after discontinuation of the drug/cessation of exposure, is also important. The most frequently mentioned rheumatic diseases caused by drugs and environmental factors include systemic lupus erythematosus (SLE), scleroderma, systemic vasculitis, polymyositis, dermatomyositis, and Sjögren's syndrome. The objective of this study is to summarize current knowledge on rheumatic diseases induced by drugs and environmental factors.

  5. Rheumatic diseases induced by drugs and environmental factors: the state-of-the-art - part one.

    Science.gov (United States)

    Niklas, Karolina; Niklas, Arkadiusz A; Majewski, Dominik; Puszczewicz, Mariusz

    2016-01-01

    The majority of rheumatic diseases belong to the group of autoimmune diseases and are associated with autoantibody production. Their etiology is not fully understood. Certain medications and environmental factors may have an influence on the occurrence of rheumatic diseases. Establishing a cause-effect relationship between a certain factor and disease induction is not always simple. It is important to administer the drug continuously or monitor exposure to a given factor in the period preceding the onset of symptoms. The lack of previously diagnosed autoimmune disease, or finally the lack of symptoms within a few weeks/months after discontinuation of the drug/cessation of exposure, is also important. The most frequently mentioned rheumatic diseases caused by drugs and environmental factors include systemic lupus erythematosus, scleroderma, systemic vasculitis, polymyositis, dermatomyositis, and Sjögren's syndrome. The objective of this study is to summarize current knowledge on rheumatic diseases induced by drugs and environmental factors.

  6. State of the art of nanocrystals technology for delivery of poorly soluble drugs

    Energy Technology Data Exchange (ETDEWEB)

    Zhou, Yuqi; Du, Juan; Wang, Lulu; Wang, Yancai, E-mail: wangyancai1999@163.com [Qilu University of Technology, School of Chemistry and Pharmaceutical Engineering (China)

    2016-09-15

    Formulation of nanocrystals is a distinctive approach which can effectively improve the delivery of poorly water-soluble drugs, thus enticing the development of the nanocrystals technology. The characteristics of nanocrystals resulted in an exceptional drug delivery conductance, including saturation solubility, dissolution velocity, adhesiveness, and affinity. Nanocrystals were treated as versatile pharmaceuticals that could be delivered through almost all routes of administration. In the current review, oral, pulmonary, and intravenous routes of administration were presented. Also, the targeting of drug nanocrystals, as well as issues of efficacy and safety, were also discussed. Several methods were applied for nanocrystals production including top-down production strategy (media milling, high-pressure homogenization), bottom-up production strategy (antisolvent precipitation, supercritical fluid process, and precipitation by removal of solvent), and the combination approaches. Moreover, this review also described the evaluation and characterization of the drug nanocrystals and summarized the current commercial pharmaceutical products utilizing nanocrystals technology.

  7. State of the art of nanocrystals technology for delivery of poorly soluble drugs

    International Nuclear Information System (INIS)

    Zhou, Yuqi; Du, Juan; Wang, Lulu; Wang, Yancai

    2016-01-01

    Formulation of nanocrystals is a distinctive approach which can effectively improve the delivery of poorly water-soluble drugs, thus enticing the development of the nanocrystals technology. The characteristics of nanocrystals resulted in an exceptional drug delivery conductance, including saturation solubility, dissolution velocity, adhesiveness, and affinity. Nanocrystals were treated as versatile pharmaceuticals that could be delivered through almost all routes of administration. In the current review, oral, pulmonary, and intravenous routes of administration were presented. Also, the targeting of drug nanocrystals, as well as issues of efficacy and safety, were also discussed. Several methods were applied for nanocrystals production including top-down production strategy (media milling, high-pressure homogenization), bottom-up production strategy (antisolvent precipitation, supercritical fluid process, and precipitation by removal of solvent), and the combination approaches. Moreover, this review also described the evaluation and characterization of the drug nanocrystals and summarized the current commercial pharmaceutical products utilizing nanocrystals technology.

  8. Drug per se laws: a review of their use in the states : traffic tech.

    Science.gov (United States)

    2010-09-01

    Research has indicated that per se laws for alcohol have been : effective in reducing alcohol-related fatalities. A difficulty : in prosecuting drivers for driving impaired by drugs other : than alcohol is that there is no scientific basis for specif...

  9. A Profile of Drug Abuse in the United States. Volume I. Basic Report.

    Science.gov (United States)

    problem in three areas--law enforcement, education, and rehabilitation; and a projection of national trends over the next several years. It excludes consideration of alcohol abuse and drug abuse in the Armed Forces.

  10. 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.

  11. Application of Fused Deposition Modelling (FDM) Method of 3D Printing in Drug Delivery.

    Science.gov (United States)

    Long, Jingjunjiao; Gholizadeh, Hamideh; Lu, Jun; Bunt, Craig; Seyfoddin, Ali

    2017-01-01

    Three-dimensional (3D) printing is an emerging manufacturing technology for biomedical and pharmaceutical applications. Fused deposition modelling (FDM) is a low cost extrusion-based 3D printing technique that can deposit materials layer-by-layer to create solid geometries. This review article aims to provide an overview of FDM based 3D printing application in developing new drug delivery systems. The principle methodology, suitable polymers and important parameters in FDM technology and its applications in fabrication of personalised tablets and drug delivery devices are discussed in this review. FDM based 3D printing is a novel and versatile manufacturing technique for creating customised drug delivery devices that contain accurate dose of medicine( s) and provide controlled drug released profiles. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Validation of ecological state space models using the Laplace approximation

    DEFF Research Database (Denmark)

    Thygesen, Uffe Høgsbro; Albertsen, Christoffer Moesgaard; Berg, Casper Willestofte

    2017-01-01

    for estimation in general mixed effects models. Implementing one-step predictions in the R package Template Model Builder, we demonstrate that it is possible to perform model validation with little effort, even if the ecological model is multivariate, has non-linear dynamics, and whether observations...... are continuous or discrete. With both simulated data, and a real data set related to geolocation of seals, we demonstrate both the potential and the limitations of the techniques. Our results fill a need for convenient methods for validating a state space model, or alternatively, rejecting it while indicating...

  13. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.

    Science.gov (United States)

    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 .

  14. TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models

    Science.gov (United States)

    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.

  15. Incentives for orphan drug research and development in the United States

    Directory of Open Access Journals (Sweden)

    Rodriguez-Monguio Rosa

    2008-12-01

    Full Text Available Abstract Background The Orphan Drug Act (1983 established several incentives to encourage the development of orphan drugs (ODs to treat rare diseases and conditions. This study analyzed the characteristics of OD designations, approvals, sponsors, and evaluated the effective patent and market exclusivity life of orphan new molecular entities (NMEs approved in the US between 1983 and 2007. Methods Primary data sources were the FDA Orange Book, the FDA Office of Orphan Drugs Development, and the US Patent and Trademark Office. Data included all orphan designations and approvals listed by the FDA and all NMEs approved by the FDA during the study period. Results The FDA listed 1,793 orphan designations and 322 approvals between 1983 and 2007. Cancer was the main group of diseases targeted for orphan approvals. Eighty-three companies concentrated 67.7% of the total orphan NMEs approvals. The average time from orphan designation to FDA approval was 4.0 ± 3.3 years (mean ± standard deviation. The average maximum effective patent and market exclusivity life was 11.7 ± 5.0 years for orphan NME. OD market exclusivity increased the average maximum effective patent and market exclusivity life of ODs by 0.8 years. Conclusion Public programs, federal regulations, and policies support orphan drugs R&D. Grants, research design support, FDA fee waivers, tax incentives, and orphan drug market exclusivity are the main incentives for orphan drug R&D. Although the 7-year orphan drug market exclusivity provision had a positive yet relatively modest overall effect on effective patent and market exclusivity life, economic incentives and public support mechanisms provide a platform for continued orphan drug development for a highly specialized market.

  16. Incentives for orphan drug research and development in the United States.

    Science.gov (United States)

    Seoane-Vazquez, Enrique; Rodriguez-Monguio, Rosa; Szeinbach, Sheryl L; Visaria, Jay

    2008-12-16

    The Orphan Drug Act (1983) established several incentives to encourage the development of orphan drugs (ODs) to treat rare diseases and conditions. This study analyzed the characteristics of OD designations, approvals, sponsors, and evaluated the effective patent and market exclusivity life of orphan new molecular entities (NMEs) approved in the US between 1983 and 2007. Primary data sources were the FDA Orange Book, the FDA Office of Orphan Drugs Development, and the US Patent and Trademark Office. Data included all orphan designations and approvals listed by the FDA and all NMEs approved by the FDA during the study period. The FDA listed 1,793 orphan designations and 322 approvals between 1983 and 2007. Cancer was the main group of diseases targeted for orphan approvals. Eighty-three companies concentrated 67.7% of the total orphan NMEs approvals. The average time from orphan designation to FDA approval was 4.0 +/- 3.3 years (mean +/- standard deviation). The average maximum effective patent and market exclusivity life was 11.7 +/- 5.0 years for orphan NME. OD market exclusivity increased the average maximum effective patent and market exclusivity life of ODs by 0.8 years. Public programs, federal regulations, and policies support orphan drugs R&D. Grants, research design support, FDA fee waivers, tax incentives, and orphan drug market exclusivity are the main incentives for orphan drug R&D. Although the 7-year orphan drug market exclusivity provision had a positive yet relatively modest overall effect on effective patent and market exclusivity life, economic incentives and public support mechanisms provide a platform for continued orphan drug development for a highly specialized market.

  17. State of the art in hair analysis for detection of drug and alcohol abuse.

    Science.gov (United States)

    Pragst, Fritz; Balikova, Marie A

    2006-08-01

    Hair differs from other materials used for toxicological analysis because of its unique ability to serve as a long-term storage of foreign substances with respect to the temporal appearance in blood. Over the last 20 years, hair testing has gained increasing attention and recognition for the retrospective investigation of chronic drug abuse as well as intentional or unintentional poisoning. In this paper, we review the physiological basics of hair growth, mechanisms of substance incorporation, analytical methods, result interpretation and practical applications of hair analysis for drugs and other organic substances. Improved chromatographic-mass spectrometric techniques with increased selectivity and sensitivity and new methods of sample preparation have improved detection limits from the ng/mg range to below pg/mg. These technical advances have substantially enhanced the ability to detect numerous drugs and other poisons in hair. For example, it was possible to detect previous administration of a single very low dose in drug-facilitated crimes. In addition to its potential application in large scale workplace drug testing and driving ability examination, hair analysis is also used for detection of gestational drug exposure, cases of criminal liability of drug addicts, diagnosis of chronic intoxication and in postmortem toxicology. Hair has only limited relevance in therapy compliance control. Fatty acid ethyl esters and ethyl glucuronide in hair have proven to be suitable markers for alcohol abuse. Hair analysis for drugs is, however, not a simple routine procedure and needs substantial guidelines throughout the testing process, i.e., from sample collection to results interpretation.

  18. Mexican Drug Trafficking Organizations: A Threat to the United States National Security

    Science.gov (United States)

    2011-03-03

    to be an existing member of Los Zetas. The immigrant, who was arrested by the Zapata Sheriffs Department while smuggling 400 pounds of marijuana...new pubs/jp1 02. pdf . Retrieved 20 February 2011. 2. US Department of Justice, National Drug Threat Assessment 2010 (Washington D.C.: National Drug...Cartels, CRS Report for Congress, (October 16, 2007), http://www.fas.org/sgp/crs/row/RL34215. pdf . 8. Jeremy Roebuck, "Violence the result of fractured

  19. Analysis of access to hypertensive and diabetic drugs in the Family Health Strategy, State of Pernambuco, Brazil.

    Science.gov (United States)

    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.

  20. Modeling of drug and drug-encapsulated nanoparticle transport in patient-specific coronary artery walls to treat vulnerable plaques

    KAUST Repository

    Hossain, Shaolie S.

    2010-01-01

    The main objective of this work is to develop computational tools to support the design of a catheter-based local drug delivery system that uses nanoparticles as drug carriers in order to treat vulnerable plaques and diffuse atherosclerotic disease.

  1. Neuro-fuzzy models as an IVIVR tool and their applicability in generic drug development.

    Science.gov (United States)

    Opara, Jerneja; Legen, Igor

    2014-03-01

    The usefulness of neuro-fuzzy (NF) models as an alternative in vitro-in vivo relationship (IVIVR) tool and as a support to quality by design (QbD) in generic drug development is presented. For drugs with complicated pharmacokinetics, immediate release drugs or nasal sprays, suggested level A correlations are not capable to satisfactorily describe the IVIVR. NF systems were recognized as a reasonable method in comparison to the published approaches for development of IVIVR. Consequently, NF models were built to predict 144 pharmacokinetic (PK) parameter ratios required for demonstration of bioequivalence (BE) for 88 pivotal BE studies. Input parameters of models included dissolution data and their combinations in different media, presence of food, formulation strength, technology type, particle size, and spray pattern for nasal sprays. Ratios of PK parameters Cmax or AUC were used as output variables. The prediction performance of models resulted in the following values: 79% of models have acceptable external prediction error (PE) below 10%, 13% of models have inconclusive PE between 10 and 20%, and remaining 8% of models show inadequate PE above 20%. Average internal predictability (LE) is 0.3%, and average external predictability of all models results in 7.7%. In average, models have acceptable internal and external predictabilities with PE lower than 10% and are therefore useful for IVIVR needs during formulation development, as a support to QbD and for the prediction of BE study outcome.

  2. Evaluation of modafinil as a perpetrator of metabolic drug-drug interactions using a model informed cocktail reaction phenotyping trial protocol.

    Science.gov (United States)

    Rowland, Angela; van Dyk, Madelé; Warncken, David; Mangoni, Arduino A; Sorich, Michael J; Rowland, Andrew

    2018-03-01

    To evaluate the capacity for modafinil to be a perpetrator of metabolic drug-drug interactions by altering cytochrome P450 activity following a single dose and dosing to steady state. A single centre, open label, single sequence cocktail drug interaction trial. On days 0, 2 and 8 participants were administered an oral drug cocktail comprising 100 mg caffeine, 30 mg dextromethorphan, 25 mg losartan, 1 mg midazolam and 20 mg enteric-coated omeprazole. Timed blood samples were collected prior to and for up to 6 h post cocktail dosing. Between days 2 and 8 participants orally self-administered 200 mg modafinil each morning. Following a single 200 mg dose of modafinil mean (± 95% CI) AUC ratios for caffeine, dextromethorphan, losartan, midazolam and omeprazole were 0.95 (± 0.08), 1.01 (± 0.35), 0.97 (± 0.10), 0.98 (± 0.10) and 1.36 (± 0.06), respectively. Following dosing of modafinil to steady state (200 mg for 7 days), AUC ratios for caffeine, dextromethorphan, losartan, midazolam and omeprazole were 0.90 (± 0.16), 0.79 (± 0.09), 0.98 (± 0.11), 0.66 (± 0.12) and 1.90 (± 0.53), respectively. These data support consideration of the risk of clinically relevant metabolic drug-drug interactions perpetrated by modafinil when this drug is co-administered with drugs that are primarily cleared by CYP2C19 (single modafinil dose or steady state modafinil dosing) or CYP3A4 (steady state modafinil dosing only) catalysed metabolic pathways. © 2017 The British Pharmacological Society.

  3. Effect of drugs of abuse on social behaviour: a review of animal models.

    Science.gov (United States)

    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.

  4. Drug interaction at hERG channel: In vitro assessment of the electrophysiological consequences of drug combinations and comparison against theoretical models.

    Science.gov (United States)

    Wiśniowska, Barbara; Lisowski, Bartosz; Kulig, Magdalena; Polak, Sebastian

    2018-04-01

    Drugs carry a proarrhythmic risk, which gets even greater when they are used in combination. In vitro assessment of the proarrhythmic potential of drugs is limited to one compound and thus neglects the potential of drug-drug interactions, including those involving active metabolites. Here we present the results of an in vitro study of potential drug-drug interactions at the level of the hERG channel for the combination of up to three compounds: loratadine, desloratadine and ketoconazole. Experiments were performed at room temperature on an automated patch-clamp device CytoPatch 2, with the use of heterogeneously, stably transfected HEK cells. Single drugs, pairs and triplets were used. The results provided as the inhibition of the I Kr current for pairs were compared against the calculated theoretical interaction. Models applied to calculate the combined effect of inhibitory actions of simultaneously given drugs include: (1) simple additive model with a maximal inhibition limit of 1 (all channels blocked in 100%); (2) Bliss independence; and (3) Loewe additivity. The observed IC 50 values for loratadine, desloratadine and ketoconazole were 5.15, 1.95 and 0.74 μm respectively. For the combination of drugs tested in pairs, the effect was concentration dependent. In lower concentrations, the synergistic effect was observed, while for the highest tested concentrations it was subadditive. To triple the effect, it was subadditive regardless of concentrations. The square root of sum of squares of differences between the observed and predicted total inhibition was calculated to assess the theoretical interaction models. For most of the drugs, the allotopic model offered the best fit. Copyright © 2017 John Wiley & Sons, Ltd.

  5. GENESIS - The GENEric SImulation System for Modelling State Transitions.

    Science.gov (United States)

    Gillman, Matthew S

    2017-09-20

    This software implements a discrete time Markov chain model, used to model transitions between states when the transition probabilities are known a priori . It is highly configurable; the user supplies two text files, a "state transition table" and a "config file", to the Perl script genesis.pl. Given the content of these files, the script generates a set of C++ classes based on the State design pattern, and a main program, which can then be compiled and run. The C++ code generated is based on the specification in the text files. Both multiple branching and bi-directional transitions are allowed. The software has been used to model the natural histories of colorectal cancer in Mexico. Although written primarily to model such disease processes, it can be used in any process which depends on discrete states with known transition probabilities between those states. One suitable area may be in environmental modelling. A test suite is supplied with the distribution. Due to its high degree of configurability and flexibility, this software has good re-use potential. It is stored on the Figshare repository.

  6. Agreement between PRE2DUP register data modeling method and comprehensive drug use interview among older persons

    Science.gov (United States)

    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

  7. Drug delivery to solid tumors: the predictive value of the multicellular tumor spheroid model for nanomedicine screening

    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

  8. Influence of pH on Drug Absorption from the Gastrointestinal Tract: A Simple Chemical Model

    Science.gov (United States)

    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.

  9. 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.

  10. Rapid increase in the use of oral antidiabetic drugs in the United States, 1990-2001.

    Science.gov (United States)

    Wysowski, Diane K; Armstrong, George; Governale, Laura

    2003-06-01

    To describe the use of oral antidiabetic drugs for management of type 2 diabetes in the U.S. from 1990 through 2001. Data on oral antidiabetic drugs were derived from two pharmaceutical marketing databases from IMS Health, the National Prescription Audit Plus and the National Disease and Therapeutic Index. In 1990, 23.4 million outpatient prescriptions of oral antidiabetic agents were dispensed. By 2001, this number had increased 3.9-fold, to 91.8 million prescriptions. Glipizide and glyburide, two sulfonylurea medications, accounted for approximately 77% of prescriptions of oral antidiabetic drugs in 1990 and 35.5% of prescriptions in 2001. By 2001, the biguanide metformin (approved in 1995) had captured approximately 33% of prescriptions, and the thiazolidinedione insulin sensitizers (rosiglitazone and pioglitazone marketed beginning in 1999) accounted for approximately 17% of market share. Compared with patients treated in 1990, those in 2001 were proportionately younger and they more often used oral antidiabetic drugs and insulin in combination. Internists and general and family practitioners were the primary prescribers of this class of drugs. Consistent with the reported increase in the prevalence of type 2 diabetes, the number of dispensed outpatient prescriptions of oral antidiabetic drugs increased rapidly between 1990 and 2001. This period was marked by an increase in the treatment of younger people and the use of oral antidiabetic drugs in combination. With the approval in the last decade of several new types of oral antidiabetic medications with different mechanisms of action, options for management of type 2 diabetes have expanded.

  11. Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development

    Science.gov (United States)

    Swat, MJ; Moodie, S; Wimalaratne, SM; Kristensen, NR; Lavielle, M; Mari, A; Magni, P; Smith, MK; Bizzotto, R; Pasotti, L; Mezzalana, E; Comets, E; Sarr, C; Terranova, N; Blaudez, E; Chan, P; Chard, J; Chatel, K; Chenel, M; Edwards, D; Franklin, C; Giorgino, T; Glont, M; Girard, P; Grenon, P; Harling, K; Hooker, AC; Kaye, R; Keizer, R; Kloft, C; Kok, JN; Kokash, N; Laibe, C; Laveille, C; Lestini, G; Mentré, F; Munafo, A; Nordgren, R; Nyberg, HB; Parra-Guillen, ZP; Plan, E; Ribba, B; Smith, G; Trocóniz, IF; Yvon, F; Milligan, PA; Harnisch, L; Karlsson, M; Hermjakob, H; Le Novère, N

    2015-01-01

    The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps. PMID:26225259

  12. Prediction models for drug-induced hepatotoxicity by using weighted molecular fingerprints.

    Science.gov (United States)

    Kim, Eunyoung; Nam, Hojung

    2017-05-31

    Drug-induced liver injury (DILI) is a critical issue in drug development because DILI causes failures in clinical trials and the withdrawal of approved drugs from the market. There have been many attempts to predict the risk of DILI based on in vivo and in silico identification of hepatotoxic compounds. In the current study, we propose the in silico prediction model predicting DILI using weighted molecular fingerprints. In this study, we used 881 bits of molecular fingerprint and used as features describing presence or absence of each substructure of compounds. Then, the Bayesian probability of each substructure was calculated and labeled (positive or negative for DILI), and a weighted fingerprint was determined from the ratio of DILI-positive to DILI-negative probability values. Using weighted fingerprint features, the prediction models were trained and evaluated with the Random Forest (RF) and Support Vector Machine (SVM) algorithms. The constructed models yielded accuracies of 73.8% and 72.6%, AUCs of 0.791 and 0.768 in cross-validation. In independent tests, models achieved accuracies of 60.1% and 61.1% for RF and SVM, respectively. The results validated that weighted features helped increase overall performance of prediction models. The constructed models were further applied to the prediction of natural compounds in herbs to identify DILI potential, and 13,996 unique herbal compounds were predicted as DILI-positive with the SVM model. The prediction models with weighted features increased the performance compared to non-weighted models. Moreover, we predicted the DILI potential of herbs with the best performed model, and the prediction results suggest that many herbal compounds could have potential to be DILI. We can thus infer that taking natural products without detailed references about the relevant pathways may be dangerous. Considering the frequency of use of compounds in natural herbs and their increased application in drug development, DILI labeling

  13. Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study.

    Science.gov (United States)

    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

  14. 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.

  15. What is a new drug worth? An innovative model for performance-based pricing.

    Science.gov (United States)

    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.

  16. Definition of the "Drug-Angiogenic-Activity-Index" that allows the quantification of the positive and negative angiogenic active drugs: a study based on the chorioallantoic membrane model.

    Science.gov (United States)

    Demir, Resit; Peros, Georgios; Hohenberger, Werner

    2011-06-01

    Since the introduction of the angiogenic therapy by Folkman et al. in the 1970'ies many antiangiogenic drugs were identified. Only few of them are still now in clinical use. Also the Vascular Endothelial Growth Factor (VEGF), the cytokine with the highest angiogenic activity, has been identified. Its antagonist, Bevacizumab, is produced and admitted for the angiogenic therapy in first line for metastatic colorectal cancer. When we look at preclinical studies, they fail of in vivo models that define the "Drug-Angiogenic-Activity-Index" of angiogenic or antiangiogenic drugs. This work proposes a possible standardized procedure to define the "Drug Angiogenic Activity Index" by counting the vascular intersections (VIS) on the Chorioallantoic Membrane after drug application. The equation was defined as follows: {ΔVIS[Drug]-ΔVIS[Control]} / Δ VIS[Control]. For VEGF a Drug-Angiogenic-Activity-Index of 0.92 was found and for Bevacizumab a -1. This means almost that double of the naturally angiogenic activity was achieved by VEGF on the Chorioallantoic membrane. A complete blocking of naturally angiogenic activity was observed after Bevacizumabs application. Establishing the "Drug-Angiogenic-Activity-Index" in the preclinical phase will give us an impact of effectiveness for the new constructed antiangiogenic drugs like the impact of effectiveness in the cortisone family.

  17. Caenorhabditis elegans as a Model to Study the Molecular and Genetic Mechanisms of Drug Addiction.

    Science.gov (United States)

    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

  18. Rethinking 'flexibilities' in the international drug control system-Potential, precedents and models for reforms.

    Science.gov (United States)

    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

  19. "A state bordering on insanity"?: identifying drug addiction in nineteenth-century Canadian asylums.

    Science.gov (United States)

    Malleck, D

    1999-01-01

    This article examines the growing awareness of drug addiction as form of mental illness in several Canadian lunatic asylums in the last half of the nineteenth century and the beginning of the twentieth. Whereas in the 1870s and 1880s, medical and reform associations formed to cure and treat addiction and inebriety, asylum evidence suggests that it was not until the turn of the century that drug habituation was considered a condition which merited admission to asylum. Prior to the turn of the century, drug use appeared in the psychological profile of asylum entrants only as an attendant condition of a more traditional form of mental illness, such as mania or melancholia. Asylum physicians, seeking traditional categories, and utilizing subjective classification methods, generally would not consider addiction to be a distinct mental illness. At the end of the century, shifts in diagnostic convention and the official endorsement of those shifts signalled a change that was taking place in the asylum. The impact of drug addiction on the psychological profile of a patient was attracting more attention in the asylum. Subsequently drug addiction joined other earlier causes of mental illness, such as masturbation, and also began to be recognized as a mental condition worthy of treatment at the public asylum. Its status as mental disease proper, however, remained a point of debate.

  20. Lipid-Based Formulations Can Enable the Model Poorly Water-Soluble Weakly Basic Drug Cinnarizine to Precipitate in an Amorphous-Salt Form during in Vitro Digestion

    DEFF Research Database (Denmark)

    Khan, Jamal; Rades, Thomas; Boyd, Ben J

    2016-01-01

    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......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...