Cytochrome P450 enzyme mediated herbal drug interactions (Part 2)

Science.gov (United States)

Wanwimolruk, Sompon; Phopin, Kamonrat; Prachayasittikul, Virapong

2014-01-01

To date, a number of significant herbal drug interactions have their origins in the alteration of cytochrome P450 (CYP) activity by various phytochemicals. Among the most noteworthy are those involving St. John's wort and drugs metabolized by human CYP3A4 enzyme. This review article is the continued work from our previous article (Part 1) published in this journal (Wanwimolruk and Prachayasittikul, 2014[ref:133]). This article extends the scope of the review to six more herbs and updates information on herbal drug interactions. These include black cohosh, ginseng, grape seed extract, green tea, kava, saw palmetto and some important Chinese medicines are also presented. Even though there have been many studies to determine the effects of herbs and herbal medicines on the activity of CYP, most of them were in vitro and in animal studies. Therefore, the studies are limited in predicting the clinical relevance of herbal drug interactions. It appeared that the majority of the herbal medicines have no clear effects on most of the CYPs examined. For example, the existing clinical trial data imply that black cohosh, ginseng and saw palmetto are unlikely to affect the pharmacokinetics of conventional drugs metabolized by human CYPs. For grape seed extract and green tea, adverse herbal drug interactions are unlikely when they are concomitantly taken with prescription drugs that are CYP substrates. Although there were few clinical studies on potential CYP-mediated interactions produced by kava, present data suggest that kava supplements have the ability to inhibit CYP1A2 and CYP2E1 significantly. Therefore, caution should be taken when patients take kava with CYP1A2 or CYP2E1 substrate drugs as it may enhance their therapeutic and adverse effects. Despite the long use of traditional Chinese herbal medicines, little is known about the potential drug interactions with these herbs. Many popularly used Chinese medicines have been shown in vitro to significantly change the

Species differences in drug glucuronidation: Humanized UDP-glucuronosyltransferase 1 mice and their application for predicting drug glucuronidation and drug-induced toxicity in humans.

Science.gov (United States)

Fujiwara, Ryoichi; Yoda, Emiko; Tukey, Robert H

2018-02-01

More than 20% of clinically used drugs are glucuronidated by a microsomal enzyme UDP-glucuronosyltransferase (UGT). Inhibition or induction of UGT can result in an increase or decrease in blood drug concentration. To avoid drug-drug interactions and adverse drug reactions in individuals, therefore, it is important to understand whether UGTs are involved in metabolism of drugs and drug candidates. While most of glucuronides are inactive metabolites, acyl-glucuronides that are formed from compounds with a carboxylic acid group can be highly toxic. Animals such as mice and rats are widely used to predict drug metabolism and drug-induced toxicity in humans. However, there are marked species differences in the expression and function of drug-metabolizing enzymes including UGTs. To overcome the species differences, mice in which certain drug-metabolizing enzymes are humanized have been recently developed. Humanized UGT1 (hUGT1) mice were created in 2010 by crossing Ugt1-null mice with human UGT1 transgenic mice in a C57BL/6 background. hUGT1 mice can be promising tools to predict human drug glucuronidation and acyl-glucuronide-associated toxicity. In this review article, studies of drug metabolism and toxicity in the hUGT1 mice are summarized. We further discuss research and strategic directions to advance the understanding of drug glucuronidation in humans. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

Drug interactions in African herbal remedies.

Science.gov (United States)

Cordier, Werner; Steenkamp, Vanessa

2011-01-01

Herbal usage remains popular as an alternative or complementary form of treatment, especially in Africa. However, the misconception that herbal remedies are safe due to their "natural" origins jeopardizes human safety, as many different interactions can occur with concomitant use with other pharmaceuticals on top of potential inherent toxicity. Cytochrome P450 enzymes are highly polymorphic, and pose a problem for pharmaceutical drug tailoring to meet an individual's specific metabolic activity. The influence of herbal remedies further complicates this. The plants included in this review have been mainly researched for determining their effect on cytochrome P450 enzymes and P-glycoprotein drug transporters. Usage of herbal remedies, such as Hypoxis hemerocallidea, Sutherlandia frutescens and Harpagophytum procumbensis popular in Africa. The literature suggests that there is a potential for drug-herb interactions, which could occur through alterations in metabolism and transportation of drugs. Research has primarily been conducted in vitro, whereas in vivo data are lacking. Research concerning the effect of African herbals on drug metabolism should also be approached, as specific plants are especially popular in conjunction with certain treatments. Although these interactions can be beneficial, the harm they pose is just as great.

Albumin-drug interaction and its clinical implication.

Science.gov (United States)

Yamasaki, Keishi; Chuang, Victor Tuan Giam; Maruyama, Toru; Otagiri, Masaki

2013-12-01

Human serum albumin acts as a reservoir and transport protein for endogenous (e.g. fatty acids or bilirubin) and exogenous compounds (e.g. drugs or nutrients) in the blood. The binding of a drug to albumin is a major determinant of its pharmacokinetic and pharmacodynamic profile. The present review discusses recent findings regarding the nature of drug binding sites, drug-albumin binding in certain diseased states or in the presence of coadministered drugs, and the potential of utilizing albumin-drug interactions in clinical applications. Drug-albumin interactions appear to predominantly occur at one or two specific binding sites. The nature of these drug binding sites has been fundamentally investigated as to location, size, charge, hydrophobicity or changes that can occur under conditions such as the content of the endogenous substances in question. Such findings can be useful tools for the analysis of drug-drug interactions or protein binding in diseased states. A change in protein binding is not always a problem in terms of drug therapy, but it can be used to enhance the efficacy of therapeutic agents or to enhance the accumulation of radiopharmaceuticals to targets for diagnostic purposes. Furthermore, several extracorporeal dialysis procedures using albumin-containing dialysates have proven to be an effective tool for removing endogenous toxins or overdosed drugs from patients. Recent findings related to albumin-drug interactions as described in this review are useful for providing safer and efficient therapies and diagnoses in clinical settings. This article is part of a Special Issue entitled Serum Albumin. Copyright © 2013 Elsevier B.V. All rights reserved.

Interaction of coenzyme Q10 with the intestinal drug transporter P-glycoprotein.

Science.gov (United States)

Itagaki, Shirou; Ochiai, Akiko; Kobayashi, Masaki; Sugawara, Mitsuru; Hirano, Takeshi; Iseki, Ken

2008-08-27

In clinical trials, patients usually take many kinds of drugs at the same time. Thus, drug-drug interactions can often directly affect the therapeutic safety and efficacy of many drugs. Oral delivery is the most desirable means of drug administration. Changes in the activity of drug transporters may substantially influence the absorption of administered drugs from the intestine. However, there have been a few studies on food-drug interactions involving transporters. It is important to be aware of the potential of food-drug interactions and to act in order to prevent undesirable and harmful clinical consequences. Coenzyme Q10 (CoQ10) is very widely consumed by humans as a food supplement because of its recognition by the public as an important nutrient in supporting human health. Since intestinal efflux transporter P-glycoprotein (P-gp) is one of the major factors in drug-drug interactions, we focused on this transporter. We report here for the first time that CoQ10, which is widely used as a food supplement, affects the transport activity of P-gp.

Comparative analysis of three drug-drug interaction screening systems against probable clinically relevant drug-drug interactions: a prospective cohort study.

Science.gov (United States)

Muhič, Neža; Mrhar, Ales; Brvar, Miran

2017-07-01

Drug-drug interaction (DDI) screening systems report potential DDIs. This study aimed to find the prevalence of probable DDI-related adverse drug reactions (ADRs) and compare the clinical usefulness of different DDI screening systems to prevent or warn against these ADRs. A prospective cohort study was conducted in patients urgently admitted to medical departments. Potential DDIs were checked using Complete Drug Interaction®, Lexicomp® Online™, and Drug Interaction Checker®. The study team identified the patients with probable clinically relevant DDI-related ADRs on admission, the causality of which was assessed using the Drug Interaction Probability Scale (DIPS). Sensitivity, specificity, and positive and negative predictive values of screening systems to prevent or warn against probable DDI-related ADRs were evaluated. Overall, 50 probable clinically relevant DDI-related ADRs were found in 37 out of 795 included patients taking at least two drugs, most common of them were bleeding, hyperkalemia, digitalis toxicity, and hypotension. Complete Drug Interaction showed the best sensitivity (0.76) for actual DDI-related ADRs, followed by Lexicomp Online (0.50), and Drug Interaction Checker (0.40). Complete Drug Interaction and Drug Interaction Checker had positive predictive values of 0.07; Lexicomp Online had 0.04. We found no difference in specificity and negative predictive values among these systems. DDI screening systems differ significantly in their ability to detect probable clinically relevant DDI-related ADRs in terms of sensitivity and positive predictive value.

Interactions between recreational drugs and antiretroviral agents.

Science.gov (United States)

Antoniou, Tony; Tseng, Alice Lin-In

2002-10-01

To summarize existing data regarding potential interactions between recreational drugs and drugs commonly used in the management of HIV-positive patients. Information was obtained via a MEDLINE search (1966-August 2002) using the MeSH headings human immunodeficiency virus, drug interactions, cytochrome P450, medication names commonly prescribed for the management of HIV and related opportunistic infections, and names of commonly used recreational drugs. Abstracts of national and international conferences, review articles, textbooks, and references of all articles were also reviewed. Literature on pharmacokinetic interactions was considered for inclusion. Pertinent information was selected and summarized for discussion. In the absence of specific data, prediction of potential clinically significant interactions was based on pharmacokinetic and pharmacodynamic properties. All protease inhibitors (PIs) and nonnucleoside reverse transcriptase inhibitors are substrates and potent inhibitors or inducers of the cytochrome P450 system. Many classes of recreational drugs, including benzodiazepines, amphetamines, and opioids, are also metabolized by the liver and can potentially interact with antiretrovirals. Controlled interaction studies are often not available, but clinically significant interactions have been observed in a number of case reports. Overdoses secondary to interactions between the "rave" drugs methylenedioxymethamphetamine (MDMA) or gamma-hydroxybutyrate (GHB) and PIs have been reported. PIs, particularly ritonavir, may also inhibit metabolism of amphetamines, ketamine, lysergic acid diethylmide (LSD), and phencyclidine (PCP). Case series and pharmacokinetic studies suggest that nevirapine and efavirenz induce methadone metabolism, which may lead to symptoms of opiate withdrawal. A similar interaction may exist between methadone and the PIs ritonavir and nelfinavir, although the data are less consistent. Opiate metabolism can be inhibited or induced by

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures

Energy Technology Data Exchange (ETDEWEB)

Cao Dongsheng [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Liu Shao [Xiangya Hospital, Central South University, Changsha 410008 (China); Xu Qingsong [School of Mathematical Sciences and Computing Technology, Central South University, Changsha 410083 (China); Lu Hongmei; Huang Jianhua [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China); Hu Qiannan [Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, and Wuhan University School of Pharmaceutical Sciences, Wuhan 430071 (China); Liang Yizeng, E-mail: yizeng_liang@263.net [Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083 (China)

2012-11-08

Highlights: Black-Right-Pointing-Pointer Drug-target interactions are predicted using an extended SAR methodology. Black-Right-Pointing-Pointer A drug-target interaction is regarded as an event triggered by many factors. Black-Right-Pointing-Pointer Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. Black-Right-Pointing-Pointer Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug-target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner. In this article, we aim at extending current structure-activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug-target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug-target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug

Drug-radiopharmaceutical interactions

International Nuclear Information System (INIS)

Hladik, W.B.; Ponto, J.A.; Stathis, V.J.

1985-01-01

Patients seen in the nuclear medicine department have a wide variety of disorders and, consequently, may be receiving any number of therapeutic drugs. For this reason, nuclear medicine professionals should be aware of the potential effects that these pharmacologic agents may have on the bio-distribution of subsequently administered radiopharmaceuticals, commonly referred to as ''drug-radiopharmaceutical interactions.'' Compared with the quantity of literature written about interactions between various therapeutic drugs, the information available on drug-radiopharmaceutical interactions is scarce. However, there has been increasing interest in this subject, particularly during the past five years. Some of the reported interactions are used intentionally to add a new dimension to the nuclear medicine study and increase its diagnostic capabilities, i.e., pharmacologic intervention. These beneficial ''interactions'' are discussed in detail in several other chapters of this book. Other interactions, however, cause changes in the normal distribution of radiopharmaceuticals, which may interfere with the diagnostic utility of various nuclear medicine procedures. The latter group of interactions is the focus of this chapter

Global patient safety and antiretroviral drug-drug interactions in the resource-limited setting.

Science.gov (United States)

Seden, Kay; Khoo, Saye H; Back, David; Byakika-Kibwika, Pauline; Lamorde, Mohammed; Ryan, Mairin; Merry, Concepta

2013-01-01

Scale-up of HIV treatment services may have contributed to an increase in functional health facilities available in resource-limited settings and an increase in patient use of facilities and retention in care. As more patients are reached with medicines, monitoring patient safety is increasingly important. Limited data from resource-limited settings suggest that medication error and antiretroviral drug-drug interactions may pose a significant risk to patient safety. Commonly cited causes of medication error in the developed world include the speed and complexity of the medication use cycle combined with inadequate systems and processes. In resource-limited settings, specific factors may contribute, such as inadequate human resources and high disease burden. Management of drug-drug interactions may be complicated by limited access to alternative medicines or laboratory monitoring. Improving patient safety by addressing the issue of antiretroviral drug-drug interactions has the potential not just to improve healthcare for individuals, but also to strengthen health systems and improve vital communication among healthcare providers and with regulatory agencies.

Drug-Drug and Herb-Drug Interaction-A Comment | Esimone ...

African Journals Online (AJOL)

Clinically relevant drug-drug interactions may be pharmacodynamic or pharmacokinetic. And herbal medicinal products are becoming increasingly popular. Drug interactions can be in vivo or in vitro. Pharmacodynamic outcomes take such forms as Additive, Synergistic, Antagonistic or Indifferent. The paper reviews and ...

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

Science.gov (United States)

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.

Drug interactions between common illicit drugs and prescription therapies.

Science.gov (United States)

Lindsey, Wesley T; Stewart, David; Childress, Darrell

2012-07-01

The aim was to summarize the clinical literature on interactions between common illicit drugs and prescription therapies. Medline, Iowa Drug Information Service, International Pharmaceutical Abstracts, EBSCO Academic Search Premier, and Google Scholar were searched from date of origin of database to March 2011. Search terms were cocaine, marijuana, cannabis, methamphetamine, amphetamine, ecstasy, N-methyl-3,4-methylenedioxymethamphetamine, methylenedioxymethamphetamine, heroin, gamma-hydroxybutyrate, sodium oxybate, and combined with interactions, drug interactions, and drug-drug interactions. This review focuses on established clinical evidence. All applicable full-text English language articles and abstracts found were evaluated and included in the review as appropriate. The interactions of illicit drugs with prescription therapies have the ability to potentiate or attenuate the effects of both the illicit agent and/or the prescription therapeutic agent, which can lead to toxic effects or a reduction in the prescription agent's therapeutic activity. Most texts and databases focus on theoretical or probable interactions due to the kinetic properties of the drugs and do not fully explore the pharmacodynamic and clinical implications of these interactions. Clinical trials with coadministration of illicit drugs and prescription drugs are discussed along with case reports that demonstrate a potential interaction between agents. The illicit drugs discussed are cocaine, marijuana, amphetamines, methylenedioxymethamphetamine, heroin, and sodium oxybate. Although the use of illicit drugs is widespread, there are little experimental or clinical data regarding the effects of these agents on common prescription therapies. Potential drug interactions between illicit drugs and prescription drugs are described and evaluated on the Drug Interaction Probability Scale by Horn and Hansten.

Data on overlapping brain disorders and emerging drug targets in human Dopamine Receptors Interaction Network

Directory of Open Access Journals (Sweden)

Avijit Podder

2017-06-01

Full Text Available Intercommunication of Dopamine Receptors (DRs with their associate protein partners is crucial to maintain regular brain function in human. Majority of the brain disorders arise due to malfunctioning of such communication process. Hence, contributions of genetic factors, as well as phenotypic indications for various neurological and psychiatric disorders are often attributed as sharing in nature. In our earlier research article entitled “Human Dopamine Receptors Interaction Network (DRIN: a systems biology perspective on topology, stability and functionality of the network” (Podder et al., 2014 [1], we had depicted a holistic interaction map of human Dopamine Receptors. Given emphasis on the topological parameters, we had characterized the functionality along with the vulnerable properties of the network. In support of this, we hereby provide an additional data highlighting the genetic overlapping of various brain disorders in the network. The data indicates the sharing nature of disease genes for various neurological and psychiatric disorders in dopamine receptors connecting protein-protein interactions network. The data also indicates toward an alternative approach to prioritize proteins for overlapping brain disorders as valuable drug targets in the network.

Chimeric mice with humanized liver: Application in drug metabolism and pharmacokinetics studies for drug discovery.

Science.gov (United States)

Naritomi, Yoichi; Sanoh, Seigo; Ohta, Shigeru

2018-02-01

Predicting human drug metabolism and pharmacokinetics (PK) is key to drug discovery. In particular, it is important to predict human PK, metabolite profiles and drug-drug interactions (DDIs). Various methods have been used for such predictions, including in vitro metabolic studies using human biological samples, such as hepatic microsomes and hepatocytes, and in vivo studies using experimental animals. However, prediction studies using these methods are often inconclusive due to discrepancies between in vitro and in vivo results, and interspecies differences in drug metabolism. Further, the prediction methods have changed from qualitative to quantitative to solve these issues. Chimeric mice with humanized liver have been developed, in which mouse liver cells are mostly replaced with human hepatocytes. Since human drug metabolizing enzymes are expressed in the liver of these mice, they are regarded as suitable models for mimicking the drug metabolism and PK observed in humans; therefore, these mice are useful for predicting human drug metabolism and PK. In this review, we discuss the current state, issues, and future directions of predicting human drug metabolism and PK using chimeric mice with humanized liver in drug discovery. Copyright © 2017 The Japanese Society for the Study of Xenobiotics. Published by Elsevier Ltd. All rights reserved.

Predicting drug?drug interactions through drug structural similarities and interaction networks incorporating pharmacokinetics and pharmacodynamics knowledge

OpenAIRE

Takeda, Takako; Hao, Ming; Cheng, Tiejun; Bryant, Stephen H.; Wang, Yanli

2017-01-01

Drug?drug interactions (DDIs) may lead to adverse effects and potentially result in drug withdrawal from the market. Predicting DDIs during drug development would help reduce development costs and time by rigorous evaluation of drug candidates. The primary mechanisms of DDIs are based on pharmacokinetics (PK) and pharmacodynamics (PD). This study examines the effects of 2D structural similarities of drugs on DDI prediction through interaction networks including both PD and PK knowledge. Our a...

Idiosyncratic Drug-Induced Liver Injury: Is Drug-Cytokine Interaction the Linchpin?

Science.gov (United States)

Roth, Robert A; Maiuri, Ashley R; Ganey, Patricia E

2017-02-01

Idiosyncratic drug-induced liver injury continues to be a human health problem in part because drugs that cause these reactions are not identified in current preclinical testing and because progress in prevention is hampered by incomplete knowledge of mechanisms that underlie these adverse responses. Several hypotheses involving adaptive immune responses, inflammatory stress, inability to adapt to stress, and multiple, concurrent factors have been proposed. Yet much remains unknown about how drugs interact with the liver to effect death of hepatocytes. Evidence supporting hypotheses implicating adaptive or innate immune responses in afflicted patients has begun to emerge and is bolstered by results obtained in experimental animal models and in vitro systems. A commonality in adaptive and innate immunity is the production of cytokines, including interferon-γ (IFNγ). IFNγ initiates cell signaling pathways that culminate in cell death or inhibition of proliferative repair. Tumor necrosis factor-α, another cytokine prominent in immune responses, can also promote cell death. Furthermore, tumor necrosis factor-α interacts with IFNγ, leading to enhanced cellular responses to each cytokine. In this short review, we propose that the interaction of drugs with these cytokines contributes to idiosyncratic drug-induced liver injury, and mechanisms by which this could occur are discussed. Copyright © 2017 by The American Society for Pharmacology and Experimental Therapeutics.

Grapefruit and drug interactions.

Science.gov (United States)

2012-12-01

Since the late 1980s, grapefruit juice has been known to affect the metabolism of certain drugs. Several serious adverse effects involving drug interactions with grapefruit juice have been published in detail. The components of grapefruit juice vary considerably depending on the variety, maturity and origin of the fruit, local climatic conditions, and the manufacturing process. No single component accounts for all observed interactions. Other grapefruit products are also occasionally implicated, including preserves, lyophylised grapefruit juice, powdered whole grapefruit, grapefruit seed extract, and zest. Clinical reports of drug interactions with grapefruit juice are supported by pharmacokinetic studies, each usually involving about 10 healthy volunteers, in which the probable clinical consequences were extrapolated from the observed plasma concentrations. Grapefruit juice inhibits CYP3A4, the cytochrome P450 isoenzyme most often involved in drug metabolism. This increases plasma concentrations of the drugs concerned, creating a risk of overdose and dose-dependent adverse effects. Grapefruit juice also inhibits several other cytochrome P450 isoenzymes, but they are less frequently implicated in interactions with clinical consequences. Drugs interacting with grapefruit and inducing serious clinical consequences (confirmed or very probable) include: immunosuppressants, some statins, benzodiazepines, most calcium channel blockers, indinavir and carbamazepine. There are large inter-individual differences in enzyme efficiency. Along with the variable composition of grapefruit juice, this makes it difficult to predict the magnitude and clinical consequences of drug interactions with grapefruit juice in a given patient. There is increasing evidence that transporter proteins such as organic anion transporters and P-glycoprotein are involved in interactions between drugs and grapefruit juice. In practice, numerous drugs interact with grapefruit juice. Although only a few

Potential drug-drug and drug-disease interactions in well-functioning community-dwelling older adults.

Science.gov (United States)

Hanlon, J T; Perera, S; Newman, A B; Thorpe, J M; Donohue, J M; Simonsick, E M; Shorr, R I; Bauer, D C; Marcum, Z A

2017-04-01

There are few studies examining both drug-drug and drug-disease interactions in older adults. Therefore, the objective of this study was to describe the prevalence of potential drug-drug and drug-disease interactions and associated factors in community-dwelling older adults. This cross-sectional study included 3055 adults aged 70-79 without mobility limitations at their baseline visit in the Health Aging and Body Composition Study conducted in the communities of Pittsburgh PA and Memphis TN, USA. The outcome factors were potential drug-drug and drug-disease interactions as per the application of explicit criteria drawn from a number of sources to self-reported prescription and non-prescription medication use. Over one-third of participants had at least one type of interaction. Approximately one quarter (25·1%) had evidence of had one or more drug-drug interactions. Nearly 10·7% of the participants had a drug-drug interaction that involved a non-prescription medication. % The most common drug-drug interaction was non-steroidal anti-inflammatory drugs (NSAIDs) affecting antihypertensives. Additionally, 16·0% had a potential drug-disease interaction with 3·7% participants having one involving non-prescription medications. The most common drug-disease interaction was aspirin/NSAID use in those with history of peptic ulcer disease without gastroprotection. Over one-third (34·0%) had at least one type of drug interaction. Each prescription medication increased the odds of having at least one type of drug interaction by 35-40% [drug-drug interaction adjusted odds ratio (AOR) = 1·35, 95% confidence interval (CI) = 1·27-1·42; drug-disease interaction AOR = 1·30; CI = 1·21-1·40; and both AOR = 1·45; CI = 1·34-1·57]. A prior hospitalization increased the odds of having at least one type of drug interaction by 49-84% compared with those not hospitalized (drug-drug interaction AOR = 1·49, 95% CI = 1·11-2·01; drug-disease interaction AOR = 1·69, CI = 1·15-2�

Estimation of the binding modes with important human cytochrome P450 enzymes, drug interaction potential, pharmacokinetics, and hepatotoxicity of ginger components using molecular docking, computational, and pharmacokinetic modeling studies.

Science.gov (United States)

Qiu, Jia-Xuan; Zhou, Zhi-Wei; He, Zhi-Xu; Zhang, Xueji; Zhou, Shu-Feng; Zhu, Shengrong

2015-01-01

Ginger is one of the most commonly used herbal medicines for the treatment of numerous ailments and improvement of body functions. It may be used in combination with prescribed drugs. The coadministration of ginger with therapeutic drugs raises a concern of potential deleterious drug interactions via the modulation of the expression and/or activity of drug-metabolizing enzymes and drug transporters, resulting in unfavorable therapeutic outcomes. This study aimed to determine the molecular interactions between 12 main active ginger components (6-gingerol, 8-gingerol, 10-gingerol, 6-shogaol, 8-shogaol, 10-shogaol, ar-curcumene, β-bisabolene, β-sesquiphelandrene, 6-gingerdione, (-)-zingiberene, and methyl-6-isogingerol) and human cytochrome P450 (CYP) 1A2, 2C9, 2C19, 2D6, and 3A4 and to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET) of the 12 ginger components using computational approaches and comprehensive literature search. Docking studies showed that ginger components interacted with a panel of amino acids in the active sites of CYP1A2, 2C9, 2C19, 2D6, and 3A4 mainly through hydrogen bond formation, to a lesser extent, via π-π stacking. The pharmacokinetic simulation studies showed that the [I]/[Ki ] value for CYP2C9, 2C19, and 3A4 ranged from 0.0002 to 19.6 and the R value ranged from 1.0002 to 20.6 and that ginger might exhibit a high risk of drug interaction via inhibition of the activity of human CYP2C9 and CYP3A4, but a low risk of drug interaction toward CYP2C19-mediated drug metabolism. Furthermore, it has been evaluated that the 12 ginger components possessed a favorable ADMET profiles with regard to the solubility, absorption, permeability across the blood-brain barrier, interactions with CYP2D6, hepatotoxicity, and plasma protein binding. The validation results showed that there was no remarkable effect of ginger on the metabolism of warfarin in humans, whereas concurrent use of ginger and nifedipine exhibited a

Drug-model membrane interactions

International Nuclear Information System (INIS)

Deniz, Usha K.

1994-01-01

In the present day world, drugs play a very important role in medicine and it is necessary to understand their mode of action at the molecular level, in order to optimise their use. Studies of drug-biomembrane interactions are essential for gaining such as understanding. However, it would be prohibitively difficult to carry out such studies, since biomembranes are highly complex systems. Hence, model membranes (made up of these lipids which are important components of biomembranes) of varying degrees of complexity are used to investigate drug-membrane interactions. Bio- as well as model-membranes undergo a chain melting transition when heated, the chains being in a disordered state above the transition point, T CM . This transition is of physiological importance since biomembranes select their components such that T CM is less than the ambient temperature but not very much so, so that membrane flexibility is ensured and porosity, avoided. The influence of drugs on the transition gives valuable clues about various parameters such as the location of the drug in the membrane. Deep insights into drug-membrane interactions are obtained by observing the effect of drugs on membrane structure and the mobilities of the various groups in lipids, near T CM . Investigation of such changes have been carried out with several drugs, using techniques such as DSC, XRD and NMR. The results indicate that the drug-membrane interaction not only depends on the nature of drug and lipids but also on the form of the model membrane - stacked bilayer or vesicles. The light that these results shed on the nature of drug-membrane interactions is discussed. (author). 13 refs., 13 figs., 1 tab

Gaussian interaction profile kernels for predicting drug-target interaction.

Science.gov (United States)

van Laarhoven, Twan; Nabuurs, Sander B; Marchiori, Elena

2011-11-01

The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of all drug-target pairs in current datasets are experimentally validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. We show that a simple machine learning method that uses the drug-target network as the only source of information is capable of predicting true interaction pairs with high accuracy. Specifically, we introduce interaction profiles of drugs (and of targets) in a network, which are binary vectors specifying the presence or absence of interaction with every target (drug) in that network. We define a kernel on these profiles, called the Gaussian Interaction Profile (GIP) kernel, and use a simple classifier, (kernel) Regularized Least Squares (RLS), for prediction drug-target interactions. We test comparatively the effectiveness of RLS with the GIP kernel on four drug-target interaction networks used in previous studies. The proposed algorithm achieves area under the precision-recall curve (AUPR) up to 92.7, significantly improving over results of state-of-the-art methods. Moreover, we show that using also kernels based on chemical and genomic information further increases accuracy, with a neat improvement on small datasets. These results substantiate the relevance of the network topology (in the form of interaction profiles) as source of information for predicting drug-target interactions. Software and Supplementary Material are available at http://cs.ru.nl/~tvanlaarhoven/drugtarget2011/. tvanlaarhoven@cs.ru.nl; elenam@cs.ru.nl. Supplementary data are available at Bioinformatics online.

Observational study of drug-drug interactions in oncological inpatients

Directory of Open Access Journals (Sweden)

María Sacramento Díaz-Carrasco

2018-01-01

Full Text Available Objective: To determine the prevalence of potential clinically relevant drug- drug interactions in adult oncological inpatients, as well as to describe the most frequent interactions. A standard database was used. Method: An observational, transversal, and descriptive study including patients admitted to the Oncology Service of a reference hospital. All prescriptions were collected twice a week during a month. They were analysed using Lexicomp® database, recording all interactions classified with a level of risk: C, D or X. Results: A total of 1 850 drug-drug interactions were detected in 218 treatments. The prevalence of treatments with at least one clinically relevant interaction was 95%, being 94.5% for those at level C and 26.1% for levels D and X. The drugs most commonly involved in the interactions detected were opioid analgesics, antipsychotics (butyrophenones, benzodiazepines, pyrazolones, glucocorticoids and heparins, whereas interactions with antineoplastics were minimal, highlighting those related to paclitaxel and between metamizole and various antineoplastics. Conclusions: The prevalence of clinically relevant drug-drug interactions rate was very high, highlighting the high risk percentage of them related to level of risk X. Due to the frequency of onset and potential severity, highlighted the concomitant use of central nervous system depressants drugs with risk of respiratory depression, the risk of onset of anticholinergic symptoms when combining morphine or haloperidol with butylscopolamine, ipratropium bromide or dexchlorpheniramine and the multiple interactions involving metamizole.

Kidney-on-a-Chip: a New Technology for Predicting Drug Efficacy, Interactions, and Drug-induced Nephrotoxicity.

Science.gov (United States)

Lee, Jeonghwan; Kim, Sejoong

2018-03-08

The kidneys play a pivotal role in most drug-removal processes and are important when evaluating drug safety. Kidney dysfunction resulting from various drugs is an important issue in clinical practice and during the drug development process. Traditional in vivo animal experiments are limited with respect to evaluating drug efficacy and nephrotoxicity due to discrepancies in drug pharmacokinetics and pharmacodynamics between humans and animals, and static cell culture experiments cannot fully reflect the actual microphysiological environment in humans. A kidney-on-a-chip is a microfluidic device that allows the culture of living renal cells in 3-dimensional channels and mimics the human microphysiological environment, thus simulating the actual drug filtering, absorption, and secretion process.. In this review, we discuss recent developments in microfluidic culturing technique and describe current and future kidney-on-a-chip applications. We focus on pharmacological interactions and drug-induced nephrotoxicity, and additionally discuss the development of multi-organ chips and their possible applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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

Science.gov (United States)

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

Drug interactions with radiopharmaceuticals

International Nuclear Information System (INIS)

Hesslewood, S.; Leung, E.

1994-01-01

Considerable information on documented drug and radiopharmaceutical interactions has been assembled in a tabular form, classified by the type of nuclear medicine study. The aim is to provide a rapid reference for nuclear medicine staff to look for such interactions. The initiation of drug chart monitoring or drug history taking of nuclear medicine patients and the reporting of such events are encouraged. (orig.)

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction: a systematic review on CYP2C9, CYP2C19 and CYP2D6.

Science.gov (United States)

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

2017-05-01

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple biotransformation pathways, which is referred to as drug-drug-gene interaction (DDGI). In this systematic review, we report the impact of pharmacogenetics on DDI and DDGI in which three major drug-metabolizing enzymes - CYP2C9, CYP2C19 and CYP2D6 - are central. We observed that several DDI and DDGI are highly gene-dependent, leading to a different magnitude of interaction. Precision drug therapy should take pharmacogenetics into account when drug interactions in clinical practice are expected.

Estimation of the binding modes with important human cytochrome P450 enzymes, drug interaction potential, pharmacokinetics, and hepatotoxicity of ginger components using molecular docking, computational, and pharmacokinetic modeling studies

Directory of Open Access Journals (Sweden)

Qiu JX

2015-02-01

Full Text Available Jia-Xuan Qiu,1,2 Zhi-Wei Zhou,3 Zhi-Xu He,4 Xueji Zhang,5 Shu-Feng Zhou,3 Shengrong Zhu11Department of Stomatology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People’s Republic of China; 2Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, People’s Republic of China; 3Department of Pharmaceutical Sciences, College of Pharmacy, University of South Florida, Tampa, FL, USA; 4Guizhou Provincial Key Laboratory for Regenerative Medicine, Stem Cell and Tissue Engineering Research Center and Sino-US Joint Laboratory for Medical Sciences, Guiyang Medical University, Guiyang, Guizhou, People’s Republic of China; 5Research Center for Bioengineering and Sensing Technology, University of Science and Technology Beijing, Beijing, People’s Republic of ChinaAbstract: Ginger is one of the most commonly used herbal medicines for the treatment of numerous ailments and improvement of body functions. It may be used in combination with prescribed drugs. The coadministration of ginger with therapeutic drugs raises a concern of potential deleterious drug interactions via the modulation of the expression and/or activity of drug-metabolizing enzymes and drug transporters, resulting in unfavorable therapeutic outcomes. This study aimed to determine the molecular interactions between 12 main active ginger components (6-gingerol, 8-gingerol, 10-gingerol, 6-shogaol, 8-shogaol, 10-shogaol, ar-curcumene, ß-bisabolene, ß-sesquiphelandrene, 6-gingerdione, (--zingiberene, and methyl-6-isogingerol and human cytochrome P450 (CYP 1A2, 2C9, 2C19, 2D6, and 3A4 and to predict the absorption, distribution, metabolism, excretion, and toxicity (ADMET of the 12 ginger components using computational approaches and comprehensive literature search. Docking studies showed that ginger components interacted with a panel of amino acids in the active sites of CYP1A

Drug-Target Interactions: Prediction Methods and Applications.

Science.gov (United States)

Anusuya, Shanmugam; Kesherwani, Manish; Priya, K Vishnu; Vimala, Antonydhason; Shanmugam, Gnanendra; Velmurugan, Devadasan; Gromiha, M Michael

2018-01-01

Identifying the interactions between drugs and target proteins is a key step in drug discovery. This not only aids to understand the disease mechanism, but also helps to identify unexpected therapeutic activity or adverse side effects of drugs. Hence, drug-target interaction prediction becomes an essential tool in the field of drug repurposing. The availability of heterogeneous biological data on known drug-target interactions enabled many researchers to develop various computational methods to decipher unknown drug-target interactions. This review provides an overview on these computational methods for predicting drug-target interactions along with available webservers and databases for drug-target interactions. Further, the applicability of drug-target interactions in various diseases for identifying lead compounds has been outlined. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Drug-drug interactions involving lysosomes: mechanisms and potential clinical implications.

Science.gov (United States)

Logan, Randall; Funk, Ryan S; Axcell, Erick; Krise, Jeffrey P

2012-08-01

Many commercially available, weakly basic drugs have been shown to be lysosomotropic, meaning they are subject to extensive sequestration in lysosomes through an ion trapping-type mechanism. The extent of lysosomal trapping of a drug is an important therapeutic consideration because it can influence both activity and pharmacokinetic disposition. The administration of certain drugs can alter lysosomes such that their accumulation capacity for co-administered and/or secondarily administered drugs is altered. In this review the authors explore what is known regarding the mechanistic basis for drug-drug interactions involving lysosomes. Specifically, the authors address the influence of drugs on lysosomal pH, volume and lipid processing. Many drugs are known to extensively accumulate in lysosomes and significantly alter their structure and function; however, the therapeutic and toxicological implications of this remain controversial. The authors propose that drug-drug interactions involving lysosomes represent an important potential source of variability in drug activity and pharmacokinetics. Most evaluations of drug-drug interactions involving lysosomes have been performed in cultured cells and isolated tissues. More comprehensive in vivo evaluations are needed to fully explore the impact of this drug-drug interaction pathway on therapeutic outcomes.

Modulation of trichloroethylene in vitro metabolism by different drugs in human.

Science.gov (United States)

Cheikh Rouhou, Mouna; Haddad, Sami

2014-08-01

Toxicological interactions with drugs have the potential to modulate the toxicity of trichloroethylene (TCE). Our objective is to identify metabolic interactions between TCE and 14 widely used drugs in human suspended hepatocytes and characterize the strongest using microsomal assays. Changes in concentrations of TCE and its metabolites were measured by headspace GC-MS. Results with hepatocytes show that amoxicillin, cimetidine, ibuprofen, mefenamic acid and ranitidine caused no significant interactions. Naproxen and salicylic acid showed to increase both TCE metabolites levels, whereas acetaminophen, carbamazepine and erythromycin rather decreased them. Finally, diclofenac, gliclazide, sulphasalazine and valproic acid had an impact on the levels of only one metabolite. Among the 14 tested drugs, 5 presented the most potent interactions and were selected for confirmation with microsomes, namely naproxen, salicylic acid, acetaminophen, carbamazepine and valproic acid. Characterization in human microsomes confirmed interaction with naproxen by competitively inhibiting trichloroethanol (TCOH) glucuronidation (Ki=2.329 mM). Inhibition of TCOH formation was also confirmed for carbamazepine (partial non-competitive with Ki=70 μM). Interactions with human microsomes were not observed with salicylic acid and acetaminophen, similar to prior results in rat material. For valproic acid, interactions with microsomes were observed in rat but not in human. Inhibition patterns were shown to be similar in human and rat hepatocytes, but some differences in mechanisms were noted in microsomal material between species. Next research efforts will focus on determining the adequacy between in vitro observations and the in vivo situation. Copyright © 2014 Elsevier Ltd. All rights reserved.

Drug-drug interactions of antifungal agents and implications for patient care.

Science.gov (United States)

Gubbins, Paul O; Amsden, Jarrett R

2005-10-01

Drug interactions in the gastrointestinal tract, liver and kidneys result from alterations in pH, ionic complexation, and interference with membrane transport proteins and enzymatic processes involved in intestinal absorption, enteric and hepatic metabolism, renal filtration and excretion. Azole antifungals can be involved in drug interactions at all the sites, by one or more of the above mechanisms. Consequently, azoles interact with a vast array of compounds. Drug-drug interactions associated with amphotericin B formulations are predictable and result from the renal toxicity and electrolyte disturbances associated with these compounds. The echinocandins are unknown cytochrome P450 substrates and to date are relatively devoid of significant drug-drug interactions. This article reviews drug interactions involving antifungal agents that affect other agents and implications for patient care are highlighted.

Exploring drug-target interaction networks of illicit drugs.

Science.gov (United States)

Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

2013-01-01

Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

Characterization of Schizophrenia Adverse Drug Interactions through a Network Approach and Drug Classification

Directory of Open Access Journals (Sweden)

Jingchun Sun

2013-01-01

Full Text Available Antipsychotic drugs are medications commonly for schizophrenia (SCZ treatment, which include two groups: typical and atypical. SCZ patients have multiple comorbidities, and the coadministration of drugs is quite common. This may result in adverse drug-drug interactions, which are events that occur when the effect of a drug is altered by the coadministration of another drug. Therefore, it is important to provide a comprehensive view of these interactions for further coadministration improvement. Here, we extracted SCZ drugs and their adverse drug interactions from the DrugBank and compiled a SCZ-specific adverse drug interaction network. This network included 28 SCZ drugs, 241 non-SCZs, and 991 interactions. By integrating the Anatomical Therapeutic Chemical (ATC classification with the network analysis, we characterized those interactions. Our results indicated that SCZ drugs tended to have more adverse drug interactions than other drugs. Furthermore, SCZ typical drugs had significant interactions with drugs of the “alimentary tract and metabolism” category while SCZ atypical drugs had significant interactions with drugs of the categories “nervous system” and “antiinfectives for systemic uses.” This study is the first to characterize the adverse drug interactions in the course of SCZ treatment and might provide useful information for the future SCZ treatment.

Long chain fatty acids alter the interactive binding of ligands to the two principal drug binding sites of human serum albumin.

Directory of Open Access Journals (Sweden)

Keishi Yamasaki

Full Text Available A wide variety of drugs bind to human serum albumin (HSA at its two principal sites, namely site I and site II. A number of reports indicate that drug binding to these two binding sites are not completely independent, and that interactions between ligands of these two discrete sites can play a role. In this study, the effect of the binding of long-chain fatty acids on the interactive binding between dansyl-L-asparagine (DNSA; site I ligand and ibuprofen (site II ligand at pH6.5 was examined. Binding experiments showed that the binding of sodium oleate (Ole to HSA induces conformational changes in the molecule, which, in turn, changes the individual binding of DNSA and ibuprofen, as well as the mode of interaction between these two ligands from a 'competitive-like' allosteric interaction in the case of the defatted HSA conformer to a 'nearly independent' binding in the case of non-defatted HSA conformer. Circular dichroism measurements indicated that ibuprofen and Ole are likely to modify the spatial orientation of DNSA at its binding site. Docking simulations suggest that the long-distance electric repulsion between DNSA and ibuprofen on defatted HSA contributes to a 'competitive-like' allosteric interaction, whereas extending the distance between ligands and/or increasing the flexibility or size of the DNSA binding site in fatted HSA evokes a change in the interaction mode to 'nearly independent' binding. The present findings provide further insights into the structural dynamics of HSA upon the binding of fatty acids, and its effects on drug binding and drug-drug interactions that occur on HSA.

Application of chimeric mice with humanized liver for study of human-specific drug metabolism.

Science.gov (United States)

Bateman, Thomas J; Reddy, Vijay G B; Kakuni, Masakazu; Morikawa, Yoshio; Kumar, Sanjeev

2014-06-01

Human-specific or disproportionately abundant human metabolites of drug candidates that are not adequately formed and qualified in preclinical safety assessment species pose an important drug development challenge. Furthermore, the overall metabolic profile of drug candidates in humans is an important determinant of their drug-drug interaction susceptibility. These risks can be effectively assessed and/or mitigated if human metabolic profile of the drug candidate could reliably be determined in early development. However, currently available in vitro human models (e.g., liver microsomes, hepatocytes) are often inadequate in this regard. Furthermore, the conduct of definitive radiolabeled human ADME studies is an expensive and time-consuming endeavor that is more suited for later in development when the risk of failure has been reduced. We evaluated a recently developed chimeric mouse model with humanized liver on uPA/SCID background for its ability to predict human disposition of four model drugs (lamotrigine, diclofenac, MRK-A, and propafenone) that are known to exhibit human-specific metabolism. The results from these studies demonstrate that chimeric mice were able to reproduce the human-specific metabolite profile for lamotrigine, diclofenac, and MRK-A. In the case of propafenone, however, the human-specific metabolism was not detected as a predominant pathway, and the metabolite profiles in native and humanized mice were similar; this was attributed to the presence of residual highly active propafenone-metabolizing mouse enzymes in chimeric mice. Overall, the data indicate that the chimeric mice with humanized liver have the potential to be a useful tool for the prediction of human-specific metabolism of xenobiotics and warrant further investigation.

Pharmacogenetics of drug-drug interaction and drug-drug-gene interaction : A systematic review on CYP2C9, CYP2C19 and CYP2D6

NARCIS (Netherlands)

Bahar, Muh Akbar; Setiawan, Didik; Hak, Eelko; Wilffert, Bob

Currently, most guidelines on drug-drug interaction (DDI) neither consider the potential effect of genetic polymorphism in the strength of the interaction nor do they account for the complex interaction caused by the combination of DDI and drug-gene interaction (DGI) where there are multiple

Herb-drug interactions.

Science.gov (United States)

Fugh-Berman, A

2000-01-08

Concurrent use of herbs may mimic, magnify, or oppose the effect of drugs. Plausible cases of herb-drug interactions include: bleeding when warfarin is combined with ginkgo (Ginkgo biloba), garlic (Allium sativum), dong quai (Angelica sinensis), or danshen (Salvia miltiorrhiza); mild serotonin syndrome in patients who mix St John's wort (Hypericum perforatum) with serotonin-reuptake inhibitors; decreased bioavailability of digoxin, theophylline, cyclosporin, and phenprocoumon when these drugs are combined with St John's wort; induction of mania in depressed patients who mix antidepressants and Panax ginseng; exacerbation of extrapyramidal effects with neuroleptic drugs and betel nut (Areca catechu); increased risk of hypertension when tricyclic antidepressants are combined with yohimbine (Pausinystalia yohimbe); potentiation of oral and topical corticosteroids by liquorice (Glycyrrhiza glabra); decreased blood concentrations of prednisolone when taken with the Chinese herbal product xaio chai hu tang (sho-salko-to); and decreased concentrations of phenytoin when combined with the Ayurvedic syrup shankhapushpi. Anthranoid-containing plants (including senna [Cassia senna] and cascara [Rhamnus purshiana]) and soluble fibres (including guar gum and psyllium) can decrease the absorption of drugs. Many reports of herb-drug interactions are sketchy and lack laboratory analysis of suspect preparations. Health-care practitioners should caution patients against mixing herbs and pharmaceutical drugs.

ORIGINAL ARTICLES Prevalence of drug-drug interactions of ...

African Journals Online (AJOL)

2008-02-02

Feb 2, 2008 ... Table II. Frequency of level 2 interactions between ARVs and the other drugs. Interacting ARVs and other drugs. N. %*. Didanosine + ketoconazole. 1. 0.91. Didanosine + ofloxacin. 1. 0.91. Didanosine + ciprofloxacin. 2. 1.82. Didanosine + iraconazole. 3. 2.73. Didanosine + ketoconazole. 2. 1.82. Efavirenz ...

Botanical-drug interactions: a scientific perspective.

Science.gov (United States)

de Lima Toccafondo Vieira, Manuela; Huang, Shiew-Mei

2012-09-01

There is a continued predisposition of concurrent use of drugs and botanical products. A general lack of knowledge of the interaction potential together with an under-reporting of botanical use poses a challenge for the health care providers and a safety concern for patients. Botanical-drug interactions increase the patient risk, especially with regard to drugs with a narrow therapeutic index (e.g., warfarin, cyclosporine, and digoxin). Examples of case reports and clinical studies evaluating botanical-drug interactions of commonly used botanicals in the US are presented. The potential pharmacokinetic and pharmacodynamic bases of such interactions are discussed, as well as the challenges associated with the interpretation of the available data and prediction of botanical-drug interactions. Recent FDA experiences with botanical products and interactions including labeling implications as a risk management strategy are highlighted. Georg Thieme Verlag KG Stuttgart · New York.

Drug-drug interactions in prescriptions for hospitalized elderly with Acute Coronary Syndrome

Directory of Open Access Journals (Sweden)

Tiago Aparecido Maschio de Lima

2017-11-01

Full Text Available The objective was to determine the rate of potential drug-drug interactions in prescriptions for elderly diagnosed with Acute Coronary Syndrome in a teaching hospital. This is an exploratory, descriptive study that analyzed 607 prescriptions through databases to identify and classify the interactions based on intensity (major, moderate or minor, the mechanism (pharmacokinetic or pharmacodynamics and documentation relevance. We detected 10,162 drug-drug interactions, distributed in 554 types of different combinations within the prescribed drugs, and 99% of prescriptions presented at least one and a maximum of 53 interactions; highlighting the prevalence of major and moderates ones. There was a correlation between the number of drug-drug interactions and the number of prescribed drugs and the hospitalization time. This study contributes for the delimitation of a prevalence pattern in drug-drug interactions in prescriptions for Acute Coronary Syndrome, besides subsidizing the importance of the effective implementation of the Clinical Pharmacy in teaching hospitals.

Considering the context: social factors in responses to drugs in humans.

Science.gov (United States)

de Wit, Harriet; Sayette, Michael

2018-04-01

Drugs are typically used in social settings. Here, we consider two factors that may contribute to this observation: (i) the presence of other people may enhance the positive mood effects of a drug, and conversely, (ii) drugs may enhance the value of social stimuli. We review evidence from controlled laboratory studies with human volunteers, which investigated either of these interactions between social factors and responses to drugs. We examine the bidirectional effects of social stimuli and single doses of alcohol, stimulants, opioids, and cannabis. All four classes of drugs interact with social contexts, but the nature of these interactions varies across drugs, and depends on whether the context is positive or negative. Alcohol and stimulant drugs enhance the attractiveness of social stimuli and the desire to socialize, and social contexts, in turn, enhance these drugs' effects. In contrast, opioids and cannabis have subtler effects on social interactions and their effects are less influenced by the presence of others. Overall, there is stronger evidence that drugs enhance positive social contexts than that they dampen the negativity of unpleasant social settings. Controlled research is needed to understand the interactions between drugs of abuse and social contexts, to model and understand the determinants of drug use outside the laboratory.

Drug-drug interactions among recently hospitalised patients--frequent but mostly clinically insignificant

DEFF Research Database (Denmark)

Glintborg, Bente; Andersen, Stig Ejdrup; Dalhoff, Kim

2005-01-01

OBJECTIVE: Patients use and store considerable amounts of drugs. The aim of the present study was to identify potential drug-drug interactions between drugs used by patients recently discharged from the hospital and, subsequently, to estimate the clinical implications of these interactions. METHODS......: Patients were visited within 1 week following their discharge from hospital and interviewed about their drug use. Stored products were inspected. We used a bibliography (Hansten and Horn; Wolters Kluwer Health, St. Louis, Mo., 2004) to identify and classify potential drug-drug interactions. RESULTS......: eight per patient; range: 1-24). With respect to those drugs used daily or on demand, 476 potential interactions were identified (126 patients); none were class 1 (always avoid drug combination) and 25 were class 2 (usually avoid combination; 24 patients). Eleven of the potential class 2 interactions...

Statin drug-drug interactions in a Romanian community pharmacy.

Science.gov (United States)

Badiu, Raluca; Bucsa, Camelia; Mogosan, Cristina; Dumitrascu, Dan

2016-01-01

Statins are frequently prescribed for patients with dyslipidemia and have a well-established safety profile. However, when associated with interacting dugs, the risk of adverse effects, especially muscular toxicity, is increased. The objective of this study was to identify, characterize and quantify the prevalence of the potential drug-drug interactions (pDDIs) of statins in reimbursed prescriptions from a community pharmacy in Bucharest. We analyzed the reimbursed prescriptions including statins collected during one month in a community pharmacy. The online program Medscape Drug Interaction Checker was used for checking the drug interactions and their classification based on severity: Serious - Use alternative, Significant - Monitor closely and Minor. 132 prescriptions pertaining to 125 patients were included in the analysis. Our study showed that 25% of the patients who were prescribed statins were exposed to pDDIs: 37 Serious and Significant interactions in 31 of the statins prescriptions. The statins involved were atorvastatin, simvastatin and rosuvastatin. Statin pDDIs have a high prevalence and patients should be monitored closely in order to prevent the development of adverse effects that result from statin interactions.

Risk of drug interaction: combination of antidepressants and other drugs

Directory of Open Access Journals (Sweden)

Miyasaka Lincoln Sakiara

2003-01-01

Full Text Available OBJECTIVE: To assess the frequency of combination of antidepressants with other drugs and risk of drug interactions in the setting public hospital units in Brazil. METHODS: Prescriptions of all patients admitted to a public hospital from November 1996 to February 1997 were surveyed from the hospital's data processing center in São Paulo, Brazil. A manual search of case notes of all patients admitted to the psychiatric unit from January 1993 to December 1995 and all patients registered in the affective disorders outpatient clinic in December 1996 was carried out. Patients taking any antidepressant were identified and concomitant use of drugs was checked. By means of a software program (Micromedex® drug interactions were identified. RESULTS: Out of 6,844 patients admitted to the hospital, 63 (0.9% used antidepressants and 16 (25.3% were at risk of drug interaction. Out of 311 patients in the psychiatric unit, 63 (20.2% used antidepressants and 13 of them (20.6% were at risk. Out of 87 patients in the affective disorders outpatient clinic, 43 (49.4% took antidepressants and 7 (16.2% were at risk. In general, the use of antidepressants was recorded in 169 patients and 36 (21.3% were at risk of drug interactions. Twenty different forms of combinations at risk of drug interactions were identified: four were classified as mild, 15 moderate and one severe interaction. CONCLUSION: In the hospital general units the number of drug interactions per patient was higher than in the psychiatric unit; and prescription for depression was lower than expected.

Investigation of the Interaction Between Human Serum Albumin and Two Drugs as Binary and Ternary Systems.

Science.gov (United States)

Abdollahpour, Nooshin; Soheili, Vahid; Saberi, Mohammad Reza; Chamani, Jamshidkhan

2016-12-01

Human serum albumin (HSA) is the most frequent protein in blood plasma. Albumin transports various compounds, preserves osmotic pressure, and buffers pH. A unique feature of albumin is its ability to bind drugs and other bioactive molecules. However, it is important to consider binary and ternary systems of two pharmaceuticals to estimate the effect of the first drug on the second one and physicochemical properties. Different techniques including time-resolved, second-derivative and anisotropy fluorescence spectroscopy, resonance light scattering (RLS), critical induced aggregation concentration (C CIAC ), particle size, zeta potential and stability analysis were employed in this assessment to elucidate the binding behavior of Amlodipine and Aspirin to HSA. Moreover, isothermal titration calorimetric techniques were performed and the QSAR properties were applied to analyze the hydration energy and log P. Multiple sequence alignments were also used to predict the structure and biological characteristics of the HSA binding site. Time-resolved fluorescence spectroscopy showed interaction of both drugs to HSA based on a static quenching mechanism. Subsequently, second-derivative fluorescence spectroscopy presented different values of parameter H in binary and ternary systems, which were suggested that tryptophan was in a more polar environment in the ternary system than in a binary system. Moreover, the polydispersity index and results from mean number measurements revealed that the presence of the second drug caused a decrease in the stability of systems and increased the heterogeneity of complex. It is also, observed that the gradual addition of HSA has led to a marked increase in fluorescence anisotropy (r) of Amlodipine and Aspirin which can be suggested that the drugs were located in a restricted environment of the protein as confirmed by Red Edge Excitation Shift (REES) studies. The isothermal titration calorimetric technique demonstrated that the interaction of

Patient Counseling about Herbal-Drug Interactions | Hussain ...

African Journals Online (AJOL)

The multitude of pharmacologically active compounds obviously increases the likelihood of interactions taking place. Hence, the likelihood of herb-drug interactions is theoretically higher than drug-drug interactions because synthetic drugs usually contain single chemical entity. Case reports and clinical studies have ...

HIV Treatment: What is a Drug Interaction?

Science.gov (United States)

... more) drugs or between a drug and a food or beverage. Taking a drug while having certain medical conditions ... interaction : A reaction between a drug and a food or beverage. Drug-condition interaction : A reaction that occurs when ...

Pharmacodynamics and common drug-drug interactions of the third-generation antiepileptic drugs.

Science.gov (United States)

Stefanović, Srđan; Janković, Slobodan M; Novaković, Milan; Milosavljević, Marko; Folić, Marko

2018-02-01

Anticonvulsants that belong to the third generation are considered as 'newer' antiepileptic drugs, including: eslicarbazepine acetate, lacosamide, perampanel, brivaracetam, rufinamide and stiripentol. Areas covered: This article reviews pharmacodynamics (i.e. mechanisms of action) and clinically relevant drug-drug interactions of the third-generation antiepileptic drugs. Expert opinion: Newer antiepileptic drugs have mechanisms of action which are not shared with the first and the second generation anticonvulsants, like inhibition of neurotransmitters release, blocking receptors for excitatory amino acids and new ways of sodium channel inactivation. New mechanisms of action increase chances of controlling forms of epilepsy resistant to older anticonvulsants. Important advantage of the third-generation anticonvulsants could be their little propensity for interactions with both antiepileptic and other drugs observed until now, making prescribing much easier and safer. However, this may change with new studies specifically designed to discover drug-drug interactions. Although the third-generation antiepileptic drugs enlarged therapeutic palette against epilepsy, 20-30% of patients with epilepsy is still treatment-resistant and need new pharmacological approach. There is great need to explore all molecular targets that may directly or indirectly be involved in generation of seizures, so a number of candidate compounds for even newer anticonvulsants could be generated.

Polypharmacy and the risk of drug-drug interactions among Danish elderly

DEFF Research Database (Denmark)

Rosholm, J U; Bjerrum, L; Hallas, J

1998-01-01

OBJECTIVE: To analyze the use of all subsidized prescription drugs with special attention to the elderly (> or = 70 years of age), including their use of drug combination generally accepted as carrying a risk of severe interactions. DESIGN: Descriptive prevalence study. SETTING: Odense...... accepted as carrying a risk of severe interactions. RESULTS: Among persons less than 70 years, 67.9% used none, 16.5% used one drug and 15.6% used two or more prescription drugs. The corresponding prevalences for the elderly were 35.7%, 15.9% and 48.4%. The 26,337 elderly patients with at least two drugs...... used 21,293 different combinations. Of the elderly patients who had purchased > or = two drugs, 4.4% had combinations of drugs carrying a risk of severe interactions. CONCLUSIONS: Most elderly use drugs and usually several drugs concomitantly. The elderly form a heterogeneous group of drug users. Drug...

Common drug-drug interactions in antifungal treatments for superficial fungal infections.

Science.gov (United States)

Gupta, Aditya K; Versteeg, Sarah G; Shear, Neil H

2018-04-01

Antifungal agents can be co-administered alongside several other medications for a variety of reasons such as the presence of comorbidities. Pharmacodynamic interactions such as synergistic and antagonistic interactions could be the result of co-administered medications. Pharmacokinetic interactions could also transpire through the inhibition of metabolizing enzymes and drug transport systems, altering the absorption, metabolism and excretion of co-administered medications. Both pharmacodynamic and pharmacokinetic interactions can result in hospitalization due to serious adverse effects associated with antifungal agents, lower therapeutic doses required to achieve desired antifungal activity, and prevent antifungal resistance. Areas covered: The objective of this review is to summarize pharmacodynamic and pharmacokinetic interactions associated with common antifungal agents used to treat superficial fungal infections. Pharmacodynamic and pharmacokinetic interactions that impact the therapeutic effects of antifungal agents and drugs that are influenced by the presence of antifungal agents was the context to which these antifungal agents were addressed. Expert opinion: The potential for drug-drug interactions is minimal for topical antifungals as opposed to oral antifungals as they have minimal exposure to other co-administered medications. Developing non-lipophilic antifungals that have unique metabolizing pathways and are topical applied are suggested properties that could help limit drug-drug interactions associated with future treatments.

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.

Anticoagulant Medicine: Potential for Drug-Food Interactions

Science.gov (United States)

... Medications Anticoagulants and Drug-Food Interactions Anticoagulants and Drug-Food Interactions Make an Appointment Ask a Question Refer Patient ... Jewish Health wants you to be aware these drug-food interactions when taking anticoagulant medicine. Ask your health care ...

From Human-Computer Interaction to Human-Robot Social Interaction

OpenAIRE

Toumi, Tarek; Zidani, Abdelmadjid

2014-01-01

Human-Robot Social Interaction became one of active research fields in which researchers from different areas propose solutions and directives leading robots to improve their interactions with humans. In this paper we propose to introduce works in both human robot interaction and human computer interaction and to make a bridge between them, i.e. to integrate emotions and capabilities concepts of the robot in human computer model to become adequate for human robot interaction and discuss chall...

Drug Interactions in Childhood Cancer

Science.gov (United States)

Haidar, Cyrine; Jeha, Sima

2016-01-01

Children with cancer are increasingly benefiting from novel therapeutic strategies and advances in supportive care, as reflected in improvements in both their survival and quality of life. However, the continuous emergence of new oncology drugs and supportive care agents has also increased the possibility of deleterious drug interactions and healthcare providers need to practice extreme caution when combining medications. In this review, we discuss the most common interactions of chemotherapeutic agents with supportive care drugs such as anticonvulsants, antiemetics, uric acid–lowering agents, acid suppressants, antimicrobials, and pain management medications in pediatric oncology patients. As chemotherapy agents interact not only with medications but also with foods and herbal supplements that patients receive during the course of their treatment, we also briefly review such interactions and provide recommendations to avoid unwanted and potentially fatal interactions in children with cancer. PMID:20869315

Identifying Drug–Drug Interactions by Data Mining

DEFF Research Database (Denmark)

Hansen, Peter Wæde; Clemmensen, Line Katrine Harder; Sehested, Thomas S.G.

2016-01-01

Background—Knowledge about drug–drug interactions commonly arises from preclinical trials, from adverse drug reports, or based on knowledge of mechanisms of action. Our aim was to investigate whether drug–drug interactions were discoverable without prior hypotheses using data mining. We focused...... registries. Additionally, we discovered a few potentially novel interactions. This opens up for the use of data mining to discover unknown drug–drug interactions in cardiovascular medicine....... on warfarin–drug interactions as the prototype. Methods and Results—We analyzed altered prothrombin time (measured as international normalized ratio [INR]) after initiation of a novel prescription in previously INR-stable warfarin-treated patients with nonvalvular atrial fibrillation. Data sets were retrieved...

Potential drug-drug interactions on in-patient medication ...

African Journals Online (AJOL)

Potential drug-drug interactions on in-patient medication prescriptions at Mbarara Regional Referral Hospital (MRRH) in western Uganda: prevalence, clinical importance and associated factors. SJ Lubinga, E Uwiduhaye ...

Interaction of cationic drugs with liposomes.

Science.gov (United States)

Howell, Brett A; Chauhan, Anuj

2009-10-20

Interactions between cationic drugs and anionic liposomes were studied by measuring binding of drugs and the effect of binding on liposome permeability. The measurements were analyzed in the context of a continuum model based on electrostatic interactions and a Langmuir isotherm. Experiments and modeling indicate that, although electrostatic interactions are important, the fraction of drug sequestered in the double-layer is negligible. The majority of drug enters the bilayer with the charged regions interacting with the charged lipid head groups and the lipophilic regions associated with the bilayer. The partitioning of the drug can be described by a Langmuir isotherm with the electrostatic interactions increasing the sublayer concentration of the drug. The binding isotherms are similar for all tricyclic antidepressants (TCA). Bupivacaine (BUP) binds significantly less compared to TCA because its structure is such that the charged region has minimal interactions with the lipid heads once the BUP molecule partitions inside the bilayer. Conversely, the TCAs are linear with distinct hydrophilic and lipophilic regions, allowing the lipophilic regions to lie inside the bilayer and the hydrophilic regions to protrude out. This conformation maximizes the permeability of the bilayer, leading to an increased release of a hydrophilic fluorescent dye from liposomes.

DRUG INTERACTIONS WITH DIAZEPAM

Directory of Open Access Journals (Sweden)

Zoran Bojanić

2011-06-01

Full Text Available Diazepam is a benzodiazepine derivative with anxyolitic, anticonvulsant, hypnotic, sedative, skeletal muscle relaxant, antitremor, and amnestic activity. It is metabolized in the liver by the cytochrome P (CYP 450 enzyme system. Diazepam is N-demethylated by CYP3A4 and CYP2C19 to the active metabolite N-desmethyldiazepam, and is hydroxylated by CYP3A4 to the active metabolite temazepam. N-desmethyl-diazepam and temazepam are both further metabolized to oxazepam. Concomitant intake of inhibitors or inducers of the CYP isozymes involved in the biotransformation of diazepam may alter plasma concentrations of this drug, although this effect is unlikely to be associated with clinically relevant interactions.The goal of this article was to review the current literature on clinically relevant pharmacokinetic drug interactions with diazepam.A search of MEDLINE and EMBASE was conducted for original research and review articles published in English between January 1971. and May 2011. Among the search terms were drug interactions, diazepam, pharmacokinetics, drug metabolism, and cytochrome P450. Only articles published in peer-reviewed journals were included, and meeting abstracts were excluded. The reference lists of relevant articles were hand-searched for additional publications.Diazepam is substantially sorbed by the plastics in flexible containers, volume control set chambers, and tubings of intravenous administration sets. Manufacturers recommend not mixing with any other drug or solution in syringe or solution, although diazepam is compatible in syringe with cimetidine and ranitidine, and in Y-site with cisatracurium, dobutamine, fentanyl, hydromorphone, methadone, morphine, nafcillin, quinidine gluconate, remifentanil, and sufentanil. Diazepam is compatible with: dextrose 5% in water, Ringers injection, Ringers injection lactated and sodium chloride 0.9%. Emulsified diazepam is compatible with Intralipid and Nutralipid.Diazepam has low potential

Potential Drug-Drug Interactions among Patients prescriptions collected from Medicine Out-patient Setting.

Science.gov (United States)

Farooqui, Riffat; Hoor, Talea; Karim, Nasim; Muneer, Mehtab

2018-01-01

To identify and evaluate the frequency, severity, mechanism and common pairs of drug-drug interactions (DDIs) in prescriptions by consultants in medicine outpatient department. This cross sectional descriptive study was done by Pharmacology department of Bahria University Medical & Dental College (BUMDC) in medicine outpatient department (OPD) of a private hospital in Karachi from December 2015 to January 2016. A total of 220 prescriptions written by consultants were collected. Medications given with patient's diagnosis were recorded. Drugs were analyzed for interactions by utilizing Medscape drug interaction checker, drugs.com checker and stockley`s drug interactions index. Two hundred eleven prescriptions were selected while remaining were excluded from the study because of unavailability of the prescribed drugs in the drug interaction checkers. In 211 prescriptions, two common diagnoses were diabetes mellitus (28.43%) and hypertension (27.96%). A total of 978 medications were given. Mean number of medications per prescription was 4.6. A total of 369 drug-drug interactions were identified in 211 prescriptions (175%). They were serious 4.33%, significant 66.12% and minor 29.53%. Pharmacokinetic and pharmacodynamic interactions were 37.94% and 51.21% respectively while 10.84% had unknown mechanism. Number wise common pairs of DDIs were Omeprazole-Losartan (S), Gabapentine- Acetaminophen (M), Losartan-Diclofenac (S). The frequency of DDIs is found to be too high in prescriptions of consultants from medicine OPD of a private hospital in Karachi. Significant drug-drug interactions were more and mostly caused by Pharmacodynamic mechanism. Number wise evaluation showed three common pairs of drugs involved in interactions.

6-mercaptopurine and daunorubicin double drug liposomes-preparation, drug-drug interaction and characterization.

Science.gov (United States)

Agrawal, Vineet; Paul, Manash K; Mukhopadhyay, Anup K

2005-01-01

This article addresses and investigates the dual incorporation of daunorubicin (DR) and 6-mercaptopurine (6-MP) in liposomes for better chemotherapy. These drugs are potential candidates for interaction due to the quinone (H acceptor) and hydroxyl (H donor) groups on DR and 6-MP, respectively. Interactions between the two drugs in solution were monitored by UV/Vis and fluorescence spectroscopy. Interaction between the two drugs inside the liposomes was evaluated by HPLC (for 6-MP) and by fluorescence spectroscopy (for daunorubicin) after phospholipase-mediated liposome lysis. Our results provide evidence for the lack of interaction between the two drugs in solution and in liposomes. The entrapment efficiencies of 6-MP in the neutral Phosphatidyl choline (PC):Cholesterol (Chol):: 2:1 and anionic PC:Chol:Cardiolipin (CL) :: 4:5:1 single and double drug liposomes were found to be 0.4% and 1.5% (on average), respectively. The entrapment efficiencies of DR in the neutral and anionic double drug liposomes were found to be 55% and 31%, respectively. The corresponding entrapment of daunorubicin in the single drug liposomes was found to be 62% on average. Our thin layer chromatography (TLC) and transmission electron microscopy (TEM) results suggest stability of lipid and liposomes, thus pointing plausible existence of double drug liposomes. Cytotoxicity experiments were performed by using both single drug and double drug liposomes. By comparing the results of phase contrast and fluorescence microscopy, it was observed that the double drug liposomes were internalized in the jurkat and Hut78 (highly resistant cell line) leukemia cells as viewed by the fluorescence of daunorubicin. The cytotoxicity was dose dependent and had shown a synergistic effect when double drug liposome was used.

Radiopharmaceuticals drug interactions: a critical review

International Nuclear Information System (INIS)

Santos-Oliveira, Ralph; Smith, Sheila W.; Carneiro-Leao, Ana Maria A.

2008-01-01

Radiopharmaceuticals play a critical role in modern medicine primarily for diagnostic purposes, but also for monitoring disease progression and response to treatment. As the use of image has been increased, so has the use of prescription medications. These trends increase the risk of interactions between medications and radiopharmaceuticals. These interactions which have an impact on image by competing with the radiopharmaceutical for binding sites for example can lead to false negative results. Drugs that accelerate the metabolism of the radiopharmaceutical can have a positive impact (i.e. speeding its clearance) or, if repeating image is needed, a negative impact. In some cases, for example in cardiac image among patients taking doxirubacin, these interactions may have a therapeutic benefit. The incidence of drug-radiopharmaceuticals adverse reactions is unknown, since they may not be reported or even recognized. Here, we compiled the medical literature, using the criteria of a systematic review established by the Cochrane Collaboration, on pharmaceutical-drug interactions to provide a summary of documented interactions by organ system and radiopharmaceuticals. The purpose is to provide a reference on drug interactions that could inform the nuclear medicine staff in their daily routine. Efforts to increase adverse event reporting, and ideally consolidate reports worldwide, can provide a critically needed resource for prevention of drug-radiopharmaceuticals interactions. (author)

Drug disposition and drug-drug interaction data in 2013 FDA new drug applications: a systematic review.

Science.gov (United States)

Yu, Jingjing; Ritchie, Tasha K; Mulgaonkar, Aditi; Ragueneau-Majlessi, Isabelle

2014-12-01

The aim of the present work was to perform a systematic review of drug metabolism, transport, pharmacokinetics, and DDI data available in the NDAs approved by the FDA in 2013, using the University of Washington Drug Interaction Database, and to highlight significant findings. Among 27 NMEs approved, 22 (81%) were well characterized with regard to drug metabolism, transport, or organ impairment, in accordance with the FDA drug interaction guidance (2012) and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. However, in vivo, only half (n = 11) showed clinically relevant drug interactions, with most related to the NMEs as victim drugs and CYP3A being the most affected enzyme. As perpetrators, the overall effects for NMEs were much less pronounced, compared with when they served as victims. In addition, the pharmacokinetic evaluation in patients with hepatic or renal impairment provided useful information for further understanding of the drugs' disposition. Copyright © 2014 by The American Society for Pharmacology and Experimental Therapeutics.

[Drug interactions in chronic prescription].

Science.gov (United States)

Comet, D; Casajuana, J; Bordas, J M; Fuentes, M A; Arnáiz, J A; Núñez, B; Pou, R

1997-06-30

Application of computerized program for detection of potential drug interactions (PDI) in chronic prescriptions in four primary care centers. To evaluate the clinical significance of PDI identified according to clinical criterions. An observational crossover study. Clutat Vella health district (City of Barcelona). Using information of Consejo General de Colegios Oficiales de Farmaceuticos databases and the chronic prescriptions database of the primary care centers, computerized drug-interaction system have been developed for detection of PDI in patients. A panel of primary care physicians and clinical pharmacists developed criteria that were used to evaluate the clinical significance of PDI. 9840 Cards of Authorized Prescription (CAP) were analyzed, 36108 medicaments and 42877 drugs. A total of 2140 patients were involved for a total of 3406 PDI, 21.75% of patients with CAP. Clinical signification for the panel was found in 40.07% of these 3406 PIF; 3.78% were suggest to avoid the association drugs. The incidence of PDI with clinical signification are lower than other studies of the literature; it suggest a appropriate knowledge of drug prescription. The application of computerized program make much more easy the detection of adverse drug interactions in chronic prescription.

Potential intravenous drug interactions in intensive care

Directory of Open Access Journals (Sweden)

Maiara Benevides Moreira

Full Text Available Abstract OBJECTIVE To analyze potential intravenous drug interactions, and their level of severity associated with the administration of these drugs based on the prescriptions of an intensive care unit. METHOD Quantitative study, with aretrospective exploratory design, and descriptive statistical analysis of the ICU prescriptions of a teaching hospital from March to June 2014. RESULTS The sample consisted of 319 prescriptions and subsamples of 50 prescriptions. The mean number of drugs per patient was 9.3 records, and a higher probability of drug interaction inherent to polypharmacy was evidenced. The study identified severe drug interactions, such as concomitant administration of Tramadol with selective serotonin reuptake inhibitor drugs (e.g., Metoclopramide and Fluconazole, increasing the risk of seizures due to their epileptogenic actions, as well as the simultaneous use of Ranitidine-Fentanyl®, which can lead to respiratory depression. CONCLUSION A previous mapping of prescriptions enables the characterization of the drug therapy, contributing to prevent potential drug interactions and their clinical consequences.

Drug interactions with oral sulphonylurea hypoglycaemic drugs.

Science.gov (United States)

Hansen, J M; Christensen, L K

1977-01-01

The effect of the oral sulphonylurea hypoglycaemic drugs may be influenced by a large number of other drugs. Some of these combinations (e.g. phenylbutazone, sulphaphenazole) may result in cases of severe hypoglycaemic collapse. Tolbutamide and chlorpropamide should never be given to a patient without a prior careful check of which medicaments are already being given. Similarly, no drug should be given to a diabetic treated with tolbutamide and chlorpropamide without consideration of the possibility of interaction phenomena.

Drug-botanical interactions: a review of the laboratory, animal, and human data for 8 common botanicals.

Science.gov (United States)

Shord, Stacy S; Shah, Kanan; Lukose, Alvina

2009-09-01

Many Americans use complementary and alternative medicine (CAM) to prevent or alleviate common illnesses, and these medicines are commonly used by individuals with cancer.These medicines or botanicals share the same metabolic and transport proteins, including cytochrome P450 enzymes (CYP), glucuronosyltransferases (UGTs), and P-glycoprotein (Pgp), with over-the-counter and prescription medicines increasing the likelihood of drug-botanical interactions.This review provides a brief description of the different proteins, such as CYPs, UGTs, and Pgp.The potential effects of drug-botanical interactions on the pharmacokinetics and pharmacodynamics of the drug or botanical and a summary of the more common models used to study drug metabolism are described.The remaining portion of this review summarizes the data extracted from several laboratory, animal, and clinical studies that describe the metabolism, transport, and potential interactions of 8 selected botanicals. The 8 botanicals include black cohosh, Echinacea, garlic, Gingko biloba, green tea, kava, milk thistle, and St John's wort; these botanicals are among some of the more common botanicals taken by individuals with cancer.These examples are included to demonstrate how to interpret the different studies and how to use these data to predict the likelihood of a clinically significant drug-botanical interaction.

Drug interactions in hospitalized elderly patients

Directory of Open Access Journals (Sweden)

Juliana Locatelli

2007-12-01

Full Text Available Objective: To assess the prevalence of drug interactions in elderlyinpatients and to describe the most prevalent interactions. Methods:A retrospective study was conducted in 155 elderly inpatients enrolledin the Clinical Pharmacy program at the elderly-care unit of theHospital Israelita Albert Einstein from January 2006 to January 2007.Interactions were classified according to severity using Micromedex®.Results: A total of 705 potential drug interactions were found, withapproximately 4 interactions per patient. According to severity, 201(28% were major severities and 504 (72% were of moderate severity.Among these 705 interactions, 444 were selected according to theirresulting effect including 161 (36% had increased risk of bleeding, 78(18% hypoglycemia or hyperglycemia, 50 (11% cardiotoxicity, 46(10% digitalis toxicity, 40 (9% phenytoin toxicity, 31 (7% additiverespiratory depression, 20 (5% hyperkalemia, 18 (4% decreasedlevothyroxine absorption. Conclusion: The high drug interactionrate found in this study shows the relevance of this issue amongelderly inpatients and the need to assess and monitor drug therapyin the elderly to prevent and reduce consequences of potential druginteraction effects.

Drug-drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems.

Science.gov (United States)

Kumar, Santosh; Rao, P S S; Earla, Ravindra; Kumar, Anil

2015-03-01

Substance abuse is a common problem among HIV-infected individuals. Importantly, addictions as well as moderate use of alcohol, smoking, or other illicit drugs have been identified as major reasons for non-adherence to antiretroviral therapy (ART) among HIV patients. The literature also suggests a decrease in the response to ART among HIV patients who use these substances, leading to failure to achieve optimal virological response and increased disease progression. This review discusses the challenges with adherence to ART as well as observed drug interactions and known toxicities with major drugs of abuse, such as alcohol, smoking, methamphetamine, cocaine, marijuana, and opioids. The lack of adherence and drug interactions potentially lead to decreased efficacy of ART drugs and increased ART, and drugs of abuse-mediated toxicity. As CYP is the common pathway in metabolizing both ART and drugs of abuse, we discuss the possible involvement of CYP pathways in such drug interactions. We acknowledge that further studies focusing on common metabolic pathways involving CYP and advance research in this area would help to potentially develop novel/alternate interventions and drug dose/regimen adjustments to improve medication outcomes in HIV patients who consume drugs of abuse.

Drug-domain interaction networks in myocardial infarction.

Science.gov (United States)

Wang, Haiying; Zheng, Huiru; Azuaje, Francisco; Zhao, Xing-Ming

2013-09-01

It has been well recognized that the pace of the development of new drugs and therapeutic interventions lags far behind biological knowledge discovery. Network-based approaches have emerged as a promising alternative to accelerate the discovery of new safe and effective drugs. Based on the integration of several biological resources including two recently published datasets i.e., Drug-target interactions in myocardial infarction (My-DTome) and drug-domain interaction network, this paper reports the association between drugs and protein domains in the context of myocardial infarction (MI). A MI drug-domain interaction network, My-DDome, was firstly constructed, followed by topological analysis and functional characterization of the network. The results show that My-DDome has a very clear modular structure, where drugs interacting with the same domain(s) within each module tend to have similar therapeutic effects. Moreover it has been found that drugs acting on blood and blood forming organs (ATC code B) and sensory organs (ATC code S) are significantly enriched in My-DDome (p drugs, their known targets, and seemingly unrelated proteins can be revealed.

Computational prediction of drug-drug interactions based on drugs functional similarities.

Science.gov (United States)

Ferdousi, Reza; Safdari, Reza; Omidi, Yadollah

2017-06-01

Therapeutic activities of drugs are often influenced by co-administration of drugs that may cause inevitable drug-drug interactions (DDIs) and inadvertent side effects. Prediction and identification of DDIs are extremely vital for the patient safety and success of treatment modalities. A number of computational methods have been employed for the prediction of DDIs based on drugs structures and/or functions. Here, we report on a computational method for DDIs prediction based on functional similarity of drugs. The model was set based on key biological elements including carriers, transporters, enzymes and targets (CTET). The model was applied for 2189 approved drugs. For each drug, all the associated CTETs were collected, and the corresponding binary vectors were constructed to determine the DDIs. Various similarity measures were conducted to detect DDIs. Of the examined similarity methods, the inner product-based similarity measures (IPSMs) were found to provide improved prediction values. Altogether, 2,394,766 potential drug pairs interactions were studied. The model was able to predict over 250,000 unknown potential DDIs. Upon our findings, we propose the current method as a robust, yet simple and fast, universal in silico approach for identification of DDIs. We envision that this proposed method can be used as a practical technique for the detection of possible DDIs based on the functional similarities of drugs. Copyright © 2017. Published by Elsevier Inc.

Drug interaction databases in medical literature

DEFF Research Database (Denmark)

Kongsholm, Gertrud Gansmo; Nielsen, Anna Katrine Toft; Damkier, Per

2015-01-01

PURPOSE: It is well documented that drug-drug interaction databases (DIDs) differ substantially with respect to classification of drug-drug interactions (DDIs). The aim of this study was to study online available transparency of ownership, funding, information, classifications, staff training...... available transparency of ownership, funding, information, classifications, staff training, and underlying documentation varies substantially among various DIDs. Open access DIDs had a statistically lower score on parameters assessed....... and the three most commonly used subscription DIDs in the medical literature. The following parameters were assessed for each of the databases: Ownership, classification of interactions, primary information sources, and staff qualification. We compared the overall proportion of yes/no answers from open access...

Antifungal therapy: drug-drug interactions at your fingertips

NARCIS (Netherlands)

Lempers, V.J.; Bruggemann, R.J.

2016-01-01

The Information Age has revolutionized the ability of healthcare professionals (HCPs) to oversee a substantial body of clinically relevant information literally at one's fingertips. In the field of clinical pharmacology, this may be particularly useful for managing drug-drug interactions (DDIs). A

Role of cytochrome P450 in drug interactions

Directory of Open Access Journals (Sweden)

Bibi Zakia

2008-10-01

Full Text Available Abstract Drug-drug interactions have become an important issue in health care. It is now realized that many drug-drug interactions can be explained by alterations in the metabolic enzymes that are present in the liver and other extra-hepatic tissues. Many of the major pharmacokinetic interactions between drugs are due to hepatic cytochrome P450 (P450 or CYP enzymes being affected by previous administration of other drugs. After coadministration, some drugs act as potent enzyme inducers, whereas others are inhibitors. However, reports of enzyme inhibition are very much more common. Understanding these mechanisms of enzyme inhibition or induction is extremely important in order to give appropriate multiple-drug therapies. In future, it may help to identify individuals at greatest risk of drug interactions and adverse events.

A review of drug-drug interactions in older HIV-infected patients.

Science.gov (United States)

Chary, Aarthi; Nguyen, Nancy N; Maiton, Kimberly; Holodniy, Mark

2017-12-01

The number of older HIV-infected people is growing due to increasing life expectancies resulting from the use of antiretroviral therapy (ART). Both HIV and aging increase the risk of other comorbidities, such as cardiovascular disease, osteoporosis, and some malignancies, leading to greater challenges in managing HIV with other conditions. This results in complex medication regimens with the potential for significant drug-drug interactions and increased morbidity and mortality. Area covered: We review the metabolic pathways of ART and other medications used to treat medical co-morbidities, highlight potential areas of concern for drug-drug interactions, and where feasible, suggest alternative approaches for treating these conditions as suggested from national guidelines or articles published in the English language. Expert commentary: There is limited evidence-based data on ART drug interactions, pharmacokinetics and pharmacodynamics in the older HIV-infected population. Choosing and maintaining effective ART regimens for older adults requires consideration of side effect profile, individual comorbidities, interactions with concurrent prescriptions and non-prescription medications and supplements, dietary patterns with respect to dosing, pill burden and ease of dosing, cost and affordability, patient preferences, social situation, and ART resistance history. Practitioners must remain vigilant for potential drug interactions and intervene when there is a potential for harm.

Clinical relevance of cimetidine drug interactions.

Science.gov (United States)

Shinn, A F

1992-01-01

The excellent efficacy and tolerability profiles of H2-antagonists have established these agents as the leading class of antiulcer drugs. Attention has been focused on drug interactions with H2-antagonists as a means of product differentiation and because many patients are receiving multiple drug therapy. The main mechanism of most drug interactions involving cimetidine appears to be inhibition of the hepatic microsomal enzyme cytochrome P450, an effect which may be related to the different structures of H2-antagonists. Ranitidine appears to have less affinity than cimetidine for this system. There have been many published case reports and studies of drug interactions with cimetidine, but many of these have provided pharmacokinetic data only, with little information concerning the clinical significance of these findings. Nevertheless, the coadministration of cimetidine with drugs that have a narrow therapeutic margin (such as theophylline) may potentially result in clinically significant adverse effects. The monitoring of serum concentrations of drugs coadministered with cimetidine may reduce the risk of adverse events but does not abolish the problem. However, for most patients, concomitant administration of cimetidine with drugs possessing a wide therapeutic margin is unlikely to pose a significant problem.

[Interactions of cytostatic agents with other drugs].

Science.gov (United States)

Sauter, C

1991-08-31

With the degree of polypharmacy currently practiced in the field of oncology, there are undoubtedly many drug interactions. In the present study the influence of "non-cytotoxic" drugs on anticancer drugs is discussed, but not the reverse. Not only is the augmentation (reversal of multidrug resistance) or the reduction of antitumor properties of cytotoxic drugs observed, but also cytostatic activities of "non-cytotoxic" drugs themselves. Examples are calmodulin inhibitors such as phenothiazines and tricyclic antidepressants. Interactions may also increase side effects of cytostatic drugs or even neutralize the antitumoral activity. To ensure that interactions are not overlooked, all medicaments being administered should be listed. It is, however, not feasible yet to determine serum concentrations of all the drugs given to the patient. The antitumor activity of supportive care could be evaluated in randomized studies (e.g. cytostatic drugs +/- antidepressants).

Evaluation of drug-drug interactions among patients with chronic ...

African Journals Online (AJOL)

Introduction: The risk of drug-drug interactions (DDIs) is high in patients with chronic kidney disease (CKD) necessitating dose adjustments or the avoidance of drug combinations. This study aimed to evaluate DDIs among patients with CKD in the University of Nigeria Teaching Hospital (UNTH), Enugu, South-East Nigeria.

A regulatory science viewpoint on botanical–drug interactions

Directory of Open Access Journals (Sweden)

Manuela Grimstein

2018-04-01

Full Text Available There is a continued predisposition of concurrent use of drugs and botanical products. Consumers often self-administer botanical products without informing their health care providers. The perceived safety of botanical products with lack of knowledge of the interaction potential poses a challenge for providers and both efficacy and safety concerns for patients. Botanical–drug combinations can produce untoward effects when botanical constituents modulate drug metabolizing enzymes and/or transporters impacting the systemic or tissue exposure of concomitant drugs. Examples of pertinent scientific literature evaluating the interaction potential of commonly used botanicals in the US are discussed. Current methodologies that can be applied to advance our efforts in predicting drug interaction liability is presented. This review also highlights the regulatory science viewpoint on botanical–drug interactions and labeling implications. Keywords: Drug interaction, Botanical product, St. John's wort, Fruit juices, Regulatory science

Human Drug Discrimination: Elucidating the Neuropharmacology of Commonly Abused Illicit Drugs.

Science.gov (United States)

Bolin, B Levi; Alcorn, Joseph L; Reynolds, Anna R; Lile, Joshua A; Stoops, William W; Rush, Craig R

2016-06-07

Drug-discrimination procedures empirically evaluate the control that internal drug states have over behavior. They provide a highly selective method to investigate the neuropharmacological underpinnings of the interoceptive effects of drugs in vivo. As a result, drug discrimination has been one of the most widely used assays in the field of behavioral pharmacology. Drug-discrimination procedures have been adapted for use with humans and are conceptually similar to preclinical drug-discrimination techniques in that a behavior is differentially reinforced contingent on the presence or absence of a specific interoceptive drug stimulus. This chapter provides a basic overview of human drug-discrimination procedures and reviews the extant literature concerning the use of these procedures to elucidate the underlying neuropharmacological mechanisms of commonly abused illicit drugs (i.e., stimulants, opioids, and cannabis) in humans. This chapter is not intended to review every available study that used drug-discrimination procedures in humans. Instead, when possible, exemplary studies that used a stimulant, opioid, or Δ 9 -tetrahydrocannabinol (the primary psychoactive constituent of cannabis) to assess the discriminative-stimulus effects of drugs in humans are reviewed for illustrative purposes. We conclude by commenting on the current state and future of human drug-discrimination research.

Interaction of an antiepileptic drug, lamotrigine with human serum albumin (HSA): Application of spectroscopic techniques and molecular modeling methods.

Science.gov (United States)

Poureshghi, Fatemeh; Ghandforoushan, Parisa; Safarnejad, Azam; Soltani, Somaieh

2017-01-01

Lamotrigine (an epileptic drug) interaction with human serum albumin (HSA) was investigated by fluorescence, UV-Vis, FTIR, CD spectroscopic techniques, and molecular modeling methods. Binding constant (K b ) of 5.74×10 3 and number of binding site of 0.97 showed that there is a slight interaction between lamotrigine and HSA. Thermodynamic studies was constructed using the flourimetric titrations in three different temperatures and the resulted data used to calculate the parameters using Vant Hoff equation. Decreased Stern Volmer quenching constant by enhanced temperature revealed the static quenching mechanism. Negative standard enthalpy (ΔH) and standard entropy (ΔS) changes indicated that van der Waals interactions and hydrogen bonds were dominant forces which facilitate the binding of Lamotrigine to HSA, the results were confirmed by molecular docking studies which showed no hydrogen binding. The FRET studies showed that there is a possibility of energy transfer between Trp214 and lamotrigine. Also the binding of lamotrigine to HSA in the studied concentrations was not as much as many other drugs, but the secondary structure of the HSA was significantly changed following the interaction in a way that α-helix percentage was reduced from 67% to 57% after the addition of lamotrigine in the molar ratio of 4:1 to HSA. According to the docking studies, lamotrigine binds to IB site preferably. Copyright © 2016. Published by Elsevier B.V.

Identification of clinically significant drug-drug interactions in cardiac ...

African Journals Online (AJOL)

Purpose: To identify clinically significant potential drug-drug interactions in cardiac intensive care units of two tertiary care ... hypertension, hyperlipidemia, diabetes or other diseases .... May result in digoxin toxicity (nausea, vomiting, cardiac.

Interaction of Citrinin with Human Serum Albumin

Directory of Open Access Journals (Sweden)

Miklós Poór

2015-12-01

Full Text Available Citrinin (CIT is a mycotoxin produced by several Aspergillus, Penicillium, and Monascus species. CIT occurs worldwide in different foods and drinks and causes health problems for humans and animals. Human serum albumin (HSA is the most abundant plasma protein in human circulation. Albumin forms stable complexes with many drugs and xenobiotics; therefore, HSA commonly plays important role in the pharmacokinetics or toxicokinetics of numerous compounds. However, the interaction of CIT with HSA is poorly characterized yet. In this study, the complex formation of CIT with HSA was investigated using fluorescence spectroscopy and ultrafiltration techniques. For the deeper understanding of the interaction, thermodynamic, and molecular modeling studies were performed as well. Our results suggest that CIT forms stable complex with HSA (logK ~ 5.3 and its primary binding site is located in subdomain IIA (Sudlow’s Site I. In vitro cell experiments also recommend that CIT-HSA interaction may have biological relevance. Finally, the complex formations of CIT with bovine, porcine, and rat serum albumin were investigated, in order to test the potential species differences of CIT-albumin interactions.

[Pharmacokinetic interactions of telaprevir with other drugs].

Science.gov (United States)

Berenguer Berenguer, Juan; González-García, Juan

2013-07-01

Telaprevir is a new direct-acting antiviral drug for the treatment of hepatitis C virus (HCV) infection and is both a substrate and an inhibitor of cytochrome P450 (CYP450) isoenzymes. With the introduction of this new drug, assessment of drug-drug interactions has become a key factor in the evaluation of patients under treatment for HCV infection. During the treatment of this infection, many patients require other drugs to mitigate the adverse effects of anti-HCV drugs and to control other comorbidities. Moreover, most patients coinfected with HIV and HCV require antiretroviral therapy during treatment for HCV. Physicians should therefore be familiar with the pharmacokinetic properties of direct-acting antivirals for HCV treatment and their potential drug-drug interactions. The present article reviews the available information to date on the interactions of telaprevir with other drugs and provides recommendations for daily clinical practice. Copyright © 2013 Elsevier España, S.L. All rights reserved.

Drug Interactions in Clinical Practice | Ohaju-Obodo | Nigerian ...

African Journals Online (AJOL)

The existence of numerous drugs available today for clinical management of patients require consideration of their potential interactions - alteration of the effects of one drug by the concurrent or prior administration of one or more drugs (drug-drug interactions). There could also be alteration of the effects of a drug by food ...

Pharmacogenomic study using bio- and nanobioelectrochemistry: Drug-DNA interaction.

Science.gov (United States)

Hasanzadeh, Mohammad; Shadjou, Nasrin

2016-04-01

Small molecules that bind genomic DNA have proven that they can be effective anticancer, antibiotic and antiviral therapeutic agents that affect the well-being of millions of people worldwide. Drug-DNA interaction affects DNA replication and division; causes strand breaks, and mutations. Therefore, the investigation of drug-DNA interaction is needed to understand the mechanism of drug action as well as in designing DNA-targeted drugs. On the other hand, the interaction between DNA and drugs can cause chemical and conformational modifications and, thus, variation of the electrochemical properties of nucleobases. For this purpose, electrochemical methods/biosensors can be used toward detection of drug-DNA interactions. The present paper reviews the drug-DNA interactions, their types and applications of electrochemical techniques used to study interactions between DNA and drugs or small ligand molecules that are potentially of pharmaceutical interest. The results are used to determine drug binding sites and sequence preference, as well as conformational changes due to drug-DNA interactions. Also, the intention of this review is to give an overview of the present state of the drug-DNA interaction cognition. The applications of electrochemical techniques for investigation of drug-DNA interaction were reviewed and we have discussed the type of qualitative or quantitative information that can be obtained from the use of each technique. Copyright © 2015 Elsevier B.V. All rights reserved.

A Novel Design for Drug-Drug Interaction Alerts Improves Prescribing Efficiency.

Science.gov (United States)

Russ, Alissa L; Chen, Siying; Melton, Brittany L; Johnson, Elizabette G; Spina, Jeffrey R; Weiner, Michael; Zillich, Alan J

2015-09-01

Drug-drug interactions (DDIs) are common in clinical care and pose serious risks for patients. Electronic health records display DDI alerts that can influence prescribers, but the interface design of DDI alerts has largely been unstudied. In this study, the objective was to apply human factors engineering principles to alert design. It was hypothesized that redesigned DDI alerts would significantly improve prescribers' efficiency and reduce prescribing errors. In a counterbalanced, crossover study with prescribers, two DDI alert designs were evaluated. Department of Veterans Affairs (VA) prescribers were video recorded as they completed fictitious patient scenarios, which included DDI alerts of varying severity. Efficiency was measured from time-stamped recordings. Prescribing errors were evaluated against predefined criteria. Efficiency and prescribing errors were analyzed with the Wilcoxon signed-rank test. Other usability data were collected on the adequacy of alert content, prescribers' use of the DDI monograph, and alert navigation. Twenty prescribers completed patient scenarios for both designs. Prescribers resolved redesigned alerts in about half the time (redesign: 52 seconds versus original design: 97 seconds; p<.001). Prescribing errors were not significantly different between the two designs. Usability results indicate that DDI alerts might be enhanced by facilitating easier access to laboratory data and dosing information and by allowing prescribers to cancel either interacting medication directly from the alert. Results also suggest that neither design provided adequate information for decision making via the primary interface. Applying human factors principles to DDI alerts improved overall efficiency. Aspects of DDI alert design that could be further enhanced prior to implementation were also identified.

Interaction Effects of Students, Drugs and Alienation

Science.gov (United States)

Jones, Woodrow, Jr.

1977-01-01

This study examined the interaction effect of students, drugs, and alienation in a large university, i.e., the linkages of both social and political alienation with drug behavior. The interaction terms which composed these forms of alienation were evaluated as to their comparative ability to produce drug behavior. (Author)

QSAR Modeling and Prediction of Drug-Drug Interactions.

Science.gov (United States)

Zakharov, Alexey V; Varlamova, Ekaterina V; Lagunin, Alexey A; Dmitriev, Alexander V; Muratov, Eugene N; Fourches, Denis; Kuz'min, Victor E; Poroikov, Vladimir V; Tropsha, Alexander; Nicklaus, Marc C

2016-02-01

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100,000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug-drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27,966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72-79% for the external test sets with a coverage of 81.36-100% when a conservative threshold for the model's applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.

Identifying Drug-Target Interactions with Decision Templates.

Science.gov (United States)

Yan, Xiao-Ying; Zhang, Shao-Wu

2018-01-01

During the development process of new drugs, identification of the drug-target interactions wins primary concerns. However, the chemical or biological experiments bear the limitation in coverage as well as the huge cost of both time and money. Based on drug similarity and target similarity, chemogenomic methods can be able to predict potential drug-target interactions (DTIs) on a large scale and have no luxurious need about target structures or ligand entries. In order to reflect the cases that the drugs having variant structures interact with common targets and the targets having dissimilar sequences interact with same drugs. In addition, though several other similarity metrics have been developed to predict DTIs, the combination of multiple similarity metrics (especially heterogeneous similarities) is too naïve to sufficiently explore the multiple similarities. In this paper, based on Gene Ontology and pathway annotation, we introduce two novel target similarity metrics to address above issues. More importantly, we propose a more effective strategy via decision template to integrate multiple classifiers designed with multiple similarity metrics. In the scenarios that predict existing targets for new drugs and predict approved drugs for new protein targets, the results on the DTI benchmark datasets show that our target similarity metrics are able to enhance the predictive accuracies in two scenarios. And the elaborate fusion strategy of multiple classifiers has better predictive power than the naïve combination of multiple similarity metrics. Compared with other two state-of-the-art approaches on the four popular benchmark datasets of binary drug-target interactions, our method achieves the best results in terms of AUC and AUPR for predicting available targets for new drugs (S2), and predicting approved drugs for new protein targets (S3).These results demonstrate that our method can effectively predict the drug-target interactions. The software package can

Clinical risk management in Dutch community pharmacies: the case of drug-drug interactions.

NARCIS (Netherlands)

Buurma, H.; Smet, P.A.G.M. de; Egberts, A.C.G.

2006-01-01

BACKGROUND: The prevention of drug-drug interactions requires a systematic approach for which the concept of clinical risk management can be used. The objective of our study was to measure the frequency, nature and management of drug-drug interaction alerts as these occur in daily practice of Dutch

Macrolides versus azalides: a drug interaction update.

Science.gov (United States)

Amsden, G W

1995-09-01

To describe the current drug interaction profiles for all approved and investigational macrolide and azalide antimicrobials, and to comment on the clinical impact of these interactions when appropriate. MEDLINE was searched to identify all pertinent studies, review articles, and case reports from 1975 to 1995. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to give an unbiased account of possible drug interactions. Data for some of the interactions were not available from the literature, but were available from abstracts or from company-supplied materials. Although the data were not always entirely explicative, the best attempt was made to deliver the pertinent information that clinical practitioners would need to formulate practice opinions. When more in-depth information was supplied in the form of a review or study report, a thorough explanation of pertinent methodology was supplied. Since the introduction of erythromycin into clinical practice, there have been several clinically significant drug interactions identified throughout the literature associated with this drug. These interactions have been caused mostly by inhibition of the CYP3A subclass of hepatic enzymes, thereby decreasing the metabolism of any other agent given concurrently that is also cleared through this mechanism. With the development and marketing of several new macrolides, it was hoped that the drug interaction profile associated with this class would improve. This has been met with variable success. Although some of the extensions of the 14-membered ring macrolides have shown an incidence of interactions equal to that of erythromycin, others have shown improved profiles. In contrast, the 16-membered ring macrolides have demonstrated a much improved, though not absent, interaction profile. The most success in avoiding drug interactions through structure modification has been accomplished

High-Throughput Cytochrome P450 Cocktail Inhibition Assay for Assessing Drug-Drug and Drug-Botanical Interactions.

Science.gov (United States)

Li, Guannan; Huang, Ke; Nikolic, Dejan; van Breemen, Richard B

2015-11-01

Detection of drug-drug interactions is essential during the early stages of drug discovery and development, and the understanding of drug-botanical interactions is important for the safe use of botanical dietary supplements. Among the different forms of drug interactions that are known, inhibition of cytochrome P450 (P450) enzymes is the most common cause of drug-drug or drug-botanical interactions. Therefore, a rapid and comprehensive mass spectrometry-based in vitro high-throughput P450 cocktail inhibition assay was developed that uses 10 substrates simultaneously against nine CYP isoforms. Including probe substrates for CYP1A2, CYP2A6, CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP2E1, and two probes targeting different binding sites of CYP3A4/5, this cocktail simultaneously assesses at least as many P450 enzymes as previous assays while remaining among the fastest due to short incubation times and rapid analysis using ultrahigh pressure liquid chromatography-tandem mass spectrometry. The method was validated using known inhibitors of each P450 enzyme and then shown to be useful not only for single-compound testing but also for the evaluation of potential drug-botanical interactions using the botanical dietary supplement licorice (Glycyrrhiza glabra) as an example. Copyright © 2015 by The American Society for Pharmacology and Experimental Therapeutics.

Hazards and Benefits of Drug Interaction

Science.gov (United States)

Labianca, Dominick A.

1978-01-01

Most cases of drug toxicity are direct consequences of drug misuse--either intentional or inadvertent. Discusses two types of drug interaction--synergistic and antagonistic. The former produces a combined effect greater than the sum of the effects of the individual drugs concerned; the latter is produced when the desired action of one drug is…

P-glycoprotein interaction with risperidone and 9-OH-risperidone studied in vitro, in knock-out mice and in drug-drug interaction experiments

DEFF Research Database (Denmark)

Ejsing, Thomas B.; Pedersen, Anne D.; Linnet, Kristian

2005-01-01

P-glycoprotein, risperidone, nortriptyline, cyclosporine A, drug-drug interaction, blood-brain barrier, knock-out mice......P-glycoprotein, risperidone, nortriptyline, cyclosporine A, drug-drug interaction, blood-brain barrier, knock-out mice...

Detecting drug-drug interactions using a database for spontaneous adverse drug reactions : an example with diuretics and non-steroidal anti-inflammatory drugs

NARCIS (Netherlands)

van Puijenbroek, E P; Egberts, A C; Heerdink, E R; Leufkens, H G

2000-01-01

OBJECTIVE: Drug-drug interactions are relatively rarely reported to spontaneous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the detection of drug-drug interactions. We developed a method that may enable

Initial Drug Dissolution from Amorphous Solid Dispersions Controlled by Polymer Dissolution and Drug-Polymer Interaction.

Science.gov (United States)

Chen, Yuejie; Wang, Shujing; Wang, Shan; Liu, Chengyu; Su, Ching; Hageman, Michael; Hussain, Munir; Haskell, Roy; Stefanski, Kevin; Qian, Feng

2016-10-01

To identify the key formulation factors controlling the initial drug and polymer dissolution rates from an amorphous solid dispersion (ASD). Ketoconazole (KTZ) ASDs using PVP, PVP-VA, HMPC, or HPMC-AS as polymeric matrix were prepared. For each drug-polymer system, two types of formulations with the same composition were prepared: 1. Spray dried dispersion (SDD) that is homogenous at molecular level, 2. Physical blend of SDD (80% drug loading) and pure polymer (SDD-PB) that is homogenous only at powder level. Flory-Huggins interaction parameters (χ) between KTZ and the four polymers were obtained by Flory-Huggins model fitting. Solution (13)C NMR and FT-IR were conducted to investigate the specific drug-polymer interaction in the solution and solid state, respectively. Intrinsic dissolution of both the drug and the polymer from ASDs were studied using a Higuchi style intrinsic dissolution apparatus. PXRD and confocal Raman microscopy were used to confirm the absence of drug crystallinity on the tablet surface before and after dissolution study. In solid state, KTZ is completely miscible with PVP, PVP-VA, or HPMC-AS, demonstrated by the negative χ values of -0.36, -0.46, -1.68, respectively; while is poorly miscible with HPMC shown by a positive χ value of 0.23. According to solution (13)C NMR and FT-IR studies, KTZ interacts with HPMC-AS strongly through H-bonding and dipole induced interaction; with PVPs and PVP-VA moderately through dipole-induced interactions; and with HPMC weakly without detectable attractive interaction. Furthermore, the "apparent" strength of drug-polymer interaction, measured by the extent of peak shift on NMR or FT-IR spectra, increases with the increasing number of interacting drug-polymer pairs. For ASDs with the presence of considerable drug-polymer interactions, such as KTZ/PVPs, KTZ/PVP-VA, or KTZ /HPMC-AS systems, drug released at the same rate as the polymer when intimate drug-polymer mixing was ensured (i.e., the SDD systems

Detecting drug-drug interactions using a database for spontaneous adverse drug reactions: an example with diuretics and non-steroidal anti-inflammatory drugs.

Science.gov (United States)

van Puijenbroek, E P; Egberts, A C; Heerdink, E R; Leufkens, H G

2000-12-01

Drug-drug interactions are relatively rarely reported to spontaneous reporting systems (SRSs) for adverse drug reactions. For this reason, the traditional approach for analysing SRS has major limitations for the detection of drug-drug interactions. We developed a method that may enable signalling of these possible interactions, which are often not explicitly reported, utilising reports of adverse drug reactions in data sets of SRS. As an example, the influence of concomitant use of diuretics and non-steroidal anti-inflammatory drugs (NSAIDs) on symptoms indicating a decreased efficacy of diuretics was examined using reports received by the Netherlands Pharmacovigilance Foundation Lareb. Reports received between 1 January 1990 and 1 January 1999 of patients older than 50 years were included in the study. Cases were defined as reports with symptoms indicating a decreased efficacy of diuretics, non-cases as all other reports. Exposure categories were the use of NSAIDs or diuretics versus the use of neither of these drugs. The influence of the combined use of both drugs was examined using logistic regression analysis. The odds ratio of the statistical interaction term of the combined use of both drugs was increased [adjusted odds ratio 2.0, 95% confidence interval (CI) 1.1-3.7], which may indicate an enhanced effect of concomitant drug use. The findings illustrate that spontaneous reporting systems have a potential for signal detection and the analysis of possible drug-drug interactions. The method described may enable a more active approach in the detection of drug-drug interactions after marketing.

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

Science.gov (United States)

Hobbs, Michael J; Bloomer, Jackie; Dear, Gordon

2017-08-01

1. In a clinical trial, a strong drug-drug interaction (DDI) was observed between dextromethorphan (DM, the object or victim drug) and GSK1034702 (the precipitant or perpetrator drug), following single and repeat doses. This study determined the inhibition parameters of GSK1034702 in vitro and applied PBPK modelling approaches to simulate the clinical observations and provide mechanistic hypotheses to understand the DDI. 2. In vitro assays were conducted to determine the inhibition parameters of human CYP2D6 by GSK1034702. PBPK models were populated with the in vitro parameters and DDI simulations conducted and compared to the observed data from a clinical study with DM and GSK1034702. 3. GSK1034702 was a potent direct and metabolism-dependent inhibitor of human CYP2D6, with inhibition parameters of: IC 50  =   1.6 μM, K inact  = 3.7 h -1 and K I  = 0.8 μM. Incorporating these data into PBPK models predicted a DDI after repeat, but not single, 5 mg doses of GSK1034702. 4. The DDI observed with repeat administration of GSK1034702 (5 mg) can be attributed to metabolism-dependent inhibition of CYP2D6. Further, in vitro data were generated and several potential mechanisms proposed to explain the interaction observed following a single dose of GSK1034702.

Indolealkylamines: biotransformations and potential drug-drug interactions.

Science.gov (United States)

Yu, Ai-Ming

2008-06-01

Indolealkylamine (IAA) drugs are 5-hydroxytryptamine (5-HT or serotonin) analogs that mainly act on the serotonin system. Some IAAs are clinically utilized for antimigraine therapy, whereas other substances are notable as drugs of abuse. In the clinical evaluation of antimigraine triptan drugs, studies on their biotransformations and pharmacokinetics would facilitate the understanding and prevention of unwanted drug-drug interactions (DDIs). A stable, principal metabolite of an IAA drug of abuse could serve as a useful biomarker in assessing intoxication of the IAA substance. Studies on the metabolism of IAA drugs of abuse including lysergic acid amides, tryptamine derivatives and beta-carbolines are therefore emerging. An important role for polymorphic cytochrome P450 2D6 (CYP2D6) in the metabolism of IAA drugs of abuse has been revealed by recent studies, suggesting that variations in IAA metabolism, pharmaco- or toxicokinetics and dynamics can arise from distinct CYP2D6 status, and CYP2D6 polymorphism may represent an additional risk factor in the use of these IAA drugs. Furthermore, DDIs with IAA agents could occur additively at the pharmaco/toxicokinetic and dynamic levels, leading to severe or even fatal serotonin toxicity. In this review, the metabolism and potential DDIs of these therapeutic and abused IAA drugs are described.

DRUG-INTERACTIONS WITH QUINOLONE ANTIBACTERIALS

NARCIS (Netherlands)

BROUWERS, JRBJ

1992-01-01

The quinolone antibacterials are prone to many interactions with other drugs. Quinolone absorption is markedly reduced with antacids containing aluminium, magnesium and/or calcium and therapeutic failure may result. Other metallic ion-containing drugs, such as sucralfate, iron salts, and zinc salts,

Drug interactions evaluation: An integrated part of risk assessment of therapeutics

International Nuclear Information System (INIS)

Zhang, Lei; Reynolds, Kellie S.; Zhao, Ping; Huang, Shiew-Mei

2010-01-01

Pharmacokinetic drug interactions can lead to serious adverse events or decreased drug efficacy. The evaluation of a new molecular entity's (NME's) drug-drug interaction potential is an integral part of risk assessment during drug development and regulatory review. Alteration of activities of enzymes or transporters involved in the absorption, distribution, metabolism, or excretion of a new molecular entity by concomitant drugs may alter drug exposure, which can impact response (safety or efficacy). The recent Food and Drug Administration (FDA) draft drug interaction guidance ( (http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm072101.pdf)) highlights the methodologies and criteria that may be used to guide drug interaction evaluation by industry and regulatory agencies and to construct informative labeling for health practitioner and patients. In addition, the Food and Drug Administration established a 'Drug Development and Drug Interactions' website to provide up-to-date information regarding evaluation of drug interactions ( (http://www.fda.gov/Drugs/DevelopmentApprovalProcess/DevelopmentResources/DrugInteractionsLabeling/ucm080499.htm)). This review summarizes key elements in the FDA drug interaction guidance and new scientific developments that can guide the evaluation of drug-drug interactions during the drug development process.

A regulatory science viewpoint on botanical-drug interactions.

Science.gov (United States)

Grimstein, Manuela; Huang, Shiew-Mei

2018-04-01

There is a continued predisposition of concurrent use of drugs and botanical products. Consumers often self-administer botanical products without informing their health care providers. The perceived safety of botanical products with lack of knowledge of the interaction potential poses a challenge for providers and both efficacy and safety concerns for patients. Botanical-drug combinations can produce untoward effects when botanical constituents modulate drug metabolizing enzymes and/or transporters impacting the systemic or tissue exposure of concomitant drugs. Examples of pertinent scientific literature evaluating the interaction potential of commonly used botanicals in the US are discussed. Current methodologies that can be applied to advance our efforts in predicting drug interaction liability is presented. This review also highlights the regulatory science viewpoint on botanical-drug interactions and labeling implications. Copyright © 2018. Published by Elsevier B.V.

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

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com.

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

Science.gov (United States)

Yao, Zhi-Jiang; Dong, Jie; Che, Yu-Jing; Zhu, Min-Feng; Wen, Ming; Wang, Ning-Ning; Wang, Shan; Lu, Ai-Ping; Cao, Dong-Sheng

2016-05-01

Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .

Drug membrane interaction and the importance for drug transport, distribution, accumulation, efficacy and resistance.

Science.gov (United States)

Seydel, J K; Coats, E A; Cordes, H P; Wiese, M

1994-10-01

Some aspects of drug membrane interaction and its influence on drug transport, accumulation, efficacy and resistance have been discussed. The interactions manifest themselves macroscopically in changes in the physical and thermodynamic properties of "pure membranes" or bilayers. As various amounts of foreign molecules enter the membrane, in particular the main gel to liquid crystalline phase transition can be dramatically changed. This may change permeability, cell-fusion, cell resistance and may also lead to changes in conformation of the embedded receptor proteins. Furthermore, specific interactions with lipids may lead to drug accumulation in membranes and thus to much larger concentrations at the active site than present in the surrounding water phase. The lipid environment may also lead to changes in the preferred conformation of drug molecules. These events are directly related to drug efficacy. The determination of essential molecular criteria for the interaction could be used to design new and more selective therapeutics. This excursion in some aspects of drug membrane interaction underlines the importance of lipids and their interaction with drug molecules for our understanding of drug action, but this is not really a new thought but has been formulated in 1884 by THUDICUM: "Phospholipids are the centre, life and chemical soul of all bioplasm whatsoever, that of plants as well as of animals".

Cellular mechanisms in drug - radiation interaction

International Nuclear Information System (INIS)

Trott, K.R.

1979-01-01

Some cytotoxic drugs, especially those belonging to the group of antibiotics and antimetabolites, sensitize the cells having survived drug treatment to the subsequent irradiation by either increasing the slope of the radiation dose response curves or by decreasing extrapolation number. Bleomycin was found to interact with radiation in L-cells and FM3A cells, but not in HeLa-cells. The data with EMT-6 cells suggest that the interaction depends on drug dose: no interaction occurred after the exposure to bleomycin which killed only 20 - 40% of the cells; yet the exposure to bleomycin which killed 90% of the cells in addition sensitized the surviving cells by the DMF of 1.3. The sensitization found 24 hr after the exposure of HeLa cells to methotrexate was due to cell synchronization. Other cytostatic drugs were found to synchronize proliferating cells even better. Therefore, the fluctuation of radiosensitivity has been commonly observed after the termination of exposure to these drugs. Preirradiation may lead to the change in drug dose response curves. The recruitment of resting cells into cycle occurs hours or days later, in some irradiated normal and malignant tissues. Since many cytostatic drugs are far more active in proliferating cells than in resting cells, the recruitment after irradiation may lead to the sudden increase in drug sensitivity, days after the irradiation. No single, simple theory seems to exist to classify and predict the cellular response to combined modality treatment. (Yamashita, S.)

Compliance with national guidelines for the management of drug-drug interactions in Dutch community pharmacies.

NARCIS (Netherlands)

Buurma, H.; Schalekamp, T.; Egberts, A.C.G.; Smet, P.A.G.M. de

2007-01-01

BACKGROUND: Pharmacists contribute to the detection and prevention of drug therapy-related problems, including drug-drug interactions. Little is known about compliance with pharmacy practice guidelines for the management of drug-drug interaction alerts. OBJECTIVE: To measure the compliance of

Position-aware deep multi-task learning for drug-drug interaction extraction.

Science.gov (United States)

Zhou, Deyu; Miao, Lei; He, Yulan

2018-05-01

A drug-drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed. In this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework. The proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Lower alert rates by clustering of related drug interaction alerts

NARCIS (Netherlands)

Heringa, M.; Siderius, Hidde; Schreudering, A.; De Smet, Peter Agm; Bouvy, M.L.

OBJECTIVE: We aimed to investigate to what extent clustering of related drug interaction alerts (drug-drug and drug-disease interaction alerts) would decrease the alert rate in clinical decision support systems (CDSSs). METHODS: We conducted a retrospective analysis of drug interaction alerts

Predicting drug-target interactions using restricted Boltzmann machines.

Science.gov (United States)

Wang, Yuhao; Zeng, Jianyang

2013-07-01

In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Software and datasets are available on request. Supplementary data are

Risk factors for potential drug interactions in general practice

DEFF Research Database (Denmark)

Bjerrum, Lars; Gonzalez Lopez-Valcarcel, Beatriz; Petersen, Gert

2008-01-01

interactions during 1 year. Patient factors associated with increased risk of potential drug interactions were high age, a high number of concurrently used drugs, and a high number of prescribers. Practice factors associated with potential drug interactions were a high percentage of elderly patients and a low......Objective: To identify patient- and practice-related factors associated with potential drug interactions. Methods: A register analysis study in general practices in the county of Funen, Denmark. Prescription data were retrieved from a population-based prescription database (Odense University......, depending on the severity of outcome and the quality of documentation. A two-level random coefficient logistic regression model was used to investigate factors related to potential drug interactions. Results: One-third of the population was exposed to polypharmacy, and 6% were exposed to potential drug...

Characterization of the interactions of human serum albumin (HSA), gatifloxacin, and metronidazole using spectroscopic and electrochemical methods

International Nuclear Information System (INIS)

Fu, Li; Liu, Xiu-fen; Zhou, Qiu-xiang; Zhang, Ji-xiang; Dong, Jing-ya; Wang, Jian-fang

2014-01-01

Human serum albumin (HSA), the most abundant protein in blood plasma, is an important carrier for many drugs. Understanding HSA-drug interactions is critical in being able to interpret the distribution and acting mechanisms of these drugs, which is particularly important in the case of multi-drug therapy. In this study, we investigated the interactions between HSA and two commonly used antibiotics, gatifloxacin (GFLX) and metronidazole (MET), in Tris–HCl buffer solution (pH=7.4). The efficacy of the individual drugs (GFLX or MET) and the efficacy of a combination of GFLX and MET were measured using fluorescence spectroscopy, UV absorption spectroscopy, and electrochemical methods. Our results demonstrated that GFLX and MET have a synergistic effect. Briefly, one drug decreased the binding stability with HSA of the other drug, thus increasing the concentration of free drug at the action sites. The interaction of drugs with HSA is a process of complex-formation static quenching. There is approximately one binding site between HSA and the drug (GFLX or MET). The binding distance, r, between the drug and HSA was determined on the basis of the theory of Forster-type non-radiative energy transfer. It was shown that the interaction between the two drugs increased the r-value. Using thermodynamic parameters, we found that the binding of drug-HSA interactions is mainly controlled by electrostatic force. Analysis of the synchronous fluorescence spectrum suggested that the interactions between the drugs have important effects on protein conformation. In conclusion, combining GFLX and MET enhances treatment efficacy. Our study provides a basis to understand the mechanism of the interaction of MET, GFLX and HSA in the human body. - Highlights: • The synergistic effects between MET and GFLX were founed. • The type of interaction between the drugs and HSA was identified

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

Science.gov (United States)

Shi, Jian-Yu; Yiu, Siu-Ming; Li, Yiming; Leung, Henry C M; Chin, Francis Y L

2015-07-15

Predicting drug-target interaction using computational approaches is an important step in drug discovery and repositioning. To predict whether there will be an interaction between a drug and a target, most existing methods identify similar drugs and targets in the database. The prediction is then made based on the known interactions of these drugs and targets. This idea is promising. However, there are two shortcomings that have not yet been addressed appropriately. Firstly, most of the methods only use 2D chemical structures and protein sequences to measure the similarity of drugs and targets respectively. However, this information may not fully capture the characteristics determining whether a drug will interact with a target. Secondly, there are very few known interactions, i.e. many interactions are "missing" in the database. Existing approaches are biased towards known interactions and have no good solutions to handle possibly missing interactions which affect the accuracy of the prediction. In this paper, we enhance the similarity measures to include non-structural (and non-sequence-based) information and introduce the concept of a "super-target" to handle the problem of possibly missing interactions. Based on evaluations on real data, we show that our similarity measure is better than the existing measures and our approach is able to achieve higher accuracy than the two best existing algorithms, WNN-GIP and KBMF2K. Our approach is available at http://web.hku.hk/∼liym1018/projects/drug/drug.html or http://www.bmlnwpu.org/us/tools/PredictingDTI_S2/METHODS.html. Copyright © 2015 Elsevier Inc. All rights reserved.

The role of drug profiles as similarity metrics: applications to repurposing, adverse effects detection and drug-drug interactions.

Science.gov (United States)

Vilar, Santiago; Hripcsak, George

2017-07-01

Explosion of the availability of big data sources along with the development in computational methods provides a useful framework to study drugs' actions, such as interactions with pharmacological targets and off-targets. Databases related to protein interactions, adverse effects and genomic profiles are available to be used for the construction of computational models. In this article, we focus on the description of biological profiles for drugs that can be used as a system to compare similarity and create methods to predict and analyze drugs' actions. We highlight profiles constructed with different biological data, such as target-protein interactions, gene expression measurements, adverse effects and disease profiles. We focus on the discovery of new targets or pathways for drugs already in the pharmaceutical market, also called drug repurposing, in the interaction with off-targets responsible for adverse reactions and in drug-drug interaction analysis. The current and future applications, strengths and challenges facing all these methods are also discussed. Biological profiles or signatures are an important source of data generation to deeply analyze biological actions with important implications in drug-related studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces.

Science.gov (United States)

Xia, Zheng; Wu, Ling-Yun; Zhou, Xiaobo; Wong, Stephen T C

2010-09-13

Predicting drug-protein interactions from heterogeneous biological data sources is a key step for in silico drug discovery. The difficulty of this prediction task lies in the rarity of known drug-protein interactions and myriad unknown interactions to be predicted. To meet this challenge, a manifold regularization semi-supervised learning method is presented to tackle this issue by using labeled and unlabeled information which often generates better results than using the labeled data alone. Furthermore, our semi-supervised learning method integrates known drug-protein interaction network information as well as chemical structure and genomic sequence data. Using the proposed method, we predicted certain drug-protein interactions on the enzyme, ion channel, GPCRs, and nuclear receptor data sets. Some of them are confirmed by the latest publicly available drug targets databases such as KEGG. We report encouraging results of using our method for drug-protein interaction network reconstruction which may shed light on the molecular interaction inference and new uses of marketed drugs.

Molecular imaging of drug-modulated protein-protein interactions in living subjects.

Science.gov (United States)

Paulmurugan, Ramasamy; Massoud, Tarik F; Huang, Jing; Gambhir, Sanjiv S

2004-03-15

Networks of protein interactions mediate cellular responses to environmental stimuli and direct the execution of many different cellular functional pathways. Small molecules synthesized within cells or recruited from the external environment mediate many protein interactions. The study of small molecule-mediated interactions of proteins is important to understand abnormal signal transduction pathways in cancer and in drug development and validation. In this study, we used split synthetic renilla luciferase (hRLUC) protein fragment-assisted complementation to evaluate heterodimerization of the human proteins FRB and FKBP12 mediated by the small molecule rapamycin. The concentration of rapamycin required for efficient dimerization and that of its competitive binder ascomycin required for dimerization inhibition were studied in cell lines. The system was dually modulated in cell culture at the transcription level, by controlling nuclear factor kappaB promoter/enhancer elements using tumor necrosis factor alpha, and at the interaction level, by controlling the concentration of the dimerizer rapamycin. The rapamycin-mediated dimerization of FRB and FKBP12 also was studied in living mice by locating, quantifying, and timing the hRLUC complementation-based bioluminescence imaging signal using a cooled charged coupled device camera. This split reporter system can be used to efficiently screen small molecule drugs that modulate protein-protein interactions and also to assess drugs in living animals. Both are essential steps in the preclinical evaluation of candidate pharmaceutical agents targeting protein-protein interactions, including signaling pathways in cancer cells.

Drug-Target Interaction Prediction through Label Propagation with Linear Neighborhood Information.

Science.gov (United States)

Zhang, Wen; Chen, Yanlin; Li, Dingfang

2017-11-25

Interactions between drugs and target proteins provide important information for the drug discovery. Currently, experiments identified only a small number of drug-target interactions. Therefore, the development of computational methods for drug-target interaction prediction is an urgent task of theoretical interest and practical significance. In this paper, we propose a label propagation method with linear neighborhood information (LPLNI) for predicting unobserved drug-target interactions. Firstly, we calculate drug-drug linear neighborhood similarity in the feature spaces, by considering how to reconstruct data points from neighbors. Then, we take similarities as the manifold of drugs, and assume the manifold unchanged in the interaction space. At last, we predict unobserved interactions between known drugs and targets by using drug-drug linear neighborhood similarity and known drug-target interactions. The experiments show that LPLNI can utilize only known drug-target interactions to make high-accuracy predictions on four benchmark datasets. Furthermore, we consider incorporating chemical structures into LPLNI models. Experimental results demonstrate that the model with integrated information (LPLNI-II) can produce improved performances, better than other state-of-the-art methods. The known drug-target interactions are an important information source for computational predictions. The usefulness of the proposed method is demonstrated by cross validation and the case study.

Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction.

Science.gov (United States)

Liu, Yong; Wu, Min; Miao, Chunyan; Zhao, Peilin; Li, Xiao-Li

2016-02-01

In pharmaceutical sciences, a crucial step of the drug discovery process is the identification of drug-target interactions. However, only a small portion of the drug-target interactions have been experimentally validated, as the experimental validation is laborious and costly. To improve the drug discovery efficiency, there is a great need for the development of accurate computational approaches that can predict potential drug-target interactions to direct the experimental verification. In this paper, we propose a novel drug-target interaction prediction algorithm, namely neighborhood regularized logistic matrix factorization (NRLMF). Specifically, the proposed NRLMF method focuses on modeling the probability that a drug would interact with a target by logistic matrix factorization, where the properties of drugs and targets are represented by drug-specific and target-specific latent vectors, respectively. Moreover, NRLMF assigns higher importance levels to positive observations (i.e., the observed interacting drug-target pairs) than negative observations (i.e., the unknown pairs). Because the positive observations are already experimentally verified, they are usually more trustworthy. Furthermore, the local structure of the drug-target interaction data has also been exploited via neighborhood regularization to achieve better prediction accuracy. We conducted extensive experiments over four benchmark datasets, and NRLMF demonstrated its effectiveness compared with five state-of-the-art approaches.

Oral chemotherapy: food-drug interactions

Directory of Open Access Journals (Sweden)

Sara Santana Martínez

2015-07-01

Full Text Available Introduction: oral chemotherapy is increasingly used in Oncology. It has important advantages. such as patient comfort. but it also brings new challenges which did not exist with the intravenous therapy. Some of these drugs have interactions with food. leading to changes in their bioavailability. As they are drugs of narrow therapeutic margin. this can lead to alterations in their efficacy and/or toxicity. Objectives: A. Assessing the level of knowledge on the administration of oral cytostatics that present restrictions with meals (drugs that have to be taken with/without food among the outpatients. B. Minimizing the incorrect administration and the risk of food-drug interactions. providing patients with information as to how and when drugs have to be administrated. Methods: once the oral cytostatics with food restrictions were identified. we asked the patients in treatment about the information they had received from the doctor and the way they were taking the medication. We provided those who were taking the drug incorrectly with the right information. In the following visit. it was confirmed if the patients that had been previously taking the cytostatic incorrectly. were taking them in a correct way (intervention accepted/not accepted. Results and conclusions: 40% of the patients interviewed used to take the drug incorrectly. We detected a great diversity depending on the dispensed drug. 95% of the 39 interventions made were accepted. The data obtained suggest the need to reinforce the information that the patient receives. It is important to make sure that the patient understands how and when the oral cytostatic should be administered

Managing Drug-Drug Interaction Between Ombitasvir, Paritaprevir/Ritonavir, Dasabuvir, and Mycophenolate Mofetil.

Science.gov (United States)

Lemaitre, Florian; Ben Ali, Zeineb; Tron, Camille; Jezequel, Caroline; Boglione-Kerrien, Christelle; Verdier, Marie-Clémence; Guyader, Dominique; Bellissant, Eric

2017-08-01

No drug-drug interaction study has been conducted to date for the combination of ombitasvir, paritaprevir/ritonavir, dasabuvir (3D), and mycophenolic acid (MPA). We here report the case of a hepatitis C virus-infected patient treated with 3D and MPA for vasculitis. In light of the threat of drug-drug interaction, the concentration of MPA was measured before, during, and 15 days after the end of the 3D treatment. Similar values were found at all 3 time points, thus indicating that there is probably no need to adapt MPA dosage to 3D.

Modeling Drug-Carrier Interaction in the Drug Release from Nanocarriers

Directory of Open Access Journals (Sweden)

Like Zeng

2011-01-01

Full Text Available Numerous nanocarriers of various compositions and geometries have been developed for the delivery and release of therapeutic and imaging agents. Due to the high specific surface areas of nanocarriers, different mechanisms such as ion pairing and hydrophobic interaction need to be explored for achieving sustained release. Recently, we developed a three-parameter model that considers reversible drug-carrier interaction and first-order drug release from liposomes. A closed-form analytical solution was obtained. Here, we further explore the ability of the model to capture the release of bioactive molecules such as drugs and growth factors from various nanocarriers. A parameter study demonstrates that the model is capable of resembling major categories of drug release kinetics. We further fit the model to 60 sets of experimental data from various drug release systems, including nanoparticles, hollow particles, fibers, and hollow fibers. Additionally, bootstrapping is used to evaluate the accuracy of parameter determination and validate the model in selected cases. The simplicity and universality of the model and the clear physical meanings of each model parameter render the model useful for the design and development of new drug delivery systems.

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

Directory of Open Access Journals (Sweden)

Lun Yang

Full Text Available Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

Drug-Target Interaction Prediction with Graph Regularized Matrix Factorization.

Science.gov (United States)

Ezzat, Ali; Zhao, Peilin; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2017-01-01

Experimental determination of drug-target interactions is expensive and time-consuming. Therefore, there is a continuous demand for more accurate predictions of interactions using computational techniques. Algorithms have been devised to infer novel interactions on a global scale where the input to these algorithms is a drug-target network (i.e., a bipartite graph where edges connect pairs of drugs and targets that are known to interact). However, these algorithms had difficulty predicting interactions involving new drugs or targets for which there are no known interactions (i.e., "orphan" nodes in the network). Since data usually lie on or near to low-dimensional non-linear manifolds, we propose two matrix factorization methods that use graph regularization in order to learn such manifolds. In addition, considering that many of the non-occurring edges in the network are actually unknown or missing cases, we developed a preprocessing step to enhance predictions in the "new drug" and "new target" cases by adding edges with intermediate interaction likelihood scores. In our cross validation experiments, our methods achieved better results than three other state-of-the-art methods in most cases. Finally, we simulated some "new drug" and "new target" cases and found that GRMF predicted the left-out interactions reasonably well.

Herb-drug interactions. Interactions between saw palmetto and prescription medications.

Science.gov (United States)

Bressler, Rubin

2005-11-01

Patients over age 50 typically present with one chronic disease per decade. Each chronic disease typically requires long-term drug therapy, meaning most older patients require several drugs to maintain health. Simultaneously, use of complementary and alternative medicine (CAM) has increased in the United States in the last 20 years, reaching 36% in 2002; herbal medicine use accounts for approximately 22% of all CAM use. Older adults often add herbal medicines to prescription medications, yet do not always inform their physicians. The drug metabolizing enzyme systems process all compounds foreign to the body, including prescription and herbal medications. Therefore use of both medicinals simultaneously has a potential for adverse interactions. This review, which discusses saw palmetto, is the last in a series covering the documented interactions among the top 5 efficacious herbal medicines and prescription drugs.

Herb-drug interactions: challenges and opportunities for improved predictions.

Science.gov (United States)

Brantley, Scott J; Argikar, Aneesh A; Lin, Yvonne S; Nagar, Swati; Paine, Mary F

2014-03-01

Supported by a usage history that predates written records and the perception that "natural" ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb-drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb-drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb-drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb-drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens.

Statin-associated rhabdomyolysis triggered by drug-drug interaction with itraconazole

DEFF Research Database (Denmark)

Dybro, Anne Mette; Damkier, Per; Rasmussen, Torsten Bloch

2016-01-01

-associated rhabdomyolysis, probably caused by a drug-drug interaction between simvastatin and itraconazole. The patient made full recovery. Three commonly used statins-simvastatin, atorvastatin and lovastatin-are metabolised by the liver enzyme CYP3A4. Several potent inhibitors of this enzyme are known, for example, azole...

21 CFR 25.31 - Human drugs and biologics.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Human drugs and biologics. 25.31 Section 25.31 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF HEALTH AND HUMAN SERVICES GENERAL ENVIRONMENTAL IMPACT CONSIDERATIONS Categorical Exclusions § 25.31 Human drugs and biologics. The classes of...

Free software to analyse the clinical relevance of drug interactions with antiretroviral agents (SIMARV®) in patients with HIV/AIDS.

Science.gov (United States)

Giraldo, N A; Amariles, P; Monsalve, M; Faus, M J

Highly active antiretroviral therapy has extended the expected lifespan of patients with HIV/AIDS. However, the therapeutic benefits of some drugs used simultaneously with highly active antiretroviral therapy may be adversely affected by drug interactions. The goal was to design and develop a free software to facilitate analysis, assessment, and clinical decision making according to the clinical relevance of drug interactions in patients with HIV/AIDS. A comprehensive Medline/PubMed database search of drug interactions was performed. Articles that recognized any drug interactions in HIV disease were selected. The publications accessed were limited to human studies in English or Spanish, with full texts retrieved. Drug interactions were analyzed, assessed, and grouped into four levels of clinical relevance according to gravity and probability. Software to systematize the information regarding drug interactions and their clinical relevance was designed and developed. Overall, 952 different references were retrieved and 446 selected; in addition, 67 articles were selected from the citation lists of identified articles. A total of 2119 pairs of drug interactions were identified; of this group, 2006 (94.7%) were drug-drug interactions, 1982 (93.5%) had an identified pharmacokinetic mechanism, and 1409 (66.5%) were mediated by enzyme inhibition. In terms of clinical relevance, 1285 (60.6%) drug interactions were clinically significant in patients with HIV (levels 1 and 2). With this information, a software program that facilitates identification and assessment of the clinical relevance of antiretroviral drug interactions (SIMARV ® ) was developed. A free software package with information on 2119 pairs of antiretroviral drug interactions was designed and developed that could facilitate analysis, assessment, and clinical decision making according to the clinical relevance of drug interactions in patients with HIV/AIDS. Copyright © 2016 Elsevier Inc. All rights reserved.

Drug-target interaction prediction via class imbalance-aware ensemble learning.

Science.gov (United States)

Ezzat, Ali; Wu, Min; Li, Xiao-Li; Kwoh, Chee-Keong

2016-12-22

Multiple computational methods for predicting drug-target interactions have been developed to facilitate the drug discovery process. These methods use available data on known drug-target interactions to train classifiers with the purpose of predicting new undiscovered interactions. However, a key challenge regarding this data that has not yet been addressed by these methods, namely class imbalance, is potentially degrading the prediction performance. Class imbalance can be divided into two sub-problems. Firstly, the number of known interacting drug-target pairs is much smaller than that of non-interacting drug-target pairs. This imbalance ratio between interacting and non-interacting drug-target pairs is referred to as the between-class imbalance. Between-class imbalance degrades prediction performance due to the bias in prediction results towards the majority class (i.e. the non-interacting pairs), leading to more prediction errors in the minority class (i.e. the interacting pairs). Secondly, there are multiple types of drug-target interactions in the data with some types having relatively fewer members (or are less represented) than others. This variation in representation of the different interaction types leads to another kind of imbalance referred to as the within-class imbalance. In within-class imbalance, prediction results are biased towards the better represented interaction types, leading to more prediction errors in the less represented interaction types. We propose an ensemble learning method that incorporates techniques to address the issues of between-class imbalance and within-class imbalance. Experiments show that the proposed method improves results over 4 state-of-the-art methods. In addition, we simulated cases for new drugs and targets to see how our method would perform in predicting their interactions. New drugs and targets are those for which no prior interactions are known. Our method displayed satisfactory prediction performance and was

Expression and Regulation of Drug Transporters and Metabolizing Enzymes in the Human Gastrointestinal Tract.

Science.gov (United States)

Drozdzik, M; Oswald, S

2016-01-01

Orally administered drugs must pass through the intestinal wall and then through the liver before reaching systemic circulation. During this process drugs are subjected to different processes that may determine the therapeutic value. The intestinal barrier with active drug metabolizing enzymes and drug transporters in enterocytes plays an important role in the determination of drug bioavailability. Accumulating information demonstrates variable distribution of drug metabolizing enzymes and transporters along the human gastrointestinal tract (GI), that creates specific barrier characteristics in different segments of the GI. In this review, expression of drug metabolizing enzymes and transporters in the healthy and diseased human GI as well as their regulatory aspects: genetic, miRNA, DNA methylation are outlined. The knowledge of unique interplay between drug metabolizing enzymes and transporters in specific segments of the GI tract allows more precise definition of drug release sites within the GI in order to assure more complete bioavailability and prediction of drug interactions.

Consistency of psychotropic drug-drug interactions listed in drug monographs.

Science.gov (United States)

Liu, Xinyue; Hatton, Randy C; Zhu, Yanmin; Hincapie-Castillo, Juan M; Bussing, Regina; Barnicoat, Marie; Winterstein, Almut G

With an increasing prevalence of psychotropic polypharmacy, clinicians depend on drug-drug interaction (DDI) references to ensure safe regimens, but the consistency of such information is frequently questioned. To evaluate the consistency of psychotropic DDIs documented in Clinical Pharmacology (CP), Micromedex (MM), and Lexicomp (LC) and summarize consistent psychotropic DDIs. In May 2016, we extracted severe or major psychotropic DDIs for 102 psychotropic drugs, including central nervous system (CNS) stimulants, antidepressants, an antimanic agent (lithium), antipsychotics, anticonvulsants, and anxiolytics-sedatives-hypnotics from CP, MM, and LC. We then summarized the psychotropic DDIs that were included in all 3 references and with evidence quality of "excellent" or "good" based on MM. We identified 1496, 938, and 1006 unique severe or major psychotropic DDIs from CP, MM, and LC, respectively. Common adverse effects related to psychotropic DDIs include increased or decreased effectiveness, CNS depression, neurotoxicity, QT prolongation, serotonin syndrome, and multiple adverse effects. Among these interactions, only 371 psychotropic DDIs were documented in all 3 references, 59 of which had "excellent" or "good" quality of evidence based on MM. The consistency of psychotropic DDI documentation across CP, MM, and LC is poor. DDI documentations need standards that would encourage consistency among drug information references. The list of the 59 DDIs may be useful in the assessment of psychotropic polypharmacy and highlighting DDI alerts in clinical practice. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Human-machine interactions

Science.gov (United States)

Forsythe, J Chris [Sandia Park, NM; Xavier, Patrick G [Albuquerque, NM; Abbott, Robert G [Albuquerque, NM; Brannon, Nathan G [Albuquerque, NM; Bernard, Michael L [Tijeras, NM; Speed, Ann E [Albuquerque, NM

2009-04-28

Digital technology utilizing a cognitive model based on human naturalistic decision-making processes, including pattern recognition and episodic memory, can reduce the dependency of human-machine interactions on the abilities of a human user and can enable a machine to more closely emulate human-like responses. Such a cognitive model can enable digital technology to use cognitive capacities fundamental to human-like communication and cooperation to interact with humans.

Solubilization and Interaction Studies of Bile Salts with Surfactants and Drugs: a Review.

Science.gov (United States)

Malik, Nisar Ahmad

2016-05-01

In this review, bile salt, bile salt-surfactant, and bile salt-drug interactions and their solubilization studies are mainly focused. Usefulness of bile salts in digestion, absorption, and excretion of various compounds and their rare properties in ordering the shape and size of the micelles owing to the presence of hydrophobic and hydrophilic faces are taken into consideration while compiling this review. Bile salts as potential bio-surfactants to solubilize drugs of interest are also highlighted. This review will give an insight into the selection of drugs in different applications as their properties get modified by interaction with bile salts, thus influencing their solution behavior which, in turn, modifies the phase-forming behavior, microemulsion, and clouding phenomenon, besides solubilization. Finally, their future perspectives are taken into consideration to assess their possible uses as bio-surfactants without side effects to human beings.

Interaction of cephalosporin drugs with dodecyltrimethylammonium Bromide

International Nuclear Information System (INIS)

Hoque, Md. Anamul; Hossain, Mohammed Delwar; Khan, Mohammed Abdullah

2013-01-01

Highlights: • We carry out the interaction of cephalosporin drugs with DTAB conductometrically. • We examine the effect of drugs on the critical micelle concentration of DTAB. • Three critical micelle concentrations are obtained for drug- DTAB system. • Electrostatic and hydrophobic interactions between drugs and DTAB are proposed. • Drug supported micelle formation of DTAB is much favoured in aq. solution of K 2 SO 4 . -- Abstract: The interaction of three cephalosporin drugs namely cefadroxyl monohydrate (CFM), cephalexin monohydrate (CLM) and cephradine monohydrate (CDM) with dodecyltrimethylammonium Bromide (DTAB) has been carried out by conductance measurements in aqueous medium and in aqueous solution of K 2 SO 4 salt over temperature range of (303.15 to 318.15) K. For pure DTAB and drug-DTAB systems, three critical micelle concentrations were obtained. The third critical micelle concentration (c ∗ 3 ) indicates that the spherical micelle turns into rod shape that is sphere to rod transition. The c ∗ values of DTAB are changed due to the addition of cephalosporin drugs. In addition, the change of the values of c ∗ 1 , c ∗ 2 and c ∗ 3 with increase of the concentration of drugs indicate the presence of interaction between drug and DTAB. The c ∗ values indicate that micellization for the cephalosporins-surfactant systems in water follow the order: CFM-surfactant ∗ values for the cephalosporins - DTAB systems in aqueous K 2 SO 4 are lower in magnitude than those in pure water and the values decrease with increase of the concentrations of K 2 SO 4 at a particular temperature. A significant decrease of c ∗ values in the presence of K 2 SO 4 for cephalosporins-DTAB systems indicates that drug supported ionic micelle formation is much favoured in aqueous K 2 SO 4 solution compared to that in pure water. For cephalosporin-DTAB systems, ΔG 0 m values are negative which indicate that the drugs mediated ionic micelle formation processes are

Prevalence of potential drug-drug interactions in cancer patients treated with oral anticancer drugs

NARCIS (Netherlands)

van Leeuwen, R. W. F.; Brundel, D. H. S.; Neef, C.; van Gelder, T.; Mathijssen, R. H. J.; Burger, D. M.; Jansman, F. G. A.

2013-01-01

Background: Potential drug-drug interactions (PDDIs) in patients with cancer are common, but have not previously been quantified for oral anticancer treatment. We assessed the prevalence and seriousness of potential PDDIs among ambulatory cancer patients on oral anticancer treatment. Methods: A

Prevalence of potential drug-drug interactions in cancer patients treated with oral anticancer drugs

NARCIS (Netherlands)

R.W.F. van Leeuwen (Roelof); D.H.S. Brundel (D. H S); C. Neef (Cees); T. van Gelder (Teun); A.H.J. Mathijssen (Ron); D.M. Burger (David); F.G.A. Jansman (Frank)

2013-01-01

textabstractBackground: Potential drug-drug interactions (PDDIs) in patients with cancer are common, but have not previously been quantified for oral anticancer treatment. We assessed the prevalence and seriousness of potential PDDIs among ambulatory cancer patients on oral anticancer treatment.

Pharmacokinetic interactions between contraceptives and antiepileptic drugs

DEFF Research Database (Denmark)

Sabers, A.

2008-01-01

The occurrence of bi-directional drug interactions between antiepileptic drugs (AEDs) and combined oral contraceptives (M) pose potential risks of unintended pregnancy and as well as seizure deterioration. It is well established that several of the older AEDs (carbamazepine, phenytoin...... AEDs, which undergoes glucuronidation processes, such as valproate and oxcarbazepine, may be affected by OCs. The magnitude of the drug-drug interactions show in general wide inter-individual variability and the change in the elimination rate is often unpredictable and can be influenced by a number...... of co-variants such as co-medication of other drugs, as well as genetic and environmental factors. It is therefore recommended that change in OC use is assisted by AED monitoring whenever possible. (C) 2007 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved Udgivelsesdato: 2008/3...

Herb–Drug Interactions: Challenges and Opportunities for Improved Predictions

Science.gov (United States)

Brantley, Scott J.; Argikar, Aneesh A.; Lin, Yvonne S.; Nagar, Swati

2014-01-01

Supported by a usage history that predates written records and the perception that “natural” ensures safety, herbal products have increasingly been incorporated into Western health care. Consumers often self-administer these products concomitantly with conventional medications without informing their health care provider(s). Such herb–drug combinations can produce untoward effects when the herbal product perturbs the activity of drug metabolizing enzymes and/or transporters. Despite increasing recognition of these types of herb–drug interactions, a standard system for interaction prediction and evaluation is nonexistent. Consequently, the mechanisms underlying herb–drug interactions remain an understudied area of pharmacotherapy. Evaluation of herbal product interaction liability is challenging due to variability in herbal product composition, uncertainty of the causative constituents, and often scant knowledge of causative constituent pharmacokinetics. These limitations are confounded further by the varying perspectives concerning herbal product regulation. Systematic evaluation of herbal product drug interaction liability, as is routine for new drugs under development, necessitates identifying individual constituents from herbal products and characterizing the interaction potential of such constituents. Integration of this information into in silico models that estimate the pharmacokinetics of individual constituents should facilitate prospective identification of herb–drug interactions. These concepts are highlighted with the exemplar herbal products milk thistle and resveratrol. Implementation of this methodology should help provide definitive information to both consumers and clinicians about the risk of adding herbal products to conventional pharmacotherapeutic regimens. PMID:24335390

Developing a Molecular Roadmap of Drug-Food Interactions

DEFF Research Database (Denmark)

Jensen, Kasper; Ni, Yueqiong; Panagiotou, Gianni

2015-01-01

therapeutic interventions, a systematic approach for identifying, predicting and preventing potential interactions between food and marketed or novel drugs is not yet available. The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4,000 dietary components present...... view of the associations between diet and dietary molecules with drug targets, metabolic enzymes, drug transporters and carriers currently deposited in Drug-Bank. Moreover, we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions, showcasing......Recent research has demonstrated that consumption of food -especially fruits and vegetables-can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes. Despite the recognition of such drug-food associations as an important element for successful...

Analysis of possible food/nutrient and drug interactions in hospitalized patients

Directory of Open Access Journals (Sweden)

Everton Moraes Lopes

2010-09-01

Full Text Available Objective: To evaluate the prescription in relation to the possible interactions between drugs and foods/nutrients in the diets of patients in the Hospital Regional Justino Luz in the municipality of Picos, Piauí, Brazil. Methods: The sample consisted of 60 medical records of patients admitted at the hospital. The records were analyzed according to the presence or absence of interactions between drugs and foods/nutrients of the prescribed diets. Results: Of the 82 drugs prescribed in all periods, there were 16 drugs (19.5% with possible interaction with food, a total of 60 interactions between nutrient/food and medicine. Thus, 18 (30%, 10 (17% and 8 (13% possible interactions were identified with captopril (cardiovascular drug with acetylsalicylic acid (anti-inflammatory and spironolactone (diuretic, respectively representing the highest numbers of interactions among the classes of investigated drugs. It was also found that the total interactions between food/nutrients and drugs, 32 (53% accounted for interactions with cardiovascular drugs, 13 (22% with anti-inflammatory drugs, 11 (18% with diuretic agents e 4 (7% with drugs that act on the digestive tract. Conclusion: There was a high number of interactions between food/nutrients and medicines emphasizing the need for prior knowledge of these interactions as a way to avoid impairment in the treatment, longer hospital stays and/or damage to the nutritional status of the patients.

Large-scale prediction of drug–target interactions using protein sequences and drug topological structures

International Nuclear Information System (INIS)

Cao Dongsheng; Liu Shao; Xu Qingsong; Lu Hongmei; Huang Jianhua; Hu Qiannan; Liang Yizeng

2012-01-01

Highlights: ► Drug–target interactions are predicted using an extended SAR methodology. ► A drug–target interaction is regarded as an event triggered by many factors. ► Molecular fingerprint and CTD descriptors are used to represent drugs and proteins. ► Our approach shows compatibility between the new scheme and current SAR methodology. - Abstract: The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug discovery. It is both consuming and costly to determine drug–target interactions by experiments alone. Therefore, there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug–target interactions in a timely manner. In this article, we aim at extending current structure–activity relationship (SAR) methodology to fulfill such requirements. In some sense, a drug–target interaction can be regarded as an event or property triggered by many influence factors from drugs and target proteins. Thus, each interaction pair can be represented theoretically by using these factors which are based on the structural and physicochemical properties simultaneously from drugs and proteins. To realize this, drug molecules are encoded with MACCS substructure fingerings representing existence of certain functional groups or fragments; and proteins are encoded with some biochemical and physicochemical properties. Four classes of drug–target interaction networks in humans involving enzymes, ion channels, G-protein-coupled receptors (GPCRs) and nuclear receptors, are independently used for establishing predictive models with support vector machines (SVMs). The SVM models gave prediction accuracy of 90.31%, 88.91%, 84.68% and 83.74% for four datasets, respectively. In conclusion, the results demonstrate the ability of our proposed method to predict the drug–target interactions, and show a general compatibility between the new scheme and current SAR

Analysis of the Mechanism of Prolonged Persistence of Drug Interaction between Terbinafine and Amitriptyline or Nortriptyline.

Science.gov (United States)

Mikami, Akiko; Hori, Satoko; Ohtani, Hisakazu; Sawada, Yasufumi

2017-01-01

The purpose of the study was to quantitatively estimate and predict drug interactions between terbinafine and tricyclic antidepressants (TCAs), amitriptyline or nortriptyline, based on in vitro studies. Inhibition of TCA-metabolizing activity by terbinafine was investigated using human liver microsomes. Based on the unbound K i values obtained in vitro and reported pharmacokinetic parameters, a pharmacokinetic model of drug interaction was fitted to the reported plasma concentration profiles of TCAs administered concomitantly with terbinafine to obtain the drug-drug interaction parameters. Then, the model was used to predict nortriptyline plasma concentration with concomitant administration of terbinafine and changes of area under the curve (AUC) of nortriptyline after cessation of terbinafine. The CYP2D6 inhibitory potency of terbinafine was unaffected by preincubation, so the inhibition seems to be reversible. Terbinafine competitively inhibited amitriptyline or nortriptyline E-10-hydroxylation, with unbound K i values of 13.7 and 12.4 nM, respectively. Observed plasma concentrations of TCAs administered concomitantly with terbinafine were successfully simulated with the drug interaction model using the in vitro parameters. Model-predicted nortriptyline plasma concentration after concomitant nortriptylene/terbinafine administration for two weeks exceeded the toxic level, and drug interaction was predicted to be prolonged; the AUC of nortriptyline was predicted to be increased by 2.5- or 2.0- and 1.5-fold at 0, 3 and 6 months after cessation of terbinafine, respectively. The developed model enables us to quantitatively predict the prolonged drug interaction between terbinafine and TCAs. The model should be helpful for clinical management of terbinafine-CYP2D6 substrate drug interactions, which are difficult to predict due to their time-dependency.

Potential drug-drug interactions with direct oral anticoagulants in elderly hospitalized patients.

Science.gov (United States)

Forbes, Heather L; Polasek, Thomas M

2017-10-01

To determine the prevalence and nature of potential drug-drug interactions (DDIs) with direct oral anticoagulants (DOACs) in elderly hospitalized patients. This was a retrospective observational study. Inclusion criteria were: aged over 65 years; taking apixaban, rivaroxaban or dabigatran; and admitted to the Repatriation General Hospital between April 2014 and July 2015. A list of clinically relevant 'perpetrator' drugs was compiled from product information, the Australian Medicines Handbook, the Australian National Prescribing Service resources, and local health network guidelines. The prevalence and nature of potential DDIs with DOACs was determined by comparing inpatient drug charts with the list of perpetrator drugs. There were 122 patients in the study with a mean age of 82 years. Most patients had nonvalvular atrial fibrillation and were taking DOACs to prevent thrombotic stroke (83%). Overall, 45 patients (37%) had a total of 54 potential DDIs. Thirty-five patients had potential pharmacodynamic DDIs with antidepressants, nonsteroidal anti-inflammatory drugs and antiplatelets (35/122, 29%). Nineteen patients had potential pharmacokinetic DDIs (19/122, 16%). Of these, 68% (13/19) were taking drugs that increase DOAC plasma concentrations (amiodarone, erythromycin, diltiazem or verapamil) and 32% (6/19) were taking drugs that decrease DOAC plasma concentrations (carbamazepine, primidone or phenytoin). There were no cases of patients taking contraindicated interacting drugs. Potential DDIs with DOACs in elderly hospital inpatients are relatively common, particularly interactions that may increase the risk of bleeding. The risk-benefit ratio of DOACs in elderly patients on polypharmacy should always be carefully considered.

Radiation and platinum drug interaction

International Nuclear Information System (INIS)

Nias, A.H.W.

1985-01-01

The ideal platinum drug-radiation interaction would achieve radiosensitization of hypoxic tumour cells with the use of a dose of drug which is completely non-toxic to normal tissues. Electron-affinic agents are employed with this aim, but the commoner platinum drugs are only weakly electron-affinic. They do have a quasi-alkylating action however, and this DNA targeting may account for the radiosensitizing effect which occurs with both pre- and post-radiation treatments. Because toxic drug dosage is usually required for this, the evidence of the biological responses to the drug and to the radiation, as well as to the combination, requires critical analysis before any claim of true enhancement, rather than simple additivity, can be accepted. The amount of enhancement will vary with both the platinum drug dose and the time interval between drug administration and radiation. Clinical schedules may produce an increase in tumour response and/or morbidity, depending upon such dose and time relationships. (author)

Drug Interactions between some antiepileptic and certain hypocholesterolaemic drugs in irradiated animals

International Nuclear Information System (INIS)

Shaaban, D.M.L.

2015-01-01

Drug Interactions between antiepileptic drug such as phenytoin and certain hypercholesterolaemia drug namely rosuvastatin were investigated on several biological parameters. Phenytoin (60 mg/kg i.p) and rosuvastatin (1.25 mg/kg i.p) were given either alone and in combination to normal and irradiated animals to investigate drug interactions between the test drugs. Anticonvulsant activity was evaluated using pentylenetetrazole in a dose (80 mg/kg i.p) in normal and irradiated mice. Brain neurotransmitters (glutamate and GABA) were investigated. Lipid profile (total cholesterol (TC), Triacylglycerol (TG), High density lipoprotein-cholesterol (HDL-C) and low density lipoprotein- cholesterol (LDL-C) were determined. Liver functions such as serum Aspartate amino transferase (AST) and serum alanine amino transferase (ALT) were also estimated. Oxidative stress bio markers namely serum malondialdehyde (MDA), serum nitric oxide (NO) and blood superoxide dismutase activity (SOD) were studied. Histopathological examinations of brain and liver tissues were performed. Administration of phenytoin concurrently with rosuvastatin is not recommended in patients receiving radiotherapy as dangerous side effects on liver functions and lipid profile may occur. The interactions between the two drugs in normal rats improve liver functions and lipid peroxidation. Apart from the action of the combination on total cholesterol, it improves lipid profile pattern. Rosuvastatin administration in combination with phenytoin may have additive anticonvulsant activity.

[Drug interactions and their management in patients with human immunodeficiency virus infection].

Science.gov (United States)

Cabarcos Ortíz de Barrón, A; Martínez Vázquez, J M; Lorenzo Zúñiga, V; Barrio Gómez, E

1998-03-01

In fact patients with human immune deficiency virus infection are in treatment with multidrugs regimen, also in antiretrovirical therapy as profilaxis and treatment opportunist infections and other problems, in other fact the high tase of intravenous drugs users in meta-done programming (one of the principal transmission cause). Consequently is necessary an rational approximation to this problem also in the deepth knowledgment of his mechanisms and his management in the daily clinical practice.

Pharmacoepidemiological assessment of drug interactions with vitamin K antagonists

DEFF Research Database (Denmark)

Pottegård, Anton; Christensen, Rene dePont; Wang, Shirley V

2014-01-01

PurposeWe present a database of prescription drugs and international normalized ratio (INR) data and the applied methodology for its use to assess drug-drug interactions with vitamin K antagonists (VKAs). We use the putative interaction between VKAs and tramadol as a case study. MethodsWe used...

Indolealkylamines: Biotransformations and Potential Drug–Drug Interactions

OpenAIRE

Yu, Ai-Ming

2008-01-01

Indolealkylamine (IAA) drugs are 5-hydroxytryptamine (5-HT or serotonin) analogs that mainly act on the serotonin system. Some IAAs are clinically utilized for antimigraine therapy, whereas other substances are notable as drugs of abuse. In the clinical evaluation of antimigraine triptan drugs, studies on their biotransformations and pharmacokinetics would facilitate the understanding and prevention of unwanted drug–drug interactions (DDIs). A stable, principal metabolite of an IAA drug of ab...

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.

Pharmacokinetic and pharmacodynamic drug interactions with ethanol (alcohol).

Science.gov (United States)

Chan, Lingtak-Neander; Anderson, Gail D

2014-12-01

Ethanol (alcohol) is one of the most widely used legal drugs in the world. Ethanol is metabolized by alcohol dehydrogenase (ADH) and the cytochrome P450 (CYP) 2E1 drug-metabolizing enzyme that is also responsible for the biotransformation of xenobiotics and fatty acids. Drugs that inhibit ADH or CYP2E1 are the most likely theoretical compounds that would lead to a clinically significant pharmacokinetic interaction with ethanol, which include only a limited number of drugs. Acute ethanol primarily alters the pharmacokinetics of other drugs by changing the rate and extent of absorption, with more limited effects on clearance. Both acute and chronic ethanol use can cause transient changes to many physiologic responses in different organ systems such as hypotension and impairment of motor and cognitive functions, resulting in both pharmacokinetic and pharmacodynamic interactions. Evaluating drug interactions with long-term use of ethanol is uniquely challenging. Specifically, it is difficult to distinguish between the effects of long-term ethanol use on liver pathology and chronic malnutrition. Ethanol-induced liver disease results in decreased activity of hepatic metabolic enzymes and changes in protein binding. Clinical studies that include patients with chronic alcohol use may be evaluating the effects of mild cirrhosis on liver metabolism, and not just ethanol itself. The definition of chronic alcohol use is very inconsistent, which greatly affects the quality of the data and clinical application of the results. Our study of the literature has shown that a significantly higher volume of clinical studies have focused on the pharmacokinetic interactions of ethanol and other drugs. The data on pharmacodynamic interactions are more limited and future research addressing pharmacodynamic interactions with ethanol, especially regarding the non-central nervous system effects, is much needed.

Pharmacokinetic drug-drug interaction and their implication in clinical management

OpenAIRE

Palleria, Caterina; DI PAOLO, Antonello; Giofrè, Chiara; Caglioti, Chiara; Leuzzi, Giacomo; Siniscalchi, Antonio; De Sarro, Giovambattista; Gallelli, Luca

2013-01-01

Drug-drug interactions (DDIs) are one of the commonest causes of medication error in developed countries, particularly in the elderly due to poly-therapy, with a prevalence of 20-40%. In particular, poly-therapy increases the complexity of therapeutic management and thereby the risk of clinically important DDIs, which can both induce the development of adverse drug reactions or reduce the clinical efficacy. DDIs can be classify into two main groups: pharmacokinetic and pharmacodynamic. In thi...

Movement coordination in applied human-human and human-robot interaction

DEFF Research Database (Denmark)

Schubö, Anna; Vesper, Cordula; Wiesbeck, Mathey

2007-01-01

and describing human-human interaction in terms of goal-oriented movement coordination is considered an important and necessary step for designing and describing human-robot interaction. In the present scenario, trajectories of hand and finger movements were recorded while two human participants performed......The present paper describes a scenario for examining mechanisms of movement coordination in humans and robots. It is assumed that coordination can best be achieved when behavioral rules that shape movement execution in humans are also considered for human-robot interaction. Investigating...... coordination were affected. Implications for human-robot interaction are discussed....

Effect of honokiol on the induction of drug-metabolizing enzymes in human hepatocytes

Directory of Open Access Journals (Sweden)

Cho YY

2014-11-01

Full Text Available Yong-Yeon Cho,1 Hyeon-Uk Jeong,1 Jeong-Han Kim,2 Hye Suk Lee1 1College of Pharmacy, The Catholic University of Korea, Bucheon, Korea; 2Department of Agricultural Biotechnology, Seoul National University, Seoul, Korea Abstract: Honokiol, 2-(4-hydroxy-3-prop-2-enyl-phenyl-4-prop-2-enyl-phenol, an active component of Magnolia officinalis and Magnolia grandiflora, exerts various pharmacological activities such as antitumorigenic, antioxidative, anti-inflammatory, neurotrophic, and antithrombotic effects. To investigate whether honokiol acts as a perpetrator in drug interactions, messenger ribonucleic acid (mRNA levels of phase I and II drug-metabolizing enzymes, including cytochrome P450 (CYP, UDP-glucuronosyltransferase (UGT, and sulfotransferase 2A1 (SULT2A1, were analyzed by real-time reverse transcription polymerase chain reaction following 48-hour honokiol exposure in three independent cryopreserved human hepatocyte cultures. Honokiol treatment at the highest concentration tested (50 µM increased the CYP2B6 mRNA level and CYP2B6-catalyzed bupropion hydroxylase activity more than two-fold in three different hepatocyte cultures, indicating that honokiol induces CYP2B6 at higher concentrations. However, honokiol treatment (0.5–50 µM did not significantly alter the mRNA levels of phase I enzymes (CYP1A2, CYP3A4, CYP2C8, CYP2C9, and CYP2C19 or phase II enzymes (UGT1A1, UGT1A4, UGT1A9, UGT2B7, and SULT2A1 in cryopreserved human hepatocyte cultures. CYP1A2-catalyzed phenacetin O-deethylase and CYP3A4-catalyzed midazolam 1'-hydroxylase activities were not affected by 48-hour honokiol treatment in cryopreserved human hepatocytes. These results indicate that honokiol is a weak CYP2B6 inducer and is unlikely to increase the metabolism of concomitant CYP2B6 substrates and cause pharmacokinetic-based drug interactions in humans. Keywords: honokiol, human hepatocytes, drug interactions, cytochrome P450, UDP-glucuronosyltransferases

Venetoclax (ABT-199) Might Act as a Perpetrator in Pharmacokinetic Drug-Drug Interactions.

Science.gov (United States)

Weiss, Johanna; Gajek, Thomas; Köhler, Bruno Christian; Haefeli, Walter Emil

2016-02-24

Venetoclax (ABT-199) represents a specific B-cell lymphoma 2 (Bcl-2) inhibitor that is currently under development for the treatment of lymphoid malignancies. So far, there is no published information on its interaction potential with important drug metabolizing enzymes and drug transporters, or its efficacy in multidrug resistant (MDR) cells. We therefore scrutinized its drug-drug interaction potential in vitro. Inhibition of cytochrome P450 enzymes (CYPs) was quantified by commercial kits. Inhibition of drug transporters (P-glycoprotein (P-gp, ABCB1), breast cancer resistance protein (BCRP), and organic anion transporting polypeptides (OATPs)) was evaluated by the use of fluorescent probe substrates. Induction of drug transporters and drug metabolizing enzymes was quantified by real-time RT-PCR. The efficacy of venetoclax in MDR cells lines was evaluated with proliferation assays. Venetoclax moderately inhibited P-gp, BCRP, OATP1B1, OATP1B3, CYP3A4, and CYP2C19, whereas CYP2B6 activity was increased. Venetoclax induced the mRNA expression of CYP1A1, CYP1A2, UGT1A3, and UGT1A9. In contrast, expression of ABCB1 was suppressed, which might revert tumor resistance towards antineoplastic P-gp substrates. P-gp over-expression led to reduced antiproliferative effects of venetoclax. Effective concentrations for inhibition and induction lay in the range of maximum plasma concentrations of venetoclax, indicating that it might act as a perpetrator drug in pharmacokinetic drug-drug interactions.

Hypericum perforatum: pharmacokinetic, mechanism of action, tolerability, and clinical drug-drug interactions.

Science.gov (United States)

Russo, Emilio; Scicchitano, Francesca; Whalley, Benjamin J; Mazzitello, Carmela; Ciriaco, Miriam; Esposito, Stefania; Patanè, Marinella; Upton, Roy; Pugliese, Michela; Chimirri, Serafina; Mammì, Maria; Palleria, Caterina; De Sarro, Giovambattista

2014-05-01

Hypericum perforatum (HP) belongs to the Hypericaceae family and is one of the oldest used and most extensively investigated medicinal herbs. The medicinal form comprises the leaves and flowering tops of which the primary ingredients of interest are naphthodianthrones, xanthones, flavonoids, phloroglucinols (e.g. hyperforin), and hypericin. Although several constituents elicit pharmacological effects that are consistent with HP's antidepressant activity, no single mechanism of action underlying these effects has thus far been found. Various clinical trials have shown that HP has a comparable antidepressant efficacy as some currently used antidepressant drugs in the treatment of mild/moderate depression. Interestingly, low-hyperforin-content preparations are effective in the treatment of depression. Moreover, HP is also used to treat certain forms of anxiety. However, HP can induce various cytochrome P450s isozymes and/or P-glycoprotein, of which many drugs are substrates and which are the main origin of HP-drug interactions. Here, we analyse the existing evidence describing the clinical consequence of HP-drug interactions. Although some of the reported interactions are based on findings from in vitro studies, the clinical importance of which remain to be demonstrated, others are based on case reports where causality can, in some cases, be determined to reveal clinically significant interactions that suggest caution, consideration, and disclosure of potential interactions prior to informed use of HP. Copyright © 2013 John Wiley & Sons, Ltd.

Clinical Drug-Drug Pharmacokinetic Interaction Potential of Sucralfate with Other Drugs: Review and Perspectives.

Science.gov (United States)

Sulochana, Suresh P; Syed, Muzeeb; Chandrasekar, Devaraj V; Mullangi, Ramesh; Srinivas, Nuggehally R

2016-10-01

Sucralfate, a complex of aluminium hydroxide with sulfated sucrose, forms a strong gastrointestinal tract (GIT) mucosal barrier with excellent anti-ulcer property. Because sucralfate does not undergo any significant oral absorption, sucralfate resides in the GIT for a considerable length of time. The unabsorbed sucralfate may alter the pharmacokinetics of the oral drugs by impeding its absorption and reducing the oral bioavailability. Because of the increased use of sucralfate, it was important to provide a reappraisal of the published clinical drug-drug interaction studies of sucralfate with scores of drugs. This review covers several category of drugs such as non-steroidal anti-inflammatory drugs, fluoroquinolones, histamine H2-receptor blockers, macrolides, anti-fungals, anti-diabetics, salicylic acid derivatives, steroidal anti-inflammatory drugs and provides pharmacokinetic data summary along with study design, objectives and key remarks. While the loss of oral bioavailability was significant for the fluoroquinolone class, it generally varied for other classes of drugs, suggesting that impact of the co-administration of sucralfate is manageable in clinical situations. Given the technology advancement in formulation development, it may be in order feasible to develop appropriate formulation strategies to either avoid or minimize the absorption-related issues when co-administered with sucralfate. It is recommended that consideration of both in vitro and preclinical studies may be in order to gauge the level of interaction of a drug with sucralfate. Such data may aid in the development of appropriate strategies to navigate the co-administration of sucralfate with other drugs in this age of polypharmacy.

Pharmacokinetic drug interactions of antimicrobial drugs : a systematic review on oxazolidinones, rifamycines, macrolides, fluoroquinolones, and Beta-lactams

NARCIS (Netherlands)

Bolhuis, Mathieu S; Panday, Prashant N; Pranger, Arianna D; Kosterink, Jos G W; Alffenaar, Jan-Willem C

2011-01-01

Like any other drug, antimicrobial drugs are prone to pharmacokinetic drug interactions. These drug interactions are a major concern in clinical practice as they may have an effect on efficacy and toxicity. This article provides an overview of all published pharmacokinetic studies on drug

Hepatic transporter drug-drug interactions: an evaluation of approaches and methodologies.

Science.gov (United States)

Williamson, Beth; Riley, Robert J

2017-12-01

Drug-drug interactions (DDIs) continue to account for 5% of hospital admissions and therefore remain a major regulatory concern. Effective, quantitative prediction of DDIs will reduce unexpected clinical findings and encourage projects to frontload DDI investigations rather than concentrating on risk management ('manage the baggage') later in drug development. A key challenge in DDI prediction is the discrepancies between reported models. Areas covered: The current synopsis focuses on four recent influential publications on hepatic drug transporter DDIs using static models that tackle interactions with individual transporters and in combination with other drug transporters and metabolising enzymes. These models vary in their assumptions (including input parameters), transparency, reproducibility and complexity. In this review, these facets are compared and contrasted with recommendations made as to their application. Expert opinion: Over the past decade, static models have evolved from simple [I]/k i models to incorporate victim and perpetrator disposition mechanisms including the absorption rate constant, the fraction of the drug metabolised/eliminated and/or clearance concepts. Nonetheless, models that comprise additional parameters and complexity do not necessarily out-perform simpler models with fewer inputs. Further, consideration of the property space to exploit some drug target classes has also highlighted the fine balance required between frontloading and back-loading studies to design out or 'manage the baggage'.

Open-source chemogenomic data-driven algorithms for predicting drug-target interactions.

Science.gov (United States)

Hao, Ming; Bryant, Stephen H; Wang, Yanli

2018-02-06

While novel technologies such as high-throughput screening have advanced together with significant investment by pharmaceutical companies during the past decades, the success rate for drug development has not yet been improved prompting researchers looking for new strategies of drug discovery. Drug repositioning is a potential approach to solve this dilemma. However, experimental identification and validation of potential drug targets encoded by the human genome is both costly and time-consuming. Therefore, effective computational approaches have been proposed to facilitate drug repositioning, which have proved to be successful in drug discovery. Doubtlessly, the availability of open-accessible data from basic chemical biology research and the success of human genome sequencing are crucial to develop effective in silico drug repositioning methods allowing the identification of potential targets for existing drugs. In this work, we review several chemogenomic data-driven computational algorithms with source codes publicly accessible for predicting drug-target interactions (DTIs). We organize these algorithms by model properties and model evolutionary relationships. We re-implemented five representative algorithms in R programming language, and compared these algorithms by means of mean percentile ranking, a new recall-based evaluation metric in the DTI prediction research field. We anticipate that this review will be objective and helpful to researchers who would like to further improve existing algorithms or need to choose appropriate algorithms to infer potential DTIs in the projects. The source codes for DTI predictions are available at: https://github.com/minghao2016/chemogenomicAlg4DTIpred. Published by Oxford University Press 2018. This work is written by US Government employees and is in the public domain in the US.

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

Science.gov (United States)

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.

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.

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

Science.gov (United States)

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Guidance for nuclear medicine staff on radiopharmaceuticals drug interaction

International Nuclear Information System (INIS)

Santos-Oliveira, Ralph

2009-01-01

Numerous drug interactions related to radiopharmaceuticals take place every day in hospitals many of which are not reported or detected. Information concerning this kind of reaction is not abundant, and nuclear medicine staff are usually overwhelmed by this information. To better understand this type of reaction, and to help nuclear medicine staff deal with it, a review of the literature was conducted. The results show that almost all of radiopharmaceuticals marketed around the world present drug interactions with a large variety of compounds. This suggests that a logical framework to make decisions based on reviews incorporating adverse reactions must be created. The review also showed that researchers undertaking a review of literature, or even a systematic review that incorporates drug interactions, must understand the rationale for the suggested methods and be able to implement them in their review. Additionally, a global effort should be made to report as many cases of drug interaction with radiopharmaceuticals as possible. With this, a complete picture of drug interactions with radiopharmaceuticals can be drawn. (author)

Predicting transporter-mediated drug interactions: Commentary on: "Pharmacokinetic evaluation of a drug transporter cocktail consisting of digoxin, furosemide, metformin and rosuvastatin" and "Validation of a microdose probe drug cocktail for clinical drug interaction assessments for drug transporters and CYP3A".

Science.gov (United States)

Zhang, L; Sparreboom, A

2017-04-01

Transporters, expressed in various tissues, govern the absorption, distribution, metabolism, and excretion of drugs, and consequently their inherent safety and efficacy profiles. Drugs may interact with a transporter as a substrate and/or an inhibitor. Understanding transporter-mediated drug-drug interactions (DDIs), in addition to enzyme-mediated DDIs, is an integral part of risk assessment in drug development and regulatory review because the concomitant use of more than one medication in patients is common. © 2016 ASCPT.

Hydrophilic interaction chromatography with a focus on the drug-phosphate interaction in drug screening to determine the phospholipidosis induction risk.

Science.gov (United States)

Okamoto, Haruka; Hamaguchi, Ryohei; Kuroda, Yukihiro

2017-04-15

Cationic amphiphilic drugs (CADs) can induce the hyperaccumulation of phospholipids in cells and tissues. This side effect, which is known as drug-induced phospholipidosis, is sometimes problematic in the development and clinical use of CADs. It is known that CADs generally interact with phospholipids via both hydrophobic and acid-base interactions, and CADs with the larger affinity to phospholipid exhibit the larger induction risk. To develop a chromatographic assay system to predict the phospholipidosis-inducing potential with considering the acid-base interaction between CAD and phosphate group of phospholipid, hydrophilic interaction chromatographic (HILIC) methods were tested in this study. First, a PC HILIC column with phosphocholine groups on a packed material was used. The acid-base or other hydrophilic interactions to the stationary phase differed among basic drugs, and retention to the PC HILIC column did not accurately reflect the induction potential of phospholipidosis. As an alternative HILIC approach, the elution of CADs with the phosphate buffer from an amide column was tested. The elution effect, which is expressed as ratio of retention factors between different phosphate content in the mobile phase, closely correlated with the induction potential. Using the elution effect and retention factor to a reversed-phase HPLC column, the phospholipidosis-inducing drugs were clearly discriminated from the non-inducers. These results suggest that the proposed chromatographic approach can screen phospholipidosis-inducing drugs. Copyright © 2017 Elsevier B.V. All rights reserved.

Potential drug–drug interactions in Alzheimer patients with behavioral symptoms

Directory of Open Access Journals (Sweden)

Pasqualetti G

2015-09-01

Full Text Available Giuseppe Pasqualetti, Sara Tognini, Valeria Calsolaro, Antonio Polini, Fabio Monzani Geriatrics Unit, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy Abstract: The use of multi drug regimens among the elderly population has increased tremendously over the last decade although the benefits of medications are always accompanied by potential harm, even when prescribed at recommended doses. The elderly populations are particularly at an increased risk of adverse drug reactions considering comorbidity, poly-therapy, physiological changes affecting the pharmacokinetics and pharmacodynamics of many drugs and, in some cases, poor compliance due to cognitive impairment and/or depression. In this setting, drug–drug interaction may represent a serious and even life-threatening clinical condition. Moreover, the inability to distinguish drug-induced symptoms from a definitive medical diagnosis often results in addition of yet another drug to treat the symptoms, which in turn increases drug–drug interactions. Cognitive enhancers, including acetylcholinesterase inhibitors and memantine, are the most widely prescribed agents for Alzheimer’s disease (AD patients. Behavioral and psychological symptoms of dementia, including psychotic symptoms and behavioral disorders, represent noncognitive disturbances frequently observed in AD patients. Antipsychotic drugs are at high risk of adverse events, even at modest doses, and may interfere with the progression of cognitive impairment and interact with several drugs including anti-arrhythmics and acetylcholinesterase inhibitors. Other medications often used in AD patients are represented by anxiolytic, like benzodiazepine, or antidepressant agents. These agents also might interfere with other concomitant drugs through both pharmacokinetic and pharmacodynamic mechanisms. In this review we focus on the most frequent drug–drug interactions, potentially harmful, in AD patients with

Drug-food interaction counseling programs in teaching hospitals.

Science.gov (United States)

Wix, A R; Doering, P L; Hatton, R C

1992-04-01

The results of a survey to characterize drug-food interaction counseling programs in teaching hospitals and solicit opinions on these programs from pharmacists and dietitians are reported. A questionnaire was mailed to the pharmacy director and the director of dietary services at teaching hospitals nationwide. The questionnaire contained 33 questions relating to hospital characteristics, drug-food interaction counseling programs, and the standard calling for such programs issued by the Joint Commission on Accreditation of Healthcare Organizations. Of 792 questionnaires mailed, 425 were returned (response rate, 53.7). A majority of the pharmacists and dietitians (51.2%) did not consider their drug-food interaction counseling program to be formal; some had no program. The pharmacy department was involved more in program development than in the daily operation of such programs. The most frequent methods of identifying patients for counseling were using lists of patients' drugs and using physicians' orders. A mean of only five drugs were targeted per program. Slightly over half the respondents rated the Joint Commission standard less effective than other standards in its ability to improve patient care. A majority of teaching hospitals did not have formal drug-food interaction counseling programs. Pharmacists and dietitians did not view these programs as greatly beneficial and did not believe that the Joint Commission has clearly delineated the requirements for meeting its standard.

Target-mediated drug disposition with drug-drug interaction, Part I: single drug case in alternative formulations.

Science.gov (United States)

Koch, Gilbert; Jusko, William J; Schropp, Johannes

2017-02-01

Target-mediated drug disposition (TMDD) describes drug binding with high affinity to a target such as a receptor. In application TMDD models are often over-parameterized and quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are essential to reduce the number of parameters. However, implementation of such approximations becomes difficult for TMDD models with drug-drug interaction (DDI) mechanisms. Hence, alternative but equivalent formulations are necessary for QE or QSS approximations. To introduce and develop such formulations, the single drug case is reanalyzed. This work opens the route for straightforward implementation of QE or QSS approximations of DDI TMDD models. The manuscript is the first part to introduce DDI TMDD models with QE or QSS approximations.

Interaction of rocuronium with human liver cytochromes P450.

Science.gov (United States)

Anzenbacherova, Eva; Spicakova, Alena; Jourova, Lenka; Ulrichova, Jitka; Adamus, Milan; Bachleda, Petr; Anzenbacher, Pavel

2015-02-01

Rocuronium is a neuromuscular blocking agent acting as a competitive antagonist of acetylcholine. Results of an inhibition of eight individual liver microsomal cytochromes P450 (CYP) are presented. As the patients are routinely premedicated with diazepam, possible interaction of diazepam with rocuronium has been also studied. Results indicated that rocuronium interacts with human liver microsomal CYPs by binding to the substrate site. Next, concentration dependent inhibition of liver microsomal CYP3A4 down to 42% (at rocuronium concentration 189 μM) was found. This effect has been confirmed with two CYP3A4 substrates, testosterone (formation of 6β-hydroxytestosterone) and diazepam (temazepam formation). CYP2C9 and CYP2C19 activities were inhibited down to 75-80% (at the same rocuronium concentration). Activities of other microsomal CYPs have not been inhibited by rocuronium. To prove the possibility of rocuronium interaction with other drugs (diazepam), the effect of rocuronium on formation of main diazepam metabolites, temazepam (by CYP3A4) and desmethyldiazepam, (also known as nordiazepam; formed by CYP2C19) in primary culture of human hepatocytes has been examined. Rocuronium has caused inhibition of both reactions by 20 and 15%, respectively. The results open a possibility that interactions of rocuronium with drugs metabolized by CYP3A4 (and possibly also CYP2C19) may be observed. Copyright © 2014 Japanese Pharmacological Society. Production and hosting by Elsevier B.V. All rights reserved.

An Oral Contraceptive Drug Interaction Study

Science.gov (United States)

Bradstreet, Thomas E.; Panebianco, Deborah L.

2004-01-01

This article focuses on a two treatment, two period, two treatment sequence crossover drug interaction study of a new drug and a standard oral contraceptive therapy. Both normal theory and distribution-free statistical analyses are provided along with a notable amount of graphical insight into the dataset. For one of the variables, the decision on…

Insights into CYP2B6-mediated drug–drug interactions

Directory of Open Access Journals (Sweden)

William D. Hedrich

2016-09-01

Full Text Available Mounting evidence demonstrates that CYP2B6 plays a much larger role in human drug metabolism than was previously believed. The discovery of multiple important substrates of CYP2B6 as well as polymorphic differences has sparked increasing interest in the genetic and xenobiotic factors contributing to the expression and function of the enzyme. The expression of CYP2B6 is regulated primarily by the xenobiotic receptors constitutive androstane receptor (CAR and pregnane X receptor (PXR in the liver. In addition to CYP2B6, these receptors also mediate the inductive expression of CYP3A4, and a number of important phase II enzymes and drug transporters. CYP2B6 has been demonstrated to play a role in the metabolism of 2%–10% of clinically used drugs including widely used antineoplastic agents cyclophosphamide and ifosfamide, anesthetics propofol and ketamine, synthetic opioids pethidine and methadone, and the antiretrovirals nevirapine and efavirenz, among others. Significant inter-individual variability in the expression and function of the human CYP2B6 gene exists and can result in altered clinical outcomes in patients receiving treatment with CYP2B6-substrate drugs. These variances arise from a number of sources including genetic polymorphism, and xenobiotic intervention. In this review, we will provide an overview of the key players in CYP2B6 expression and function and highlight recent advances made in assessing clinical ramifications of important CYP2B6-mediated drug–drug interactions.

Relative contributions of the major human CYP450 to the metabolism of icotinib and its implication in prediction of drug-drug interaction between icotinib and CYP3A4 inhibitors/inducers using physiologically based pharmacokinetic modeling.

Science.gov (United States)

Chen, Jia; Liu, Dongyang; Zheng, Xin; Zhao, Qian; Jiang, Ji; Hu, Pei

2015-06-01

Icotinib is an anticancer drug, but relative contributions of CYP450 have not been identified. This study was carried out to identify the contribution percentage of CYP450 to icotinib and use the results to develop a physiologically based pharmacokinetic (PBPK) model, which can help to predict drug-drug interaction (DDI). Human liver microsome (HLM) and supersome using relative activity factor (RAF) were employed to determine the relative contributions of the major human P450 to the net hepatic metabolism of icotinib. These values were introduced to develop a PBPK model using SimCYP. The model was validated by the observed data in a Phase I clinical trial in Chinese healthy subjects. Finally, the model was used to simulate the DDI with ketoconazole or rifampin. Final contribution of CYP450 isoforms determined by HLM showed that CYP3A4 provided major contributions to the metabolism of icotinib. The percentage contributions of the P450 to the net hepatic metabolism of icotinib were determined by HLM inhibition assay and RAF. The AUC ratio under concomitant use of ketoconazole and rifampin was 3.22 and 0.55, respectively. Percentage of contribution of CYP450 to icotinib metabolism was calculated by RAF. The model has been proven to fit the observed data and is used in predicting icotinib-ketoconazole/rifampin interaction.

Curcumin as a clinically-promising anti-cancer agent: pharmacokinetics and drug interactions.

Science.gov (United States)

Adiwidjaja, Jeffry; McLachlan, Andrew J; Boddy, Alan V

2017-09-01

Curcumin has been extensively studied for its anti-cancer properties. While a diverse array of in vitro and preclinical research support the prospect of curcumin use as an anti-cancer therapeutic, most human studies have failed to meet the intended clinical expectation. Poor systemic availability of orally-administered curcumin may account for this disparity. Areas covered: This descriptive review aims to concisely summarise available clinical studies investigating curcumin pharmacokinetics when administered in different formulations. A critical analysis of pharmacokinetic- and pharmacodynamic-based interactions of curcumin with concomitantly administered drugs is also provided. Expert opinion: The encouraging clinical results of curcumin administration are currently limited to people with colorectal cancer, given that sufficient curcumin concentrations persist in colonic mucosa. Higher parent curcumin systemic exposure, which can be achieved by several newer formulations, has important implications for optimal treatment of cancers other than those in gastrointestinal tract. Curcumin-drug pharmacokinetic interactions are also almost exclusively in the enterocytes, owing to extensive first pass metabolism and poor curcumin bioavailability. Greater scope of these interactions, i.e. modulation of the systemic elimination of co-administered drugs, may be expected from more-bioavailable curcumin formulations. Further studies are still warranted, especially with newer formulations to support the inclusion of curcumin in cancer therapy regimens.

iP-gp , a novel cell line with tight barrier function and expression of human P-glycoprotein (ABCB1) for drug screening

DEFF Research Database (Denmark)

Brodin, Birger; Ozgür, Burak; Saaby, Lasse

that new API's are evaluated with respect to P-gp interactions.  Aim : The aim of the present work was to validate the suitability of the newly developed iP-gp cell line for investigating P-gp interactions with human P-gp. Methods: IPEC-J2 MDR1 (iP-gp) cells were cultured on permeable supports for 17......Background : The efflux transporter P-glycoprotein (P-gp, product of the MDR1/ABCB1 gene) hinders uptake of drug compounds to the brain, limits intestinal uptake, is a cause of resistance to chemoterapeutics and a potential "site" for drug-drug interaction. Regulatory agencies therefore recommend.......04 +/- 0.01 µM in transport experiments including digoxin and rhodamine 123, respectively. Summary/Conclusion : The iP-gp cell line may become a useful screening tool for interactions between drug compounds and human P-gp....

Transporter-mediated natural product–drug interactions for the treatment of cardiovascular diseases

Directory of Open Access Journals (Sweden)

Weibin Zha

2018-04-01

Full Text Available The growing use of natural products in cardiovascular (CV patients has been greatly raising the concerns about potential natural product–CV drug interactions. Some of these may lead to unexpected cardiovascular adverse effects and it is, therefore, essential to identify or predict potential natural product–CV drug interactions, and to understand the underlying mechanisms. Drug transporters are important determinants for the pharmacokinetics of drugs and alterations of drug transport has been recognized as one of the major causes of natural product–drug interactions. In last two decades, many CV drugs (e.g., angiotensin II receptor blockers, beta-blockers and statins have been identified to be substrates and inhibitors of the solute carrier (SLC transporters and the ATP-binding cassette (ABC transporters, which are two major transporter superfamilies. Meanwhile, in vitro and in vivo studies indicate that a growing number of natural products showed cardioprotective effects (e.g., gingko biloba, danshen and their active ingredients are also substrates and inhibitors of drug transporters. Thus, to understand transporter-mediated natural product–CV drug interactions is important and some transporter-mediated interactions have already shown to have clinical relevance. In this review, we review the current knowledge on the role of ABC and SLC transporters in CV therapy, as well as transporter modulation by natural products used in CV diseases and their induced natural product–CV drug interactions through alterations of drug transport. We hope our review will aid in a comprehensive summary of transporter-mediated natural product–CV drug interactions and help public and physicians understand these type of interactions. Keywords: Cardiovascular drugs, Natural products, Drug transporters, Natural product–drug interaction, Pharmacokinetics

Clinically relevant potential drug-drug interactions among outpatients: A nationwide database study.

Science.gov (United States)

Jazbar, Janja; Locatelli, Igor; Horvat, Nejc; Kos, Mitja

2018-06-01

Adverse drug events due to drug-drug interactions (DDIs) represent a considerable public health burden, also in Slovenia. A better understanding of the most frequently occurring potential DDIs may enable safer pharmacotherapy and minimize drug-related problems. The aim of this study was to evaluate the prevalence and predictors of potential DDIs among outpatients in Slovenia. An analysis of potential DDIs was performed using health claims data on prescription drugs from a nationwide database. The Lexi-Interact Module was used as the reference source of interactions. The influence of patient-specific predictors on the risk of potential clinically relevant DDIs was evaluated using logistic regression model. The study population included 1,179,803 outpatients who received 15,811,979 prescriptions. The total number of potential DDI cases identified was 3,974,994, of which 15.6% were potentially clinically relevant. Altogether, 9.3% (N = 191,213) of the total population in Slovenia is exposed to clinically relevant potential DDIs, and the proportion is higher among women and the elderly. After adjustment for cofactors, higher number of medications and older age are associated with higher odds of clinically relevant potential DDIs. The burden of DDIs is highest with drug combinations that increase risk of bleeding, enhance CNS depression or anticholinergic effects or cause cardiovascular complications. The current study revealed that 1 in 10 individuals in the total Slovenian population is exposed to clinically relevant potential DDIs yearly. Taking into account the literature based conservative estimate that approximately 1% of potential DDIs result in negative health outcomes, roughly 1800 individuals in Slovenia experience an adverse health outcome each year as a result of clinically relevant potential interactions alone. Copyright © 2017 Elsevier Inc. All rights reserved.

Interaction of an atypical Plasmodium falciparum ETRAMP with human apolipoproteins

Directory of Open Access Journals (Sweden)

Sahasrabudhe Sudhir

2008-10-01

Full Text Available Abstract Background In order to establish a successful infection in the human host, the malaria parasite Plasmodium falciparum must establish interactions with a variety of human proteins on the surface of different cell types, as well as with proteins inside the host cells. To better understand this aspect of malaria pathogenesis, a study was conducted with the goal of identifying interactions between proteins of the parasite and those of its human host. Methods A modified yeast two-hybrid methodology that preferentially selects protein fragments that can be expressed in yeast was used to conduct high-throughput screens with P. falciparum protein fragments against human liver and cerebellum libraries. The resulting dataset was analyzed to exclude interactions that are not likely to occur in the human host during infection. Results An initial set of 2,200 interactions was curated to remove proteins that are unlikely to play a role in pathogenesis based on their annotation or localization, and proteins that behave promiscuously in the two-hybrid assay, resulting in a final dataset of 456 interactions. A cluster that implicates binding between P. falciparum PFE1590w/ETRAMP5, a putative parasitophorous vacuole membrane protein, and human apolipoproteins ApoA, ApoB and ApoE was selected for further analysis. Different isoforms of ApoE, which are associated with different outcomes of malaria infection, were shown to display differential interactions with PFE1590w. Conclusion A dataset of interactions between proteins of P. falciparum and those of its human host was generated. The preferential interaction of the P. falciparum PFE1590w protein with the human ApoE ε3 and ApoE ε4 isoforms, but not the ApoE ε2 isoform, supports the hypothesis that ApoE genotype affects risk of malaria infection. The dataset contains other interactions of potential relevance to disease that may identify possible vaccine candidates and drug targets.

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information.

Science.gov (United States)

Luo, Yunan; Zhao, Xinbin; Zhou, Jingtian; Yang, Jinglin; Zhang, Yanqing; Kuang, Wenhua; Peng, Jian; Chen, Ligong; Zeng, Jianyang

2017-09-18

The emergence of large-scale genomic, chemical and pharmacological data provides new opportunities for drug discovery and repositioning. In this work, we develop a computational pipeline, called DTINet, to predict novel drug-target interactions from a constructed heterogeneous network, which integrates diverse drug-related information. DTINet focuses on learning a low-dimensional vector representation of features, which accurately explains the topological properties of individual nodes in the heterogeneous network, and then makes prediction based on these representations via a vector space projection scheme. DTINet achieves substantial performance improvement over other state-of-the-art methods for drug-target interaction prediction. Moreover, we experimentally validate the novel interactions between three drugs and the cyclooxygenase proteins predicted by DTINet, and demonstrate the new potential applications of these identified cyclooxygenase inhibitors in preventing inflammatory diseases. These results indicate that DTINet can provide a practically useful tool for integrating heterogeneous information to predict new drug-target interactions and repurpose existing drugs.Network-based data integration for drug-target prediction is a promising avenue for drug repositioning, but performance is wanting. Here, the authors introduce DTINet, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations.

78 FR 29755 - Human Immunodeficiency Virus Patient-Focused Drug Development and Human Immunodeficiency Virus...

Science.gov (United States)

2013-05-21

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2013-N-0473] Human Immunodeficiency Virus Patient-Focused Drug Development and Human Immunodeficiency Virus Cure... an opportunity for public comment on human immunodeficiency virus (HIV) Patient-Focused Drug...

Erythromycin potentiates PR interval prolonging effect of verapamil in the rat: A pharmacodynamic drug interaction

International Nuclear Information System (INIS)

Dakhel, Yaman; Jamali, Fakhreddin

2006-01-01

Calcium channel blockers and macrolide antibiotics account for many drug interactions. Anecdotal reports suggest interactions between the two resulting in severe side effects. We studied the interaction between verapamil and erythromycin in the rat to see whether it occurs at the pharmacokinetics or pharmacodynamic level. Adult male Sprague-Dawley rats received doses of 1 mg/kg verapamil or 100 mg/kg erythromycin alone or in combination (n = 6/group). Serial blood samples (0-6 h) were taken for determination of the drug concentrations using HPLC. Electrocardiograms were recorded (0-6 h) through subcutaneously inserted lead II. Binding of the drugs to plasma proteins was studied using spiked plasma. Verapamil prolonged PR but not QT interval. Erythromycin prolonged QT but not PR interval. The combination resulted in a significant increase in PR interval prolongation and AV node blocks but did not further prolong QT interval. Pharmacokinetics and protein binding of neither drug were altered by the other. Our rat data confirm the anecdotal human case reports that combination of erythromycin and verapamil can result in potentiation of the cardiovascular response. The interaction appears to be at the pharmacodynamic rather than pharmacokinetic level hence may be extrapolated to other calcium channel antagonists

FTIR Drug-Polymer Interactions Studies of Perindopril Erbumine

International Nuclear Information System (INIS)

Modni, A.; Ahmad, S.; Din, I.; Hussain, Z.

2014-01-01

The present study was carried out to prepare different combinations of Perindopril Erbumine with different polymers like Hydroxy propyl methyl cellulose, Hydroxy propyl methyl cellulose K4M, Hydroxy propyl methyl cellulose K15M, Xanthan gum and Ethyl cellulose, thereby to determine any possible interactions between Perindopril erbumine and polymers. The analytical technique Fourier Transform Infrared (FTIR) spectroscopy was used to take spectra of individual drug, polymers and combination of drug with polymers. The results were analyzed to find out any interactions of Perindopril erbumine and polymers. From this study it was concluded that there were no any significant changes in characteristic peaks of drug after combinations with polymers which indicated no interaction between Perindopril erbumine and polymers. (author)

78 FR 46969 - Human Immunodeficiency Virus Patient-Focused Drug Development and Human Immunodeficiency Virus...

Science.gov (United States)

2013-08-02

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration [Docket No. FDA-2013-N-0473] Human Immunodeficiency Virus Patient-Focused Drug Development and Human Immunodeficiency Virus Cure... for the notice of public meeting entitled ``Human Immunodeficiency Virus (HIV) Patient-Focused Drug...

Co-morbidity and clinically significant interactions between antiepileptic drugs and other drugs in elderly patients with newly diagnosed epilepsy.

Science.gov (United States)

Bruun, Emmi; Virta, Lauri J; Kälviäinen, Reetta; Keränen, Tapani

2017-08-01

A study was conducted to investigate the frequency of potential pharmacokinetic drug-to-drug interactions in elderly patients with newly diagnosed epilepsy. We also investigated co-morbid conditions associated with epilepsy. From the register of Kuopio University Hospital (KUH) we identified community-dwelling patients aged 65 or above with newly diagnosed epilepsy and in whom use of the first individual antiepileptic drug (AED) began in 2000-2013 (n=529). Furthermore, register data of the Social Insurance Institution of Finland were used for assessing potential interactions in a nationwide cohort of elderly subjects with newly diagnosed epilepsy. We extracted all patients aged 65 or above who had received special reimbursement for the cost of AEDs prescribed on account of epilepsy in 2012 where their first AED was recorded in 2011-2012 as monotherapy (n=1081). Clinically relevant drug interactions (of class C or D) at the time of starting of the first AED, as assessed via the SFINX-PHARAO database, were analysed. Hypertension (67%), dyslipidemia (45%), and ischaemic stroke (32%) were the most common co-morbid conditions in the hospital cohort of patients. In these patients, excessive polypharmacy (more than 10 concomitant drugs) was identified in 27% of cases. Of the patients started on carbamazepine, 52 subjects (32%) had one class-C or class-D drug interaction and 51 (31%) had two or more C- or D-class interactions. Only 2% of the subjects started on valproate exhibited a class-C interaction. None of the subjects using oxcarbazepine displayed class-C or class-D interactions. Patients with 3-5 (OR 4.22; p=0.05) or over six (OR 8.86; p=0.003) other drugs were more likely to have C- or D-class interaction. The most common drugs with potential interactions with carbamazepine were dihydropyridine calcium-blockers, statins, warfarin, and psychotropic drugs. Elderly patients with newly diagnosed epilepsy are at high risk of clinically relevant pharmacokinetic

The effects of Andrographis paniculata (Burm.f.) Nees extract and diterpenoids on the CYP450 isoforms' activities, a review of possible herb-drug interaction risks.

Science.gov (United States)

Tan, Mei Lan; Lim, Lin Ee

2015-01-01

Andrographis paniculata (Burm.f.) Nees is a popular medicinal plant and its components are used in various traditional product preparations. However, its herb-drug interactions risks remain unclear. This review specifically discusses the various published studies carried out to evaluate the effects of Andrographis paniculata (Burm.f.) Nees plant extracts and diterpenoids on the CYP450 metabolic enzyme and if the plant components pose a possible herb-drug interaction risk. Unfortunately, the current data are insufficient to indicate if the extracts or diterpenoids can be labeled as in vitro CYP1A2, CYP2C9 or CYP3A4 inhibitors. A complete CYP inhibition assay utilizing human liver microsomes and the derivation of relevant parameters to predict herb-drug interaction risks may be necessary for these isoforms. However, based on the current studies, none of the extracts and diterpenoids exhibited CYP450 induction activity in human hepatocytes or human-derived cell lines. It is crucial that a well-defined experimental design is needed to make a meaningful herb-drug interaction prediction.

Drug-drug interactions involving antidepressants: focus on desvenlafaxine.

Science.gov (United States)

Low, Yvette; Setia, Sajita; Lima, Graca

2018-01-01

Psychiatric and physical conditions often coexist, and there is robust evidence that associates the frequency of depression with single and multiple physical conditions. More than half of patients with depression may have at least one chronic physical condition. Therefore, antidepressants are often used in cotherapy with other medications for the management of both psychiatric and chronic physical illnesses. The risk of drug-drug interactions (DDIs) is augmented by complex polypharmacy regimens and extended periods of treatment required, of which possible outcomes range from tolerability issues to lack of efficacy and serious adverse events. Optimal patient outcomes may be achieved through drug selection with minimal potential for DDIs. Desvenlafaxine is a serotonin-norepinephrine reuptake inhibitor approved for the treatment of adults with major depressive disorder. Pharmacokinetic studies of desvenlafaxine have shown a simple metabolic profile unique among antidepressants. This review examines the DDI profiles of antidepressants, particularly desvenlafaxine, in relation to drugs of different therapeutic areas. The summary and comparison of information available is meant to help clinicians in making informed decisions when using desvenlafaxine in patients with depression and comorbid chronic conditions.

Emotional valence and context of social influences on drug abuse-related behavior in animal models of social stress and prosocial interaction.

Science.gov (United States)

Neisewander, J L; Peartree, N A; Pentkowski, N S

2012-11-01

Social factors are important determinants of drug dependence and relapse. We reviewed pre-clinical literature examining the role of social experiences from early life through the development of drug dependence and relapse, emphasizing two aspects of these experiences: (1) whether the social interaction is appetitive or aversive and (2) whether the social interaction occurs within or outside of the drug-taking context. The models reviewed include neonatal care, isolation, social defeat, chronic subordination, and prosocial interactions. We review results from these models in regard to effects on self-administration and conditioned place preference established with alcohol, psychostimulants, and opiates. We suggest that in general, when the interactions occur outside of the drug-taking context, prosocial interactions are protective against drug abuse-related behaviors, whereas social stressors facilitate these behaviors. By contrast, positive or negative social interactions occurring within the drug-taking context may interact with other risk factors to enhance or inhibit these behaviors. Despite differences in the nature and complexity of human social behavior compared to other species, the evolving animal literature provides useful models for understanding social influences on drug abuse-related behavior that will allow for research on the behavioral and biological mechanisms involved. The models have contributed to understanding social influences on initiation and maintenance of drug use, but more research is needed to understand social influences on drug relapse.

[Terbinafine : Relevant drug interactions and their management].

Science.gov (United States)

Dürrbeck, A; Nenoff, P

2016-09-01

The allylamine terbinafine is the probably most frequently prescribed systemic antifungal agent in Germany for the treatment of dermatomycoses and onychomycoses. According to the German drug law, terbinafine is approved for patients who are 18 years and older; however, this antifungal agent is increasingly used off-label for treatment of onychomycoses and tinea capitis in children. Terbinafine is associated with only a few interactions with other drugs, which is why terbinafine can generally be used without problems in older and multimorbid patients. Nevertheless, some potential interactions of terbinafine with certain drug substances are known, including substances of the group of antidepressants/antipsychotics and some cardiovascular drugs. Decisive for the relevance of interactions is-along with the therapeutic index of the substrate and the possible alternative degradation pathways-the genetically determined type of metabolism. When combining terbinafine with tricyclic antidepressants or selective serotonin reuptake inhibitors and serotonin/noradrenalin reuptake inhibitors, the clinical response and potential side effects must be monitored. Problematic is the use of terbinafine with simultaneous treatment with tamoxifen. The administration of potent CYP2D6 inhibitors leads to a diminished efficacy of tamoxifen because one of its most important active metabolites-endoxifen-is not sufficiently available. Therefore, combination of tamoxifen and terbinafine should be avoided. In conclusion, the number of substances which are able to cause clinically relevant interactions in case of simultaneously administration with terbinafine is clear and should be manageable in the dermatological office with adequate monitoring.

Studies on the interactions of chloroquine diphosphate and phenelzine sulfate drugs with human serum albumin and human hemoglobin proteins by spectroscopic techniques

Energy Technology Data Exchange (ETDEWEB)

Tunç, Sibel, E-mail: stunc@akdeniz.edu.tr; Duman, Osman, E-mail: osmanduman@akdeniz.edu.tr; Bozoğlan, Bahar Kancı

2013-08-15

The interactions of chloroquine diphosphate (CQP) and phenelzine sulfate (PS) drugs with human serum albumin (HSA) and human hemoglobin (HMG) proteins were investigated by various spectroscopic methods. It was found that CQP caused the fluorescence quenching of protein molecules through a static quenching mechanism, but PS did not. The values of Stern–Volmer quenching constant, bimolecular quenching constant, binding constant and number of binding site on the protein molecules were calculated for HSA–CQP and HMG–CQP systems at pH 7.4 and different temperatures. For CQP, there was only one binding site on HSA and HMG proteins and the binding affinity of HSA was higher than that of HMG. The binding constants decreased with increasing temperature. The values of negative enthalpy change and positive entropy change indicated that electrostatic interactions play an important role in the binding processes. In addition, the binding processes were spontaneous and carried out by exothermic reactions. According to Förster resonance energy transfer theory, the average binding distance between proteins and CQP was calculated as 3.72 nm for HSA–CQP system and 3.45 nm for HMG–CQP system. Circular dichroism analysis displayed that the addition of CQP led to a decrease in the α-helix amount of HSA and HMG proteins. -- Highlights: • Unlike PS, CQP was bounded by HSA and HMG proteins. • The fluorescence spectra of HSA and HMG were quenched by CQP through static mechanism. • HSA–CQP and HMG–CQP complexes were stabilized by electrostatic attraction forces. • Binding constants, thermodynamic parameters and binding distances were calculated. • The binding of CQP changed the conformational structure of HSA and HMG proteins.

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

Science.gov (United States)

Zhang, Shao-Wu; Yan, Xiao-Ying

2017-01-01

System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-consuming, tedious and expensive, and sometimes lack reproducibility. Thus, it is highly desired to develop computational methods for efficiently and effectively analyzing and detecting new drug-target interaction pairs. With the explosive growth of different types of omics data, such as genome, pharmacology, phenotypic, and other kinds of molecular networks, numerous computational approaches have been developed to predict Drug-Target Interactions (DTI). In this review, we make a survey on the recent advances in predicting drug-target interaction with network-based models from the following aspects: i) Available public data sources and benchmark datasets; ii) Drug/target similarity metrics; iii) Network construction; iv) Common network algorithms; v) Performance comparison of existing network-based DTI predictors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

In vitro drug interaction of levocetirizine and diclofenac: Theoretical and spectroscopic studies.

Science.gov (United States)

Abo Dena, Ahmed S; Abdel Gaber, Sara A

2017-06-15

Levocetirizine dihydrochloride is known to interact with some anti-inflammatory drugs. We report here a comprehensive integrated theoretical and experimental study for the in vitro drug interaction between levocetirizine dihydrochloride (LEV) and diclofenac sodium (DIC). The interaction of the two drugs was confirmed by the molecular ion peak obtained from the mass spectrum of the product. Moreover, FTIR and 1 HNMR spectra of the individual drugs and their interaction product were inspected to allocate the possible sites of interaction. In addition, quantum mechanical DFT calculations were performed to search for the interaction sites and to verify the types of interactions deduced from the spectroscopic studies such as charge-transfer and non-bonding π-π interactions. It was found that the studied drugs interact with each other in aqueous solution via four types of interactions, namely, ion-pair formation, three weak hydrogen bonds, non-bonding π-π interactions and charge-transfer from DIC to LEV. Copyright © 2017 Elsevier B.V. All rights reserved.

In vitro drug interaction of levocetirizine and diclofenac: Theoretical and spectroscopic studies

Science.gov (United States)

Abo Dena, Ahmed S.; Abdel Gaber, Sara A.

2017-06-01

Levocetirizine dihydrochloride is known to interact with some anti-inflammatory drugs. We report here a comprehensive integrated theoretical and experimental study for the in vitro drug interaction between levocetirizine dihydrochloride (LEV) and diclofenac sodium (DIC). The interaction of the two drugs was confirmed by the molecular ion peak obtained from the mass spectrum of the product. Moreover, FTIR and 1HNMR spectra of the individual drugs and their interaction product were inspected to allocate the possible sites of interaction. In addition, quantum mechanical DFT calculations were performed to search for the interaction sites and to verify the types of interactions deduced from the spectroscopic studies such as charge-transfer and non-bonding π-π interactions. It was found that the studied drugs interact with each other in aqueous solution via four types of interactions, namely, ion-pair formation, three weak hydrogen bonds, non-bonding π-π interactions and charge-transfer from DIC to LEV.

The Two Faces of Social Interaction Reward in Animal Models of Drug Dependence.

Science.gov (United States)

El Rawas, Rana; Saria, Alois

2016-03-01

Drug dependence is a serious health and social problem. Social factors can modify vulnerability to developing drug dependence, acting as risk factors or protective factors. Whereas stress and peer environment that encourage substance use may increase drug taking, strong attachments between family members and peer environment that do not experience drug use may protect against drug taking and, ultimately, drug dependence. The rewarding effects of drug abuse and social interaction can be evaluated using animal models. In this review we focus on evaluating social interaction reward in the conditioned place preference paradigm. We give an overview of how social interaction, if made available within the drug context, may facilitate, promote and interact with the drug's effects. However, social interaction, if offered alternatively outside the drug context, may have pronounced protective effects against drug abuse and relapse. We also address the importance of the weight difference parameter between the social partners in determining the positive or "agonistic" versus the hostile or "antagonistic" social interaction. We conclude that understanding social interaction reward and its subsequent effects on drug reward is sorely needed for therapeutic interventions against drug dependence.

Clinical management of drug-drug interactions in HCV therapy: Challenges and solutions

NARCIS (Netherlands)

Burger, D.M.; Back, D.; Buggisch, P.; Buti, M.; Craxi, A.; Foster, G.; Klinker, H.; Larrey, D.; Nikitin, I.; Pol, S. van der; Puoti, M.; Romero-Gomez, M.; Wedemeyer, H.; Zeuzem, S.

2013-01-01

Hepatitis C virus (HCV) infected patients often take multiple co-medications to treat adverse events related to HCV therapy, or to manage other co-morbidities. Drug-drug interactions associated with this polypharmacy are relatively new to the field of HCV pharmacotherapy. With the advent of the

[Molecular fundamentals of drug interactions in the therapy of colorectal cancer].

Science.gov (United States)

Regulska, Katarzyna; Stanisz, Beata; Regulski, Miłosz; Gieremek, Paulina

2014-03-04

Rapid advances in the field of chemotherapy have resulted in the introduction of numerous antineoplastic drugs into clinical practice, which increased the efficiency of patient management. Also the prevalent use of combination treatment based on drug action synergy contributed to the improved clinical effect associated with cytotoxic drug administration. It seems, however, obvious that the multidirectional pharmacotherapy in oncology requires a thorough knowledge of drugs' pharmaceutical behavior in order to maximize their collective action and prevent the occurrence of unintended drug interactions that could potentially impair treatment effectiveness. In fact, drug interactions constitute a serious problem for current oncology primarily resulting from a narrow therapeutic index specific for the majority of anticancer drugs. This, in turn, indicates that even slight deviations of their pharmacokinetics could cause significant clinical consequences, manifested by alteration of the toxicological profile or reduction of therapeutic efficiency. Hence, the investigation of molecular aspects underlying the mechanisms of various drug interactions seems to be essential for proper and safe patient management. The present article is devoted to the extensive subject of drug interactions occurring in the therapy of colorectal cancer. It presents the available literature data on both positive and negative effects of interactions and it discusses their mechanisms complying with their classification into pharmacokinetic and pharmacodynamic ones.

Drug Transporter Expression and Activity in Human Hepatoma HuH-7 Cells

Directory of Open Access Journals (Sweden)

Elodie Jouan

2016-12-01

Full Text Available Human hepatoma cells may represent a valuable alternative to the use of human hepatocytes for studying hepatic drug transporters, which is now a regulatory issue during drug development. In the present work, we have characterized hepatic drug transporter expression, activity and regulation in human hepatoma HuH-7 cells, in order to determine the potential relevance of these cells for drug transport assays. HuH-7 cells displayed notable multidrug resistance-associated protein (MRP activity, presumed to reflect expression of various hepatic MRPs, including MRP2. By contrast, they failed to display functional activities of the uptake transporters sodium taurocholate co-transporting polypeptide (NTCP, organic anion-transporting polypeptides (OATPs and organic cation transporter 1 (OCT1, and of the canalicular transporters P-glycoprotein and breast cancer resistance protein (BCRP. Concomitantly, mRNA expressions of various sinusoidal and canalicular hepatic drug transporters were not detected (NTCP, OATP1B1, organic anion transporter 2 (OAT2, OCT1 and bile salt export pump or were found to be lower (OATP1B3, OATP2B1, multidrug and toxin extrusion protein 1, BCRP and MRP3 in hepatoma HuH-7 cells than those found in human hepatocytes, whereas other transporters such as OAT7, MRP4 and MRP5 were up-regulated. HuH-7 cells additionally exhibited farnesoid X receptor (FXR- and nuclear factor erythroid 2-related factor 2 (Nrf2-related up-regulation of some transporters. Such data indicate that HuH-7 cells, although expressing rather poorly some main hepatic drug transporters, may be useful for investigating interactions of drugs with MRPs, notably MRP2, and for studying FXR- or Nrf2-mediated gene regulation.

Review of pharmacological interactions of oral anticancer drugs provided at pharmacy department

Directory of Open Access Journals (Sweden)

E. Sánchez Gómez

2014-07-01

Full Text Available Abstract: Objective: To identify the pharmacologic interactions of oral anti-cancer drugs provided at an outpatient clinic. Material and methods: Anti-cancer drugs included in the Phamacotherapeutic Guideline of the Hospital were identified. A literature search was carried out on the pharmacologic interactions in MEDLINE® and EMBASE® (with the filer language English or Spanish, and the descriptors: “name of the anti-cancer drug” AND (“drug interactions” OR “pharmacokinetic”, Up-to-date®, MICROMEDEX® and the drug information sheet for the EMA and the FDA. Information was also gathered from the abstract presented to European and Spanish scientific meetings for the last 4 years. When an interaction was analyzed and had clinical relevance, the best pharmacotherapeutic interaction-free alternative was sought. Results: Twenty-three drugs were identified, of which Chlorambucil, Fludarabine, Lenalidomide, Melphalan, and Thalidomide were the active compounds with the lowest likelihood of producing a pharmacologic interaction. Tyrosine kinase inhibitors (particularly Erlotinib, Imatinib, Lapatinib, and Pazopanib are the drugs with highest number of pharmacologic interactions described, many of them with severe clinical consequences, with increases and decreases of the plasma levels of anti-cancer drugs. The active compounds identified that may have pharmacologic interactions with anticancer drugs were mainly: Allopurinol, Amiodarone, Carbamazepine, Dabigatran, Digoxin, Spironolactone, Phenytoin, Itraconazol, Repaglinide, Silodosin, Tamoxifen, Verapamil, and Warfarin. Pharmacologic interactions through the cytochrome P450 1A2, 2D6, 2C8, 2C9, 3A4 were the most important for tyrosine kinase inhibitors. Other non-pharmacologic compounds, with an important potential of producing relevant pharmacologic interaction were immunomodulators (Echinacea extracts and Hypericum perforatum. Conclusions: Oral anticancer drugs have numerous pharmacologic

Human-Robot Interaction and Human Self-Realization

DEFF Research Database (Denmark)

Nørskov, Marco

2014-01-01

is to test the basis for this type of discrimination when it comes to human-robot interaction. Furthermore, the paper will take Heidegger's warning concerning technology as a vantage point and explore the possibility of human-robot interaction forming a praxis that might help humans to be with robots beyond...

Warfarin: pharmacological profile and drug interactions with antidepressants

Directory of Open Access Journals (Sweden)

Juliana Souto Teles

2012-03-01

Full Text Available Oral anticoagulants are among the drugs with the greatest numberof drug interactions. The concomitant use of several medications isa common practice in patients with cardiovascular problems, whooften also present with depression; therefore, the probability of aninteraction occurring between warfarin and the antidepressants ishigh, and may result in increased or decreased anticoagulant activity.Since the possible interactions between these two classes of drugshave been poorly explored in literature, with a risk to the patients who use them, we reviewed the pharmacology of warfarin and its possible interactions with antidepressants. Of the antidepressants analyzed, those that showed relevant effects on the interaction with warfarin were, in decreasing order: paroxetine, venlafaxine, fluoxetine, and duloxetine.

Pharmacokinetic drug-drug interaction and their implication in clinical management.

Science.gov (United States)

Palleria, Caterina; Di Paolo, Antonello; Giofrè, Chiara; Caglioti, Chiara; Leuzzi, Giacomo; Siniscalchi, Antonio; De Sarro, Giovambattista; Gallelli, Luca

2013-07-01

Drug-drug interactions (DDIs) are one of the commonest causes of medication error in developed countries, particularly in the elderly due to poly-therapy, with a prevalence of 20-40%. In particular, poly-therapy increases the complexity of therapeutic management and thereby the risk of clinically important DDIs, which can both induce the development of adverse drug reactions or reduce the clinical efficacy. DDIs can be classify into two main groups: pharmacokinetic and pharmacodynamic. In this review, using Medline, PubMed, Embase, Cochrane library and Reference lists we searched articles published until June 30 2012, and we described the mechanism of pharmacokinetic DDIs focusing the interest on their clinical implications.

Transporter-mediated natural product-drug interactions for the treatment of cardiovascular diseases.

Science.gov (United States)

Zha, Weibin

2018-04-01

The growing use of natural products in cardiovascular (CV) patients has been greatly raising the concerns about potential natural product-CV drug interactions. Some of these may lead to unexpected cardiovascular adverse effects and it is, therefore, essential to identify or predict potential natural product-CV drug interactions, and to understand the underlying mechanisms. Drug transporters are important determinants for the pharmacokinetics of drugs and alterations of drug transport has been recognized as one of the major causes of natural product-drug interactions. In last two decades, many CV drugs (e.g., angiotensin II receptor blockers, beta-blockers and statins) have been identified to be substrates and inhibitors of the solute carrier (SLC) transporters and the ATP-binding cassette (ABC) transporters, which are two major transporter superfamilies. Meanwhile, in vitro and in vivo studies indicate that a growing number of natural products showed cardioprotective effects (e.g., gingko biloba, danshen and their active ingredients) are also substrates and inhibitors of drug transporters. Thus, to understand transporter-mediated natural product-CV drug interactions is important and some transporter-mediated interactions have already shown to have clinical relevance. In this review, we review the current knowledge on the role of ABC and SLC transporters in CV therapy, as well as transporter modulation by natural products used in CV diseases and their induced natural product-CV drug interactions through alterations of drug transport. We hope our review will aid in a comprehensive summary of transporter-mediated natural product-CV drug interactions and help public and physicians understand these type of interactions. Copyright © 2017. Published by Elsevier B.V.

Potential intravenous drug interactions in intensive care.

Science.gov (United States)

Moreira, Maiara Benevides; Mesquita, Maria Gefé da Rosa; Stipp, Marluci Andrade Conceição; Paes, Graciele Oroski

2017-07-20

To analyze potential intravenous drug interactions, and their level of severity associated with the administration of these drugs based on the prescriptions of an intensive care unit. Quantitative study, with aretrospective exploratory design, and descriptive statistical analysis of the ICU prescriptions of a teaching hospital from March to June 2014. The sample consisted of 319 prescriptions and subsamples of 50 prescriptions. The mean number of drugs per patient was 9.3 records, and a higher probability of drug interaction inherent to polypharmacy was evidenced. The study identified severe drug interactions, such as concomitant administration of Tramadol with selective serotonin reuptake inhibitor drugs (e.g., Metoclopramide and Fluconazole), increasing the risk of seizures due to their epileptogenic actions, as well as the simultaneous use of Ranitidine-Fentanyl®, which can lead to respiratory depression. A previous mapping of prescriptions enables the characterization of the drug therapy, contributing to prevent potential drug interactions and their clinical consequences. Analisar as potenciais interações medicamentosas intravenosas e seu grau de severidade associadas à administração desses medicamentos a partir das prescrições do Centro de Terapia Intensiva. Estudo quantitativo, tipologia retrospectiva exploratória, com análise estatística descritiva das prescrições medicamentosas do Centro de Terapia Intensiva de um Hospital Universitário, no período de março-junho/2014. A amostra foi composta de 319 prescrições e subamostras de 50 prescrições. Constatou-se que a média de medicamentos por paciente foi de 9,3 registros, e evidenciou-se maior probabilidade para ocorrência de interação medicamentosa inerente à polifarmácia. O estudo identificou interações medicamentosas graves, como a administração concomitante de Tramadol com medicamentos inibidores seletivos da recaptação da serotonina, (exemplo: Metoclopramida e Fluconazol

Drug-target interaction prediction: A Bayesian ranking approach.

Science.gov (United States)

Peska, Ladislav; Buza, Krisztian; Koller, Júlia

2017-12-01

In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug

Using Nonexperts for Annotating Pharmacokinetic Drug-Drug Interaction Mentions in Product Labeling: A Feasibility Study.

Science.gov (United States)

Hochheiser, Harry; Ning, Yifan; Hernandez, Andres; Horn, John R; Jacobson, Rebecca; Boyce, Richard D

2016-04-11

Because vital details of potential pharmacokinetic drug-drug interactions are often described in free-text structured product labels, manual curation is a necessary but expensive step in the development of electronic drug-drug interaction information resources. The use of nonexperts to annotate potential drug-drug interaction (PDDI) mentions in drug product label annotation may be a means of lessening the burden of manual curation. Our goal was to explore the practicality of using nonexpert participants to annotate drug-drug interaction descriptions from structured product labels. By presenting annotation tasks to both pharmacy experts and relatively naïve participants, we hoped to demonstrate the feasibility of using nonexpert annotators for drug-drug information annotation. We were also interested in exploring whether and to what extent natural language processing (NLP) preannotation helped improve task completion time, accuracy, and subjective satisfaction. Two experts and 4 nonexperts were asked to annotate 208 structured product label sections under 4 conditions completed sequentially: (1) no NLP assistance, (2) preannotation of drug mentions, (3) preannotation of drug mentions and PDDIs, and (4) a repeat of the no-annotation condition. Results were evaluated within the 2 groups and relative to an existing gold standard. Participants were asked to provide reports on the time required to complete tasks and their perceptions of task difficulty. One of the experts and 3 of the nonexperts completed all tasks. Annotation results from the nonexpert group were relatively strong in every scenario and better than the performance of the NLP pipeline. The expert and 2 of the nonexperts were able to complete most tasks in less than 3 hours. Usability perceptions were generally positive (3.67 for expert, mean of 3.33 for nonexperts). The results suggest that nonexpert annotation might be a feasible option for comprehensive labeling of annotated PDDIs across a broader

A novel algorithm for analyzing drug-drug interactions from MEDLINE literature.

Science.gov (United States)

Lu, Yin; Shen, Dan; Pietsch, Maxwell; Nagar, Chetan; Fadli, Zayd; Huang, Hong; Tu, Yi-Cheng; Cheng, Feng

2015-11-27

Drug-drug interaction (DDI) is becoming a serious clinical safety issue as the use of multiple medications becomes more common. Searching the MEDLINE database for journal articles related to DDI produces over 330,000 results. It is impossible to read and summarize these references manually. As the volume of biomedical reference in the MEDLINE database continues to expand at a rapid pace, automatic identification of DDIs from literature is becoming increasingly important. In this article, we present a random-sampling-based statistical algorithm to identify possible DDIs and the underlying mechanism from the substances field of MEDLINE records. The substances terms are essentially carriers of compound (including protein) information in a MEDLINE record. Four case studies on warfarin, ibuprofen, furosemide and sertraline implied that our method was able to rank possible DDIs with high accuracy (90.0% for warfarin, 83.3% for ibuprofen, 70.0% for furosemide and 100% for sertraline in the top 10% of a list of compounds ranked by p-value). A social network analysis of substance terms was also performed to construct networks between proteins and drug pairs to elucidate how the two drugs could interact.

Core drug-drug interaction alerts for inclusion in pediatric electronic health records with computerized prescriber order entry.

Science.gov (United States)

Harper, Marvin B; Longhurst, Christopher A; McGuire, Troy L; Tarrago, Rod; Desai, Bimal R; Patterson, Al

2014-03-01

The study aims to develop a core set of pediatric drug-drug interaction (DDI) pairs for which electronic alerts should be presented to prescribers during the ordering process. A clinical decision support working group composed of Children's Hospital Association (CHA) members was developed. CHA Pharmacists and Chief Medical Information Officers participated. Consensus was reached on a core set of 19 DDI pairs that should be presented to pediatric prescribers during the order process. We have provided a core list of 19 high value drug pairs for electronic drug-drug interaction alerts to be recommended for inclusion as high value alerts in prescriber order entry software used with a pediatric patient population. We believe this list represents the most important pediatric drug interactions for practical implementation within computerized prescriber order entry systems.

Accelerating Precision Drug Development and Drug Repurposing by Leveraging Human Genetics.

Science.gov (United States)

Pulley, Jill M; Shirey-Rice, Jana K; Lavieri, Robert R; Jerome, Rebecca N; Zaleski, Nicole M; Aronoff, David M; Bastarache, Lisa; Niu, Xinnan; Holroyd, Kenneth J; Roden, Dan M; Skaar, Eric P; Niswender, Colleen M; Marnett, Lawrence J; Lindsley, Craig W; Ekstrom, Leeland B; Bentley, Alan R; Bernard, Gordon R; Hong, Charles C; Denny, Joshua C

2017-04-01

The potential impact of using human genetic data linked to longitudinal electronic medical records on drug development is extraordinary; however, the practical application of these data necessitates some organizational innovations. Vanderbilt has created resources such as an easily queried database of >2.6 million de-identified electronic health records linked to BioVU, which is a DNA biobank with more than 230,000 unique samples. To ensure these data are used to maximally benefit and accelerate both de novo drug discovery and drug repurposing efforts, we created the Accelerating Drug Development and Repurposing Incubator, a multidisciplinary think tank of experts in various therapeutic areas within both basic and clinical science as well as experts in legal, business, and other operational domains. The Incubator supports a diverse pipeline of drug indication finding projects, leveraging the natural experiment of human genetics.

Drug interactions in primary health care in the George subdistrict ...

African Journals Online (AJOL)

2012-02-15

Feb 15, 2012 ... Drug-drug interactions are a recognised cause of morbidity and mortality ..... or fatal if the interaction increases toxicity or reduces the intended effect of the ... antihypertensive effect of angiotensin-converting enzyme inhibitors ...

Pharmacokinetic Interactions between Drugs and Botanical Dietary Supplements.

Science.gov (United States)

Sprouse, Alyssa A; van Breemen, Richard B

2016-02-01

The use of botanical dietary supplements has grown steadily over the last 20 years despite incomplete information regarding active constituents, mechanisms of action, efficacy, and safety. An important but underinvestigated safety concern is the potential for popular botanical dietary supplements to interfere with the absorption, transport, and/or metabolism of pharmaceutical agents. Clinical trials of drug-botanical interactions are the gold standard and are usually carried out only when indicated by unexpected consumer side effects or, preferably, by predictive preclinical studies. For example, phase 1 clinical trials have confirmed preclinical studies and clinical case reports that St. John's wort (Hypericum perforatum) induces CYP3A4/CYP3A5. However, clinical studies of most botanicals that were predicted to interact with drugs have shown no clinically significant effects. For example, clinical trials did not substantiate preclinical predictions that milk thistle (Silybum marianum) would inhibit CYP1A2, CYP2C9, CYP2D6, CYP2E1, and/or CYP3A4. Here, we highlight discrepancies between preclinical and clinical data concerning drug-botanical interactions and critically evaluate why some preclinical models perform better than others in predicting the potential for drug-botanical interactions. Gaps in knowledge are also highlighted for the potential of some popular botanical dietary supplements to interact with therapeutic agents with respect to absorption, transport, and metabolism. Copyright © 2016 by The American Society for Pharmacology and Experimental Therapeutics.

Exploiting Large-Scale Drug-Protein Interaction Information for Computational Drug Repurposing

Science.gov (United States)

2014-06-20

studies that have reported antimalarial activities of azole compounds [39-43] lend support to our model predictions. The highest-scored non-malarial...Table 4, verapamil and cimetidine, do not have antimal- arial activities themselves but exhibit synergism when used in combination with antimalarial ... activators . Because of their high frequencies among the antimalarial drugs, according to Eq. 3, the drug-protein interactions contributing most to the

Molecular fundamentals of drug interactions in the therapy of colorectal cancer

Directory of Open Access Journals (Sweden)

Katarzyna Regulska

2014-03-01

Full Text Available Rapid advances in the field of chemotherapy have resulted in the introduction of numerous antineoplastic drugs into clinical practice, which increased the efficiency of patient management. Also the prevalent use of combination treatment based on drug action synergy contributed to the improved clinical effect associated with cytotoxic drug administration. It seems, however, obvious that the multidirectional pharmacotherapy in oncology requires a thorough knowledge of drugs’ pharmaceutical behavior in order to maximize their collective action and prevent the occurrence of unintended drug interactions that could potentially impair treatment effectiveness. In fact, drug interactions constitute a serious problem for current oncology primarily resulting from a narrow therapeutic index specific for the majority of anticancer drugs. This, in turn, indicates that even slight deviations of their pharmacokinetics could cause significant clinical consequences, manifested by alteration of the toxicological profile or reduction of therapeutic efficiency. Hence, the investigation of molecular aspects underlying the mechanisms of various drug interactions seems to be essential for proper and safe patient management. The present article is devoted to the extensive subject of drug interactions occurring in the therapy of colorectal cancer. It presents the available literature data on both positive and negative effects of interactions and it discusses their mechanisms complying with their classification into pharmacokinetic and pharmacodynamic ones.

Developing a molecular roadmap of drug-food interactions.

Directory of Open Access Journals (Sweden)

Kasper Jensen

2015-02-01

Full Text Available Recent research has demonstrated that consumption of food -especially fruits and vegetables- can alter the effects of drugs by interfering either with their pharmacokinetic or pharmacodynamic processes. Despite the recognition of such drug-food associations as an important element for successful therapeutic interventions, a systematic approach for identifying, predicting and preventing potential interactions between food and marketed or novel drugs is not yet available. The overall objective of this work was to sketch a comprehensive picture of the interference of ∼ 4,000 dietary components present in ∼1800 plant-based foods with the pharmacokinetics and pharmacodynamics processes of medicine, with the purpose of elucidating the molecular mechanisms involved. By employing a systems chemical biology approach that integrates data from the scientific literature and online databases, we gained a global view of the associations between diet and dietary molecules with drug targets, metabolic enzymes, drug transporters and carriers currently deposited in DrugBank. Moreover, we identified disease areas and drug targets that are most prone to the negative effects of drug-food interactions, showcasing a platform for making recommendations in relation to foods that should be avoided under certain medications. Lastly, by investigating the correlation of gene expression signatures of foods and drugs we were able to generate a completely novel drug-diet interactome map.

Theoretical and experimental investigation of drug-polymer interaction and miscibility and its impact on drug supersaturation in aqueous medium.

Science.gov (United States)

Baghel, Shrawan; Cathcart, Helen; O'Reilly, Niall J

2016-10-01

Amorphous solid dispersions (ASDs) have the potential to offer higher apparent solubility and bioavailability of BCS class II drugs. Knowledge of the solid state drug-polymer solubility/miscibility and their mutual interaction are fundamental requirements for the effective design and development of such systems. To this end, we have carried out a comprehensive investigation of various ASD systems of dipyridamole and cinnarizine in polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) at different drug loadings. Theoretical and experimental examinations (by implementing binary and ternary Flory-Huggins (F-H) theory) related to drug-polymer interaction/miscibility including solubility parameter approach, melting point depression method, phase diagram, drug-polymer interaction in the presence of moisture and the effect of drug loading on interaction parameter were performed. The information obtained from this study was used to predict the stability of ASDs at different drug loadings and under different thermal and moisture conditions. Thermal and moisture sorption analysis not only provided the composition-dependent interaction parameter but also predicted the composition dependent miscibility. DPM-PVP, DPM-PAA and CNZ-PAA systems have shown molecular level mixing over the complete range of drug loading. For CNZ-PVP, the presence of a single Tg at lower drug loadings (10, 20 and 35%w/w) indicates the formation of solid solution. However, drug recrystallization was observed for samples with higher drug weight fractions (50 and 65%w/w). Finally, the role of polymer in maintaining drug supersaturation has also been explored. It has been found that drug-polymer combinations capable of hydrogen-bonding in the solution state (DPM-PVP, DPM-PAA and CNZ-PAA) are more effective in preventing drug crystallization compared to the drug-polymer systems without such interaction (CNZ-PVP). The DPM-PAA system outperformed all other ASDs in various stability conditions (dry-state, in

Potential drug interactions in patients given antiretroviral therapy.

Science.gov (United States)

Santos, Wendel Mombaque Dos; Secoli, Silvia Regina; Padoin, Stela Maris de Mello

2016-11-21

to investigate potential drug-drug interactions (PDDI) in patients with HIV infection on antiretroviral therapy. a cross-sectional study was conducted on 161 adults with HIV infection. Clinical, socio demographic, and antiretroviral treatment data were collected. To analyze the potential drug interactions, we used the software Micromedex(r). Statistical analysis was performed by binary logistic regression, with a p-value of ≤0.05 considered statistically significant. of the participants, 52.2% were exposed to potential drug-drug interactions. In total, there were 218 potential drug-drug interactions, of which 79.8% occurred between drugs used for antiretroviral therapy. There was an association between the use of five or more medications and potential drug-drug interactions (p = 0.000) and between the time period of antiretroviral therapy being over six years and potential drug-drug interactions (p central nervous and cardiovascular systems, but also can interfere in tests used for detection of HIV resistance to antiretroviral drugs. investigar potenciais interações droga-droga (PDDI) em pacientes infectados com HIV em terapia de antirretroviral. um estudo de corte transversal foi conduzido em 161 pessoas infectadas com o HIV. Dados de tratamentos clínicos, sociodemográficos e antirretrovirais foram coletados. Para analisar a possível interação medicamentosa, nós usamos o software Micromedex(r). A análise estatística foi feita por regressão logística binária, com um valor P de ≤0.05, considerado estatisticamente significativo. dos participantes, 52.2% foram expostos a potenciais interações droga-droga. No total, houve 218 interações droga-droga, das quais 79.8% ocorreram entre drogas usadas para a terapia antirretroviral. Houve uma associação entre o uso de cinco ou mais medicamentos e possíveis interações droga-droga (p = 0.000), e entre o período de tempo de terapia antirretroviral acima de seis anos e possíveis interações droga

Analysis of clinical drug-drug interaction data to predict uncharacterized interaction magnitudes between antiretroviral drugs and co-medications.

Science.gov (United States)

Stader, Felix; Kinvig, Hannah; Battegay, Manuel; Khoo, Saye; Owen, Andrew; Siccardi, Marco; Marzolini, Catia

2018-04-23

Despite their high potential for drug-drug-interactions (DDI), clinical DDI studies of antiretroviral drugs (ARVs) are often lacking, because the full range of potential interactions cannot feasibly or pragmatically be studied, with some high-risk DDI studies also ethically difficult to undertake. Thus, a robust method to screen and to predict the likelihood of DDIs is required.We developed a method to predict DDIs based on two parameters: the degree of metabolism by specific enzymes such as CYP3A and the strength of an inhibitor or inducer. These parameters were derived from existing studies utilizing paradigm substrates, inducers and inhibitors of CYP3A, to assess the predictive performance of this method by verifying predicted magnitudes of changes in drug exposure against clinical DDI studies involving ARVs.The derived parameters were consistent with the FDA classification of sensitive CYP3A substrates and the strength of CYP3A inhibitors and inducers. Characterized DDI magnitudes (n = 68) between ARVs and co-medications were successfully quantified meaning 53%, 85% and 98% of the predictions were within 1.25-fold (0.80 - 1.25), 1.5-fold (0.66 - 1.48) and 2-fold (0.66 - 1.94) of the observed clinical data. In addition, the method identifies CYP3A substrates likely to be highly or conversely minimally impacted by CYP3A inhibitors or inducers, thus categorizing the magnitude of DDIs.The developed effective and robust method has the potential to support a more rational identification of dose adjustment to overcome DDIs being particularly relevant in a HIV-setting giving the treatments complexity, high DDI risk and limited guidance on the management of DDIs. Copyright © 2018 American Society for Microbiology.

Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells

International Nuclear Information System (INIS)

Artursson, P.; Karlsson, J.

1991-01-01

Monolayers of a well differentiated human intestinal epithelial cell line, Caco-2, were used as a model to study passive drug absorption across the intestinal epithelium. Absorption rate constants (expressed as apparent permeability coefficients) were determined for 20 drugs and peptides with different structural properties. The permeability coefficients ranged from approximately 5 x 10 - 8 to 5 x 10 - 5 cm/s. A good correlation was obtained between data on oral absorption in humans and the results in the Caco-2 model. Drugs that are completely absorbed in humans had permeability coefficients greater than 1 x 10 - 6 cm/s. Drugs that are absorbed to greater than 1% but less than 100% had permeability coefficients of 0.1-1.0 x 10 - 6 cm/s while drugs and peptides that are absorbed to less than 1% had permeability coefficients of less than or equal to 1 x 10 - 7 cm/s. The results indicate that Caco-2 monolayers can be used as a model for studies on intestinal drug absorption

Pharmacokinetic drug-drug interaction and their implication in clinical management

Directory of Open Access Journals (Sweden)

Palleria Caterina

2013-01-01

Full Text Available Drug-drug interactions (DDIs are one of the commonest causes of medication error in developed countries, particularly in the elderly due to poly-therapy, with a prevalence of 20-40%. In particular, poly-therapy increases the complexity of therapeutic management and thereby the risk of clinically important DDIs, which can both induce the development of adverse drug reactions or reduce the clinical efficacy. DDIs can be classify into two main groups: pharmacokinetic and pharmacodynamic. In this review, using Medline, PubMed, Embase, Cochrane library and Reference lists we searched articles published until June 30 2012, and we described the mechanism of pharmacokinetic DDIs focusing the interest on their clinical implications.

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

Directory of Open Access Journals (Sweden)

Kanika Madaan

2014-01-01

Full Text Available Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity.

Dendrimers in drug delivery and targeting: Drug-dendrimer interactions and toxicity issues

Science.gov (United States)

Madaan, Kanika; Kumar, Sandeep; Poonia, Neelam; Lather, Viney; Pandita, Deepti

2014-01-01

Dendrimers are the emerging polymeric architectures that are known for their defined structures, versatility in drug delivery and high functionality whose properties resemble with biomolecules. These nanostructured macromolecules have shown their potential abilities in entrapping and/or conjugating the high molecular weight hydrophilic/hydrophobic entities by host-guest interactions and covalent bonding (prodrug approach) respectively. Moreover, high ratio of surface groups to molecular volume has made them a promising synthetic vector for gene delivery. Owing to these properties dendrimers have fascinated the researchers in the development of new drug carriers and they have been implicated in many therapeutic and biomedical applications. Despite of their extensive applications, their use in biological systems is limited due to toxicity issues associated with them. Considering this, the present review has focused on the different strategies of their synthesis, drug delivery and targeting, gene delivery and other biomedical applications, interactions involved in formation of drug-dendrimer complex along with characterization techniques employed for their evaluation, toxicity problems and associated approaches to alleviate their inherent toxicity. PMID:25035633

The antiprogesterone Org 31710 inhibits human blastocyst-endometrial interactions in vitro

DEFF Research Database (Denmark)

Petersen, Astrid; Bentin-Ley, Ursula; Ravn, Vibeke

2005-01-01

OBJECTIVE: To investigate the effect of the anti-P Org 31710 on human blastocyst attachment to cultured endometrial epithelial cells. DESIGN: Experimental in vitro study. SETTING: University hospital. PATIENT(S): Eleven fertile endometrial donors. INTERVENTION(S): Timed endometrial biopsy for cell...... statistical significance. The presence of swollen microvilli, precursors of endometrial pinopodes, was significantly reduced on cultures with Org 31710 (P=.03). CONCLUSION(S): The study presents a model for human blastocyst-endometrial interactions responding to an anti-P drug. The exact mechanism...

In Vitro Drug Metabolism by Human Carboxylesterase 1

DEFF Research Database (Denmark)

Thomsen, Ragnar; Rasmussen, Henrik B; Linnet, Kristian

2014-01-01

Carboxylesterase 1 (CES1) is the major hydrolase in human liver. The enzyme is involved in the metabolism of several important therapeutic agents, drugs of abuse, and endogenous compounds. However, no studies have described the role of human CES1 in the activation of two commonly prescribed...... a panel of therapeutic drugs and drugs of abuse to assess their inhibition of the hydrolysis of p-nitrophenyl acetate by recombinant CES1 and human liver microsomes. The screening assay confirmed several known inhibitors of CES1 and identified two previously unreported inhibitors: the dihydropyridine...... calcium antagonist, isradipine, and the immunosuppressive agent, tacrolimus. CES1 plays a role in the metabolism of several drugs used in the treatment of common conditions, including hypertension, congestive heart failure, and diabetes mellitus; thus, there is a potential for clinically relevant drug-drug...

[Rhabdomyolysis and severe hepatotoxicity due to a drug-drug interaction between ritonavir and simvastatin. Could we use the most cost-effective statin in all human immunodeficiency virus-infected patients?].

Science.gov (United States)

Bastida, Carla; Also, Maria Antonia; Pericas, Juan Manuel; Letang, Emili; Tuset, Montse; Miró, Josep Maria

2014-11-01

Drugs like statins may induce rhabdomyolysis. Simvastatin and lovastatin have a high hepatic metabolism and their potential toxicity could be increased by interactions with other drugs that reduce their metabolism. A case-report is presented of an HIV-infected patient treated with antiretroviral drugs who developed a rhabdomyolysis-induced renal failure and liver toxicity when simvastatin was substituted for atorvastatin. A literature review is also presented. The patient required hospital admission and showed a favorable response after hydration and urine alkalinization. There were 4 additional cases published of which there was one death. Drug-drug interactions can increase the risk of statin induced rhabdomyolysis. In order to evaluate them properly, physicians at all levels of clinical care should be aware of all drugs prescribed to their patients and the contraindicated combinations. Copyright © 2014 Elsevier España, S.L.U. y Sociedad Española de Enfermedades Infecciosas y Microbiología Clínica. All rights reserved.

[Enantioselective determinination of R-warfarin/S-warfarin in human plasma using liquid chromatography-tandem mass spectrometry and its application in a drug-drug interaction study].

Science.gov (United States)

Jin, Shu; Zhang, Yi-Fan; Chen, Xiao-Yan; Liu, Ke; Zhong, Da-Fang

2012-01-01

To study the drug-drug interaction of morinidazole and warfarin and its application, a sensitive and rapid liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed for the determination of R-warfarin/S-warfarin in human plasma. In a random, two-period crossover study, 12 healthy volunteers received a single oral dose of 5 mg racemic warfarin in the absence and presence of morinidazole. Blood samples were collected according to a pre-designed time schedule. R-warfarin, S-warfarin and methyclothiazide were extracted with ethylether : methylenechloride (3 : 2), then separated on a Astec Chirobiotic V (150 mm x 4.6 mm ID, 5 microm) column using 5 mmol x L(-1) ammonium acetate (pH 4.0) - acetonitrile as mobile phase at a flow-rate of 1.5 mL x min(-1). The mobile phase was splitted and 0.5 mL x min(-1) was introduced into MS. A tandem mass spectrometer equipped with electrospray ionization source was used as detector and operated in the negative ion mode. Quantification was performed using multiple reaction monitoring (MRM). The resolution of warfarin enantiomers is 1.56. The linear calibration curves for R-warfarin and S-warfarin both were obtained in the concentration range of 5 - 1 000 ng x mL(-1). Intra- and inter-day relative standard deviation (RSD) for R-warfarin and S-warfarin over the entire concentration range across three validation runs was both less than 10%, and relative error (RE) ranged from -4.9% to 0.7%, separately. The method herein described is effective and convenient, and suitable for the study of metabolic interaction between morinidazole and warfarin. The results showed that coadministration of warfarin with morinidazole did not affect the pharmacokinetics of either R-warfarin or S-warfarin.

Interactions between hormonal contraception and antiepileptic drugs

DEFF Research Database (Denmark)

Reimers, Arne; Brodtkorb, Eylert; Sabers, Anne

2015-01-01

Antiepileptic drugs (AEDs) and hormonal contraceptives may affect each other's metabolism and clinical efficacy. Loss of seizure control and unplanned pregnancy may occur when these compounds are used concomitantly. Although a large number of available preparations yield a plethora of possible drug...... combinations, most of these drug interactions are predictable and, thus, avoidable. Unfortunately, there is a substantial lack of data regarding the newer AEDs. Detailed understanding of these issues is necessary for those who prescribe AEDs and/or hormonal contraception to women with epilepsy, as well...

Radiopharmaceuticals drug interactions: a critical review

Directory of Open Access Journals (Sweden)

Ralph Santos-Oliveira

2008-12-01

Full Text Available Radiopharmaceuticals play a critical role in modern medicine primarily for diagnostic purposes, but also for monitoring disease progression and response to treatment. As the use of image has been increased, so has the use of prescription medications. These trends increase the risk of interactions between medications and radiopharmaceuticals. These interactions which have an impact on image by competing with the radiopharmaceutical for binding sites for example can lead to false negative results. Drugs that accelerate the metabolism of the radiopharmaceutical can have a positive impact (i.e. speeding its clearance or, if repeating image is needed, a negative impact. In some cases, for example in cardiac image among patients taking doxirubacin, these interactions may have a therapeutic benefit. The incidence of drug-radiopharmaceuticals adverse reactions is unknown, since they may not be reported or even recognized. Here,we compiled the medical literature, using the criteria of a systematic review established by the Cochrane Collaboration, on pharmaceutical-drug interactions to provide a summary of documented interactions by organ system and radiopharmaceuticals. The purpose is to provide a reference on drug interactions that could inform the nuclear medicine staff in their daily routine. Efforts to increase adverse event reporting, and ideally consolidate reports worldwide, can provide a critically needed resource for prevention of drug-radiopharmaceuticals interactions.Os radiofármacos desempenham função crítica na medicina moderna, primariamente para fins diagnósticos, mas também no monitoramento da progressão de doenças assim como na avaliação de respostas ao tratamento. O uso da tecnologia por imagem tem crescido e conseqüentemente as prescrições de medicamentos (radiofármacos em especial com esse propósito. Este fato, aumenta o risco de interações entre medicamentos e radiofármacos. Interações que podem ter um impacto na

Prolonged Drug-Drug Interaction between Terbinafine and Perphenazine.

Science.gov (United States)

Park, Young-Min

2012-12-01

I report here an elderly woman receiving perphenazine together with terbinafine. After 1 week of terbinafine treatment she experienced extrapyramidal symptoms and, in particular, akathisia. Her symptoms did not disappear for 6 weeks, and so at 2 weeks prior to this most recent admission she had stopped taking terbinafine. However, these symptoms persisted for 3 weeks after discontinuing terbinafine. It is well known that terbinafine inhibits CYP2D6 and that perphenazine is metabolized mainly by CYP2D6. Thus, when terbinafine and perphenazine are coadministrated, the subsequent increase in the concentration of perphenazine may induce extrapyramidal symptoms. Thus, terbinafine therapy may be associated with the induction and persistence of extrapyramidal symptoms, including akathisia. This case report emphasizes the importance of monitoring drug-drug interactions in patients undergoing terbinafine and perphenazine therapy.

Human serum albumin unfolding pathway upon drug binding: A thermodynamic and spectroscopic description

International Nuclear Information System (INIS)

Cheema, Mohammad Arif; Taboada, Pablo; Barbosa, Silvia; Juarez, Josue; Gutierrez-Pichel, Manuel; Siddiq, Mohammad; Mosquera, Victor

2009-01-01

The interest on phenothiazine drugs has been increased during last years due to their proved utility in the treatment of several diseases and biomolecular processes. In the present work, the binding of the amphiphilic phenothiazines promazine and thioridazine hydrochlorides to the carrier protein human serum albumin (HSA) has been examined by ζ-potential, isothermal titration calorimetry (ITC), fluorescence and circular dichorism (CD) spectroscopies, and dynamic light scattering (DLS) at physiological pH with the aim of analyzing the role of the different interactions in the drug complexation process with this protein. The ζ-potential results were used to check the existence of complexation. This is confirmed by a progressive screening of the protein charge up to a reversal point as a consequence of drug binding. On the other hand, binding causes alterations on the tertiary and secondary structures of the protein, which were observed by fluorescence and CD spectroscopies, involving a two-step, three-state transition. The thermodynamics of the binding process was derived from ITC results. The binding enthalpies were negative, which reveal the existence of electrostatic interactions between protein and drug molecules. In addition, increases in entropy are consistent with the predominance of hydrophobic interactions. Two different classes of binding sites were detected, viz. Binding to the first class of binding sites is dominated by an enthalpic contribution due to electrostatic interactions whereas binding to a second class of binding sites is dominated by hydrophobic bonding. In the light of these results, protein conformational change resembles the acid-induced denaturation of HSA with accumulation of an intermediate state. Binding isotherms were derived from microcalorimetric results by using a theoretical model based on the Langmuir isotherm. On the other hand, the population distribution of the different species in solution and their sizes were determined

Human serum albumin unfolding pathway upon drug binding: A thermodynamic and spectroscopic description

Energy Technology Data Exchange (ETDEWEB)

Cheema, Mohammad Arif [Grupo de Fisica de Coloides y Polimeros, Departamento de Fisica de la Materia Condensada, Facultad de Fisica, Universidad de Santiago de Compostela, E-15782, Santiago de Compostela (Spain); Department of Chemistry, Quaid-i-Azam University, Islamabad 45320 (Pakistan); Taboada, Pablo [Grupo de Fisica de Coloides y Polimeros, Departamento de Fisica de la Materia Condensada, Facultad de Fisica, Universidad de Santiago de Compostela, E-15782, Santiago de Compostela (Spain); Department of Chemistry, Quaid-i-Azam University, Islamabad 45320 (Pakistan)], E-mail: pablo.taboada@usc.es; Barbosa, Silvia; Juarez, Josue; Gutierrez-Pichel, Manuel [Grupo de Fisica de Coloides y Polimeros, Departamento de Fisica de la Materia Condensada, Facultad de Fisica, Universidad de Santiago de Compostela, E-15782, Santiago de Compostela (Spain); Department of Chemistry, Quaid-i-Azam University, Islamabad 45320 (Pakistan); Siddiq, Mohammad [Department of Chemistry, Quaid-i-Azam University, Islamabad 45320 (Pakistan); Mosquera, Victor [Grupo de Fisica de Coloides y Polimeros, Departamento de Fisica de la Materia Condensada, Facultad de Fisica, Universidad de Santiago de Compostela, E-15782, Santiago de Compostela (Spain); Department of Chemistry, Quaid-i-Azam University, Islamabad 45320 (Pakistan)

2009-04-15

The interest on phenothiazine drugs has been increased during last years due to their proved utility in the treatment of several diseases and biomolecular processes. In the present work, the binding of the amphiphilic phenothiazines promazine and thioridazine hydrochlorides to the carrier protein human serum albumin (HSA) has been examined by {zeta}-potential, isothermal titration calorimetry (ITC), fluorescence and circular dichorism (CD) spectroscopies, and dynamic light scattering (DLS) at physiological pH with the aim of analyzing the role of the different interactions in the drug complexation process with this protein. The {zeta}-potential results were used to check the existence of complexation. This is confirmed by a progressive screening of the protein charge up to a reversal point as a consequence of drug binding. On the other hand, binding causes alterations on the tertiary and secondary structures of the protein, which were observed by fluorescence and CD spectroscopies, involving a two-step, three-state transition. The thermodynamics of the binding process was derived from ITC results. The binding enthalpies were negative, which reveal the existence of electrostatic interactions between protein and drug molecules. In addition, increases in entropy are consistent with the predominance of hydrophobic interactions. Two different classes of binding sites were detected, viz. Binding to the first class of binding sites is dominated by an enthalpic contribution due to electrostatic interactions whereas binding to a second class of binding sites is dominated by hydrophobic bonding. In the light of these results, protein conformational change resembles the acid-induced denaturation of HSA with accumulation of an intermediate state. Binding isotherms were derived from microcalorimetric results by using a theoretical model based on the Langmuir isotherm. On the other hand, the population distribution of the different species in solution and their sizes were

Radiosensitivity of drug-resistant human tumour xenografts

International Nuclear Information System (INIS)

Mattern, J.; Bak, M. Jr.; Volm, M.; Hoever, K.H.

1989-01-01

The radiosensitivity of three drug-resistant sublines of a human epidermoid lung carcinoma growing as xenografts in nude mice was investigated. Drug resistance to vincristine, actinomycin D and cisplatin was developed in vivo by repeated drug treatment. It was found that all three drug-resistant tumour lines were not cross-resistant to irradiation. (orig.) [de

Drug-Nutrition Interactions in Older People

NARCIS (Netherlands)

Orten-Luiten, van A.C.; Janse, A.; Witkamp, R.

2016-01-01

Although both malnutrition and polypharmacy in elderly populations are relevant clinical issues, relatively little is known about their mutual relationship through drug-nutrition interactions (DNIs). To address this knowledge gap, DNIs are discussed, captured in a framework of five classes: the

Bliss and Loewe interaction analyses of clinically relevant drug combinations in human colon cancer cell lines reveal complex patterns of synergy and antagonism.

Science.gov (United States)

Kashif, Muhammad; Andersson, Claes; Mansoori, Sharmineh; Larsson, Rolf; Nygren, Peter; Gustafsson, Mats G

2017-11-28

We analyzed survival effects for 15 different pairs of clinically relevant anti-cancer drugs in three iso-genic pairs of human colorectal cancer carcinoma cell lines, by applying for the first time our novel software (R package) called COMBIA. In our experiments iso-genic pairs of cell lines were used, differing only with respect to a single clinically important KRAS or BRAF mutation. Frequently, concentration dependent but mutation independent joint Bliss and Loewe synergy/antagonism was found statistically significant. Four combinations were found synergistic/antagonistic specifically to the parental (harboring KRAS or BRAF mutation) cell line of the corresponding iso-genic cell lines pair. COMBIA offers considerable improvements over established software for synergy analysis such as MacSynergy™ II as it includes both Bliss (independence) and Loewe (additivity) analyses, together with a tailored non-parametric statistical analysis employing heteroscedasticity, controlled resampling, and global (omnibus) testing. In many cases Loewe analyses found significant synergistic as well as antagonistic effects in a cell line at different concentrations of a tested drug combination. By contrast, Bliss analysis found only one type of significant effect per cell line. In conclusion, the integrated Bliss and Loewe interaction analysis based on non-parametric statistics may provide more robust interaction analyses and reveal complex patterns of synergy and antagonism.

Clinical assessment of drug-drug interactions of tasimelteon, a novel dual melatonin receptor agonist.

Science.gov (United States)

Ogilvie, Brian W; Torres, Rosarelis; Dressman, Marlene A; Kramer, William G; Baroldi, Paolo

2015-09-01

Tasimelteon ([1R-trans]-N-[(2-[2,3-dihydro-4-benzofuranyl] cyclopropyl) methyl] propanamide), a novel dual melatonin receptor agonist that demonstrates specificity and high affinity for melatonin receptor types 1 and 2 (MT1 and MT2 receptors), is the first treatment approved by the US Food and Drug Administration for Non-24-Hour Sleep-Wake Disorder. Tasimelteon is rapidly absorbed, with a mean absolute bioavailability of approximately 38%, and is extensively metabolized primarily by oxidation at multiple sites, mainly by cytochrome P450 (CYP) 1A2 and CYP3A4/5, as initially demonstrated by in vitro studies and confirmed by the results of clinical drug-drug interactions presented here. The effects of strong inhibitors and moderate or strong inducers of CYP1A2 and CYP3A4/5 on the pharmacokinetics of tasimelteon were evaluated in humans. Coadministration with fluvoxamine resulted in an approximately 6.5-fold increase in tasimelteon's area under the curve (AUC), whereas cigarette smoking decreased tasimelteon's exposure by approximately 40%. Coadministration with ketoconazole resulted in an approximately 54% increase in tasimelteon's AUC, whereas rifampin pretreatment resulted in a decrease in tasimelteon's exposure of approximately 89%. © 2015 The Authors. The Journal of Clinical Pharmacology published by Wiley Periodicals, Inc. on behalf of American College of Clinical Pharmacology.

Drug-drug interactions in patients treated for cancer : a prospective study on clinical interventions

NARCIS (Netherlands)

van Leeuwen, R. W. F.; Jansman, F. G. A.; van den Bemt, P. M. L. A.; de Man, F.; Piran, F.; Vincenten, I.; Jager, A.; Rijneveld, A. W.; Brugma, J. D.; Mathijssen, R. H. J.; van Gelder, T.

Background: Drug-drug interactions (DDIs) are of major concern in oncology, since cancer patients typically take many concomitant medications. Retrospective studies have been conducted to determine the prevalence of DDIs. However, prospective studies on DDIs needing interventions in cancer patients

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

Possible drug–drug interaction in dogs and cats resulted from alteration in drug metabolism: A mini review

Directory of Open Access Journals (Sweden)

Kazuaki Sasaki

2015-05-01

Full Text Available Pharmacokinetic drug–drug interactions (in particular at metabolism may result in fatal adverse effects in some cases. This basic information, therefore, is needed for drug therapy even in veterinary medicine, as multidrug therapy is not rare in canines and felines. The aim of this review was focused on possible drug–drug interactions in dogs and cats. The interaction includes enzyme induction by phenobarbital, enzyme inhibition by ketoconazole and fluoroquinolones, and down-regulation of enzymes by dexamethasone. A final conclusion based upon the available literatures and author’s experience is given at the end of the review.

Detection of First-Line Drug Resistance Mutations and Drug-Protein Interaction Dynamics from Tuberculosis Patients in South India.

Science.gov (United States)

Nachappa, Somanna Ajjamada; Neelambike, Sumana M; Amruthavalli, Chokkanna; Ramachandra, Nallur B

2018-05-01

Diagnosis of drug-resistant tuberculosis predominantly relies on culture-based drug susceptibility testing, which take weeks to produce a result and a more time-efficient alternative method is multiplex allele-specific PCR (MAS-PCR). Also, understanding the role of mutations in causing resistance helps better drug designing. To evaluate the ability of MAS-PCR in the detection of drug resistance and to understand the mechanism of interaction of drugs with mutant proteins in Mycobacterium tuberculosis. Detection of drug-resistant mutations using MAS-PCR and validation through DNA sequencing. MAS-PCR targeted five loci on three genes, katG 315 and inhA -15 for the drug isoniazid (INH), and rpoB 516, 526, and 531 for rifampicin (RIF). Furthermore, the sequence data were analyzed to study the effect on interaction of the anti-TB drug molecule with the target protein using in silico docking. We identified drug-resistant mutations in 8 out of 114 isolates with 2 of them as multidrug-resistant TB using MAS-PCR. DNA sequencing confirmed only six of these, recording a sensitivity of 85.7% and specificity of 99.3% for MAS-PCR. Molecular docking showed estimated free energy of binding (ΔG) being higher for RIF binding with RpoB S531L mutant. Codon 315 in KatG does not directly interact with INH but blocks the drug access to active site. We propose DNA sequencing-based drug resistance detection for TB, which is more accurate than MAS-PCR. Understanding the action of resistant mutations in disrupting the normal drug-protein interaction aids in designing effective drug alternatives.

Study of interaction between antiobesity and hypolipidemic drugs ...

African Journals Online (AJOL)

PURPOSE: To explore the interaction between antiobesity drug, topiramate, and hypolipidemic drug, atorvastatin, in rats. METHODS: Obesity was induced in Wistar albino rats by administering cafeteria diet (CD) for 40 days and divided into 5 groups. While one group served as control, each other group received either ...

Simulating human behavior for national security human interactions.

Energy Technology Data Exchange (ETDEWEB)

Bernard, Michael Lewis; Hart, Dereck H.; Verzi, Stephen J.; Glickman, Matthew R.; Wolfenbarger, Paul R.; Xavier, Patrick Gordon

2007-01-01

This 3-year research and development effort focused on what we believe is a significant technical gap in existing modeling and simulation capabilities: the representation of plausible human cognition and behaviors within a dynamic, simulated environment. Specifically, the intent of the ''Simulating Human Behavior for National Security Human Interactions'' project was to demonstrate initial simulated human modeling capability that realistically represents intra- and inter-group interaction behaviors between simulated humans and human-controlled avatars as they respond to their environment. Significant process was made towards simulating human behaviors through the development of a framework that produces realistic characteristics and movement. The simulated humans were created from models designed to be psychologically plausible by being based on robust psychological research and theory. Progress was also made towards enhancing Sandia National Laboratories existing cognitive models to support culturally plausible behaviors that are important in representing group interactions. These models were implemented in the modular, interoperable, and commercially supported Umbra{reg_sign} simulation framework.

Simultaneous Assessment of Transporter-Mediated Drug-Drug Interactions Using a Probe Drug Cocktail in Cynomolgus Monkey.

Science.gov (United States)

Kosa, Rachel E; Lazzaro, Sarah; Bi, Yi-An; Tierney, Brendan; Gates, Dana; Modi, Sweta; Costales, Chester; Rodrigues, A David; Tremaine, Larry M; Varma, Manthena V

2018-06-07

We aim to establish an in vivo preclinical model to enable simultaneous assessment of inhibition potential of an investigational drug on clinically relevant drug transporters, organic anion transporting polypeptide (OATP)1B, breast cancer resistance protein (BCRP), P-glycoprotein (P-gp) and organic anion transporter (OAT)3. Pharmacokinetics of substrate cocktail consisting of pitavastatin (OATP1B substrate), rosuvastatin (OATP1B/BCRP/OAT3), sulfasalazine (BCRP) and talinolol (P-gp) were obtained in cynomolgus monkey - alone or in combination with transporter inhibitors. Single dose rifampicin (30 mg/kg) significantly (pdrugs, with a marked effect on pitavastatin and rosuvastatin (AUC ratio ~21-39). Elacridar, BCRP/P-gp inhibitor, increased the AUC of sulfasalazine, talinolol, as well as rosuvastatin and pitavastatin. An OAT1/3 inhibitor (probenecid) significantly (pdrug-drug interaction risk assessment, before advancing a new molecular entity into clinical development, as well as providing mechanistic insights on transporter-mediated interactions. The American Society for Pharmacology and Experimental Therapeutics.

Drug-drug interaction and doping, part 1: an in vitro study on the effect of non-prohibited drugs on the phase I metabolic profile of toremifene.

Science.gov (United States)

Mazzarino, Monica; de la Torre, Xavier; Fiacco, Ilaria; Palermo, Amelia; Botrè, Francesco

2014-05-01

The present study was designed to provide preliminary information on the potential impact of metabolic drug-drug interaction on the effectiveness of doping control strategies currently followed by the anti-doping laboratories to detect the intake of banned agents. In vitro assays based on the use of human liver microsomes and recombinant CYP isoforms were designed and performed to characterize the phase I metabolic profile of the prohibited agent toremifene, selected as a prototype drug of the class of selective oestrogen receptor modulators, both in the absence and in the presence of medicaments (fluconazole, ketoconazole, itraconazole, miconazole, cimetidine, ranitidine, fluoxetine, paroxetine, nefazodone) not included in the World Anti-Doping Agency list of prohibited substances and methods and frequently administered to athletes. The results show that the in vitro model developed in this study was adequate to simulate the in vivo metabolism of toremifene, confirming the results obtained in previous studies. Furthermore, our data also show that ketoconazole, itraconazole, miconazole and nefazodone cause a marked modification in the production of the metabolic products (i.e. hydroxylated and carboxylated metabolites) normally selected by the anti-doping laboratories as target analytes to detect toremifene intake; moderate variations were registered in the presence of fluconazole, paroxetine and fluoxetine; while no significant modifications were measured in the presence of ranitidine and cimetidine. This evidence imposes that the potential effect of drug-drug interactions is duly taken into account in anti-doping analysis, also for a broader significance of the analytical results. Copyright © 2014 John Wiley & Sons, Ltd.

Drug-Drug Interaction Extraction via Convolutional Neural Networks

Directory of Open Access Journals (Sweden)

Shengyu Liu

2016-01-01

Full Text Available Drug-drug interaction (DDI extraction as a typical relation extraction task in natural language processing (NLP has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM with a large number of manually defined features. Recently, convolutional neural networks (CNN, a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.

Contrast media: interactions with other drugs and clinical tests

International Nuclear Information System (INIS)

Morcos, Sameh K.; Exley, C.M.; Thomsen, Henrik S.

2005-01-01

Many patients with multiple medical problems who are receiving a variety of drugs are investigated with imaging techniques which require intravascular contrast media. The Contrast Media Safety Committee of the European Society of Urogenital Radiology therefore decided to review the literature and to draw up simple guidelines on interactions between contrast media and other drugs. An extensive literature search was carried out and summarized in a report. Based on the available information, simple guidelines have been drawn up. The report and guidelines were discussed at the 11th European Symposium on Urogenital Radiology in Santiago de Compostela. Contrast media may interact with other drugs, and may interfere with isotope studies and biochemical measurements. Awareness of the patient drug history is important to avoid potential hazards. Simple guidelines are presented. (orig.)

iNR-Drug: predicting the interaction of drugs with nuclear receptors in cellular networking.

Science.gov (United States)

Fan, Yue-Nong; Xiao, Xuan; Min, Jian-Liang; Chou, Kuo-Chen

2014-03-19

Nuclear receptors (NRs) are closely associated with various major diseases such as cancer, diabetes, inflammatory disease, and osteoporosis. Therefore, NRs have become a frequent target for drug development. During the process of developing drugs against these diseases by targeting NRs, we are often facing a problem: Given a NR and chemical compound, can we identify whether they are really in interaction with each other in a cell? To address this problem, a predictor called "iNR-Drug" was developed. In the predictor, the drug compound concerned was formulated by a 256-D (dimensional) vector derived from its molecular fingerprint, and the NR by a 500-D vector formed by incorporating its sequential evolution information and physicochemical features into the general form of pseudo amino acid composition, and the prediction engine was operated by the SVM (support vector machine) algorithm. Compared with the existing prediction methods in this area, iNR-Drug not only can yield a higher success rate, but is also featured by a user-friendly web-server established at http://www.jci-bioinfo.cn/iNR-Drug/, which is particularly useful for most experimental scientists to obtain their desired data in a timely manner. It is anticipated that the iNR-Drug server may become a useful high throughput tool for both basic research and drug development, and that the current approach may be easily extended to study the interactions of drug with other targets as well.

Cognitive enhancers (nootropics). Part 2: drugs interacting with enzymes.

Science.gov (United States)

Froestl, Wolfgang; Muhs, Andreas; Pfeifer, Andrea

2013-01-01

Cognitive enhancers (nootropics) are drugs to treat cognition deficits in patients suffering from Alzheimer's disease, schizophrenia, stroke, attention deficit hyperactivity disorder, or aging. Cognition refers to a capacity for information processing, applying knowledge, and changing preferences. It involves memory, attention, executive functions, perception, language, and psychomotor functions. The term nootropics was coined in 1972 when memory enhancing properties of piracetam were observed in clinical trials. In the meantime, hundreds of drugs have been evaluated in clinical trials or in preclinical experiments. To classify the compounds, a concept is proposed assigning drugs to 19 categories according to their mechanism(s) of action, in particular drugs interacting with receptors, enzymes, ion channels, nerve growth factors, re-uptake transporters, antioxidants, metal chelators, and disease modifying drugs meaning small molecules, vaccines, and monoclonal antibodies interacting with amyloid-β and tau. For drugs whose mechanism of action is not known, they are either classified according to structure, e.g., peptides, or their origin, e.g., natural products. This review covers the evolution of research in this field over the last 25 years.

Cognitive enhancers (nootropics). Part 1: drugs interacting with receptors.

Science.gov (United States)

Froestl, Wolfgang; Muhs, Andreas; Pfeifer, Andrea

2012-01-01

Cognitive enhancers (nootropics) are drugs to treat cognition deficits in patients suffering from Alzheimer's disease, schizophrenia, stroke, attention deficit hyperactivity disorder, or aging. Cognition refers to a capacity for information processing, applying knowledge, and changing preferences. It involves memory, attention, executive functions, perception, language, and psychomotor functions. The term nootropics was coined in 1972 when memory enhancing properties of piracetam were observed in clinical trials. In the meantime, hundreds of drugs have been evaluated in clinical trials or in preclinical experiments. To classify the compounds, a concept is proposed assigning drugs to 18 categories according to their mechanism(s) of action, in particular drugs interacting with receptors, enzymes, ion channels, nerve growth factors, re-uptake transporters, antioxidants, metal chelators, and disease-modifying drugs meaning small molecules, vaccines, and monoclonal antibodies interacting with amyloid-β and tau. For drugs, whose mechanism of action is not known, they are either classified according to structure, e.g., peptides, or their origin, e.g., natural products. The review covers the evolution of research in this field over the last 25 years.

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.

Consensus-based evaluation of clinical significance and management of anticancer drug interactions

NARCIS (Netherlands)

Jansman, F.G.A.; Reyners, A.K.L.; van Roon, E.N.; Smorenburg, C.H.; Helgason, H.H.; le Comte, M.; Wensveen, B.M.; van den Tweel, A.M.A.; de Blois, M.; Kwee, W.; Kerremans, A.L.; Brouwers, J.R.B.J.

Background: Anticancer drug interactions can affect the efficacy and toxicity of anticancer treatment and that of the interacting drugs. However, information on the significance, prevention, and management of these interactions is currently lacking. Objective: The purpose of this study was to assess

Target mediated drug disposition with drug-drug interaction, Part II: competitive and uncompetitive cases.

Science.gov (United States)

Koch, Gilbert; Jusko, William J; Schropp, Johannes

2017-02-01

We present competitive and uncompetitive drug-drug interaction (DDI) with target mediated drug disposition (TMDD) equations and investigate their pharmacokinetic DDI properties. For application of TMDD models, quasi-equilibrium (QE) or quasi-steady state (QSS) approximations are necessary to reduce the number of parameters. To realize those approximations of DDI TMDD models, we derive an ordinary differential equation (ODE) representation formulated in free concentration and free receptor variables. This ODE formulation can be straightforward implemented in typical PKPD software without solving any non-linear equation system arising from the QE or QSS approximation of the rapid binding assumptions. This manuscript is the second in a series to introduce and investigate DDI TMDD models and to apply the QE or QSS approximation.

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

Directory of Open Access Journals (Sweden)

R Pignatello

2011-01-01

Full Text Available Contact with many different biological membranes goes along the destiny of a drug after its systemic administration. From the circulating macrophage cells to the vessel endothelium, to more complex absorption barriers, the interaction of a biomolecule with these membranes largely affects its rate and time of biodistribution in the body and at the target sites. Therefore, investigating the phenomena occurring on the cell membranes, as well as their different interaction with drugs in the physiological or pathological conditions, is important to exploit the molecular basis of many diseases and to identify new potential therapeutic strategies. Of course, the complexity of the structure and functions of biological and cell membranes, has pushed researchers toward the proposition and validation of simpler two- and three-dimensional membrane models, whose utility and drawbacks will be discussed. This review also describes the analytical methods used to look at the interactions among bioactive compounds with biological membrane models, with a particular accent on the calorimetric techniques. These studies can be considered as a powerful tool for medicinal chemistry and pharmaceutical technology, in the steps of designing new drugs and optimizing the activity and safety profile of compounds already used in the therapy.

Analysis of Drugs Interaction among Pediatric Inpatients at Hospital in Palu

Directory of Open Access Journals (Sweden)

Akhmed G. Sjahadat

2013-12-01

Full Text Available We performed drug interaction analyses in the pediatric inpatient unit at one of hospitals in Palu. In this study, those analysesstudy are important to prevent childhood morbidity, mortality and to improve patient’s safety. By using a cross-sectional descriptive study, we collected retrospective data from January until December 2012. We included patients at age of 0- 18 years old who were hospitalized during 2012 and received two or more drugs from a prescription sheet. In particular, we excluded pediatric inpatients in emergency and intensive care units who received topical medications (e.g., ointment, creams, eye drops, ear drops, and nasal drops. Each drug was analyzed by using Drug.Com software. In total, we minor interactions (44.78%. We found several drug interactions in the combination of rifampicin-isoniazid, dexamethasone-ibuprofen, acetaminophen-isoniazid, gentamicin-cefotaxime-ceftriaxone and diazepam- dexamethasone.

Detection of Potential Drug-Drug Interactions for Outpatients across Hospitals

Directory of Open Access Journals (Sweden)

Yu-Ting Yeh

2014-01-01

Full Text Available The National Health Insurance Administration (NHIA has adopted smart cards (or NHI-IC cards as health cards to carry patients’ medication histories across hospitals in Taiwan. The aims of this study are to enhance a computerized physician order entry system to support drug-drug interaction (DDI checking based on a patient’s medication history stored in his/her NHI-IC card. For performance evaluation, we developed a transaction tracking log to keep track of every operation on NHI-IC cards. Based on analysis of the transaction tracking log from 1 August to 31 October 2007, physicians read patients’ NHI-IC cards in 71.01% (8,246 of patient visits; 33.02% (2,723 of the card reads showed at least one medicine currently being taken by the patient, 82.94% of which were prescribed during the last visit. Among 10,036 issued prescriptions, seven prescriptions (0.09% contained at least one drug item that might interact with the currently-taken medicines stored in NHI-IC cards and triggered pop-up alerts. This study showed that the capacity of an NHI-IC card is adequate to support DDI checking across hospitals. Thus, the enhanced computerized physician order entry (CPOE system can support better DDI checking when physicians are making prescriptions and provide safer medication care, particularly for patients who receive medication care from different hospitals.

Detection of potential drug-drug interactions for outpatients across hospitals.

Science.gov (United States)

Yeh, Yu-Ting; Hsu, Min-Hui; Chen, Chien-Yuan; Lo, Yu-Sheng; Liu, Chien-Tsai

2014-01-27

The National Health Insurance Administration (NHIA) has adopted smart cards (or NHI-IC cards) as health cards to carry patients' medication histories across hospitals in Taiwan. The aims of this study are to enhance a computerized physician order entry system to support drug-drug interaction (DDI) checking based on a patient's medication history stored in his/her NHI-IC card. For performance evaluation, we developed a transaction tracking log to keep track of every operation on NHI-IC cards. Based on analysis of the transaction tracking log from 1 August to 31 October 2007, physicians read patients' NHI-IC cards in 71.01% (8,246) of patient visits; 33.02% (2,723) of the card reads showed at least one medicine currently being taken by the patient, 82.94% of which were prescribed during the last visit. Among 10,036 issued prescriptions, seven prescriptions (0.09%) contained at least one drug item that might interact with the currently-taken medicines stored in NHI-IC cards and triggered pop-up alerts. This study showed that the capacity of an NHI-IC card is adequate to support DDI checking across hospitals. Thus, the enhanced computerized physician order entry (CPOE) system can support better DDI checking when physicians are making prescriptions and provide safer medication care, particularly for patients who receive medication care from different hospitals.

People who use drugs, HIV, and human rights.

Science.gov (United States)

Jürgens, Ralf; Csete, Joanne; Amon, Joseph J; Baral, Stefan; Beyrer, Chris

2010-08-07

We reviewed evidence from more than 900 studies and reports on the link between human rights abuses experienced by people who use drugs and vulnerability to HIV infection and access to services. Published work documents widespread abuses of human rights, which increase vulnerability to HIV infection and negatively affect delivery of HIV programmes. These abuses include denial of harm-reduction services, discriminatory access to antiretroviral therapy, abusive law enforcement practices, and coercion in the guise of treatment for drug dependence. Protection of the human rights of people who use drugs therefore is important not only because their rights must be respected, protected, and fulfilled, but also because it is an essential precondition to improving the health of people who use drugs. Rights-based responses to HIV and drug use have had good outcomes where they have been implemented, and they should be replicated in other countries. Copyright 2010 Elsevier Ltd. All rights reserved.

Recombinant human serum albumin hydrogel as a novel drug delivery vehicle

International Nuclear Information System (INIS)

Hirose, Masaaki; Tachibana, Akira; Tanabe, Toshizumi

2010-01-01

Serum albumin acts as a physiological carrier for various compounds including drugs. A hydrogel consisting of recombinant human serum albumin (rHSA) was prepared to take advantage of drug binding ability of albumin for a sustained drug release carrier. The hydrogel was prepared by mixing rHSA and dithiothreitol and casted to a polystyrene mold. Hydrogel formation was thought to occur through the intermolecular interaction of the hydrophobic groups by protein denaturation. The release of sodium benzoate and salicylic acid from the hydrogel completed in 2 h, while warfarin release continued for 24 h. The total amounts of the drugs released from 100 mg of 15 and 5% rHSA hydrogel were 2.3 and 1.4 μmol for warfarin, 1.4 and 1.1 μmol for salicylic acid and 0.9 and 0.9 μmol for sodium benzoate. These results reflected the order of the binding ability of drugs for intact albumin indicating that the drug binding ability of HSA still remained after the hydrogel formation. However, fibroblast cells attached and proliferated well on the hydrogel, indicating that denaturation of rHSA proceeded to the extent to allow the cell attachment. The present rHSA hydrogel might be suitable for a sustained release carrier of drugs having affinity for albumin.

Recombinant human serum albumin hydrogel as a novel drug delivery vehicle

Energy Technology Data Exchange (ETDEWEB)

Hirose, Masaaki, E-mail: Hirose.Masaaki@mh.mt-pharma.co.jp [Advanced Medical Research Laboratory, Research Division, Mitsubishi Tanabe Pharma Corporation, 3-16-89 Kashima, Yodogawa-ku, Osaka 532-8505 (Japan); Department of Applied Chemistry and Bioengineering, Graduate School of Engineering, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585 (Japan); Tachibana, Akira; Tanabe, Toshizumi [Department of Applied Chemistry and Bioengineering, Graduate School of Engineering, Osaka City University, 3-3-138 Sugimoto, Sumiyoshi-ku, Osaka 558-8585 (Japan)

2010-06-15

Serum albumin acts as a physiological carrier for various compounds including drugs. A hydrogel consisting of recombinant human serum albumin (rHSA) was prepared to take advantage of drug binding ability of albumin for a sustained drug release carrier. The hydrogel was prepared by mixing rHSA and dithiothreitol and casted to a polystyrene mold. Hydrogel formation was thought to occur through the intermolecular interaction of the hydrophobic groups by protein denaturation. The release of sodium benzoate and salicylic acid from the hydrogel completed in 2 h, while warfarin release continued for 24 h. The total amounts of the drugs released from 100 mg of 15 and 5% rHSA hydrogel were 2.3 and 1.4 {mu}mol for warfarin, 1.4 and 1.1 {mu}mol for salicylic acid and 0.9 and 0.9 {mu}mol for sodium benzoate. These results reflected the order of the binding ability of drugs for intact albumin indicating that the drug binding ability of HSA still remained after the hydrogel formation. However, fibroblast cells attached and proliferated well on the hydrogel, indicating that denaturation of rHSA proceeded to the extent to allow the cell attachment. The present rHSA hydrogel might be suitable for a sustained release carrier of drugs having affinity for albumin.

Current status of prediction of drug disposition and toxicity in humans using chimeric mice with humanized liver.

Science.gov (United States)

Kitamura, Shigeyuki; Sugihara, Kazumi

2014-01-01

1. Human-chimeric mice with humanized liver have been constructed by transplantation of human hepatocytes into several types of mice having genetic modifications that injure endogenous liver cells. Here, we focus on liver urokinase-type plasminogen activator-transgenic severe combined immunodeficiency (uPA/SCID) mice, which are the most widely used human-chimeric mice. Studies so far indicate that drug metabolism, drug transport, pharmacological effects and toxicological action in these mice are broadly similar to those in humans. 2. Expression of various drug-metabolizing enzymes is known to be different between humans and rodents. However, the expression pattern of cytochrome P450, aldehyde oxidase and phase II enzymes in the liver of human-chimeric mice resembles that in humans, not that in the host mice. 3. Metabolism of various drugs, including S-warfarin, zaleplon, ibuprofen, naproxen, coumarin, troglitazone and midazolam, in human-chimeric mice is mediated by human drug-metabolizing enzymes, not by host mouse enzymes, and thus resembles that in humans. 4. Pharmacological and toxicological effects of various drugs in human-chimeric mice are also similar to those in humans. 5. The current consensus is that chimeric mice with humanized liver are useful to predict drug metabolism catalyzed by cytochrome P450, aldehyde oxidase and phase II enzymes in humans in vivo and in vitro. Some remaining issues are discussed in this review.

Predicting Drug-Target Interactions Based on Small Positive Samples.

Science.gov (United States)

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

Human drug metabolism: an introduction

National Research Council Canada - National Science Library

Coleman, Michael D

2010-01-01

Human Drug Metabolism, An Introduction, Second Edition provides an accessible introduction to the subject and will be particularly invaluable to those who already have some understanding of the life sciences...

Interaction in the Research Interview and Drug-Related Disclosures among Respondents.

Science.gov (United States)

Myers, Vincent

1979-01-01

Interviewers and respondents judged interview interactions during a survey of drug-related sentiments. Pronounced variability in interviewer-respondent judgements occurred in unanticipated ways related to gender, role, and ethnicity of participants. Positive interaction yielded different respondent cognitions and reports of illicit drug ingestion…

In vitro effects of the anti-Alzheimer drug memantine on the human erythrocyte membrane and molecular models

International Nuclear Information System (INIS)

Zambrano, Pablo; Suwalsky, Mario; Villena, Fernando; Jemiola-Rzeminska, Malgorzata; Strzalka, Kazimierz

2017-01-01

Memantine is a NMDA antagonist receptor clinically used for treating Alzheimer's disease. NMDA receptors are present in the human neurons and erythrocyte membranes. The aim of the present study was to investigate the effects of memantine on human erythrocytes. With this purpose, the drug was developed to in vitro interact with human red cells and bilayers built-up of dimyristoylphosphatidylcholine (DMPC) and dimyristoylphosphatidylethanolamine (DMPE). The latter represent lipids respectively present in both outer and inner monolayers of the red cell membrane. Results obtained by scanning electron microscopy (SEM) showed that memantine changed the normal biconcave shape of red cells to cup-shaped stomatocytes. According to the bilayer-couple hypothesis the drug intercalated into the inner monolayer of the erythrocyte membrane. Experimental results obtained by X-ray diffraction on multibilayers of DMPC and DMPE, and by differential scanning calorimetry on multilamellar vesicles indicated that memantine preferentially interacted with DMPC in a concentration-dependent manner. Thus, it can be concluded that in the low therapeutic plasma concentration of circa 1 μM memantine is located in NMDA receptor channel without affecting the erythrocyte shape. However, at higher concentrations, once the receptors became saturated excess of memantine molecules (20 μM) would interact with phosphoinositide lipids present in the inner monolayer of the erythrocyte membrane inducing the formation of stomatocytes. However, 40–50 μM memantine was required to interact with isolated phosphatidylcholine bilayers. - Highlights: • The interaction of memantine with human erythrocytes and lipid bilayers were assessed. • Memantine induced morphological changes to human erythrocytes. • Memantine interacted with classes of phospholipids present in the erythrocyte membrane. • Results support the hypothesis that memantine interacts with NMDA receptors.

The Self-Organization of Human Interaction

DEFF Research Database (Denmark)

Dale, Rick; Fusaroli, Riccardo; Duran, Nicholas

2013-01-01

We describe a “centipede’s dilemma” that faces the sciences of human interaction. Research on human interaction has been involved in extensive theoretical debate, although the vast majority of research tends to focus on a small set of human behaviors, cognitive processes, and interactive contexts...

Measuring Multimodal Synchrony for Human-Computer Interaction

NARCIS (Netherlands)

Reidsma, Dennis; Nijholt, Antinus; Tschacher, Wolfgang; Ramseyer, Fabian; Sourin, A.

2010-01-01

Nonverbal synchrony is an important and natural element in human-human interaction. It can also play various roles in human-computer interaction. In particular this is the case in the interaction between humans and the virtual humans that inhabit our cyberworlds. Virtual humans need to adapt their

Pharmacogenomics of the human ABC transporter ABCG2: from functional evaluation to drug molecular design

Science.gov (United States)

Ishikawa, Toshihisa; Tamura, Ai; Saito, Hikaru; Wakabayashi, Kanako; Nakagawa, Hiroshi

2005-10-01

In the post-genome-sequencing era, emerging genomic technologies are shifting the paradigm for drug discovery and development. Nevertheless, drug discovery and development still remain high-risk and high-stakes ventures with long and costly timelines. Indeed, the attrition of drug candidates in preclinical and development stages is a major problem in drug design. For at least 30% of the candidates, this attrition is due to poor pharmacokinetics and toxicity. Thus, pharmaceutical companies have begun to seriously re-evaluate their current strategies of drug discovery and development. In that light, we propose that a transport mechanism-based design might help to create new, pharmacokinetically advantageous drugs, and as such should be considered an important component of drug design strategy. Performing enzyme- and/or cell-based drug transporter, interaction tests may greatly facilitate drug development and allow the prediction of drug-drug interactions. We recently developed methods for high-speed functional screening and quantitative structure-activity relationship analysis to study the substrate specificity of ABC transporters and to evaluate the effect of genetic polymorphisms on their function. These methods would provide a practical tool to screen synthetic and natural compounds, and these data can be applied to the molecular design of new drugs. In this review article, we present an overview on the genetic polymorphisms of human ABC transporter ABCG2 and new camptothecin analogues that can circumvent AGCG2-associated multidrug resistance of cancer.

iNR-Drug: Predicting the Interaction of Drugs with Nuclear Receptors in Cellular Networking

Directory of Open Access Journals (Sweden)

Yue-Nong Fan

2014-03-01

Full Text Available Nuclear receptors (NRs are closely associated with various major diseases such as cancer, diabetes, inflammatory disease, and osteoporosis. Therefore, NRs have become a frequent target for drug development. During the process of developing drugs against these diseases by targeting NRs, we are often facing a problem: Given a NR and chemical compound, can we identify whether they are really in interaction with each other in a cell? To address this problem, a predictor called “iNR-Drug” was developed. In the predictor, the drug compound concerned was formulated by a 256-D (dimensional vector derived from its molecular fingerprint, and the NR by a 500-D vector formed by incorporating its sequential evolution information and physicochemical features into the general form of pseudo amino acid composition, and the prediction engine was operated by the SVM (support vector machine algorithm. Compared with the existing prediction methods in this area, iNR-Drug not only can yield a higher success rate, but is also featured by a user-friendly web-server established at http://www.jci-bioinfo.cn/iNR-Drug/, which is particularly useful for most experimental scientists to obtain their desired data in a timely manner. It is anticipated that the iNR-Drug server may become a useful high throughput tool for both basic research and drug development, and that the current approach may be easily extended to study the interactions of drug with other targets as well.

Timing and Duration of Drug Exposure Affects Outcomes of a Drug-Nutrient Interaction During Ontogeny

Directory of Open Access Journals (Sweden)

Jane Alcorn

2010-10-01

Full Text Available Significant drug-nutrient interactions are possible when drugs and nutrients share the same absorption and disposition mechanisms. During postnatal development, the outcomes of drug-nutrient interactions may change with postnatal age since these processes undergo ontogenesis through the postnatal period. Our study investigated the dependence of a significant drug-nutrient interaction (cefepime-carnitine on the timing and duration of drug exposure relative to postnatal age. Rat pups were administered cefepime (5 mg/kg twice daily subcutaneously according to different dosing schedules (postnatal day 1-4, 1-8, 8-11, 8-20, or 1-20. Cefepime significantly reduced serum and heart L-carnitine levels in postnatal day 1-4, 1-8 and 8-11 groups and caused severe degenerative changes in ventricular myocardium in these groups. Cefepime also altered the ontogeny of several key L-carnitine homeostasis pathways. The qualitative and quantitative changes in levels of hepatic γ-butyrobetaine hydroxylase mRNA and activity, hepatic trimethyllysine hydroxlase mRNA, intestinal organic cation/carnitine transporter (Octn mRNA, and renal Octn2 mRNA depended on when during postnatal development the cefepime exposure occurred and duration of exposure. Despite lower levels of heart L-carnitine in earlier postnatal groups, levels of carnitine palmitoyltransferase mRNA and activity, heart Octn2 mRNA and ATP levels in all treatment groups remained unchanged with cefepime exposure. However, changes in other high energy phosphate substrates were noted and reductions in the phosphocreatine/ATP ratio were found in rat pups with normal serum L-carnitine levels. In summary, our data suggest a significant drug-nutrient transport interaction in developing neonates, the nature of which depends on the timing and duration of exposure relative to postnatal age.

Metabolic Pathway of Icotinib In Vitro: The Differential Roles of CYP3A4, CYP3A5, and CYP1A2 on Potential Pharmacokinetic Drug-Drug Interaction.

Science.gov (United States)

Zhang, TianHong; Zhang, KeRong; Ma, Li; Li, Zheng; Wang, Juan; Zhang, YunXia; Lu, Chuang; Zhu, Mingshe; Zhuang, XiaoMei

2018-04-01

Icotinib is the first self-developed small molecule drug in China for targeted therapy of non-small cell lung cancer. To date, systematic studies on the pharmacokinetic drug-drug interaction of icotinib were limited. By identifying metabolite generated in human liver microsomes and revealing the contributions of major cytochromes P450 (CYPs) in the formation of major metabolites, the aim of the present work was to understand the mechanisms underlying pharmacokinetic and pharmacological variability in clinic. A liquid chromatography/UV/high-resolution mass spectrometer method was developed to characterize the icotinib metabolites. The formation of 6 major metabolites was studied in recombinant CYP isozymes and human liver microsomes with specific inhibitors to identify the CYPs responsible for icotinib metabolism. The metabolic pathways observed in vitro are consistent with those observed in human. Results demonstrated that the metabolites are predominantly catalyzed by CYP3A4 (77%∼87%), with a moderate contribution from CYP3A5 (5%∼15%) and CYP1A2 (3.7%∼7.5%). The contribution of CYP2C8, 2C9, 2C19, and 2D6 is insignificant. Based on our observations, to minimize drug-drug interaction risk in clinic, coprescription of icotinib with strong CYP3A inhibitors or inducers must be weighed. CYP1A2, a highly inducible enzyme in the smoking population, may also represent a determinant of pharmacokinetic and pharmacological variability of icotinib, especially in lung cancer patients with smoking history. Copyright © 2018 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Emotion based human-robot interaction

Directory of Open Access Journals (Sweden)

Berns Karsten

2018-01-01

Full Text Available Human-machine interaction is a major challenge in the development of complex humanoid robots. In addition to verbal communication the use of non-verbal cues such as hand, arm and body gestures or mimics can improve the understanding of the intention of the robot. On the other hand, by perceiving such mechanisms of a human in a typical interaction scenario the humanoid robot can adapt its interaction skills in a better way. In this work, the perception system of two social robots, ROMAN and ROBIN of the RRLAB of the TU Kaiserslautern, is presented in the range of human-robot interaction.

Interaction between human BAP31 and respiratory syncytial virus small hydrophobic (SH) protein

International Nuclear Information System (INIS)

Li, Yan; Jain, Neeraj; Limpanawat, Suweeraya; To, Janet; Quistgaard, Esben M.; Nordlund, Par; Thanabalu, Thirumaran; Torres, Jaume

2015-01-01

The small hydrophobic (SH) protein is a short channel-forming polypeptide encoded by the human respiratory syncytial virus (hRSV). Deletion of SH protein leads to the viral attenuation in mice and primates, and delayed apoptosis in infected cells. We have used a membrane-based yeast two-hybrid system (MbY2H) and a library from human lung cDNA to detect proteins that bind SH protein. This led to the identification of a membrane protein, B-cell associated protein 31 (BAP31). Transfected SH protein co-localizes with transfected BAP31 in cells, and pulls down endogenous BAP31. Titration of purified C-terminal endodomain of BAP31 against isotopically labeled SH protein in detergent micelles suggests direct interaction between the two proteins. Given the key role of BAP31 in protein trafficking and its critical involvement in pro- and anti-apoptotic pathways, this novel interaction may constitute a potential drug target. - Highlights: • A yeast two-hybrid system (MbY2H) detected BAP31 as a binder of RSV SH protein. • Transfected SH and BAP31 co-localize in lung epithelial cells. • Endogenous BAP31 is pulled down by RSV SH protein. • BAP31 endodomain interacts with the N-terminal α-helix of SH protein in micelles. • This interaction is proposed to be a potential drug target

Interaction between human BAP31 and respiratory syncytial virus small hydrophobic (SH) protein

Energy Technology Data Exchange (ETDEWEB)

Li, Yan; Jain, Neeraj; Limpanawat, Suweeraya; To, Janet [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Quistgaard, Esben M. [Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm (Sweden); Nordlund, Par [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm (Sweden); Thanabalu, Thirumaran [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore); Torres, Jaume, E-mail: jtorres@ntu.edu.sg [School of Biological Sciences, Nanyang Technological University, 637551 (Singapore)

2015-08-15

The small hydrophobic (SH) protein is a short channel-forming polypeptide encoded by the human respiratory syncytial virus (hRSV). Deletion of SH protein leads to the viral attenuation in mice and primates, and delayed apoptosis in infected cells. We have used a membrane-based yeast two-hybrid system (MbY2H) and a library from human lung cDNA to detect proteins that bind SH protein. This led to the identification of a membrane protein, B-cell associated protein 31 (BAP31). Transfected SH protein co-localizes with transfected BAP31 in cells, and pulls down endogenous BAP31. Titration of purified C-terminal endodomain of BAP31 against isotopically labeled SH protein in detergent micelles suggests direct interaction between the two proteins. Given the key role of BAP31 in protein trafficking and its critical involvement in pro- and anti-apoptotic pathways, this novel interaction may constitute a potential drug target. - Highlights: • A yeast two-hybrid system (MbY2H) detected BAP31 as a binder of RSV SH protein. • Transfected SH and BAP31 co-localize in lung epithelial cells. • Endogenous BAP31 is pulled down by RSV SH protein. • BAP31 endodomain interacts with the N-terminal α-helix of SH protein in micelles. • This interaction is proposed to be a potential drug target.

Is the clinical relevance of drug-food and drug-herb interactions limited to grapefruit juice and Saint-John's Wort?

Science.gov (United States)

Mouly, Stéphane; Lloret-Linares, Célia; Sellier, Pierre-Olivier; Sene, Damien; Bergmann, J-F

2017-04-01

An interaction of drug with food, herbs, and dietary supplements is usually the consequence of a physical, chemical or physiologic relationship between a drug and a product consumed as food, nutritional supplement or over-the-counter medicinal plant. The current educational review aims at reminding to the prescribing physicians that the most clinically relevant drug-food interactions may not be strictly limited to those with grapefruit juice and with the Saint John's Wort herbal extract and may be responsible for changes in drug plasma concentrations, which in turn decrease efficacy or led to sometimes life-threatening toxicity. Common situations handled in clinical practice such as aging, concomitant medications, transplant recipients, patients with cancer, malnutrition, HIV infection and those receiving enteral or parenteral feeding may be at increased risk of drug-food or drug-herb interactions. Medications with narrow therapeutic index or potential life-threatening toxicity, e.g., the non-steroidal anti-inflammatory drugs, opioid analgesics, cardiovascular medications, warfarin, anticancer drugs and immunosuppressants may be at risk of significant drug-food interactions to occur. Despite the fact that considerable effort has been achieved to increase patient' and doctor's information and ability to anticipate their occurrence and consequences in clinical practice, a thorough and detailed health history and dietary recall are essential for identifying potential problems in order to optimize patient prescriptions and drug dosing on an individual basis as well as to increase the treatment risk/benefit ratio. Copyright © 2016 Elsevier Ltd. All rights reserved.

Drug-drug interactions as a determinant of elevated lithium serum levels in daily clinical practice

NARCIS (Netherlands)

Wilting, [No Value; Movig, KL; Moolenaar, M; Hekster, YA; Brouwers, [No Value; Heerdink, ER; Nolen, WA; Egberts, AC

Objective: Lithium is a drug with a narrow therapeutic window. Concomitantly used medication is a potentially influencing factor of lithium serum concentrations. We conducted a multicentre retrospective case-control study with the aim of investigating lithium-related drug interactions as

Phytotherapeutics: The Emerging Role of Intestinal and Hepatocellular Transporters in Drug Interactions with Botanical Supplements.

Science.gov (United States)

Murtaza, Ghulam; Ullah, Naveed; Mukhtar, Farah; Nawazish, Shamyla; Muneer, Saiqa

2017-10-21

In herbalism, botanical supplements are commonly believed to be safe remedies, however, botanical supplements and dietary ingredients interact with transport and metabolic processes, affecting drug disposition. Although a large number of studies have described that botanical supplements interfere with drug metabolism, the mode of their interaction with drug transport processes is not well described. Such interactions may result in serious undesired effects and changed drug efficacy, therefore, some studies on interaction between botanical supplement ingredients and drug transporters such as P-gp and OATPs are described here, suggesting that the interaction between botanical supplements and the drug transporters is clinically significant.

Interaction debugging : an integral approach to analyze human-robot interaction

NARCIS (Netherlands)

Kooijmans, T.; Kanda, T.; Bartneck, C.; Ishiguro, H.; Hagita, N.

2006-01-01

Along with the development of interactive robots, controlled experiments and field trials are regularly conducted to stage human-robot interaction. Experience in this field has shown that analyzing human-robot interaction for evaluation purposes fosters the development of improved systems and the

Information needs for making clinical recommendations about potential drug-drug interactions: a synthesis of literature review and interviews.

Science.gov (United States)

Romagnoli, Katrina M; Nelson, Scott D; Hines, Lisa; Empey, Philip; Boyce, Richard D; Hochheiser, Harry

2017-02-22

Drug information compendia and drug-drug interaction information databases are critical resources for clinicians and pharmacists working to avoid adverse events due to exposure to potential drug-drug interactions (PDDIs). Our goal is to develop information models, annotated data, and search tools that will facilitate the interpretation of PDDI information. To better understand the information needs and work practices of specialists who search and synthesize PDDI evidence for drug information resources, we conducted an inquiry that combined a thematic analysis of published literature with unstructured interviews. Starting from an initial set of relevant articles, we developed search terms and conducted a literature search. Two reviewers conducted a thematic analysis of included articles. Unstructured interviews with drug information experts were conducted and similarly coded. Information needs, work processes, and indicators of potential strengths and weaknesses of information systems were identified. Review of 92 papers and 10 interviews identified 56 categories of information needs related to the interpretation of PDDI information including drug and interaction information; study design; evidence including clinical details, quality and content of reports, and consequences; and potential recommendations. We also identified strengths/weaknesses of PDDI information systems. We identified the kinds of information that might be most effective for summarizing PDDIs. The drug information experts we interviewed had differing goals, suggesting a need for detailed information models and flexible presentations. Several information needs not discussed in previous work were identified, including temporal overlaps in drug administration, biological plausibility of interactions, and assessment of the quality and content of reports. Richly structured depictions of PDDI information may help drug information experts more effectively interpret data and develop recommendations

Update of green tea interactions with cardiovascular drugs and putative mechanisms

Directory of Open Access Journals (Sweden)

José Pablo Werba

2018-04-01

Full Text Available Many patients treated with cardiovascular (CV drugs drink green tea (GT, either as a cultural tradition or persuaded of its putative beneficial effects for health. Yet, GT may affect the pharmacokinetics and pharmacodynamics of CV compounds. Novel GT-CV drug interactions were reported for rosuvastatin, sildenafil and tacrolimus. Putative mechanisms involve inhibitory effects of GT catechins at the intestinal level on influx transporters OATP1A2 or OATP2B1 for rosuvastatin, on CYP3A for sildenafil and on both CYP3A and the efflux transporter p-glycoprotein for tacrolimus. These interactions, which add to those previously described with simvastatin, nadolol and warfarin, might lead, in some cases, to reduced drug efficacy or risk of drug toxicity. Oddly, available data on GT interaction with CV compounds with a narrow therapeutic index, such as warfarin and tacrolimus, derive from single case reports. Conversely, GT interactions with simvastatin, rosuvastatin, nadolol and sildenafil were documented through pharmacokinetic studies. In these, the effect of GT or GT derivatives on drug exposure was mild to moderate, but a high inter-individual variability was observed. Further investigations, including studies on the effect of the dose and the time of GT intake are necessary to understand more in depth the clinical relevance of GT-CV drug interactions. Keywords: Cardiovascular drugs, Green tea, Herb–drug interactions

DGIdb 3.0: a redesign and expansion of the drug-gene interaction database.

Science.gov (United States)

Cotto, Kelsy C; Wagner, Alex H; Feng, Yang-Yang; Kiwala, Susanna; Coffman, Adam C; Spies, Gregory; Wollam, Alex; Spies, Nicholas C; Griffith, Obi L; Griffith, Malachi

2018-01-04

The drug-gene interaction database (DGIdb, www.dgidb.org) consolidates, organizes and presents drug-gene interactions and gene druggability information from papers, databases and web resources. DGIdb normalizes content from 30 disparate sources and allows for user-friendly advanced browsing, searching and filtering for ease of access through an intuitive web user interface, application programming interface (API) and public cloud-based server image. DGIdb v3.0 represents a major update of the database. Nine of the previously included 24 sources were updated. Six new resources were added, bringing the total number of sources to 30. These updates and additions of sources have cumulatively resulted in 56 309 interaction claims. This has also substantially expanded the comprehensive catalogue of druggable genes and anti-neoplastic drug-gene interactions included in the DGIdb. Along with these content updates, v3.0 has received a major overhaul of its codebase, including an updated user interface, preset interaction search filters, consolidation of interaction information into interaction groups, greatly improved search response times and upgrading the underlying web application framework. In addition, the expanded API features new endpoints which allow users to extract more detailed information about queried drugs, genes and drug-gene interactions, including listings of PubMed IDs, interaction type and other interaction metadata.

Prevalence of Potential and Clinically Relevant Statin-Drug Interactions in Frail and Robust Older Inpatients.

Science.gov (United States)

Thai, Michele; Hilmer, Sarah; Pearson, Sallie-Anne; Reeve, Emily; Gnjidic, Danijela

2015-10-01

A significant proportion of older people are prescribed statins and are also exposed to polypharmacy, placing them at increased risk of statin-drug interactions. To describe the prevalence rates of potential and clinically relevant statin-drug interactions in older inpatients according to frailty status. A cross-sectional study of patients aged ≥65 years who were prescribed a statin and were admitted to a teaching hospital between 30 July and 10 October 2014 in Sydney, Australia, was conducted. Data on socio-demographics, comorbidities and medications were collected using a standardized questionnaire. Potential statin-drug interactions were defined if listed in the Australian Medicines Handbook and three international drug information sources: the British National Formulary, Drug Interaction Facts and Drug-Reax(®). Clinically relevant statin-drug interactions were defined as interactions with the highest severity rating in at least two of the three international drug information sources. Frailty was assessed using the Reported Edmonton Frail Scale. A total of 180 participants were recruited (median age 78 years, interquartile range 14), 35.0% frail and 65.0% robust. Potential statin-drug interactions were identified in 10% of participants, 12.7% of frail participants and 8.5% of robust participants. Clinically relevant statin-drug interactions were identified in 7.8% of participants, 9.5% of frail participants and 6.8% of robust participants. Depending on the drug information source used, the prevalence rates of potential and clinically relevant statin-drug interactions ranged between 14.4 and 35.6% and between 14.4 and 20.6%, respectively. In our study of frail and robust older inpatients taking statins, the overall prevalence of potential statin-drug interactions was low and varied significantly according to the drug information source used.

Basic principles of drug--excipients interactions.

Science.gov (United States)

Vranić, Edina

2004-05-01

Excipients are generally considered inert additives included in drug formulation to help in the manufacturing, administration or absorption. Other reasons for inclusion concern product differentiation, appearance enhancement or retention of quality. Excipients can initiate, propagate or participate in chemical or physical interactions with an active substance, possibly leading to compromised quality or performance of the medication. Understanding the chemical and physical nature of excipients, the impurities or residues associated with them and how they may interact with other materials, or with each other, forewarns the pharmaceutical technologist of possibilities for undesirable developments.

The role of progestins in the behavioral effects of cocaine and other drugs of abuse: human and animal research.

Science.gov (United States)

Anker, Justin J; Carroll, Marilyn E

2010-11-01

This review summarizes findings from human and animal research investigating the influence of progesterone and its metabolites allopreganolone and pregnanolone (progestins) on the effects of cocaine and other drugs of abuse. Since a majority of these studies have used cocaine, this will be the primary focus; however, the influence of progestins on other drugs of abuse will also be discussed. Collectively, findings from these studies support a role for progestins in (1) attenuating the subjective and physiological effects of cocaine in humans, (2) blocking the reinforcing and other behavioral effects of cocaine in animal models of drug abuse, and (3) influencing behavioral responses to other drugs of abuse such as alcohol and nicotine in animals. Administration of several drugs of abuse in both human and nonhuman animals significantly increased progestin levels, and this is explained in terms of progestins acting as homeostatic regulators that decrease and normalize heightened stress and reward responses which lead to increased drug craving and relapse. The findings discussed here highlight the complexity of progestin-drug interactions, and they suggest a possible use for these agents in understanding the etiology of and developing treatments for drug abuse. Copyright © 2010 Elsevier Ltd. All rights reserved.

[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.

Evaluation of Drug Interactions and Prescription Errors of Poultry Veterinarians in North of Iran

Directory of Open Access Journals (Sweden)

Madadi MS

2014-03-01

Full Text Available Drug prescription errors are a common cause of adverse incidents and may lead to adverse outcomes, sometimes in subtle ways, being compounded by circumstances or further errors. Therefore, it is important that veterinarians issue the correct drug at the correct dose. Using two or more prescribed drugs may lead to drug interactions. Some drug interactions are very harmful and may have potential threats to the patient's health that is called antagonism. In a survey study, medication errors of 750 prescriptions, including dosage errors and drug interactions were studied. The results indicated that 20.8% of prescriptions had at least one drug interaction. The most interactions were related to antibiotics (69.1%, Sulfonamides (46.7%, Methenamine (46.7% and Florfenicol (20.2%. Analysis of dosage errors indicated that total drugs consumed by broilers in the summer are more than winter seasons. Based on these results, avoiding medication errors are important in the balanced prescribing of drugs and regular education of veterinary practitioners in a certain interval is needed.

Analysis of possible food/nutrient and drug interactions in hospitalized patients

OpenAIRE

Lopes, Everton Moraes; Carvalho, Rumão Batista Nunes de; Freitas, Rivelilson Mendes de

2010-01-01

ABSTRACT Objective: To evaluate the prescription in relation to the possible interactions between drugs and foods/nutrients in the diets of patients in the Hospital Regional Justino Luz in the municipality of Picos, Piauí, Brazil. Methods: The sample consisted of 60 medical records of patients admitted at the hospital. The records were analyzed according to the presence or absence of interactions between drugs and foods/nutrients of the prescribed diets. Results: Of the 82 drugs prescribed...

Prediction of Human Pharmacokinetic Profile After Transdermal Drug Application Using Excised Human Skin.

Science.gov (United States)

Yamamoto, Syunsuke; Karashima, Masatoshi; Arai, Yuta; Tohyama, Kimio; Amano, Nobuyuki

2017-09-01

Although several mathematical models have been reported for the estimation of human plasma concentration profiles of drug substances after dermal application, the successful cases that can predict human pharmacokinetic profiles are limited. Therefore, the aim of this study is to investigate the prediction of human plasma concentrations after dermal application using in vitro permeation parameters obtained from excised human skin. The in vitro skin permeability of 7 marketed drug products was evaluated. The plasma concentration-time profiles of the drug substances in humans after their dermal application were simulated using compartment models and the clinical pharmacokinetic parameters. The transdermal process was simulated using the in vitro skin permeation rate and lag time assuming a zero-order absorption. These simulated plasma concentration profiles were compared with the clinical data. The result revealed that the steady-state plasma concentration of diclofenac and the maximum concentrations of nicotine, bisoprolol, rivastigmine, and lidocaine after topical application were within 2-fold of the clinical data. Furthermore, the simulated concentration profiles of bisoprolol, nicotine, and rivastigmine reproduced the decrease in absorption due to drug depletion from the formulation. In conclusion, this simple compartment model using in vitro human skin permeation parameters as zero-order absorption predicted the human plasma concentrations accurately. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

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

Food-drug interactions precipitated by fruit juices other than grapefruit juice: An update review

Directory of Open Access Journals (Sweden)

Meng Chen

2018-04-01

Full Text Available This review addressed drug interactions precipitated by fruit juices other than grapefruit juice based on randomized controlled trials (RCTs. Literature was identified by searching PubMed, Cochrane Library, Scopus and Web of Science till December 30 2017. Among 46 finally included RCTs, six RCTs simply addressed pharmacodynamic interactions and 33 RCTs studied pharmacokinetic interactions, whereas seven RCTs investigated both pharmacokinetic and pharmacodynamic interactions. Twenty-two juice-drug combinations showed potential clinical relevance. The beneficial combinations included orange juice-ferrous fumarate, lemon juice-99mTc-tetrofosmin, pomegranate juice-intravenous iron during hemodialysis, cranberry juice-triple therapy medications for H. pylori, blueberry juice-etanercept, lime juice-antimalarials, and wheat grass juice-chemotherapy. The potential adverse interactions included decreased drug bioavailability (apple juice-fexofenadine, atenolol, aliskiren; orange juice-aliskiren, atenolol, celiprolol, montelukast, fluoroquinolones, alendronate; pomelo juice-sildenafil; grape juice-cyclosporine, increased bioavailability (Seville orange juice-felodipine, pomelo juice-cyclosporine, orange-aluminum containing antacids. Unlike furanocoumarin-rich grapefruit juice which could primarily precipitate drug interactions by strong inhibition of cytochrome P450 3A4 isoenzyme and P-glycoprotein and thus cause deadly outcomes due to co-ingestion with some medications, other fruit juices did not precipitate severely detrimental food–drug interaction despite of sporadic case reports. The extent of a juice-drug interaction may be associated with volume of drinking juice, fruit varieties, type of fruit, time between juice drinking and drug intake, genetic polymorphism in the enzymes or transporters and anthropometric variables. Pharmacists and health professionals should properly screen for and educate patients about potential adverse juice-drug

New Equilibrium Models of Drug-Receptor Interactions Derived from Target-Mediated Drug Disposition.

Science.gov (United States)

Peletier, Lambertus A; Gabrielsson, Johan

2018-05-14

In vivo analyses of pharmacological data are traditionally based on a closed system approach not incorporating turnover of target and ligand-target kinetics, but mainly focussing on ligand-target binding properties. This study incorporates information about target and ligand-target kinetics parallel to binding. In a previous paper, steady-state relationships between target- and ligand-target complex versus ligand exposure were derived and a new expression of in vivo potency was derived for a circulating target. This communication is extending the equilibrium relationships and in vivo potency expression for (i) two separate targets competing for one ligand, (ii) two different ligands competing for a single target and (iii) a single ligand-target interaction located in tissue. The derived expressions of the in vivo potencies will be useful both in drug-related discovery projects and mechanistic studies. The equilibrium states of two targets and one ligand may have implications in safety assessment, whilst the equilibrium states of two competing ligands for one target may cast light on when pharmacodynamic drug-drug interactions are important. The proposed equilibrium expressions for a peripherally located target may also be useful for small molecule interactions with extravascularly located targets. Including target turnover, ligand-target complex kinetics and binding properties in expressions of potency and efficacy will improve our understanding of within and between-individual (and across species) variability. The new expressions of potencies highlight the fact that the level of drug-induced target suppression is very much governed by target turnover properties rather than by the target expression level as such.

Modeling multimodal human-computer interaction

NARCIS (Netherlands)

Obrenovic, Z.; Starcevic, D.

2004-01-01

Incorporating the well-known Unified Modeling Language into a generic modeling framework makes research on multimodal human-computer interaction accessible to a wide range off software engineers. Multimodal interaction is part of everyday human discourse: We speak, move, gesture, and shift our gaze

Drug interactions: volatile anesthetics and opioids.

Science.gov (United States)

Glass, P S; Gan, T J; Howell, S; Ginsberg, B

1997-09-01

Multiple drugs are used to provide anesthesia. Volatile anesthetics are commonly combined with opioids. Several studies have demonstrated that small doses of opioid (i.e., within the analgesic range) result in a marked reduction in minimum alveolar concentration (MAC) of the volatile anesthetic that will prevent purposeful movement in 50% of patients at skin incision). Further increases in opioid dose provide only a further small reduction in MAC. Thus, a ceiling effect of the opioid is observed at a MAC value of the volatile anesthetic equal to its MAC awake. Recovery from anesthesia when an opioid is combined with a volatile anesthetic is dependent on the rate of decrease of both drugs to their respective concentrations that are associated with adequate spontaneous ventilation and awakening. Through an understanding of the pharmacodynamic interaction of volatile anesthetics with opioids and the pharmacokinetic processes responsible for the recovery from drug effect, optimal dosing schemes can thus be developed. A review of these pharmacodynamic and pharmacokinetic principles that will allow clinicians to administer drugs to provide a more optimal anesthetic is provided.

A high-speed drug interaction search system for ease of use in the clinical environment.

Science.gov (United States)

Takada, Masahiro; Inada, Hiroshi; Nakazawa, Kazuo; Tani, Shoko; Iwata, Michiaki; Sugimoto, Yoshihisa; Nagata, Satoru

2012-12-01

With the advancement of pharmaceutical development, drug interactions have become increasingly complex. As a result, a computer-based drug interaction search system is required to organize the whole of drug interaction data. To overcome problems faced with the existing systems, we developed a drug interaction search system using a hash table, which offers higher processing speeds and easier maintenance operations compared with relational databases (RDB). In order to compare the performance of our system and MySQL RDB in terms of search speed, drug interaction searches were repeated for all 45 possible combinations of two out of a group of 10 drugs for two cases: 5,604 and 56,040 drug interaction data. As the principal result, our system was able to process the search approximately 19 times faster than the system using the MySQL RDB. Our system also has several other merits such as that drug interaction data can be created in comma-separated value (CSV) format, thereby facilitating data maintenance. Although our system uses the well-known method of a hash table, it is expected to resolve problems common to existing systems and to be an effective system that enables the safe management of drugs.

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

Science.gov (United States)

Cherkaoui-Rbati, Mohammed H; Paine, Stuart W; Littlewood, Peter; Rauch, Cyril

2017-01-01

All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs) of new chemical entities (NCEs) and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit), located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level). A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK) model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s) including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions.

Directory of Open Access Journals (Sweden)

Mohammed H Cherkaoui-Rbati

Full Text Available All pharmaceutical companies are required to assess pharmacokinetic drug-drug interactions (DDIs of new chemical entities (NCEs and mathematical prediction helps to select the best NCE candidate with regard to adverse effects resulting from a DDI before any costly clinical studies. Most current models assume that the liver is a homogeneous organ where the majority of the metabolism occurs. However, the circulatory system of the liver has a complex hierarchical geometry which distributes xenobiotics throughout the organ. Nevertheless, the lobule (liver unit, located at the end of each branch, is composed of many sinusoids where the blood flow can vary and therefore creates heterogeneity (e.g. drug concentration, enzyme level. A liver model was constructed by describing the geometry of a lobule, where the blood velocity increases toward the central vein, and by modeling the exchange mechanisms between the blood and hepatocytes. Moreover, the three major DDI mechanisms of metabolic enzymes; competitive inhibition, mechanism based inhibition and induction, were accounted for with an undefined number of drugs and/or enzymes. The liver model was incorporated into a physiological-based pharmacokinetic (PBPK model and simulations produced, that in turn were compared to ten clinical results. The liver model generated a hierarchy of 5 sinusoidal levels and estimated a blood volume of 283 mL and a cell density of 193 × 106 cells/g in the liver. The overall PBPK model predicted the pharmacokinetics of midazolam and the magnitude of the clinical DDI with perpetrator drug(s including spatial and temporal enzyme levels changes. The model presented herein may reduce costs and the use of laboratory animals and give the opportunity to explore different clinical scenarios, which reduce the risk of adverse events, prior to costly human clinical studies.

Chemotherapy drugs form ion pores in membranes due to physical interactions with lipids.

Science.gov (United States)

Ashrafuzzaman, Mohammad; Tseng, Chih-Yuan; Duszyk, Marek; Tuszynski, Jack A

2012-12-01

We demonstrate the effects on membrane of the tubulin-binding chemotherapy drugs: thiocolchicoside and taxol. Electrophysiology recordings across lipid membranes in aqueous phases containing drugs were used to investigate the drug effects on membrane conductance. Molecular dynamics simulation of the chemotherapy drug-lipid complexes was used to elucidate the mechanism at an atomistic level. Both drugs are observed to induce stable ion-flowing pores across membranes. Discrete pore current-time plots exhibit triangular conductance events in contrast to rectangular ones found for ion channels. Molecular dynamics simulations indicate that drugs and lipids experience electrostatic and van der Waals interactions for short periods of time when found within each other's proximity. The energies from these two interactions are found to be similar to the energies derived theoretically using the screened Coulomb and the van der Waals interactions between peptides and lipids due to mainly their charge properties while forming peptide-induced ion channels in lipid bilayers. Experimental and in silico studies together suggest that the chemotherapy drugs induce ion pores inside lipid membranes due to drug-lipid physical interactions. The findings reveal cytotoxic effects of drugs on the cell membrane, which may aid in novel drug development for treatment of cancer and other diseases. © 2012 John Wiley & Sons A/S.

Hemodynamic changes by drug interaction of adrenaline with chlorpromazine.

Science.gov (United States)

Higuchi, Hitoshi; Yabuki, Akiko; Ishii-Maruhama, Minako; Tomoyasu, Yumiko; Maeda, Shigeru; Miyawaki, Takuya

2014-01-01

Adrenaline (epinephrine) is included in dental local anesthesia for the purpose of vasoconstriction. In Japan, adrenaline is contraindicated for use in patients receiving antipsychotic therapy, because the combination of adrenaline and an antipsychotic is considered to cause severe hypotension; however, there is insufficient evidence supporting this claim. The purpose of the present study was to clarify the changes in hemodynamics caused by drug interaction between adrenaline and an antipsychotic and to evaluate the safety of the combined use of adrenaline and an antipsychotic in an animal study. Male Sprague-Dawley rats were anesthetized with sodium pentobarbital. A catheter was inserted into the femoral artery to measure blood pressure and pulse rate. Rats were pretreated by intraperitoneal injection of chlorpromazine or chlorpromazine and propranolol, and after 20 minutes, saline or 1 of 3 different doses of adrenaline was administered by intraperitoneal injection. Changes in the ratio of mean arterial blood pressure and pulse rate were measured after the injection of adrenaline. Significant hypotension and tachycardia were observed after the injection of adrenaline in the chlorpromazine-pretreated rats. These effects were in a dose-dependent manner, and 100 μg/kg adrenaline induced significant hemodynamic changes. Furthermore, in the chlorpromazine and propranolol-pretreated rats, modest hypertension was induced by adrenaline, but hypotension and tachycardia were not significantly shown. Hypotension was caused by a drug interaction between adrenaline and chlorpromazine through the activation of the β-adrenergic receptor and showed a dose-dependent effect. Low-dose adrenaline similar to what might be used in human dental treatment did not result in a significant homodynamic change.

Effects of Social Interaction and Warm Ambient Temperature on Brain Hyperthermia Induced by the Designer Drugs Methylone and MDPV

Science.gov (United States)

Kiyatkin, Eugene A; Kim, Albert H; Wakabayashi, Ken T; Baumann, Michael H; Shaham, Yavin

2015-01-01

3,4-Methylenedioxymethcathinone (methylone) and 3,4-methylenedioxypyrovalerone (MDPV) are new drugs of abuse that have gained worldwide popularity. These drugs are structurally similar to 3,4-methylenedioxymethamphetamine (MDMA) and share many of its physiological and behavioral effects in humans, including the development of hyperthermia during acute intoxication. Here, we examined the effects of methylone (1–9 mg/kg, s.c.) or MDPV (0.1–1.0 mg/kg, s.c.) on brain temperature homeostasis in rats maintained in a standard laboratory environment (single-housed in a quiet rest at 22 °C) and under conditions that model human drug use (social interaction and 29 °C ambient temperature). By simultaneously monitoring temperatures in the nucleus accumbens, temporal muscle, and facial skin, we assessed the effects of methylone and MDPV on intra-brain heat production and cutaneous vascular tone, two critical factors that control brain temperature responses. Both methylone and MDPV dose-dependently increased brain temperature, but even at high doses that induced robust locomotor activation, hyperthermia was modest in magnitude (up to ∼2 °C). Both drugs also induced dose-dependent peripheral vasoconstriction, which appears to be a primary mechanism determining the brain hyperthermic responses. In contrast to the powerful potentiation of MDMA-induced hyperthermia by social interaction and warm ambient temperature, such potentiation was absent for methylone and minimal for MDPV. Taken together, despite structural similarities to MDMA, exposure to methylone or MDPV under conditions commonly associated with human drug use does not lead to profound elevations in brain temperature and sustained vasoconstriction, two critical factors associated with MDMA toxicity. PMID:25074640

iGPCR-drug: a web server for predicting interaction between GPCRs and drugs in cellular networking.

Directory of Open Access Journals (Sweden)

Xuan Xiao

Full Text Available Involved in many diseases such as cancer, diabetes, neurodegenerative, inflammatory and respiratory disorders, G-protein-coupled receptors (GPCRs are among the most frequent targets of therapeutic drugs. It is time-consuming and expensive to determine whether a drug and a GPCR are to interact with each other in a cellular network purely by means of experimental techniques. Although some computational methods were developed in this regard based on the knowledge of the 3D (dimensional structure of protein, unfortunately their usage is quite limited because the 3D structures for most GPCRs are still unknown. To overcome the situation, a sequence-based classifier, called "iGPCR-drug", was developed to predict the interactions between GPCRs and drugs in cellular networking. In the predictor, the drug compound is formulated by a 2D (dimensional fingerprint via a 256D vector, GPCR by the PseAAC (pseudo amino acid composition generated with the grey model theory, and the prediction engine is operated by the fuzzy K-nearest neighbour algorithm. Moreover, a user-friendly web-server for iGPCR-drug was established at http://www.jci-bioinfo.cn/iGPCR-Drug/. For the convenience of most experimental scientists, a step-by-step guide is provided on how to use the web-server to get the desired results without the need to follow the complicated math equations presented in this paper just for its integrity. The overall success rate achieved by iGPCR-drug via the jackknife test was 85.5%, which is remarkably higher than the rate by the existing peer method developed in 2010 although no web server was ever established for it. It is anticipated that iGPCR-Drug may become a useful high throughput tool for both basic research and drug development, and that the approach presented here can also be extended to study other drug - target interaction networks.

Effects of atorvastatin metabolites on induction of drug-metabolizing enzymes and membrane transporters through human pregnane X receptor

Science.gov (United States)

Hoffart, E; Ghebreghiorghis, L; Nussler, AK; Thasler, WE; Weiss, TS; Schwab, M; Burk, O

2012-01-01

BACKGROUND AND PURPOSE Atorvastatin metabolites differ in their potential for drug interaction because of differential inhibition of drug-metabolizing enzymes and transporters. We here investigate whether they exert differential effects on the induction of these genes via activation of pregnane X receptor (PXR) and constitutive androstane receptor (CAR). EXPERIMENTAL APPROACH Ligand binding to PXR or CAR was analysed by mammalian two-hybrid assembly and promoter/reporter gene assays. Additionally, surface plasmon resonance was used to analyse ligand binding to CAR. Primary human hepatocytes were treated with atorvastatin metabolites, and mRNA and protein expression of PXR-regulated genes was measured. Two-hybrid co-activator interaction and co-repressor release assays were utilized to elucidate the molecular mechanism of PXR activation. KEY RESULTS All atorvastatin metabolites induced the assembly of PXR and activated CYP3A4 promoter activity. Ligand binding to CAR could not be proven. In primary human hepatocytes, the para-hydroxy metabolite markedly reduced or abolished induction of cytochrome P450 and transporter genes. While significant differences in co-activator recruitment were not observed, para-hydroxy atorvastatin demonstrated only 50% release of co-repressors. CONCLUSIONS AND IMPLICATIONS Atorvastatin metabolites are ligands of PXR but not of CAR. Atorvastatin metabolites demonstrate differential induction of PXR target genes, which results from impaired release of co-repressors. Consequently, the properties of drug metabolites have to be taken into account when analysing PXR-dependent induction of drug metabolism and transport. The drug interaction potential of the active metabolite, para-hydroxy atorvastatin, might be lower than that of the parent compound. PMID:21913896

Validation of a microdose probe drug cocktail for clinical drug interaction assessments for drug transporters and CYP3A.

Science.gov (United States)

Prueksaritanont, T; Tatosian, D A; Chu, X; Railkar, R; Evers, R; Chavez-Eng, C; Lutz, R; Zeng, W; Yabut, J; Chan, G H; Cai, X; Latham, A H; Hehman, J; Stypinski, D; Brejda, J; Zhou, C; Thornton, B; Bateman, K P; Fraser, I; Stoch, S A

2017-04-01

A microdose cocktail containing midazolam, dabigatran etexilate, pitavastatin, rosuvastatin, and atorvastatin has been established to allow simultaneous assessment of a perpetrator impact on the most common drug metabolizing enzyme, cytochrome P450 (CYP)3A, and the major transporters organic anion-transporting polypeptides (OATP)1B, breast cancer resistance protein (BCRP), and MDR1 P-glycoprotein (P-gp). The clinical utility of these microdose cocktail probe substrates was qualified by conducting clinical drug interaction studies with three inhibitors with different in vitro inhibitory profiles (rifampin, itraconazole, and clarithromycin). Generally, the pharmacokinetic profiles of the probe substrates, in the absence and presence of the inhibitors, were comparable to their reported corresponding pharmacological doses, and/or in agreement with theoretical expectations. The exception was dabigatran, which resulted in an approximately twofold higher magnitude for microdose compared to conventional dosing, and, thus, can be used to flag a worst-case scenario for P-gp. Broader application of the microdose cocktail will facilitate a more comprehensive understanding of the roles of drug transporters in drug disposition and drug interactions. © 2016 American Society for Clinical Pharmacology and Therapeutics.

Public health relevance of drug-nutrition interactions

NARCIS (Netherlands)

Péter, Szabolcs; Navis, Gerjan; de Borst, Martin H; von Schacky, Clemens; van Orten-Luiten, Anne Claire B; Zhernakova, Alexandra; Witkamp, Renger F; Janse, André; Weber, Peter; Bakker, Stephan J L; Eggersdorfer, Manfred

The public health relevance of drug-nutrition interactions is currently highly undervalued and overlooked. This is particularly the case for elderly persons where multi-morbidity and consequently polypharmacy is very common. Vitamins and other micronutrients have central functions in metabolism, and

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

Science.gov (United States)

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.

A survey of attitudes, practices, and knowledge regarding drug-drug interactions among medical residents in Iran

NARCIS (Netherlands)

Nabovati, Ehsan; Vakili-Arki, Hasan; Taherzadeh, Zhila; Saberi, Mohammad Reza; Abu-Hanna, Ameen; Eslami, Saeid

2017-01-01

Background When prescribing medications, physicians should recognize clinically relevant potential drug-drug interactions (DDIs). To improve medication safety, it is important to understand prescribers' knowledge and opinions pertaining to DDIs. Objective To determine the current DDI information

Prediction of Effective Drug Combinations by Chemical Interaction, Protein Interaction and Target Enrichment of KEGG Pathways

Directory of Open Access Journals (Sweden)

Lei Chen

2013-01-01

Full Text Available Drug combinatorial therapy could be more effective in treating some complex diseases than single agents due to better efficacy and reduced side effects. Although some drug combinations are being used, their underlying molecular mechanisms are still poorly understood. Therefore, it is of great interest to deduce a novel drug combination by their molecular mechanisms in a robust and rigorous way. This paper attempts to predict effective drug combinations by a combined consideration of: (1 chemical interaction between drugs, (2 protein interactions between drugs’ targets, and (3 target enrichment of KEGG pathways. A benchmark dataset was constructed, consisting of 121 confirmed effective combinations and 605 random combinations. Each drug combination was represented by 465 features derived from the aforementioned three properties. Some feature selection techniques, including Minimum Redundancy Maximum Relevance and Incremental Feature Selection, were adopted to extract the key features. Random forest model was built with its performance evaluated by 5-fold cross-validation. As a result, 55 key features providing the best prediction result were selected. These important features may help to gain insights into the mechanisms of drug combinations, and the proposed prediction model could become a useful tool for screening possible drug combinations.

Cumulative organic anion transporter-mediated drug-drug interaction potential of multiple components in salvia miltiorrhiza (danshen) preparations.

Science.gov (United States)

Wang, Li; Venitz, Jürgen; Sweet, Douglas H

2014-12-01

To evaluate organic anion transporter-mediated drug-drug interaction (DDI) potential for individual active components of Danshen (Salvia miltiorrhiza) vs. combinations using in vitro and in silico approaches. Inhibition profiles for single Danshen components and combinations were generated in stably-expressing human (h)OAT1 and hOAT3 cells. Plasma concentration-time profiles for compounds were estimated from in vivo human data using an i.v. two-compartment model (with first-order elimination). The cumulative DDI index was proposed as an indicator of DDI potential for combination products. This index was used to evaluate the DDI potential for Danshen injectables from 16 different manufacturers and 14 different lots from a single manufacturer. The cumulative DDI index predicted in vivo inhibition potentials, 82% (hOAT1) and 74% (hOAT3), comparable with those observed in vitro, 72 ± 7% (hOAT1) and 81 ± 10% (hOAT3), for Danshen component combinations. Using simulated unbound Cmax values, a wide range in cumulative DDI index between manufacturers, and between lots, was predicted. Many products exhibited a cumulative DDI index > 1 (50% inhibition). Danshen injectables will likely exhibit strong potential to inhibit hOAT1 and hOAT3 function in vivo. The proposed cumulative DDI index might improve prediction of DDI potential of herbal medicines or pharmaceutical preparations containing multiple components.

Regulation of drug-metabolizing enzymes in infectious and inflammatory disease: implications for biologics-small molecule drug interactions.

Science.gov (United States)

Mallick, Pankajini; Taneja, Guncha; Moorthy, Bhagavatula; Ghose, Romi

2017-06-01

Drug-metabolizing enzymes (DMEs) are primarily down-regulated during infectious and inflammatory diseases, leading to disruption in the metabolism of small molecule drugs (smds), which are increasingly being prescribed therapeutically in combination with biologics for a number of chronic diseases. The biologics may exert pro- or anti-inflammatory effect, which may in turn affect the expression/activity of DMEs. Thus, patients with infectious/inflammatory diseases undergoing biologic/smd treatment can have complex changes in DMEs due to combined effects of the disease and treatment. Areas covered: We will discuss clinical biologics-SMD interaction and regulation of DMEs during infection and inflammatory diseases. Mechanistic studies will be discussed and consequences on biologic-small molecule combination therapy on disease outcome due to changes in drug metabolism will be highlighted. Expert opinion: The involvement of immunomodulatory mediators in biologic-SMDs is well known. Regulatory guidelines recommend appropriate in vitro or in vivo assessments for possible interactions. The role of cytokines in biologic-SMDs has been documented. However, the mechanisms of drug-drug interactions is much more complex, and is probably multi-factorial. Studies aimed at understanding the mechanism by which biologics effect the DMEs during inflammation/infection are clinically important.

Towards quantifying dynamic human-human physical interactions for robot assisted stroke therapy.

Science.gov (United States)

Mohan, Mayumi; Mendonca, Rochelle; Johnson, Michelle J

2017-07-01

Human-Robot Interaction is a prominent field of robotics today. Knowledge of human-human physical interaction can prove vital in creating dynamic physical interactions between human and robots. Most of the current work in studying this interaction has been from a haptic perspective. Through this paper, we present metrics that can be used to identify if a physical interaction occurred between two people using kinematics. We present a simple Activity of Daily Living (ADL) task which involves a simple interaction. We show that we can use these metrics to successfully identify interactions.

Toxicokinetics of drugs of abuse: current knowledge of the isoenzymes involved in the human metabolism of tetrahydrocannabinol, cocaine, heroin, morphine, and codeine.

Science.gov (United States)

Maurer, Hans H; Sauer, Christoph; Theobald, Denis S

2006-06-01

This review summarizes the major metabolic pathways of the drugs of abuse, tetrahydrocannabinol, cocaine, heroin, morphine, and codeine, in humans including the involvement of isoenzymes. This knowledge may be important for predicting their possible interactions with other xenobiotics, understanding pharmaco-/toxicokinetic and pharmacogenetic variations, toxicological risk assessment, developing suitable toxicological analysis procedures, and finally for understanding certain pitfalls in drug testing. The detection times of these drugs and/or their metabolites in biological samples are summarized and the implications of the presented data on the possible interactions of drugs of abuse with other xenobiotics, ie, inhibition or induction of individual polymorphic and nonpolymorphic isoenzymes, discussed.

Food-drug interactions precipitated by fruit juices other than grapefruit juice: An update review.

Science.gov (United States)

Chen, Meng; Zhou, Shu-Yi; Fabriaga, Erlinda; Zhang, Pian-Hong; Zhou, Quan

2018-04-01

This review addressed drug interactions precipitated by fruit juices other than grapefruit juice based on randomized controlled trials (RCTs). Literature was identified by searching PubMed, Cochrane Library, Scopus and Web of Science till December 30 2017. Among 46 finally included RCTs, six RCTs simply addressed pharmacodynamic interactions and 33 RCTs studied pharmacokinetic interactions, whereas seven RCTs investigated both pharmacokinetic and pharmacodynamic interactions. Twenty-two juice-drug combinations showed potential clinical relevance. The beneficial combinations included orange juice-ferrous fumarate, lemon juice- 99m Tc-tetrofosmin, pomegranate juice-intravenous iron during hemodialysis, cranberry juice-triple therapy medications for H. pylori, blueberry juice-etanercept, lime juice-antimalarials, and wheat grass juice-chemotherapy. The potential adverse interactions included decreased drug bioavailability (apple juice-fexofenadine, atenolol, aliskiren; orange juice-aliskiren, atenolol, celiprolol, montelukast, fluoroquinolones, alendronate; pomelo juice-sildenafil; grape juice-cyclosporine), increased bioavailability (Seville orange juice-felodipine, pomelo juice-cyclosporine, orange-aluminum containing antacids). Unlike furanocoumarin-rich grapefruit juice which could primarily precipitate drug interactions by strong inhibition of cytochrome P450 3A4 isoenzyme and P-glycoprotein and thus cause deadly outcomes due to co-ingestion with some medications, other fruit juices did not precipitate severely detrimental food-drug interaction despite of sporadic case reports. The extent of a juice-drug interaction may be associated with volume of drinking juice, fruit varieties, type of fruit, time between juice drinking and drug intake, genetic polymorphism in the enzymes or transporters and anthropometric variables. Pharmacists and health professionals should properly screen for and educate patients about potential adverse juice-drug interactions and help

The potential drug-drug interaction between proton pump inhibitors and warfarin

DEFF Research Database (Denmark)

Henriksen, Daniel Pilsgaard; Stage, Tore Bjerregaard; Hansen, Morten Rix

2015-01-01

BACKGROUND: Proton pump inhibitors (PPIs) have been suggested to increase the effect of warfarin, and clinical guidelines recommend careful monitoring of international normalized ratio (INR) when initiating PPI among warfarin users. However, this drug-drug interaction is sparsely investigated...... in a clinical setting. The aim was to assess whether initiation of PPI treatment among users of warfarin leads to increased INR values. METHODS: The study was an observational self-controlled study from 1998 to 2012 leveraging data on INR measurements on patients treated with warfarin from primary care...... and outpatient clinics and their use of prescription drugs. Data were analyzed in 2015. We assessed INR, warfarin dose, and dose/INR ratio before and after initiating PPI treatment using the paired student's t-test. RESULTS: We identified 305 warfarin users initiating treatment with PPIs. The median age was 71...

Drug-interaction-induced hemodynamically mediated acute renal failure in postsurgical patient

Directory of Open Access Journals (Sweden)

Arup K Misra

2014-01-01

Full Text Available Acute renal failure is a life threatening condition. Nonsteroidal antiinflammatory drugs (NSAIDs and cephalosporins are widely used postoperative drugs. NSAID-induced acute renal failure has been reported in the past. In this case, drug interaction and decompensated state of the patient precipitate the condition. NSAIDs inhibit prostaglandins synthesis and thus aggravate ischemia to the kidney that is already facing volume crisis due to surgery. Due to renal dysfunction, plasma ceftriaxone level increases due to decrease clearance and it also acts as nephrotoxic by unknown mechanism. On the other hand, ceftriaxone on its interaction with diclofenac for renal tubular clearance also increases the level of diclofenac and thus further aggravate the ischemia. It is a reversible condition with excluding diclofenac from the treatment regimen and giving adequate hydration to the patient. This highlights the importance of hydration and knowledge of drugs interactions in a postsurgical patient.

Adverse drug reactions and drug–drug interactions with over-the-counter NSAIDs

Directory of Open Access Journals (Sweden)

Moore N

2015-07-01

Full Text Available Nicholas Moore,1 Charles Pollack,2 Paul Butkerait2 1Department of Pharmacology, Université de Bordeaux, Bordeaux, France; 2Pfizer Consumer Healthcare, Madison, NJ, USA Abstract: Nonsteroidal anti-inflammatory drugs (NSAIDs such as ibuprofen have a long history of safe and effective use as both prescription and over-the-counter (OTC analgesics/antipyretics. The mechanism of action of all NSAIDs is through reversible inhibition of cyclooxygenase enzymes. Adverse drug reactions (ADRs including gastrointestinal bleeding as well as cardiovascular and renal effects have been reported with NSAID use. In many cases, ADRs may occur because of drug–drug interactions (DDIs between the NSAID and a concomitant medication. For example, DDIs have been reported when NSAIDs are coadministered with aspirin, alcohol, some antihypertensives, antidepressants, and other commonly used medications. Because of the pharmacologic nature of these interactions, there is a continuum of risk in that the potential for an ADR is dependent on total drug exposure. Therefore, consideration of dose and duration of NSAID use, as well as the type or class of comedication administered, is important when assessing potential risk for ADRs. Safety findings from clinical studies evaluating prescription-strength NSAIDs may not be directly applicable to OTC dosing. Health care providers can be instrumental in educating patients that using OTC NSAIDs at the lowest effective dose for the shortest required duration is vital to balancing efficacy and safety. This review discusses some of the most clinically relevant DDIs reported with NSAIDs based on major sites of ADRs and classes of medication, with a focus on OTC ibuprofen, for which the most data are available. Keywords: adverse effects, nonsteroidal anti-inflammatory drugs, gastrointestinal, cardiovascular, renal

Prevalence of possible drug-drug interactions between antiretroviral agents in different age groups in a section of the private health care sector setting in South Africa.

Science.gov (United States)

Katende-Kyenda, N L; Lubbe, M S; Serfontein, J H P; Truter, I

2008-08-01

The chronic nature of human immunodeficiency virus (HIV) infection requires lifelong highly active antiretroviral (ARV) therapy (HAART) to continuously suppress HIV-1 viral replication, thus reducing morbidity and mortality. HAART is restricted by complex dosing, drug-drug interactions (DDIs) and toxicities. To determine the prevalence of possible DDIs between ARV drugs in different age groups in a section of the private primary health care sector in South Africa. A quantitative, retrospective drug utilization review was performed on 47 085 ARV prescriptions claimed through a national medicine claims database during 2006. Possible DDIs identified were classified according to a clinical significance rating as described by Tatro [Drug Interaction Facts 2005. St Louis, MO: Facts and Comparisons (2005)]. The total number of patients who received prescriptions that were claimed through the medicine claims database was 275 424, of whom 25.11% were males, 28.28% were females and the gender of 46.61% patients was unknown. Of the total number of patients, 3.27% were HIV patients of which an average of 5.23 +/- 3.86 ARV prescriptions (n = 47 085) per patient were claimed for representing 4.73% of the total number of prescriptions claimed during the study period (N = 993 804). HIV patients received an average of 2.36 +/- 0.61 ARVs per prescription. Only 4.95% of the prescriptions had one ARV medicine item, 56.04% two, 37.10% three, 1.75% four and 6 years and 12 and 60 years with patients <40 years and < or =60 years having the highest number of DDIs and patients older than 60 years the lowest. The majority of DDIs between the ARVs presented in significance levels 2 and 4. The most important interactions were between: indinavir (IDV) and ritonavir (n = 199); efavirenz (EFV) and lopinavir/ritonavir (n = 65) and EFV and IDV (n = 60) all interacting at level 2. The importance of using drug utilization study as an identification tool to provide insight into the prescribing and

Comparative genomics allowed the identification of drug targets against human fungal pathogens

Directory of Open Access Journals (Sweden)

Martins Natalia F

2011-01-01

Full Text Available Abstract Background The prevalence of invasive fungal infections (IFIs has increased steadily worldwide in the last few decades. Particularly, there has been a global rise in the number of infections among immunosuppressed people. These patients present severe clinical forms of the infections, which are commonly fatal, and they are more susceptible to opportunistic fungal infections than non-immunocompromised people. IFIs have historically been associated with high morbidity and mortality, partly because of the limitations of available antifungal therapies, including side effects, toxicities, drug interactions and antifungal resistance. Thus, the search for alternative therapies and/or the development of more specific drugs is a challenge that needs to be met. Genomics has created new ways of examining genes, which open new strategies for drug development and control of human diseases. Results In silico analyses and manual mining selected initially 57 potential drug targets, based on 55 genes experimentally confirmed as essential for Candida albicans or Aspergillus fumigatus and other 2 genes (kre2 and erg6 relevant for fungal survival within the host. Orthologs for those 57 potential targets were also identified in eight human fungal pathogens (C. albicans, A. fumigatus, Blastomyces dermatitidis, Paracoccidioides brasiliensis, Paracoccidioides lutzii, Coccidioides immitis, Cryptococcus neoformans and Histoplasma capsulatum. Of those, 10 genes were present in all pathogenic fungi analyzed and absent in the human genome. We focused on four candidates: trr1 that encodes for thioredoxin reductase, rim8 that encodes for a protein involved in the proteolytic activation of a transcriptional factor in response to alkaline pH, kre2 that encodes for α-1,2-mannosyltransferase and erg6 that encodes for Δ(24-sterol C-methyltransferase. Conclusions Our data show that the comparative genomics analysis of eight fungal pathogens enabled the identification of

Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.

Science.gov (United States)

Yu, Hui; Mao, Kui-Tao; Shi, Jian-Yu; Huang, Hua; Chen, Zhi; Dong, Kai; Yiu, Siu-Ming

2018-04-11

Drug-drug interactions (DDIs) always cause unexpected and even adverse drug reactions. It is important to identify DDIs before drugs are used in the market. However, preclinical identification of DDIs requires much money and time. Computational approaches have exhibited their abilities to predict potential DDIs on a large scale by utilizing pre-market drug properties (e.g. chemical structure). Nevertheless, none of them can predict two comprehensive types of DDIs, including enhancive and degressive DDIs, which increases and decreases the behaviors of the interacting drugs respectively. There is a lack of systematic analysis on the structural relationship among known DDIs. Revealing such a relationship is very important, because it is able to help understand how DDIs occur. Both the prediction of comprehensive DDIs and the discovery of structural relationship among them play an important guidance when making a co-prescription. In this work, treating a set of comprehensive DDIs as a signed network, we design a novel model (DDINMF) for the prediction of enhancive and degressive DDIs based on semi-nonnegative matrix factorization. Inspiringly, DDINMF achieves the conventional DDI prediction (AUROC = 0.872 and AUPR = 0.605) and the comprehensive DDI prediction (AUROC = 0.796 and AUPR = 0.579). Compared with two state-of-the-art approaches, DDINMF shows it superiority. Finally, representing DDIs as a binary network and a signed network respectively, an analysis based on NMF reveals crucial knowledge hidden among DDIs. Our approach is able to predict not only conventional binary DDIs but also comprehensive DDIs. More importantly, it reveals several key points about the DDI network: (1) both binary and signed networks show fairly clear clusters, in which both drug degree and the difference between positive degree and negative degree show significant distribution; (2) the drugs having large degrees tend to have a larger difference between positive degree

Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine.

Science.gov (United States)

Su, Qiao; Guan, Tianbing; Lv, Haitao

2016-04-14

Uropathogenic Escherichia coli (UPEC) growth in women's bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the "interactive metabolome", which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI.

Drug Interaction between Sirolimus and Ranolazine in a Kidney Transplant Patient

Directory of Open Access Journals (Sweden)

Joanna C. Masters

2014-01-01

Full Text Available Purpose. The case of a kidney transplant recipient who experienced a probable drug interaction between sirolimus and ranolazine is reported. Summary. The narrow therapeutic window of immunosuppressive therapy in transplant recipients requires close monitoring for potential drug-drug interactions. The patient, a 57-year-old Caucasian male kidney transplant recipient, was stable for years on sirolimus as his primary immunosuppressive agent and had a history of chronic angina, for which he was prescribed ranolazine. Upon addition and dose escalation of ranolazine, whole blood sirolimus levels more than tripled, rising to immeasurably high concentrations. After holding sirolimus on multiple occasions and reducing dosage more than 50%, blood levels returned to therapeutic range, while continuing ranolazine. Conclusion. Since ranolazine is a documented P-GP and CYP3A inhibitor, and sirolimus a known substrate for both pathways, it is proposed that ranolazine inhibition of P-GP and CYP3A4 contributed to the significant elevation in sirolimus exposure. No alternative causes for the rise in sirolimus exposure were found, and assessment with the Drug Interaction Probability Scale finds this interaction to be probable. Clinicians should be aware of the potential for this interaction to cause elevated sirolimus exposure and subsequent increase in clinical effect or toxicity, in this case overimmunosuppression.

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y