[Optimization of cluster analysis based on drug resistance profiles of MRSA isolates].

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Tani, Hiroya; Kishi, Takahiko; Gotoh, Minehiro; Yamagishi, Yuka; Mikamo, Hiroshige

2015-12-01

We examined 402 methicillin-resistant Staphylococcus aureus (MRSA) strains isolated from clinical specimens in our hospital between November 19, 2010 and December 27, 2011 to evaluate the similarity between cluster analysis of drug susceptibility tests and pulsed-field gel electrophoresis (PFGE). The results showed that the 402 strains tested were classified into 27 PFGE patterns (151 subtypes of patterns). Cluster analyses of drug susceptibility tests with the cut-off distance yielding a similar classification capability showed favorable results--when the MIC method was used, and minimum inhibitory concentration (MIC) values were used directly in the method, the level of agreement with PFGE was 74.2% when 15 drugs were tested. The Unweighted Pair Group Method with Arithmetic mean (UPGMA) method was effective when the cut-off distance was 16. Using the SIR method in which susceptible (S), intermediate (I), and resistant (R) were coded as 0, 2, and 3, respectively, according to the Clinical and Laboratory Standards Institute (CLSI) criteria, the level of agreement with PFGE was 75.9% when the number of drugs tested was 17, the method used for clustering was the UPGMA, and the cut-off distance was 3.6. In addition, to assess the reproducibility of the results, 10 strains were randomly sampled from the overall test and subjected to cluster analysis. This was repeated 100 times under the same conditions. The results indicated good reproducibility of the results, with the level of agreement with PFGE showing a mean of 82.0%, standard deviation of 12.1%, and mode of 90.0% for the MIC method and a mean of 80.0%, standard deviation of 13.4%, and mode of 90.0% for the SIR method. In summary, cluster analysis for drug susceptibility tests is useful for the epidemiological analysis of MRSA.

Pharmacokinetic-Pharmacodynamic (PKPD) Analysis with Drug Discrimination.

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Negus, S Stevens; Banks, Matthew L

2016-08-30

Discriminative stimulus and other drug effects are determined by the concentration of drug at its target receptor and by the pharmacodynamic consequences of drug-receptor interaction. For in vivo procedures such as drug discrimination, drug concentration at receptors in a given anatomical location (e.g., the brain) is determined both by the dose of drug administered and by pharmacokinetic processes of absorption, distribution, metabolism, and excretion that deliver drug to and from that anatomical location. Drug discrimination data are often analyzed by strategies of dose-effect analysis to determine parameters such as potency and efficacy. Pharmacokinetic-Pharmacodynamic (PKPD) analysis is an alternative to conventional dose-effect analysis, and it relates drug effects to a measure of drug concentration in a body compartment (e.g., venous blood) rather than to drug dose. PKPD analysis can yield insights on pharmacokinetic and pharmacodynamic determinants of drug action. PKPD analysis can also facilitate translational research by identifying species differences in pharmacokinetics and providing a basis for integrating these differences into interpretation of drug effects. Examples are discussed here to illustrate the application of PKPD analysis to the evaluation of drug effects in rhesus monkeys trained to discriminate cocaine from saline.

Characteristics of the anti-dementia drug system of Zisu Fang preparations based on pharmacokinetic and pharmacodynamic analysis

Directory of Open Access Journals (Sweden)

Jianye Quan

2017-04-01

Conclusions: Based on the PK and PD correlation analysis, baicalin, rosmarinic acid, salvianolic acid B, matrine, and tanshinone IIA are the main active ingredients of Zisu Fang preparations with regard to its anti-dementia effects, and represent the basic characteristics of drug system: natures, synergy, and affinity.

Protein-Based Drug-Delivery Materials

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Dave Jao

2017-05-01

Full Text Available There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based polymers compared to synthetic polymers have the advantages of good biocompatibility, biodegradability, environmental sustainability, cost effectiveness and availability. This review addresses the sources of protein-based polymers, compares the similarity and differences, and highlights characteristic properties and functionality of these protein materials for sustained and controlled drug release. Targeted drug delivery using highly functional multicomponent protein composites to guide active drugs to the site of interest will also be discussed. A systematical elucidation of drug-delivery efficiency in the case of molecular weight, particle size, shape, morphology, and porosity of materials will then be demonstrated to achieve increased drug absorption. Finally, several important biomedical applications of protein-based materials with drug-delivery function—including bone healing, antibiotic release, wound healing, and corneal regeneration, as well as diabetes, neuroinflammation and cancer treatments—are summarized at the end of this review.

Community-based management versus traditional hospitalization in treatment of drug-resistant tuberculosis: a systematic review and meta-analysis.

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Williams, Abimbola Onigbanjo; Makinde, Olusesan Ayodeji; Ojo, Mojisola

2016-01-01

Multidrug drug resistant Tuberculosis (MDR-TB) and extensively drug resistant Tuberculosis (XDR-TB) have emerged as significant public health threats worldwide. This systematic review and meta-analysis aimed to investigate the effects of community-based treatment to traditional hospitalization in improving treatment success rates among MDR-TB and XDR-TB patients in the 27 MDR-TB High burden countries (HBC). We searched PubMed, Cochrane, Lancet, Web of Science, International Journal of Tuberculosis and Lung Disease, and Centre for Reviews and Dissemination (CRD) for studies on community-based treatment and traditional hospitalization and MDR-TB and XDR-TB from the 27 MDR-TB HBC. Data on treatment success and failure rates were extracted from retrospective and prospective cohort studies, and a case control study. Sensitivity analysis, subgroup analyses, and meta-regression analysis were used to explore bias and potential sources of heterogeneity. The final sample included 16 studies involving 3344 patients from nine countries; Bangladesh, China, Ethiopia, Kenya, India, South Africa, Philippines, Russia, and Uzbekistan. Based on a random-effects model, we observed a higher treatment success rate in community-based treatment (Point estimate = 0.68, 95 % CI: 0.59 to 0.76, p   18 months, and regimen with drugs >5 reported higher treatment success rate. In the meta-regression model, age of patients, adverse events, treatment duration, and lost to follow up explains some of the heterogeneity of treatment effects between studies. Community-based management improved treatment outcomes. A mix of interventions with DOTS-Plus throughout therapy and treatment duration > 18 months as well as strategies in place for lost to follow up and adverse events should be considered in MDR-TB and XDR-TB interventions, as they influenced positively, treatment success.

Silk Electrogel Based Gastroretentive Drug Delivery System

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Wang, Qianrui

Gastric cancer has become a global pandemic and there is imperative to develop efficient therapies. Oral dosing strategy is the preferred route to deliver drugs for treating the disease. Recent studies suggested silk electro hydrogel, which is pH sensitive and reversible, has potential as a vehicle to deliver the drug in the stomach environment. The aim of this study is to establish in vitro electrogelation e-gel based silk gel as a gastroretentive drug delivery system. We successfully extended the duration of silk e-gel in artificial gastric juice by mixing silk solution with glycerol at different ratios before the electrogelation. Structural analysis indicated the extended duration was due to the change of beta sheet content. The glycerol mixed silk e-gel had good doxorubicin loading capability and could release doxorubicin in a sustained-release profile. Doxorubicin loaded silk e-gels were applied to human gastric cancer cells. Significant cell viability decrease was observed. We believe that with further characterization as well as functional analysis, the silk e-gel system has the potential to become an effective vehicle for gastric drug delivery applications.

The Social Construction of "Evidence-Based" Drug Prevention Programs: A Reanalysis of Data from the Drug Abuse Resistance Education (DARE) Program

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Gorman, Dennis M.; Huber, J. Charles, Jr.

2009-01-01

This study explores the possibility that any drug prevention program might be considered "evidence-based" given the use of data analysis procedures that optimize the chance of producing statistically significant results by reanalyzing data from a Drug Abuse Resistance Education (DARE) program evaluation. The analysis produced a number of…

Fast analysis of narcotic drugs by optical chemical imaging

International Nuclear Information System (INIS)

Fisher, Michal; Bulatov, Vallery; Schechter, Israel

2003-01-01

A new technique is proposed for fast detection, identification and imaging of narcotic drugs in their solid phase. This technique, which requires only a tiny sample of a few microns, is based on microscopic chemical imaging. Minor sample preparation is required, and results are obtained within seconds. As far as we know, this is the most sensitive detection system available today for solid drugs. The technique can be applied for fast analysis of minute drug residues, and therefore is of considerable importance for forensic applications. It is shown that identification of drug traces in realistic matrixes is possible. Two main methods were applied in this study for detection of drugs and drug derivatives. The first method was based on direct detection and chemical imaging of the auto-fluorescence of the analyzed drugs. This method is applicable when the analyzed drug emits fluorescence under the experiment conditions, such as lysergic acid diethylamide (known as LSD). The second method was used for obtaining chemical imaging of drugs that do not fluoresce under the experiment conditions. In these cases fluorescent labeling dyes were applied to the examined samples (including the drug and the matrix). Both methods are simple and rapid, and require minor or no sample preparation at all. Detection limits are very low in the picogram range

Silk Fibroin-Based Nanoparticles for Drug Delivery

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Zhao, Zheng; Li, Yi; Xie, Mao-Bin

2015-01-01

Silk fibroin (SF) is a protein-based biomacromolecule with excellent biocompatibility, biodegradability and low immunogenicity. The development of SF-based nanoparticles for drug delivery have received considerable attention due to high binding capacity for various drugs, controlled drug release properties and mild preparation conditions. By adjusting the particle size, the chemical structure and properties, the modified or recombinant SF-based nanoparticles can be designed to improve the therapeutic efficiency of drugs encapsulated into these nanoparticles. Therefore, they can be used to deliver small molecule drugs (e.g., anti-cancer drugs), protein and growth factor drugs, gene drugs, etc. This paper reviews recent progress on SF-based nanoparticles, including chemical structure, properties, and preparation methods. In addition, the applications of SF-based nanoparticles as carriers for therapeutic drugs are also reviewed. PMID:25749470

Model-based global sensitivity analysis as applied to identification of anti-cancer drug targets and biomarkers of drug resistance in the ErbB2/3 network

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Lebedeva, Galina; Sorokin, Anatoly; Faratian, Dana; Mullen, Peter; Goltsov, Alexey; Langdon, Simon P.; Harrison, David J.; Goryanin, Igor

2012-01-01

High levels of variability in cancer-related cellular signalling networks and a lack of parameter identifiability in large-scale network models hamper translation of the results of modelling studies into the process of anti-cancer drug development. Recently global sensitivity analysis (GSA) has been recognised as a useful technique, capable of addressing the uncertainty of the model parameters and generating valid predictions on parametric sensitivities. Here we propose a novel implementation of model-based GSA specially designed to explore how multi-parametric network perturbations affect signal propagation through cancer-related networks. We use area-under-the-curve for time course of changes in phosphorylation of proteins as a characteristic for sensitivity analysis and rank network parameters with regard to their impact on the level of key cancer-related outputs, separating strong inhibitory from stimulatory effects. This allows interpretation of the results in terms which can incorporate the effects of potential anti-cancer drugs on targets and the associated biological markers of cancer. To illustrate the method we applied it to an ErbB signalling network model and explored the sensitivity profile of its key model readout, phosphorylated Akt, in the absence and presence of the ErbB2 inhibitor pertuzumab. The method successfully identified the parameters associated with elevation or suppression of Akt phosphorylation in the ErbB2/3 network. From analysis and comparison of the sensitivity profiles of pAkt in the absence and presence of targeted drugs we derived predictions of drug targets, cancer-related biomarkers and generated hypotheses for combinatorial therapy. Several key predictions have been confirmed in experiments using human ovarian carcinoma cell lines. We also compared GSA-derived predictions with the results of local sensitivity analysis and discuss the applicability of both methods. We propose that the developed GSA procedure can serve as a

Etiology of Drug Abuse: A Narrative Analysis

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Nadjme Jadidi

2014-01-01

Full Text Available Introduction and Aim. Further gains in the prevention of drug abuse disorders require in-depth and holistic understanding of the risk factors of addiction from different perspectives. Lay persons and experts have different concepts of risk which could complement each other. The purpose of this study was to elaborate drug abuse risk factors through the story of individuals who had become drug dependent. Design and Methods. In this qualitative research, 33 individuals attending treatment centres for drug abuse were interviewed about the story of their addiction in Kerman, Iran. Interview questions were around the story of the participants. Results. All participants were male and in the age range of 18–40 years. Narrative analysis identified five themes as the main risk factors: family factors, peer pressure, the effect of gateway drugs (especially waterpipe, individual characteristics, and the community factors. More emphasis was placed upon the role of family factors, peer influence, and gateway effect. Discussion and Conclusion. This study elicited information from drug dependent subjects regarding the risk factors of drug abuse. According to drug dependent individuals’ views, more attention should be devoted to family and peer influences by policy makers, in developing culture-based preventive strategies.

Neutron-based portable drug probe

International Nuclear Information System (INIS)

Womble, P. C.; Vourvopoulos, G.; Ball Howard, J.; Paschal, J.

1999-01-01

Based on previous measurements, a probe prototype for contraband detection utilizing the neutron technique of Pulsed Fast-Thermal Neutron Analysis (PFTNA) is being constructed. The prototype weighs less than 45 kg and is composed of a probe (5 cm diameter), a power pack and a data acquisition and display system. The probe is designed to be inserted in confined spaces such as the boiler of a ship or a tanker truck filled with liquid. The probe provides information on a) the elemental content, and b) the density variations of the interrogated object. By measuring elemental content, the probe can differentiate between innocuous materials and drugs. Density variations can be found through fast neutron transmission. In all cases, hidden drugs are identified through the measurement of the elemental content of the object, and the comparison of expected and measured elemental ratios

Protein-Based Drug-Delivery Materials

OpenAIRE

Jao, Dave; Xue, Ye; Medina, Jethro; Hu, Xiao

2017-01-01

There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based pol...

Arthritis Genetics Analysis Aids Drug Discovery

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... NIH Research Matters January 13, 2014 Arthritis Genetics Analysis Aids Drug Discovery An international research team identified 42 new ... Edition Distracted Driving Raises Crash Risk Arthritis Genetics Analysis Aids Drug Discovery Oxytocin Affects Facial Recognition Connect with Us ...

e-Drug3D: 3D structure collections dedicated to drug repurposing and fragment-based drug design.

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Pihan, Emilie; Colliandre, Lionel; Guichou, Jean-François; Douguet, Dominique

2012-06-01

In the drug discovery field, new uses for old drugs, selective optimization of side activities and fragment-based drug design (FBDD) have proved to be successful alternatives to high-throughput screening. e-Drug3D is a database of 3D chemical structures of drugs that provides several collections of ready-to-screen SD files of drugs and commercial drug fragments. They are natural inputs in studies dedicated to drug repurposing and FBDD. e-Drug3D collections are freely available at http://chemoinfo.ipmc.cnrs.fr/e-drug3d.html either for download or for direct in silico web-based screenings.

Investigating the correlation between wastewater analysis and roadside drug testing in South Australia.

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Bade, Richard; Tscharke, Benjamin J; Longo, Marie; Cooke, Richard; White, Jason M; Gerber, Cobus

2018-04-10

The societal impact of drug use is well known. An example is when drug-intoxicated drivers increase the burden on policing and healthcare services. This work presents the correlation of wastewater analysis (using UHPLC-MS/MS) and positive roadside drug testing results for methamphetamine, 3,4-methylenedioxymethamphetamine (MDMA) and cannabis from December 2011-December 2016 in South Australia. Methamphetamine and MDMA showed similar trends between the data sources with matching increases and decreases, respectively. Cannabis was relatively steady based on wastewater analysis, but the roadside drug testing data started to diverge in the final part of the measurement period. The ability to triangulate data as shown here validates both wastewater analysis and roadside drug testing. This suggests that changes in overall population drug use revealed by WWA is consistent and proportional with changes in drug-driving behaviours. The results show that, at higher levels of drug use as measured by wastewater analysis, there is an increase in drug driving in the community and therefore more strain on health services and police. Copyright © 2018 Elsevier B.V. All rights reserved.

Deuterated drugs; updates and obviousness analysis.

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Timmins, Graham S

2017-12-01

The pharmacokinetics and/or toxicity of many known drugs can be modified by selective deuteration, an area of significant commercial interest and scientific and regulatory progress. Areas covered: This review firstly discusses recent developments in deuterated drugs including the FDA approval of deutetrabenazine. Secondly, it discusses 35 U.S.C. §103 'obviousness' as it relates to recent patent prosecution, and also to Inter Partes Review (IPR). IPR is a new post-award review of patentability under §102 or §103, two IPR petitions upon deuterated drugs have been instituted and included §103 arguments. Finally, an extended analysis of §103 obviousness based upon the practices of major pharmaceutical companies is provided, that supports rather late priority dates, while §102 is also discussed. Expert opinion: The total value of transactions involving deuterated drugs is close to $5 billion. While the importance of §103 'obviousness' rejections remains in patent applications under current prosecution, IPR of issued patents is developing and will affect likely affect §103 interpretations in this area. However, patents are still issuing with later priority dates, and further litigation will likely occur.

Budget impact analysis of drugs for ultra-orphan non-oncological diseases in Europe.

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Schlander, Michael; Adarkwah, Charles Christian; Gandjour, Afschin

2015-02-01

Ultra-orphan diseases (UODs) have been defined by a prevalence of less than 1 per 50,000 persons. However, little is known about budget impact of ultra-orphan drugs. For analysis, the budget impact analysis (BIA) had a time horizon of 10 years (2012-2021) and a pan-European payer's perspective, based on prevalence data for UODs for which patented drugs are available and/or for which drugs are in clinical development. A total of 18 drugs under patent protection or orphan drug designation for non-oncological UODs were identified. Furthermore, 29 ultra-orphan drugs for non-oncological diseases under development that have the potential of reaching the market by 2021 were found. Total budget impact over 10 years was estimated to be €15,660 and €4965 million for approved and pipeline ultra-orphan drugs, respectively (total: €20,625 million). The analysis does not support concerns regarding an uncontrolled growth in expenditures for drugs for UODs.

Research on Optimization of Pooling System and Its Application in Drug Supply Chain Based on Big Data Analysis.

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Wu, DengFeng; Mao, Hongyi

2017-01-01

Reform of drug procurement is being extensively implemented and expanded in China, especially in today's big data environment. However, the pattern of supply mode innovation lags behind procurement improvement. Problems in financial strain and supply break frequently occur, which affect the stability of drug supply. Drug Pooling System is proposed and applied in a few pilot cities to resolve these problems. From the perspective of supply chain, this study analyzes the process of setting important parameters and sets out the tasks of involved parties in a pooling system according to the issues identified in the pilot run. The approach is based on big data analysis and simulation using system dynamic theory and modeling of Vensim software to optimize system performance. This study proposes a theoretical framework to resolve problems and attempts to provide a valuable reference for future application of pooling systems.

Nanostructured surfaces for analysis of anticancer drug and cell diagnosis based on electrochemical and SERS tools

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El-Said, Waleed A.; Yoon, Jinho; Choi, Jeong-Woo

2018-04-01

Discovering new anticancer drugs and screening their efficacy requires a huge amount of resources and time-consuming processes. The development of fast, sensitive, and nondestructive methods for the in vitro and in vivo detection of anticancer drugs' effects and action mechanisms have been done to reduce the time and resources required to discover new anticancer drugs. For the in vitro and in vivo detection of the efficiency, distribution, and action mechanism of anticancer drugs, the applications of electrochemical techniques such as electrochemical cell chips and optical techniques such as surface-enhanced Raman spectroscopy (SERS) have been developed based on the nanostructured surface. Research focused on electrochemical cell chips and the SERS technique have been reviewed here; electrochemical cell chips based on nanostructured surfaces have been developed for the in vitro detection of cell viability and the evaluation of the effects of anticancer drugs, which showed the high capability to evaluate the cytotoxic effects of several chemicals at low concentrations. SERS technique based on the nanostructured surface have been used as label-free, simple, and nondestructive techniques for the in vitro and in vivo monitoring of the distribution, mechanism, and metabolism of different anticancer drugs at the cellular level. The use of electrochemical cell chips and the SERS technique based on the nanostructured surface should be good tools to detect the effects and action mechanisms of anticancer drugs.

Introduction to fragment-based drug discovery.

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Erlanson, Daniel A

2012-01-01

Fragment-based drug discovery (FBDD) has emerged in the past decade as a powerful tool for discovering drug leads. The approach first identifies starting points: very small molecules (fragments) that are about half the size of typical drugs. These fragments are then expanded or linked together to generate drug leads. Although the origins of the technique date back some 30 years, it was only in the mid-1990s that experimental techniques became sufficiently sensitive and rapid for the concept to be become practical. Since that time, the field has exploded: FBDD has played a role in discovery of at least 18 drugs that have entered the clinic, and practitioners of FBDD can be found throughout the world in both academia and industry. Literally dozens of reviews have been published on various aspects of FBDD or on the field as a whole, as have three books (Jahnke and Erlanson, Fragment-based approaches in drug discovery, 2006; Zartler and Shapiro, Fragment-based drug discovery: a practical approach, 2008; Kuo, Fragment based drug design: tools, practical approaches, and examples, 2011). However, this chapter will assume that the reader is approaching the field with little prior knowledge. It will introduce some of the key concepts, set the stage for the chapters to follow, and demonstrate how X-ray crystallography plays a central role in fragment identification and advancement.

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

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Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Assessment of Web-Based Consumer Reviews as a Resource for Drug Performance

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Adusumalli, Swarnaseetha; Lee, HueyTyng; Hoi, Qiangze; Koo, Si-Lin; Tan, Iain Beehuat

2015-01-01

Background Some health websites provide a public forum for consumers to post ratings and reviews on drugs. Drug reviews are easily accessible and comprehensible, unlike clinical trials and published literature. Because the public increasingly uses the Internet as a source of medical information, it is important to know whether such information is reliable. Objective We aim to examine whether Web-based consumer drug ratings and reviews can be used as a resource to compare drug performance. Methods We analyzed 103,411 consumer-generated reviews on 615 drugs used to treat 249 disease conditions from the health website WebMD. Statistical analysis identified 427 drug pairs from 24 conditions for which two drugs treating the same condition had significantly and substantially different satisfaction ratings (with at least a half-point difference between Web-based ratings and Paddictive properties were rated higher than their counterparts in Web-based reviews, and (3) second-line or alternative drugs were rated higher. In addition, Web-based ratings indicated drug delivery problems. If FDA black box warning labels are used to resolve disagreements between publications and online trends, the concordance rate increases to 71% (55/77) (Pmanufacturers to assess the performance of a drug. However, one should be cautious to rely solely on consumer reviews as ratings can be strongly influenced by the consumer experience. PMID:26319108

SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

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Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development and Evaluation of Cefadroxil Drug Loaded Biopolymeric Films Based on Chitosan-Furfural Schiff Base

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Dixit, Ritu B.; Uplana, Rahul A.; Patel, Vishnu A.; Dixit, Bharat C.; Patel, Tarosh S.

2010-01-01

Cefadroxil drug loaded biopolymeric films of chitosan-furfural schiff base were prepared by reacting chitosan with furfural in presence of acetic acid and perchloric acid respectively for the external use. Prepared films were evaluated for their strength, swelling index, thickness, drug content, uniformity, tensile strength, percent elongation, FTIR spectral analysis and SEM. The results of in vitro diffusion studies revealed that the films exhibited enhanced drug diffusion as compared to the films prepared using untreated chitosan. The films also demonstrated good to moderate antibacterial activities against selective gram positive and gram negative bacteria. PMID:21179325

Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors.

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Mitra, A K; Mukherjee, U K; Harding, T; Jang, J S; Stessman, H; Li, Y; Abyzov, A; Jen, J; Kumar, S; Rajkumar, V; Van Ness, B

2016-05-01

Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that have a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Although genome profiling studies have demonstrated heterogeneity in subclonal architecture that may ultimately lead to relapse, a gene expression-based prediction program that can identify, distinguish and quantify drug response in sub-populations within a bulk population of myeloma cells is lacking. In this study, we performed targeted transcriptome analysis on 528 pre-treatment single cells from 11 myeloma cell lines and 418 single cells from 8 drug-naïve MM patients, followed by intensive bioinformatics and statistical analysis for prediction of proteasome inhibitor sensitivity in individual cells. Using our previously reported drug response gene expression profile signature at the single-cell level, we developed an R Statistical analysis package available at https://github.com/bvnlabSCATTome, SCATTome (single-cell analysis of targeted transcriptome), that restructures the data obtained from Fluidigm single-cell quantitative real-time-PCR analysis run, filters missing data, performs scaling of filtered data, builds classification models and predicts drug response of individual cells based on targeted transcriptome using an assortment of machine learning methods. Application of SCATT should contribute to clinically relevant analysis of intratumor heterogeneity, and better inform drug choices based on subclonal cellular responses.

Young people's attitudes towards illicit drugs: A population-based study.

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Friis, Karina; Østergaard, Jeanette; Reese, Sidsel; Lasgaard, Mathias

2017-12-01

Previous studies indicate that young people who have positive attitudes towards illicit drugs are more inclined to experiment with them. The first aim of our study was to identify the sociodemographic and risk behaviour characteristics of young people (16-24 years) with positive attitudes towards illicit drug use. The second aim was to identify the characteristics of young people with positive attitudes towards illicit drugs among those who had never tried drugs, those who had tried cannabis but no other illicit drugs, and those who regularly used cannabis and/or had tried other illicit drugs. The analysis was based on a population-based survey from 2013 ( N = 3812). Multiple logistic regression was used to analyse the association between sociodemographic and risk behaviour characteristics and positive attitudes towards illicit drugs. Young men had twice the odds of having positive attitudes towards illicit drug use compared with young women (AOR = 2.1). Also, young age, being single, being employed, smoking tobacco, practising unprotected sex, and experimental cannabis use were associated with positive attitudes towards illicit drug use. Finally, use of cannabis at least 10 times during the previous year and/or use of other illicit drugs had the strongest association with positive attitudes to illicit drug use (AOR = 6.0). Young people who have positive attitudes towards illicit drug use are characterized by a broad range of risky behaviours. These findings may help to identify young people at risk of initiating illicit drug use and thereby support the development and implementation of prevention programmes.

Nanotechnology-based drug delivery systems

Directory of Open Access Journals (Sweden)

Singh Baljit

2007-12-01

Full Text Available Abstract Nanoparticles hold tremendous potential as an effective drug delivery system. In this review we discussed recent developments in nanotechnology for drug delivery. To overcome the problems of gene and drug delivery, nanotechnology has gained interest in recent years. Nanosystems with different compositions and biological properties have been extensively investigated for drug and gene delivery applications. To achieve efficient drug delivery it is important to understand the interactions of nanomaterials with the biological environment, targeting cell-surface receptors, drug release, multiple drug administration, stability of therapeutic agents and molecular mechanisms of cell signalling involved in pathobiology of the disease under consideration. Several anti-cancer drugs including paclitaxel, doxorubicin, 5-fluorouracil and dexamethasone have been successfully formulated using nanomaterials. Quantom dots, chitosan, Polylactic/glycolic acid (PLGA and PLGA-based nanoparticles have also been used for in vitro RNAi delivery. Brain cancer is one of the most difficult malignancies to detect and treat mainly because of the difficulty in getting imaging and therapeutic agents past the blood-brain barrier and into the brain. Anti-cancer drugs such as loperamide and doxorubicin bound to nanomaterials have been shown to cross the intact blood-brain barrier and released at therapeutic concentrations in the brain. The use of nanomaterials including peptide-based nanotubes to target the vascular endothelial growth factor (VEGF receptor and cell adhesion molecules like integrins, cadherins and selectins, is a new approach to control disease progression.

Drug-perturbation-based stratification of blood cancer

Science.gov (United States)

Dietrich, Sascha; Lu, Junyan; Wu, Bian; Hüllein, Jennifer; da Silva Liberio, Michelle; Walther, Tatjana; Wagner, Lena; Rabe, Sophie; Ghidelli-Disse, Sonja; Bantscheff, Marcus; Słabicki, Mikołaj; Mock, Andreas; Oakes, Christopher C.; Wang, Shihui; Oppermann, Sina; Lukas, Marina; Kim, Vladislav; Sill, Martin; Jauch, Anna; Sutton, Lesley Ann; Rosenquist, Richard; Liu, Xiyang; Jethwa, Alexander; Lee, Kwang Seok; Lewis, Joe; Putzker, Kerstin; Lutz, Christoph; Rossi, Davide; Oellerich, Thomas; Herling, Marco; Nguyen-Khac, Florence; Plass, Christoph; von Kalle, Christof; Ho, Anthony D.; Hensel, Manfred; Dürig, Jan; Ringshausen, Ingo; Huber, Wolfgang

2017-01-01

As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care. PMID:29227286

Discovery and characterization of antibody variants using mass spectrometry-based comparative analysis for biosimilar candidates of monoclonal antibody drugs.

Science.gov (United States)

Li, Wenhua; Yang, Bin; Zhou, Dongmei; Xu, Jun; Ke, Zhi; Suen, Wen-Chen

2016-07-01

Liquid chromatography mass spectrometry (LC-MS) is the most commonly used technique for the characterization of antibody variants. MAb-X and mAb-Y are two approved IgG1 subtype monoclonal antibody drugs recombinantly produced in Chinese hamster ovary (CHO) cells. We report here that two unexpected and rare antibody variants have been discovered during cell culture process development of biosimilars for these two approved drugs through intact mass analysis. We then used comprehensive mass spectrometry-based comparative analysis including reduced light, heavy chains, and domain-specific mass as well as peptide mapping analysis to fully characterize the observed antibody variants. The "middle-up" mass comparative analysis demonstrated that the antibody variant from mAb-X biosimilar candidate was caused by mass variation of antibody crystalline fragment (Fc), whereas a different variant with mass variation in antibody antigen-binding fragment (Fab) from mAb-Y biosimilar candidate was identified. Endoproteinase Lys-C digested peptide mapping and tandem mass spectrometry analysis further revealed that a leucine to glutamine change in N-terminal 402 site of heavy chain was responsible for the generation of mAb-X antibody variant. Lys-C and trypsin coupled non-reduced and reduced peptide mapping comparative analysis showed that the formation of the light-heavy interchain trisulfide bond resulted in the mAb-Y antibody variant. These two cases confirmed that mass spectrometry-based comparative analysis plays a critical role for the characterization of monoclonal antibody variants, and biosimilar developers should start with a comprehensive structural assessment and comparative analysis to decrease the risk of the process development for biosimilars. Copyright © 2016 Elsevier B.V. All rights reserved.

Determinants of orphan drugs prices in France: a regression analysis.

Science.gov (United States)

Korchagina, Daria; Millier, Aurelie; Vataire, Anne-Lise; Aballea, Samuel; Falissard, Bruno; Toumi, Mondher

2017-04-21

The introduction of the orphan drug legislation led to the increase in the number of available orphan drugs, but the access to them is often limited due to the high price. Social preferences regarding funding orphan drugs as well as the criteria taken into consideration while setting the price remain unclear. The study aimed at identifying the determinant of orphan drug prices in France using a regression analysis. All drugs with a valid orphan designation at the moment of launch for which the price was available in France were included in the analysis. The selection of covariates was based on a literature review and included drug characteristics (Anatomical Therapeutic Chemical (ATC) class, treatment line, age of target population), diseases characteristics (severity, prevalence, availability of alternative therapeutic options), health technology assessment (HTA) details (actual benefit (AB) and improvement in actual benefit (IAB) scores, delay between the HTA and commercialisation), and study characteristics (type of study, comparator, type of endpoint). The main data sources were European public assessment reports, HTA reports, summaries of opinion on orphan designation of the European Medicines Agency, and the French insurance database of drugs and tariffs. A generalized regression model was developed to test the association between the annual treatment cost and selected covariates. A total of 68 drugs were included. The mean annual treatment cost was €96,518. In the univariate analysis, the ATC class (p = 0.01), availability of alternative treatment options (p = 0.02) and the prevalence (p = 0.02) showed a significant correlation with the annual cost. The multivariate analysis demonstrated significant association between the annual cost and availability of alternative treatment options, ATC class, IAB score, type of comparator in the pivotal clinical trial, as well as commercialisation date and delay between the HTA and commercialisation. The

Albumin-based drug delivery

DEFF Research Database (Denmark)

Larsen, Maja Thim; Kuhlmann, Matthias; Hvam, Michael Lykke

2016-01-01

The effectiveness of a drug is dependent on accumulation at the site of action at therapeutic levels, however, challenges such as rapid renal clearance, degradation or non-specific accumulation requires drug delivery enabling technologies. Albumin is a natural transport protein with multiple ligand...... binding sites, cellular receptor engagement, and a long circulatory half-life due to interaction with the recycling neonatal Fc receptor. Exploitation of these properties promotes albumin as an attractive candidate for half-life extension and targeted intracellular delivery of drugs attached by covalent...... conjugation, genetic fusions, association or ligand-mediated association. This review will give an overview of albumin-based products with focus on the natural biological properties and molecular interactions that can be harnessed for the design of a next-generation drug delivery platform....

Solution NMR Spectroscopy in Target-Based Drug Discovery.

Science.gov (United States)

Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

Marijuana-based drugs: innovative therapeutics or designer drugs of abuse?

Science.gov (United States)

Seely, Kathryn A; Prather, Paul L; James, Laura P; Moran, Jeffery H

2011-02-01

The principal psychoactive component of marijuana, Δ(9)-tetrahydrocannabinol (THC), activates CB1 cannabinoid receptors (CB1Rs). Unfortunately, pharmacological research into the design of effective THC analogs has been hampered by psychiatric side effects. THC-based drug design of a less academic nature, however, has led to the marketing of "synthetic marijuana," labeled as K2 or "Spice," among other terms, which elicits psychotropic actions via CB1R activation. Because of structural dissimilarity to THC, the active ingredients of K2/Spice preparations are widely unregulated. The K2/Spice "phenomenon" provides a context for considering whether marijuana-based drugs will truly provide innovative therapeutics or merely perpetuate drug abuse.

Micelle-like nanoassemblies based on polymer-drug conjugates as an emerging platform for drug delivery.

Science.gov (United States)

Liu, Zhihong; Wang, Yutao; Zhang, Na

2012-07-01

During the past decades, polymer-drug conjugates are one of the hottest topics in novel drug development fields. Amphiphilic polymer-drug conjugates in aqueous solution could form micelles or micelle-like nanoassemblies. Compared with polymer-drug conjugates and the micelles into which drugs are physically entrapped, micelles or micelle-like nanoassemblies based on polymer-drug conjugates bring several additional advantages, including increased drug-loading capacity, enhanced intracellular uptake, reduced systemic toxicity, and improved therapeutic efficacy. This review focuses on recent progress achieved in the research field of micelles or micelle-like nanoassemblies based on polymer-drug conjugates. Firstly, properties of polymers, drugs, and linkers which could be used to build polymer-drug conjugate micelles or micelle-like nanoassemblies are summarized. Then, the characterization methods are described. Finally, the drug-targeting mechanisms are discussed. Micelles or micelle-like nanoassemblies based on polymer-drug conjugates as an emerging platform have the potential to achieve medical treatments with enhanced therapeutic effect. The application of micelles or micelle-like nanoassemblies based on polymer-drug conjugates may give new life to old active compounds abandoned due to their low solubility problems. For clinical application, there is a need to further optimize the properties of the polymer, drug, and linker.

Prediction of drug synergy in cancer using ensemble-based machine learning techniques

Science.gov (United States)

Singh, Harpreet; Rana, Prashant Singh; Singh, Urvinder

2018-04-01

Drug synergy prediction plays a significant role in the medical field for inhibiting specific cancer agents. It can be developed as a pre-processing tool for therapeutic successes. Examination of different drug-drug interaction can be done by drug synergy score. It needs efficient regression-based machine learning approaches to minimize the prediction errors. Numerous machine learning techniques such as neural networks, support vector machines, random forests, LASSO, Elastic Nets, etc., have been used in the past to realize requirement as mentioned above. However, these techniques individually do not provide significant accuracy in drug synergy score. Therefore, the primary objective of this paper is to design a neuro-fuzzy-based ensembling approach. To achieve this, nine well-known machine learning techniques have been implemented by considering the drug synergy data. Based on the accuracy of each model, four techniques with high accuracy are selected to develop ensemble-based machine learning model. These models are Random forest, Fuzzy Rules Using Genetic Cooperative-Competitive Learning method (GFS.GCCL), Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Dynamic Evolving Neural-Fuzzy Inference System method (DENFIS). Ensembling is achieved by evaluating the biased weighted aggregation (i.e. adding more weights to the model with a higher prediction score) of predicted data by selected models. The proposed and existing machine learning techniques have been evaluated on drug synergy score data. The comparative analysis reveals that the proposed method outperforms others in terms of accuracy, root mean square error and coefficient of correlation.

Mexicans' use of illicit drugs in an era of drug reform: national comparative analysis by migrant status.

Science.gov (United States)

Guerrero, Erick G; Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A; Mora, Maria Elena Medina

2014-05-01

Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and US migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N=16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans' migrant status - (1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals) - featured analysis of variance and Chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR=2.453, 95% CI=1.933, 3.113) and using more illicit drugs (IRR=2.061, 95% CI=1.626, 2.613). Women were less likely than men to report having used drugs (OR=0.187, 95% CI=0.146, 0.239) and using more illicit drugs (IRR=0.153, 95% CI=0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. Copyright © 2014 Elsevier B.V. All rights reserved.

Mexicans’ Use of Illicit Drugs in an Era of Drug Reform: National Comparative Analysis by Migrant Status

Science.gov (United States)

Villatoro, Jorge Ameth; Kong, Yinfei; Gamiño, Marycarmen Bustos; Vega, William A.; Mora, Maria Elena Medina

2014-01-01

Although rates of illicit drug use are considerably lower in Mexico than in the United States, rates in Mexico have risen significantly. This increase has particular implications for Mexican women and U.S. migrants, who are considered at increased risk of drug use. Due to drug reforms enacted in Mexico in 2008, it is critical to evaluate patterns of drug use among migrants who reside in both regions. We analysed a sample of Mexicans (N = 16,249) surveyed during a national household survey in 2011, the Encuesta Nacional de Adicciones (National Survey of Addictions). Comparative analyses based on Mexicans’ migrant status—(1) never in the United States, (2) visited the United States, or (3) lived in the United States (transnationals)—featured analysis of variance and chi-square global tests. Two multilevel regressions were conducted to determine the relationships among migrant status, women, and illicit drug use. Comparative findings showed significant differences in type and number of drugs used among Mexicans by migrant status. The regression models showed that compared with Mexicans who had never visited the United States, Mexican transnationals were more likely to report having used drugs (OR = 2.453, 95% CI = 1.933, 3.113) and using more illicit drugs (IRR = 2.061, 95% CI = 1.626, 2.613). Women were less likely than men to report having used drugs (OR = 0.187, 95% CI = 0.146, 0.239) and using more illicit drugs (IRR = 0.153, 95% CI = 0.116, 0.202). Overall, the findings support further exploration of risk factors for illicit drug use among Mexican transnationals, who exhibit greater drug use behaviours than Mexicans never in the United States. Because drug reform mandates referrals to treatment for those with recurrent issues of drug use, it is critical for the Mexican government and civic society to develop the capacity to offer evidence-based substance abuse treatment for returning migrants with high-risk drug behaviours. PMID:24816376

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.

CImbinator: a web-based tool for drug synergy analysis in small- and large-scale datasets.

Science.gov (United States)

Flobak, Åsmund; Vazquez, Miguel; Lægreid, Astrid; Valencia, Alfonso

2017-08-01

Drug synergies are sought to identify combinations of drugs particularly beneficial. User-friendly software solutions that can assist analysis of large-scale datasets are required. CImbinator is a web-service that can aid in batch-wise and in-depth analyzes of data from small-scale and large-scale drug combination screens. CImbinator offers to quantify drug combination effects, using both the commonly employed median effect equation, as well as advanced experimental mathematical models describing dose response relationships. CImbinator is written in Ruby and R. It uses the R package drc for advanced drug response modeling. CImbinator is available at http://cimbinator.bioinfo.cnio.es , the source-code is open and available at https://github.com/Rbbt-Workflows/combination_index . A Docker image is also available at https://hub.docker.com/r/mikisvaz/rbbt-ci_mbinator/ . asmund.flobak@ntnu.no or miguel.vazquez@cnio.es. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Technology-based interventions for tobacco and other drug use in university and college students: a systematic review and meta-analysis.

Science.gov (United States)

Gulliver, Amelia; Farrer, Louise; Chan, Jade K Y; Tait, Robert J; Bennett, Kylie; Calear, Alison L; Griffiths, Kathleen M

2015-02-24

University students have high levels of tobacco and other drug use, yet they are unlikely to seek traditional care. Technology-based interventions are highly relevant to this population. This paper comprises a systematic review and meta-analysis of published randomized trials of technology-based interventions evaluated in a tertiary (university/college) setting for tobacco and other drug use (excluding alcohol). It extends previous reviews by using a broad definition of technology. PubMed, PsycInfo, and the Cochrane databases were searched using keywords, phrases, and MeSH terms. Retrieved abstracts (n = 627) were double screened and coded. Included studies met the following criteria: (1) the study was a randomized trial or a randomized controlled trial (RCT); (2) the sample was composed of students attending a tertiary (e.g., university, college) institution; (3) the intervention was either delivered by or accessed using a technological device or process (e.g., computer/internet, telephone, mobile short message services [SMS]); (4) the age range or mean of the sample was between 18 and 25 years; and (5) the intervention was designed to alter a drug use outcome relating to tobacco or other drugs (excluding alcohol). A total of 12 papers met inclusion criteria for the current review. The majority of included papers examined tobacco use (n = 9; 75%), two studies targeted marijuana use (17%); and one targeted stress, marijuana, alcohol, and tobacco use. A quantitative meta-analysis was conducted on the tobacco use studies using an abstinence outcome measure (n = 6), demonstrating that the interventions increased the rate of abstinence by 1.5 times that of controls (Risk Ratio [RR] = 1.54; 95% Confidence Interval [CI] = 1.20-1.98). Across all 12 studies, a total of 20 technology-based interventions were reviewed. A range of technology was employed in the interventions, including stand-alone computer programs (n = 10), internet (n = 5), telephone (n = 3), and mobile SMS

Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

Science.gov (United States)

He, Yongqun

2016-06-01

Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

In silico fragment-based drug design.

Science.gov (United States)

Konteatis, Zenon D

2010-11-01

In silico fragment-based drug design (FBDD) is a relatively new approach inspired by the success of the biophysical fragment-based drug discovery field. Here, we review the progress made by this approach in the last decade and showcase how it complements and expands the capabilities of biophysical FBDD and structure-based drug design to generate diverse, efficient drug candidates. Advancements in several areas of research that have enabled the development of in silico FBDD and some applications in drug discovery projects are reviewed. The reader is introduced to various computational methods that are used for in silico FBDD, the fragment library composition for this technique, special applications used to identify binding sites on the surface of proteins and how to assess the druggability of these sites. In addition, the reader will gain insight into the proper application of this approach from examples of successful programs. In silico FBDD captures a much larger chemical space than high-throughput screening and biophysical FBDD increasing the probability of developing more diverse, patentable and efficient molecules that can become oral drugs. The application of in silico FBDD holds great promise for historically challenging targets such as protein-protein interactions. Future advances in force fields, scoring functions and automated methods for determining synthetic accessibility will all aid in delivering more successes with in silico FBDD.

An attention-based effective neural model for drug-drug interactions extraction.

Science.gov (United States)

Zheng, Wei; Lin, Hongfei; Luo, Ling; Zhao, Zhehuan; Li, Zhengguang; Zhang, Yijia; Yang, Zhihao; Wang, Jian

2017-10-10

Drug-drug interactions (DDIs) often bring unexpected side effects. The clinical recognition of DDIs is a crucial issue for both patient safety and healthcare cost control. However, although text-mining-based systems explore various methods to classify DDIs, the classification performance with regard to DDIs in long and complex sentences is still unsatisfactory. In this study, we propose an effective model that classifies DDIs from the literature by combining an attention mechanism and a recurrent neural network with long short-term memory (LSTM) units. In our approach, first, a candidate-drug-oriented input attention acting on word-embedding vectors automatically learns which words are more influential for a given drug pair. Next, the inputs merging the position- and POS-embedding vectors are passed to a bidirectional LSTM layer whose outputs at the last time step represent the high-level semantic information of the whole sentence. Finally, a softmax layer performs DDI classification. Experimental results from the DDIExtraction 2013 corpus show that our system performs the best with respect to detection and classification (84.0% and 77.3%, respectively) compared with other state-of-the-art methods. In particular, for the Medline-2013 dataset with long and complex sentences, our F-score far exceeds those of top-ranking systems by 12.6%. Our approach effectively improves the performance of DDI classification tasks. Experimental analysis demonstrates that our model performs better with respect to recognizing not only close-range but also long-range patterns among words, especially for long, complex and compound sentences.

Rational drug therapy education in clinical phase carried out by task-based learning

Science.gov (United States)

Bilge, S. Sırrı; Akyüz, Bahar; Ağrı, Arzu Erdal; Özlem, Mıdık

2017-01-01

Objectives: Irrational drug use results in drug interactions, treatment noncompliance, and drug resistance. Rational pharmacotherapy education is being implemented in many faculties of medicine. Our aim is to introduce rational pharmacotherapy education by clinicians and to evaluate task-based rational drug therapy education in the clinical context. Methods: The Kirkpatrick's evaluation model was used for the evaluation of the program. The participants evaluated the program in terms of constituents of the program, utilization, and contribution to learning. Voluntary participants responded to the evaluation forms after the educational program. Data are evaluated using both quantitative and qualitative tools. SPSS (version 21) used for quantitative data for determining mean and standard deviation values. Descriptive qualitative analysis approach is used for the analysis of open-ended questions. Results: It was revealed that the program and its components have been favorable. A total 95.9% of the students consider the education to be beneficial. Simulated patients practice and personal drug choice/problem-based learning sessions were appreciated by the students in particular. 93.9% of the students stated that all students of medicine should undergo this educational program. Among the five presentations contained in the program, “The Principles of Prescribing” received the highest points (9 ± 1.00) from participating students in general evaluation of the educational program. Conclusion: This study was carried out to improve task-based rational drug therapy education. According to feedback from the students concerning content, method, resource, assessment, and program design; some important changes, especially in number of facilitators and indications, are made in rational pharmacotherapy education in clinical task-based learning program. PMID:28458432

Teens and Prescription Drugs: An Analysis of Recent Trends on the Emerging Drug Threat

Science.gov (United States)

Office of National Drug Control Policy, 2007

2007-01-01

This report synthesizes a number of national studies that show the intentional abuse of prescription drugs to get high is a growing concern, particularly among teens. The analysis shows that teens are turning away from street drugs and using prescription drugs to get high. New users of prescription drugs have caught up with new users of marijuana.…

Drug repositioning for enzyme modulator based on human metabolite-likeness.

Science.gov (United States)

Lee, Yoon Hyeok; Choi, Hojae; Park, Seongyong; Lee, Boah; Yi, Gwan-Su

2017-05-31

Recently, the metabolite-likeness of the drug space has emerged and has opened a new possibility for exploring human metabolite-like candidates in drug discovery. However, the applicability of metabolite-likeness in drug discovery has been largely unexplored. Moreover, there are no reports on its applications for the repositioning of drugs to possible enzyme modulators, although enzyme-drug relations could be directly inferred from the similarity relationships between enzyme's metabolites and drugs. We constructed a drug-metabolite structural similarity matrix, which contains 1,861 FDA-approved drugs and 1,110 human intermediary metabolites scored with the Tanimoto similarity. To verify the metabolite-likeness measure for drug repositioning, we analyzed 17 known antimetabolite drugs that resemble the innate metabolites of their eleven target enzymes as the gold standard positives. Highly scored drugs were selected as possible modulators of enzymes for their corresponding metabolites. Then, we assessed the performance of metabolite-likeness with a receiver operating characteristic analysis and compared it with other drug-target prediction methods. We set the similarity threshold for drug repositioning candidates of new enzyme modulators based on maximization of the Youden's index. We also carried out literature surveys for supporting the drug repositioning results based on the metabolite-likeness. In this paper, we applied metabolite-likeness to repurpose FDA-approved drugs to disease-associated enzyme modulators that resemble human innate metabolites. All antimetabolite drugs were mapped with their known 11 target enzymes with statistically significant similarity values to the corresponding metabolites. The comparison with other drug-target prediction methods showed the higher performance of metabolite-likeness for predicting enzyme modulators. After that, the drugs scored higher than similarity score of 0.654 were selected as possible modulators of enzymes for

Cost-effectiveness analysis of introducing malaria diagnostic testing in drug shops

DEFF Research Database (Denmark)

Hansen, Kristian Schultz; Clarke, Siân E.; Lal, Sham

2017-01-01

Background Private sector drug shops are an important source of malaria treatment in Africa, yet diagnosis without parasitological testing is common among these providers. Accurate rapid diagnostic tests for malaria (mRDTs) require limited training and present an opportunity to increase access...... to correct diagnosis. The present study was a cost-effectiveness analysis of the introduction of mRDTs in Ugandan drug shops. Methods Drug shop vendors were trained to perform and sell subsidised mRDTs and artemisinin-based combination therapies (ACTs) in the intervention arm while vendors offered ACTs...... following presumptive diagnosis of malaria in the control arm. The effect on the proportion of customers with fever ‘appropriately treated of malaria with ACT’ was captured during a randomised trial in drug shops in Mukono District, Uganda. Health sector costs included: training of drug shop vendors...

Microsponges based novel drug delivery system for augmented arthritis therapy.

Science.gov (United States)

Osmani, Riyaz Ali M; Aloorkar, Nagesh H; Ingale, Dipti J; Kulkarni, Parthasarathi K; Hani, Umme; Bhosale, Rohit R; Jayachandra Dev, Dandasi

2015-10-01

The motive behind present work was to formulate and evaluate gel containing microsponges of diclofenac diethylamine to provide prolonged release for proficient arthritis therapy. Quasi-emulsion solvent diffusion method was implied using Eudragit RS-100 and microsponges with varied drug-polymer ratios were prepared. For the sake of optimization, diverse factors affecting microparticles physical properties were too investigated. Microsponges were characterized by SEM, DSC, FT-IR, XRPD and particle size analysis, and evaluated for morphology, drug loading, in vitro drug release and ex vivo diffusion as well. There were no chemical interactions between drug and polymers used as revealed by compatibility studies outcomes. The drug polymer ratio reflected notable effect on drug content, encapsulation efficiency and particle size. SEM results revealed spherical microsponges with porous surface, and had 7.21 μm mean particle size. The microsponges were then incorporated in gel; which exhibited viscous modulus along with pseudoplastic behavior. In vitro drug release results depicted that microsponges with 1:2 drug-polymer ratio were more efficient to give extended drug release of 75.88% at the end of 8 h; while conventional formulation get exhausted incredibly earlier by releasing 81.11% drug at the end of 4 h only. Thus the formulated microsponge-based gel of diclofenac diethylamine would be a promising alternative to conventional therapy for safer and efficient treatment of arthritis and musculoskeletal disorders.

Cost-offsets of prescription drug expenditures: data analysis via a copula-based bivariate dynamic hurdle model.

Science.gov (United States)

Deb, Partha; Trivedi, Pravin K; Zimmer, David M

2014-10-01

In this paper, we estimate a copula-based bivariate dynamic hurdle model of prescription drug and nondrug expenditures to test the cost-offset hypothesis, which posits that increased expenditures on prescription drugs are offset by reductions in other nondrug expenditures. We apply the proposed methodology to data from the Medical Expenditure Panel Survey, which have the following features: (i) the observed bivariate outcomes are a mixture of zeros and continuously measured positives; (ii) both the zero and positive outcomes show state dependence and inter-temporal interdependence; and (iii) the zeros and the positives display contemporaneous association. The point mass at zero is accommodated using a hurdle or a two-part approach. The copula-based approach to generating joint distributions is appealing because the contemporaneous association involves asymmetric dependence. The paper studies samples categorized by four health conditions: arthritis, diabetes, heart disease, and mental illness. There is evidence of greater than dollar-for-dollar cost-offsets of expenditures on prescribed drugs for relatively low levels of spending on drugs and less than dollar-for-dollar cost-offsets at higher levels of drug expenditures. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of individual drug use as a time-varying determinant of exposure in prospective population-based cohort studies

NARCIS (Netherlands)

B.H.Ch. Stricker (Bruno); Th. Stijnen (Theo)

2010-01-01

textabstractIn pharmaco-epidemiology, the use of drugs is the determinant of interest when studying exposure-outcome associations. The increased availability of computerized information about drug use on an individual basis has greatly facilitated analyses of drug effects on a population-based

Population pharmacokinetics analysis of olanzapine for Chinese psychotic patients based on clinical therapeutic drug monitoring data with assistance of meta-analysis.

Science.gov (United States)

Yin, Anyue; Shang, Dewei; Wen, Yuguan; Li, Liang; Zhou, Tianyan; Lu, Wei

2016-08-01

The aim of this study was to build an eligible population pharmacokinetic (PK) model for olanzapine in Chinese psychotic patients based on therapeutic drug monitoring (TDM) data, with assistance of meta-analysis, to facilitate individualized therapy. Population PK analysis for olanzapine was performed using NONMEM software (version 7.3.0). TDM data were collected from Guangzhou Brain Hospital (China). Because of the limitations of TDM data, model-based meta-analysis was performed to construct a structural model to assist the modeling of TDM data as prior estimates. After analyzing related covariates, a simulation was performed to predict concentrations for different types of patients under common dose regimens. A two-compartment model with first-order absorption and elimination was developed for olanzapine oral tablets, based on 23 articles with 390 data points. The model was then applied to the TDM data. Gender and smoking habits were found to be significant covariates that influence the clearance of olanzapine. To achieve a blood concentration of 20 ng/mL (the lower boundary of the recommended therapeutic range), simulation results indicated that the dose regimen of olanzapine should be 5 mg BID (twice a day), ≥ 5 mg QD (every day) plus 10 mg QN (every night), or >10 mg BID for female nonsmokers, male nonsmokers and male smokers, respectively. The population PK model, built using meta-analysis, could facilitate the modeling of TDM data collected from Chinese psychotic patients. The factors that significantly influence olanzapine disposition were determined and the final model could be used for individualized treatment.

Synthesis, characterization and in vitro cytotoxicity analysis of a novel cellulose based drug carrier for the controlled delivery of 5-fluorouracil, an anticancer drug

Science.gov (United States)

Anirudhan, Thayyath S.; Nima, Jayachandran; Divya, Peethambaran L.

2015-11-01

The present investigation concerns the development and evaluation of a novel drug delivery system, aminated-glycidylmethacrylate grafted cellulose-grafted polymethacrylic acid-succinyl cyclodextrin (Cell-g-(GMA/en)-PMA-SCD) for the controlled release of 5-Fluorouracil, an anticancer drug. The prepared drug carrier was characterized by FT-IR, XRD and SEM techniques. Binding kinetics and isotherm studies of 5-FU onto Cell-g-(GMA/en)-PMA-SCD were found to follow pseudo-second-order and Langmuir model respectively. Maximum binding capacity of drug carrier was found to be 149.09 mg g-1 at 37 °C. Swelling studies, in vitro release kinetics, drug loading efficiency and encapsulation efficiency of Cell-g-(GMA/en)-PMA-SCD were studied. The release kinetics was analyzed using Ritger-Peppas equation at pH 7.4. Cytotoxicity analysis on MCF-7 (human breast carcinoma) cells indicated that the drug carrier shows sustained and controlled release of drug to the target site. Hence, it is evident from this investigation that Cell-g-(GMA/en)-PMA-SCD could be a promising carrier for 5-FU.

Experiences in fragment-based drug discovery.

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Murray, Christopher W; Verdonk, Marcel L; Rees, David C

2012-05-01

Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches. Copyright © 2012 Elsevier Ltd. All rights reserved.

Drug knowledge bases and their applications in biomedical informatics research.

Science.gov (United States)

Zhu, Yongjun; Elemento, Olivier; Pathak, Jyotishman; Wang, Fei

2018-01-03

Recent advances in biomedical research have generated a large volume of drug-related data. To effectively handle this flood of data, many initiatives have been taken to help researchers make good use of them. As the results of these initiatives, many drug knowledge bases have been constructed. They range from simple ones with specific focuses to comprehensive ones that contain information on almost every aspect of a drug. These curated drug knowledge bases have made significant contributions to the development of efficient and effective health information technologies for better health-care service delivery. Understanding and comparing existing drug knowledge bases and how they are applied in various biomedical studies will help us recognize the state of the art and design better knowledge bases in the future. In addition, researchers can get insights on novel applications of the drug knowledge bases through a review of successful use cases. In this study, we provide a review of existing popular drug knowledge bases and their applications in drug-related studies. We discuss challenges in constructing and using drug knowledge bases as well as future research directions toward a better ecosystem of drug knowledge bases. © The Author(s) 2018. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Principles that underpin effective school-based drug education.

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Midford, Richard; Munro, Geoffrey; McBride, Nyanda; Snow, Pamela; Ladzinski, Ursula

2002-01-01

This study identifies the conceptual underpinnings of effective school-based drug education practice in light of contemporary research evidence and the practical experience of a broad range of drug education stakeholders. The research involved a review of the literature, a national survey of 210 Australian teachers and others involved in drug education, and structured interviews with 22 key Australian drug education policy stakeholders. The findings from this research have been distilled and presented as a list of 16 principles that underpin effective drug education. In broad terms, drug education should be evidence-based, developmentally appropriate, sequential, and contextual. Programs should be initiated before drug use commences. Strategies should be linked to goals and should incorporate harm minimization. Teaching should be interactive and use peer leaders. The role of the classroom teacher is central. Certain program content is important, as is social and resistance skills training. Community values, the social context of use, and the nature of drug harm have to be addressed. Coverage needs to be adequate and supported by follow-up. It is envisaged that these principles will provide all those involved in the drug education field with a set of up-to-date, research-based guidelines against which to reference decisions on program design, selection, implementation, and evaluation.

Microemulsions based transdermal drug delivery systems.

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Vadlamudi, Harini C; Narendran, Hyndavi; Nagaswaram, Tejeswari; Yaga, Gowri; Thanniru, Jyotsna; Yalavarthi, Prasanna R

2014-01-01

Since the discovery of microemulsions by Jack H Schulman, there has been huge progress made in applying microemulsion systems in plethora of research and industrial process. Microemulsions are optically isotropic systems consisting of water, oil and amphiphile. These systems are beneficial due to their thermodynamic stability, optical clarity, ease of preparation, higher diffusion and absorption rates. Moreover, it has been reported that the ingredients of microemulsion can effectively overcome the diffusion barrier and penetrate through the stratum corneum of the skin. Hence it becomes promising for both transdermal and dermal drug delivery. However, low viscosity of microemulsion restrains its applicability in pharmaceutical industry. To overcome the above drawback, the low viscous microemulsions were added to viscous gel bases to potentiate its applications as topical drug delivery systems so that various drug related toxic effects and erratic drug absorption can be avoided. The present review deals with the microemulsions, various techniques involved in the development of organic nanoparticles. The review emphasized on microemulsion based systems such as hydrogels and organogels. The physicochemical characteristics, mechanical properties, rheological and stability principles involved in microemulsion based viscous gels were also explored.

Fabrication and Analysis of Tapered Tip Silicon Microneedles for MEMS based Drug Delivery System

Directory of Open Access Journals (Sweden)

Muhammad Waseem Ashraf

2010-11-01

Full Text Available In this paper, a novel design of transdermal drug delivery (TDD system is presented. The proposed system consists of controlled electronic circuit and microelectromechanical system (MEMS based devices like microneedles, micropump, flow sensor, and blood pressure sensor. The aim of this project is to develop a system that can eliminate the limitations associated with oral therapy. In this phase tapered tip silicon microneedles have been fabricated using inductively coupled plasma (ICP etching technology. Using ANSYS, simulation of microneedles has been conducted before the fabrication process to test the design suitability for TDD. More over multifield analysis of reservoir integrated with microneedle array using piezoelectric actuator has also been performed. The effects of frequency and voltage on actuator and fluid flow rate through 6×6 microneedle array have been investigated. This work provides envisage data to design suitable devices for TDD.

Mechanism-based drug exposure classification in pharmacoepidemiological studies

NARCIS (Netherlands)

Verdel, B.M.

2010-01-01

Mechanism-based classification of drug exposure in pharmacoepidemiological studies In pharmacoepidemiology and pharmacovigilance, the relation between drug exposure and clinical outcomes is crucial. Exposure classification in pharmacoepidemiological studies is traditionally based on

Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases.

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Mello, Juliana da Fonseca Rezende E; Gomes, Renan Augusto; Vital-Fujii, Drielli Gomes; Ferreira, Glaucio Monteiro; Trossini, Gustavo Henrique Goulart

2017-12-01

Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs. © 2017 John Wiley & Sons A/S.

Target based drug design - a reality in virtual sphere.

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Verma, Saroj; Prabhakar, Yenamandra S

2015-01-01

The target based drug design approaches are a series of computational procedures, including visualization tools, to support the decision systems of drug design/discovery process. In the essence of biological targets shaping the potential lead/drug molecules, this review presents a comprehensive position of different components of target based drug design which include target identification, protein modeling, molecular dynamics simulations, binding/catalytic sites identification, docking, virtual screening, fragment based strategies, substructure treatment of targets in tackling drug resistance, in silico ADMET, structural vaccinology, etc along with the key issues involved therein and some well investigated case studies. The concepts and working of these procedures are critically discussed to arouse interest and to advance the drug research.

Effect of intravenous drug administration mode on drug distribution in a tumor slab: a finite Fourier transform analysis.

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Subramaniam, B; Claudius, J S

1990-03-08

for optimum scheduling of subsequent bolus injections in a multiple bolus dosing regimen. There are no reported applications of the FFT method to solve repeated input functions in either the chemical engineering or pharmaceutical science literature. Thus, the application of FFT method to solve multiple bolus injections is a unique one. Use of this FFT based analysis as a predictor tool can limit the number of costly experiments which are being done now to achieve this purpose. Even though the model in its present form is simplified, the analysis thereof has nevertheless led to a better understanding of the various factors that must be taken into account for rational design of drug therapy.

Gene expression analysis of two extensively drug-resistant tuberculosis isolates show that two-component response systems enhance drug resistance.

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Yu, Guohua; Cui, Zhenling; Sun, Xian; Peng, Jinfu; Jiang, Jun; Wu, Wei; Huang, Wenhua; Chu, Kaili; Zhang, Lu; Ge, Baoxue; Li, Yao

2015-05-01

Global analysis of expression profiles using DNA microarrays was performed between a reference strain H37Rv and two clinical extensively drug-resistant isolates in response to three anti-tuberculosis drug exposures (isoniazid, capreomycin, and rifampicin). A deep analysis was then conducted using a combination of genome sequences of the resistant isolates, resistance information, and related public microarray data. Certain known resistance-associated gene sets were significantly overrepresented in upregulated genes in the resistant isolates relative to that observed in H37Rv, which suggested a link between resistance and expression levels of particular genes. In addition, isoniazid and capreomycin response genes, but not rifampicin, either obtained from published works or our data, were highly consistent with the differentially expressed genes of resistant isolates compared to those of H37Rv, indicating a strong association between drug resistance of the isolates and genes differentially regulated by isoniazid and capreomycin exposures. Based on these results, 92 genes of the studied isolates were identified as candidate resistance genes, 10 of which are known resistance-related genes. Regulatory network analysis of candidate resistance genes using published networks and literature mining showed that three two-component regulatory systems and regulator CRP play significant roles in the resistance of the isolates by mediating the production of essential envelope components. Finally, drug sensitivity testing indicated strong correlations between expression levels of these regulatory genes and sensitivity to multiple anti-tuberculosis drugs in Mycobacterium tuberculosis. These findings may provide novel insights into the mechanism underlying the emergence and development of drug resistance in resistant tuberculosis isolates and useful clues for further studies on this issue. Copyright © 2015 Elsevier Ltd. All rights reserved.

Employment-based abstinence reinforcement promotes opiate and cocaine abstinence in out-of-treatment injection drug users.

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Holtyn, August F; Koffarnus, Mikhail N; DeFulio, Anthony; Sigurdsson, Sigurdur O; Strain, Eric C; Schwartz, Robert P; Silverman, Kenneth

2014-01-01

We examined the use of employment-based abstinence reinforcement in out-of-treatment injection drug users, in this secondary analysis of a previously reported trial. Participants (N = 33) could work in the therapeutic workplace, a model employment-based program for drug addiction, for 30 weeks and could earn approximately $10 per hr. During a 4-week induction, participants only had to work to earn pay. After induction, access to the workplace was contingent on enrollment in methadone treatment. After participants met the methadone contingency for 3 weeks, they had to provide opiate-negative urine samples to maintain maximum pay. After participants met those contingencies for 3 weeks, they had to provide opiate- and cocaine-negative urine samples to maintain maximum pay. The percentage of drug-negative urine samples remained stable until the abstinence reinforcement contingency for each drug was applied. The percentage of opiate- and cocaine-negative urine samples increased abruptly and significantly after the opiate- and cocaine-abstinence contingencies, respectively, were applied. These results demonstrate that the sequential administration of employment-based abstinence reinforcement can increase opiate and cocaine abstinence among out-of-treatment injection drug users. © Society for the Experimental Analysis of Behavior.

Drug supply indicators: Pitfalls and possibilities for improvements to assist comparative analysis.

Science.gov (United States)

Singleton, Nicola; Cunningham, Andrew; Groshkova, Teodora; Royuela, Luis; Sedefov, Roumen

2018-06-01

Interventions to tackle the supply of drugs are seen as standard components of illicit drug policies. Therefore drug market-related administrative data, such as seizures, price, purity and drug-related offending, are used in most countries for policy monitoring and assessment of the drug situation. International agencies, such as the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) and the UN Office of Drugs and Crime, also monitor and report on the drug situation cross-nationally and therefore seek to collect and make available key data in a uniform manner from the countries they cover. However, these data are not primarily collected for this purpose, which makes interpretation and comparative analysis difficult. Examples of limitations of these data sources include: the extent to which they reflect operational priorities rather than market changes; question marks over the robustness of and consistency in data collection methods, and issues around the timeliness of data availability. Such problems are compounded by cultural, social and contextual differences between countries. Making sense of such data is therefore challenging and extreme care needs to be taken using it. Nevertheless, these data provide an important window on a hidden area, so improving the quality of the data collected and expanding its scope should be a priority for those seeking to understand or monitor drug markets and supply reduction. In addition to highlighting some of the potential pitfalls in using supply indicators for comparative analysis, this paper presents a selection of options for improvements based on the current EMCDDA programme of work to improve their supply-related monitoring and analysis. The conceptual framework developed to steer this work may have wider application. Adopting this approach has the potential to provide a richer picture of drug markets, at both national and international levels, and make it easier to compare data between countries. Copyright �

Psychoactive drug advertising: content analysis.

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Mastroianni, Patrícia C; Vaz, Amanda Cristina R; Noto, Ana Regina; Galduróz, José Carlos F

2008-10-01

The goal of this study was to describe the human figures portrayed in psychoactive drug advertising in terms of gender, age, ethnic group, and social context. Content analysis for 86 new pieces of printed advertisements released in 2005 was carried out. Fisher exact test was used to analyze the association between categories. There was a preponderance of women (62.8%) who were four times more present in advertisements for antidepressants and anxyolitics than men. Most of the people shown were Caucasian (98.8%) young adults (72%). These people were pictured in leisure activities (46.5%), at home (29%), or in contact with nature (16.2%). The message conveyed was that the drugs treat routinely felt subjective symptoms of discomfort, inducing in an irrational appeal that may affect drug prescription.

[Quantitative analysis of drug expenditures variability in dermatology units].

Science.gov (United States)

Moreno-Ramírez, David; Ferrándiz, Lara; Ramírez-Soto, Gabriel; Muñoyerro, M Dolores

2013-01-01

Variability in adjusted drug expenditures among clinical departments raises the possibility of difficult access to certain therapies at the time that avoidable expenditures may also exist. Nevertheless, drug expenditures are not usually applied to clinical practice variability analysis. To identify and quantify variability in drug expenditures in comparable dermatology department of the Servicio Andaluz de Salud. Comparative economic analysis regarding the drug expenditures adjusted to population and health care production in 18 dermatology departments of the Servicio Andaluz de Salud. The 2012 cost and production data (homogeneous production units -HPU-)were provided by Inforcoan, the cost accounting information system of the Servicio Andaluz de Salud. The observed drug expenditure ratio ranged from 0.97?/inh to 8.90?/inh and from 208.45?/HPU to 1,471.95?/ HPU. The Pearson correlation between drug expenditure and population was 0.25 and 0.35 for the correlation between expenditure and homogeneous production (p=0.32 and p=0,15, respectively), both Pearson coefficients confirming the lack of correlation and arelevant degree of variability in drug expenditures. The quantitative analysis of variability performed through Pearson correlation has confirmed the existence of drug expenditure variability among comparable dermatology departments. Copyright © 2013 SEFH. Published by AULA MEDICA. All rights reserved.

Toxicological Analysis of Some Drugs of Abuse in Biological Samples

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Anne Marie Ciobanu

2015-10-01

Full Text Available Consumption of drugs of abuse is a scourge of modern world. Abuse, drug addiction and their consequences are one of the major current problems of European society because of the significant repercussions in individual, family, social and economic level. In this context, toxicological analysis of the drugs of abuse in biological samples is a useful tool for: diagnosis of drug addiction, checking an auto-response, mandatory screening in some treatment programs, identification of a substance in the case of an overdose, determining compliance of the treatment. The present paper aims to address the needs of healthcare professionals involved in drugs addiction treatment through systematic presentation of information regarding their toxicological analysis. Basically, it is a tool that help you to select the suitable biological sample and the right collecting time, as well as the proper analysis technique, depending on the purpose of analysis, pharmacokinetic characteristics of the drugs of abuse, available equipment and staff expertise.

Prediction of potential drug targets based on simple sequence properties

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Lai Luhua

2007-09-01

Full Text Available Abstract Background During the past decades, research and development in drug discovery have attracted much attention and efforts. However, only 324 drug targets are known for clinical drugs up to now. Identifying potential drug targets is the first step in the process of modern drug discovery for developing novel therapeutic agents. Therefore, the identification and validation of new and effective drug targets are of great value for drug discovery in both academia and pharmaceutical industry. If a protein can be predicted in advance for its potential application as a drug target, the drug discovery process targeting this protein will be greatly speeded up. In the current study, based on the properties of known drug targets, we have developed a sequence-based drug target prediction method for fast identification of novel drug targets. Results Based on simple physicochemical properties extracted from protein sequences of known drug targets, several support vector machine models have been constructed in this study. The best model can distinguish currently known drug targets from non drug targets at an accuracy of 84%. Using this model, potential protein drug targets of human origin from Swiss-Prot were predicted, some of which have already attracted much attention as potential drug targets in pharmaceutical research. Conclusion We have developed a drug target prediction method based solely on protein sequence information without the knowledge of family/domain annotation, or the protein 3D structure. This method can be applied in novel drug target identification and validation, as well as genome scale drug target predictions.

System of Objectified Judgement Analysis (SOJA) as a tool in rational and transparent drug-decision making.

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Janknegt, Robert; Scott, Mike; Mairs, Jill; Timoney, Mark; McElnay, James; Brenninkmeijer, Rob

2007-10-01

Drug selection should be a rational process that embraces the principles of evidence-based medicine. However, many factors may affect the choice of agent. It is against this background that the System of Objectified Judgement Analysis (SOJA) process for rational drug-selection was developed. This article describes how the information on which the SOJA process is based, was researched and processed.

Drug target mining and analysis of the Chinese tree shrew for pharmacological testing.

Directory of Open Access Journals (Sweden)

Feng Zhao

Full Text Available The discovery of new drugs requires the development of improved animal models for drug testing. The Chinese tree shrew is considered to be a realistic candidate model. To assess the potential of the Chinese tree shrew for pharmacological testing, we performed drug target prediction and analysis on genomic and transcriptomic scales. Using our pipeline, 3,482 proteins were predicted to be drug targets. Of these predicted targets, 446 and 1,049 proteins with the highest rank and total scores, respectively, included homologs of targets for cancer chemotherapy, depression, age-related decline and cardiovascular disease. Based on comparative analyses, more than half of drug target proteins identified from the tree shrew genome were shown to be higher similarity to human targets than in the mouse. Target validation also demonstrated that the constitutive expression of the proteinase-activated receptors of tree shrew platelets is similar to that of human platelets but differs from that of mouse platelets. We developed an effective pipeline and search strategy for drug target prediction and the evaluation of model-based target identification for drug testing. This work provides useful information for future studies of the Chinese tree shrew as a source of novel targets for drug discovery research.

Web-based drug repurposing tools: a survey.

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Sam, Elizabeth; Athri, Prashanth

2017-10-06

Drug repurposing (a.k.a. drug repositioning) is the search for new indications or molecular targets distinct from a drug's putative activity, pharmacological effect or binding specificities. With the ever-increasing rates of termination of drugs in clinical trials, drug repositioning has risen as one of the effective solutions against the risk of drug failures. Repositioning finds a way to reverse the grim but real trend that Eroom's law portends for the pharmaceutical and biotech industry, and drug discovery in general. Further, the advent of high-throughput technologies to explore biological systems has enabled the generation of zeta bytes of data and a massive collection of databases that store them. Computational analytics and mining are frequently used as effective tools to explore this byzantine series of biological and biomedical data. However, advanced computational tools are often difficult to understand or use, thereby limiting their accessibility to scientists without a strong computational background. Hence it is of great importance to build user-friendly interfaces to extend the user-base beyond computational scientists, to include life scientists who may have deeper chemical and biological insights. This survey is focused on systematically presenting the available Web-based tools that aid in repositioning drugs. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The mass-action law based algorithm for cost-effective approach for cancer drug discovery and development.

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Chou, Ting-Chao

2011-01-01

The mass-action law based system analysis via mathematical induction and deduction lead to the generalized theory and algorithm that allows computerized simulation of dose-effect dynamics with small size experiments using a small number of data points in vitro, in animals, and in humans. The median-effect equation of the mass-action law deduced from over 300 mechanism specific-equations has been shown to be the unified theory that serves as the common-link for complicated biomedical systems. After using the median-effect principle as the common denominator, its applications are mechanism-independent, drug unit-independent, and dynamic order-independent; and can be used generally for single drug analysis or for multiple drug combinations in constant-ratio or non-constant ratios. Since the "median" is the common link and universal reference point in biological systems, these general enabling lead to computerized quantitative bio-informatics for econo-green bio-research in broad disciplines. Specific applications of the theory, especially relevant to drug discovery, drug combination, and clinical trials, have been cited or illustrated in terms of algorithms, experimental design and computerized simulation for data analysis. Lessons learned from cancer research during the past fifty years provide a valuable opportunity to reflect, and to improve the conventional divergent approach and to introduce a new convergent avenue, based on the mass-action law principle, for the efficient cancer drug discovery and the low-cost drug development.

Methadone maintenance therapy as evidence based drug abuse ...

African Journals Online (AJOL)

Methadone maintenance therapy as evidence based drug abuse planning in ... drugs are being used as artificial problem-solvers such as frustrations, stress or ... Drug use is a problem to users when it begins to cause some damage to their ...

DNA nanostructure-based drug delivery nanosystems in cancer therapy.

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Wu, Dandan; Wang, Lei; Li, Wei; Xu, Xiaowen; Jiang, Wei

2017-11-25

DNA as a novel biomaterial can be used to fabricate different kinds of DNA nanostructures based on its principle of GC/AT complementary base pairing. Studies have shown that DNA nanostructure is a nice drug carrier to overcome big obstacles existing in cancer therapy such as systemic toxicity and unsatisfied drug efficacy. Thus, different types of DNA nanostructure-based drug delivery nanosystems have been designed in cancer therapy. To improve treating efficacy, they are also developed into more functional drug delivery nanosystems. In recent years, some important progresses have been made. The objective of this review is to make a retrospect and summary about these different kinds of DNA nanostructure-based drug delivery nanosystems and their latest progresses: (1) active targeting; (2) mutidrug co-delivery; (3) construction of stimuli-responsive/intelligent nanosystems. Copyright © 2017 Elsevier B.V. All rights reserved.

Fall-Risk-Increasing Drugs: A Systematic Review and Meta-Analysis: I. Cardiovascular Drugs.

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de Vries, Max; Seppala, Lotta J; Daams, Joost G; van de Glind, Esther M M; Masud, Tahir; van der Velde, Nathalie

2018-04-01

Use of certain medications is recognized as a major and modifiable risk factor for falls. Although the literature on psychotropic drugs is compelling, the literature on cardiovascular drugs as potential fall-risk-increasing drugs is conflicting. The aim of this systematic review and meta-analysis is to provide a comprehensive overview of the associations between cardiovascular medications and fall risk in older adults. Design: A systematic review and meta-analysis. Medline, Embase, and PsycINFO. Key search concepts were "fall," "aged," "causality," and "medication." Studies that investigated cardiovascular medications as risk factors for falls in participants ≥60 years old or participants with a mean age of 70 or older were included. A meta-analysis was performed using the generic inverse variance method, pooling unadjusted and adjusted odds ratios (ORs) separately. In total, 131 studies were included in the qualitative synthesis. Meta-analysis using adjusted ORs showed significant results (pooled OR [95% confidence interval]) for loop diuretics, OR 1.36 (1.17, 1.57), and beta-blocking agents, OR 0.88 (0.80, 0.97). Meta-analysis using unadjusted ORs showed significant results for digitalis, OR 1.60 (1.08, 2.36); digoxin, OR 2.06 (1.56, 2.74); and statins, OR 0.80 (0.65, 0.98). Most of the meta-analyses resulted in substantial heterogeneity that mostly did not disappear after stratification for population and setting. In a descriptive synthesis, consistent associations were not observed. Loop diuretics were significantly associated with increased fall risk, whereas beta-blockers were significantly associated with decreased fall risk. Digitalis and digoxin may increase the risk of falling, and statins may reduce it. For the majority of cardiovascular medication groups, outcomes were inconsistent. Furthermore, recent studies indicate that specific drug properties, such as selectivity of beta-blockers, may affect fall risk, and drug-disease interaction also may play

In Silico Identification of Proteins Associated with Drug-induced Liver Injury Based on the Prediction of Drug-target Interactions.

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Ivanov, Sergey; Semin, Maxim; Lagunin, Alexey; Filimonov, Dmitry; Poroikov, Vladimir

2017-07-01

Drug-induced liver injury (DILI) is the leading cause of acute liver failure as well as one of the major reasons for drug withdrawal from clinical trials and the market. Elucidation of molecular interactions associated with DILI may help to detect potentially hazardous pharmacological agents at the early stages of drug development. The purpose of our study is to investigate which interactions with specific human protein targets may cause DILI. Prediction of interactions with 1534 human proteins was performed for the dataset with information about 699 drugs, which were divided into three categories of DILI: severe (178 drugs), moderate (310 drugs) and without DILI (211 drugs). Based on the comparison of drug-target interactions predicted for different drugs' categories and interpretation of those results using clustering, Gene Ontology, pathway and gene expression analysis, we identified 61 protein targets associated with DILI. Most of the revealed proteins were linked with hepatocytes' death caused by disruption of vital cellular processes, as well as the emergence of inflammation in the liver. It was found that interaction of a drug with the identified targets is the essential molecular mechanism of the severe DILI for the most of the considered pharmaceuticals. Thus, pharmaceutical agents interacting with many of the identified targets may be considered as candidates for filtering out at the early stages of drug research. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

Science.gov (United States)

Cervero, Miguel; Torres, Rafael; Jusdado, Juan José; Pastor, Susana; Agud, Jose Luis

2016-04-15

To determine the prevalence and types of clinically significant drug-drug interactions (CSDI) in the drug regimens of HIV-infected patients receiving antiretroviral treatment. retrospective review of database. Centre: Hospital Universitario Severo Ochoa, Infectious Unit. one hundred and forty-two participants followed by one of the authors were selected from January 1985 to December 2014. from their outpatient medical records we reviewed information from the last available visit of the participants, in relation to HIV infection, comorbidities, demographics and the drugs that they were receiving; both antiretroviral drugs and drugs not related to HIV infection. We defined CSDI from the information sheet and/or database on antiretroviral drug interactions of the University of Liverpool (http://www.hiv-druginteractions.org) and we developed a diagnostic tool to predict the possibility of CSDI. By multivariate logistic regression analysis and by estimating the diagnostic performance curve obtained, we identified a quick tool to predict the existence of drug interactions. Of 142 patients, 39 (29.11%) had some type of CSDI and in 11.2% 2 or more interactions were detected. In only one patient the combination of drugs was contraindicated (this patient was receiving darunavir/r and quetiapine). In multivariate analyses, predictors of CSDI were regimen type (PI or NNRTI) and the use of 3 or more non-antiretroviral drugs (AUC 0.886, 95% CI 0.828 to 0.944; P=.0001). The risk was 18.55 times in those receiving NNRTI and 27,95 times in those receiving IP compared to those taking raltegravir. Drug interactions, including those defined as clinically significant, are common in HIV-infected patients treated with antiretroviral drugs, and the risk is greater in IP-based regimens. Raltegravir-based prescribing, especially in patients who receive at least 3 non-HIV drugs could avoid interactions. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

[Integration of pharmacokinetics and pharmacodynamics based on the in vivo analysis of drug-receptor binding].

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Yamada, Shizuo

2015-01-01

  As I was deeply interested in the effects of drugs on the human body, I chose pharmacology as the subject of special study when I became a 4th year student at Shizuoka College of Pharmacy. I studied abroad as a postdoctoral fellow for two years, from 1978, under the tutelage of Professor Henry I. Yamamura (pharmacology) in the College of Medicine at the University of Arizona, USA. He taught me a variety of valuable skills such as the radioreceptor binding assay, which represented the most advanced technology developed in the US at that time. After returning home, I engaged in clarifying receptor abnormalities in pathological conditions, as well as in drug action mechanisms, by making the best use of this radioreceptor binding assay. In 1989, following the founding of the University of Shizuoka, I was invited by Professor Ryohei Kimura to join the Department of Pharmacokinetics. This switch in discipline provided a good opportunity for me to broaden my perspectives in pharmaceutical sciences. I worked on evaluating drug-receptor binding in vivo as a combined index for pharmacokinetics and pharmacological effect manifestation, with the aim of bridging pharmacology and pharmacokinetics. In fact, by focusing on data from in vivo receptor binding, it became possible to clearly rationalize the important consideration of drug dose-concentration-action relationships, and to study quantitative and kinetic analyses of relationships among pharmacokinetics, receptor binding and pharmacological effects. Based on this concept, I was able to demonstrate the utility of dynamic analyses of drug-receptor binding in drug discovery, drug fostering, and the proper use of pharmacokinetics with regard to many drugs.

Text mining-based in silico drug discovery in oral mucositis caused by high-dose cancer therapy.

Science.gov (United States)

Kirk, Jon; Shah, Nirav; Noll, Braxton; Stevens, Craig B; Lawler, Marshall; Mougeot, Farah B; Mougeot, Jean-Luc C

2018-08-01

Oral mucositis (OM) is a major dose-limiting side effect of chemotherapy and radiation used in cancer treatment. Due to the complex nature of OM, currently available drug-based treatments are of limited efficacy. Our objectives were (i) to determine genes and molecular pathways associated with OM and wound healing using computational tools and publicly available data and (ii) to identify drugs formulated for topical use targeting the relevant OM molecular pathways. OM and wound healing-associated genes were determined by text mining, and the intersection of the two gene sets was selected for gene ontology analysis using the GeneCodis program. Protein interaction network analysis was performed using STRING-db. Enriched gene sets belonging to the identified pathways were queried against the Drug-Gene Interaction database to find drug candidates for topical use in OM. Our analysis identified 447 genes common to both the "OM" and "wound healing" text mining concepts. Gene enrichment analysis yielded 20 genes representing six pathways and targetable by a total of 32 drugs which could possibly be formulated for topical application. A manual search on ClinicalTrials.gov confirmed no relevant pathway/drug candidate had been overlooked. Twenty-five of the 32 drugs can directly affect the PTGS2 (COX-2) pathway, the pathway that has been targeted in previous clinical trials with limited success. Drug discovery using in silico text mining and pathway analysis tools can facilitate the identification of existing drugs that have the potential of topical administration to improve OM treatment.

Deep-Learning-Based Drug-Target Interaction Prediction.

Science.gov (United States)

Wen, Ming; Zhang, Zhimin; Niu, Shaoyu; Sha, Haozhi; Yang, Ruihan; Yun, Yonghuan; Lu, Hongmei

2017-04-07

Identifying interactions between known drugs and targets is a major challenge in drug repositioning. In silico prediction of drug-target interaction (DTI) can speed up the expensive and time-consuming experimental work by providing the most potent DTIs. In silico prediction of DTI can also provide insights about the potential drug-drug interaction and promote the exploration of drug side effects. Traditionally, the performance of DTI prediction depends heavily on the descriptors used to represent the drugs and the target proteins. In this paper, to accurately predict new DTIs between approved drugs and targets without separating the targets into different classes, we developed a deep-learning-based algorithmic framework named DeepDTIs. It first abstracts representations from raw input descriptors using unsupervised pretraining and then applies known label pairs of interaction to build a classification model. Compared with other methods, it is found that DeepDTIs reaches or outperforms other state-of-the-art methods. The DeepDTIs can be further used to predict whether a new drug targets to some existing targets or whether a new target interacts with some existing drugs.

Polysaccharides-based polyelectrolyte nanoparticles as protein drugs delivery system

Energy Technology Data Exchange (ETDEWEB)

Shu Shujun; Sun Lei; Zhang Xinge, E-mail: zhangxinge@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China); Wu Zhongming [Tianjin Medical University, Metabolic Diseases Hospital (China); Wang Zhen; Li Chaoxing, E-mail: lcx@nankai.edu.cn [Nankai University, Key Laboratory of Functional Polymer Materials Ministry of Education, Institute of Polymer Chemistry (China)

2011-09-15

Polysaccharides-based nanoparticles were prepared by synthesized quaternized chitosan and dextran sulfate through simple ionic-gelation self-assembled method. Introduction of quaternized groups was intended to increase water solubility of chitosan and make the nanoparticles have broader pH sensitive range which can remain more stable in physiological pH and decrease the loss of protein drugs caused by the gastric cavity. The load of BSA was affected by molecular parameter, i.e., degree of substitution, and average molecular weight of quaternized chitosan, as well as concentration of BSA. Fast release occurred in phosphate buffer solution (pH 7.4) while the release was slow in hydrochloric acid (pH 1.4). The drug release mechanism is Fickian diffusion through release kinetics analysis. Cell uptake demonstrated nanoparicles can internalize into Caco-2 cells, which suggested that nanoparticles had good biocompatibility. No significant conformation change was noted for the released BSA in comparison with native BSA using circular dichroism spectroscopy. This kind of novel composite nanoparticles may be a promising delivery system for oral protein and peptide drugs.

Recent developments in oral lipid-based drug delivery

DEFF Research Database (Denmark)

Thomas, N.; Rades, T.; Müllertz, A.

2013-01-01

The increasing number of poorly water-soluble drugs in development in the pharmaceutical industry has sparked interest in novel drug delivery options such as lipid-based drug delivery systems (LbDDS). Several LbDDS have been marketed successfully and have shown superior and more reliable...... bioavailability compared to conventional formulations. However, some reluctance in the broader application of LbDDS still appears, despite the growing commercial interest in lipids as a drug delivery platform. This reluctance might at least in part be related to the complexity associated with the development...... and characterization of LbDDS. In particular, the lack of standardized test protocols can be identified as the major obstacles for the broader application of LbDDS. This review seeks to summarize recent approaches in the field of lipid-based drug delivery that try to elucidate some critical steps in their development...

Fragment-based drug discovery and molecular docking in drug design.

Science.gov (United States)

Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong

2015-01-01

Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.

A web-based quantitative signal detection system on adverse drug reaction in China.

Science.gov (United States)

Li, Chanjuan; Xia, Jielai; Deng, Jianxiong; Chen, Wenge; Wang, Suzhen; Jiang, Jing; Chen, Guanquan

2009-07-01

To establish a web-based quantitative signal detection system for adverse drug reactions (ADRs) based on spontaneous reporting to the Guangdong province drug-monitoring database in China. Using Microsoft Visual Basic and Active Server Pages programming languages and SQL Server 2000, a web-based system with three software modules was programmed to perform data preparation and association detection, and to generate reports. Information component (IC), the internationally recognized measure of disproportionality for quantitative signal detection, was integrated into the system, and its capacity for signal detection was tested with ADR reports collected from 1 January 2002 to 30 June 2007 in Guangdong. A total of 2,496 associations including known signals were mined from the test database. Signals (e.g., cefradine-induced hematuria) were found early by using the IC analysis. In addition, 291 drug-ADR associations were alerted for the first time in the second quarter of 2007. The system can be used for the detection of significant associations from the Guangdong drug-monitoring database and could be an extremely useful adjunct to the expert assessment of very large numbers of spontaneously reported ADRs for the first time in China.

MALDI-MS drug analysis in biological samples: opportunities and challenges.

Science.gov (United States)

Steuer, Andrea E; Poetzsch, Michael; Kraemer, Thomas

2016-09-01

Drug analysis represents a large field in different disciplines. Plasma is commonly considered to be the biosample of choice for that purpose. However, concentrations often do not represent the levels present within deeper compartments and therefore cannot sufficiently explain efficacy or toxicology of drugs. MALDI-MS in drug analysis is of great interest for high-throughput quantification and particularly spatially resolved tissue imaging. The current perspective article will deal with challenges and opportunities of MALDI-MS drug analysis in different biological samples. A particular focus will be on hair samples. Recent applications were included, reviewed for their instrumental setup and sample preparation and pros and cons as well as future perspectives are critically discussed.

Quantitative Analysis of Complex Drug-Drug Interactions Between Repaglinide and Cyclosporin A/Gemfibrozil Using Physiologically Based Pharmacokinetic Models With In Vitro Transporter/Enzyme Inhibition Data.

Science.gov (United States)

Kim, Soo-Jin; Toshimoto, Kota; Yao, Yoshiaki; Yoshikado, Takashi; Sugiyama, Yuichi

2017-09-01

Quantitative analysis of transporter- and enzyme-mediated complex drug-drug interactions (DDIs) is challenging. Repaglinide (RPG) is transported into the liver by OATP1B1 and then is metabolized by CYP2C8 and CYP3A4. The purpose of this study was to describe the complex DDIs of RPG quantitatively based on unified physiologically based pharmacokinetic (PBPK) models using in vitro K i values for OATP1B1, CYP3A4, and CYP2C8. Cyclosporin A (CsA) or gemfibrozil (GEM) increased the blood concentrations of RPG. The time profiles of RPG and the inhibitors were analyzed by PBPK models, considering the inhibition of OATP1B1 and CYP3A4 by CsA or OATP1B1 inhibition by GEM and its glucuronide and the mechanism-based inhibition of CYP2C8 by GEM glucuronide. RPG-CsA interaction was closely predicted using a reported in vitro K i,OATP1B1 value in the presence of CsA preincubation. RPG-GEM interaction was underestimated compared with observed data, but the simulation was improved with the increase of f m,CYP2C8 . These results based on in vitro K i values for transport and metabolism suggest the possibility of a bottom-up approach with in vitro inhibition data for the prediction of complex DDIs using unified PBPK models and in vitro f m value of a substrate for multiple enzymes should be considered carefully for the prediction. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Chiral Drug Analysis in Forensic Chemistry: An Overview

OpenAIRE

Cláudia Ribeiro; Cristiana Santos; Valter Gonçalves; Ana Ramos; Carlos Afonso; Maria Elizabeth Tiritan

2018-01-01

Many substances of forensic interest are chiral and available either as racemates or pure enantiomers. Application of chiral analysis in biological samples can be useful for the determination of legal or illicit drugs consumption or interpretation of unexpected toxicological effects. Chiral substances can also be found in environmental samples and revealed to be useful for determination of community drug usage (sewage epidemiology), identification of illicit drug manufacturing locations, ille...

Sentiment Analysis of User-Generated Content on Drug Review Websites

Directory of Open Access Journals (Sweden)

Na, Jin-Cheon

2015-03-01

Full Text Available This study develops an effective method for sentiment analysis of user-generated content on drug review websites, which has not been investigated extensively compared to other general domains, such as product reviews. A clause-level sentiment analysis algorithm is developed since each sentence can contain multiple clauses discussing multiple aspects of a drug. The method adopts a pure linguistic approach of computing the sentiment orientation (positive, negative, or neutral of a clause from the prior sentiment scores assigned to words, taking into consideration the grammatical relations and semantic annotation (such as disorder terms of words in the clause. Experiment results with 2,700 clauses show the effectiveness of the proposed approach, and it performed significantly better than the baseline approaches using a machine learning approach. Various challenging issues were identified and discussed through error analysis. The application of the proposed sentiment analysis approach will be useful not only for patients, but also for drug makers and clinicians to obtain valuable summaries of public opinion. Since sentiment analysis is domain specific, domain knowledge in drug reviews is incorporated into the sentiment analysis algorithm to provide more accurate analysis. In particular, MetaMap is used to map various health and medical terms (such as disease and drug names to semantic types in the Unified Medical Language System (UMLS Semantic Network.

Bioengineered protein-based nanocage for drug delivery.

Science.gov (United States)

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

EMPLOYMENT-BASED ABSTINENCE REINFORCEMENT PROMOTES OPIATE AND COCAINE ABSTINENCE IN OUT-OF-TREATMENT INJECTION DRUG USERS

OpenAIRE

Holtyn, August F.; Koffarnus, Mikhail N.; DeFulio, Anthony; Sigurdsson, Sigurdur O.; Strain, Eric C.; Schwartz, Robert P.; Silverman, Kenneth

2014-01-01

We examined the use of employment-based abstinence reinforcement in out-of-treatment injection drug users, in this secondary analysis of a previously reported trial. Participants (N = 33) could work in the therapeutic workplace, a model employment-based program for drug addiction, for 30 weeks and could earn approximately $10 per hr. During a 4-week induction, participants only had to work to earn pay. After induction, access to the workplace was contingent on enrollment in methadone treatmen...

Fragment-based drug discovery and its application to challenging drug targets.

Science.gov (United States)

Price, Amanda J; Howard, Steven; Cons, Benjamin D

2017-11-08

Fragment-based drug discovery (FBDD) is a technique for identifying low molecular weight chemical starting points for drug discovery. Since its inception 20 years ago, FBDD has grown in popularity to the point where it is now an established technique in industry and academia. The approach involves the biophysical screening of proteins against collections of low molecular weight compounds (fragments). Although fragments bind to proteins with relatively low affinity, they form efficient, high quality binding interactions with the protein architecture as they have to overcome a significant entropy barrier to bind. Of the biophysical methods available for fragment screening, X-ray protein crystallography is one of the most sensitive and least prone to false positives. It also provides detailed structural information of the protein-fragment complex at the atomic level. Fragment-based screening using X-ray crystallography is therefore an efficient method for identifying binding hotspots on proteins, which can then be exploited by chemists and biologists for the discovery of new drugs. The use of FBDD is illustrated here with a recently published case study of a drug discovery programme targeting the challenging protein-protein interaction Kelch-like ECH-associated protein 1:nuclear factor erythroid 2-related factor 2. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

From crystal to compound: structure-based antimalarial drug discovery.

Science.gov (United States)

Drinkwater, Nyssa; McGowan, Sheena

2014-08-01

Despite a century of control and eradication campaigns, malaria remains one of the world's most devastating diseases. Our once-powerful therapeutic weapons are losing the war against the Plasmodium parasite, whose ability to rapidly develop and spread drug resistance hamper past and present malaria-control efforts. Finding new and effective treatments for malaria is now a top global health priority, fuelling an increase in funding and promoting open-source collaborations between researchers and pharmaceutical consortia around the world. The result of this is rapid advances in drug discovery approaches and technologies, with three major methods for antimalarial drug development emerging: (i) chemistry-based, (ii) target-based, and (iii) cell-based. Common to all three of these approaches is the unique ability of structural biology to inform and accelerate drug development. Where possible, SBDD (structure-based drug discovery) is a foundation for antimalarial drug development programmes, and has been invaluable to the development of a number of current pre-clinical and clinical candidates. However, as we expand our understanding of the malarial life cycle and mechanisms of resistance development, SBDD as a field must continue to evolve in order to develop compounds that adhere to the ideal characteristics for novel antimalarial therapeutics and to avoid high attrition rates pre- and post-clinic. In the present review, we aim to examine the contribution that SBDD has made to current antimalarial drug development efforts, covering hit discovery to lead optimization and prevention of parasite resistance. Finally, the potential for structural biology, particularly high-throughput structural genomics programmes, to identify future targets for drug discovery are discussed.

Investigation of drug products received for analysis in the Swedish STRIDA project on new psychoactive substances.

Science.gov (United States)

Bäckberg, Matilda; Jönsson, Karl-Henrik; Beck, Olof; Helander, Anders

2018-02-01

The web-based open sale of unregulated new psychoactive substances (NPS) has shown a steady increase in recent years. Analysis of drug products sold as NPS is useful to confirm the true chemical contents, for comparison with the substances detected in corresponding body fluids, but also to study drug trends. This work describes the examination of 251 drug products that were randomly submitted for analysis in 173 cases of suspected NPS-related intoxications in the Swedish STRIDA project in 2010-2015. Of the products, 39% were powders/crystals, 32% tablets/capsules, 16% herbal materials, 8% liquids, 1% blotters, and 4% others. The analysis involved tandem mass spectrometry and nuclear magnetic resonance spectroscopy. In 88 products (35%), classic psychoactive substances, prescription pharmaceuticals, dietary supplements, or doping agents were found; however, in none of these cases had an NPS-related intoxication been indicated from product markings or patient self-reports. Another 12 products tested negative for psychoactive substances. The remaining 151 products contained 86 different NPS (30% contained ≥2 substances). In 104 drug products, a specific NPS ingredient was indicated based on labelling (69%) or patient self-report; in 92 cases this was also analytically confirmed to be correct. Overall, the NPS products submitted for analysis in the STRIDA project showed a high degree of consistency between suspected and actual content (88%). The results of related urine and/or blood analysis further demonstrated that the patients commonly (89%) tested positive for the indicated NPS, but also revealed that polysubstance intoxication was common (83%), indicating use of additional drug products. Copyright © 2017 John Wiley & Sons, Ltd.

Buying drugs on a Darknet market: A better deal? Studying the online illicit drug market through the analysis of digital, physical and chemical data.

Science.gov (United States)

Rhumorbarbe, Damien; Staehli, Ludovic; Broséus, Julian; Rossy, Quentin; Esseiva, Pierre

2016-10-01

Darknet markets, also known as cryptomarkets, are websites located on the Darknet and designed to allow the trafficking of illicit products, mainly drugs. This study aims at presenting the added value of combining digital, chemical and physical information to reconstruct sellers' activities. In particular, this research focuses on Evolution, one of the most popular cryptomarkets active from January 2014 to March 2015. Evolution source code files were analysed using Python scripts based on regular expressions to extract information about listings (i.e., sales proposals) and sellers. The results revealed more than 48,000 listings and around 2700 vendors claiming to send illicit drug products from 70 countries. The most frequent categories of illicit drugs offered by vendors were cannabis-related products (around 25%) followed by ecstasy (MDA, MDMA) and stimulants (cocaine, speed). The cryptomarket was then especially studied from a Swiss point of view. Illicit drugs were purchased from three sellers located in Switzerland. The purchases were carried out to confront digital information (e.g., the type of drug, the purity, the shipping country and the concealment methods mentioned on listings) with the physical analysis of the shipment packaging and the chemical analysis of the received product (purity, cutting agents, chemical profile based on minor and major alkaloids, chemical class). The results show that digital information, such as concealment methods and shipping country, seems accurate. But the illicit drugs purity is found to be different from the information indicated on their respective listings. Moreover, chemical profiling highlighted links between cocaine sold online and specimens seized in Western Switzerland. This study highlights that (1) the forensic analysis of the received products allows the evaluation of the accuracy of digital data collected on the website, and (2) the information from digital and physical/chemical traces are complementary to

Meta-Analysis of Randomized Clinical Trials Comparing Biodegradable Polymer Drug-Eluting Stent to Second-Generation Durable Polymer Drug-Eluting Stents.

Science.gov (United States)

El-Hayek, Georges; Bangalore, Sripal; Casso Dominguez, Abel; Devireddy, Chandan; Jaber, Wissam; Kumar, Gautam; Mavromatis, Kreton; Tamis-Holland, Jacqueline; Samady, Habib

2017-03-13

The authors sought to perform a meta-analysis of randomized clinical trials (RCTs) comparing the safety and efficacy of biodegradable polymer drug-eluting stents (BP-DES) to second-generation durable polymer drug-eluting stents (DP-DES). Prior meta-analyses have established the superiority of BP-DES over bare-metal stents and first-generation DP-DES; however, their advantage compared with second-generation DP-DES remains controversial. The authors searched PubMed and Scopus databases for RCTs comparing BP-DES to the second-generation DP-DES. Outcomes included target vessel revascularization (TVR) as efficacy outcome and cardiac death, myocardial infarction (MI), and definite or probable stent thrombosis (ST) as safety outcomes. In addition, we performed landmark analysis for endpoints beyond 1 year of follow-up and a subgroup analysis based on the stent characteristics. The authors included 16 RCTs comprising 19,886 patients in the meta-analysis. At the longest available follow-up (mean duration 26 months), we observed no significant differences in TVR (p = 0.62), cardiac death (p = 0.46), MI (p = 0.98), or ST (risk ratio: 0.83, 95% confidence interval: 0.64 to 1.09; p = 0.19). Our landmark analysis showed that BP-DES were not associated with a reduction in the risk of very late ST (risk ratio: 0.87, 95% confidence interval: 0.49 to 1.53; p = 0.62). Similar outcomes were seen regardless of the eluting drug (biolimus vs. sirolimus), the stent platform (stainless steel vs. alloy), the kinetics of polymer degradation or drug release (6 months), the strut thickness of the BP-DES (thin 100 μm), or the DAPT duration (≥6 months vs. ≥12 months). BP-DES have similar safety and efficacy profiles to second-generation DP-DES. Published by Elsevier Inc.

The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development.

Science.gov (United States)

Kunz, Meik; Liang, Chunguang; Nilla, Santosh; Cecil, Alexander; Dandekar, Thomas

2016-01-01

The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure-activity relationships.Database URL:http://drumpid.bioapps.biozentrum.uni-wuerzburg.de. © The Author(s) 2016. Published by Oxford University Press.

An Evidence-Based Assessment of the Clinical Significance of Drug-Drug Interactions Between Disease-Modifying Antirheumatic Drugs and Non-Antirheumatic Drugs According to Rheumatologists and Pharmacists

NARCIS (Netherlands)

van Roon, Eric N.; van den Bemt, Patricia M. L. A.; Jansen, Tim L. Th. A.; Houtman, Nella M.; van de Laar, Mart A. F. J.; Brouwers, Jacobus R. B. J.

Background: Clinically relevant drug-drug interactions (DDIs) must be recognized in a timely manner and managed appropriately to prevent adverse drug reactions or therapeutic failure. Because the evidence for most DDIs is based on case reports or poorly documented clinical information, there is a

MLViS: A Web Tool for Machine Learning-Based Virtual Screening in Early-Phase of Drug Discovery and Development.

Science.gov (United States)

Korkmaz, Selcuk; Zararsiz, Gokmen; Goksuluk, Dincer

2015-01-01

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/.

Methodological aspects on drug receptor binding analysis

International Nuclear Information System (INIS)

Wahlstroem, A.

1978-01-01

Although drug receptors occur in relatively low concentrations, they can be visualized by the use of appropriate radioindicators. In most cases the procedure is rapid and can reach a high degree of accuracy. Specificity of the interaction is studied by competition analysis. The necessity of using several radioindicators to define a receptor population is emphasized. It may be possible to define isoreceptors and drugs with selectivity for one isoreceptor. (Author)

DRUG EVALUATION AND DECISION MAKING IN CATALONIA: DEVELOPMENT AND VALIDATION OF A METHODOLOGICAL FRAMEWORK BASED ON MULTI-CRITERIA DECISION ANALYSIS (MCDA) FOR ORPHAN DRUGS.

Science.gov (United States)

Gilabert-Perramon, Antoni; Torrent-Farnell, Josep; Catalan, Arancha; Prat, Alba; Fontanet, Manel; Puig-Peiró, Ruth; Merino-Montero, Sandra; Khoury, Hanane; Goetghebeur, Mireille M; Badia, Xavier

2017-01-01

The aim of this study was to adapt and assess the value of a Multi-Criteria Decision Analysis (MCDA) framework (EVIDEM) for the evaluation of Orphan drugs in Catalonia (Catalan Health Service). The standard evaluation and decision-making procedures of CatSalut were compared with the EVIDEM methodology and contents. The EVIDEM framework was adapted to the Catalan context, focusing on the evaluation of Orphan drugs (PASFTAC program), during a Workshop with sixteen PASFTAC members. The criteria weighting was done using two different techniques (nonhierarchical and hierarchical). Reliability was assessed by re-test. The EVIDEM framework and methodology was found useful and feasible for Orphan drugs evaluation and decision making in Catalonia. All the criteria considered for the development of the CatSalut Technical Reports and decision making were considered in the framework. Nevertheless, the framework could improve the reporting of some of these criteria (i.e., "unmet needs" or "nonmedical costs"). Some Contextual criteria were removed (i.e., "Mandate and scope of healthcare system", "Environmental impact") or adapted ("population priorities and access") for CatSalut purposes. Independently of the weighting technique considered, the most important evaluation criteria identified for orphan drugs were: "disease severity", "unmet needs" and "comparative effectiveness", while the "size of the population" had the lowest relevance for decision making. Test-retest analysis showed weight consistency among techniques, supporting reliability overtime. MCDA (EVIDEM framework) could be a useful tool to complement the current evaluation methods of CatSalut, contributing to standardization and pragmatism, providing a method to tackle ethical dilemmas and facilitating discussions related to decision making.

Association between HIV/AIDS and multi-drug resistance tuberculosis: a systematic review and meta-analysis.

Directory of Open Access Journals (Sweden)

Yonatan Moges Mesfin

Full Text Available BACKGROUND: Human immunodeficiency virus (HIV, multi-drug resistant tuberculosis (MDR is emerging as major challenge facing tuberculosis control programs worldwide particularly in Asia and Africa. Findings from different studies on associations of HIV co-infection and drug resistance among patients with TB have been contradictory (discordant. Some institution based studies found strongly increased risks for multi-drug resistant TB (MDR TB among patients co-infected with TB and HIV, whereas other studies found no increased risk (it remains less clear in community based studies. The aim was to conduct a systematic review and meta-analysis of the association between multi-drug resistant tuberculosis and HIV infection. METHODS AND FINDINGS: Systematic review of the published literature of observational studies was conducted. Original studies were identified using databases of Medline/Pubmed, Google Scholar and HINARI. The descriptions of original studies were made using frequency and forest plot. Publication bias was assessed using Funnel plot graphically and Egger weighted and Begg rank regression tests statistically. Heterogeneity across studies was checked using Cochrane Q test statistic and I(2. Pool risk estimates of MDR-TB and sub-grouping analysis were computed to analyze associations with HIV. Random effects of the meta-analysis of all 24 observational studies showed that HIV is associated with a marginal increased risk of multi-drug resistant tuberculosis (estimated Pooled OR 1.24; 95%, 1.04-1.43. Subgroup analyses showed that effect estimates were higher (Pooled OR 2.28; 95%, 1.52-3.04 for primary multi-drug resistance tuberculosis and moderate association between HIV/AIDS and MDR-TB among population based studies and no significant association in institution settings. CONCLUSIONS: This study demonstrated that there is association between MDR-TB and HIV. Capacity for diagnosis of MDR-TB and initiating and scale up of antiretroviral

Tubulin Inhibitor-Based Antibody-Drug Conjugates for Cancer Therapy

Directory of Open Access Journals (Sweden)

Hao Chen

2017-08-01

Full Text Available Antibody-drug conjugates (ADCs are a class of highly potent biopharmaceutical drugs generated by conjugating cytotoxic drugs with specific monoclonal antibodies through appropriate linkers. Specific antibodies used to guide potent warheads to tumor tissues can effectively reduce undesired side effects of the cytotoxic drugs. An in-depth understanding of antibodies, linkers, conjugation strategies, cytotoxic drugs, and their molecular targets has led to the successful development of several approved ADCs. These ADCs are powerful therapeutics for cancer treatment, enabling wider therapeutic windows, improved pharmacokinetic/pharmacodynamic properties, and enhanced efficacy. Since tubulin inhibitors are one of the most successful cytotoxic drugs in the ADC armamentarium, this review focuses on the progress in tubulin inhibitor-based ADCs, as well as lessons learned from the unsuccessful ADCs containing tubulin inhibitors. This review should be helpful to facilitate future development of new generations of tubulin inhibitor-based ADCs for cancer therapy.

Spatial and Temporal Assessment on Drug Addiction Using Multivariate Analysis and GIS

International Nuclear Information System (INIS)

Mohd Ekhwan Toriman; Mohd Ekhwan Toriman; Siti Nor Fazillah Abdullah; Izwan Arif Azizan; Mohd Khairul Amri Kamarudin; Roslan Umar; Nasir Mohamad

2015-01-01

There is a need for managing and displaying drug addiction phenomena and trend at both spatial and temporal scales. Spatial and temporal assessment on drug addiction in Terengganu was undertaken to understand the geographical area of district in the same cluster, in addition, identify the hot spot area of this problem and analysis the trend of drug addiction. Data used were topography map of Terengganu and number of drug addicted person in Terengganu by district within 10 years (2004-2013). Number of drug addicted person by district were mapped using Geographic Information system and analysed using a combination of multivariate analysis which is cluster analysis were applied to the database in order to validate the correlation between data in the same cluster. Result showed a cluster analysis for number of drug addiction by district generated three clusters which are Besut and Kuala Terengganu in cluster 1 named moderate drug addicted person (MDA), Dungun, Marang, Setiu and Hulu Terengganu in cluster 2 named lower drug addicted person (LDA) and Kemaman in cluster 3 named high drug addicted person(HDA). This analysis indicates that cluster 3 which is Kemaman is a hot spot area. These results were beneficial for stakeholder to monitor and manage this problem especially in the hot spot area which needs to be emphasized. (author)

Risk of Clinically Relevant Pharmacokinetic-based Drug-drug Interactions with Drugs Approved by the U.S. Food and Drug Administration Between 2013 and 2016.

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Yu, Jingjing; Zhou, Zhu; Tay-Sontheimer, Jessica; Levy, Rene H; Ragueneau-Majlessi, Isabelle

2018-03-23

A total of 103 drugs (including 14 combination drugs) were approved by the U.S. Food and Drug Administration from 2013 to 2016. Pharmacokinetic-based drug interaction profiles were analyzed using the University of Washington Drug Interaction Database and the clinical relevance of these observations was characterized based on information from New Drug Application reviews. CYP3A was identified as a major contributor to clinical drug-drug interactions (DDIs), involved in approximately 2/3 of all interactions. Transporters (alone or with enzymes) were found to participate in about half of all interactions, although most of these were weak-to-moderate interactions. When considered as victims, eight new molecular entities (NMEs; cobimetinib, ibrutnib, isavuconazole, ivabradine, naloxegol, paritaprevir, simeprevir, and venetoclax) were identified as sensitive substrates of CYP3A, two NMEs (pirfenidone and tasimelteon) were sensitive substrates of CYP1A2, one NME (dasabuvir) was a sensitive substrate of CYP2C8, one NME (eliglustat) was a sensitive substrate of CYP2D6, and one NME (grazoprevir) was a sensitive substrate of OATP1B1/3 (with changes in exposure greater than 5-fold when co-administered with a strong inhibitor). Interestingly, approximately 75% of identified CYP3A substrates were also substrates of P-gp. As perpetrators, most clinical DDIs involved weak-to-moderate inhibition or induction, with only two drugs (Viekira Pak and idelalisib) showing strong inhibition of CYP3A, and one NME (lumacaftor) considered as a strong CYP3A inducer. Among drugs with large changes in exposure (≥ 5-fold), whether as victim or perpetrator, the most represented therapeutic classes were antivirals and oncology drugs, suggesting a significant risk of clinical DDIs in these patient populations. The American Society for Pharmacology and Experimental Therapeutics.

Using Population Based Data on Drugs Abuse to Estimate the Relative Need for Medical Services in Thailand.

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Leyatikul, Poonrut; Kanato, Manop

2015-07-01

Epidemiological background shows a trend in drug abuse and essential need for revising its strategic plans, allocating resources, and advocating services for populations. The relative need for drug abuse prevention and medical services across different geographic areas of Thailand, which has been examined through an analysis of existing population-based datasets and reported routinely. The objective was to develop an indicator of relative need for drug abuse prevention and medical services. Qualitative data were collected as primary data sources from 10 focus group discussions throughout Thailand. The primary data were integrated into study framework with the result from literature review. Data sets in 2011 were retrieved from the national databank to obtain variables regarding drug abuse. Multiple regression and factor analysis were undertaken using the district as the unit of analysis. A factor analysis, which revealed six factors that explained 64% of the variance in the data set. Factors identified in the analysis were taken as indicators of variation in the need for services as all of the drugs-related variables loaded strongly on these factors. The distribution of ranks for factor scores (determined through regression) obtained for these factors across districts in Thailand showed that scores were highest in urban and suburban areas. In terms of practical implications, the study results could be used for resource allocation in medical service plans for community drug abuse.

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

Mechanism-based risk assessment strategy for drug-induced cholestasis using the transcriptional benchmark dose derived by toxicogenomics.

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Kawamoto, Taisuke; Ito, Yuichi; Morita, Osamu; Honda, Hiroshi

2017-01-01

Cholestasis is one of the major causes of drug-induced liver injury (DILI), which can result in withdrawal of approved drugs from the market. Early identification of cholestatic drugs is difficult due to the complex mechanisms involved. In order to develop a strategy for mechanism-based risk assessment of cholestatic drugs, we analyzed gene expression data obtained from the livers of rats that had been orally administered with 12 known cholestatic compounds repeatedly for 28 days at three dose levels. Qualitative analyses were performed using two statistical approaches (hierarchical clustering and principle component analysis), in addition to pathway analysis. The transcriptional benchmark dose (tBMD) and tBMD 95% lower limit (tBMDL) were used for quantitative analyses, which revealed three compound sub-groups that produced different types of differential gene expression; these groups of genes were mainly involved in inflammation, cholesterol biosynthesis, and oxidative stress. Furthermore, the tBMDL values for each test compound were in good agreement with the relevant no observed adverse effect level. These results indicate that our novel strategy for drug safety evaluation using mechanism-based classification and tBMDL would facilitate the application of toxicogenomics for risk assessment of cholestatic DILI.

Population Analysis of Pharmacogenetic Polymorphisms Related to Acute Lymphoblastic Leukemia Drug Treatment

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Marcela A. Chiabai

2012-01-01

Full Text Available This study aimed to evaluate in the Brazilian population, the genotypes and population frequencies of pharmacogenetic polymorphisms involved in the response to drugs used in treatment of acute lymphoblastic leukemia (ALL, and to compare the data with data from the HapMap populations. There was significant differentiation between most population pairs, but few associations between genetic ancestry and SNPs in the Brazilian population were observed. AMOVA analysis comparing the Brazilian population to all other populations retrieved from HapMap pointed to a genetic proximity with the European population. These associations point to preclusion of the use of genetic ancestry as a proxy for predicting drug response. In this way, any study aiming to correlate genotype with drug response in the Brazilian population should be based on pharmacogenetic SNP genotypes.

The Relationship Between Osteomyelitis Complication and Drug-Resistant Infection Risk in Diabetic Foot Ulcer: A Meta-analysis.

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Chen, Yin; Ding, Hui; Wu, Hua; Chen, Hong-Lin

2017-09-01

In this study, we aimed to investigate the relationship between osteomyelitis complications and drug-resistant infection risk in diabetic foot ulcer. Searches of MEDLINE and ISI databases were performed for the studies. Odds ratios (ORs) for drug-resistant infection incidence were calculated for diabetic foot ulcer patients with or without osteomyelitis complications. Eleven studies (12 cohorts) with 1526 patients were included in this study. Meta-analysis showed that the summary OR was 3.343 (95% CI = 2.355-4.745; Z = 6.75, P analysis by only pooled the adjusted ORs showed that the result was robust (the summary OR = 4.081, 95% CI = 2.471-6.739). Subgroup analysis by drug-resistant type showed that the summary OR was 4.391 (95% CI = 2.287-8.394) for methicillin-resistant infection subgroup, and 2.693 (95% CI = 1.882-3.851) for multidrug-resistant infection subgroup. The meta-regression showed that drug-resistant incidence ( t = -0.90, P = .389) and published year ( t = -0.11, P = .913) were not related with the OR changes. In conclusion, our meta-analysis indicates that osteomyelitis complications are related with drug-resistant infection risk in diabetic foot ulcer. We suggest bone culture-based narrow-spectrum antibiotic therapy for osteomyelitis for prevention drug-resistant infection in diabetic foot ulcer.

Hybrid Drug Delivery Patches Based on Spherical Cellulose Nanocrystals and Colloid Titania—Synthesis and Antibacterial Properties

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Olga L. Evdokimova

2018-04-01

Full Text Available Spherical cellulose nanocrystal-based hybrids grafted with titania nanoparticles were successfully produced for topical drug delivery. The conventional analytical filter paper was used as a precursor material for cellulose nanocrystals (CNC production. Cellulose nanocrystals were extracted via a simple and quick two-step process based on first the complexation with Cu(II solution in aqueous ammonia followed by acid hydrolysis with diluted H2SO4. Triclosan was selected as a model drug for complexation with titania and further introduction into the nanocellulose based composite. Obtained materials were characterized by a broad variety of microscopic, spectroscopic, and thermal analysis methods. The drug release studies showed long-term release profiles of triclosan from the titania based nanocomposite that agreed with Higuchi model. The bacterial susceptibility tests demonstrated that released triclosan retained its antibacterial activity against Escherichia coli and Staphylococcus aureus. It was found that a small amount of titania significantly improved the antibacterial activity of obtained nanocomposites, even without immobilization of model drug. Thus, the developed hybrid patches are highly promising candidates for potential application as antibacterial agents.

Application of the fragment molecular orbital method analysis to fragment-based drug discovery of BET (bromodomain and extra-terminal proteins) inhibitors.

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Ozawa, Motoyasu; Ozawa, Tomonaga; Ueda, Kazuyoshi

2017-06-01

The molecular interactions of inhibitors of bromodomains (BRDs) were investigated. BRDs are protein interaction modules that recognizing ε-N-acetyl-lysine (εAc-Lys) motifs found in histone tails and are promising protein-protein interaction (PPI) targets. First, we analyzed a peptide ligand containing εAc-Lys to evaluate native PPIs. We then analyzed tetrahydroquinazoline-6-yl-benzensulfonamide derivatives found by fragment-based drug design (FBDD) and examined their interactions with the protein compared with the peptide ligand in terms of the inter-fragment interaction energy. In addition, we analyzed benzodiazepine derivatives that are high-affinity ligands for BRDs and examined differences in the CH/π interactions of the amino acid residues. We further surveyed changes in the charges of the amino acid residues among individual ligands, performed pair interaction energy decomposition analysis and estimated the water profile within the ligand binding site. Thus, useful insights for drug design were provided. Through these analyses and considerations, we show that the FMO method is a useful drug design tool to evaluate the process of FBDD and to explore PPI inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.

Cogena, a novel tool for co-expressed gene-set enrichment analysis, applied to drug repositioning and drug mode of action discovery.

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Jia, Zhilong; Liu, Ying; Guan, Naiyang; Bo, Xiaochen; Luo, Zhigang; Barnes, Michael R

2016-05-27

Drug repositioning, finding new indications for existing drugs, has gained much recent attention as a potentially efficient and economical strategy for accelerating new therapies into the clinic. Although improvement in the sensitivity of computational drug repositioning methods has identified numerous credible repositioning opportunities, few have been progressed. Arguably the "black box" nature of drug action in a new indication is one of the main blocks to progression, highlighting the need for methods that inform on the broader target mechanism in the disease context. We demonstrate that the analysis of co-expressed genes may be a critical first step towards illumination of both disease pathology and mode of drug action. We achieve this using a novel framework, co-expressed gene-set enrichment analysis (cogena) for co-expression analysis of gene expression signatures and gene set enrichment analysis of co-expressed genes. The cogena framework enables simultaneous, pathway driven, disease and drug repositioning analysis. Cogena can be used to illuminate coordinated changes within disease transcriptomes and identify drugs acting mechanistically within this framework. We illustrate this using a psoriatic skin transcriptome, as an exemplar, and recover two widely used Psoriasis drugs (Methotrexate and Ciclosporin) with distinct modes of action. Cogena out-performs the results of Connectivity Map and NFFinder webservers in similar disease transcriptome analyses. Furthermore, we investigated the literature support for the other top-ranked compounds to treat psoriasis and showed how the outputs of cogena analysis can contribute new insight to support the progression of drugs into the clinic. We have made cogena freely available within Bioconductor or https://github.com/zhilongjia/cogena . In conclusion, by targeting co-expressed genes within disease transcriptomes, cogena offers novel biological insight, which can be effectively harnessed for drug discovery and

Native Mass Spectrometry in Fragment-Based Drug Discovery

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Liliana Pedro

2016-07-01

Full Text Available The advent of native mass spectrometry (MS in 1990 led to the development of new mass spectrometry instrumentation and methodologies for the analysis of noncovalent protein–ligand complexes. Native MS has matured to become a fast, simple, highly sensitive and automatable technique with well-established utility for fragment-based drug discovery (FBDD. Native MS has the capability to directly detect weak ligand binding to proteins, to determine stoichiometry, relative or absolute binding affinities and specificities. Native MS can be used to delineate ligand-binding sites, to elucidate mechanisms of cooperativity and to study the thermodynamics of binding. This review highlights key attributes of native MS for FBDD campaigns.

Native Mass Spectrometry in Fragment-Based Drug Discovery.

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Pedro, Liliana; Quinn, Ronald J

2016-07-28

The advent of native mass spectrometry (MS) in 1990 led to the development of new mass spectrometry instrumentation and methodologies for the analysis of noncovalent protein-ligand complexes. Native MS has matured to become a fast, simple, highly sensitive and automatable technique with well-established utility for fragment-based drug discovery (FBDD). Native MS has the capability to directly detect weak ligand binding to proteins, to determine stoichiometry, relative or absolute binding affinities and specificities. Native MS can be used to delineate ligand-binding sites, to elucidate mechanisms of cooperativity and to study the thermodynamics of binding. This review highlights key attributes of native MS for FBDD campaigns.

Integrated Teaching of Structure-Based Drug Design and Biopharmaceutics: A Computer-Based Approach

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Sutch, Brian T.; Romero, Rebecca M.; Neamati, Nouri; Haworth, Ian S.

2012-01-01

Rational drug design requires expertise in structural biology, medicinal chemistry, physiology, and related fields. In teaching structure-based drug design, it is important to develop an understanding of the need for early recognition of molecules with "drug-like" properties as a key component. That is, it is not merely sufficient to teach…

Pooling, meta-analysis, and the evaluation of drug safety

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Leizorovicz Alain

2002-03-01

Full Text Available Abstract Background The "integrated safety report" of the drug registration files submitted to health authorities usually summarizes the rates of adverse events observed for a new drug, placebo or active control drugs by pooling the safety data across the trials. Pooling consists of adding the numbers of events observed in a given treatment group across the trials and dividing the results by the total number of patients included in this group. Because it considers treatment groups rather than studies, pooling ignores validity of the comparisons and is subject to a particular kind of bias, termed "Simpson's paradox." In contrast, meta-analysis and other stratified analyses are less susceptible to bias. Methods We use a hypothetical, but not atypical, application to demonstrate that the results of a meta-analysis can differ greatly from those obtained by pooling the same data. In our hypothetical model, a new drug is compared to 1 a placebo in 4 relatively small trials in patients at high risk for a certain adverse event and 2 an active reference drug in 2 larger trials of patients at low risk for this event. Results Using meta-analysis, the relative risk of experiencing the adverse event with the new drug was 1.78 (95% confidence interval [1.02; 3.12] compared to placebo and 2.20 [0.76; 6.32] compared to active control. By pooling the data, the results were, respectively, 1.00 [0.59; 1.70] and 5.20 [2.07; 13.08]. Conclusions Because these findings could mislead health authorities and doctors, regulatory agencies should require meta-analyses or stratified analyses of safety data in drug registration files.

An analysis of potential costs of adverse events based on Drug Programs in Poland. Pulmonology focus

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Szkultecka-Debek Monika

2014-06-01

Full Text Available The project was performed within the Polish Society for Pharmacoeconomics (PTFE. The objective was to estimate the potential costs of treatment of side effects, which theoretically may occur as a result of treatment of selected diseases. We analyzed the Drug Programs financed by National Health Fund in Poland in 2012 and for the first analysis we selected those Programs where the same medicinal products were used. We based the adverse events selection on the Summary of Product Characteristics of the chosen products. We extracted all the potential adverse events defined as frequent and very frequent, grouping them according to therapeutic areas. This paper is related to the results in the pulmonology area. The events described as very common had an incidence of ≥ 1/10, and the common ones ≥ 1/100, <1/10. In order to identify the resources used, we performed a survey with the engagement of clinical experts. On the basis of the collected data we allocated direct costs incurred by the public payer. We used the costs valid in December 2013. The paper presents the estimated costs of treatment of side effects related to the pulmonology disease area. Taking into account the costs incurred by the NHF and the patient separately e calculated the total spending and the percentage of each component cost in detail. The treatment of adverse drug reactions generates a significant cost incurred by both the public payer and the patient.

Predicting the effect of cytochrome P450 inhibitors on substrate drugs: analysis of physiologically based pharmacokinetic modeling submissions to the US Food and Drug Administration.

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Wagner, Christian; Pan, Yuzhuo; Hsu, Vicky; Grillo, Joseph A; Zhang, Lei; Reynolds, Kellie S; Sinha, Vikram; Zhao, Ping

2015-01-01

The US Food and Drug Administration (FDA) has seen a recent increase in the application of physiologically based pharmacokinetic (PBPK) modeling towards assessing the potential of drug-drug interactions (DDI) in clinically relevant scenarios. To continue our assessment of such approaches, we evaluated the predictive performance of PBPK modeling in predicting cytochrome P450 (CYP)-mediated DDI. This evaluation was based on 15 substrate PBPK models submitted by nine sponsors between 2009 and 2013. For these 15 models, a total of 26 DDI studies (cases) with various CYP inhibitors were available. Sponsors developed the PBPK models, reportedly without considering clinical DDI data. Inhibitor models were either developed by sponsors or provided by PBPK software developers and applied with minimal or no modification. The metric for assessing predictive performance of the sponsors' PBPK approach was the R predicted/observed value (R predicted/observed = [predicted mean exposure ratio]/[observed mean exposure ratio], with the exposure ratio defined as [C max (maximum plasma concentration) or AUC (area under the plasma concentration-time curve) in the presence of CYP inhibition]/[C max or AUC in the absence of CYP inhibition]). In 81 % (21/26) and 77 % (20/26) of cases, respectively, the R predicted/observed values for AUC and C max ratios were within a pre-defined threshold of 1.25-fold of the observed data. For all cases, the R predicted/observed values for AUC and C max were within a 2-fold range. These results suggest that, based on the submissions to the FDA to date, there is a high degree of concordance between PBPK-predicted and observed effects of CYP inhibition, especially CYP3A-based, on the exposure of drug substrates.

Chiral Drug Analysis in Forensic Chemistry: An Overview

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Cláudia Ribeiro

2018-01-01

Full Text Available Many substances of forensic interest are chiral and available either as racemates or pure enantiomers. Application of chiral analysis in biological samples can be useful for the determination of legal or illicit drugs consumption or interpretation of unexpected toxicological effects. Chiral substances can also be found in environmental samples and revealed to be useful for determination of community drug usage (sewage epidemiology, identification of illicit drug manufacturing locations, illegal discharge of sewage and in environmental risk assessment. Thus, the purpose of this paper is to provide an overview of the application of chiral analysis in biological and environmental samples and their relevance in the forensic field. Most frequently analytical methods used to quantify the enantiomers are liquid and gas chromatography using both indirect, with enantiomerically pure derivatizing reagents, and direct methods recurring to chiral stationary phases.

How do we talk about doctors and drugs? Sentiment analysis in forums expressing opinions for medical domain.

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Jiménez-Zafra, Salud María; Martín-Valdivia, M Teresa; Molina-González, M Dolores; Ureña-López, L Alfonso

2018-04-20

The main goal of this study is to examine how people express their opinion in medical forums. We analyze the language used in order to determine the best way to tackle sentiment analysis in this domain. We have applied supervised learning and lexicon-based sentiment analysis approaches over two different corpora extracted from social web. Specifically, we have focused on two aspects: drugs and doctors. We have selected two forums and we have collected corpora for each one: (i) DOS, a Spanish corpus of drug reviews and (ii) COPOS, a Spanish corpus of patients' opinions about physicians. The classification results show that drug reviews are more difficult to classify than those about physicians. In order to understand the difference in the results, we have studied the linguistic features of both corpora. Although opinions about physicians and drugs are written in most cases by non-professional users, reviews about physicians are characterized by the use of an informal language while reviews about drugs are characterized by a combination of informal language with specific terminology (e.g. adverse effects, drug names) with greater lexical diversity, making the task of sentiment analysis difficult. Copyright © 2018 Elsevier B.V. All rights reserved.

Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations

OpenAIRE

Hethey, Christoph Philipp

2017-01-01

Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. In...

A Multimodal Data Analysis Approach for Targeted Drug Discovery Involving Topological Data Analysis (TDA).

Science.gov (United States)

Alagappan, Muthuraman; Jiang, Dadi; Denko, Nicholas; Koong, Albert C

In silico drug discovery refers to a combination of computational techniques that augment our ability to discover drug compounds from compound libraries. Many such techniques exist, including virtual high-throughput screening (vHTS), high-throughput screening (HTS), and mechanisms for data storage and querying. However, presently these tools are often used independent of one another. In this chapter, we describe a new multimodal in silico technique for the hit identification and lead generation phases of traditional drug discovery. Our technique leverages the benefits of three independent methods-virtual high-throughput screening, high-throughput screening, and structural fingerprint analysis-by using a fourth technique called topological data analysis (TDA). We describe how a compound library can be independently tested with vHTS, HTS, and fingerprint analysis, and how the results can be transformed into a topological data analysis network to identify compounds from a diverse group of structural families. This process of using TDA or similar clustering methods to identify drug leads is advantageous because it provides a mechanism for choosing structurally diverse compounds while maintaining the unique advantages of already established techniques such as vHTS and HTS.

Modelling a budgetary impact analysis for funding drug-based smoking cessation therapies for patients with major depressive disorder in Spain.

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Rejas-Gutiérrez, J; Bruguera, E; Cedillo, S

2017-09-01

Smoking is associated with high healthcare resource utilisation and cost to society. Patients with major depressive disorder (MDD) exhibit high susceptibility to nicotine dependence. Varenicline, bupropion and nicotine replacement therapy are all indicated for smoking cessation; however funding by the Spanish national health system (SNHS) is limited. We modelled a budgetary impact analysis (BIA) to estimate the impact of the SNHS funding drug-based therapies for smoking cessation in smokers with MDD. The BIA compared the current unfunded scenario versus a funded scenario (varenicline, bupropion, nicotine replacement therapy combined with medical follow-up and counselling) using the Spanish SNHS and societal perspectives. The BIA design was a hybrid model using a decision tree algorithm (population size: smokers with MDD) and Markov chains (smoking cessation attempts) over a 5-year horizon. Smoking cessation drug efficacy was derived from clinical trials, and smoking cessation costs avoided were taken from an analysis of the Spanish National Health Survey. Results were shown as incremental cost savings. Scenarios and threshold univariate sensitivity analyses tested model robustness. The funded scenario resulted in an increase of 43,478 cessation attempts and 8930 fewer smokers after 5 years compared to the unfunded scenario. The cost of funding was €25.3 million and costs avoided were €26.5 million. There was a cumulative 5-year incremental cost saving of €1.2 million to Spanish society. Results were robust using alternative scenarios. Funding smoking cessation drugs in patients with MDD is of economic benefit to Spain and could produce net savings from the third year of implementation. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Functionalization of protein-based nanocages for drug delivery applications.

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Schoonen, Lise; van Hest, Jan C M

2014-07-07

Traditional drug delivery strategies involve drugs which are not targeted towards the desired tissue. This can lead to undesired side effects, as normal cells are affected by the drugs as well. Therefore, new systems are now being developed which combine targeting functionalities with encapsulation of drug cargo. Protein nanocages are highly promising drug delivery platforms due to their perfectly defined structures, biocompatibility, biodegradability and low toxicity. A variety of protein nanocages have been modified and functionalized for these types of applications. In this review, we aim to give an overview of different types of modifications of protein-based nanocontainers for drug delivery applications.

Current applications of miniaturized chromatographic and electrophoretic techniques in drug analysis.

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Aturki, Zeineb; Rocco, Anna; Rocchi, Silvia; Fanali, Salvatore

2014-12-01

In the last decade, miniaturized separation techniques have become greatly popular in pharmaceutical analysis. Miniaturized separation methods are increasingly utilized in all processes of drug discovery as well as quality control of pharmaceutical preparation. The great advantages presented by the analytical miniaturized techniques, including high separation efficiency and resolution, rapid analysis and minimal consumption of reagents and samples, make them an attractive alternative to the conventional chromatographic methods for drug analysis. The purpose of this review is to give a general overview of the applicability of capillary electrophoresis (CE), capillary electrochromatography (CEC) and micro/capillary/nano-liquid chromatography (micro-LC/CLC/nano-LC) for the analysis of pharmaceutical formulations, active pharmaceutical ingredients (API), drug impurity testing, chiral drug separation, determination of drugs and metabolites in biological fluids. The results concerning the use of CEC, micro-LC, CLC, and nano-LC in the period 2009-2013, while for CE, those from 2012 up to the review draft are here summarized and some specific examples are discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

21 CFR 201.125 - Drugs for use in teaching, law enforcement, research, and analysis.

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2010-04-01

... 21 Food and Drugs 4 2010-04-01 2010-04-01 false Drugs for use in teaching, law enforcement, research, and analysis. 201.125 Section 201.125 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... § 201.125 Drugs for use in teaching, law enforcement, research, and analysis. A drug subject to § 201...

Current and emerging lipid-based systems for transdermal drug delivery.

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Singla, Sumeet K; Sachdeva, Vishal

2015-01-01

Developing a transdermal drug delivery system is a challenging task considering the selective permeability of the skin and the physicochemical properties the drug must possess to permeate through the skin. Lipid-based drug delivery systems have contributed a great deal in this direction in the last few decades, and thereby have helped to expand the range of therapeutic molecules that can be delivered through the skin in a safe and effective manner. Additionally, vesicular delivery systems such as nanoparticles and emulsions have also played important roles in providing alternative novel approaches for drug delivery. In this article, we will discuss some of the current and future lipid-based systems for transdermal drug delivery along with the associated challenges.

Accounting for the drug life cycle and future drug prices in cost-effectiveness analysis.

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Hoyle, Martin

2011-01-01

Economic evaluations of health technologies typically assume constant real drug prices and model only the cohort of patients currently eligible for treatment. It has recently been suggested that, in the UK, we should assume that real drug prices decrease at 4% per annum and, in New Zealand, that real drug prices decrease at 2% per annum and at patent expiry the drug price falls. It has also recently been suggested that we should model multiple future incident cohorts. In this article, the cost effectiveness of drugs is modelled based on these ideas. Algebraic expressions are developed to capture all costs and benefits over the entire life cycle of a new drug. The lifetime of a new drug in the UK, a key model parameter, is estimated as 33 years, based on the historical lifetime of drugs in England over the last 27 years. Under the proposed methodology, cost effectiveness is calculated for seven new drugs recently appraised in the UK. Cost effectiveness as assessed in the future is also estimated. Whilst the article is framed in mathematics, the findings and recommendations are also explained in non-mathematical language. The 'life-cycle correction factor' is introduced, which is used to convert estimates of cost effectiveness as traditionally calculated into estimates under the proposed methodology. Under the proposed methodology, all seven drugs appear far more cost effective in the UK than published. For example, the incremental cost-effectiveness ratio decreases by 46%, from £61, 900 to £33, 500 per QALY, for cinacalcet versus best supportive care for end-stage renal disease, and by 45%, from £31,100 to £17,000 per QALY, for imatinib versus interferon-α for chronic myeloid leukaemia. Assuming real drug prices decrease over time, the chance that a drug is publicly funded increases over time, and is greater when modelling multiple cohorts than with a single cohort. Using the methodology (compared with traditional methodology) all drugs in the UK and New

A dose-dependent relationship between exposure to a street-based drug scene and health-related harms among people who use injection drugs.

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Debeck, Kora; Wood, Evan; Zhang, Ruth; Buxton, Jane; Montaner, Julio; Kerr, Thomas

2011-08-01

While the community impacts of drug-related street disorder have been well described, lesser attention has been given to the potential health and social implications of drug scene exposure on street-involved people who use illicit drugs. Therefore, we sought to assess the impacts of exposure to a street-based drug scene among injection drug users (IDU) in a Canadian setting. Data were derived from a prospective cohort study known as the Vancouver Injection Drug Users Study. Four categories of drug scene exposure were defined based on the numbers of hours spent on the street each day. Three generalized estimating equation (GEE) logistic regression models were constructed to identify factors associated with varying levels of drug scene exposure (2-6, 6-15, over 15 hours) during the period of December 2005 to March 2009. Among our sample of 1,486 IDU, at baseline, a total of 314 (21%) fit the criteria for high drug scene exposure (>15 hours per day). In multivariate GEE analysis, factors significantly and independently associated with high exposure included: unstable housing (adjusted odds ratio [AOR] = 9.50; 95% confidence interval [CI], 6.36-14.20); daily crack use (AOR = 2.70; 95% CI, 2.07-3.52); encounters with police (AOR = 2.11; 95% CI, 1.62-2.75); and being a victim of violence (AOR = 1.49; 95 % CI, 1.14-1.95). Regular employment (AOR = 0.50; 95% CI, 0.38-0.65), and engagement with addiction treatment (AOR = 0.58; 95% CI, 0.45-0.75) were negatively associated with high exposure. Our findings indicate that drug scene exposure is associated with markers of vulnerability and higher intensity addiction. Intensity of drug scene exposure was associated with indicators of vulnerability to harm in a dose-dependent fashion. These findings highlight opportunities for policy interventions to address exposure to street disorder in the areas of employment, housing, and addiction treatment.

Microneedle-based drug and vaccine delivery via nanoporous microneedle arrays

OpenAIRE

Maaden, van der, Koen; Lüttge, R Regina; Vos, PJW; Bouwstra, Joke A; Kersten, Gideon FA; Ploemen, IHJ Ingmar

2015-01-01

In the literature, several types of microneedles have been extensively described. However, porous microneedle arrays only received minimal attention. Hence, only little is known about drug delivery via these microneedles. However, porous microneedle arrays may have potential for future microneedle-based drug and vaccine delivery and could be a valuable addition to the other microneedle-based drug delivery approaches. To gain more insight into porous microneedle technologies, the scientific an...

The impact of engagement in street-based income generation activities on stimulant drug use cessation among people who inject drugs.

Science.gov (United States)

Ti, Lianping; Richardson, Lindsey; DeBeck, Kora; Nguyen, Paul; Montaner, Julio; Wood, Evan; Kerr, Thomas

2014-08-01

Despite the growing prevalence of illicit stimulant drug use internationally, and the widespread involvement of people who inject drugs (IDU) within street-based drug markets, little is known about the impact of different types of street-based income generation activities on the cessation of stimulant use among IDU. Data were derived from an open prospective cohort of IDU in Vancouver, Canada. We used Kaplan-Meier methods and Cox proportional hazards regression to examine the effect of different types of street-based income generation activities (e.g., sex work, drug dealing, and scavenging) on time to cessation of stimulant use. Between December, 2005 and November, 2012, 887 IDU who use stimulant drugs (cocaine, crack cocaine, or crystal methamphetamine) were prospectively followed-up for a median duration of 47 months. In Kaplan-Meier analyses, compared to those who did not engage in street-based income generation activities, participants who reported sex work, drug dealing, scavenging, or more than one of these activities were significantly less likely to report stimulant drug use cessation (all pstreet-based income generation activity remained significantly associated with a slower time to stimulant drug cessation (all p<0.005). Our findings highlight the urgent need for strategies to address stimulant dependence, including novel pharmacotherapies. Also important, structural interventions, such as low-threshold employment opportunities, availability of supportive housing, legal reforms regarding drug use, and evidence-based approaches that reduce harm among IDU are urgently required. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Adverse drug reaction reports for cardiometabolic drugs from sub-Saharan Africa: a study in VigiBase.

Science.gov (United States)

Berhe, Derbew Fikadu; Juhlin, Kristina; Star, Kristina; Beyene, Kidanemariam G M; Dheda, Mukesh; Haaijer-Ruskamp, Flora M; Taxis, Katja; Mol, Peter G M

2015-06-01

Identifying key features in individual case safety reports (ICSR) of suspected adverse drug reactions (ADRs) with cardiometabolic drugs from sub-Saharan Africa (SSA) compared with reports from the rest of the world (RoW). Reports on suspected ADRs of cardiometabolic drugs (ATC: A10[antidiabetic], B01[antithrombotics] and C[cardiovascular]) were extracted from WHO Global database, VigiBase(®) (1992-2013). We used vigiPoint, a logarithmic odds ratios (log2 OR)-based method to study disproportional reporting between SSA and RoW. Case-defining features were considered relevant if the lower limit of the 99% CI > 0.5. In SSA, 3773 (9%) of reported ADRs were for cardiometabolic drugs, in RoW for 18%. Of these, 79% originated from South Africa and 81% were received after 2007. Most reports were for drugs acting on the renin-angiotensin system (36% SSA & 14% RoW). Compared with RoW, reports were more often sent for patients 18-44 years old (log2 OR 0.95 [99 CI 0.80; 1.09]) or with non-fatal outcome (log2 OR 1.16 [99 CI 1.10; 1.22]). Eight ADRs (cough, angioedema, lip swelling, face oedema, swollen tongue, throat irritation, drug ineffective and blood glucose abnormal) and seven drugs (enalapril, rosuvastatin, perindopril, vildagliptin, insulin glulisine, nifedipine and insulin lispro) were disproportionally more reported in SSA than in the RoW. 'In recent years, the number of adverse drug reactions (ADRs) reported in Sub-Saharan Africa (SSA) has sharply increased. The data showed the well-known population-based differential ADR profile of ACE inhibitors in the SSA population.' © 2015 John Wiley & Sons Ltd.

ACFIS: a web server for fragment-based drug discovery

Science.gov (United States)

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-01-01

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown ‘chemical space’ to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for ‘chemical space’, which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. PMID:27150808

A prediction model-based algorithm for computer-assisted database screening of adverse drug reactions in the Netherlands.

Science.gov (United States)

Scholl, Joep H G; van Hunsel, Florence P A M; Hak, Eelko; van Puijenbroek, Eugène P

2018-02-01

The statistical screening of pharmacovigilance databases containing spontaneously reported adverse drug reactions (ADRs) is mainly based on disproportionality analysis. The aim of this study was to improve the efficiency of full database screening using a prediction model-based approach. A logistic regression-based prediction model containing 5 candidate predictors was developed and internally validated using the Summary of Product Characteristics as the gold standard for the outcome. All drug-ADR associations, with the exception of those related to vaccines, with a minimum of 3 reports formed the training data for the model. Performance was based on the area under the receiver operating characteristic curve (AUC). Results were compared with the current method of database screening based on the number of previously analyzed associations. A total of 25 026 unique drug-ADR associations formed the training data for the model. The final model contained all 5 candidate predictors (number of reports, disproportionality, reports from healthcare professionals, reports from marketing authorization holders, Naranjo score). The AUC for the full model was 0.740 (95% CI; 0.734-0.747). The internal validity was good based on the calibration curve and bootstrapping analysis (AUC after bootstrapping = 0.739). Compared with the old method, the AUC increased from 0.649 to 0.740, and the proportion of potential signals increased by approximately 50% (from 12.3% to 19.4%). A prediction model-based approach can be a useful tool to create priority-based listings for signal detection in databases consisting of spontaneous ADRs. © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd.

Toxicological Analysis of Some Drugs of Abuse in Biological Samples

OpenAIRE

Anne Marie Ciobanu; Daniela Baconi; Cristian Bălălău; Carolina Negrei; Miriana Stan; Maria Bârcă

2015-01-01

Consumption of drugs of abuse is a scourge of modern world. Abuse, drug addiction and their consequences are one of the major current problems of European society because of the significant repercussions in individual, family, social and economic level. In this context, toxicological analysis of the drugs of abuse in biological samples is a useful tool for: diagnosis of drug addiction, checking an auto-response, mandatory screening in some treatment programs, identification of a substance ...

Drug utilization according to reason for prescribing: a pharmacoepidemiologic method based on an indication hierarchy

DEFF Research Database (Denmark)

Kildemoes, Helle Wallach; Hendriksen, Carsten; Morten, Andersen

2011-01-01

ABSTRACT Purpose To develop a pharmacoepidemiologic method for drug utilization analysis according to indication, gender, and age by means of register-based information. Statin utilization in 2005 was applied as an example. Methods Following the recommendations for statin therapy, we constructed ...

Drug May Help Prevent Resistance to Toxin-Based Leukemia Therapy

Science.gov (United States)

Adding the drug 5-AZA to moxetumomab pasudotox, a toxin-based cancer drug, may improve its efficacy in acute lymphoblastic leukemia (ALL). As this Cancer Currents blog post explains, in mice, both drugs were more effective than moxetumomab alone.

Analysis of factors associated with hiccups based on the Japanese Adverse Drug Event Report database.

Science.gov (United States)

Hosoya, Ryuichiro; Uesawa, Yoshihiro; Ishii-Nozawa, Reiko; Kagaya, Hajime

2017-01-01

Hiccups are occasionally experienced by most individuals. Although hiccups are not life-threatening, they may lead to a decline in quality of life. Previous studies showed that hiccups may occur as an adverse effect of certain medicines during chemotherapy. Furthermore, a male dominance in hiccups has been reported. However, due to the limited number of studies conducted on this phenomenon, debate still surrounds the few factors influencing hiccups. The present study aimed to investigate the influence of medicines and patient characteristics on hiccups using a large-sized adverse drug event report database and, specifically, the Japanese Adverse Drug Event Report (JADER) database. Cases of adverse effects associated with medications were extracted from JADER, and Fisher's exact test was performed to assess the presence or absence of hiccups for each medication. In a multivariate analysis, we conducted a multiple logistic regression analysis using medication and patient characteristic variables exhibiting significance. We also examined the role of dexamethasone in inducing hiccups during chemotherapy. Medicines associated with hiccups included dexamethasone, levofolinate, fluorouracil, oxaliplatin, carboplatin, and irinotecan. Patient characteristics associated with hiccups included a male gender and greater height. The combination of anti-cancer agent and dexamethasone use was noted in more than 95% of patients in the dexamethasone-use group. Hiccups also occurred in patients in the anti-cancer agent-use group who did not use dexamethasone. Most of the medications that induce hiccups are used in chemotherapy. The results of the present study suggest that it is possible to predict a high risk of hiccups using patient characteristics. We confirmed that dexamethasone was the drug that has the strongest influence on the induction of hiccups. However, the influence of anti-cancer agents on the induction of hiccups cannot be denied. We consider the results of the present

Residue analysis of veterinary drugs and growth-promoting agents

NARCIS (Netherlands)

Stolker, A.A.M.; Zuidema, T.; Nielen, M.W.F.

2007-01-01

Two major trends are observed in the analysis of veterinary drugs and growth-promoting agents. First is the selection of sample material for monitoring the use of registered veterinary drugs. Traditionally meat, kidney and liver were analyzed but, due to the food scandals in which meat was very

Using Statistics and Data Mining Approaches to Analyze Male Sexual Behaviors and Use of Erectile Dysfunction Drugs Based on Large Questionnaire Data.

Science.gov (United States)

Qiao, Zhi; Li, Xiang; Liu, Haifeng; Zhang, Lei; Cao, Junyang; Xie, Guotong; Qin, Nan; Jiang, Hui; Lin, Haocheng

2017-01-01

The prevalence of erectile dysfunction (ED) has been extensively studied worldwide. Erectile dysfunction drugs has shown great efficacy in preventing male erectile dysfunction. In order to help doctors know drug taken preference of patients and better prescribe, it is crucial to analyze who actually take erectile dysfunction drugs and the relation between sexual behaviors and drug use. Existing clinical studies usually used descriptive statistics and regression analysis based on small volume of data. In this paper, based on big volume of data (48,630 questionnaires), we use data mining approaches besides statistics and regression analysis to comprehensively analyze the relation between male sexual behaviors and use of erectile dysfunction drugs for unravelling the characteristic of patients who take erectile dysfunction drugs. We firstly analyze the impact of multiple sexual behavior factors on whether to use the erectile dysfunction drugs. Then, we explore to mine the Decision Rules for Stratification to discover patients who are more likely to take drugs. Based on the decision rules, the patients can be partitioned into four potential groups for use of erectile dysfunction: high potential group, intermediate potential-1 group, intermediate potential-2 group and low potential group. Experimental results show 1) the sexual behavior factors, erectile hardness and time length to prepare (how long to prepares for sexual behaviors ahead of time), have bigger impacts both in correlation analysis and potential drug taking patients discovering; 2) odds ratio between patients identified as low potential and high potential was 6.098 (95% confidence interval, 5.159-7.209) with statistically significant differences in taking drug potential detected between all potential groups.

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

Science.gov (United States)

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

iADRs: towards online adverse drug reaction analysis.

Science.gov (United States)

Lin, Wen-Yang; Li, He-Yi; Du, Jhih-Wei; Feng, Wen-Yu; Lo, Chiao-Feng; Soo, Von-Wun

2012-12-01

Adverse Drug Reaction (ADR) is one of the most important issues in the assessment of drug safety. In fact, many adverse drug reactions are not discovered during limited pre-marketing clinical trials; instead, they are only observed after long term post-marketing surveillance of drug usage. In light of this, the detection of adverse drug reactions, as early as possible, is an important topic of research for the pharmaceutical industry. Recently, large numbers of adverse events and the development of data mining technology have motivated the development of statistical and data mining methods for the detection of ADRs. These stand-alone methods, with no integration into knowledge discovery systems, are tedious and inconvenient for users and the processes for exploration are time-consuming. This paper proposes an interactive system platform for the detection of ADRs. By integrating an ADR data warehouse and innovative data mining techniques, the proposed system not only supports OLAP style multidimensional analysis of ADRs, but also allows the interactive discovery of associations between drugs and symptoms, called a drug-ADR association rule, which can be further developed using other factors of interest to the user, such as demographic information. The experiments indicate that interesting and valuable drug-ADR association rules can be efficiently mined.

Tenofovir-based regimens associated with less drug resistance in HIV-1-infected Nigerians failing first-line antiretroviral therapy.

Science.gov (United States)

Etiebet, Mary-Ann A; Shepherd, James; Nowak, Rebecca G; Charurat, Man; Chang, Harry; Ajayi, Samuel; Elegba, Olufunmilayo; Ndembi, Nicaise; Abimiku, Alashle; Carr, Jean K; Eyzaguirre, Lindsay M; Blattner, William A

2013-02-20

In resource-limited settings, HIV-1 drug resistance testing to guide antiretroviral therapy (ART) selection is unavailable. We retrospectively conducted genotypic analysis on archived samples from Nigerian patients who received targeted viral load testing to confirm treatment failure and report their drug resistance mutation patterns. Stored plasma from 349 adult patients on non-nucleoside reverse transcriptase inhibitor (NNRTI) regimens was assayed for HIV-1 RNA viral load, and samples with more than 1000 copies/ml were sequenced in the pol gene. Analysis for resistance mutations utilized the IAS-US 2011 Drug Resistance Mutation list. One hundred and seventy-five samples were genotyped; the majority of the subtypes were G (42.9%) and CRF02_AG (33.7%). Patients were on ART for a median of 27 months. 90% had the M184V/I mutation, 62% had at least one thymidine analog mutation, and 14% had the K65R mutation. 97% had an NNRTI resistance mutation and 47% had at least two etravirine-associated mutations. In multivariate analysis tenofovir-based regimens were less likely to have at least three nucleoside reverse transcriptase inhibitor (NRTI) mutations after adjusting for subtype, previous ART, CD4, and HIV viral load [P < 0.001, odds ratio (OR) 0.04]. 70% of patients on tenofovir-based regimens had at least two susceptible NRTIs to include in a second-line regimen compared with 40% on zidovudine-based regimens (P = 0.04, OR = 3.4). At recognition of treatment failure, patients on tenofovir-based first-line regimens had fewer NRTI drug-resistant mutations and more active NRTI drugs available for second-line regimens. These findings can inform strategies for ART regimen sequencing to optimize long-term HIV treatment outcomes in low-resource settings.

Inhalation of nanoparticle-based drug for lung cancer treatment: Advantages and challenges

Directory of Open Access Journals (Sweden)

Wing-Hin Lee

2015-12-01

Full Text Available Ever since the success of developing inhalable insulin, drug delivery via pulmonary administration has become an attractive route to treat chronic diseases. Pulmonary delivery system for nanotechnology is a relatively new concept especially when applicable to lung cancer therapy. Nano-based systems such as liposome, polymeric nanoparticles or micelles are strategically designed to enhance the therapeutic index of anti-cancer drugs through improvement of their bioavailability, stability and residency at targeted lung regions. Along with these benefits, nano-based systems also provide additional diagnostic advantages during lung cancer treatment, including imaging, screening and drug tracking. Nevertheless, delivery of nano-based drugs via pulmonary administration for lung cancer therapy is still in its infancy and numerous challenges are expected. Pharmacology, immunology, toxicology and large-scale manufacturing (stability and activity of drugs are some aspects in nanotechnology that should be taken into consideration for the development of inhalable nano-based chemotherapeutic drugs. This review will focus on the current inhalable nano-based drugs for lung cancer treatment.

Mesoporous Silica Molecular Sieve based Nanocarriers: Transpiring Drug Dissolution Research.

Science.gov (United States)

Pattnaik, Satyanarayan; Pathak, Kamla

2017-01-01

Improvement of oral bioavailability through enhancement of dissolution for poorly soluble drugs has been a very promising approach. Recently, mesoporous silica based molecular sieves have demonstrated excellent properties to enhance the dissolution velocity of poorly water-soluble drugs. Current research in this area is focused on investigating the factors influencing the drug release from these carriers, the kinetics of drug release and manufacturing approaches to scale-up production for commercial manufacture. This comprehensive review provides an overview of different methods adopted for synthesis of mesoporous materials, influence of processing factors on properties of these materials and drug loading methods. The drug release kinetics from mesoporous silica systems, the manufacturability and stability of these formulations are reviewed. Finally, the safety and biocompatibility issues related to these silica based materials are discussed. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A study on nanodiamond-based drug delivery system

International Nuclear Information System (INIS)

Li Jing; Zhang Xiaoyong; Zhu Ying; Li Wenxin; Huang Qing

2010-01-01

A multifunctional drug delivery system based on nanodiamonds (NDs) has been developed. FITC, HCPT and TF were absorbed on NDs successively to form the multifunctional complex. The NDs and ND complex samples were characterized by TEM, FR-IR and UV-V. The results indicated that this drug delivery system is a high loading system. Efficacy of the drug delivery system on Hela cell was evaluated with MTT assays and fluorescence microscopy. The results show that multifunction of the NDs complex include fluorescence, targeting and high efficacy. (authors)

Plasma vs heart tissue concentration in humans - literature data analysis of drugs distribution.

Science.gov (United States)

Tylutki, Zofia; Polak, Sebastian

2015-03-12

Little is known about the uptake of drugs into the human heart, although it is of great importance nowadays, when science desires to predict tissue level behavior rather than to measure it. Although the drug concentration in cardiac tissue seems a better predictor for physiological and electrophysiological changes than its level in plasma, knowledge of this value is very limited. Tissue to plasma partition coefficients (Kp) come to rescue since they characterize the distribution of a drug among tissues as being one of the input parameters in physiologically based pharmacokinetic (PBPK) models. The article reviews cardiac surgery and forensic medical studies to provide a reference for drug concentrations in human cardiac tissue. Firstly, the focus is on whether a drug penetrates into heart tissue at a therapeutic level; the provided values refer to antibiotics, antifungals and anticancer drugs. Drugs that directly affect cardiomyocyte electrophysiology are another group of interest. Measured levels of amiodarone, digoxin, perhexiline and verapamil in different sites in human cardiac tissue where the compounds might meet ion channels, gives an insight into how these more lipophilic drugs penetrate the heart. Much data are derived from postmortem studies and they provide insight to the cardiac distribution of more than 200 drugs. The analysis depicts potential problems in defining the active concentration location, what may indirectly suggest multiple mechanisms involved in the drug distribution within the heart. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Drugs & the Brain: Case-based Instruction for an Undergraduate Neuropharmacology Course.

Science.gov (United States)

Nagel, Anastasia; Nicholas, Andrea

2017-01-01

In order to transform a traditional large non-majors general education (GE) neurobiology lecture (Drugs & the Brain) into an active learning course, we developed a series of directed mini-cases targeting major drug classes. Humorous and captivating case-based situations were used to better engage and motivate students to solve problems related to neuropharmacology and physiology. Here we provide directed cases, questions and learning outcomes for our opiates mini-cases. In addition, we describe how case studies were incorporated into our course and assessed using peer review and online quizzing. An in-depth analysis of the overall course transformation on student exam performance, opinions and instructor evaluations can be found in the JUNE article Don't Believe the Gripe! Increasing Course Structure in a Large Non-majors Neuroscience Course.

Microneedle-based drug and vaccine delivery via nanoporous microneedle arrays.

Science.gov (United States)

van der Maaden, Koen; Luttge, Regina; Vos, Pieter Jan; Bouwstra, Joke; Kersten, Gideon; Ploemen, Ivo

2015-08-01

In the literature, several types of microneedles have been extensively described. However, porous microneedle arrays only received minimal attention. Hence, only little is known about drug delivery via these microneedles. However, porous microneedle arrays may have potential for future microneedle-based drug and vaccine delivery and could be a valuable addition to the other microneedle-based drug delivery approaches. To gain more insight into porous microneedle technologies, the scientific and patent literature is reviewed, and we focus on the possibilities and constraints of porous microneedle technologies for dermal drug delivery. Furthermore, we show preliminary data with commercially available porous microneedles and describe future directions in this field of research.

Drug-target interaction prediction from PSSM based evolutionary information.

Science.gov (United States)

Mousavian, Zaynab; Khakabimamaghani, Sahand; Kavousi, Kaveh; Masoudi-Nejad, Ali

2016-01-01

The labor-intensive and expensive experimental process of drug-target interaction prediction has motivated many researchers to focus on in silico prediction, which leads to the helpful information in supporting the experimental interaction data. Therefore, they have proposed several computational approaches for discovering new drug-target interactions. Several learning-based methods have been increasingly developed which can be categorized into two main groups: similarity-based and feature-based. In this paper, we firstly use the bi-gram features extracted from the Position Specific Scoring Matrix (PSSM) of proteins in predicting drug-target interactions. Our results demonstrate the high-confidence prediction ability of the Bigram-PSSM model in terms of several performance indicators specifically for enzymes and ion channels. Moreover, we investigate the impact of negative selection strategy on the performance of the prediction, which is not widely taken into account in the other relevant studies. This is important, as the number of non-interacting drug-target pairs are usually extremely large in comparison with the number of interacting ones in existing drug-target interaction data. An interesting observation is that different levels of performance reduction have been attained for four datasets when we change the sampling method from the random sampling to the balanced sampling. Copyright © 2015 Elsevier Inc. All rights reserved.

Drug loading to lipid-based cationic nanoparticles

International Nuclear Information System (INIS)

Cavalcanti, Leide P.; Konovalov, Oleg; Torriani, Iris L.; Haas, Heinrich

2005-01-01

Lipid-based cationic nanoparticles are a new promising option for tumor therapy, because they display enhanced binding and uptake at the neo-angiogenic endothelial cells, which a tumor needs for its nutrition and growth. By loading suitable cytotoxic compounds to the cationic carrier, the tumor endothelial and consequently also the tumor itself can be destroyed. For the development of such novel anti-tumor agents, the control of drug loading and drug release from the carrier matrix is essential. We have studied the incorporation of the hydrophobic anti-cancer agent Paclitaxel (PXL) into a variety of lipid matrices by X-Ray reflectivity measurements. Liposome suspensions from cationic and zwitterionic lipids, comprising different molar fractions of Paclitaxel, were deposited on planar glass substrates. After drying at controlled humidity, well ordered, oriented multilayer stacks were obtained, as proven by the presence of bilayer Bragg peaks to several orders in the reflectivity curves. The presence of the drug induced a decrease of the lipid bilayer spacing, and with an excess of drug, also Bragg peaks of drug crystals could be observed. From the results, insight into the solubility of Paclitaxel in the model membranes was obtained and a structural model of the organization of the drug in the membrane was derived. Results from subsequent pressure/area-isotherm and grazing incidence diffraction (GID) measurements performed with drug/lipid Langmuir monolayers were in accordance with these conjectures

Plant-based Rasayana drugs from Ayurveda.

Science.gov (United States)

Balasubramani, Subramani Paranthaman; Venkatasubramanian, Padma; Kukkupuni, Subrahmanya Kumar; Patwardhan, Bhushan

2011-02-01

Rasayana tantra is one of the eight specialties of Ayurveda. It is a specialized practice in the form of rejuvenative recipes, dietary regimen, special health promoting behaviour and drugs. Properly administered Rasayana can bestow the human being with several benefits like longevity, memory, intelligence, freedom from diseases, youthful age, excellence of luster, complexion and voice, optimum strength of physique and sense organs, respectability and brilliance. Various types of plant based Rasayana recipes are mentioned in Ayurveda. Review of the current literature available on Rasayanas indicates that anti-oxidant and immunomodulation are the most studied activities of the Rasayana drugs. Querying in Pubmed database on Rasayanas reveals that single plants as well as poly herbal formulations have been researched on. This article reviews the basics of Rasayana therapy and the published research on different Rasayana drugs for specific health conditions. It also provides the possible directions for future research.

Polymer based drug delivery systems for mycobacterial infections.

Science.gov (United States)

Pandey, Rajesh; Khuller, G K

2004-07-01

In the last decade, polymer based technologies have found wide biomedical applications. Polymers, whether synthetic (e.g. polylactide-co-glycolide or PLG) or natural (e.g. alginate, chitosan etc.), have the property of encapsulating a diverse range of molecules of biological interest and bear distinct therapeutic advantages such as controlled release of drugs, protection against the premature degradation of drugs and reduction in drug toxicity. These are important considerations in the long-duration treatment of chronic infectious diseases such as tuberculosis in which patient non-compliance is the major obstacle to successful chemotherapy. Antitubercular drugs, singly or in combination, have been encapsulated in polymers to provide controlled drug release and the system also offers the flexibility of selecting various routes of administration such as oral, subcutaneous and aerosol. The present review highlights the approaches towards the preparation of polymeric antitubercular drug delivery systems, emphasizing how the route of administration may influence drug bioavailability as well as the chemotherapeutic efficacy. In addition, the pros and cons of the various delivery systems are also discussed.

Potential applications for halloysite nanotubes based drug delivery systems

Science.gov (United States)

Sun, Lin

Drug delivery refers to approaches, formulations, technologies, and systems for transporting a drug in the body. The purpose is to enhance the drug efficacy and to reduce side reactions, which can significantly improve treatment outcomes. Halloysite is a naturally occurred alumino-silicate clay with a tubular structure. It is a biocompatible material with a big surface area which can be used for attachment of targeted molecules. Besides, loaded molecules can present a sustained release manner in solution. These properties make halloysite nanotubes (HNTs) a good option for drug delivery. In this study, a drug delivery system was built based on halloysite via three different fabrication methods: physical adsorption, vacuum loading and layer-by-layer coating. Methotrexate was used as the model drug. Factors that may affect performance in both drug loading and release were tested. Results showed that methotrexate could be incorporated within the HNTs system and released in a sustained manner. Layer-by-layer coating showed a better potential than the other two methods in both MTX loading and release. Besides, lower pH could greatly improve MTX loading and release while the increased number of polyelectrolytes bilayers had a limited impact. Osteosarcoma is the most common primary bone malignancy in children and adolescents. Postoperative recurrence and metastasis has become one of the leading causes for patient death after surgical remove of the tumor mass. A strategy could be a sustained release of chemotherapeutics directly at the primary tumor sites where recurrence would mostly occur. Then, this HNTs based system was tested with osteosarcoma cells in vitro to show the potential of delivering chemotherapeutics in the treatment of osteosarcoma. Methotrexate was incorporated within HNTs with a layer-bylayer coating technique, and drug coated HNTs were filled into nylon-6 which is a common material for surgical sutures in industry. Results showed that (1) methotrexate

Characterization of Nanodiamond-based anti-HIV drug Delivery to the Brain.

Science.gov (United States)

Roy, Upal; Drozd, Vadym; Durygin, Andriy; Rodriguez, Jesse; Barber, Paul; Atluri, Venkata; Liu, Xiaohua; Voss, Thomas G; Saxena, Surendra; Nair, Madhavan

2018-01-25

Human Immunodeficiency Virus Type 1 (HIV-1) remains one of the leading causes of death worldwide. Present combination antiretroviral therapy has substantially improved HIV-1 related pathology. However, delivery of therapeutic agents to the HIV reservoir organ like Central nervous system (CNS) remains a major challenge primarily due to the ineffective transmigration of drugs through Blood Brain Barrier (BBB). The recent advent of nanomedicine-based drug delivery has stimulated the development of innovative systems for drug delivery. In this regard, particular focus has been given to nanodiamond due to its natural biocompatibility and non-toxic nature-making it a more efficient drug carrier than other carbon-based materials. Considering its potential and importance, we have characterized unmodified and surface-modified (-COOH and -NH 2 ) nanodiamond for its capacity to load the anti-HIV-1 drug efavirenz and cytotoxicity, in vitro. Overall, our study has established that unmodified nanodiamond conjugated drug formulation has significantly higher drug loading capacity than surface-modified nanodiamond with minimum toxicity. Further, this nanodrug formulation was characterized by its drug dissolution profile, transmigration through the BBB, and its therapeutic efficacy. The present biological characterizations provide a foundation for further study of in-vivo pharmacokinetics and pharmacodynamics of nanodiamond-based anti-HIV drugs.

Advanced surface chemical analysis of continuously manufactured drug loaded composite pellets.

Science.gov (United States)

Hossain, Akter; Nandi, Uttom; Fule, Ritesh; Nokhodchi, Ali; Maniruzzaman, Mohammed

2017-04-15

The aim of the present study was to develop and characterise polymeric composite pellets by means of continuous melt extrusion techniques. Powder blends of a steroid hormone (SH) as a model drug and either ethyl cellulose (EC N10 and EC P7 grades) or hydroxypropyl methylcellulose (HPMC AS grade) as polymeric carrier were extruded using a Pharma 11mm twin screw extruder in a continuous mode of operation to manufacture extruded composite pellets of 1mm length. Molecular modelling study using commercial Gaussian 09 software outlined a possible drug-polymer interaction in the molecular level to develop solid dispersions of the drug in the pellets. Solid-state analysis conducted via a differential scanning calorimetry (DSC), hot stage microscopy (HSM) and X-ray powder diffraction (XRPD) analyses revealed the amorphous state of the drug in the polymer matrices. Surface analysis using SEM/energy dispersive X-ray (EDX) of the produced pellets arguably showed a homogenous distribution of the C and O atoms in the pellet matrices. Moreover, advanced chemical surface analysis conducted via atomic force microscopy (AFM) showed a homogenous phase system having the drug molecule dispersed onto the amorphous matrices while Raman mapping confirmed the homogenous single-phase drug distribution in the manufactured composite pellets. Such composite pellets are expected to deliver multidisciplinary applications in drug delivery and medical sciences by e.g. modifying drug solubility/dissolutions or stabilizing the unstable drug (e.g. hormone, protein) in the composite network. Copyright © 2016. Published by Elsevier Inc.

Nanotechnology-based combinational drug delivery: an emerging approach for cancer therapy.

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Parhi, Priyambada; Mohanty, Chandana; Sahoo, Sanjeeb Kumar

2012-09-01

Combination therapy for the treatment of cancer is becoming more popular because it generates synergistic anticancer effects, reduces individual drug-related toxicity and suppresses multi-drug resistance through different mechanisms of action. In recent years, nanotechnology-based combination drug delivery to tumor tissues has emerged as an effective strategy by overcoming many biological, biophysical and biomedical barriers that the body stages against successful delivery of anticancer drugs. The sustained, controlled and targeted delivery of chemotherapeutic drugs in a combination approach enhanced therapeutic anticancer effects with reduced drug-associated side effects. In this article, we have reviewed the scope of various nanotechnology-based combination drug delivery approaches and also summarized the current perspective and challenges facing the successful treatment of cancer. Copyright © 2012 Elsevier Ltd. All rights reserved.

C_1_8-attached membrane funnel-based spray ionization mass spectrometry for quantification of anti-diabetic drug from human plasma

International Nuclear Information System (INIS)

Li, Wan; Chen, Xiangfeng; Wong, Y.-L. Elaine; Hung, Y.-L. Winnie; Wang, Ze; Deng, Liulin; Dominic Chan, T.-W.

2016-01-01

In this work, sorbent-attached membrane funnel-based spray ionization mass spectrometry was explored for quantitative analysis of anti-diabetic drugs spiked in human plasma. C_1_8-attached membrane funnel was fabricated for in situ extraction and clean-up to alleviate matrix suppression effect in the ionization process. Repaglinide was used as a target analyte of anti-diabetic drugs. Under optimal working conditions, good linearity (R"2 > 0.99) was obtained in the concentration range of 1–100 ng mL"−"1. The method detection limit of target drugs spiked in the human plasma was around 0.30 ng mL"−"1. Through the application of an isotope-labeled internal standard, the signal fluctuation caused by residual background matrices was largely alleviated and the precision of measurement (RSD) was below 15%. The recovery of repaglinide for 5, 25, and 100 ng mL"−"1 of spiked human plasma matrixes ranged from 87% to 112%. The developed method was successfully applied to determine repaglinide in plasma volunteers who orally received a dose of drug association. Our results demonstrated that membrane funnel-based spray is a simple and sensitive method for rapid screening analysis of complex biological samples. - Highlights: • Sorbent attached membrane funnel based spray platform was used for drug determination in human plasma. • The matrix suppression effect of human plasma was largely eliminated. • The method was applied to determine repaglinide in plasma volunteers. • Membrane funnel-based spray is promising for analysis of biological samples.

Silent Synapse-Based Circuitry Remodeling in Drug Addiction.

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Dong, Yan

2016-05-01

Exposure to cocaine, and likely other drugs of abuse, generates α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor-silent glutamatergic synapses in the nucleus accumbens. These immature synaptic contacts evolve after drug withdrawal to redefine the neurocircuital properties. These results raise at least three critical questions: (1) what are the molecular and cellular mechanisms that mediate drug-induced generation of silent synapses; (2) how are neurocircuits remodeled upon generation and evolution of drug-generated silent synapses; and (3) what behavioral consequences are produced by silent synapse-based circuitry remodeling? This short review analyzes related experimental results, and extends them to some speculations. © The Author 2015. Published by Oxford University Press on behalf of CINP.

Traditional Chinese Medicine-Based Network Pharmacology Could Lead to New Multicompound Drug Discovery

Directory of Open Access Journals (Sweden)

Jian Li

2012-01-01

Full Text Available Current strategies for drug discovery have reached a bottleneck where the paradigm is generally “one gene, one drug, one disease.” However, using holistic and systemic views, network pharmacology may be the next paradigm in drug discovery. Based on network pharmacology, a combinational drug with two or more compounds could offer beneficial synergistic effects for complex diseases. Interestingly, traditional chinese medicine (TCM has been practicing holistic views for over 3,000 years, and its distinguished feature is using herbal formulas to treat diseases based on the unique pattern classification. Though TCM herbal formulas are acknowledged as a great source for drug discovery, no drug discovery strategies compatible with the multidimensional complexities of TCM herbal formulas have been developed. In this paper, we highlighted some novel paradigms in TCM-based network pharmacology and new drug discovery. A multiple compound drug can be discovered by merging herbal formula-based pharmacological networks with TCM pattern-based disease molecular networks. Herbal formulas would be a source for multiple compound drug candidates, and the TCM pattern in the disease would be an indication for a new drug.

Barriers to community-based drug dependence treatment: implications for police roles, collaborations and performance indicators

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Ma, Yi; Du, Chunhua; Cai, Thomas; Han, Qingfeng; Yuan, Huanhuan; Luo, Tingyan; Ren, Guoliang; Mburu, Gitau; Wang, Bangyuan; Golichenko, Olga; Zhang, Chaoxiong

2016-01-01

Introduction Worldwide, people who use drugs (PWUD) are among the populations at highest risk for HIV infection. In China, PWUD are primarily sentenced to compulsory detainment centres, in which access to healthcare, including HIV treatment and prevention services, is limited or non-existent. In 2008, China's 2008 Anti-Drug Law encouraged the development and use of community-based drug dependence rehabilitation, yet there is limited evidence evaluating the efficacy and challenges of this model in China. In this study, we explore these challenges and describe how cooperation between law enforcement and health departments can meet the needs of PWUD. Methods In 2015, we conducted semi-structured, in-depth interviews with all four staff members and 16 clients of the Ping An Centre No. 1 for community-based drug treatment, three local police officers and three officials from the local Centre for Disease Control. Interviews explored obstacles in implementing community-based drug dependence treatment and efforts to resolve these difficulties. Transcripts were coded and analyzed with qualitative data analysis software (MAXQDA 11). Results We identified three challenges to community-based drug treatment at the Ping An Centre No. 1: (1) suboptimal coordination among parties involved, (2) a divergence in attitudes towards PWUD and harm reduction between law enforcement and health officials and (3) conflicting performance targets for police and health officials that undermine the shared goal of treatment. We also identified the take-home methadone maintenance treatment model at the Ping An Centre No. 1 as an example of an early successful collaboration between the police, the health department and PWUD. Conclusions To overcome barriers to effective community-based drug treatment, we recommend aligning the goals of law enforcement and public health agencies towards health-based performance indicators. Furthermore, tensions between PWUD and police need to be addressed and trust

Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

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Bian, Yuemin; Xie, Xiang-Qun Sean

2018-04-09

Fragment-based drug design (FBDD) has become an effective methodology for drug development for decades. Successful applications of this strategy brought both opportunities and challenges to the field of Pharmaceutical Science. Recent progress in the computational fragment-based drug design provide an additional approach for future research in a time- and labor-efficient manner. Combining multiple in silico methodologies, computational FBDD possesses flexibilities on fragment library selection, protein model generation, and fragments/compounds docking mode prediction. These characteristics provide computational FBDD superiority in designing novel and potential compounds for a certain target. The purpose of this review is to discuss the latest advances, ranging from commonly used strategies to novel concepts and technologies in computational fragment-based drug design. Particularly, in this review, specifications and advantages are compared between experimental and computational FBDD, and additionally, limitations and future prospective are discussed and emphasized.

PIXE analysis of trace and other mineral elements in phytopharmaceutical drugs

International Nuclear Information System (INIS)

Preoteasa, E. A.; Harangus, Livia; Iordan, Andreea; Gugiu, M.

2002-01-01

Despite of ongoing progress in the biochemistry of phytopharmaceutical drugs, their mineral micro- and trace elements have not been studied in detail. These elements may have therapeutic or toxic activity which should be assessed by sensitive investigations. The latter can be done by multielemental analysis with nuclear and atomic methods. We previously found 28 elements in some Romanian plant drugs by nuclear activation analysis. The availability of this method is, however, limited by the access to a nuclear reactor. Particle-induced X-ray emission (PIXE) is an alternative method with high performances in biomedicine and requiring no sample preparation for drugs' studies. We applied PIXE in the qualitative analysis of three plant drugs - Liv52, Mentat, and Geriforte - used as invigorators, protectors and prophylactics in oxidative stress diseases. Measurements with 3 MeV protons at the 8.5 MV NIPNE-HH (Horia Hulubei National Institute for Physics and Nuclear Engineering) tandem accelerator, using a hyper-pure Ge detector and no additional absorber foil, evidenced unusually complex elemental compositions of drugs. Up to 31 elements with Z > 15 were found: P, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Br, Rb, Sr, Y, Zr, Cs, Ba, La, Ce, Pr, Nd, Sm, Eu, Hg, and As and/or Pb, from major to trace levels. The three drugs' qualitative composition were found to be rather similar. Relative concentrations were well evaluated with X-ray yields calculated for another kind of light element thick target. Drug's toxic elements - As and/or Pb, Hg, and possibly Ga - were all at trace levels, but their accumulation might be harmful. Some essential elements like K, Ca, Cr, Fe, Cu, Zn, Br, Rb, Sr can be biologically useful. X-ray yields improvement and other ways for PIXE quantitative analysis of the phytotherapeutic drugs are outlined. (authors)

Lifetime use of illicit drugs and associated factors among Brazilian schoolchildren, National Adolescent School-based Health Survey (PeNSE 2012).

Science.gov (United States)

Horta, Rogério Lessa; Horta, Bernardo Lessa; da Costa, Andre Wallace Nery; do Prado, Rogério Ruscitto; Oliveira-Campos, Maryane; Malta, Deborah Carvalho

2014-01-01

This study aimed at describing the prevalence of illicit drug use among 9th grade students in the morning period of public and private schools in Brazil, and assessing associated factors. The Brazilian survey PeNSE (National Adolescent School-based Health Survey) 2012 evaluated a representative sample of 9th grade students in the morning period, in Brazil and its five regions. The use of illicit drugs at least once in life was assessed for the most commonly used drugs, such as marijuana, cocaine, crack, solvent-based glue, general ether-based inhalants, ecstasy and oxy. Data were subjected to descriptive analysis, and Pearson's χ² test and logistic regression was used in the multivariate analysis. The use of illicit drugs at least once in life was reported by 7.3% (95%CI 5.3 - 9.4) of the respondents. Logistic regression was used for multivariate analysis and the evidences suggest that illicit drug use is associated to social conditions of greater consumption power, the use of alcohol and tobacco, behaviors related to socialization, such as having friends or sexual activity, and also the perception of loneliness, loose contact between school and parents and experiences of abuse in the family environment. The outcome was inversely associated with close contact with parents and parental supervision. In addition to the association with the processes of socialization and consumption, the influence of family and school is expressed in a particularly protective manner in different records of direct supervision and care.

ACFIS: a web server for fragment-based drug discovery.

Science.gov (United States)

Hao, Ge-Fei; Jiang, Wen; Ye, Yuan-Nong; Wu, Feng-Xu; Zhu, Xiao-Lei; Guo, Feng-Biao; Yang, Guang-Fu

2016-07-08

In order to foster innovation and improve the effectiveness of drug discovery, there is a considerable interest in exploring unknown 'chemical space' to identify new bioactive compounds with novel and diverse scaffolds. Hence, fragment-based drug discovery (FBDD) was developed rapidly due to its advanced expansive search for 'chemical space', which can lead to a higher hit rate and ligand efficiency (LE). However, computational screening of fragments is always hampered by the promiscuous binding model. In this study, we developed a new web server Auto Core Fragment in silico Screening (ACFIS). It includes three computational modules, PARA_GEN, CORE_GEN and CAND_GEN. ACFIS can generate core fragment structure from the active molecule using fragment deconstruction analysis and perform in silico screening by growing fragments to the junction of core fragment structure. An integrated energy calculation rapidly identifies which fragments fit the binding site of a protein. We constructed a simple interface to enable users to view top-ranking molecules in 2D and the binding mode in 3D for further experimental exploration. This makes the ACFIS a highly valuable tool for drug discovery. The ACFIS web server is free and open to all users at http://chemyang.ccnu.edu.cn/ccb/server/ACFIS/. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Mining drug-disease relationships as a complement to medical genetics-based drug repositioning: Where a recommendation system meets genome-wide association studies.

Science.gov (United States)

Wang, H; Gu, Q; Wei, J; Cao, Z; Liu, Q

2015-05-01

A novel recommendation-based drug repositioning strategy is presented to simultaneously determine novel drug indications and side effects in one integrated framework. This strategy provides a complementary method to medical genetics-based drug repositioning, which reduces the occurrence of false positives in medical genetics-based drug repositioning, resulting in a ranked list of new candidate indications and/or side effects with different confidence levels. Several new drug indications and side effects are reported with high prediction confidences. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Analysis of drug effects on neurotransmitter release

International Nuclear Information System (INIS)

Rowell, P.; Garner, A.

1986-01-01

The release of neurotransmitter is routinely studied in a superfusion system in which serial samples are collected and the effects of drugs or other treatments on the amount of material in the superfusate is determined. With frequent sampling interval, this procedure provides a mechanism for dynamically characterizing the release process itself. Using automated data collection in conjunction with polyexponential computer analysis, the equation which describes the release process in each experiment is determined. Analysis of the data during the nontreated phase of the experiment allows an internal control to be used for accurately assessing any changes in neurotransmitter release which may occur during a subsequent treatment phase. The use of internal controls greatly improves the signal to noise ratio and allows determinations of very low concentrations of drugs on small amounts of tissue to be made. In this presentation, the effects of 10 μM nicotine on 3 H-dopamine release in rat nucleus accumbens is described. The time course, potency and efficacy of the drug treatment is characterized using this system. Determinations of the exponential order of the release as well as the rate constants allow one to study the mechanism of the release process. A description of 3 H-dopamine release in normal as well as Ca ++ -free medium is presented

Drug safety data mining with a tree-based scan statistic.

Science.gov (United States)

Kulldorff, Martin; Dashevsky, Inna; Avery, Taliser R; Chan, Arnold K; Davis, Robert L; Graham, David; Platt, Richard; Andrade, Susan E; Boudreau, Denise; Gunter, Margaret J; Herrinton, Lisa J; Pawloski, Pamala A; Raebel, Marsha A; Roblin, Douglas; Brown, Jeffrey S

2013-05-01

In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright © 2013 John Wiley & Sons, Ltd.

Analysis of antiepileptic drugs in biological fluids by means of electrokinetic chromatography.

Science.gov (United States)

Pucci, Vincenzo; Raggi, Maria Augusta

2005-02-01

An overview of the electrokinetic chromatographic methods for the analysis of antiepileptic drug levels in biological samples is presented. In particular, micellar electrokinetic capillary chromatography is a very suitable method for the determination of these drugs, because it allows a rapid, selective, and accurate analysis. In addition to the electrokinetic chromatographic studies on the determination of antiepileptic drugs, some information regarding sample pretreatment will also be reported: this is a critical step when the analysis of biological fluids is concerned. The electrokinetic chromatographic methods for the determination of recent antiepileptic drugs (e.g., lamotrigine, levetiracetam) and classical anticonvulsants (e.g., carbamazepine, phenytoin, ethosuximide, valproic acid) will be discussed in depth, and their pharmacological profiles will be briefly described as well.

An adverse events potential costs analysis based on Drug Programs in Poland. Dermatology focus

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Szkultecka-Debek Monika

2014-09-01

Full Text Available The aim of the project, carried out within the Polish Society for Pharmacoeconomics (PTFE, was to estimate the potential costs of treatment of the side effects which (theoretically may occur as a result of treatments for the selected diseases. This paper deals solely with dermatology related events. Herein, several Drug Programs financed by the National Health Fund in Poland, in 2012, were analyzed. The adverse events were selected based on the Summary of Product Characteristics of the chosen products. We focused the project on those potential adverse events which were defined in SPC as frequent and very frequent. The results are presented according to their therapeutic areas, and in this paper, the focus is upon that which is related to dermatology. The events described as ‘very common’ had an incidence of ≥ 1/10, and that which is ‘common’ - ≥ 1/100, <1 /10. In order to identify the resources used, we, with the engagement of clinical experts, performed a survey. In our work, we employed only the total direct costs incurred by the public payer, based on valid individual cost data in February 2014. Moreover, we calculated the total spending from the public payer’s perspective, as well as the patient’s perspective, and the percentage of each component of the total cost in detail. The paper, thus, informs the reader of the estimated costs of treatment of side effects related to the dermatologic symptoms and reactions. Based on our work, we can state that the treatment of skin adverse drug reactions generates a significant cost - one incurred by both the public payer and the patient.

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

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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.

REVIEW: CHITOSAN BASED HYDROGEL POLYMERIC BEADS – AS DRUG DELIVERY SYSTEM

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Manjusha Rani

2010-11-01

Full Text Available Chitosan obtained by alkaline deacetylation of chitin is a non-toxic, biocompatible, and biodegradable natural polymer. Chitosan-based hydrogel polymeric beads have been extensively studied as micro- or nano-particulate carriers in the pharmaceutical and medical fields, where they have shown promise for drug delivery as a result of their controlled and sustained release properties, as well as biocompatibility with tissue and cells. To introduce desired properties and enlarge the scope of the potential applications of chitosan, graft copolymerization with natural or synthetic polymers on it has been carried out, and also, various chitosan derivatives have been utilized to form beads. The desired kinetics, duration, and rate of drug release up to therapeutical level from polymeric beads are limited by specific conditions such as beads material and their composition, bead preparation method, amount of drug loading, drug solubility, and drug polymer interaction. The present review summarizes most of the available reports about compositional and structural effects of chitosan-based hydrogel polymeric beads on swelling, drug loading, and releasing properties. From the studies reviewed it is concluded that chitosan-based hydrogel polymeric beads are promising drug delivery systems.

The analysis of a trace amount of elements in crude drugs

International Nuclear Information System (INIS)

Wakayama, I.; Akagawa, J.; Yase, Y.; Yoshida, S.; Sasajima, Kazuhisa

2001-01-01

The concentrations and the pharmacological actions of iron and zinc in nearly 30 kinds of crude drugs of Chinese medicine are studied using the neutron activation analysis, quantitatively. The quantitative analytical results are also compared with the semi-quantitative analytical results of iron and zinc obtained by particle induced X-ray emission spectroscopy. The crude drugs with higher iron concentration were almost drugs for the mentality. The crude drugs with highest zinc concentration were also the drugs for the mentality. (H. Katsuta)

Rhamnogalacturonan-I based microcapsules for targeted drug release

DEFF Research Database (Denmark)

Svagan, Anna J.; Kusic, Anja; De Gobba, Cristian

2016-01-01

Drug targeting to the colon via the oral administration route for local treatment of e.g. inflammatory bowel disease and colonic cancer has several advantages such as needle-free administration and low infection risk. A new source for delivery is plant-polysaccharide based delivery platforms...... such as Rhamnogalacturonan-I (RG-I). In the gastro-intestinal tract the RG-I is only degraded by the action of the colonic microflora. For assessment of potential drug delivery properties, RG-I based microcapsules (~1 μm in diameter) were prepared by an interfacial poly-addition reaction. The cross-linked capsules were...

Knowledge Integration and Use-Case Analysis for a Customized Drug-Drug Interaction CDS Service

Science.gov (United States)

Kam, Hye Jin; Park, Man Young; Kim, Woojae; Yoon, Duk Yong; Ahn, Eun Kyoung; Park, Rae Woong

Clinical decision support systems (CDSSs) are thought to reduce adverse drug events (ADEs) by monitoring drug-drug interactions(DDIs). However, clinically improper or excessive alerts can result in high alert overrides. A tailored CDS service, which is appropriate for clinicians and their ordering situations, is required to increase alert acceptance. In this study, we conducted a 12-week pilot project adopting a tailed CDSS at an emergency department. The new CDSS was conducted via a stepwise integration of additional new rules. The alert status with changes in acceptance rate was analyzed. The most frequent DDI alerts were related to prescriptions of anti-inflammatory drugs. The percentages of alert overrides for each stage were 98.0%, 96.0%, 96.9%, and 98.1%, respectively. 91.5% of overridden alerts were related to discharge medications. To reduce the potential hazards of ADEs, the development of an effective customized DDI CDSS is required, via in-depth analysis on alert patterns and overridden reasons.

Advances in fragment-based drug discovery platforms.

Science.gov (United States)

Orita, Masaya; Warizaya, Masaichi; Amano, Yasushi; Ohno, Kazuki; Niimi, Tatsuya

2009-11-01

Fragment-based drug discovery (FBDD) has been established as a powerful alternative and complement to traditional high-throughput screening techniques for identifying drug leads. At present, this technique is widely used among academic groups as well as small biotech and large pharmaceutical companies. In recent years, > 10 new compounds developed with FBDD have entered clinical development, and more and more attention in the drug discovery field is being focused on this technique. Under the FBDD approach, a fragment library of relatively small compounds (molecular mass = 100 - 300 Da) is screened by various methods and the identified fragment hits which normally weakly bind to the target are used as starting points to generate more potent drug leads. Because FBDD is still a relatively new drug discovery technology, further developments and optimizations in screening platforms and fragment exploitation can be expected. This review summarizes recent advances in FBDD platforms and discusses the factors important for the successful application of this technique. Under the FBDD approach, both identifying the starting fragment hit to be developed and generating the drug lead from that starting fragment hit are important. Integration of various techniques, such as computational technology, X-ray crystallography, NMR, surface plasmon resonance, isothermal titration calorimetry, mass spectrometry and high-concentration screening, must be applied in a situation-appropriate manner.

Automated tool for virtual screening and pharmacology-based pathway prediction and analysis

Directory of Open Access Journals (Sweden)

Sugandh Kumar

2017-10-01

Full Text Available The virtual screening is an effective tool for the lead identification in drug discovery. However, there are limited numbers of crystal structures available as compared to the number of biological sequences which makes (Structure Based Drug Discovery SBDD a difficult choice. The current tool is an attempt to automate the protein structure modelling and automatic virtual screening followed by pharmacology-based prediction and analysis. Starting from sequence(s, this tool automates protein structure modelling, binding site identification, automated docking, ligand preparation, post docking analysis and identification of hits in the biological pathways that can be modulated by a group of ligands. This automation helps in the characterization of ligands selectivity and action of ligands on a complex biological molecular network as well as on individual receptor. The judicial combination of the ligands binding different receptors can be used to inhibit selective biological pathways in a disease. This tool also allows the user to systemically investigate network-dependent effects of a drug or drug candidate.

A meta-analysis of Drug resistant Tuberculosis in Sub-Saharan Africa

African Journals Online (AJOL)

Background: In Sub-Saharan Africa, the fight against tuberculosis (TB) has encountered a great challenge because of the emergence of drug resistant TB strains and the high prevalence of HIV infection. The aim of this meta-analysis was to determine the association of drug-resistant TB with anti-TB drug treatment history ...

C{sub 18}-attached membrane funnel-based spray ionization mass spectrometry for quantification of anti-diabetic drug from human plasma

Energy Technology Data Exchange (ETDEWEB)

Li, Wan [Department of Chemistry, The Chinese University of Hong Kong, Hong Kong Special Administrative Region (Hong Kong); Chen, Xiangfeng, E-mail: xiangfchensdas@163.com [Department of Chemistry, The Chinese University of Hong Kong, Hong Kong Special Administrative Region (Hong Kong); Shandong Analysis and Test Centre, Shandong Academy of Sciences, Jinan, Shandong (China); Wong, Y.-L. Elaine; Hung, Y.-L. Winnie; Wang, Ze; Deng, Liulin [Department of Chemistry, The Chinese University of Hong Kong, Hong Kong Special Administrative Region (Hong Kong); Dominic Chan, T.-W., E-mail: twdchan@cuhk.edu.hk [Department of Chemistry, The Chinese University of Hong Kong, Hong Kong Special Administrative Region (Hong Kong)

2016-08-24

In this work, sorbent-attached membrane funnel-based spray ionization mass spectrometry was explored for quantitative analysis of anti-diabetic drugs spiked in human plasma. C{sub 18}-attached membrane funnel was fabricated for in situ extraction and clean-up to alleviate matrix suppression effect in the ionization process. Repaglinide was used as a target analyte of anti-diabetic drugs. Under optimal working conditions, good linearity (R{sup 2} > 0.99) was obtained in the concentration range of 1–100 ng mL{sup −1}. The method detection limit of target drugs spiked in the human plasma was around 0.30 ng mL{sup −1}. Through the application of an isotope-labeled internal standard, the signal fluctuation caused by residual background matrices was largely alleviated and the precision of measurement (RSD) was below 15%. The recovery of repaglinide for 5, 25, and 100 ng mL{sup −1} of spiked human plasma matrixes ranged from 87% to 112%. The developed method was successfully applied to determine repaglinide in plasma volunteers who orally received a dose of drug association. Our results demonstrated that membrane funnel-based spray is a simple and sensitive method for rapid screening analysis of complex biological samples. - Highlights: • Sorbent attached membrane funnel based spray platform was used for drug determination in human plasma. • The matrix suppression effect of human plasma was largely eliminated. • The method was applied to determine repaglinide in plasma volunteers. • Membrane funnel-based spray is promising for analysis of biological samples.

Evaluation of rational drug use based on World Health Organization core drug use indicators in selected public hospitals of eastern Ethiopia: a cross sectional study.

Science.gov (United States)

Sisay, Mekonnen; Mengistu, Getnet; Molla, Bereket; Amare, Firehiwot; Gabriel, Tesfaye

2017-02-23

Despite the complexity of drug use, a number of indicators have been developed, standardized and evaluated by the World Health Organization (WHO). These indicators are grouped in to three categories namely: prescribing indicators, patient care indicators and facility indicators. The study was aimed to evaluate rational drug use based on WHO-core drug use indicators in Dilchora referral hospital, Dire Dawa; Hiwot Fana specialized university hospital, Harar and Karamara general hospital, Jigjiga, eastern Ethiopia. Hospital based quantitative cross sectional study design was employed to evaluate rational drug use based on WHO core drug use indicators in selected hospitals. Systematic random sampling for prescribing indicators and convenient sampling for patient care indicators was employed. Taking WHO recommendations in to account, a total of 1,500 prescription papers (500 from each hospitals) were investigated. In each hospital, 200 outpatient attendants and 30 key essential drugs were also selected using the WHO recommendation. Data were collected using retrospective and prospective structured observational check list. Data were entered to EPI Data Version 3.1, exported and analyzed using SPSS version 16.0. Besides, the data were evaluated as per the WHO guidelines. Statistical significance was determined by one way analysis of variance (ANOVA) for some variables. P-value of less than 0.05 was considered statistically significant. Finally, tabular presentation was used to present the data. Mean, 2.34 (±1.08) drugs were prescribed in the selected hospitals. Prescriptions containing antibiotics and that of injectables were 57.87 and 10.9% respectively. The average consultation and dispensing time were 276.5 s and 61.12 s respectively. Besides, 75.77% of the prescribed drugs were actually dispensed. Only 3.3% of prescriptions were adequately labeled and 75.7% patients know about the dosage of the prescription. Not more than, 20(66.7%) key drugs were available in

Alignment-independent comparison of binding sites based on DrugScore potential fields encoded by 3D Zernike descriptors.

Science.gov (United States)

Nisius, Britta; Gohlke, Holger

2012-09-24

Analyzing protein binding sites provides detailed insights into the biological processes proteins are involved in, e.g., into drug-target interactions, and so is of crucial importance in drug discovery. Herein, we present novel alignment-independent binding site descriptors based on DrugScore potential fields. The potential fields are transformed to a set of information-rich descriptors using a series expansion in 3D Zernike polynomials. The resulting Zernike descriptors show a promising performance in detecting similarities among proteins with low pairwise sequence identities that bind identical ligands, as well as within subfamilies of one target class. Furthermore, the Zernike descriptors are robust against structural variations among protein binding sites. Finally, the Zernike descriptors show a high data compression power, and computing similarities between binding sites based on these descriptors is highly efficient. Consequently, the Zernike descriptors are a useful tool for computational binding site analysis, e.g., to predict the function of novel proteins, off-targets for drug candidates, or novel targets for known drugs.

Opportunities for Web-based Drug Repositioning: Searching for Potential Antihypertensive Agents with Hypotension Adverse Events.

Science.gov (United States)

Wang, Kejian; Wan, Mei; Wang, Rui-Sheng; Weng, Zuquan

2016-04-01

Drug repositioning refers to the process of developing new indications for existing drugs. As a phenotypic indicator of drug response in humans, clinical side effects may provide straightforward signals and unique opportunities for drug repositioning. We aimed to identify drugs frequently associated with hypotension adverse reactions (ie, the opposite condition of hypertension), which could be potential candidates as antihypertensive agents. We systematically searched the electronic records of the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) through the openFDA platform to assess the association between hypotension incidence and antihypertensive therapeutic effect regarding a list of 683 drugs. Statistical analysis of FAERS data demonstrated that those drugs frequently co-occurring with hypotension events were more likely to have antihypertensive activity. Ranked by the statistical significance of frequent hypotension reporting, the well-known antihypertensive drugs were effectively distinguished from others (with an area under the receiver operating characteristic curve > 0.80 and a normalized discounted cumulative gain of 0.77). In addition, we found a series of antihypertensive agents (particularly drugs originally developed for treating nervous system diseases) among the drugs with top significant reporting, suggesting the good potential of Web-based and data-driven drug repositioning. We found several candidate agents among the hypotension-related drugs on our list that may be redirected for lowering blood pressure. More important, we showed that a pharmacovigilance system could alternatively be used to identify antihypertensive agents and sustainably create opportunities for drug repositioning.

Qualitative PIXE analysis of mineral elements in some phytopharmaceutic drugs

International Nuclear Information System (INIS)

Preoteasa, E.A.; Harangus, Livia; Gugiu, M; Iordan, Andreea; Ciortea, C.

2002-01-01

A large number of phytopharmaceutic drugs are being developed, due to positive effects in various diseases and to high tolerance by the organism. While their medicinally active compounds have been identified, little attention has been paid to their mineral micro- and trace elements. The mineral elements in the drug may have therapeutic or toxic effects which should be properly assessed. Nuclear and atomic methods allow sensitive multielement detection and we previously performed nuclear activation analysis of some Romanian drugs made by plants. Despite this method's high sensitivity, its use is limited by the availability of a nuclear reactor. Particle-induced X-ray emission (PIXE) provides an alternative, and here we examined its potential for the analysis of mineral elements in three commercial phytopharmaceutical preparations, namely, Liv52, Mentat, and Geriforte. The PIXE measurements were performed with 3 MeV protons at the 8.5 MV NIPNE-HH tandem accelerator, using a hyper pure Ge detector, normally oriented and connected to a multichannel analyzer and to a computer; the drug pills were fixed at 45 angle with respect to the beam. In all drugs PIXE detected mineral elements with Z > 16 down to trace levels. Major elements included K, Ca, Fe, Cu, and Zn, and minor/trace amounts of S, Cl, Ti, Cr, Mn, Ni, Ga, Br, Rb, Sr, Hg, and As/Pb were detected. Some differences were seen between the three drugs. Although at trace levels Ga, As, Hg and Pb are not toxic, one should consider that their accumulation might be harmful and caution seems recommendable on long-term cure. Most of the other elements are known to exert a positive biological role, and both in major and trace levels they may contribute to the therapeutic action. Thus PIXE analysis of mineral elements in phytopharmaceutic drugs, even qualitative, is useful for evaluating the benefits and risks in the therapy. (authors)

Large-scale exploration and analysis of drug combinations.

Science.gov (United States)

Li, Peng; Huang, Chao; Fu, Yingxue; Wang, Jinan; Wu, Ziyin; Ru, Jinlong; Zheng, Chunli; Guo, Zihu; Chen, Xuetong; Zhou, Wei; Zhang, Wenjuan; Li, Yan; Chen, Jianxin; Lu, Aiping; Wang, Yonghua

2015-06-15

Drug combinations are a promising strategy for combating complex diseases by improving the efficacy and reducing corresponding side effects. Currently, a widely studied problem in pharmacology is to predict effective drug combinations, either through empirically screening in clinic or pure experimental trials. However, the large-scale prediction of drug combination by a systems method is rarely considered. We report a systems pharmacology framework to predict drug combinations (PreDCs) on a computational model, termed probability ensemble approach (PEA), for analysis of both the efficacy and adverse effects of drug combinations. First, a Bayesian network integrating with a similarity algorithm is developed to model the combinations from drug molecular and pharmacological phenotypes, and the predictions are then assessed with both clinical efficacy and adverse effects. It is illustrated that PEA can predict the combination efficacy of drugs spanning different therapeutic classes with high specificity and sensitivity (AUC = 0.90), which was further validated by independent data or new experimental assays. PEA also evaluates the adverse effects (AUC = 0.95) quantitatively and detects the therapeutic indications for drug combinations. Finally, the PreDC database includes 1571 known and 3269 predicted optimal combinations as well as their potential side effects and therapeutic indications. The PreDC database is available at http://sm.nwsuaf.edu.cn/lsp/predc.php. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Drug Revolving Fund-Based

African Journals Online (AJOL)

Background: The Drug Revolving Fund (DRF) was instituted in 1996 in Oyo State to ensure sustainable drug availability at primary health care level with a seed stock of drugs supplied by the Petroleum Trust Fund. This was discontinued in 1999 and replaced in January 2000, with free health service, which involves ...

Blood alcohol analysis alone versus comprehensive toxicological analysis - Systematic investigation of missed co-ingested other drugs in suspected alcohol-impaired drivers.

Science.gov (United States)

Steuer, Andrea E; Eisenbeiss, Lisa; Kraemer, Thomas

2016-10-01

Driving under the influence of alcohol and/or drugs (DUID) is a safety issue of increasing public concern. When a police officer has reasonable grounds to classify a driver as impaired, he may arrange for a blood sample to be taken. In many countries, alcohol analysis only is ordered if impairment is suspected to be exclusively due to alcohol while comprehensive toxicological screening will be performed if additional suspicion for other illegal drugs of abuse (DoA) or medicinal drugs is on hand. The aim of the present study was firstly to evaluate whether signs of impairment can be differentiated to be caused by alcohol alone or a combination of alcohol and other driving-impairing drugs and secondly to which extent additional drugs are missed in suspected alcohol-impaired drivers. A total of 293 DUID cases (negative n=41; alcohol positive only, n=131; alcohol+active drug positive, n=121) analyzed in 2015 in the Canton of Zurich were evaluated for their documented impairment symptoms by translating these into a severity score and comparing them applying principle component analysis (PCA). Additional 500 cases suspected for alcohol-impaired driving only were reanalyzed using comprehensive LC-MS/MS screening methods covering about 1500 compounds. Drugs detected were classified for severity of driving impairment using the classification system established in the DRUID study of the European Commission. As partly expected from the pharmacological and toxicological point of view, PCA analysis revealed no differences between signs of impairment caused by alcohol alone and those caused by alcohol plus at least one active drug. Breaking it down to different blood alcohol concentration ranges, only between 0.3 and 0.5g/kg trends could be observed in terms of more severe impairment for combined alcohol and drug intake. In the 500 blood samples retrospectively analyzed in this study, a total of 330 additional drugs could be detected; in some cases up to 9 co-ingested ones. In

Pharmaceutical companies and their drugs on social media: a content analysis of drug information on popular social media sites.

Science.gov (United States)

Tyrawski, Jennifer; DeAndrea, David C

2015-06-01

Many concerns have been raised about pharmaceutical companies marketing their drugs directly to consumers on social media. This form of direct-to-consumer advertising (DTCA) can be interactive and, because it is largely unmonitored, the benefits of pharmaceutical treatment could easily be overemphasized compared to the risks. Additionally, nonexpert consumers can share their own drug product testimonials on social media and illegal online pharmacies can market their services on popular social media sites. There is great potential for the public to be exposed to misleading or dangerous information about pharmaceutical drugs on social media. Our central aim was to examine how pharmaceutical companies use social media to interact with the general public and market their drugs. We also sought to analyze the nature of information that appears in search results for widely used pharmaceutical drugs in the United States on Facebook, Twitter, and YouTube with a particular emphasis on the presence of illegal pharmacies. Content analyses were performed on (1) social media content on the Facebook, Twitter, and YouTube accounts of the top 15 pharmaceutical companies in the world and (2) the content that appears when searching on Facebook, Twitter, and YouTube for the top 20 pharmaceutical drugs purchased in the United States. Notably, for the company-specific analysis, we examined the presence of information similar to various forms of DTCA, the audience reach of company postings, and the quantity and quality of company-consumer interaction. For the drug-specific analysis, we documented the presence of illegal pharmacies, personal testimonials, and drug efficacy claims. From the company-specific analysis, we found information similar to help-seeking DTCA in 40.7% (301/740) of pharmaceutical companies' social media posts. Drug product claims were present in only 1.6% (12/740) of posts. Overall, there was a substantial amount of consumers who interacted with pharmaceutical

Pharmaceutical Companies and Their Drugs on Social Media: A Content Analysis of Drug Information on Popular Social Media Sites

Science.gov (United States)

2015-01-01

Background Many concerns have been raised about pharmaceutical companies marketing their drugs directly to consumers on social media. This form of direct-to-consumer advertising (DTCA) can be interactive and, because it is largely unmonitored, the benefits of pharmaceutical treatment could easily be overemphasized compared to the risks. Additionally, nonexpert consumers can share their own drug product testimonials on social media and illegal online pharmacies can market their services on popular social media sites. There is great potential for the public to be exposed to misleading or dangerous information about pharmaceutical drugs on social media. Objective Our central aim was to examine how pharmaceutical companies use social media to interact with the general public and market their drugs. We also sought to analyze the nature of information that appears in search results for widely used pharmaceutical drugs in the United States on Facebook, Twitter, and YouTube with a particular emphasis on the presence of illegal pharmacies. Methods Content analyses were performed on (1) social media content on the Facebook, Twitter, and YouTube accounts of the top 15 pharmaceutical companies in the world and (2) the content that appears when searching on Facebook, Twitter, and YouTube for the top 20 pharmaceutical drugs purchased in the United States. Notably, for the company-specific analysis, we examined the presence of information similar to various forms of DTCA, the audience reach of company postings, and the quantity and quality of company-consumer interaction. For the drug-specific analysis, we documented the presence of illegal pharmacies, personal testimonials, and drug efficacy claims. Results From the company-specific analysis, we found information similar to help-seeking DTCA in 40.7% (301/740) of pharmaceutical companies’ social media posts. Drug product claims were present in only 1.6% (12/740) of posts. Overall, there was a substantial amount of consumers

A MULTIMODAL DISCOURSE ANALYSIS OF SELECTED ADVERTISEMENT OF MALARIA DRUGS

OpenAIRE

Ayodeji Olowu; Susan Olajoke Akinkurolere

2015-01-01

This study identified and analyzed the visual and linguistic components associated with the selected advertisement of malaria drugs. This was with a view to describing the essential communication devices the advertisers of such drugs have employed. Data for the study were drawn from both primary and secondary sources. The primary source for the study comprised 4 purposively selected posters, stickers and drugs literature advertisement on malaria. Analysis of the data followed the framework of...

Data Decision and Drug Therapy Based on Non-Small Cell Lung Cancer in a Big Data Medical System in Developing Countries

Directory of Open Access Journals (Sweden)

Jia Wu

2018-05-01

Full Text Available In many developing or underdeveloped countries, limited medical resources and large populations may affect the survival of mankind. The research for the medical information system and recommendation of effective treatment methods may improve diagnosis and drug therapy for patients in developing or underdeveloped countries. In this study, we built a system model for the drug therapy, relevance parameter analysis, and data decision making in non-small cell lung cancer. Based on the probability analysis and status decision, the optimized therapeutic schedule can be calculated and selected, and then effective drug therapy methods can be determined to improve relevance parameters. Statistical analysis of clinical data proves that the model of the probability analysis and decision making can provide fast and accurate clinical data.

Synthesis and structural characterization of some trisulfide analoges of thiouracil-based antithyroid drugs

Science.gov (United States)

Bhabak, Krishna P.; Bhowmick, Debasish

2012-08-01

Thiourea-based antithyroid drugs are effectively used for the treatment of hyperthyroidism. In this paper, we describe the synthesis of new trisulfides (11-12) from the commonly used thiourea-based antithyroid drugs such as 6-n-propyl-2-thiouracil (PTU) and 6-methyl-2-thiouracil (MTU) in the reaction with I2/KI system. Structural analysis by single crystal X-ray diffraction studies revealed the stabilization of trisulfides by a lactam-lactim tautomerism facilitating effective intramolecular as well as intermolecular non-covalent interactions. Although the structures of both trisulfides were found to be quite similar, a notable difference in the intermolecular interactions was observed between compounds 11 and 12 leading to different structural patterns. Structural stabilization of these trisulfides by tautomerism followed by intramolecular as well as intermolecular H-bonds makes these molecules as perfect examples in molecular recognition with self-complementary donor and acceptor units within a single molecule.

Extracting drug mechanism and pharmacodynamic information from clinical electroencephalographic data using generalised semi-linear canonical correlation analysis

International Nuclear Information System (INIS)

Brain, P; Strimenopoulou, F; Ivarsson, M; Wilson, F J; Diukova, A; Wise, R G; Berry, E; Jolly, A; Hall, J E

2014-01-01

Conventional analysis of clinical resting electroencephalography (EEG) recordings typically involves assessment of spectral power in pre-defined frequency bands at specific electrodes. EEG is a potentially useful technique in drug development for measuring the pharmacodynamic (PD) effects of a centrally acting compound and hence to assess the likelihood of success of a novel drug based on pharmacokinetic–pharmacodynamic (PK–PD) principles. However, the need to define the electrodes and spectral bands to be analysed a priori is limiting where the nature of the drug-induced EEG effects is initially not known. We describe the extension to human EEG data of a generalised semi-linear canonical correlation analysis (GSLCCA), developed for small animal data. GSLCCA uses data from the whole spectrum, the entire recording duration and multiple electrodes. It provides interpretable information on the mechanism of drug action and a PD measure suitable for use in PK–PD modelling. Data from a study with low (analgesic) doses of the μ-opioid agonist, remifentanil, in 12 healthy subjects were analysed using conventional spectral edge analysis and GSLCCA. At this low dose, the conventional analysis was unsuccessful but plausible results consistent with previous observations were obtained using GSLCCA, confirming that GSLCCA can be successfully applied to clinical EEG data. (paper)

Human cytosolic glutathione-S-transferases: quantitative analysis of expression, comparative analysis of structures and inhibition strategies of isozymes involved in drug resistance.

Science.gov (United States)

Mohana, Krishnamoorthy; Achary, Anant

2017-08-01

Glutathione-S-transferase (GST) inhibition is a strategy to overcome drug resistance. Several isoforms of human GSTs are present and they are expressed in almost all the organs. Specific expression levels of GSTs in various organs are collected from the human transcriptome data and analysis of the organ-specific expression of GST isoforms is carried out. The variations in the level of expressions of GST isoforms are statistically significant. The GST expression differs in diseased conditions as reported by many investigators and some of the isoforms of GSTs are disease markers or drug targets. Structure analysis of various isoforms is carried out and literature mining has been performed to identify the differences in the active sites of the GSTs. The xenobiotic binding H site is classified into H1, H2, and H3 and the differences in the amino acid composition, the hydrophobicity and other structural features of H site of GSTs are discussed. The existing inhibition strategies are compared. The advent of rational drug design, mechanism-based inhibition strategies, availability of high-throughput screening, target specific, and selective inhibition of GST isoforms involved in drug resistance could be achieved for the reversal of drug resistance and aid in the treatment of diseases.

3-D Image Analysis of Fluorescent Drug Binding

Directory of Open Access Journals (Sweden)

M. Raquel Miquel

2005-01-01

Full Text Available Fluorescent ligands provide the means of studying receptors in whole tissues using confocal laser scanning microscopy and have advantages over antibody- or non-fluorescence-based method. Confocal microscopy provides large volumes of images to be measured. Histogram analysis of 3-D image volumes is proposed as a method of graphically displaying large amounts of volumetric image data to be quickly analyzed and compared. The fluorescent ligand BODIPY FL-prazosin (QAPB was used in mouse aorta. Histogram analysis reports the amount of ligand-receptor binding under different conditions and the technique is sensitive enough to detect changes in receptor availability after antagonist incubation or genetic manipulations. QAPB binding was concentration dependent, causing concentration-related rightward shifts in the histogram. In the presence of 10 μM phenoxybenzamine (blocking agent, the QAPB (50 nM histogram overlaps the autofluorescence curve. The histogram obtained for the 1D knockout aorta lay to the left of that of control and 1B knockout aorta, indicating a reduction in 1D receptors. We have shown, for the first time, that it is possible to graphically display binding of a fluorescent drug to a biological tissue. Although our application is specific to adrenergic receptors, the general method could be applied to any volumetric, fluorescence-image-based assay.

A MULTIMODAL DISCOURSE ANALYSIS OF SELECTED ADVERTISEMENT OF MALARIA DRUGS

Directory of Open Access Journals (Sweden)

Ayodeji Olowu

2015-06-01

Full Text Available This study identified and analyzed the visual and linguistic components associated with the selected advertisement of malaria drugs. This was with a view to describing the essential communication devices the advertisers of such drugs have employed. Data for the study were drawn from both primary and secondary sources. The primary source for the study comprised 4 purposively selected posters, stickers and drugs literature advertisement on malaria. Analysis of the data followed the framework of Kress and Leeuwen’s Multimodal Discourse Analysis. The results showed that such visual resources as colour, pictures, symbols and icons, gaze and posture enhance the semantic quality of the advertisement. In the whole, the study emphasizes the vitality of visual and linguistic elements as important communication devices in advertising.

Modular reservoir concept for MEMS-based transdermal drug delivery systems

International Nuclear Information System (INIS)

Cantwell, Cara T; Wei, Pinghung; Ziaie, Babak; Rao, Masaru P

2014-01-01

While MEMS-based transdermal drug delivery device development efforts have typically focused on tightly-integrated solutions, we propose an alternate conception based upon a novel, modular drug reservoir approach. By decoupling the drug storage functionality from the rest of the delivery system, this approach seeks to minimize cold chain storage volume, enhance compatibility with conventional pharmaceutical practices, and allow independent optimization of reservoir device design, materials, and fabrication. Herein, we report the design, fabrication, and preliminary characterization of modular reservoirs that demonstrate the virtue of this approach within the application context of transdermal insulin administration for diabetes management. (technical note)

Modular reservoir concept for MEMS-based transdermal drug delivery systems

Science.gov (United States)

Cantwell, Cara T.; Wei, Pinghung; Ziaie, Babak; Rao, Masaru P.

2014-11-01

While MEMS-based transdermal drug delivery device development efforts have typically focused on tightly-integrated solutions, we propose an alternate conception based upon a novel, modular drug reservoir approach. By decoupling the drug storage functionality from the rest of the delivery system, this approach seeks to minimize cold chain storage volume, enhance compatibility with conventional pharmaceutical practices, and allow independent optimization of reservoir device design, materials, and fabrication. Herein, we report the design, fabrication, and preliminary characterization of modular reservoirs that demonstrate the virtue of this approach within the application context of transdermal insulin administration for diabetes management.

The development of a value based pricing index for new drugs in metastatic colorectal cancer.

Science.gov (United States)

Dranitsaris, George; Truter, Ilse; Lubbe, Martie S

2011-06-01

Worldwide, prices for cancer drugs have been under downward pressure where several governments have mandated price cuts of branded products. A better alternative to government mandated price cuts would be to estimate a final price based on drug performance, cost effectiveness and a country's ability to pay. We developed a global pricing index for new cancer drugs in patients with metastatic colorectal cancer (mCRC) that encompasses all of these attributes. A pharmacoeconomic model was developed to simulate mCRC patients receiving chemotherapy plus a 'new drug' that improves survival by 1.4, 3 and 6months, respectively. Cost and utility data were obtained from cancer centres and oncology nurses (n=112) in Canada, Spain, India, South Africa and Malaysia. Multivariable analysis was then used to develop the pricing index, which considers survival benefit, per capita GDP and income dispersion (as measured by the Gini coefficient) as predictor variables. Higher survival benefits were associated with elevated drug prices, especially in higher income countries such as Canada. For Argentina with a per capita GDP of $15,000 and a Gini coefficient of 51, the index estimated that for a drug which provides a 4month survival benefit in mCRC, the value based price would be $US 630 per dose. In contrast, the same drug in a wealthier country like Norway (per capita GDP=$50,000) could command a price of $US 2,775 per dose. The application of this index to estimate a price based on cost effectiveness and the wealth of a nation would be important for opening dialogue between the key stakeholders and a better alternative to government mandated price cuts. Copyright © 2011 Elsevier Ltd. All rights reserved.

Formulation and characterization of lipid-based drug delivery system of raloxifene-microemulsion and self-microemulsifying drug delivery system

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Hetal Thakkar

2011-01-01

Full Text Available Background : Raloxifene, a second-generation selective estrogen receptor modulator (SERM used to prevent osteoporosis in postmenopausal women is administered orally in the form of a tablet. The absolute bioavailability of the drug is only 2% because of extensive hepatic first-pass metabolism. Lipid-based formulations are reported to reduce the first-pass metabolism by promoting its lymphatic uptake. Materials and Methods : In the present investigation, microemulsion and Self-Microemulsifying Drug Delivery System (SMEDDS formulations of Raloxifene were prepared. The prepared formulations were characterized for drug loading, size, transparency, zeta potential, Transmission Electron Microscopy (TEM and in vitro intestinal permeability. Results : The results indicated that high drug loading, optimum size and desired zeta potential and transparency could be achieved with both SMEDDS and microemulsion. The TEM studies indicated the absence of aggregation with both the systems. The in vitro intestinal permeability results showed that the permeation of the drug from the microemulsion and SMEDDs was significantly higher than that obtained from the drug dispersion and marketed formulation. Conclusion : Lipid based formulations such as microemulsion and Self Microemulsifying drug delivery systems are expected to increase the oral bioavailability as evidenced by the increased intestinal permeation.

Formulation and characterization of lipid-based drug delivery system of raloxifene-microemulsion and self-microemulsifying drug delivery system

Science.gov (United States)

Thakkar, Hetal; Nangesh, Jitesh; Parmar, Mayur; Patel, Divyakant

2011-01-01

Background: Raloxifene, a second-generation selective estrogen receptor modulator (SERM) used to prevent osteoporosis in postmenopausal women is administered orally in the form of a tablet. The absolute bioavailability of the drug is only 2% because of extensive hepatic first-pass metabolism. Lipid-based formulations are reported to reduce the first-pass metabolism by promoting its lymphatic uptake. Materials and Methods: In the present investigation, microemulsion and Self-Microemulsifying Drug Delivery System (SMEDDS) formulations of Raloxifene were prepared. The prepared formulations were characterized for drug loading, size, transparency, zeta potential, Transmission Electron Microscopy (TEM) and in vitro intestinal permeability. Results: The results indicated that high drug loading, optimum size and desired zeta potential and transparency could be achieved with both SMEDDS and microemulsion. The TEM studies indicated the absence of aggregation with both the systems. The in vitro intestinal permeability results showed that the permeation of the drug from the microemulsion and SMEDDs was significantly higher than that obtained from the drug dispersion and marketed formulation. Conclusion: Lipid based formulations such as microemulsion and Self Microemulsifying drug delivery systems are expected to increase the oral bioavailability as evidenced by the increased intestinal permeation. PMID:21966167

Drug use among youth and adults in a population-based survey in South Africa

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Karl Peltzer

2018-04-01

Full Text Available Objective: Illicit drug use is a growing public health problem. The aim of the study was to assess the prevalence of drug use and the sociodemographic and health characteristics that influence it among young and adult South Africans. Methods: Data based on the South African national population-based survey in 2012 for 26 453 individuals (52.0% women and 48.0% men aged 15 years and older were analysed. Past 3-month drug use was assessed with the ‘Alcohol, Smoking and Substance use Involvement Screening Test (ASSIST’. Bivariate and multivariable logistic regression was conducted to assess the association between sociodemographic factors, health variables and any past 3-month drug use. Results: Overall, any past 3-month drug use was 4.4%, 7.9% among men and 1.3% among women. The proportion of past 3-month cannabis use was 4.0%, followed by sedatives or sleeping pills 0.4%, amphetamine-type stimulants 0.3%, cocaine 0.3%, opiates 0.3%, inhalants 0.2% and hallucinogens 0.1%. Among the nine South African provinces, any past 3-month drug use was the highest in the Western Cape (7.1%, followed by the Free State (6.3% and Northern Cape (5.2%. In adjusted, multivariable, logistic regression analysis among both men and women, younger age, being mixed race and hazardous or harmful alcohol use were associated with any past 3-month drug use. In addition, having been a victim of violent crime and sexual risk behaviour among men and having psychological distress among women were associated with any past 3-month drug use. Conclusion: An increase of any past 3-month drug use from 3.7% in 2008 to 4.4% in 2012 was observed in South Africa. Prevention and intervention activities targeting drug use, in particular in identified risk groups, need to be strengthened in South Africa.

Preferences of Patients and Pharmacists with Regard to the Management of Drug-Drug Interactions : A Choice-Based Conjoint Analysis

NARCIS (Netherlands)

Heringa, Mette; Floor-Schreudering, Annemieke; Wouters, Hans; De Smet, Peter A G M; Bouvy, Marcel L

INTRODUCTION: The management of drug-drug interactions (DDIs) is a complex process in which risk-benefit assessments should be combined with the patient's perspective. OBJECTIVE: The aim of this study was to determine patients' and pharmacists' preferences regarding DDI management. METHODS: We

A knowledge-based approach for identification of drugs against vivapain-2 protein of Plasmodium vivax through pharmacophore-based virtual screening with comparative modelling.

Science.gov (United States)

Yadav, Manoj Kumar; Singh, Amisha; Swati, D

2014-08-01

Malaria is one of the most infectious diseases in the world. Plasmodium vivax, the pathogen causing endemic malaria in humans worldwide, is responsible for extensive disease morbidity. Due to the emergence of resistance to common anti-malarial drugs, there is a continuous need to develop a new class of drugs for this pathogen. P. vivax cysteine protease, also known as vivapain-2, plays an important role in haemoglobin hydrolysis and is considered essential for the survival of the parasite. The three-dimensional (3D) structure of vivapain-2 is not predicted experimentally, so its structure is modelled by using comparative modelling approach and further validated by Qualitative Model Energy Analysis (QMEAN) and RAMPAGE tools. The potential binding site of selected vivapain-2 structure has been detected by grid-based function prediction method. Drug targets and their respective drugs similar to vivapain-2 have been identified using three publicly available databases: STITCH 3.1, DrugBank and Therapeutic Target Database (TTD). The second approach of this work focuses on docking study of selected drug E-64 against vivapain-2 protein. Docking reveals crucial information about key residues (Asn281, Cys283, Val396 and Asp398) that are responsible for holding the ligand in the active site. The similarity-search criterion is used for the preparation of our in-house database of drugs, obtained from filtering the drugs from the DrugBank database. A five-point 3D pharmacophore model is generated for the docked complex of vivapain-2 with E-64. This study of 3D pharmacophore-based virtual screening results in identifying three new drugs, amongst which one is approved and the other two are experimentally proved. The ADMET properties of these drugs are found to be in the desired range. These drugs with novel scaffolds may act as potent drugs for treating malaria caused by P. vivax.

Designed Synthesis of Nanostructured Magnetic Hydroxyapatite Based Drug Nanocarrier for Anti-Cancer Drug Delivery toward the Treatment of Human Epidermoid Carcinoma

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Bharath Govindan

2017-06-01

Full Text Available Superparamagnetic Fe3O4 nanoparticles on hydroxyapatite nanorod based nanostructures (Fe3O4/HAp were synthesized using hydrothermal techniques at 180 °C for 12 h and were used as drug delivery nanocarriers for cancer cell therapeutic applications. The synthesized Fe3O4/HAp nanocomposites were characterized by X-ray diffraction analysis (XRD, Field emission scanning electron microscopy (FESEM, Fourier transform infrared spectroscopy (FTIR, Brunauer-Emmett-Teller (BET-analysis, and vibrating sample magnetometry (VSM. The morphologies of the Fe3O4/HAp nanocomposites show 15 nm Fe3O4 nanoparticles dispersed in the form of rods. The BET result shows that the synthesized samples have a high specific surface area of 80 m2 g−1 with mesoporous structures. Magnetic measurements revealed that the sample has high saturation magnetization of 18 emu/g with low coercivity. The Fe3O4/HAp nanocomposites had a large specific surface area (SSA, high mesoporous volume, and good magnetic property, which made it a suitable nanocarrier for targeted drug delivery systems. The chemotherapeutic agent, andrographolide, was used to investigate the drug delivery behavior of the Fe3O4/HAp nanocomposites. The human epidermoid skin cancer cells (A431 were used as the model targeting cell lines by treating with andrographolide loaded Fe3O4/HAp nanosystems and were further evaluated for their antiproliferative activities and the induction of apoptosis. Also, the present nanocomposite shows better biocompatibility, therefore it can be used as suitable drug vehicle for cancer therapy applications.

Hair analysis and its concordance with self-report for drug users presenting in emergency department.

Science.gov (United States)

Sharma, Gaurav; Oden, Neal; VanVeldhuisen, Paul C; Bogenschutz, Michael P

2016-10-01

Secondary analysis using data from the National Drug Abuse Treatment Clinical Trials Network randomized trial (NCT # 01207791), in which 1285 adult ED patients endorsing moderate to severe problems related to drug use were recruited from 6 US academic hospitals. To investigate the utility of hair analysis in drug use disorder trials with infrequent visits, and its concordance with Timeline Follow Back (TLFB). This study compared the self-reported drug use on the TLFB instrument with the biological measure of drug use from hair analysis for four major drug classes (Cannabis, Cocaine, Prescribed Opioids and Street Opioids). Both hair analysis and TLFB were conducted at 3, 6 and 12 month follow-up visit and each covered a 90-day recall period prior to the visit. The concordance between the hair sample results and the TLFB was high for cannabis and street opioids, but was low to moderate for cocaine and prescribed opioids. Under-reporting of drug use given the positive hair sample was always significantly lower for the drug the study participant noted as their primary drug of choice compared with other drugs the participant reported taking, irrespective of whether the drug of choice was cannabis, cocaine, street opioids and prescribed opioids. Over-reporting of drug use given the negative hair sample was always significantly higher for the drug of choice, except for cocaine. This study extends the literature on hair analysis supporting its use as a secondary outcome measure in clinical trials. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Differentiation of drug and non-drug Cannabis using a single nucleotide polymorphism (SNP) assay.

Science.gov (United States)

Rotherham, D; Harbison, S A

2011-04-15

Cannabis sativa is both an illegal drug and a legitimate crop. The differentiation of illegal drug Cannabis from non-drug forms of Cannabis is relevant in the context of the growth of fibre and seed oil varieties of Cannabis for commercial purposes. This differentiation is currently determined based on the levels of tetrahydrocannabinol (THC) in adult plants. DNA based methods have the potential to assay Cannabis material unsuitable for analysis using conventional means including seeds, pollen and severely degraded material. The purpose of this research was to develop a single nucleotide polymorphism (SNP) assay for the differentiation of "drug" and "non-drug"Cannabis plants. An assay was developed based on four polymorphisms within a 399 bp fragment of the tetrahydrocannabinolic acid (THCA) synthase gene, utilising the snapshot multiplex kit. This SNP assay was tested on 94 Cannabis plants, which included 10 blind samples, and was able to differentiate between "drug" and "non-drug"Cannabis in all cases, while also differentiating between Cannabis and other species. Non-drug plants were found to be homozygous at the four sites assayed while drug Cannabis plants were either homozygous or heterozygous. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Medicinal chemistry inspired fragment-based drug discovery.

Science.gov (United States)

Lanter, James; Zhang, Xuqing; Sui, Zhihua

2011-01-01

Lead generation can be a very challenging phase of the drug discovery process. The two principal methods for this stage of research are blind screening and rational design. Among the rational or semirational design approaches, fragment-based drug discovery (FBDD) has emerged as a useful tool for the generation of lead structures. It is particularly powerful as a complement to high-throughput screening approaches when the latter failed to yield viable hits for further development. Engagement of medicinal chemists early in the process can accelerate the progression of FBDD efforts by incorporating drug-friendly properties in the earliest stages of the design process. Medium-chain acyl-CoA synthetase 2b and ketohexokinase are chosen as examples to illustrate the importance of close collaboration of medicinal chemists, crystallography, and modeling. Copyright © 2011 Elsevier Inc. All rights reserved.

Exploration of approaches to adjusting brand-name drug prices in Mainland of China: based on comparison and analysis of some brand-name drug prices of Mainland and Taiwan, China.

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Weng, Geng; Han, Sheng; Pu, Run; Pan, Wynn H T; Shi, Luwen

2014-01-01

Under the circumstance of the New Medical Reform in Mainland of China, lowering drug prices has become an approach to relieving increase of medical expenses, and lowering brand-name medication price is a key strategy. This study, by comparing and analyzing brand-name medication prices between Mainland of China and Taiwan, explores how to adjust brand-name medication prices in Mainland of China in the consideration of the drug administrative strategies in Taiwan. By selecting brand-name drug with generic name and dose types matched in Mainland and Taiwan, calculate the average unit price and standard deviation and test it with the paired t-test. In the mean time, drug administrative strategies between Mainland and Taiwan are also compared systematically. Among the 70 brand-name medications with generic names and matched dose types, 54 are at higher prices in Mainland of China than Taiwan, which is statistically significant in t-test. Also, among the 47 medications with all of matched generic names, dose types, and manufacturing enterprises, 38 are at higher prices in Mainland than Taiwan, and the gap is also statistically significant in t-test. In Mainland of China, brand-name medication took cost-plus pricing and price-based price adjustment, while in Taiwan, brand-name medication took internal and external reference pricing and market-based price adjustment. Brand-name drug prices were higher in Mainland of China than in Taiwan. The adjustment strategies of drug prices are scientific in Taiwan and are worth reference by Mainland of China.

MONITORING POTENTIAL DRUG INTERACTIONS AND REACTIONS VIA NETWORK ANALYSIS OF INSTAGRAM USER TIMELINES.

Science.gov (United States)

Correia, Rion Brattig; Li, Lang; Rocha, Luis M

2016-01-01

Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this "Bibliome", the universe of social media provides a very promising source of large-scale data that can help identify DDI and ADR in ways that have not been hitherto possible. Given the large number of users, analysis of social media data may be useful to identify under-reported, population-level pathology associated with DDI, thus further contributing to improvements in population health. Moreover, tapping into this data allows us to infer drug interactions with natural products-including cannabis-which constitute an array of DDI very poorly explored by biomedical research thus far. Our goal is to determine the potential of Instagram for public health monitoring and surveillance for DDI, ADR, and behavioral pathology at large. Most social media analysis focuses on Twitter and Facebook, but Instagram is an increasingly important platform, especially among teens, with unrestricted access of public posts, high availability of posts with geolocation coordinates, and images to supplement textual analysis. Using drug, symptom, and natural product dictionaries for identification of the various types of DDI and ADR evidence, we have collected close to 7000 user timelines spanning from October 2010 to June 2015.We report on 1) the development of a monitoring tool to easily observe user-level timelines associated with drug and symptom terms of interest, and 2) population-level behavior via the analysis of co-occurrence networks computed from user timelines at three different scales: monthly, weekly, and daily occurrences. Analysis of these networks further reveals 3) drug and symptom direct and indirect associations with greater support in user timelines, as well as 4) clusters of symptoms and drugs revealed by the collective behavior of the observed population. This demonstrates that Instagram

Seaweed Polysaccharide-Based Nanoparticles: Preparation and Applications for Drug Delivery

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Jayachandran Venkatesan

2016-01-01

Full Text Available In recent years, there have been major advances and increasing amounts of research on the utilization of natural polymeric materials as drug delivery vehicles due to their biocompatibility and biodegradability. Seaweed polysaccharides are abundant resources and have been extensively studied for several biological, biomedical, and functional food applications. The exploration of seaweed polysaccharides for drug delivery applications is still in its infancy. Alginate, carrageenan, fucoidan, ulvan, and laminarin are polysaccharides commonly isolated from seaweed. These natural polymers can be converted into nanoparticles (NPs by different types of methods, such as ionic gelation, emulsion, and polyelectrolyte complexing. Ionic gelation and polyelectrolyte complexing are commonly employed by adding cationic molecules to these anionic polymers to produce NPs of a desired shape, size, and charge. In the present review, we have discussed the preparation of seaweed polysaccharide-based NPs using different types of methods as well as their usage as carriers for the delivery of various therapeutic molecules (e.g., proteins, peptides, anti-cancer drugs, and antibiotics. Seaweed polysaccharide-based NPs exhibit suitable particle size, high drug encapsulation, and sustained drug release with high biocompatibility, thereby demonstrating their high potential for safe and efficient drug delivery.

How do Australian news media depict illicit drug issues? An analysis of print media reporting across and between illicit drugs, 2003-2008.

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Hughes, Caitlin Elizabeth; Lancaster, Kari; Spicer, Bridget

2011-07-01

Media reporting on illicit issues has been frequently criticised for being sensationalised, biased and narrow. Yet, there have been few broad and systematic analyses of the nature of reporting. Using a large sample and methods commonly adopted in media communications analysis this paper sought to identify the dominant media portrayals used to denote illicit drugs in Australian newspapers and to compare and contrast portrayals across drug types. A retrospective content analysis of Australian print media was carried out over the period 2003-2008 from a sample comprised of 11 newspapers. Articles that contained one or more mention of five different drugs (or derivatives) were identified: cannabis, amphetamines, ecstasy, cocaine and heroin. A sub-sample of 4397 articles was selected for media content analysis (with 2045 selected for full content analysis) and a large number of text elements coded for each. Key elements included topic, explicit or implicit messages about the consequences of drugs/use and three value dimensions: overall tone, whether drugs were portrayed as a crisis issue and moral evaluations of drugs/use. The dominant media portrayals depicted law enforcement or criminal justice action (55%), but most articles were reported in a neutral manner, in the absence of crisis framings. Portrayals differed between drugs, with some containing more narrow frames and more explicit moral evaluations than others. For example, heroin was disproportionately framed as a drug that will lead to legal problems. In contrast, ecstasy and cocaine were much more likely to emphasise health and social problems. Media reporting on illicit drugs is heavily distorted towards crime and deviance framings, but may be less overtly sensationalised, biased and narrowly framed than previously suggested. This is not to suggest there is no sensationalism or imbalance, but this appears more associated with particular drug types and episodes of heightened public concern. Copyright © 2011

Competitive intelligence and patent analysis in drug discovery.

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Grandjean, Nicolas; Charpiot, Brigitte; Pena, Carlos Andres; Peitsch, Manuel C

2005-01-01

Patents are a major source of information in drug discovery and, when properly processed and analyzed, can yield a wealth of information on competitors activities, R&D trends, emerging fields, collaborations, among others. This review discusses the current state-of-the-art in textual data analysis and exploration methods as applied to patent analysis.: © 2005 Elsevier Ltd . All rights reserved.

Is Web-Based Education Effective in Reducing Belief Toward Drug Abuse Among College Students?

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Jalilian

2015-02-01

Full Text Available Background Addiction is considered a basic structural problem in modern society, and seems to reach an epidemic scale in the last decades. Choosing a method to fulfill the intervention is an important issue to conduct educational interventions to prevent addictive behaviors. In this regard, web-based education has been widely used to introduce preventive programs to risky behaviors during recent years. Objectives The aim of the present study was to investigate the impact of web-based education intervention to decrease positive beliefs encouraging drug abuse among male medical college students. Patients and Methods This was a prospective-retrospective intervention study that was conducted among 75 male students in Kermanshah University of Medical Sciences, Kermanshah, Iran, during 2014. t-test was used for the statistical analysis. Results Our findings indicated that the belief toward drug abuse was significantly reduced after education (P = 0.003. In addition, compared pre and post-intervention scores on survey items showed a significant reduction in enjoyment, improve energy, attraction, higher strength, and higher self-esteem items after education (P 0.05. Conclusions Our findings showed that designing and implementing web-based educational intervention could be effective to reduce the positive beliefs toward drug abuse among college students.

A multilayer microdevice for cell-based high-throughput drug screening

International Nuclear Information System (INIS)

Liu, Chong; Wang, Lei; Li, Jingmin; Ding, Xiping; Chunyu, Li; Xu, Zheng; Wang, Qi

2012-01-01

A multilayer polydimethylsiloxane microdevice for cell-based high-throughput drug screening is described in this paper. This established microdevice was based on a modularization method and it integrated a drug/medium concentration gradient generator (CGG), pneumatic microvalves and a cell culture microchamber array. The CGG was able to generate five steps of linear concentrations with the same outlet flow rate. The medium/drug flowed through CGG and then into the pear-shaped cell culture microchambers vertically. This vertical perfusion mode was used to reduce the impact of the shear stress on the physiology of cells induced by the fluid flow in the microchambers. Pear-shaped microchambers with two arrays of miropillars at each outlet were adopted in this microdevice, which were beneficial to cell distribution. The chemotherapeutics Cisplatin (DDP)-induced Cisplatin-resistant cell line A549/DDP apoptotic experiments were performed well on this platform. The results showed that this novel microdevice could not only provide well-defined and stable conditions for cell culture, but was also useful for cell-based high-throughput drug screening with less reagents and time consumption. (paper)

Versatile Chemical Derivatizations to Design Glycol Chitosan-Based Drug Carriers

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Sung Eun Kim

2017-10-01

Full Text Available Glycol chitosan (GC and its derivatives have been extensively investigated as safe and effective drug delivery carriers because of their unique physiochemical and biological properties. The reactive functional groups such as the amine and hydroxyl groups on the GC backbone allow for easy chemical modification with various chemical compounds (e.g., hydrophobic molecules, crosslinkers, and acid-sensitive and labile molecules, and the versatility in chemical modifications enables production of a wide range of GC-based drug carriers. This review summarizes the versatile chemical modification methods that can be used to design GC-based drug carriers and describes their recent applications in disease therapy.

The redistributive effect of the move from age-based to income-based prescription drug coverage in British Columbia, Canada.

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Hanley, Gillian E; Morgan, Steve; Barer, Morris; Reid, Robert J

2011-07-01

To explore the redistributive impact of two different pharmaceutical financing policies (age-based versus income-based pharmacare) on the distribution of income in British Columbia (B.C.), Canada. Using household-level data on all payments that are used to finance prescription drugs in B.C. (including taxation and private payments), we performed a redistributive analysis to indicate how much income inequality in the province changed as a result of payments made for prescription drugs. We also illustrated changes in vertical equity (different treatment according to ability-to-pay) and horizontal equity (equals, according to ability-to-pay, being treated equally) between the two years separately through a pre-post policy examination. We found that payments made to finance prescription drugs increased overall income inequality in the province. This negative impact was larger after the move to income-based pharmacare. Our results also show increasing horizontal inequity after the policy change, and suggest that the increased reliance on out-of-pocket payments was a major source of the negative impact on the B.C.'s overall income distribution. We also show that the consequences of the move to income-based pharmacare would have been less severe had the level of public financing not decreased substantially between the two years. The increase in income inequality in B.C. following the policy change was an unintended consequence of the move to income-based pharmacare. This finding is worth consideration as countries and jurisdictions weigh pharmaceutical policy alternatives. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Perhaps More Consideration of Pavlovian-Operant Interaction May Improve the Clinical Efficacy of Behaviorally Based Drug Treatment Programs.

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Troisi, Joseph R

2013-01-01

Drug abuse remains costly. Drug-related cues can evoke cue-reactivity and craving, contributing to relapse. The Pavlovian extinction-based cue-exposure therapy (CET) has not been very successful in treating drug abuse. A functional operant analysis of complex rituals involved in CET is outlined and reinterpreted as an operant heterogeneous chain maintained by observing responses, conditioned reinforcers, and discriminative stimuli. It is further noted that operant functions are not predicated on Pavlovian processes but can be influenced by them in contributing to relapse; several empirical studies from the animal and human literature highlight this view. Cue-reactivity evoked by Pavlovian processes is conceptualized as an operant establishing/motivating operation. CET may be more effective in incorporating an operant-based approach that takes into account the complexity of Pavlovian-operant interaction. Extinction of the operant chain coupled with the shaping of alternative behaviors is proposed as an integrated therapy. It is proposed that operant-based drug abuse treatments (contingency management, voucher programs, and the therapeutic work environment) might consider incorporating cue-reactivity, as establishing/motivating operations, to increase long-term success-a hybrid approach based on Pavlovian-operant interaction.

Perhaps More Consideration of Pavlovian–Operant Interaction May Improve the Clinical Efficacy of Behaviorally Based Drug Treatment Programs

Science.gov (United States)

Troisi, Joseph R.

2014-01-01

Drug abuse remains costly. Drug-related cues can evoke cue-reactivity and craving, contributing to relapse. The Pavlovian extinction-based cue-exposure therapy (CET) has not been very successful in treating drug abuse. A functional operant analysis of complex rituals involved in CET is outlined and reinterpreted as an operant heterogeneous chain maintained by observing responses, conditioned reinforcers, and discriminative stimuli. It is further noted that operant functions are not predicated on Pavlovian processes but can be influenced by them in contributing to relapse; several empirical studies from the animal and human literature highlight this view. Cue-reactivity evoked by Pavlovian processes is conceptualized as an operant establishing/motivating operation. CET may be more effective in incorporating an operant-based approach that takes into account the complexity of Pavlovian–operant interaction. Extinction of the operant chain coupled with the shaping of alternative behaviors is proposed as an integrated therapy. It is proposed that operant-based drug abuse treatments (contingency management, voucher programs, and the therapeutic work environment) might consider incorporating cue-reactivity, as establishing/motivating operations, to increase long-term success—a hybrid approach based on Pavlovian–operant interaction. PMID:25346551

Relationship among reaction rate, release rate and efficiency of nanomachine-based targeted drug delivery.

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Zhao, Qingying; Li, Min; Luo, Jun

2017-12-04

In nanomachine applications towards targeted drug delivery, drug molecules released by nanomachines propagate and chemically react with tumor cells in aqueous environment. If the nanomachines release drug molecules faster than the tumor cells react, it will result in loss and waste of drug molecules. It is a potential issue associated with the relationship among reaction rate, release rate and efficiency. This paper aims to investigate the relationship among reaction rate, release rate and efficiency based on two drug reception models. We expect to pave a way for designing a control method of drug release. We adopted two analytical methods that one is drug reception process based on collision with tumors and another is based on Michaelis Menten enzymatic kinetics. To evaluate the analytical formulations, we used the well-known simulation framework N3Sim to establish simulations. The analytical results of the relationship among reaction rate, release rate and efficiency is obtained, which match well with the numerical simulation results in a 3-D environment. Based upon two drug reception models, the results of this paper would be beneficial for designing a control method of nanomahine-based drug release.

Developing artemisinin based drug combinations for the treatment of drug resistant falciparum malaria: A review

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Olliaro P

2004-01-01

Full Text Available The emergence and spread of drug resistant malaria represents a considerable challenge to controlling malaria. To date, malaria control has relied heavily on a comparatively small number of chemically related drugs, belonging to either the quinoline or the antifolate groups. Only recently have the artemisinin derivatives been used but mostly in south east Asia. Experience has shown that resistance eventually curtails the life-span of antimalarial drugs. Controlling resistance is key to ensuring that the investment put into developing new antimalarial drugs is not wasted. Current efforts focus on research into new compounds with novel mechanisms of action, and on measures to prevent or delay resistance when drugs are introduced. Drug discovery and development are long, risky and costly ventures. Antimalarial drug development has traditionally been slow but now various private and public institutions are at work to discover and develop new compounds. Today, the antimalarial development pipeline is looking reasonably healthy. Most development relies on the quinoline, antifolate and artemisinin compounds. There is a pressing need to have effective, easy to use, affordable drugs that will last a long time. Drug combinations that have independent modes of action are seen as a way of enhancing efficacy while ensuring mutual protection against resistance. Most research work has focused on the use of artesunate combined with currently used standard drugs, namely, mefloquine, amodiaquine, sulfadoxine/pyrimethamine, and chloroquine. There is clear evidence that combinations improve efficacy without increasing toxicity. However, the absolute cure rates that are achieved by combinations vary widely and depend on the level of resistance of the standard drug. From these studies, further work is underway to produce fixed dose combinations that will be packaged in blister packs. This review will summarise current antimalarial drug developments and outline recent

Detection of Anti-Hepatitis B Virus Drug Resistance Mutations Based on Multicolor Melting Curve Analysis.

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Mou, Yi; Athar, Muhammad Ammar; Wu, Yuzhen; Xu, Ye; Wu, Jianhua; Xu, Zhenxing; Hayder, Zulfiqar; Khan, Saeed; Idrees, Muhammad; Nasir, Muhammad Israr; Liao, Yiqun; Li, Qingge

2016-11-01

Detection of anti-hepatitis B virus (HBV) drug resistance mutations is critical for therapeutic decisions for chronic hepatitis B virus infection. We describe a real-time PCR-based assay using multicolor melting curve analysis (MMCA) that could accurately detect 24 HBV nucleotide mutations at 10 amino acid positions in the reverse transcriptase region of the HBV polymerase gene. The two-reaction assay had a limit of detection of 5 copies per reaction and could detect a minor mutant population (5% of the total population) with the reverse transcriptase M204V amino acid mutation in the presence of the major wild-type population when the overall concentration was 10 4 copies/μl. The assay could be finished within 3 h, and the cost of materials for each sample was less than $10. Clinical validation studies using three groups of samples from both nucleos(t)ide analog-treated and -untreated patients showed that the results for 99.3% (840/846) of the samples and 99.9% (8,454/8,460) of the amino acids were concordant with those of Sanger sequencing of the PCR amplicon from the HBV reverse transcriptase region (PCR Sanger sequencing). HBV DNA in six samples with mixed infections consisting of minor mutant subpopulations was undetected by the PCR Sanger sequencing method but was detected by MMCA, and the results were confirmed by coamplification at a lower denaturation temperature-PCR Sanger sequencing. Among the treated patients, 48.6% (103/212) harbored viruses that displayed lamivudine monoresistance, adefovir monoresistance, entecavir resistance, or lamivudine and adefovir resistance. Among the untreated patients, the Chinese group had more mutation-containing samples than did the Pakistani group (3.3% versus 0.56%). Because of its accuracy, rapidness, wide-range coverage, and cost-effectiveness, the real-time PCR assay could be a robust tool for the detection if anti-HBV drug resistance mutations in resource-limited countries. Copyright © 2016, American Society for

The Forty-Sixth Euro Congress on Drug Synthesis and Analysis: Snapshot †

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Pavel Mucaji

2017-10-01

Full Text Available The 46th EuroCongress on Drug Synthesis and Analysis (ECDSA-2017 was arranged within the celebration of the 65th Anniversary of the Faculty of Pharmacy at Comenius University in Bratislava, Slovakia from 5–8 September 2017 to get together specialists in medicinal chemistry, organic synthesis, pharmaceutical analysis, screening of bioactive compounds, pharmacology and drug formulations; promote the exchange of scientific results, methods and ideas; and encourage cooperation between researchers from all over the world. The topic of the conference, “Drug Synthesis and Analysis,” meant that the symposium welcomed all pharmacists and/or researchers (chemists, analysts, biologists and students interested in scientific work dealing with investigations of biologically active compounds as potential drugs. The authors of this manuscript were plenary speakers and other participants of the symposium and members of their research teams. The following summary highlights the major points/topics of the meeting.

Phenytoin-Bovine Serum Albumin interactions - modeling plasma protein - drug binding: A multi-spectroscopy and in silico-based correlation

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Suresh, P. K.; Divya, Naik; Nidhi, Shah; Rajasekaran, R.

2018-03-01

The study focused on the analysis of the nature and site of binding of Phenytoin (PHT) -(a model hydrophobic drug) with Bovine Serum Albumin (BSA) (a model protein used as a surrogate for HSA). Interactions with defined amounts of Phenytoin and BSA demonstrated a blue shift (hypsochromic -change in the microenvironment of the tryptophan residue with decrease in the polar environment and more of hydrophobicity) with respect to the albumin protein and a red shift (bathochromic -hydrophobicity and polarity related changes) in the case of the model hydrophobic drug. This shift, albeit lower in magnitude, has been substantiated by a fairly convincing, Phenytoin-mediated quenching of the endogenous fluorophore in BSA. Spectral shifts studied at varying pH, temperatures and incubation periods (at varying concentrations of PHT with a defined/constant BSA concentration) showed no significant differences (data not shown). FTIR analysis provided evidence of the interaction of PHT with BSA with a stretching vibration of 1737.86 cm- 1, apart from the vibrations characteristically associated with the amine and carboxyl groups respectively. Our in vitro findings were extended to molecular docking of BSA with PHT (with the different ionized forms of the drug) and the subsequent LIGPLOT-based analysis. In general, a preponderance of hydrophobic interactions was observed. These hydrophobic interactions corroborate the tryptophan-based spectral shifts and the fluorescence quenching data. These results substantiates our hitherto unreported in vitro/in silico experimental flow and provides a basis for screening other hydrophobic drugs in its class.

Population-based differences in treatment outcome following anticancer drug therapies.

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Ma, Brigette By; Hui, Edwin P; Mok, Tony Sk

2010-01-01

Population-based differences in toxicity and clinical outcome following treatment with anticancer drugs have an important effect on oncology practice and drug development. These differences arise from complex interactions between biological and environmental factors, which include genetic diversity affecting drug metabolism and the expression of drug targets, variations in tumour biology and host physiology, socioeconomic disparities, and regional preferences in treatment standards. Some well-known examples include the high prevalence of activating epidermal growth factor receptor (EGFR) mutations in pulmonary adenocarcinoma among northeast (China, Japan, Korea) and parts of southeast Asia (excluding India) non-smokers, which predict sensitivity to EGFR kinase inhibitors, and the sharp contrast between Japan and the west in the management and survival outcome of gastric cancer. This review is a critical overview of population-based differences in the four most prevalent cancers in the world: lung, breast, colorectal, and stomach cancer. Particular attention is given to the clinical relevance of such knowledge in terms of the individualisation of drug therapy and in the design of clinical trials. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Manual of Standard Operating Procedures for Veterinary Drug Residue Analysis

International Nuclear Information System (INIS)

2016-01-01

Laboratories are crucial to national veterinary drug residue monitoring programmes. However, one of the main challenges laboratories encounter is obtaining access to relevant methods of analysis. Thus, in addition to training, providing technical advice and transferring technology, the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture has resolved to develop clear and practical manuals to support Member State laboratories. The Coordinated Research Project (CRP) on Development of Radiometric and Allied Analytical Methods to Strengthen Residue Control Programs for Antibiotic and Anthelmintic Veterinary Drug Residues has developed a number of analytical methods as standard operating procedures (SOPs), which are now compiled here. This publication contains SOPs on chromatographic and spectrometric techniques, as well as radioimmunoassay and associated screening techniques, for various anthelmintic and antimicrobial veterinary drug residue analysis. Some analytical method validation protocols are also included. The publication is primarily aimed at food and environmental safety laboratories involved in testing veterinary drug residues, including under organized national residue monitoring programmes. It is expected to enhance laboratory capacity building and competence through the use of radiometric and complementary tools and techniques. The publication is also relevant for applied research on residues of veterinary drugs in food and environmental samples

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: myocardial and infectious adverse reactions as application cases.

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Wang, Kejian; Weng, Zuquan; Sun, Liya; Sun, Jiazhi; Zhou, Shu-Feng; He, Lin

2015-02-13

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure-activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. Copyright © 2015 Elsevier Inc. All rights reserved.

Evaluation of poly-drug use in methadone-related fatalities using segmental hair analysis.

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Nielsen, Marie Katrine Klose; Johansen, Sys Stybe; Linnet, Kristian

2015-03-01

In Denmark, fatal poisoning among drug addicts is often related to methadone. The primary mechanism contributing to fatal methadone overdose is respiratory depression. Concurrent use of other central nervous system (CNS) depressants is suggested to heighten the potential for fatal methadone toxicity. Reduced tolerance due to a short-time abstinence period is also proposed to determine a risk for fatal overdose. The primary aims of this study were to investigate if concurrent use of CNS depressants or reduced tolerance were significant risk factors in methadone-related fatalities using segmental hair analysis. The study included 99 methadone-related fatalities collected in Denmark from 2008 to 2011, where both blood and hair were available. The cases were divided into three subgroups based on the cause of death; methadone poisoning (N=64), poly-drug poisoning (N=28) or methadone poisoning combined with fatal diseases (N=7). No significant differences between methadone concentrations in the subgroups were obtained in both blood and hair. The methadone blood concentrations were highly variable (0.015-5.3, median: 0.52mg/kg) and mainly within the concentration range detected in living methadone users. In hair, methadone was detected in 97 fatalities with concentrations ranging from 0.061 to 211ng/mg (median: 11ng/mg). In the remaining two cases, methadone was detected in blood but absent in hair specimens, suggesting that these two subjects were methadone-naive users. Extensive poly-drug use was observed in all three subgroups, both recently and within the last months prior to death. Especially, concurrent use of multiple benzodiazepines was prevalent among the deceased followed by the abuse of morphine, codeine, amphetamine, cannabis, cocaine and ethanol. By including quantitative segmental hair analysis, additional information on poly-drug use was obtained. Especially, 6-acetylmorphine was detected more frequently in hair specimens, indicating that regular abuse of

Pancreatic Safety of Incretin-Based Drugs - FDA and EMA Assessment

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Egan, Amy G.; Blind, Eberhard; Dunder, Kristina; de Graeff, Pieter A.; Hummer, B. Timothy; Bourcier, Todd; Rosebraugh, Curtis

2014-01-01

After evaluating a safety signal regarding pancreatitis and pancreatic cancer in patients using incretin-based drugs, the Food and Drug Administration and the European Medicines Agency conclude that assertions of a causal association are inconsistent with the data. With approximately 25.8 million

Predicting Hepatotoxicity of Drug Metabolites Via an Ensemble Approach Based on Support Vector Machine

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Lu, Yin; Liu, Lili; Lu, Dong; Cai, Yudong; Zheng, Mingyue; Luo, Xiaomin; Jiang, Hualiang; Chen, Kaixian

2017-11-20

Drug-induced liver injury (DILI) is a major cause of drug withdrawal. The chemical properties of the drug, especially drug metabolites, play key roles in DILI. Our goal is to construct a QSAR model to predict drug hepatotoxicity based on drug metabolites. 64 hepatotoxic drug metabolites and 3,339 non-hepatotoxic drug metabolites were gathered from MDL Metabolite Database. Considering the imbalance of the dataset, we randomly split the negative samples and combined each portion with all the positive samples to construct individually balanced datasets for constructing independent classifiers. Then, we adopted an ensemble approach to make prediction based on the results of all individual classifiers and applied the minimum Redundancy Maximum Relevance (mRMR) feature selection method to select the molecular descriptors. Eventually, for the drugs in the external test set, a Bayesian inference method was used to predict the hepatotoxicity of a drug based on its metabolites. The model showed the average balanced accuracy=78.47%, sensitivity =74.17%, and specificity=82.77%. Five molecular descriptors characterizing molecular polarity, intramolecular bonding strength, and molecular frontier orbital energy were obtained. When predicting the hepatotoxicity of a drug based on all its metabolites, the sensitivity, specificity and balanced accuracy were 60.38%, 70.00%, and 65.19%, respectively, indicating that this method is useful for identifying the hepatotoxicity of drugs. We developed an in silico model to predict hepatotoxicity of drug metabolites. Moreover, Bayesian inference was applied to predict the hepatotoxicity of a drug based on its metabolites which brought out valuable high sensitivity and specificity. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

[Animal drugs quality status and reason analysis].

Science.gov (United States)

Ding, Qing; Qiu, Ya-jing; Fang, Ke-hui; Hu, Hao-bin; Wu, Yue

2015-11-01

In order to reaction the quality present situation, problems on the current quality of animal sources of drugs are summed up by using test data analysis, literature search and marketing research. This paper can also help the improvement of the quality management, the revision of the relevant department policy system and the improvement of standards.

Drug-likeness analysis of traditional Chinese medicines: 2. Characterization of scaffold architectures for drug-like compounds, non-drug-like compounds, and natural compounds from traditional Chinese medicines.

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Tian, Sheng; Li, Youyong; Wang, Junmei; Xu, Xiaojie; Xu, Lei; Wang, Xiaohong; Chen, Lei; Hou, Tingjun

2013-01-21

In order to better understand the structural features of natural compounds from traditional Chinese medicines, the scaffold architectures of drug-like compounds in MACCS-II Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD) were explored and compared. First, the different scaffolds were extracted from ACD, MDDR and TCMCD by using three scaffold representations, including Murcko frameworks, Scaffold Tree, and ring systems with different complexity and side chains. Then, by examining the accumulative frequency of the scaffolds in each dataset, we observed that the Level 1 scaffolds of the Scaffold Tree offer advantages over the other scaffold architectures to represent the scaffold diversity of the compound libraries. By comparing the similarity of the scaffold architectures presented in MDDR, ACD and TCMCD, structural overlaps were observed not only between MDDR and TCMCD but also between MDDR and ACD. Finally, Tree Maps were used to cluster the Level 1 scaffolds of the Scaffold Tree and visualize the scaffold space of the three datasets. The analysis of the scaffold architectures of MDDR, ACD and TCMCD shows that, on average, drug-like molecules in MDDR have the highest diversity while natural compounds in TCMCD have the highest complexity. According to the Tree Maps, it can be observed that the Level 1 scaffolds present in MDDR have higher diversity than those presented in TCMCD and ACD. However, some representative scaffolds in MDDR with high frequency show structural similarities to those in TCMCD and ACD, suggesting that some scaffolds in TCMCD and ACD may be potentially drug-like fragments for fragment-based and de novo drug design.

Study of the Dynamic Uptake of Free Drug and Nanostructures for Drug Delivery Based on Bioluminescence Measurements

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Zhongjian Fang

2017-01-01

Full Text Available The past two decades have witnessed the great growth of the development of novel drug carriers. However, the releasing dynamics of drug from drug carriers in vivo and the interactions between cells and drug carriers remain unclear. In this paper, liposomes were prepared to encapsulate D-luciferin, which was the substrate of luciferase and served as a model drug. Based on the theoretical calculation of active loading, methods of preparation for liposomes were optimized. Only when D-luciferin was released from liposomes or taken in by the cells could bioluminescence be produced under the catalysis of luciferase. Models of multicellular tumor spheroid (MCTS were built with 4T1-luc cells that expressed luciferase stably. The kinetic processes of uptake and distribution of free drugs and liposomal drugs were determined with models of cell suspension, monolayer cells, MCTS, and tumor-bearing nude mice. The technology platform has been demonstrated to be effective for the study of the distribution and kinetic profiles of various liposomes as drug delivery systems.

Lipid-based formulations for oral administration of poorly water-soluble drugs

DEFF Research Database (Denmark)

Mu, Huiling; Holm, René; Müllertz, Anette

2013-01-01

Lipid-based drug delivery systems have shown great potentials in oral delivery of poorly water-soluble drugs, primarily for lipophilic drugs, with several successfully marketed products. Pre-dissolving drugs in lipids, surfactants, or mixtures of lipids and surfactants omits the dissolving....../dissolution step, which is a potential rate limiting factor for oral absorption of poorly water-soluble drugs. Lipids not only vary in structures and physiochemical properties, but also in their digestibility and absorption pathway; therefore selection of lipid excipients and dosage form has a pronounced effect...

Study of small-cell lung cancer cell-based sensor and its applications in chemotherapy effects rapid evaluation for anticancer drugs.

Science.gov (United States)

Guohua, Hui; Hongyang, Lu; Zhiming, Jiang; Danhua, Zhu; Haifang, Wan

2017-11-15

Small cell lung cancer (SCLC) is a smoking-related cancer disease. Despite improvement in clinical survival, SCLC outcome remains extremely poor. Cisplatin (DDP) is the first-line chemotherapy drug for SCLC, but the choice of second-line chemotherapy drugs is not clear. In this paper, a SCLC cell-based sensor was proposed, and its applications in chemotherapy effects rapid evaluation for anticancer drugs were investigated. SCLC cell lines lung adenocarcinoma cell (LTEP-P) and DDP-resistant lung adenocarcinoma cell (LTEP-P/DDP-1.0) are cultured on carbon screen-printed electrode (CSPE) to fabricate integrated cell-based sensor. Several chemotherapy anticancer drugs, including cisplatin, ifosmamide, gemcitabine, paclitaxel, docetaxel, vinorelbine, etoposide, camptothecin, and topotecan, are selected as experimental chemicals. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) tests are conducted to evaluate chemotherapy drug effects on LTEP-P and LTEP-P/DDP-1.0 cell lines. Electrical cell-substrate impedance sensing (ECIS) responses to anti-tumor chemicals are measured and processed by double-layered cascaded stochastic resonance (DCSR). Cisplatin solutions in different concentrations measurement results demonstrate that LTEP-P cell-based sensor presents quantitative analysis abilities for cisplatin and topotecan. Cisplatin and its mixtures can also be discriminated. Results demonstrate that LTEP-P cell-based sensor sensitively evaluates chemotherapy drugs' apoptosis function to SCLC cells. LTEP-P/DDP-1.0 cell-based sensor responses demonstrate that gemcitabine, vinorelbine, and camptothecin are ideal second-line drugs for clinical post-cisplatin therapy than other drugs according to MTT test results. This work provides a novel way for SCLC second-line clinical chemotherapy drug screening. Copyright © 2017 Elsevier B.V. All rights reserved.

ANALYSIS OF DRUG-PROTEIN BINDING BY ULTRAFAST AFFINITY CHROMATOGRAPHY USING IMMOBILIZED HUMAN SERUM ALBUMIN

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Mallik, Rangan; Yoo, Michelle J.; Briscoe, Chad J.; Hage, David S.

2010-01-01

Human serum albumin (HSA) was explored for use as a stationary phase and ligand in affinity microcolumns for the ultrafast extraction of free drug fractions and the use of this information for the analysis of drug-protein binding. Warfarin, imipramine, and ibuprofen were used as model analytes in this study. It was found that greater than 95% extraction of all these drugs could be achieved in as little as 250 ms on HSA microcolumns. The retained drug fraction was then eluted from the same column under isocratic conditions, giving elution in less than 40 s when working at 4.5 mL/min. The chromatographic behavior of this system gave a good fit with that predicted by computer simulations based on a reversible, saturable model for the binding of an injected drug with immobilized HSA. The free fractions measured by this method were found to be comparable to those determined by ultrafiltration, and equilibrium constants estimated by this approach gave good agreement with literature values. Advantages of this method include its speed and the relatively low cost of microcolumns that contain HSA. The ability of HSA to bind many types of drugs also creates the possibility of using the same affinity microcolumn to study and measure the free fractions for a variety of pharmaceutical agents. These properties make this technique appealing for use in drug binding studies and in the high-throughput screening of new drug candidates. PMID:20227701

Trace drug analysis by surface-enhanced Raman spectroscopy

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Farquharson, Stuart; Lee, Vincent Y.

2000-12-01

Drug overdose involves more than 10 percent of emergency room (ER) cases, and a method to rapidly identify and quantify the abused drug is critical to the ability of the ER physician to administer the appropriate care. To this end, we have been developing a surface-enhanced Raman (SER) active material capable of detecting target drugs at physiological concentrations in urine. The SER-active material consists of a metal-doped sol-gel that provides not only a million fold increase in sensitivity but also reproducible measurements. The porous silica network offers a unique environment for stabilizing SER active metal particles and the high surface area increase the interaction between the analyte and metal particles. The sol-gel has been coated on the inside walls of glass samples vials, such that urine specimens may simply be introduced for analysis. Here we present the surface-enhanced Raman spectra of a series of barbiturates, actual urine specimens, and a drug 'spiked' urine specimen. The utility of pH adjustment to suppress dominant biochemicals associated with urine is also presented.

Reevaluation of Meta-analysis on prophylactic drug management for recurrence of febrile seizures

Directory of Open Access Journals (Sweden)

Huan LIAO

2015-08-01

Full Text Available Objective To explore the efficiency and safety of drugs to prevent the recurrence of febrile seizures (FS.  Methods Relevant literatures were searched via PubMed, EMBASE/SCOPUS, EBSCO-CINAHL, Web of Science, Cochrane Database of Systematic Reviews from December 1997 to November 2014 using the following keywords: febrile seizure OR febrile convulsion, recurrence, prevention OR prophylaxis, medicine OR medication. Publication type was limited to Meta-analysis. Extract the relevant information of Meta-analysis, such as characteristics of objects, types of study design, number of clinical trials, number of cases, search strategies, databases, information of methodology (methods of randomization, concealment, blinding, withdrawal and exit, follow-up time, heterogeneity analysis, subgroup analysis and outcome assessment, etc. Quality of Reporting of Meta-analyses (QUOROM and Oxman-Guyatt Overview Quality Assessment Questionnaire (OQAQ were used to assess the quality of included Meta-analyses. Jadad decision was used to assess inclusion and exclusion criteria, search strategies, effectiveness evaluation, data extraction and data analysis, to explore reliable evidence of evidence-based medicine.  Results Eventually, four Meta-analyses were included after screening of all the literatures that can be searched out. Among those Meta-analyses, the Meta-analysis of Offringa and Newton (2012 was relatively more reliable. The results suggesed that no clinically important benefits were found in administering intermittent oral or rectal diazepam, oral phenobarbitone, phenytoin, valproate, pyridoxine, buprofen, diclofenac and acetominophen to children with FE. Only one clinical trial reported that intermittent oral clobazam could reduce the recurrence of FE in comparing with placebo at 6-month follow-up (RR = 0.360, 95% CI: 0.200-0.640; P = 0.000, but it should be verified by more randomized controlled trials (RCTs. Among 4 Meta-analyses included in this study

Prediction of Smoking, Alcohol, Drugs, and Psychoactive Drugs Abuse Based on Emotional Dysregulation and Child Abuse Experience in People with Borderline Personality Traits

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M GannadiFarnood

2014-12-01

Full Text Available Objective: This research was an attempt to predict the tendency of people having borderline personality traits to smoking, drinking alcohol, and taking psychoactive drugs based on emotional dysregulation and child abuse. Method: This study employed a correlation method which is categorized in descriptive category. A sample including 600 male and female bachelor students of Tabriz University was selected by cluster sampling. Then, high risk behaviors scale, Emotional dysregulation Scale, Child abuse scale, and borderline personality scale (STB were distributed among this group. Findings: Stepwise multiple regression analysis suggested that emotional dysregulation and child abuse significantly predicted varying degrees of smoking, drug, and alcohol usage. Conclusion: The research findings suggest the basic role of initial biological vulnerability in terms of emotional regulation (dysregulation and invalidating family environment (child abuse in the prediction of catching the disorder of borderline personality traits and producing high riskbehaviorssuch as alcohol drink and drug usage.

The Use of Gene Ontology Term and KEGG Pathway Enrichment for Analysis of Drug Half-Life.

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Yu-Hang Zhang

Full Text Available A drug's biological half-life is defined as the time required for the human body to metabolize or eliminate 50% of the initial drug dosage. Correctly measuring the half-life of a given drug is helpful for the safe and accurate usage of the drug. In this study, we investigated which gene ontology (GO terms and biological pathways were highly related to the determination of drug half-life. The investigated drugs, with known half-lives, were analyzed based on their enrichment scores for associated GO terms and KEGG pathways. These scores indicate which GO terms or KEGG pathways the drug targets. The feature selection method, minimum redundancy maximum relevance, was used to analyze these GO terms and KEGG pathways and to identify important GO terms and pathways, such as sodium-independent organic anion transmembrane transporter activity (GO:0015347, monoamine transmembrane transporter activity (GO:0008504, negative regulation of synaptic transmission (GO:0050805, neuroactive ligand-receptor interaction (hsa04080, serotonergic synapse (hsa04726, and linoleic acid metabolism (hsa00591, among others. This analysis confirmed our results and may show evidence for a new method in studying drug half-lives and building effective computational methods for the prediction of drug half-lives.

Drug Synthesis and Analysis on a Dime: A Capstone Medicinal Chemistry Experience for the Undergraduate Biochemistry Laboratory

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Streu, Craig N.; Reif, Randall D.; Neiles, Kelly Y.; Schech, Amanda J.; Mertz, Pamela S.

2016-01-01

Integrative, research-based experiences have shown tremendous potential as effective pedagogical approaches. Pharmaceutical development is an exciting field that draws heavily on organic chemistry and biochemistry techniques. A capstone drug synthesis/analysis laboratory is described where biochemistry students synthesize azo-stilbenoid compounds…

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

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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.

Data-driven prediction of adverse drug reactions induced by drug-drug interactions.

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Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Kumar, Kamal; Yu, Xueping; Wallqvist, Anders; Reifman, Jaques

2017-06-08

The expanded use of multiple drugs has increased the occurrence of adverse drug reactions (ADRs) induced by drug-drug interactions (DDIs). However, such reactions are typically not observed in clinical drug-development studies because most of them focus on single-drug therapies. ADR reporting systems collect information on adverse health effects caused by both single drugs and DDIs. A major challenge is to unambiguously identify the effects caused by DDIs and to attribute them to specific drug interactions. A computational method that provides prospective predictions of potential DDI-induced ADRs will help to identify and mitigate these adverse health effects. We hypothesize that drug-protein interactions can be used as independent variables in predicting ADRs. We constructed drug pair-protein interaction profiles for ~800 drugs using drug-protein interaction information in the public domain. We then constructed statistical models to score drug pairs for their potential to induce ADRs based on drug pair-protein interaction profiles. We used extensive clinical database information to construct categorical prediction models for drug pairs that are likely to induce ADRs via synergistic DDIs and showed that model performance deteriorated only slightly, with a moderate amount of false positives and false negatives in the training samples, as evaluated by our cross-validation analysis. The cross validation calculations showed an average prediction accuracy of 89% across 1,096 ADR models that captured the deleterious effects of synergistic DDIs. Because the models rely on drug-protein interactions, we made predictions for pairwise combinations of 764 drugs that are currently on the market and for which drug-protein interaction information is available. These predictions are publicly accessible at http://avoid-db.bhsai.org . We used the predictive models to analyze broader aspects of DDI-induced ADRs, showing that ~10% of all combinations have the potential to induce ADRs

CRITICAL ASSESSMENT OF CONTRIBUTION FROM INDIAN PUBLICATIONS: THE ROLE OF IN SILICO DESIGNING METHODS LEADING TO DRUGS OR DRUG-LIKE COMPOUNDS USING TEXT BASED MINING AND ASSOCIATION

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Pawan Kumar

2017-09-01

Full Text Available Over the several decades, India is constantly challenged by communicable and non-communicable diseases which are originated either by poor lifestyle or by environmental factors. The pools of diseases are constantly posing serious threats to mankind especially among the poverty-stricken families. Scientific communities across the globe are working continuously to design drug molecules to overcome the burden of these life threaten diseases. In last three decades, many computational algorithms and tools have been developed to identify potential drug targets and their inhibitors. It is believed that computational techniques have reduced the time and money required to develop an inhibitor into drug. However, applicability and deliverability of these in silico techniques in rational drug designing are not fully evaluated. In the present study, PubMed/Medline extracted data driven analysis has been performed to highlight the influence and progress of the theoretical methods in the field of drug discovery across India and compared with the world. Drug discovery related keyword dictionary has been built and utilized to select only drug discovery related PubMed abstract. A second keyword set (related to bioinformatics tools is used for normalized pointwise mutual information (PMI based association analysis. Observations show that drug discovery has been an interdisciplinary research and used many tools starting with QSAR, docking, pharmacophore, Molecular Simulations etc. The publications contributed from India (2% are similar as compared to the contribution in total world publications, suggesting large scope in future. Data coverage as represented since 1990-2015 in PubMed as indicated by number of publications associated with drug discovery is almost same in world and India (~75%. Emerging institutes/Universities are contributing since last 10 years as observed from Indian publication list. However, this method has many limitations as discussed.

Additivity versus repair inhibition in fractionated treatments combining drugs and X rays: a theoretical analysis

International Nuclear Information System (INIS)

Begg, A.C.

1987-01-01

Drugs which inhibit the repair of radiation damage could potentially be useful for enhancing the effects of radiotherapy. In pre-clinical combined modality studies, however, it is often difficult to state with certainty whether or not a drug has inhibited radiation damage repair. This paper shows that several commonly used parameters for assessing repair can give the wrong answer regarding the presence of drug-induced repair inhibition. These parameters are; the difference in radiation dose between 1 and n fractions to give the same effect, the fractional recovered dose per fraction interval, FR, and the related parameter FREC. A further parameter used for treatment comparisons is the enhancement ratio for the drug (D.E.R.; ratio of radiation doses, with and without drug, to cause a given effect). An increasing D.E.R. with increasing number of radiation fractions has been taken as an indication that the drug inhibited repair. The present report demonstrates that this, too, can be misleading. From an analysis based on a linear-quadratic survival curve for X rays, it is suggested that deriving and comparing alpha/beta ratios (ratio of the linea to quadratic coefficients) gives the best indication of drug-induced changes in survival curve shape which may reflect underlying changes in repair capacity

MONITORING POTENTIAL DRUG INTERACTIONS AND REACTIONS VIA NETWORK ANALYSIS OF INSTAGRAM USER TIMELINES

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CORREIA, RION BRATTIG; LI, LANG; ROCHA, LUIS M.

2015-01-01

Much recent research aims to identify evidence for Drug-Drug Interactions (DDI) and Adverse Drug reactions (ADR) from the biomedical scientific literature. In addition to this “Bibliome”, the universe of social media provides a very promising source of large-scale data that can help identify DDI and ADR in ways that have not been hitherto possible. Given the large number of users, analysis of social media data may be useful to identify under-reported, population-level pathology associated with DDI, thus further contributing to improvements in population health. Moreover, tapping into this data allows us to infer drug interactions with natural products—including cannabis—which constitute an array of DDI very poorly explored by biomedical research thus far. Our goal is to determine the potential of Instagram for public health monitoring and surveillance for DDI, ADR, and behavioral pathology at large. Most social media analysis focuses on Twitter and Facebook, but Instagram is an increasingly important platform, especially among teens, with unrestricted access of public posts, high availability of posts with geolocation coordinates, and images to supplement textual analysis. Using drug, symptom, and natural product dictionaries for identification of the various types of DDI and ADR evidence, we have collected close to 7000 user timelines spanning from October 2010 to June 2015. We report on 1) the development of a monitoring tool to easily observe user-level timelines associated with drug and symptom terms of interest, and 2) population-level behavior via the analysis of co-occurrence networks computed from user timelines at three different scales: monthly, weekly, and daily occurrences. Analysis of these networks further reveals 3) drug and symptom direct and indirect associations with greater support in user timelines, as well as 4) clusters of symptoms and drugs revealed by the collective behavior of the observed population. This demonstrates that

New indicators of illegal drug use to compare drug user populations for policy evaluation

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Francesco Fabi

2013-11-01

Full Text Available Background: New trends in drug consumption show a trend towards higher poly-use. Epidemiological indicators presently used are mostly based on the prevalence of users of the “main” substances and the ranking of harm caused by drug use is based on a single substance analysis.Methods: In this paper new indicators are proposed; the approach consider the segmentation of the population with respect to the frequency of use in the last 30 days and the harm score of the various substances used by a poly-user. Scoring is based on single substance score table reported in recent papers and principal component analysis is applied to reduce dimensionality. Any user ischaracterized by the two new scores: frequency of use score and poly-use score.Results: The method is applied to the drug user populations interviewed in Communities and Low Threshold Services within the Problem Drug Use 2012 survey in four different European countries. The comparison of the poly-use score cumulative distributions gives insight about behavioural trends of drug use and also evaluate the efficacy of the intervention services. Furthermore, the application of this method to School Population Survey 2011 data allows a definition of the expected behaviour of the poly-drug score for the General Population Survey to be representative.Conclusions: In general, the method is simply and intuitive, and could be applied to surveys containing questions about drug use. A possible limitations could be that the median is chosen for calculating the frequency of use score in questionnaires containing the frequency of drug use in classes.

Fabrication and characterization of sol-gel based nanoparticles for drug delivery

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Yadav, Reeta

Nanogels are cross linked polymeric sol-gel based nanoparticles that offer an interior network for incorporation and protection of biomolecules, exhibiting unique advantages for polymer based delivery systems. We have successfully synthesized stable sol-gel nanoparticles by means of [a] silicification reactions using cationic peptides like polylysine as gelating agents, and [b] lyophilization of sol-gels. Macromolecules such as Hemoglobin and Glucose Oxidase and small molecules such as Sodium Nitroprusside (SNP) and antibiotics were encapsulated within the nanogels. We have used transmission electron microscopy, dynamic light scattering, zeta potential analysis, and spectroscopy to perform a physicochemical characterization of the nanogels resulting from the two approaches. Our studies have indicated that the nanogel encapsulated proteins and small molecules remain intact, stable and functional. A Hydrogen Peroxide (H2O2) and Nitric Oxide (NO) generating drug carrier was synthesized using these nanogels and the effect of generation of H2O2 from Glucose Oxidase encapsulated nanogels and NO from SNP encapsulated nanogels was tested on E.coli. The results show that the nanoparticles exert antimicrobial activity against E.Coli, in addition NO generating nanogels potentiated H2O2 generating nanogels induced killing. These data suggest that these NO and H2O2 releasing nanogels have the potential to serve as a novel class of antimicrobials for the treatment of multidrug resistant bacteria. The unique properties of these protein/drug incorporated nanogels raise the prospect of fine tailoring to specific applications such as drug delivery and bio imaging.

Microbial and chemical analysis of illicit drugs samples confiscated from different areas of PakistanMicrobial and chemical analysis of illicit drugs samples confiscated from different areas of Pakistan.

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Hussain, Shahzad; Khattak, Zainab; Mahmood, Sidra; Malik, Farnaz; Riaz, Humayun; Raza, Syed Atif; Khan, Samiullah

2016-09-01

The microbial and chemical analysis of illicit drug samples from different areas of Pakistan i.e. Quetta, Karachi, Lahore and Islamabad was conducted in a cross-sectional study at National Institute of Health, Islamabad. The drug samples were confiscated by Anti Narcotics Force (ANF), Pakistan. Microbial analysis was done by estimating bioburden which revealed the presence of gram negative and positive bacteria's, fungus, Streptococcus, Staphylococcus species. Trypton soya agar was used for total aerobic count, MacConkey agar for gram-negative bacteria, Sabouraud dextrose agar for fungus and Vogel-Johnson agar for Streptococcus and Staphylococcus species. Colour tests were applied to identify the drug samples. Qualitative and quantitative analysis of suspected samples of Heroin, morphine, cocaine and acetic anhydride was made by employing different chromatographic techniques i.e. Thin-layer chromatography (TLC) and High-performance liquid chromatography (HPLC). The samples were found to be adulterated with paracetamol, diazepam and Dextromethorphen. Acetic anhydride was adulterated with hydrochloric acid (HCl). There is lack of information providing structured advice on responses to the consequences of illicit drug adulteration. Robust and rehearsed interventions and communication strategies would provide a basis for response for a wide variety of organisations. Research into the usefulness of media warnings about adulteration of illicit drugs is required.

Chitosan/alginate based multilayers to control drug release fromophthalmic lens

OpenAIRE

Silva, Diana; Pinto, Luís F. V.; Bozukova, Dimitriya; Santos, Luís F.; Serro, Ana Paula; Saramago, Benilde

2016-01-01

In this study we investigated the possibility of using layer-by-layer deposition, based in natural polymers (chitosan and alginate), to control the release of different ophthalmic drugs from three types of lens materials: a silicone-based hydrogel recently proposed by our group as drug releasing soft contact lens (SCL) material and two commercially available materials: CI26Y for intraocular lens (IOLs) and Definitive 50 for SCLs. The optimised coating, consisting in one double layer of (algin...

Network-based analysis of proteomic profiles

KAUST Repository

Wong, Limsoon

2016-01-26

Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

Nanoparticle-based drug delivery systems: promising approaches against infections

International Nuclear Information System (INIS)

Ranghar, Shweta; Sirohi, Parul; Verma, Pritam; Agarwal, Vishnu

2014-01-01

Despite the fact that many new drugs and technologies have been developed to combat the infectious diseases, these have continued to be global health challenges. The use of conventional antimicrobial agents against these infections is always associated with problems such as the development of multiple drug resistance and adverse side effects. In addition, the inefficient traditional drug delivery system results in inadequate therapeutic index, low bioavailability of drugs and many other limitations. In this regard, antimicrobial nanoparticles and nanosized drug delivery carriers have emerged as potent effective agents against the infections. Nanoparticles have unique properties owing to their ultra small and controllable size such as high surface area, enhanced reactivity, and functionalizable structure. This review focused on different classes of antimicrobial nanoparticles, including metal, metal oxide and others along with their mechanism of action and their potential use against the infections. The review also focused on the development of nanoparticle systems for antimicrobial drug delivery and use of these systems for delivery of various antimicrobial agents, giving an overview about modern nanoparticle based therapeutic strategies against the infections. (author)

Nanoparticle-based drug delivery systems: promising approaches against infections

Energy Technology Data Exchange (ETDEWEB)

Ranghar, Shweta; Sirohi, Parul [Department of Applied Mechanics, Motilal Nehru National Institute of Technology, Allahabad (India); Verma, Pritam; Agarwal, Vishnu [Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad (India)

2014-03-15

Despite the fact that many new drugs and technologies have been developed to combat the infectious diseases, these have continued to be global health challenges. The use of conventional antimicrobial agents against these infections is always associated with problems such as the development of multiple drug resistance and adverse side effects. In addition, the inefficient traditional drug delivery system results in inadequate therapeutic index, low bioavailability of drugs and many other limitations. In this regard, antimicrobial nanoparticles and nanosized drug delivery carriers have emerged as potent effective agents against the infections. Nanoparticles have unique properties owing to their ultra small and controllable size such as high surface area, enhanced reactivity, and functionalizable structure. This review focused on different classes of antimicrobial nanoparticles, including metal, metal oxide and others along with their mechanism of action and their potential use against the infections. The review also focused on the development of nanoparticle systems for antimicrobial drug delivery and use of these systems for delivery of various antimicrobial agents, giving an overview about modern nanoparticle based therapeutic strategies against the infections. (author)

Statistical Analysis of a Method to Predict Drug-Polymer Miscibility

DEFF Research Database (Denmark)

Knopp, Matthias Manne; Olesen, Niels Erik; Huang, Yanbin

2016-01-01

In this study, a method proposed to predict drug-polymer miscibility from differential scanning calorimetry measurements was subjected to statistical analysis. The method is relatively fast and inexpensive and has gained popularity as a result of the increasing interest in the formulation of drug...... as provided in this study. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci....

High-resolution two-dimensional liquid chromatography analysis of key linker drug intermediate used in antibody drug conjugates.

Science.gov (United States)

Venkatramani, C J; Huang, Shu Rong; Al-Sayah, Mohammad; Patel, Ila; Wigman, Larry

2017-10-27

In this manuscript, the application of high-resolution sampling (HRS) two-dimensional liquid chromatography (2D-LC) in the detailed analysis of key linker drug intermediate is presented. Using HRS, selected regions of the primary column eluent were transferred to a secondary column with fidelity enabling qualitative and quantitative analysis of linker drugs. The primary column purity of linker drug intermediate ranged from 88.9% to 94.5% and the secondary column purity ranged from 99.6% to 99.9%, showing lot-to-lot variability, significant differences between the three lots, and substantiating the synthetic and analytical challenges of ADCs. Over 15 impurities co-eluting with the linker drug intermediate in the primary dimension were resolved in the secondary dimension. The concentrations of most of these impurities were over three orders of magnitude lower than the linker drug. Effective peak focusing and high-speed secondary column analysis resulted in sharp peaks in the secondary dimension, improving the signal-to-noise ratios. The sensitivity of 2D-LC separation was over five fold better than conventional HPLC separation. The limit of quantitation (LOQ) was less than 0.01%. Many peaks originating from primary dimension were resolved into multiple components in the complementary secondary dimension, demonstrating the complexity of these samples. The 2D-LC was highly reproducible, showing good precision between runs with%RSD of peak areas less than 0.1 for the main component. The absolute difference in the peak areas of impurities less than 0.1% were within ±0.01% and for impurities in the range of 0.1%-0.3%, the absolute difference were ±0.02%, which are comparable to 1D-LC. The overall purity of the linker drug intermediate was determined from the product of primary and secondary column purity (HPLC Purity=%peak area of main component in the primary dimension×%peak area of main component in the secondary dimension). Additionally, the 2D-LC separation enables

Quantitative Analysis of Therapeutic Drugs in Dried Blood Spot Samples by Paper Spray Mass Spectrometry: An Avenue to Therapeutic Drug Monitoring

Science.gov (United States)

Manicke, Nicholas Edward; Abu-Rabie, Paul; Spooner, Neil; Ouyang, Zheng; Cooks, R. Graham

2011-09-01

A method is presented for the direct quantitative analysis of therapeutic drugs from dried blood spot samples by mass spectrometry. The method, paper spray mass spectrometry, generates gas phase ions directly from the blood card paper used to store dried blood samples without the need for complex sample preparation and separation; the entire time for preparation and analysis of blood samples is around 30 s. Limits of detection were investigated for a chemically diverse set of some 15 therapeutic drugs; hydrophobic and weakly basic drugs, such as sunitinib, citalopram, and verapamil, were found to be routinely detectable at approximately 1 ng/mL. Samples were prepared by addition of the drug to whole blood. Drug concentrations were measured quantitatively over several orders of magnitude, with accuracies within 10% of the expected value and relative standard deviation (RSD) of around 10% by prespotting an internal standard solution onto the paper prior to application of the blood sample. We have demonstrated that paper spray mass spectrometry can be used to quantitatively measure drug concentrations over the entire therapeutic range for a wide variety of drugs. The high quality analytical data obtained indicate that the technique may be a viable option for therapeutic drug monitoring.

Drug loading optimization and extended drug delivery of corticoids from pHEMA based soft contact lenses hydrogels via chemical and microstructural modifications.

Science.gov (United States)

García-Millán, Eva; Koprivnik, Sandra; Otero-Espinar, Francisco Javier

2015-06-20

This paper proposes an approach to improve drug loading capacity and release properties of poly(2-hydroxyethyl methacrylate) (p(HEMA)) soft contact lenses based on the optimization of the hydrogel composition and microstructural modifications using water during the polymerization process. P(HEMA) based soft contact lenses were prepared by thermal or photopolymerization of 2-hydroxyethyl methacrylate (HEMA) solutions containing ethylene glycol di-methacrylate as crosslinker and different proportions of N-vinyl-2-pyrrolidone (NVP) or methacrylic acid (MA) as co-monomers. Transmittance, water uptake, swelling, microstructure, drug absorption isotherms and in vitro release were characterized using triamcinolone acetonide (TA) as model drug. Best drug loading ratios were obtained with lenses containing the highest amount (200 mM) of MA. Incorporation of 40% V/V of water during the polymerization increases the hydrogel porosity giving a better drug loading capacity. In vitro TA release kinetics shows that MA hydrogels released the drug significantly faster than NVP-hydrogels. Drug release was found to be diffusion controlled and kinetics was shown to be reproducible after consecutive drug loading/release processes. Results of p(HEMA) based soft contact lenses copolymerized with ethylene glycol dimethacrylate (EGDMA) and different co-monomers could be a good alternative to optimize the loading and ocular drug delivery of this corticosteroid drug. Copyright © 2015. Published by Elsevier B.V.

[Failure mode and effects analysis on computerized drug prescriptions].

Science.gov (United States)

Paredes-Atenciano, J A; Roldán-Aviña, J P; González-García, Mercedes; Blanco-Sánchez, M C; Pinto-Melero, M A; Pérez-Ramírez, C; Calvo Rubio-Burgos, Miguel; Osuna-Navarro, F J; Jurado-Carmona, A M

2015-01-01

To identify and analyze errors in drug prescriptions of patients treated in a "high resolution" hospital by applying a Failure mode and effects analysis (FMEA).Material and methods A multidisciplinary group of medical specialties and nursing analyzed medical records where drug prescriptions were held in free text format. An FMEA was developed in which the risk priority index (RPI) was obtained from a cross-sectional observational study using an audit of the medical records, carried out in 2 phases: 1) Pre-intervention testing, and (2) evaluation of improvement actions after the first analysis. An audit sample size of 679 medical records from a total of 2,096 patients was calculated using stratified sampling and random selection of clinical events. Prescription errors decreased by 22.2% in the second phase. FMEA showed a greater RPI in "unspecified route of administration" and "dosage unspecified", with no significant decreases observed in the second phase, although it did detect, "incorrect dosing time", "contraindication due to drug allergy", "wrong patient" or "duplicate prescription", which resulted in the improvement of prescriptions. Drug prescription errors have been identified and analyzed by FMEA methodology, improving the clinical safety of these prescriptions. This tool allows updates of electronic prescribing to be monitored. To avoid such errors would require the mandatory completion of all sections of a prescription. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Cathepsin B Cleavage of vcMMAE-Based Antibody-Drug Conjugate Is Not Drug Location or Monoclonal Antibody Carrier Specific.

Science.gov (United States)

Gikanga, Benson; Adeniji, Nia S; Patapoff, Thomas W; Chih, Hung-Wei; Yi, Li

2016-04-20

Antibody-drug conjugates (ADCs) require thorough characterization and understanding of product quality attributes. The framework of many ADCs comprises one molecule of antibody that is usually conjugated with multiple drug molecules at various locations. It is unknown whether the drug release rate from the ADC is dependent on drug location, and/or local environment, dictated by the sequence and structure of the antibody carrier. This study addresses these issues with valine-citrulline-monomethylauristatin E (vc-MMAE)-based ADC molecules conjugated at reduced disulfide bonds, by evaluating the cathepsin B catalyzed drug release rate of ADC molecules with different drug distributions or antibody carriers. MMAE drug release rates at different locations on ADC I were compared to evaluate the impact of drug location. No difference in rates was observed for drug released from the V(H), V(L), or C(H)2 domains of ADC I. Furthermore, four vc-MMAE ADC molecules were chosen as substrates for cathepsin B for evaluation of Michaelis-Menten parameters. There was no significant difference in K(M) or k(cat) values, suggesting that different sequences of the antibody carrier do not result in different drug release rates. Comparison between ADCs and small molecules containing vc-MMAE moieties as substrates for cathepsin B suggests that the presence of IgG1 antibody carrier, regardless of its bulkiness, does not impact drug release rate. Finally, a molecular dynamics simulation on ADC II revealed that the val-cit moiety at each of the eight possible conjugation sites was, on average, solvent accessible over 50% of its maximum solvent accessible surface area (SASA) during a 500 ns trajectory. Combined, these results suggest that the cathepsin cleavage sites for conjugated drugs are exposed enough for the enzyme to access and that the drug release rate is rather independent of drug location or monoclonal antibody carrier. Therefore, the distribution of drug conjugation at different

Drug treatment or alleviating the negative consequences of imprisonment? A critical view of prison-based drug treatment in Denmark.

Science.gov (United States)

Kolind, Torsten; Frank, Vibeke Asmussen; Dahl, Helle

2010-01-01

The availability of prison-based drug treatment has increased markedly throughout Europe over the last 15 years in terms of both volume and programme diversity. However, prison drug treatment faces problems and challenges because of the tension between ideologies of rehabilitation and punishment. This article reports on a study of four cannabis treatment programmes and four psychosocial drug treatment programmes in four Danish prisons during 2007. The data include the transcripts of 22 semi-structured qualitative interviews with counsellors and prison employees, prison statistics, and information about Danish laws and regulations. These treatment programmes reflect the 'treatment guarantee' in Danish prisons. However, they are simultaneously embedded in a new policy of zero tolerance and intensified disciplinary sanctions. This ambivalence is reflected in the experiences of treatment counsellors: reluctantly, they feel associated with the prison institution in the eyes of the prisoners; they experience severe opposition from prison officers; and the official goals of the programmes, such as making clients drug free and preparing them for a life without crime, are replaced by more pragmatic aims such as alleviating the pain of imprisonment felt by programme clients. The article concludes that at a time when prison-based drug treatment is growing, it is crucial that we thoroughly research and critically discuss its content and the restrictions facing such treatment programmes. One way of doing this is through research with counsellors involved in delivering drug treatment services. By so doing, the programmes can become more pragmatic and focused, and alternatives to prison-based drug treatment can be seriously considered.

Redox-based Epigenetic status in Drug Addiction: Potential mediator of drug-induced gene priming phenomenon and use of metabolic intervention for symptomatic treatment in drug addiction.

Directory of Open Access Journals (Sweden)

Malav Suchin Trivedi

2015-01-01

Full Text Available Alcohol and other drugs of abuse, including psychostimulants and opioids, can induce epigenetic changes: a contributing factor for drug addiction, tolerance and associated withdrawal symptoms. DNA methylation is the major epigenetic mechanism and it is one of more than 200 methylation reactions supported by methyl donor S-adenosylmethionine (SAM. The levels of SAM are controlled by cellular redox status via the folate and vitamin B12-dependent enzyme methionine synthase (MS, for example; under oxidative conditions MS is inhibited, diverting its substrate homocysteine (HCY to the transsulfuration pathway. Alcohol, dopamine and morphine, can alter intracellular levels of glutathione (GSH-based cellular redox status, subsequently affecting S-adenosylmethionine (SAM levels and DNA methylation status. In this discussion, we compile this and other existing evidence in a coherent manner to present a novel hypothesis implicating the involvement of redox-based epigenetic changes in drug addiction. Next, we also discuss how gene priming phenomenon can contribute to maintenance of redox and methylation status homeostasis under various stimuli including drugs of abuse. Lastly, based on our hypothesis and some preliminary evidence, we discuss a mechanistic explanation for use of metabolic interventions / redox-replenishers as symptomatic treatment of alcohol addiction and associated withdrawal symptoms. Hence, the current review article strengthens the hypothesis that neuronal metabolism has a critical bidirectional coupling with epigenetic changes in drug addiction and we support this claim via exemplifying the link between redox-based metabolic changes and resultant epigenetic consequences under the effect of drugs of abuse.

Polysaccharide-Based Micelles for Drug Delivery

Directory of Open Access Journals (Sweden)

Nan Zhang

2013-05-01

Full Text Available Delivery of hydrophobic molecules and proteins has been an issue due to poor bioavailability following administration. Thus, micelle carrier systems are being investigated to improve drug solubility and stability. Due to problems with toxicity and immunogenicity, natural polysaccharides are being explored as substitutes for synthetic polymers in the development of new micelle systems. By grafting hydrophobic moieties to the polysaccharide backbone, self-assembled micelles can be readily formed in aqueous solution. Many polysaccharides also possess inherent bioactivity that can facilitate mucoadhesion, enhanced targeting of specific tissues, and a reduction in the inflammatory response. Furthermore, the hydrophilic nature of some polysaccharides can be exploited to enhance circulatory stability. This review will highlight the advantages of polysaccharide use in the development of drug delivery systems and will provide an overview of the polysaccharide-based micelles that have been developed to date.

A sight on protein-based nanoparticles as drug/gene delivery systems.

Science.gov (United States)

Salatin, Sara; Jelvehgari, Mitra; Maleki-Dizaj, Solmaz; Adibkia, Khosro

2015-01-01

Polymeric nanomaterials have extensively been applied for the preparation of targeted and controlled release drug/gene delivery systems. However, problems involved in the formulation of synthetic polymers such as using of the toxic solvents and surfactants have limited their desirable applications. In this regard, natural biomolecules including proteins and polysaccharide are suitable alternatives due to their safety. According to literature, protein-based nanoparticles possess many advantages for drug and gene delivery such as biocompatibility, biodegradability and ability to functionalize with targeting ligands. This review provides a general sight on the application of biodegradable protein-based nanoparticles in drug/gene delivery based on their origins. Their unique physicochemical properties that help them to be formulated as pharmaceutical carriers are also discussed.

Microfluidic-Based Synthesis of Hydrogel Particles for Cell Microencapsulation and Cell-Based Drug Delivery

Directory of Open Access Journals (Sweden)

Jiandi Wan

2012-04-01

Full Text Available Encapsulation of cells in hydrogel particles has been demonstrated as an effective approach to deliver therapeutic agents. The properties of hydrogel particles, such as the chemical composition, size, porosity, and number of cells per particle, affect cellular functions and consequently play important roles for the cell-based drug delivery. Microfluidics has shown unparalleled advantages for the synthesis of polymer particles and been utilized to produce hydrogel particles with a well-defined size, shape and morphology. Most importantly, during the encapsulation process, microfluidics can control the number of cells per particle and the overall encapsulation efficiency. Therefore, microfluidics is becoming the powerful approach for cell microencapsulation and construction of cell-based drug delivery systems. In this article, I summarize and discuss microfluidic approaches that have been developed recently for the synthesis of hydrogel particles and encapsulation of cells. I will start by classifying different types of hydrogel material, including natural biopolymers and synthetic polymers that are used for cell encapsulation, and then focus on the current status and challenges of microfluidic-based approaches. Finally, applications of cell-containing hydrogel particles for cell-based drug delivery, particularly for cancer therapy, are discussed.

Albumin-based drug delivery: harnessing nature to cure disease.

Science.gov (United States)

Larsen, Maja Thim; Kuhlmann, Matthias; Hvam, Michael Lykke; Howard, Kenneth A

2016-01-01

The effectiveness of a drug is dependent on accumulation at the site of action at therapeutic levels, however, challenges such as rapid renal clearance, degradation or non-specific accumulation requires drug delivery enabling technologies. Albumin is a natural transport protein with multiple ligand binding sites, cellular receptor engagement, and a long circulatory half-life due to interaction with the recycling neonatal Fc receptor. Exploitation of these properties promotes albumin as an attractive candidate for half-life extension and targeted intracellular delivery of drugs attached by covalent conjugation, genetic fusions, association or ligand-mediated association. This review will give an overview of albumin-based products with focus on the natural biological properties and molecular interactions that can be harnessed for the design of a next-generation drug delivery platform.

The application of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the stratum corneum.

Science.gov (United States)

Goh, Choon Fu; Craig, Duncan Q M; Hadgraft, Jonathan; Lane, Majella E

2017-02-01

Drug permeation through the intercellular lipids, which pack around and between corneocytes, may be enhanced by increasing the thermodynamic activity of the active in a formulation. However, this may also result in unwanted drug crystallisation on and in the skin. In this work, we explore the combination of ATR-FTIR spectroscopy and multivariate data analysis to study drug crystallisation in the skin. Ex vivo permeation studies of saturated solutions of diclofenac sodium (DF Na) in two vehicles, propylene glycol (PG) and dimethyl sulphoxide (DMSO), were carried out in porcine ear skin. Tape stripping and ATR-FTIR spectroscopy were conducted simultaneously to collect spectral data as a function of skin depth. Multivariate data analysis was applied to visualise and categorise the spectral data in the region of interest (1700-1500cm -1 ) containing the carboxylate (COO - ) asymmetric stretching vibrations of DF Na. Spectral data showed the redshifts of the COO - asymmetric stretching vibrations for DF Na in the solution compared with solid drug. Similar shifts were evident following application of saturated solutions of DF Na to porcine skin samples. Multivariate data analysis categorised the spectral data based on the spectral differences and drug crystallisation was found to be confined to the upper layers of the skin. This proof-of-concept study highlights the utility of ATR-FTIR spectroscopy in combination with multivariate data analysis as a simple and rapid approach in the investigation of drug deposition in the skin. The approach described here will be extended to the study of other actives for topical application to the skin. Copyright © 2016 Elsevier B.V. All rights reserved.

Priority setting for orphan drugs: an international comparison.

Science.gov (United States)

Rosenberg-Yunger, Zahava R S; Daar, Abdallah S; Thorsteinsdóttir, Halla; Martin, Douglas K

2011-04-01

To describe the process of priority setting for two orphan drugs - Cerezyme and Fabrazyme - in Canada, Australia and Israel, in order to understand and improve the process based on stakeholder perspectives. We conducted qualitative case studies of how three independent drug advisory committees made decisions relating to the funding of Cerezyme and Fabrazyme. Interviews were conducted with 22 informants, including committee members, patient groups and industry representatives. (1) DESCRIPTION: Orphan drugs reimbursement recommendations by expert panels were based on clinical evidence, cost and cost-effectiveness analysis. (2) EVALUATION: Committee members expressed an overall preference for the current drug review process used by their own committee, but were concerned with the fairness of the process particularly for orphan drugs. Other informants suggested the inclusion of other relevant values (e.g. lack of alternative treatments) in order to improve the priority setting process. Some patient groups suggested the use of an alternative funding mechanism for orphan drugs. Priority setting for drugs is not solely a technical process (involving cost-effective analysis, evidence-based medicine, etc.). Understanding the process by which reimbursement decisions are made for orphan drugs may help improve the system for future orphan drugs. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

A further component analysis for illicit drugs mixtures with THz-TDS

Science.gov (United States)

Xiong, Wei; Shen, Jingling; He, Ting; Pan, Rui

2009-07-01

A new method for quantitative analysis of mixtures of illicit drugs with THz time domain spectroscopy was proposed and verified experimentally. In traditional method we need fingerprints of all the pure chemical components. In practical as only the objective components in a mixture and their absorption features are known, it is necessary and important to present a more practical technique for the detection and identification. Our new method of quantitatively inspect of the mixtures of illicit drugs is developed by using derivative spectrum. In this method, the ratio of objective components in a mixture can be obtained on the assumption that all objective components in the mixture and their absorption features are known but the unknown components are not needed. Then methamphetamine and flour, a illicit drug and a common adulterant, were selected for our experiment. The experimental result verified the effectiveness of the method, which suggested that it could be an effective method for quantitative identification of illicit drugs. This THz spectroscopy technique is great significant in the real-world applications of illicit drugs quantitative analysis. It could be an effective method in the field of security and pharmaceuticals inspection.

Drug Delivery to CNS: Challenges and Opportunities with Emphasis on Biomaterials Based Drug Delivery Strategies.

Science.gov (United States)

Khambhla, Ekta; Shah, Viral; Baviskar, Kalpesh

2016-01-01

The current epoch has witnessed a lifestyle impregnated with stress, which is a major cause of several neurological disorders. High morbidity and mortality rate due to neurological diseases and disorders have generated a huge social impact. Despite voluminous research, patients suffering from fatal and/or debilitating CNS diseases such as brain tumors, HIV, encephalopathy, Alzheimer's, epilepsy, Parkinson's, migraine and multiple sclerosis outnumbered those suffering from systemic cancer or heart diseases. The brain being a highly sensitive neuronal organ, has evolved with vasculature barriers, which regulates the efflux and influx of substances to CNS. Treatment of CNS diseases/disorders is challenging because of physiologic, metabolic and biochemical obstacles created by these barriers which comprise mainly of BBB and BCFB. The inability of achieving therapeutically active concentration has become the bottleneck level difficulty, hampering the therapeutic efficiency of several promising drug candidates for CNS related disorders. Parallel maturation of an effective CNS drug delivery strategy with CNS drug discovery is the need of the hour. Recently, the focus of the pharmaceutical community has aggravated in the direction of developing novel and more efficient drug delivery systems, giving the potential of more effective and safer CNS therapies. The present review outlines several hurdles in drug delivery to the CNS along with ideal physicochemical properties desired in drug substance/formulation for CNS delivery. The review also focuses on different conventional and novel strategies for drug delivery to the CNS. The article also assesses and emphasizes on possible benefits of biomaterial based formulations for drug delivery to the CNS.

Recent Trends in Nanotechnology-Based Drugs and Formulations for Targeted Therapeutic Delivery.

Science.gov (United States)

Iqbal, Hafiz M N; Rodriguez, Angel M V; Khandia, Rekha; Munjal, Ashok; Dhama, Kuldeep

2017-01-01

In the recent past, a wider spectrum of nanotechnologybased drugs or drug-loaded devices and systems has been engineered and investigated with high interests. The key objective is to help for an enhanced/better quality of patient life in a secure way by avoiding/limiting drug abuse, or severe adverse effects of some in practice traditional therapies. Various methodological approaches including in vitro, in vivo, and ex vivo techniques have been exploited, so far. Among them, nanoparticles-based therapeutic agents are of supreme interests for an enhanced and efficient delivery in the current biomedical sector of the modern world. The development of new types of novel, effective and highly reliable therapeutic drug delivery system (DDS) for multipurpose applications is essential and a core demand to tackle many human health related diseases. In this context, nanotechnology-based several advanced DDS have been engineered with novel characteristics for biomedical, pharmaceutical and cosmeceutical applications that include but not limited to the enhanced/improved bioactivity, bioavailability, drug efficacy, targeted delivery, and therapeutically safer with an extra advantage of overcoming demerits of traditional drug formulations/designs. This review work is focused on recent trends/advances in nanotechnology-based drugs and formulations designed for targeted therapeutic delivery. Moreover, information is also reviewed and given from recent patents and summarized or illustrated diagrammatically to depict a better understanding. Recent patents covering various nanotechnology-based approaches for several applications have also been reviewed. The drug-loaded nanoparticles are among versatile candidates with multifunctional characteristics for potential applications in biomedical, and tissue engineering sector. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Sampling of illicit drugs for quantitative analysis--part II. Study of particle size and its influence on mass reduction.

Science.gov (United States)

Bovens, M; Csesztregi, T; Franc, A; Nagy, J; Dujourdy, L

2014-01-01

The basic goal in sampling for the quantitative analysis of illicit drugs is to maintain the average concentration of the drug in the material from its original seized state (the primary sample) all the way through to the analytical sample, where the effect of particle size is most critical. The size of the largest particles of different authentic illicit drug materials, in their original state and after homogenisation, using manual or mechanical procedures, was measured using a microscope with a camera attachment. The comminution methods employed included pestle and mortar (manual) and various ball and knife mills (mechanical). The drugs investigated were amphetamine, heroin, cocaine and herbal cannabis. It was shown that comminution of illicit drug materials using these techniques reduces the nominal particle size from approximately 600 μm down to between 200 and 300 μm. It was demonstrated that the choice of 1 g increments for the primary samples of powdered drugs and cannabis resin, which were used in the heterogeneity part of our study (Part I) was correct for the routine quantitative analysis of illicit seized drugs. For herbal cannabis we found that the appropriate increment size was larger. Based on the results of this study we can generally state that: An analytical sample weight of between 20 and 35 mg of an illicit powdered drug, with an assumed purity of 5% or higher, would be considered appropriate and would generate an RSDsampling in the same region as the RSDanalysis for a typical quantitative method of analysis for the most common, powdered, illicit drugs. For herbal cannabis, with an assumed purity of 1% THC (tetrahydrocannabinol) or higher, an analytical sample weight of approximately 200 mg would be appropriate. In Part III we will pull together our homogeneity studies and particle size investigations and use them to devise sampling plans and sample preparations suitable for the quantitative instrumental analysis of the most common illicit

Fragment-based quantitative structure-activity relationship (FB-QSAR) for fragment-based drug design.

Science.gov (United States)

Du, Qi-Shi; Huang, Ri-Bo; Wei, Yu-Tuo; Pang, Zong-Wen; Du, Li-Qin; Chou, Kuo-Chen

2009-01-30

In cooperation with the fragment-based design a new drug design method, the so-called "fragment-based quantitative structure-activity relationship" (FB-QSAR) is proposed. The essence of the new method is that the molecular framework in a family of drug candidates are divided into several fragments according to their substitutes being investigated. The bioactivities of molecules are correlated with the physicochemical properties of the molecular fragments through two sets of coefficients in the linear free energy equations. One coefficient set is for the physicochemical properties and the other for the weight factors of the molecular fragments. Meanwhile, an iterative double least square (IDLS) technique is developed to solve the two sets of coefficients in a training data set alternately and iteratively. The IDLS technique is a feedback procedure with machine learning ability. The standard Two-dimensional quantitative structure-activity relationship (2D-QSAR) is a special case, in the FB-QSAR, when the whole molecule is treated as one entity. The FB-QSAR approach can remarkably enhance the predictive power and provide more structural insights into rational drug design. As an example, the FB-QSAR is applied to build a predictive model of neuraminidase inhibitors for drug development against H5N1 influenza virus. (c) 2008 Wiley Periodicals, Inc.

Fragment-based approaches to TB drugs.

Science.gov (United States)

Marchetti, Chiara; Chan, Daniel S H; Coyne, Anthony G; Abell, Chris

2018-02-01

Tuberculosis is an infectious disease associated with significant mortality and morbidity worldwide, particularly in developing countries. The rise of antibiotic resistance in Mycobacterium tuberculosis (Mtb) urgently demands the development of new drug leads to tackle resistant strains. Fragment-based methods have recently emerged at the forefront of pharmaceutical development as a means to generate more effective lead structures, via the identification of fragment molecules that form weak but high quality interactions with the target biomolecule and subsequent fragment optimization. This review highlights a number of novel inhibitors of Mtb targets that have been developed through fragment-based approaches in recent years.

Electron beam sterilization of crude drug and its detection based on genetic analysis

Energy Technology Data Exchange (ETDEWEB)

Satake, Motoyoshi; Sekita, Setsuko; Kamakura, Hiroyuki [National Inst. of Health Sciences, Tokyo (Japan)

2000-02-01

Chinese traditional crude drugs are medicines derived from natural materials so that most of them include various microorganisms such as soil microbials. Therefore, it is needed to develop a sterilization method for crude drugs not disturbing the efficacy of them. As one of such sterilization method, electron beam sterilization is paid attention now. In this study, the sterilizing effects of electron beam irradiation at various doses were investigated and the changes of low molecular substances were monitored. Phellodendron bark, rehmannia root, bupleurum root and Japanese angelica root samples were used as the subjects. Irradiation was made with {gamma}-ray ({sup 60}Co) and electron beam at 5, 10, 20, 30 and 60 kGy and the number of organisms included in each drug and the contents of effective ingredients were determined after radiation exposure was determined. The number of microbials in these crude drugs were reduced ten times or more by electron beam irradiation, indicating that electron beam exposure has similar effects to those of {gamma}-ray exposure at 10 kGy previously reported. Furthermore, the contents of effective ingredients of crude drugs, especially low molecular substances such as berberine, saponin, catalpol were not significantly changed by the electron beam exposure at the doses tested in this study and electron beam exposure as well as {gamma}-ray exposure hardly affects those ingredients even at 60 kGy. Meanwhile, significant differences were observed in large molecular fractions of gel filtration chromatography between before and after the electron beam exposure at 60 kGy, suggesting that there were structural changes in some large molecules. In addition, to develop a detection method for these crude drugs, genomic DNA was extracted from them and digested with a restriction enzyme, MspI and EcoRI. Then, the ends of the respective DNAs were linked. After amplification by primary PCR, selective PCR was conducted with three MspI primers and Eco

Electron beam sterilization of crude drug and its detection based on genetic analysis

International Nuclear Information System (INIS)

Satake, Motoyoshi; Sekita, Setsuko; Kamakura, Hiroyuki

2000-01-01

Chinese traditional crude drugs are medicines derived from natural materials so that most of them include various microorganisms such as soil microbials. Therefore, it is needed to develop a sterilization method for crude drugs not disturbing the efficacy of them. As one of such sterilization method, electron beam sterilization is paid attention now. In this study, the sterilizing effects of electron beam irradiation at various doses were investigated and the changes of low molecular substances were monitored. Phellodendron bark, rehmannia root, bupleurum root and Japanese angelica root samples were used as the subjects. Irradiation was made with γ-ray ( 60 Co) and electron beam at 5, 10, 20, 30 and 60 kGy and the number of organisms included in each drug and the contents of effective ingredients were determined after radiation exposure was determined. The number of microbials in these crude drugs were reduced ten times or more by electron beam irradiation, indicating that electron beam exposure has similar effects to those of γ-ray exposure at 10 kGy previously reported. Furthermore, the contents of effective ingredients of crude drugs, especially low molecular substances such as berberine, saponin, catalpol were not significantly changed by the electron beam exposure at the doses tested in this study and electron beam exposure as well as γ-ray exposure hardly affects those ingredients even at 60 kGy. Meanwhile, significant differences were observed in large molecular fractions of gel filtration chromatography between before and after the electron beam exposure at 60 kGy, suggesting that there were structural changes in some large molecules. In addition, to develop a detection method for these crude drugs, genomic DNA was extracted from them and digested with a restriction enzyme, MspI and EcoRI. Then, the ends of the respective DNAs were linked. After amplification by primary PCR, selective PCR was conducted with three MspI primers and EcoRI primer. The

Self-Nanoemulsifying Drug Delivery Systems Based on Melon Oil ...

African Journals Online (AJOL)

Erah

Tropical Journal of Pharmaceutical Research June 2011; 10 (3): 299-307 ... membrane (the major pathway for absorption of drugs) ... [7,8] and a more reproducible plasma level - ... Proximate analysis ..... ionic surfactant-vegetable oil mixture.

Risk behaviours of illicit drug users while travelling

Directory of Open Access Journals (Sweden)

Tatja Kostnapfel Rihtar

2013-07-01

Full Text Available Introduction: Despite various formal limitations, an increasing number of opioid users, especially those stabilised in substitution therapy, travel abroad, away from their permanent residence to neighbouring and remote countries on other continents. Drug users are particularly at risk to get infected with hepatitis A, B, C and HIV during travelling.The main objectives of the study were to identify and determine the frequency of potential travel-related risk behaviour, such as illicit drug use, sharing of injecting equipment, unprotected sex, involvement in criminal activities and the extent of risk in illicit drug users, included in the programmes of the Centers for Prevention and Treatment of Drug Addiction in Slovenia.Methods: The study was carried out in two phases. The first phase included semi-structured interviews conducted in a group of drug users willing to participate in the study. Based on the analysis of transcripts and additional data, the original questionnaire Risky behaviour of illicit drug users during travels was developed and filled in anonymously and on a voluntary basis at the network of Centres for Prevention and Treatment of Drug Addiction. Univariate analysis between independent and dependent factors was conducted based on chi-square test and t-test for independent factors. Multivariate analysis of the impact of independent factors on the dependent factor was conducted based on binary logistic regression.Results: The questionnaire was filled out anonymously and voluntarily by 776 individuals in 14 Slovene centres for prevention and treatment of drug addiction. The results confirmed the first hypothesis that drug users travelling away from their permanent residence are more likely to share their injecting equipment, and engage in unprotected sex and in drug-related crime, and the second hypothesis stating that illegal drug users included in the substitution treatment programmes, who regularly use drugs at home, more often

Large-scale structural and textual similarity-based mining of knowledge graph to predict drug-drug interactions

KAUST Repository

Abdelaziz, Ibrahim; Fokoue, Achille; Hassanzadeh, Oktie; Zhang, Ping; Sadoghi, Mohammad

2017-01-01

Drug-Drug Interactions (DDIs) are a major cause of preventable Adverse Drug Reactions (ADRs), causing a significant burden on the patients’ health and the healthcare system. It is widely known that clinical studies cannot sufficiently and accurately identify DDIs for new drugs before they are made available on the market. In addition, existing public and proprietary sources of DDI information are known to be incomplete and/or inaccurate and so not reliable. As a result, there is an emerging body of research on in-silico prediction of drug-drug interactions. In this paper, we present Tiresias, a large-scale similarity-based framework that predicts DDIs through link prediction. Tiresias takes in various sources of drug-related data and knowledge as inputs, and provides DDI predictions as outputs. The process starts with semantic integration of the input data that results in a knowledge graph describing drug attributes and relationships with various related entities such as enzymes, chemical structures, and pathways. The knowledge graph is then used to compute several similarity measures between all the drugs in a scalable and distributed framework. In particular, Tiresias utilizes two classes of features in a knowledge graph: local and global features. Local features are derived from the information directly associated to each drug (i.e., one hop away) while global features are learnt by minimizing a global loss function that considers the complete structure of the knowledge graph. The resulting similarity metrics are used to build features for a large-scale logistic regression model to predict potential DDIs. We highlight the novelty of our proposed Tiresias and perform thorough evaluation of the quality of the predictions. The results show the effectiveness of Tiresias in both predicting new interactions among existing drugs as well as newly developed drugs.

Large-scale structural and textual similarity-based mining of knowledge graph to predict drug-drug interactions

KAUST Repository

Abdelaziz, Ibrahim

2017-06-12

Drug-Drug Interactions (DDIs) are a major cause of preventable Adverse Drug Reactions (ADRs), causing a significant burden on the patients’ health and the healthcare system. It is widely known that clinical studies cannot sufficiently and accurately identify DDIs for new drugs before they are made available on the market. In addition, existing public and proprietary sources of DDI information are known to be incomplete and/or inaccurate and so not reliable. As a result, there is an emerging body of research on in-silico prediction of drug-drug interactions. In this paper, we present Tiresias, a large-scale similarity-based framework that predicts DDIs through link prediction. Tiresias takes in various sources of drug-related data and knowledge as inputs, and provides DDI predictions as outputs. The process starts with semantic integration of the input data that results in a knowledge graph describing drug attributes and relationships with various related entities such as enzymes, chemical structures, and pathways. The knowledge graph is then used to compute several similarity measures between all the drugs in a scalable and distributed framework. In particular, Tiresias utilizes two classes of features in a knowledge graph: local and global features. Local features are derived from the information directly associated to each drug (i.e., one hop away) while global features are learnt by minimizing a global loss function that considers the complete structure of the knowledge graph. The resulting similarity metrics are used to build features for a large-scale logistic regression model to predict potential DDIs. We highlight the novelty of our proposed Tiresias and perform thorough evaluation of the quality of the predictions. The results show the effectiveness of Tiresias in both predicting new interactions among existing drugs as well as newly developed drugs.

Biomaterial-based drug delivery systems for the controlled release of neurotrophic factors

International Nuclear Information System (INIS)

Mohtaram, Nima Khadem; Montgomery, Amy; Willerth, Stephanie M

2013-01-01

This review highlights recent work on the use of biomaterial-based drug delivery systems to control the release of neurotrophic factors as a potential strategy for the treatment of neurological disorders. Examples of neurotrophic factors include the nerve growth factor, the glial cell line-derived neurotrophic factor, the brain-derived neurotrophic factor and neurotrophin-3. In particular, this review focuses on two methods of drug delivery: affinity-based and reservoir-based systems. We review the advantages and challenges associated with both types of drug delivery system and how these systems can be applied to neurological diseases and disorders. While a limited number of affinity-based delivery systems have been developed for the delivery of neurotrophic factors, we also examine the broad spectrum of reservoir-based delivery systems, including microspheres, electrospun nanofibers, hydrogels and combinations of these systems. Finally, conclusions are drawn about the current state of such drug delivery systems as applied to neural tissue engineering along with some thoughts on the future direction of the field. (topical review)

Understanding drugs in breast cancer through drug sensitivity screening.

Science.gov (United States)

Uhr, Katharina; Prager-van der Smissen, Wendy J C; Heine, Anouk A J; Ozturk, Bahar; Smid, Marcel; Göhlmann, Hinrich W H; Jager, Agnes; Foekens, John A; Martens, John W M

2015-01-01

With substantial numbers of breast tumors showing or acquiring treatment resistance, it is of utmost importance to develop new agents for the treatment of the disease, to know their effectiveness against breast cancer and to understand their relationships with other drugs to best assign the right drug to the right patient. To achieve this goal drug screenings on breast cancer cell lines are a promising approach. In this study a large-scale drug screening of 37 compounds was performed on a panel of 42 breast cancer cell lines representing the main breast cancer subtypes. Clustering, correlation and pathway analyses were used for data analysis. We found that compounds with a related mechanism of action had correlated IC50 values and thus grouped together when the cell lines were hierarchically clustered based on IC50 values. In total we found six clusters of drugs of which five consisted of drugs with related mode of action and one cluster with two drugs not previously connected. In total, 25 correlated and four anti-correlated drug sensitivities were revealed of which only one drug, Sirolimus, showed significantly lower IC50 values in the luminal/ERBB2 breast cancer subtype. We found expected interactions but also discovered new relationships between drugs which might have implications for cancer treatment regimens.

An emerging platform for drug delivery: aerogel based systems.

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Ulker, Zeynep; Erkey, Can

2014-03-10

Over the past few decades, advances in "aerogel science" have provoked an increasing interest for these materials in pharmaceutical sciences for drug delivery applications. Because of their high surface areas, high porosities and open pore structures which can be tuned and controlled by manipulation of synthesis conditions, nanostructured aerogels represent a promising class of materials for delivery of various drugs as well as enzymes and proteins. Along with biocompatible inorganic aerogels and biodegradable organic aerogels, more complex systems such as surface functionalized aerogels, composite aerogels and layered aerogels have also been under development and possess huge potential. Emphasis is given to the details of the aerogel synthesis and drug loading methods as well as the influence of synthesis parameters and loading methods on the adsorption and release of the drugs. Owing to their ability to increase the bioavailability of low solubility drugs, to improve both their stability and their release kinetics, there are an increasing number of research articles concerning aerogels in different drug delivery applications. This review presents an up to date overview of the advances in all kinds of aerogel based drug delivery systems which are currently under investigation. Copyright © 2014 Elsevier B.V. All rights reserved.

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

International Nuclear Information System (INIS)

Wang, Kejian; Weng, Zuquan; Sun, Liya; Sun, Jiazhi; Zhou, Shu-Feng; He, Lin

2015-01-01

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development

Systematic drug safety evaluation based on public genomic expression (Connectivity Map) data: Myocardial and infectious adverse reactions as application cases

Energy Technology Data Exchange (ETDEWEB)

Wang, Kejian, E-mail: kejian.wang.bio@gmail.com [Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai (China); Weng, Zuquan [Japan National Institute of Occupational Safety and Health, Kawasaki (Japan); Sun, Liya [Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai (China); Sun, Jiazhi; Zhou, Shu-Feng [Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL (United States); He, Lin, E-mail: helin@Bio-X.com [Bio-X Institutes, Key Laboratory for the Genetics of Developmental and Neuropsychiatric Disorders, Shanghai Jiao Tong University, Shanghai (China)

2015-02-13

Adverse drug reaction (ADR) is of great importance to both regulatory agencies and the pharmaceutical industry. Various techniques, such as quantitative structure–activity relationship (QSAR) and animal toxicology, are widely used to identify potential risks during the preclinical stage of drug development. Despite these efforts, drugs with safety liabilities can still pass through safety checkpoints and enter the market. This situation raises the concern that conventional chemical structure analysis and phenotypic screening are not sufficient to avoid all clinical adverse events. Genomic expression data following in vitro drug treatments characterize drug actions and thus have become widely used in drug repositioning. In the present study, we explored prediction of ADRs based on the drug-induced gene-expression profiles from cultured human cells in the Connectivity Map (CMap) database. The results showed that drugs inducing comparable ADRs generally lead to similar CMap expression profiles. Based on such ADR-gene expression association, we established prediction models for various ADRs, including severe myocardial and infectious events. Drugs with FDA boxed warnings of safety liability were effectively identified. We therefore suggest that drug-induced gene expression change, in combination with effective computational methods, may provide a new dimension of information to facilitate systematic drug safety evaluation. - Highlights: • Drugs causing common toxicity lead to similar in vitro gene expression changes. • We built a model to predict drug toxicity with drug-specific expression profiles. • Drugs with FDA black box warnings were effectively identified by our model. • In vitro assay can detect severe toxicity in the early stage of drug development.

Content analysis of false and misleading claims in television advertising for prescription and nonprescription drugs.

Science.gov (United States)

Faerber, Adrienne E; Kreling, David H

2014-01-01

False and misleading advertising for drugs can harm consumers and the healthcare system, and previous research has demonstrated that physician-targeted drug advertisements may be misleading. However, there is a dearth of research comparing consumer-targeted drug advertising to evidence to evaluate whether misleading or false information is being presented in these ads. To compare claims in consumer-targeted television drug advertising to evidence, in order to evaluate the frequency of false or misleading television drug advertising targeted to consumers. A content analysis of a cross-section of television advertisements for prescription and nonprescription drugs aired from 2008 through 2010. We analyzed commercial segments containing prescription and nonprescription drug advertisements randomly selected from the Vanderbilt Television News Archive, a census of national news broadcasts. For each advertisement, the most-emphasized claim in each ad was identified based on claim iteration, mode of communication, duration and placement. This claim was then compared to evidence by trained coders, and categorized as being objectively true, potentially misleading, or false. Potentially misleading claims omitted important information, exaggerated information, made lifestyle associations, or expressed opinions. False claims were factually false or unsubstantiated. Of the most emphasized claims in prescription (n = 84) and nonprescription (n = 84) drug advertisements, 33 % were objectively true, 57 % were potentially misleading and 10 % were false. In prescription drug ads, there were more objectively true claims (43 %) and fewer false claims (2 %) than in nonprescription drug ads (23 % objectively true, 7 % false). There were similar numbers of potentially misleading claims in prescription (55 %) and nonprescription (61 %) drug ads. Potentially misleading claims are prevalent throughout consumer-targeted prescription and nonprescription drug advertising on

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

ANALYSIS OF DISEASE MODIFYING DRUGS ADMINISTRATION FREGUENCY AND CAUSES OF THEIR WITHDRAWAL IN RHEUMATOID ARTHRITIS

Directory of Open Access Journals (Sweden)

E V Pavlova

2000-01-01

Full Text Available Aim of studdy: To assess the frequency of practical application of different basic drugs in rheumatoid arthritis (RA. Material and methods: Tlxe study was conducted basing of questionner of pts and analysis of ycases by randomized sampling among 103 consequent pts (M:F= 13:90 with reliable RA (ARA, 1987 in rheumatologic department of Clinical Hospital Nol in Ekaterinburg. 74% of pts under study demonstrated systemic manifestations: anemia (in 47 pts, lymphadenopathy (in 34, rheumatoid nodules (in 15, Sjogren s syndrome (in 4, nephropathy (in 4, vascular disturbances including Raynaud s phenomenon, capillarites (by 1 pt. Results: In the course of disease basic therapy was prescribed to 88 out of103 (85.4% pts and one and the same patient could take different basic drugs. Aminochinoline drugs prevailed, after them more frequent were immunodepressants and gold preparations. More rarely pts had sulfasalazin, cuprenil and wobenzym. In general, in 133 out of 184 cases of prescribing basic drugs they were canceled. The reason for cancellation were: prevalently absence of the drug in the pharmaceutical stores (in 48 cases averagely in 8 months of taking the drug; then they insufficient efficacy (44 cases averagely in 1.3 year. In 18 cases pts themselves stopped treatment averagely in 3.5 months of drug taking. Conclusion: In the majority of cases of basic drugs cancellation in RA the cause is their absence in sail especially on free of charge prescription. Cases ofself-cancellation of the drug demonstrate the need of explaining to pts the necessity> of long-term taking disease-modifying drugs.

Drug and bioactive molecule screening based on a bioelectrical impedance cell culture platform

Directory of Open Access Journals (Sweden)

Ramasamy S

2014-12-01

Full Text Available Sakthivel Ramasamy,1 Devasier Bennet,1 Sanghyo Kim1,2 1Department of Bionanotechnology, Gachon University, Gyeonggi-Do, Republic of Korea; 2Graduate Gachon Medical Research Institute, Gil Medical Center, Incheon, Republic of Korea Abstract: This review will present a brief discussion on the recent advancements of bioelectrical impedance cell-based biosensors, especially the electric cell-substrate impedance sensing (ECIS system for screening of various bioactive molecules. The different technical integrations of various chip types, working principles, measurement systems, and applications for drug targeting of molecules in cells are highlighted in this paper. Screening of bioactive molecules based on electric cell-substrate impedance sensing is a trial-and-error process toward the development of therapeutically active agents for drug discovery and therapeutics. In general, bioactive molecule screening can be used to identify active molecular targets for various diseases and toxicity at the cellular level with nanoscale resolution. In the innovation and screening of new drugs or bioactive molecules, the activeness, the efficacy of the compound, and safety in biological systems are the main concerns on which determination of drug candidates is based. Further, drug discovery and screening of compounds are often performed in cell-based test systems in order to reduce costs and save time. Moreover, this system can provide more relevant results in in vivo studies, as well as high-throughput drug screening for various diseases during the early stages of drug discovery. Recently, MEMS technologies and integration with image detection techniques have been employed successfully. These new technologies and their possible ongoing transformations are addressed. Select reports are outlined, and not all the work that has been performed in the field of drug screening and development is covered. Keywords: screening of bioactive agents, impedance-based cell

Conformational Analysis of Drug Molecules: A Practical Exercise in the Medicinal Chemistry Course

Science.gov (United States)

Yuriev, Elizabeth; Chalmers, David; Capuano, Ben

2009-01-01

Medicinal chemistry is a specialized, scientific discipline. Computational chemistry and structure-based drug design constitute important themes in the education of medicinal chemists. This problem-based task is associated with structure-based drug design lectures. It requires students to use computational techniques to investigate conformational…

SemaTyP: a knowledge graph based literature mining method for drug discovery.

Science.gov (United States)

Sang, Shengtian; Yang, Zhihao; Wang, Lei; Liu, Xiaoxia; Lin, Hongfei; Wang, Jian

2018-05-30

Drug discovery is the process through which potential new medicines are identified. High-throughput screening and computer-aided drug discovery/design are the two main drug discovery methods for now, which have successfully discovered a series of drugs. However, development of new drugs is still an extremely time-consuming and expensive process. Biomedical literature contains important clues for the identification of potential treatments. It could support experts in biomedicine on their way towards new discoveries. Here, we propose a biomedical knowledge graph-based drug discovery method called SemaTyP, which discovers candidate drugs for diseases by mining published biomedical literature. We first construct a biomedical knowledge graph with the relations extracted from biomedical abstracts, then a logistic regression model is trained by learning the semantic types of paths of known drug therapies' existing in the biomedical knowledge graph, finally the learned model is used to discover drug therapies for new diseases. The experimental results show that our method could not only effectively discover new drug therapies for new diseases, but also could provide the potential mechanism of action of the candidate drugs. In this paper we propose a novel knowledge graph based literature mining method for drug discovery. It could be a supplementary method for current drug discovery methods.

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.

Drivers of Vaginal Drug Delivery System Acceptability from Internet-Based Conjoint Analysis.

Directory of Open Access Journals (Sweden)

Rachel J Primrose

Full Text Available Vaginal microbicides potentially empower women to protect themselves from HIV and other sexually transmitted infections (STIs, especially when culture, religion, or social status may prevent them from negotiating condom use. The open literature contains minimal information on factors that drive user acceptability of women's health products or vaginal drug delivery systems. By understanding what women find to be most important with regard to sensory properties and product functionality, developers can iteratively formulate a more desirable product. Conjoint analysis is a technique widely used in market research to determine what combination of elements influence a consumer's willingness to try or use a product. We applied conjoint analysis here to better understand what sexually-active woman want in a microbicide, toward our goal of formulating a product that is highly acceptable to women. Both sensory and non-sensory attributes were tested, including shape, color, wait time, partner awareness, messiness/leakage, duration of protection, and functionality. Heterosexually active women between 18 and 35 years of age in the United States (n = 302 completed an anonymous online conjoint survey using IdeaMap software. Attributes (product elements were systematically presented in various combinations; women rated these combinations of a 9-point willingness-to-try scale. By coupling systematic combinations and regression modeling, we can estimate the unique appeal of each element. In this population, a multifunctional product (i.e., broad spectrum STI protection, coupled with conception is far more desirable than a microbicide targeted solely for HIV protection; we also found partner awareness and leakage are potentially strong barriers to use.

Drivers of Vaginal Drug Delivery System Acceptability from Internet-Based Conjoint Analysis.

Science.gov (United States)

Primrose, Rachel J; Zaveri, Toral; Bakke, Alyssa J; Ziegler, Gregory R; Moskowitz, Howard R; Hayes, John E

2016-01-01

Vaginal microbicides potentially empower women to protect themselves from HIV and other sexually transmitted infections (STIs), especially when culture, religion, or social status may prevent them from negotiating condom use. The open literature contains minimal information on factors that drive user acceptability of women's health products or vaginal drug delivery systems. By understanding what women find to be most important with regard to sensory properties and product functionality, developers can iteratively formulate a more desirable product. Conjoint analysis is a technique widely used in market research to determine what combination of elements influence a consumer's willingness to try or use a product. We applied conjoint analysis here to better understand what sexually-active woman want in a microbicide, toward our goal of formulating a product that is highly acceptable to women. Both sensory and non-sensory attributes were tested, including shape, color, wait time, partner awareness, messiness/leakage, duration of protection, and functionality. Heterosexually active women between 18 and 35 years of age in the United States (n = 302) completed an anonymous online conjoint survey using IdeaMap software. Attributes (product elements) were systematically presented in various combinations; women rated these combinations of a 9-point willingness-to-try scale. By coupling systematic combinations and regression modeling, we can estimate the unique appeal of each element. In this population, a multifunctional product (i.e., broad spectrum STI protection, coupled with conception) is far more desirable than a microbicide targeted solely for HIV protection; we also found partner awareness and leakage are potentially strong barriers to use.

Effectiveness of multi-drug regimen chemotherapy treatment in osteosarcoma patients: a network meta-analysis of randomized controlled trials.

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Wang, Xiaojie; Zheng, Hong; Shou, Tao; Tang, Chunming; Miao, Kun; Wang, Ping

2017-03-29

Osteosarcoma is the most common malignant bone tumour. Due to the high metastasis rate and drug resistance of this disease, multi-drug regimens are necessary to control tumour cells at various stages of the cell cycle, eliminate local or distant micrometastases, and reduce the emergence of drug-resistant cells. Many adjuvant chemotherapy protocols have shown different efficacies and controversial results. Therefore, we classified the types of drugs used for adjuvant chemotherapy and evaluated the differences between single- and multi-drug chemotherapy regimens using network meta-analysis. We searched electronic databases, including PubMed (MEDLINE), EmBase, and the Cochrane Library, through November 2016 using the keywords "osteosarcoma", "osteogenic sarcoma", "chemotherapy", and "random*" without language restrictions. The major outcome in the present analysis was progression-free survival (PFS), and the secondary outcome was overall survival (OS). We used a random effect network meta-analysis for mixed multiple treatment comparisons. We included 23 articles assessing a total of 5742 patients in the present systematic review. The analysis of PFS indicated that the T12 protocol (including adriamycin, bleomycin, cyclophosphamide, dactinomycin, methotrexate, cisplatin) plays a more critical role in osteosarcoma treatment (surface under the cumulative ranking (SUCRA) probability 76.9%), with a better effect on prolonging the PFS of patients when combined with ifosfamide (94.1%) or vincristine (81.9%). For the analysis of OS, we separated the regimens to two groups, reflecting the disconnection. The T12 protocol plus vincristine (94.7%) or the removal of cisplatinum (89.4%) is most likely the best regimen. We concluded that multi-drug regimens have a better effect on prolonging the PFS and OS of osteosarcoma patients, and the T12 protocol has a better effect on prolonging the PFS of osteosarcoma patients, particularly in combination with ifosfamide or vincristine

Sex, drugs, and HIV: rapid assessment of HIV risk behaviors among street-based drug using sex workers in Durban, South Africa.

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Needle, Richard; Kroeger, Karen; Belani, Hrishikesh; Achrekar, Angeli; Parry, Charles D; Dewing, Sarah

2008-11-01

South Africa is experiencing significant changes in patterns of illicit drug use, including increasing injection and non-injection drug use, and the use of drugs by persons engaged in sex work, both of which could further expand the HIV/AIDS epidemic. In 2005, a rapid ethnographic assessment was conducted in Durban, South Africa, to learn more about patterns of drug use and HIV risk behaviors among drug-using, street-based sex workers. Field teams recruited 52 current injection and non-injection drug users for key informant interviews and focus groups, and they conducted mapping and observation in identified high-risk neighborhoods. Key informants were offered free, voluntary counseling and HIV rapid testing. The results of the assessment indicate that in this population, drugs play an organizing role in patterns of daily activities, with sex work closely linked to the buying, selling, and using of drugs. Participants reported using multiple drugs including crack cocaine, heroin, Ecstasy and Mandrax, and their choices were based on their expectations about the functional role and behavioral and pharmacological properties of the drugs. The organization of sex work and patterns of drug use differ by gender, with males exercising more control over daily routines and drug and sexual transactions than females. Activities of female sex workers are subject to considerable control by individual pimps, many of whom also function as landlords and drug dealers. A strong hold over the overlapping economies of drugs and sex work by a few individuals extends to control of the physical and social settings in which sex is exchanged and drugs are sold and used as well as the terms under which sex work is carried out. The potential for accelerated HIV spread is considerable given the evidence of overlapping drug-using and sexual risk behaviors and the mixing patterns across drug and sexual risk networks.

[Analysis of drug-related problems in a tertiary university hospital in Barcelona (Spain)].

Science.gov (United States)

Ferrández, Olivia; Casañ, Borja; Grau, Santiago; Louro, Javier; Salas, Esther; Castells, Xavier; Sala, Maria

2018-05-07

To describe drug-related problems identified in hospitalized patients and to assess physicians' acceptance rate of pharmacists' recommendations. Retrospective observational study that included all drug-related problems detected in hospitalized patients during 2014-2015. Statistical analysis included a descriptive analysis of the data and a multivariate logistic regression to evaluate the association between pharmacists' recommendation acceptance rate and the variable of interest. During the study period 4587 drug-related problems were identified in 44,870 hospitalized patients. Main drug-related problems were prescription errors due to incorrect use of the computerized physician order entry (18.1%), inappropriate drug-drug combination (13.3%) and dose adjustment by renal and/or hepatic function (11.5%). Acceptance rate of pharmacist therapy advice in evaluable cases was 81.0%. Medical versus surgical admitting department, specific types of intervention (addition of a new drug, drug discontinuation and correction of a prescription error) and oral communication of the recommendation were associated with a higher acceptance rate. The results of this study allow areas to be identified on which to implement optimization strategies. These include training courses for physicians on the computerized physician order entry, on drugs that need dose adjustment with renal impairment, and on relevant drug interactions. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

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

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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.

The rise of fragment-based drug discovery.

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Murray, Christopher W; Rees, David C

2009-06-01

The search for new drugs is plagued by high attrition rates at all stages in research and development. Chemists have an opportunity to tackle this problem because attrition can be traced back, in part, to the quality of the chemical leads. Fragment-based drug discovery (FBDD) is a new approach, increasingly used in the pharmaceutical industry, for reducing attrition and providing leads for previously intractable biological targets. FBDD identifies low-molecular-weight ligands (∼150 Da) that bind to biologically important macromolecules. The three-dimensional experimental binding mode of these fragments is determined using X-ray crystallography or NMR spectroscopy, and is used to facilitate their optimization into potent molecules with drug-like properties. Compared with high-throughput-screening, the fragment approach requires fewer compounds to be screened, and, despite the lower initial potency of the screening hits, offers more efficient and fruitful optimization campaigns. Here, we review the rise of FBDD, including its application to discovering clinical candidates against targets for which other chemistry approaches have struggled.

Identification of novel psychoactive drug use in Sweden based on laboratory analysis--initial experiences from the STRIDA project.

Science.gov (United States)

Helander, Anders; Beck, Olof; Hägerkvist, Robert; Hultén, Peter

2013-08-01

The study aimed to collect information concerning the increasing use of new psychoactive substances, commonly sold through online shops as 'Internet drugs' or 'legal highs', or in terms of masked products such as 'bath salts' and 'plant food'. The Karolinska Institutet and Karolinska University Laboratory and the Swedish Poisons Information Centre have initiated a project called 'STRIDA' aiming to monitor the occurrence and trends of new psychoactive substances in Sweden, and collect information about their clinical symptoms, toxicity and associated health risks. A liquid chromatographic-tandem mass spectrometric (LC-MS/MS) multi-component method has been developed, currently allowing for the determination of > 80 novel psychoactive compounds or metabolites thereof. This study focused mainly on the particular drug substances identified and the population demographics of the initial STRIDA cases. In urine and/or blood samples obtained from 103 consecutive cases of admitted or suspected recreational drug intoxications in mostly young subjects (78% were ≤ 25 years, and 81% were males) presenting at emergency departments all over the country, psychoactive substances were detected in 82%. The substances comprised synthetic cannabinoids ('Spice'; JWH analogues), substituted cathinones ('bath salts'; e.g. butylone, MDPV and methylone) and tryptamines (4-HO-MET), plant-based substances (mitragynine and psilocin), as well as conventional drugs-of-abuse. In 44% of the cases, more than one new psychoactive substance, or a mixture of new and/or conventional drugs were detected. The initial results of the STRIDA project have documented use of a broad variety of new psychoactive substances among mainly young people all over Sweden.

Hair analysis in toxicological investigation of drug-facilitated crimes in Denmark over a 8-year period

DEFF Research Database (Denmark)

Wang, Xin; Johansen, Sys Stybe; Nielsen, Marie Katrine Klose

2018-01-01

analgesics, antipsychotics, barbiturates, and illicit drugs from DFC cases. Drug detection in hair in DFC cases following a single or few intakes of chlorprothixene, codeine, diphenhydramine, oxazepam, oxycodone, promethazine, and phenobarbital is reported for the first time in forensic toxicology......Hair can serve as a specimen for identifying past drug exposure. Segmental hair analysis may differentiate a single exposure from chronic use. Consequently, segmental hair analysis is useful for disclosing a single drug ingestion, as well as for determining repeated exposures in drug......-facilitated crimes (DFCs). This paper presents an overview of toxicological investigations that have used hair analysis in DFC cases from 2009 to 2016 in Denmark. Hair concentrations were determined for 24 DFC-related drugs and metabolites, including benzodiazepines and other hypnotics, antihistamines, opioid...

Zero-inflated Poisson model based likelihood ratio test for drug safety signal detection.

Science.gov (United States)

Huang, Lan; Zheng, Dan; Zalkikar, Jyoti; Tiwari, Ram

2017-02-01

In recent decades, numerous methods have been developed for data mining of large drug safety databases, such as Food and Drug Administration's (FDA's) Adverse Event Reporting System, where data matrices are formed by drugs such as columns and adverse events as rows. Often, a large number of cells in these data matrices have zero cell counts and some of them are "true zeros" indicating that the drug-adverse event pairs cannot occur, and these zero counts are distinguished from the other zero counts that are modeled zero counts and simply indicate that the drug-adverse event pairs have not occurred yet or have not been reported yet. In this paper, a zero-inflated Poisson model based likelihood ratio test method is proposed to identify drug-adverse event pairs that have disproportionately high reporting rates, which are also called signals. The maximum likelihood estimates of the model parameters of zero-inflated Poisson model based likelihood ratio test are obtained using the expectation and maximization algorithm. The zero-inflated Poisson model based likelihood ratio test is also modified to handle the stratified analyses for binary and categorical covariates (e.g. gender and age) in the data. The proposed zero-inflated Poisson model based likelihood ratio test method is shown to asymptotically control the type I error and false discovery rate, and its finite sample performance for signal detection is evaluated through a simulation study. The simulation results show that the zero-inflated Poisson model based likelihood ratio test method performs similar to Poisson model based likelihood ratio test method when the estimated percentage of true zeros in the database is small. Both the zero-inflated Poisson model based likelihood ratio test and likelihood ratio test methods are applied to six selected drugs, from the 2006 to 2011 Adverse Event Reporting System database, with varying percentages of observed zero-count cells.

Analysis of stimulant drugs in the wastewater of five Nordic capitals.

Science.gov (United States)

Löve, Arndís Sue Ching; Baz-Lomba, Jose Antonio; Reid, Malcolm J; Kankaanpää, Aino; Gunnar, Teemu; Dam, Maria; Ólafsdóttir, Kristín; Thomas, Kevin V

2018-06-15

Wastewater-based epidemiology is an efficient way to assess illicit drug use, complementing currently used methods retrieved from different data sources. The aim of this study is to compare stimulant drug use in five Nordic capital cities that include for the first time wastewater samples from Torshavn in the Faroe Islands. Currently there are no published reports that compare stimulant drug use in these Nordic capitals. All wastewater samples were analyzed using solid phase extraction and ultra-high performance liquid chromatography coupled to tandem mass spectrometry. The results were compared with data published by the European Monitoring Centre for Drugs and Drug Addiction based on illicit drugs in wastewater from over 50 European cities. Confirming previous reports, the results showed high amphetamine loads compared with other European countries. Very little apparent abuse of stimulant drugs was detected in Torshavn. Methamphetamine loads were the highest from Helsinki of the Nordic countries, indicating substantial fluctuations in the availability of the drug compared with previous studies. Methamphetamine loads from Oslo confirmed that the use continues to be high. Estimated cocaine use was found to be in the lower range compared with other cities in the southern and western part of Europe. Ecstasy and cocaine showed clear variations between weekdays and weekends, indicating recreational use. This study further demonstrates geographical trends in the stimulant drug market in five Nordic capitals, which enables a better comparison with other areas of the continent. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

A laser based reusable microjet injector for transdermal drug delivery

Science.gov (United States)

Han, Tae-hee; Yoh, Jack J.

2010-05-01

A laser based needle-free liquid drug injection device has been developed. A laser beam is focused inside the liquid contained in the rubber chamber of microscale. The focused laser beam causes explosive bubble growth, and the sudden volume increase in a sealed chamber drives a microjet of liquid drug through the micronozzle. The exit diameter of a nozzle is 125 μm and the injected microjet reaches an average velocity of 264 m/s. This device adds the time-varying feature of microjet to the current state of liquid injection for drug delivery.

A population-based prescription study of asthma drugs during pregnancy

DEFF Research Database (Denmark)

Olesen, Charlotte; Thrane, Nana; Nielsen, G.L.

2001-01-01

Background: Among the goals of gestational asthma, therapy is optimisation of pulmonary function. According to the US Food and Drug Administration, no asthma drugs can be considered ‘safe’ during pregnancy. Fear of adverse fetal effects may thus lead to restrictive use of asthma drugs during...... pregnancy, and no population-based studies concerning gestational asthma therapy exist. Objectives: To examine whether asthma drugs or changing intensity of asthma therapy during pregnancy was associated with deviations from expected values of gestational age, birth weight, length at birth, or malformations....... Methods: The Birth Registry was used to identify all 15,756 primiparous women who gave birth in the County of North Jutland between 1991 and 1996. According to the North Jutland Prescription Database, 303 of these women received prescriptions for asthma drugs during pregnancy. Women who did not purchase...

Fragment approaches in structure-based drug discovery

International Nuclear Information System (INIS)

Hubbard, Roderick E.

2008-01-01

Fragment-based methods are successfully generating novel and selective drug-like inhibitors of protein targets, with a number of groups reporting compounds entering clinical trials. This paper summarizes the key features of the approach as one of the tools in structure-guided drug discovery. There has been considerable interest recently in what is known as 'fragment-based lead discovery'. The novel feature of the approach is to begin with small low-affinity compounds. The main advantage is that a larger potential chemical diversity can be sampled with fewer compounds, which is particularly important for new target classes. The approach relies on careful design of the fragment library, a method that can detect binding of the fragment to the protein target, determination of the structure of the fragment bound to the target, and the conventional use of structural information to guide compound optimization. In this article the methods are reviewed, and experiences in fragment-based discovery of lead series of compounds against kinases such as PDK1 and ATPases such as Hsp90 are discussed. The examples illustrate some of the key benefits and issues of the approach and also provide anecdotal examples of the patterns seen in selectivity and the binding mode of fragments across different protein targets

Drug injecting and HIV risk among injecting drug users in Hai Phong, Vietnam: a qualitative analysis.

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Ahmed, Tanvir; Long, Thanh Nguyen; Huong, Phan Thi; Stewart, Donald Edwin

2015-01-29

Hai Phong, located in northern Vietnam, has become a high HIV prevalence province among Injecting Drug Users (IDUs) since the infection shifted from the southern to the northern region of the country. Previous research indicates high levels of drug and sex related risk behaviour especially among younger IDUs. Our recent qualitative research provides a deeper understanding of HIV risk behaviour and highlights views and experiences of IDUs relating to drug injecting and sharing practices. Fifteen IDUs participated in semi-structured interviews conducted in September-October, 2012. Eligible participants were selected from those recruited in a larger scale behavioural research project and identified through screening questions. Interviews were conducted by two local interviewers in Vietnamese and were audiotaped. Ethical procedures, including informed consent and participants' understanding of their right to skip and withdraw, were applied. Transcripts were translated and double checked. The data were categorised and coded according to themes. Thematic analysis was conducted and a qualitative data analysis thematic framework was used. Qualitative analysis highlighted situational circumstances associated with HIV risks among IDUs in Hai Phong and revealed three primary themes: (i) places for injecting, (ii) injecting drugs in small groups, and (iii) sharing practices. Our results showed that shared use of jointly purchased drugs and group injecting were widespread among IDUs without adequate recognition of these as HIV risk behaviours. Frequent police raids generated a constant fear of arrest. As a consequence, the majority preferred either rail lines or isolated public places for injection, while some injected in their own or a friend's home. Price, a heroin crisis, and strong group norms encouraged collective preparation and group injecting. Risk practices were enhanced by a number of factors: the difficulty in getting new syringes, quick withdrawal management

Renewable poly(δ-decalactone based block copolymer micelles as drug delivery vehicle: in vitro and in vivo evaluation

Directory of Open Access Journals (Sweden)

Kuldeep K. Bansal

2018-03-01

Full Text Available Polymers from natural resources are attracting much attention in various fields including drug delivery as green alternatives to fossil fuel based polymers. In this quest, novel block copolymers based on renewable poly(δ-decalactone (PDL were evaluated for their drug delivery capabilities and compared with a fossil fuel based polymer i.e. methoxy-poly(ethylene glycol-b-poly(ε-caprolactone (mPEG-b-PCL. Using curcumin as a hydrophobic drug model, micelles of PDL block copolymers with different orientation i.e. AB (mPEG-b-PDL, ABA (PDL-b-PEG-b-PDL, ABC (mPEG-b-PDL-b-poly(pentadecalactone and (mPEG-b-PCL were prepared by nanoprecipitation method. The size, drug loading and curcumin stability studies results indicated that mPEG-b-PDL micelles was comparable to its counterpart mPEG-b-PCL micelles towards improved delivery of curcumin. Therefore, mixed micelles using these two copolymers were also evaluated to see any change in size, loading and drug release. Drug release studies proposed that sustained release can be obtained using poly(pentadecalactone as crystalline core whereas rapid release can be achieved using amorphous PDL core. Further, mPEG-b-PDL micelles were found to be non-haemolytic, up to the concentration of 40 mg/mL. In vivo toxicity studies on rats advised low-toxic behaviour of these micelles up to 400 mg/kg dose, as evident by histopathological and biochemical analysis. In summary, it is anticipated that mPEG-b-PDL block copolymer micelles could serve as a renewable alternative for mPEG-b-PCL copolymers in drug delivery applications.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

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Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

Use of fertility drugs in Denmark 1973-1993. An analysis based on sale statistics

DEFF Research Database (Denmark)

Mosgaard, B; Lidegaard, Øjvind; Andersen, A N

1995-01-01

The increasing use of drugs for ovarian stimulation and the possibility of long-term risks has actualized a quantitative assessment of the use of such therapy. The aim of the study was to analyze the development in the sale of different types of drugs used for ovarian stimulation in Denmark during...

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

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Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2018-03-01

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN

Advanced Therapeutic Strategies for Chronic Lung Disease Using Nanoparticle-Based Drug Delivery

Directory of Open Access Journals (Sweden)

Ji Young Yhee

2016-09-01

Full Text Available Chronic lung diseases include a variety of obstinate and fatal diseases, including asthma, chronic obstructive pulmonary disease (COPD, cystic fibrosis (CF, idiopathic pulmonary fibrosis (IPF, and lung cancers. Pharmacotherapy is important for the treatment of chronic lung diseases, and current progress in nanoparticles offers great potential as an advanced strategy for drug delivery. Based on their biophysical properties, nanoparticles have shown improved pharmacokinetics of therapeutics and controlled drug delivery, gaining great attention. Herein, we will review the nanoparticle-based drug delivery system for the treatment of chronic lung diseases. Various types of nanoparticles will be introduced, and recent innovative efforts to utilize the nanoparticles as novel drug carriers for the effective treatment of chronic lung diseases will also be discussed.

Towards novel therapeutics for HIV through fragment-based screening and drug design.

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Tiefendbrunn, Theresa; Stout, C David

2014-01-01

Fragment-based drug discovery has been applied with varying levels of success to a number of proteins involved in the HIV (Human Immunodeficiency Virus) life cycle. Fragment-based approaches have led to the discovery of novel binding sites within protease, reverse transcriptase, integrase, and gp41. Novel compounds that bind to known pockets within CCR5 have also been identified via fragment screening, and a fragment-based approach to target the TAR-Tat interaction was explored. In the context of HIV-1 reverse transcriptase (RT), fragment-based approaches have yielded fragment hits with mid-μM activity in an in vitro activity assay, as well as fragment hits that are active against drug-resistant variants of RT. Fragment-based drug discovery is a powerful method to elucidate novel binding sites within proteins, and the method has had significant success in the context of HIV proteins.

Anti-hypertensive drugs and skin cancer risk: a review of the literature and meta-analysis.

Science.gov (United States)

Gandini, Sara; Palli, Domenico; Spadola, Giuseppe; Bendinelli, Benedetta; Cocorocchio, Emilia; Stanganelli, Ignazio; Miligi, Lucia; Masala, Giovanna; Caini, Saverio

2018-02-01

Several anti-hypertensive drugs have photosensitizing properties, however it remains unclear whether long-term users of these drugs are also at increased risk of skin malignancies. We conducted a literature review and meta-analysis on the association between use of anti-hypertensive drugs and the risk of cutaneous melanoma and non-melanoma skin cancer (NMSC). We searched PubMed, EMBASE, Google Scholar and the Cochrane Library, and included observational and experimental epidemiological studies published until February 28th, 2017. We calculated summary relative risk (SRR) and 95% confidence intervals (95% CI) through random effect models to estimate the risk of skin malignancies among users of the following classes of anti-hypertensive drugs: thiazide diuretics, angiotensin converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), calcium channel blockers (CCB) and β-blockers. We conducted sub-group and sensitivity analysis to explore causes of between-studies heterogeneity, and assessed publication bias using a funnel-plot based approach. Nineteen independent studies were included in the meta-analysis. CCB users were at increased skin cancer risk (SRR 1.14, 95% CI 1.07-1.21), and β-blockers users were at increased risk of developing cutaneous melanoma (SRR 1.21, 95% CI 1.05-1.40), with acceptable between-studies heterogeneity (I 2  skin cancer risk. We found no evidence of publication bias affecting the results. Family doctors and clinicians should inform their patients about the increased risk of skin cancer associated with the use of CCB and β-blockers and instruct them to perform periodic skin self-examination. Further studies are warranted to elucidate the observed associations. Copyright © 2017 Elsevier B.V. All rights reserved.

Fragment-based drug design.

Science.gov (United States)

Feyfant, Eric; Cross, Jason B; Paris, Kevin; Tsao, Désirée H H

2011-01-01

Fragment-based drug design (FBDD), which is comprised of both fragment screening and the use of fragment hits to design leads, began more than 15 years ago and has been steadily gaining in popularity and utility. Its origin lies on the fact that the coverage of chemical space and the binding efficiency of hits are directly related to the size of the compounds screened. Nevertheless, FBDD still faces challenges, among them developing fragment screening libraries that ensure optimal coverage of chemical space, physical properties and chemical tractability. Fragment screening also requires sensitive assays, often biophysical in nature, to detect weak binders. In this chapter we will introduce the technologies used to address these challenges and outline the experimental advantages that make FBDD one of the most popular new hit-to-lead process.

A Performance/Cost Evaluation for a GPU-Based Drug Discovery Application on Volunteer Computing

Science.gov (United States)

Guerrero, Ginés D.; Imbernón, Baldomero; García, José M.

2014-01-01

Bioinformatics is an interdisciplinary research field that develops tools for the analysis of large biological databases, and, thus, the use of high performance computing (HPC) platforms is mandatory for the generation of useful biological knowledge. The latest generation of graphics processing units (GPUs) has democratized the use of HPC as they push desktop computers to cluster-level performance. Many applications within this field have been developed to leverage these powerful and low-cost architectures. However, these applications still need to scale to larger GPU-based systems to enable remarkable advances in the fields of healthcare, drug discovery, genome research, etc. The inclusion of GPUs in HPC systems exacerbates power and temperature issues, increasing the total cost of ownership (TCO). This paper explores the benefits of volunteer computing to scale bioinformatics applications as an alternative to own large GPU-based local infrastructures. We use as a benchmark a GPU-based drug discovery application called BINDSURF that their computational requirements go beyond a single desktop machine. Volunteer computing is presented as a cheap and valid HPC system for those bioinformatics applications that need to process huge amounts of data and where the response time is not a critical factor. PMID:25025055

Nonlinear mixed effects dose response modeling in high throughput drug screens: application to melanoma cell line analysis.

Science.gov (United States)

Ding, Kuan-Fu; Petricoin, Emanuel F; Finlay, Darren; Yin, Hongwei; Hendricks, William P D; Sereduk, Chris; Kiefer, Jeffrey; Sekulic, Aleksandar; LoRusso, Patricia M; Vuori, Kristiina; Trent, Jeffrey M; Schork, Nicholas J

2018-01-12

Cancer cell lines are often used in high throughput drug screens (HTS) to explore the relationship between cell line characteristics and responsiveness to different therapies. Many current analysis methods infer relationships by focusing on one aspect of cell line drug-specific dose-response curves (DRCs), the concentration causing 50% inhibition of a phenotypic endpoint (IC 50 ). Such methods may overlook DRC features and do not simultaneously leverage information about drug response patterns across cell lines, potentially increasing false positive and negative rates in drug response associations. We consider the application of two methods, each rooted in nonlinear mixed effects (NLME) models, that test the relationship relationships between estimated cell line DRCs and factors that might mitigate response. Both methods leverage estimation and testing techniques that consider the simultaneous analysis of different cell lines to draw inferences about any one cell line. One of the methods is designed to provide an omnibus test of the differences between cell line DRCs that is not focused on any one aspect of the DRC (such as the IC 50 value). We simulated different settings and compared the different methods on the simulated data. We also compared the proposed methods against traditional IC 50 -based methods using 40 melanoma cell lines whose transcriptomes, proteomes, and, importantly, BRAF and related mutation profiles were available. Ultimately, we find that the NLME-based methods are more robust, powerful and, for the omnibus test, more flexible, than traditional methods. Their application to the melanoma cell lines reveals insights into factors that may be clinically useful.

Toward Omics-Based, Systems Biomedicine, and Path and Drug Discovery Methodologies for Depression-Inflammation Research.

Science.gov (United States)

Maes, Michael; Nowak, Gabriel; Caso, Javier R; Leza, Juan Carlos; Song, Cai; Kubera, Marta; Klein, Hans; Galecki, Piotr; Noto, Cristiano; Glaab, Enrico; Balling, Rudi; Berk, Michael

2016-07-01

Meta-analyses confirm that depression is accompanied by signs of inflammation including increased levels of acute phase proteins, e.g., C-reactive protein, and pro-inflammatory cytokines, e.g., interleukin-6. Supporting the translational significance of this, a meta-analysis showed that anti-inflammatory drugs may have antidepressant effects. Here, we argue that inflammation and depression research needs to get onto a new track. Firstly, the choice of inflammatory biomarkers in depression research was often too selective and did not consider the broader pathways. Secondly, although mild inflammatory responses are present in depression, other immune-related pathways cannot be disregarded as new drug targets, e.g., activation of cell-mediated immunity, oxidative and nitrosative stress (O&NS) pathways, autoimmune responses, bacterial translocation, and activation of the toll-like receptor and neuroprogressive pathways. Thirdly, anti-inflammatory treatments are sometimes used without full understanding of their effects on the broader pathways underpinning depression. Since many of the activated immune-inflammatory pathways in depression actually confer protection against an overzealous inflammatory response, targeting these pathways may result in unpredictable and unwanted results. Furthermore, this paper discusses the required improvements in research strategy, i.e., path and drug discovery processes, omics-based techniques, and systems biomedicine methodologies. Firstly, novel methods should be employed to examine the intracellular networks that control and modulate the immune, O&NS and neuroprogressive pathways using omics-based assays, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, immunoproteomics and metagenomics. Secondly, systems biomedicine analyses are essential to unravel the complex interactions between these cellular networks, pathways, and the multifactorial trigger factors and to delineate new drug targets in the cellular

A cost-effective smartphone-based antimicrobial susceptibility test reader for drug resistance testing (Conference Presentation)

Science.gov (United States)

Feng, Steve W.; Tseng, Derek; Di Carlo, Dino; Garner, Omai B.; Ozcan, Aydogan

2017-03-01

Antimicrobial susceptibility testing (AST) is commonly used for determining microbial drug resistance, but routine testing, which can significantly reduce the spread of multi-drug resistant organisms, is not regularly performed in resource-limited and field-settings due to technological challenges and lack of trained diagnosticians. We developed a portable cost-effective smartphone-based colorimetric 96-well microtiter plate (MTP) reader capable of automated AST without the need for a trained diagnostician. This system is composed of a smartphone used in conjunction with a 3D-printed opto-mechanical attachment, which holds a set of inexpensive light-emitting-diodes and fiber-optic cables coupled to the 96-well MTP for enabling the capture of the transmitted light through each well by the smartphone camera. Images of the MTP plate are captured at multiple exposures and uploaded to a local or remote server (e.g., a laptop) for automated processing/analysis of the results using a custom-designed smartphone application. Each set of images are combined to generate a high dynamic-range image and analyzed for well turbidity (indicative of bacterial growth), followed by interpretative analysis per plate to determine minimum inhibitory concentration (MIC) and drug susceptibility for the specific bacterium. Results are returned to the originating device within 1 minute and shown to the user in tabular form. We demonstrated the capability of this platform using MTPs prepared with 17 antibiotic drugs targeting Gram-negative bacteria and tested 82 patient isolate MTPs of Klebsiella pneumoniae, achieving well turbidity accuracy of 98.19%, MIC accuracy of 95.15%, and drug susceptibility interpretation accuracy of 99.06%, meeting the FDA defined criteria for AST.

Development of a Nafion/MWCNT-SPCE-Based Portable Sensor for the Voltammetric Analysis of the Anti-Tuberculosis Drug Ethambutol

Directory of Open Access Journals (Sweden)

Rosa A. S. Couto

2016-06-01

Full Text Available Herein we describe the development, characterization and application of an electrochemical sensor based on the use of Nafion/MWCNT-modified screen-printed carbon electrodes (SPCEs for the voltammetric detection of the anti-tuberculosis (anti-TB drug ethambutol (ETB. The electrochemical behaviour of the drug at the surface of the developed Nafion/MWCNT-SPCEs was studied through cyclic voltammetry (CV and square wave voltammetry (SWV techniques. Electrochemical impedance spectroscopy (EIS and scanning electron microscopy (SEM were employed to characterize the modified surface of the electrodes. Results showed that, compared to both unmodified and MWCNTs-modified SPCEs, negatively charged Nafion/MWCNT-SPCEs remarkably enhanced the electrochemical sensitivity and selectivity for ETB due to the synergistic effect of the electrostatic interaction between cationic ETB molecules and negatively charged Nafion polymer and the inherent electrocatalytic properties of both MWCNTs and Nafion. Nafion/MWCNT-SPCEs provided excellent biocompatibility, good electrical conductivity, low electrochemical interferences and a high signal-to-noise ratio, providing excellent performance towards ETB quantification in microvolumes of human urine and human blood serum samples. The outcomes of this paper confirm that the Nafion/MWCNT-SPCE-based device could be a potential candidate for the development of a low-cost, yet reliable and efficient electrochemical portable sensor for the low-level detection of this antimycobacterial drug in biological samples.

[Analysis on replacement of traditional Chinese medicine bear bile with bile acids based on drug properties].

Science.gov (United States)

Yuan, Bin; Ren, Ying-Long; Ma, Li; Gu, Hao; Wang, Yun; Qiao, Yan-Jiang

2014-02-01

To discuss the rationality of the clinical replacement of traditional Chinese medicine (TCM) bear bile with bile acid constituents, and analyze the difference between these constituents and bear bile in drug properties. Summarizing the drug properties of bear bile by reference to medical literatures for drug properties of TCM bear bile and Science of Traditional Chinese Medicine (China Press of Traditional Chinese Medicine, 2007). Analyzing and summarizing the pharmacological effects of main bile acid constituents according to relevant literatures for studies on pharmacological effects of main bile acid constituents in CNKI database. Predicating the drug properties of these bile acid constituents by using the drug property predication model established by the study group according the pharmacological effects of main bile acid constituents in the paper, and compare the prediction results with the drug properties of bear bile. Bile acid constituents in bear bile were mostly cold in property, bitter in taste, and the combination of their drug properties could reflect the combined drug properties of bear bile. All of these bile acid constituents in bear bile could show part of effects of bear bile. Attention shall be given to regulate the medication scheme in clinical application according to actual conditions.

Big Data Mining and Adverse Event Pattern Analysis in Clinical Drug Trials.

Science.gov (United States)

Federer, Callie; Yoo, Minjae; Tan, Aik Choon

2016-12-01

Drug adverse events (AEs) are a major health threat to patients seeking medical treatment and a significant barrier in drug discovery and development. AEs are now required to be submitted during clinical trials and can be extracted from ClinicalTrials.gov ( https://clinicaltrials.gov/ ), a database of clinical studies around the world. By extracting drug and AE information from ClinicalTrials.gov and structuring it into a database, drug-AEs could be established for future drug development and repositioning. To our knowledge, current AE databases contain mainly U.S. Food and Drug Administration (FDA)-approved drugs. However, our database contains both FDA-approved and experimental compounds extracted from ClinicalTrials.gov . Our database contains 8,161 clinical trials of 3,102,675 patients and 713,103 reported AEs. We extracted the information from ClinicalTrials.gov using a set of python scripts, and then used regular expressions and a drug dictionary to process and structure relevant information into a relational database. We performed data mining and pattern analysis of drug-AEs in our database. Our database can serve as a tool to assist researchers to discover drug-AE relationships for developing, repositioning, and repurposing drugs.

Incarcerated women's relationship-based strategies to avoid drug use after community re-entry.

Science.gov (United States)

Snell-Rood, Claire; Staton-Tindall, Michele; Victor, Grant

2016-10-01

While recent research has stressed the supportive role that family and friends play for incarcerated persons as they re-enter the community, drug-using incarcerated women re-entering the community often have to rely on family, community, and intimate relationships that have played a role in their substance abuse and criminalization. In this study the authors conducted qualitative analysis of clinical sessions with rural, drug-using women (N = 20) in a larger prison-based HIV risk reduction intervention in Kentucky during 2012-2014 to examine incarcerated women's perceptions of the role of their family, community, and intimate relationships in their plans to decrease their substance abuse upon community re-entry. Women stressed the obstacles to receiving support in many of their family and drug-using relationships after community re-entry. Nonetheless, they asserted that changes in their relationships could support their desires to end their substance abuse by setting limits on and using their positive relationships, particularly with their children, to motivate them to change. Interventions to promote incarcerated women's health behavior changes-including substance abuse-must acknowledge the complex social environments in which they live.

77 FR 9946 - Draft Guidance for Industry on Drug Interaction Studies-Study Design, Data Analysis, Implications...

Science.gov (United States)

2012-02-21

... industry entitled ``Drug Interaction Studies--Study Design, Data Analysis, Implications for Dosing, and... data analysis in the context of identifying potential drug interactions. The guidance also addresses... Studies--Study Design, Data Analysis, and Implications for Dosing and Labeling.'' Comments were received...

Prescriptive Oriented Drug Analysis of Multiple Sclerosis Disease by LC-UV in Whole Human Blood.

Science.gov (United States)

Suneetha, A; Rajeswari, Raja K

2016-02-01

As a polytherapy treatment, multiple sclerosis disease demands prescriptions with more than one drug. Polytherapy is sometimes rational for drug combinations chosen to minimize adverse effects. Estimation of drugs that are concomitantly administered in polytherapy is acceptable as it shortens the analytical timepoints and also the usage of biological matrices. In clinical phase trials, the withdrawal of biofluids is a critical issue for each analysis. Estimating all the coadminsitered drugs in a single shot will be more effective and economical for pharmaceuticals. A single, simple, rapid and sensitive high-performance liquid chromatography assay method has been developed with UV detection and fully validated for the quantification of 14 drugs (at random combinations) used in the treatment of multiple sclerosis disease. The set of combinations was based on prescriptions to patients. Separations were achieved on an X-Terra MS C18 (100 × 3.9 mm, 5 µm) column. The analytes were extracted from 50 µL aliquots of whole human blood with protein precipitation using acetonitrile. All the drugs were sufficiently stable during storage for 24 h at room temperature and for 23 days at 2-8°C. The percentage recoveries of all drugs were between 90 and 115%, with RSD values <10.6%. This method has been shown to be reproducible and sensitive and can be applied to clinical samples from pharmacokinetic studies and also a useful tool in studying the drug interaction studies. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Fragment-based drug discovery using rational design.

Science.gov (United States)

Jhoti, H

2007-01-01

Fragment-based drug discovery (FBDD) is established as an alternative approach to high-throughput screening for generating novel small molecule drug candidates. In FBDD, relatively small libraries of low molecular weight compounds (or fragments) are screened using sensitive biophysical techniques to detect their binding to the target protein. A lower absolute affinity of binding is expected from fragments, compared to much higher molecular weight hits detected by high-throughput screening, due to their reduced size and complexity. Through the use of iterative cycles of medicinal chemistry, ideally guided by three-dimensional structural data, it is often then relatively straightforward to optimize these weak binding fragment hits into potent and selective lead compounds. As with most other lead discovery methods there are two key components of FBDD; the detection technology and the compound library. In this review I outline the two main approaches used for detecting the binding of low affinity fragments and also some of the key principles that are used to generate a fragment library. In addition, I describe an example of how FBDD has led to the generation of a drug candidate that is now being tested in clinical trials for the treatment of cancer.

Development of controlled drug release systems based on thiolated polymers.

Science.gov (United States)

Bernkop-Schnürch, A; Scholler, S; Biebel, R G

2000-05-03

The purpose of the present study was to generate mucoadhesive matrix-tablets based on thiolated polymers. Mediated by a carbodiimide, L-cysteine was thereby covalently linked to polycarbophil (PCP) and sodium carboxymethylcellulose (CMC). The resulting thiolated polymers displayed 100+/-8 and 1280+/-84 micromol thiol groups per gram, respectively (means+/-S.D.; n=6-8). In aqueous solutions these modified polymers were capable of forming inter- and/or intramolecular disulfide bonds. The velocity of this process augmented with increase of the polymer- and decrease of the proton-concentration. The oxidation proceeded more rapidly within thiolated PCP than within thiolated CMC. Due to the formation of disulfide bonds within thiol-containing polymers, the stability of matrix-tablets based on such polymers could be strongly improved. Whereas tablets based on the corresponding unmodified polymer disintegrated within 2 h, the swollen carrier matrix of thiolated CMC and PCP remained stable for 6.2 h (mean, n=4) and more than 48 h, respectively. Release studies of the model drug rifampicin demonstrated that a controlled release can be provided by thiolated polymer tablets. The combination of high stability, controlled drug release and mucoadhesive properties renders matrix-tablets based on thiolated polymers useful as novel drug delivery systems.

Illicit Drugs, Policing and the Evidence-Based Policy Paradigm

Science.gov (United States)

Ritter, Alison; Lancaster, Kari

2013-01-01

The mantra of evidence-based policy (EBP) suggests that endeavours to implement evidence-based policing will produce better outcomes. However there is dissonance between the rhetoric of EBP and the actuality of policing policy. This disjuncture is critically analysed using the case study of illicit drugs policing. The dissonance may be ameliorated…

Fragment-based drug discovery and protein–protein interactions

Directory of Open Access Journals (Sweden)

Turnbull AP

2014-09-01

Full Text Available Andrew P Turnbull,1 Susan M Boyd,2 Björn Walse31CRT Discovery Laboratories, Department of Biological Sciences, Birkbeck, University of London, London, UK; 2IOTA Pharmaceuticals Ltd, Cambridge, UK; 3SARomics Biostructures AB, Lund, SwedenAbstract: Protein–protein interactions (PPIs are involved in many biological processes, with an estimated 400,000 PPIs within the human proteome. There is significant interest in exploiting the relatively unexplored potential of these interactions in drug discovery, driven by the need to find new therapeutic targets. Compared with classical drug discovery against targets with well-defined binding sites, developing small-molecule inhibitors against PPIs where the contact surfaces are frequently more extensive and comparatively flat, with most of the binding energy localized in “hot spots”, has proven far more challenging. However, despite the difficulties associated with targeting PPIs, important progress has been made in recent years with fragment-based drug discovery playing a pivotal role in improving their tractability. Computational and empirical approaches can be used to identify hot-spot regions and assess the druggability and ligandability of new targets, whilst fragment screening campaigns can detect low-affinity fragments that either directly or indirectly perturb the PPI. Once fragment hits have been identified and confirmed using biochemical and biophysical approaches, three-dimensional structural data derived from nuclear magnetic resonance or X-ray crystallography can be used to drive medicinal chemistry efforts towards the development of more potent inhibitors. A small-scale comparison presented in this review of “standard” fragments with those targeting PPIs has revealed that the latter tend to be larger, be more lipophilic, and contain more polar (acid/base functionality, whereas three-dimensional descriptor data indicate that there is little difference in their three

Building a knowledge base of severe adverse drug events based on AERS reporting data using semantic web technologies.

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Jiang, Guoqian; Wang, Liwei; Liu, Hongfang; Solbrig, Harold R; Chute, Christopher G

2013-01-01

A semantically coded knowledge base of adverse drug events (ADEs) with severity information is critical for clinical decision support systems and translational research applications. However it remains challenging to measure and identify the severity information of ADEs. The objective of the study is to develop and evaluate a semantic web based approach for building a knowledge base of severe ADEs based on the FDA Adverse Event Reporting System (AERS) reporting data. We utilized a normalized AERS reporting dataset and extracted putative drug-ADE pairs and their associated outcome codes in the domain of cardiac disorders. We validated the drug-ADE associations using ADE datasets from SIDe Effect Resource (SIDER) and the UMLS. We leveraged the Common Terminology Criteria for Adverse Event (CTCAE) grading system and classified the ADEs into the CTCAE in the Web Ontology Language (OWL). We identified and validated 2,444 unique Drug-ADE pairs in the domain of cardiac disorders, of which 760 pairs are in Grade 5, 775 pairs in Grade 4 and 2,196 pairs in Grade 3.

Proteomic analysis of drug-resistant Mycobacterium tuberculosis by one-dimensional gel electrophoresis and charge chromatography.

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Yari, Shamsi; Hadizadeh Tasbiti, Alireza; Ghanei, Mostafa; Shokrgozar, Mohammad Ali; Fateh, Abolfazl; Mahdian, Reza; Yari, Fatemeh; Bahrmand, Ahmadreza

2017-01-01

Multidrug-resistant tuberculosis (MDR-TB) is a form of TB caused by Mycobacterium tuberculosis (M. tuberculosis) that do not respond to, at least, isoniazid and rifampicin, the two most powerful, first-line (or standard) anti-TB drugs. Novel intervention strategies for eliminating this disease were based on finding proteins that can be used for designing new drugs or new and reliable kits for diagnosis. The aim of this study was to compare the protein profiles of MDR-TB with sensitive isolates. Proteomic analysis of M. tuberculosis MDR-TB and sensitive isolates was obtained with ion exchange chromatography coupled with MALDI-TOF-TOF (matrix-assisted laser desorption/ionization) in order to identify individual proteins that have different expression in MDR-TB to be used as a drug target or diagnostic marker for designing valuable TB vaccines or TB rapid tests. We identified eight proteins in MDR-TB isolates, and analyses showed that these proteins are absent in M. tuberculosis-sensitive isolates: (Rv2140c, Rv0009, Rv1932, Rv0251c, Rv2558, Rv1284, Rv3699 and MMP major membrane proteins). These data will provide valuable clues in further investigation for suitable TB rapid tests or drug targets against drug-resistant and sensitive M. tuberculosis isolates.

Adolescent neurocognitive development, self-regulation, and school-based drug use prevention.

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Pokhrel, Pallav; Herzog, Thaddeus A; Black, David S; Zaman, Adnin; Riggs, Nathaniel R; Sussman, Steve

2013-06-01

Adolescence is marked by several key development-related changes, including neurocognitive changes. Cognitive abilities associated with self-regulation are not fully developed until late adolescence or early adulthood whereas tendencies to take risks and seek thrilling and novel experience seem to increase significantly throughout this phase, resulting in a discrepancy between increased susceptibility to poor regulation and lower ability to exercise self-control. Increased vulnerability to drug use initiation, maintenance, and dependence during adolescence may be explained based on this imbalance in the self-regulation system. In this paper, we highlight the relevance of schools as a setting for delivering adolescent drug use prevention programs that are based on recent findings from neuroscience concerning adolescent brain development. We discuss evidence from school-based as well as laboratory research that suggests that suitable training may improve adolescents' executive brain functions that underlie self-regulation abilities and, as a result, help prevent drug use and abuse. We note that considerable further research is needed in order (1) to determine that self-regulation training has effects at the neurocognitive level and (2) to effectively incorporate self-regulation training based on neuropsychological models into school-based programming.

Illicit drug use is increasing among non-medical users of prescription drugs-Results from population-based surveys 2002-2014.

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Karjalainen, Karoliina; Lintonen, Tomi; Hakkarainen, Pekka

2017-09-01

Non-medical use of prescription drugs (NMUPD) is known to be associated with illicit drug use, but less is known about how illicit drug use has changed in NMUPD. We examined (1) the changes in illicit drug use among Finnish non-medical users of prescription drugs during the 2000s and (2) whether the trends of illicit drug use differ by non-medical use of prescription drugs in the general population. Data were derived from population-based (aged 15-69) Drug Surveys conducted in Finland in 2002, 2006, 2010 and 2014. The response rates varied between 63% and 48%. NMUPD during the last year was measured (n=252). Past-year illicit drug use among non-medical users of prescription drugs and the reference population not reporting NMUPD (n=10,967) was compared. Logistic regression was used to estimate the p-values for trends. Illicit drug use has increased notably among Finnish non-medical users of prescription drugs (from 21% to 70%, p for trendillicit drug use also increased statistically significantly, but much more moderately (from 2.5% to 5.4%). The difference between the trends was confirmed by an interaction test (p=0.022). NMUPD seems to be increasingly merging with illicit drug use. This indicates an increasing prevalence of polydrug use among non-medical users of prescription drugs, which may bring about more severe harms and worse health outcomes for users and more challenges in regard to treatment. Copyright © 2017 Elsevier B.V. All rights reserved.

Hair analysis in toxicological investigation of drug-facilitated crimes in Denmark over a 8-year period.

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Wang, Xin; Johansen, Sys Stybe; Nielsen, Marie Katrine Klose; Linnet, Kristian

2018-04-01

Hair can serve as a specimen for identifying past drug exposure. Segmental hair analysis may differentiate a single exposure from chronic use. Consequently, segmental hair analysis is useful for disclosing a single drug ingestion, as well as for determining repeated exposures in drug-facilitated crimes (DFCs). This paper presents an overview of toxicological investigations that have used hair analysis in DFC cases from 2009 to 2016 in Denmark. Hair concentrations were determined for 24 DFC-related drugs and metabolites, including benzodiazepines and other hypnotics, antihistamines, opioid analgesics, antipsychotics, barbiturates, and illicit drugs from DFC cases. Drug detection in hair in DFC cases following a single or few intakes of chlorprothixene, codeine, diphenhydramine, oxazepam, oxycodone, promethazine, and phenobarbital is reported for the first time in forensic toxicology. A literature review on concentrations in the published DFC-related hair cases and on concentrations in hair of these substances after single and multiple doses is included. These cases demonstrate the value of segmental hair analysis in DFCs and facilitate future interpretations of results. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

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Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2018-01-01

Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Determination of drugs and drug-like compounds in different samples with direct analysis in real time mass spectrometry.

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Chernetsova, Elena S; Morlock, Gertrud E

2011-01-01

Direct analysis in real time (DART), a relatively new ionization source for mass spectrometry, ionizes small-molecule components from different kinds of samples without any sample preparation and chromatographic separation. The current paper reviews the published data available on the determination of drugs and drug-like compounds in different matrices with DART-MS, including identification and quantitation issues. Parameters that affect ionization efficiency and mass spectra composition are also discussed. Copyright © 2011 Wiley Periodicals, Inc.

Ingenious pH-sensitive dextran/mesoporous silica nanoparticles based drug delivery systems for controlled intracellular drug release.

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Zhang, Min; Liu, Jia; Kuang, Ying; Li, Qilin; Zheng, Di-Wei; Song, Qiongfang; Chen, Hui; Chen, Xueqin; Xu, Yanglin; Li, Cao; Jiang, Bingbing

2017-05-01

In this work, dextran, a polysaccharide with excellent biocompatibility, is applied as the "gatekeeper" to fabricate the pH-sensitive dextran/mesoporous silica nanoparticles (MSNs) based drug delivery systems for controlled intracellular drug release. Dextran encapsulating on the surface of MSNs is oxidized by NaIO 4 to obtain three kinds of dextran dialdehydes (PADs), which are then coupled with MSNs via pH-sensitive hydrazone bond to fabricate three kinds of drug carriers. At pH 7.4, PADs block the pores to prevent premature release of anti-cancer drug doxorubicin hydrochloride (DOX). However, in the weakly acidic intracellular environment (pH∼5.5) the hydrazone can be ruptured; and the drug can be released from the carriers. The drug loading capacity, entrapment efficiency and release rates of the drug carriers can be adjusted by the amount of NaIO 4 applied in the oxidation reaction. And from which DOX@MSN-NH-N=C-PAD 10 is chosen as the most satisfactory one for the further in vitro cytotoxicity studies and cellular uptake studies. The results demonstrate that DOX@MSN-NH-N=C-PAD 10 with an excellent pH-sensitivity can enter HeLa cells to release DOX intracellular due to the weakly acidic pH intracellular and kill the cells. In our opinion, the ingenious pH-sensitive drug delivery systems have application potentials for cancer therapy. Copyright © 2017 Elsevier B.V. All rights reserved.

Derivatization reactions in the gas—liquid chromatographic analysis of drugs in biological fluids

NARCIS (Netherlands)

Hulshoff, A.; Lingeman, H.

1984-01-01

Alkylation, acylation, silylation and other derivatization reactions applied to the gas chromatographic analysis of drugs in biological matrices are reviewed. Reaction conditions are discussed in relation to reaction mechanisms. Detector-oriented labelling of drugs, and derivatization with chiral

Are patients reliable when self-reporting medication use? Validation of structured drug interviews and home visits by drug analysis and prescription data in acutely hospitalized patients

DEFF Research Database (Denmark)

Glintborg, Bente; Hillestrøm, Peter René; Olsen, Lenette Holm

2007-01-01

inspected, and patients were interviewed about their drug use. Additional blood samples were drawn for drug analysis. The median age of included patients was 72 years, and 298 patients (60%) were women. Patients reported use of 3 (median) prescription-only medications (range, 0-14) during the structured...... interview. The congruence between self-report and drug analysis was high for all 5 drugs measured (all kappa >0.8). However, 9 patients (2%) reported use of drugs that were not detected in their blood samples. In 29 patients (6%), the blood samples contained drugs not reported during the structured...... to an acute medical department at a Danish university hospital were interviewed on the day of admission about their recent medication use. Blood samples drawn immediately after admission were screened for contents of 5 drugs (digoxin, bendroflumethiazide, amlodipine, simvastatin, glimepiride), and the results...

The effect of activated charcoal on drug exposure in healthy volunteers: a meta-analysis

DEFF Research Database (Denmark)

Jürgens, G; Hoegberg, L C Groth; Graudal, N A

2009-01-01

The objective of the study was to estimate the effect of activated charcoal (AC) administered during the first 6 h after drug intake and the effect of drug properties on drug exposure. Sixty-four controlled studies were integrated in a meta-analysis. AC administered 0-5 min after administration...

Predicting Drug-Target Interactions Based on Small Positive Samples.

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Hu, Pengwei; Chan, Keith C C; Hu, Yanxing

2018-01-01

A basic task in drug discovery is to find new medication in the form of candidate compounds that act on a target protein. In other words, a drug has to interact with a target and such drug-target interaction (DTI) is not expected to be random. Significant and interesting patterns are expected to be hidden in them. If these patterns can be discovered, new drugs are expected to be more easily discoverable. Currently, a number of computational methods have been proposed to predict DTIs based on their similarity. However, such as approach does not allow biochemical features to be directly considered. As a result, some methods have been proposed to try to discover patterns in physicochemical interactions. Since the number of potential negative DTIs are very high both in absolute terms and in comparison to that of the known ones, these methods are rather computationally expensive and they can only rely on subsets, rather than the full set, of negative DTIs for training and validation. As there is always a relatively high chance for negative DTIs to be falsely identified and as only partial subset of such DTIs is considered, existing approaches can be further improved to better predict DTIs. In this paper, we present a novel approach, called ODT (one class drug target interaction prediction), for such purpose. One main task of ODT is to discover association patterns between interacting drugs and proteins from the chemical structure of the former and the protein sequence network of the latter. ODT does so in two phases. First, the DTI-network is transformed to a representation by structural properties. Second, it applies a oneclass classification algorithm to build a prediction model based only on known positive interactions. We compared the best AUROC scores of the ODT with several state-of-art approaches on Gold standard data. The prediction accuracy of the ODT is superior in comparison with all the other methods at GPCRs dataset and Ion channels dataset. Performance