[Drug-Drug Interactions with Consideration of Pharmacogenetics].

Science.gov (United States)

Ozawa, Shogo

2018-01-01

　Elderly patients often suffer from a variety of diseases and therefore may be prescribed several kinds of drugs. Interactions between these drugs may cause problems in some patients. Guidelines for drug interactions were released on July 8, 2014 "Drug Interaction Guideline for Drug Development and Labeling Recommendations (Final Draft)". These guidelines include the theoretical basis for evaluating the mechanisms of drug interaction, the possible extent of drug interactions, and take into consideration special populations (e.g., infants, children, elderly patients, patients with hepatic or renal dysfunction, and subjects with minor deficient alleles for drug metabolizing enzymes and drug transporters). In this symposium article, I discuss this last special population: altered drug metabolism and drug interactions in subjects with minor alleles of genes encoding deficient drug metabolizing enzymes. I further discuss a drug label for eliglustat (Cerdelga) with instructions for patients with ultra-rapid, extensive, intermediate, and poor metabolizer phenotypes that arise from different CYP2D6 gene alleles.

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

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.

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�

Evaluation of drug interaction microcomputer software: Dambro's Drug Interactions.

Science.gov (United States)

Poirier, T I; Giudici, R A

1990-01-01

Dambro's Drug Interactions was evaluated using general and specific criteria. The installation process, ease of learning and use were rated excellent. The user documentation and quality of the technical support were good. The scope of coverage, clinical documentation, frequency of updates, and overall clinical performance were fair. The primary advantages of the program are the quick searching and detection of drug interactions, and the attempt to provide useful interaction data, i.e., significance and reference. The disadvantages are the lack of current drug interaction information, outdated references, lack of evaluative drug interaction information, and the inability to save or print patient profiles. The program is not a good value for the pharmacist but has limited use as a quick screening tool.

Drug Interaction API

Data.gov (United States)

U.S. Department of Health & Human Services — The Interaction API is a web service for accessing drug-drug interactions. No license is needed to use the Interaction API. Currently, the API uses DrugBank for its...

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.

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...

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 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.

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.

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

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.

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

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

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.

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

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions.

Science.gov (United States)

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel; Wilkinson, Mark D

2013-04-05

The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this prototype was limited to a single knowledge domain

The SADI Personal Health Lens: A Web Browser-Based System for Identifying Personally Relevant Drug Interactions

Science.gov (United States)

Vandervalk, Ben; McCarthy, E Luke; Cruz-Toledo, José; Klein, Artjom; Baker, Christopher J O; Dumontier, Michel

2013-01-01

Background The Web provides widespread access to vast quantities of health-related information that can improve quality-of-life through better understanding of personal symptoms, medical conditions, and available treatments. Unfortunately, identifying a credible and personally relevant subset of information can be a time-consuming and challenging task for users without a medical background. Objective The objective of the Personal Health Lens system is to aid users when reading health-related webpages by providing warnings about personally relevant drug interactions. More broadly, we wish to present a prototype for a novel, generalizable approach to facilitating interactions between a patient, their practitioner(s), and the Web. Methods We utilized a distributed, Semantic Web-based architecture for recognizing personally dangerous drugs consisting of: (1) a private, local triple store of personal health information, (2) Semantic Web services, following the Semantic Automated Discovery and Integration (SADI) design pattern, for text mining and identifying substance interactions, (3) a bookmarklet to trigger analysis of a webpage and annotate it with personalized warnings, and (4) a semantic query that acts as an abstract template of the analytical workflow to be enacted by the system. Results A prototype implementation of the system is provided in the form of a Java standalone executable JAR file. The JAR file bundles all components of the system: the personal health database, locally-running versions of the SADI services, and a javascript bookmarklet that triggers analysis of a webpage. In addition, the demonstration includes a hypothetical personal health profile, allowing the system to be used immediately without configuration. Usage instructions are provided. Conclusions The main strength of the Personal Health Lens system is its ability to organize medical information and to present it to the user in a personalized and contextually relevant manner. While this

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-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

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.

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.

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.

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

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.

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

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.

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...

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...

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

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 ...

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.

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.)

Clinical relevancy and determinants of potential drug–drug interactions in chronic kidney disease patients: results from a retrospective analysis

Directory of Open Access Journals (Sweden)

Saleem A

2017-02-01

Full Text Available Ahsan Saleem,1,2 Imran Masood,1 Tahir Mehmood Khan3 1Department of Pharmacy, The Islamia University of Bahawalpur, Bahawalpur, Pakistan; 2Pharmacy Services Department, Integrated Medical Center, The Aga Khan University Hospital, Lahore, Pakistan; 3School of Pharmacy, Monash University, Sunway Campus, Selangor, Malaysia Background: Chronic kidney disease (CKD alters the pharmacokinetic and pharmacodynamic responses of various renally excreted drugs and increases the risk of drug-related problems, such as drug–drug interactions.Objectives: To assess the pattern, determinants, and clinical relevancy of potential drug–drug interactions (pDDIs in CKD patients.Materials and methods: This study retrospectively reviewed medical charts of all CKD patients admitted in the nephrology unit of a tertiary care hospital in Pakistan from January 2013 to December 2014. The Micromedex Drug-Reax® system was used to screen patient profiles for pDDIs, and IBM SPSS version 20 was used to carry out statistical analysis.Results: We evaluated 209 medical charts and found pDDIs in nearly 78.5% CKD patients. Overall, 541 pDDIs were observed, of which, nearly 60.8% patients had moderate, 41.1% had minor, 27.8% had major, and 13.4% had contraindicated interactions. Among those interactions, 49.4% had good evidence, 44.0% had fair, 6.3% had excellent evidence, and 35.5% interactions had delayed onset of action. The potential adverse outcomes of pDDIs included postural hypotension, QT prolongation, ceftriaxone–calcium precipitation, cardiac arrhythmias, and reduction in therapeutic effectiveness. The occurrence of pDDIs was found strongly associated with the age of <60 years, number of prescribed medicines ≥5, hypertension, and the lengthy hospitalization of patients.Conclusion: The occurrence of pDDIs was high in CKD patients. It was observed that CKD patients with an older age, higher number of prescribed medicines, lengthy hospitalization, and hypertension were at

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.

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

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 ...

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.

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

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.

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-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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Identifying clinically relevant drug resistance genes in drug-induced resistant cancer cell lines and post-chemotherapy tissues.

Science.gov (United States)

Tong, Mengsha; Zheng, Weicheng; Lu, Xingrong; Ao, Lu; Li, Xiangyu; Guan, Qingzhou; Cai, Hao; Li, Mengyao; Yan, Haidan; Guo, You; Chi, Pan; Guo, Zheng

2015-12-01

Until recently, few molecular signatures of drug resistance identified in drug-induced resistant cancer cell models can be translated into clinical practice. Here, we defined differentially expressed genes (DEGs) between pre-chemotherapy colorectal cancer (CRC) tissue samples of non-responders and responders for 5-fluorouracil and oxaliplatin-based therapy as clinically relevant drug resistance genes (CRG5-FU/L-OHP). Taking CRG5-FU/L-OHP as reference, we evaluated the clinical relevance of several types of genes derived from HCT116 CRC cells with resistance to 5-fluorouracil and oxaliplatin, respectively. The results revealed that DEGs between parental and resistant cells, when both were treated with the corresponding drug for a certain time, were significantly consistent with the CRG5-FU/L-OHP as well as the DEGs between the post-chemotherapy CRC specimens of responders and non-responders. This study suggests a novel strategy to extract clinically relevant drug resistance genes from both drug-induced resistant cell models and post-chemotherapy cancer tissue specimens.

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

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

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.

HIV Treatment: What is a Drug Interaction?

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... 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 ...

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

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

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

2017-02-01

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

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 ...

Community Pharmacists' Perception of the Relevance of Drug ...

African Journals Online (AJOL)

HP

Community Pharmacists' Perception of the Relevance of. Drug Package Insert as Source of Drug Information in. Southwestern Nigeria. Kenechuckwu Diobi, Titilayo O Fakeye* and Rasaq Adisa. Department of Clinical Pharmacy & Pharmacy Administration, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria.

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

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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.

Botanical-drug interactions: a scientific perspective.

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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.

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

Deep-Learning-Based Drug-Target Interaction Prediction.

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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.

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

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

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

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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.

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.

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.

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

Macrolide drug interactions: an update.

Science.gov (United States)

Pai, M P; Graci, D M; Amsden, G W

2000-04-01

To describe the current drug interaction profiles for the commonly used macrolides in the US and Europe, and to comment on the clinical impact of these interactions. A MEDLINE search (1975-1998) was performed to identify all pertinent studies, review articles, and case reports. When appropriate information was not available in the literature, data were obtained from the product manufacturers. All available data were reviewed to provide 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 company-supplied materials. Although the data were not always explicit, the best attempt was made to deliver 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. Several clinically significant drug interactions have been identified since the approval of erythromycin. These interactions usually were related to the inhibition of the cytochrome P450 enzyme systems, which are responsible for the metabolism of many drugs. The decreased metabolism by the macrolides has in some instances resulted in potentially severe adverse events. The development and marketing of newer macrolides are hoped to improve the drug interaction profile associated with this class. However, this has produced variable success. Some of the newer macrolides demonstrated an interaction profile similar to that of erythromycin; others have improved profiles. The most success in avoiding drug interactions related to the inhibition of cytochrome P450 has been through the development of the azalide subclass, of which azithromycin is the first and only to be marketed. Azithromycin has not been demonstrated to inhibit the cytochrome P450 system in studies using a human liver microsome model, and to date has produced none of the

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

[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.

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 ...

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

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...

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.

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-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.

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…

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.

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.

Investigation of bioequivalence of a new fixed-dose combination of nifedipine and candesartan with the corresponding loose combination as well as the drug-drug interaction potential between both drugs under fasting conditions.

Science.gov (United States)

Brendel, Erich; Weimann, Boris; Dietrich, Hartmut; Froede, Christoph; Thomas, Dirk

2013-09-01

To determine the bioequivalence of a nifedipine and candesartan fixed-dose combination (FDC) with the corresponding loose combination, and to investigate the pharmacokinetic drug-drug interaction potential between both drugs. 49 healthy, white, male subjects received: 60 mg nifedipine and 32 mg candesartan FDC, the loose combination of 60 mg nifedipine GITS and 32 mg candesartan, 60 mg nifedipine GITS alone, or 32 mg candesartan alone in a randomized, non-blinded, 4-period, 4-way crossover design with each dosing following overnight fasting. Treatment periods were separated by washout periods of ≥ 5 days. Plasma samples were collected for 48 hours after dosing and assayed using a validated LC-MS/MS method. Bioequivalence between the FDC and the loose combination as well as the impact of combined treatment with both drugs on candesartan pharmacokinetics was evaluated in 47 subjects, while the corresponding impact of treatment with both drugs on nifedipine pharmacokinetics was assessed in 46 patients. For AUC(0-tlast) and Cmax the 90% confidence intervals (CIs) for the ratios of the FDC vs. the corresponding loose combination were within the acceptance range for bioequivalence of 80 - 125%. When comparing AUC(0-tlast) and Cmax of nifedipine and candesartan after dosing with the loose combination vs. each drug alone, the 90% CIs remained within the range of 80 - 125% indicating the absence of a clinically relevant pharmacokinetic drug-drug interaction. Nifedipine and candesartan as well as the combinations were well tolerated. The FDC containing 60 mg nifedipine and 32 mg candesartan was bioequivalent to the corresponding loose combination following single oral doses under fasting conditions. No clinically relevant pharmacokinetic drug-drug interaction between nifedipine and candesartan was observed.

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.

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.

[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).

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".

[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.

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.

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 ...

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

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.

PXR as a mediator of herb–drug interaction

Directory of Open Access Journals (Sweden)

Brett C. Hogle

2018-04-01

Full Text Available Medicinal herbs have been a part of human medicine for thousands of years. The herb–drug interaction is an extension of drug–drug interaction, in which the consumptions of herbs cause alterations in the metabolism of drugs the patients happen to take at the same time. The pregnane X receptor (PXR has been established as one of the most important transcriptional factors that regulate the expression of phase I enzymes, phase II enzymes, and drug transporters in the xenobiotic responses. Since its initial discovery, PXR has been implicated in multiple herb–drug interactions that can lead to alterations of the drug's pharmacokinetic properties and cause fluctuating therapeutic efficacies, possibly leading to complications. Regions of the world that heavily incorporate herbalism into their primary health care and people turning to alternative medicines as a personal choice could be at risk for adverse reactions or unintended results from these interactions. This article is intended to highlight our understanding of the PXR-mediated herb–drug interactions. Keywords: Drug metabolism, Herb–drug interaction, PXR, St. John's Wort, Xenobiotics

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.

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...

Evaluation of Drug-Drug Interaction Potential Between Sacubitril/Valsartan (LCZ696) and Statins Using a Physiologically Based Pharmacokinetic Model.

Science.gov (United States)

Lin, Wen; Ji, Tao; Einolf, Heidi; Ayalasomayajula, Surya; Lin, Tsu-Han; Hanna, Imad; Heimbach, Tycho; Breen, Christopher; Jarugula, Venkateswar; He, Handan

2017-05-01

Sacubitril/valsartan (LCZ696) has been approved for the treatment of heart failure. Sacubitril is an in vitro inhibitor of organic anion-transporting polypeptides (OATPs). In clinical studies, LCZ696 increased atorvastatin C max by 1.7-fold and area under the plasma concentration-time curve by 1.3-fold, but had little or no effect on simvastatin or simvastatin acid exposure. A physiologically based pharmacokinetics modeling approach was applied to explore the underlying mechanisms behind the statin-specific LCZ696 drug interaction observations. The model incorporated OATP-mediated clearance (CL int,T ) for simvastatin and simvastatin acid to successfully describe the pharmacokinetic profiles of either analyte in the absence or presence of LCZ696. Moreover, the model successfully described the clinically observed drug effect with atorvastatin. The simulations clarified the critical parameters responsible for the observation of a low, yet clinically relevant, drug-drug interaction DDI between sacubitril and atorvastatin and the lack of effect with simvastatin acid. Atorvastatin is administered in its active form and rapidly achieves C max that coincide with the low C max of sacubitril. In contrast, simvastatin requires a hydrolysis step to the acid form and therefore is not present at the site of interactions at sacubitril concentrations that are inhibitory. Similar models were used to evaluate the drug-drug interaction risk for additional OATP-transported statins which predicted to maximally result in a 1.5-fold exposure increase. Copyright © 2017. Published by Elsevier Inc.

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)

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'.

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...

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

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...

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.

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

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

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.

Characterization of the mechanism of drug-drug interactions from PubMed using MeSH terms.

Science.gov (United States)

Lu, Yin; Figler, Bryan; Huang, Hong; Tu, Yi-Cheng; Wang, Ju; Cheng, Feng

2017-01-01

Identifying drug-drug interaction (DDI) is an important topic for the development of safe pharmaceutical drugs and for the optimization of multidrug regimens for complex diseases such as cancer and HIV. There have been about 150,000 publications on DDIs in PubMed, which is a great resource for DDI studies. In this paper, we introduced an automatic computational method for the systematic analysis of the mechanism of DDIs using MeSH (Medical Subject Headings) terms from PubMed literature. MeSH term is a controlled vocabulary thesaurus developed by the National Library of Medicine for indexing and annotating articles. Our method can effectively identify DDI-relevant MeSH terms such as drugs, proteins and phenomena with high accuracy. The connections among these MeSH terms were investigated by using co-occurrence heatmaps and social network analysis. Our approach can be used to visualize relationships of DDI terms, which has the potential to help users better understand DDIs. As the volume of PubMed records increases, our method for automatic analysis of DDIs from the PubMed database will become more accurate.

Drug-drug interactions as a result of co-administering Δ9-THC and CBD with other psychotropic agents.

Science.gov (United States)

Rong, Carola; Carmona, Nicole E; Lee, Yena L; Ragguett, Renee-Marie; Pan, Zihang; Rosenblat, Joshua D; Subramaniapillai, Mehala; Shekotikhina, Margarita; Almatham, Fahad; Alageel, Asem; Mansur, Rodrigo; Ho, Roger C; McIntyre, Roger S

2018-01-01

To determine, via narrative, non-systematic review of pre-clinical and clinical studies, whether the effect of cannabis on hepatic biotransformation pathways would be predicted to result in clinically significant drug-drug interactions (DDIs) with commonly prescribed psychotropic agents. Areas covered: A non-systematic literature search was conducted using the following databases: PubMed, PsycInfo, and Scopus from inception to January 2017. The search term cannabis was cross-referenced with the terms drug interactions, cytochrome, cannabinoids, cannabidiol, and medical marijuana. Pharmacological, molecular, and physiologic studies evaluating the pharmacokinetics of Δ 9 -tetrahydrocannabinol (Δ 9 -THC) and cannabidiol (CBD), both in vitro and in vivo, were included. Bibliographies were also manually searched for additional citations that were relevant to the overarching aim of this paper. Expert opinion: Δ 9 -Tetrahydrocannabinol and CBD are substrates and inhibitors of cytochrome P450 enzymatic pathways relevant to the biotransformation of commonly prescribed psychotropic agents. The high frequency and increasing use of cannabis invites the need for healthcare providers to familiarize themselves with potential DDIs in persons receiving select psychotropic agents, and additionally consuming medical marijuana and/or recreational marijuana.

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.

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.

Responsiveness to physicians' requests for information concerning drug interactions: a comparison of brand and generic companies.

Science.gov (United States)

Thomas, M; Lexchin, J

1990-01-01

Research-based pharmaceutical companies maintain that there are important differences between themselves and their generic competitors. Prominent among them is an alleged greater ability to provide accurate and rapid responses to requests from physicians for information about drug products. This study evaluates pharmaceutical company behavior with regard to these issues. Two drug-drug interactions were identified, along with all of the companies in Canada marketing any of the four drugs involved. Each company received a letter describing symptoms suggestive of an interaction in a patient taking its particular product and the relevant second drug. The companies were asked if they were aware of any evidence of an interaction involving the two drugs. They were also asked to provide references regarding the interaction. Responses were received from all companies contacted except one. There were no significant differences (in the hypothesized direction) between the generic and brand companies with regard to either the accuracy or promptness of the response, or the usefulness of the references cited. On the contrary, generic firms were markedly quicker to respond than were brand manufacturers. The latter were slightly more likely to acknowledge evidence of an adverse drug interaction, and to provide useful references to relevant published research.

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)

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.

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.

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.)

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...

PXR as a mediator of herb-drug interaction.

Science.gov (United States)

Hogle, Brett C; Guan, Xiudong; Folan, M Maggie; Xie, Wen

2018-04-01

Medicinal herbs have been a part of human medicine for thousands of years. The herb-drug interaction is an extension of drug-drug interaction, in which the consumptions of herbs cause alterations in the metabolism of drugs the patients happen to take at the same time. The pregnane X receptor (PXR) has been established as one of the most important transcriptional factors that regulate the expression of phase I enzymes, phase II enzymes, and drug transporters in the xenobiotic responses. Since its initial discovery, PXR has been implicated in multiple herb-drug interactions that can lead to alterations of the drug's pharmacokinetic properties and cause fluctuating therapeutic efficacies, possibly leading to complications. Regions of the world that heavily incorporate herbalism into their primary health care and people turning to alternative medicines as a personal choice could be at risk for adverse reactions or unintended results from these interactions. This article is intended to highlight our understanding of the PXR-mediated herb-drug interactions. Copyright © 2017. Published by Elsevier B.V.

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.

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.

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

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 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,

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)

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.

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.

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

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

[Potential antimicrobial drug interactions in clinical practice: consequences of polypharmacy and multidrug resistance].

Science.gov (United States)

Martínez-Múgica, Cristina

2015-12-01

Polypharmacy is a growing problem nowadays, which can increase the risk of potential drug interactions, and result in a loss of effectiveness. This is particularly relevant to the anti-infective therapy, especially when infection is produced by resistant bacteria, because therapeutic options are limited and interactions can cause treatment failure. All antimicrobial prescriptions were retrospectively reviewed during a week in the Pharmacy Department, in order to detect potential drug-interactions and analysing their clinical significance. A total of 314 antimicrobial prescriptions from 151 patients were checked. There was at least one potential interaction detected in 40% of patients, being more frequent and severe in those infected with multidrug-resistant microorganisms. Drugs most commonly involved were quinolones, azoles, linezolid and vancomycin. Potential drug interactions with antimicrobial agents are a frequent problem that can result in a loss of effectiveness. This is why they should be detected and avoided when possible, in order to optimize antimicrobial therapy, especially in case of multidrug resistant infections.

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.

Characterization of the mechanism of drug-drug interactions from PubMed using MeSH terms.

Directory of Open Access Journals (Sweden)

Yin Lu

Full Text Available Identifying drug-drug interaction (DDI is an important topic for the development of safe pharmaceutical drugs and for the optimization of multidrug regimens for complex diseases such as cancer and HIV. There have been about 150,000 publications on DDIs in PubMed, which is a great resource for DDI studies. In this paper, we introduced an automatic computational method for the systematic analysis of the mechanism of DDIs using MeSH (Medical Subject Headings terms from PubMed literature. MeSH term is a controlled vocabulary thesaurus developed by the National Library of Medicine for indexing and annotating articles. Our method can effectively identify DDI-relevant MeSH terms such as drugs, proteins and phenomena with high accuracy. The connections among these MeSH terms were investigated by using co-occurrence heatmaps and social network analysis. Our approach can be used to visualize relationships of DDI terms, which has the potential to help users better understand DDIs. As the volume of PubMed records increases, our method for automatic analysis of DDIs from the PubMed database will become more accurate.

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.

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.

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

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...

Pharmacokinetic Herb-Drug Interactions: Insight into Mechanisms and Consequences.

Science.gov (United States)

Oga, Enoche F; Sekine, Shuichi; Shitara, Yoshihisa; Horie, Toshiharu

2016-04-01

Herbal medicines are currently in high demand, and their popularity is steadily increasing. Because of their perceived effectiveness, fewer side effects and relatively low cost, they are being used for the management of numerous medical conditions. However, they are capable of affecting the pharmacokinetics and pharmacodynamics of coadministered conventional drugs. These interactions are particularly of clinically relevance when metabolizing enzymes and xenobiotic transporters, which are responsible for the fate of many drugs, are induced or inhibited, sometimes resulting in unexpected outcomes. This article discusses the general use of herbal medicines in the management of several ailments, their concurrent use with conventional therapy, mechanisms underlying herb-drug interactions (HDIs) as well as the drawbacks of herbal remedy use. The authors also suggest means of surveillance and safety monitoring of herbal medicines. Contrary to popular belief that "herbal medicines are totally safe," we are of the view that they are capable of causing significant toxic effects and altered pharmaceutical outcomes when coadministered with conventional medicines. Due to the paucity of information as well as sometimes conflicting reports on HDIs, much more research in this field is needed. The authors further suggest the need to standardize and better regulate herbal medicines in order to ensure their safety and efficacy when used alone or in combination with conventional drugs.

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

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.

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...

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.

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

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

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

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...

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

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.

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.

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...

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.

Impact of Drug Metabolism/Pharmacokinetics and Their Relevance upon Taxus-based Drug Development.

Science.gov (United States)

Hao, Da-Cheng; Ge, Guang-Bo; Wang, Ping; Yang, Ling

2018-05-22

Drug metabolism and pharmacokinetic (DMPK) studies of Taxus natural products, their semi-synthetic derivatives and analogs are indispensable in the optimization of lead compounds and clinical therapy. These studies can lead to development of new drug entities with improved absorption, distribution, metabolism, excretion and toxicity (ADME/T) profiles. To date, there have been no comprehensive reviews of the DMPK features of Taxus derived medicinal compounds.Natural and semi-synthetic taxanes may cause and could be affected by drug-drug interaction (DDI). Hence ADME/T studies of various taxane-containing formulations are important; to date these studies indicate that the role of cytochrome p450s and drug transporters is more prominent than phase II drug metabolizing enzymes. Mechanisms of taxane DMPK mediated by nuclear receptors, microRNAs, and single nucleotide polymorphisms are being revealed. Herein we review the latest knowledge on these topics, as well as the gaps in knowledge of the DMPK issues of Taxus compounds. DDIs significantly impact the PK/pharmacodynamics performance of taxanes and co-administered chemicals, which may inspire researchers to develop novel formula. While the ADME/T profiles of some taxanes are well defined, DMPK studies should be extended to more Taxus compounds, species, and Taxus -involved formulations, which would be streamlined by versatile omics platforms and computational analyses. Further biopharmaceutical investigations will be beneficial tothe translation of bench findings to the clinical applications. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

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.

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.

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

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.

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.

Dabigatran - Metabolism, Pharmacologic Properties and Drug Interactions.

Science.gov (United States)

Antonijevic, Nebojsa M; Zivkovic, Ivana D; Jovanovic, Ljubica M; Matic, Dragan M; Kocica, Mladen J; Mrdovic, Igor B; Kanjuh, Vladimir I; Culafic, Milica D

2017-01-01

The superiority of dabigatran has been well proven in the standard dosing regimen in prevention of stroke and systemic embolism in patients with non-valvular atrial fibrillation (NVAF) and extended venous thromboembolism (VTE) treatment. Dabigatran, an anticoagulant with a good safety profile, reduces intracranial bleeding in patients with atrial fibrillation and decreases major and clinically relevant non-major bleeding in acute VTE treatment. However, several important clinical issues are not fully covered by currently available directions with regard to dabigatran administration. The prominent one is reflected in the fact that dynamic impairment in renal function due to dehydratation may lead to haemorragic complications on the one hand, while on the other hand glomerular hyperfiltration may be a possible cause of dabigatran subdosing, hence reducing the drug's efficacy. Furthermore, limitations of the Cockcroft-Gault formula, considered a standard equation for assessing the renal function, may imply that other calculations are likely to obtain more accurate estimates of the kidney function in specific patient populations. Method and Conclusions: Although not routinely recommended, a possibility of monitoring dabigatran in special clinical settings adds to optimization of its dosage regimens, timely perioperative care and administration of urgently demanded thrombolytic therapy, therefore significantly improving this drug's safety profile. Despite the fact that dabigatran has fewer reported interactions with drugs, food constituents, and dietary supplements, certain interactions still remain, requiring considerable caution, notably in elderly, high bleeding risk patients, patients with decreased renal function and those on complex drug regimens. Additionally, upon approval of idarucizumab, an antidote to dabigatran solution, hitherto being a major safety concern, has been finally reached, which plays a vital role in life-threatening bleeding and emergency

Drug interactions at the human placenta: what is the evidence?

Directory of Open Access Journals (Sweden)

Miriam eRubinchik-Stern

2012-07-01

Full Text Available Pregnant women (and their fetuses are treated with a significant number of prescription and nonprescription medications. Interactions among those drugs may affect their efficacy and toxicity in both mother and fetus. Whereas interactions that result in altered drug concentrations in maternal plasma are detectable, those involving modulation of placental transfer mechanisms are rarely reflected by altered drug concentrations in maternal plasma. Therefore, they are often overlooked. Placental-mediated interactions are possible because the placenta is not only a passive diffusional barrier, but also expresses a variety of influx and efflux transporters and drug metabolizing enzymes. Current data on placental-mediated drug interactions are limited. In rodents, pharmacological or genetic manipulations of placental transporters significantly affect fetal drug exposure. In contrast, studies in human placentae suggest that the magnitude of such interactions is modest in most cases. Nevertheless, under certain circumstances, such interactions may be of clinical significance. This review describes currently known mechanisms of placental-mediated drug interactions and the potential implications of such interactions in humans. Better understanding of those mechanisms is important for minimizing fetal toxicity from drugs while improving their efficacy when directed to treat the fetus.

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

[Relevance of drug use in clinical manifestations of schizophrenia].

Science.gov (United States)

Arias Horcajadas, F; Sánchez Romero, S; Padín Calo, J J

2002-01-01

To study the association between drugs use with schizophrenia clinical manifestations. The sample consists of 82 out-patients with schizophrenia, between 18 and 45 years old. They were evaluated with Addiction Severity Index (ASI) and with Positive and Negative Syndrome Scale (PANSS). A 6 months follow up was carried out. 37,8% patients had lifetime drug dependence (including alcohol and others drugs except for tobacco). The prevalence of dependence for the different drugs were: opioids 9,8%, cocaine 11%, alcohol 29,3%, cannabis 24,4%, tobacco 68,3%, caffeine 15,9%. Drug dependent had more family and legal problems. At the multiple regression analysis it was observed that cannabis and tobacco dependence was associated with a decrease in the PANSS negative symptoms subscale, and on the contrary, alcohol dependence produces a similar intensity increase at that scoring. We don't detect any clinical relevance effects over positive symptoms. Cannabis and tobacco may improve schizophrenia negative symptoms or neuroleptic secondary effects or patients with few negative symptoms may have more predisposition to the use, on the contrary alcohol use can impairment those symptoms.

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.

Clinical Drug-Drug Pharmacokinetic Interaction Potential of Sucralfate with Other Drugs

DEFF Research Database (Denmark)

Sulochana, Suresh P; Syed, Muzeeb; Chandrasekar, Devaraj V

2016-01-01

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...

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.

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

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

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.

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

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.

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...

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.

Projecting ADME Behavior and Drug-Drug Interactions in Early Discovery and Development: Application of the Extended Clearance Classification System.

Science.gov (United States)

El-Kattan, Ayman F; Varma, Manthena V; Steyn, Stefan J; Scott, Dennis O; Maurer, Tristan S; Bergman, Arthur

2016-12-01

To assess the utility of Extended Clearance Classification System (ECCS) in understanding absorption, distribution, metabolism, and elimination (ADME) attributes and enabling victim drug-drug interaction (DDI) predictions. A database of 368 drugs with relevant ADME parameters, main metabolizing enzymes, uptake transporters, efflux transporters, and highest change in exposure (%AUC) in presence of inhibitors was developed using published literature. Drugs were characterized according to ECCS using ionization, molecular weight and estimated permeability. Analyses suggested that ECCS class 1A drugs are well absorbed and systemic clearance is determined by metabolism mediated by CYP2C, esterases, and UGTs. For class 1B drugs, oral absorption is high and the predominant clearance mechanism is hepatic uptake mediated by OATP transporters. High permeability neutral/basic drugs (class 2) showed high oral absorption, with metabolism mediated generally by CYP3A, CYP2D6 and UGTs as the predominant clearance mechanism. Class 3A/4 drugs showed moderate absorption with dominant renal clearance involving OAT/OCT2 transporters. Class 3B drugs showed low to moderate absorption with hepatic uptake (OATPs) and/or renal clearance as primary clearance mechanisms. The highest DDI risk is typically seen with class 2/1B/3B compounds manifested by inhibition of either CYP metabolism or active hepatic uptake. Class 2 showed a wider range in AUC change likely due to a variety of enzymes involved. DDI risk for class 3A/4 is small and associated with inhibition of renal transporters. ECCS provides a framework to project ADME profiles and further enables prediction of victim DDI liabilities in drug discovery and development.

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.

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…

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.

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

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

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

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.

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.

[Drugs and light].

Science.gov (United States)

Tønnesen, H H

1997-06-30

The number of drugs that are found to be photochemically unstable or able to induce phototoxic side-effects is steadily increasing. It can be difficult, however, to obtain relevant information on the photoreactivity of drugs or drug products from the commonly used handbooks. This is because of lack of standard methods of evaluation or a requirement for official specifications for a given product. The author points to the main problems connected with interactions between drugs and light in vitro and in vivo. The most obvious result of exposure to light is reduced potency of the drug because of photodecomposition. Adverse effects due to the formation of photodegradation products during storage and use have also been reported. The drug substance can further cause light-induced side-effects after administration to the patient, e.g. phototoxicity and photoallergy. More data on photoreactivity are needed in order to minimize the side-effects of frequently used drugs. The article includes a list of potential photosensitizing drug substances on the Norwegian market.

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.

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.

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.

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

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.

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

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.

Episodic memories and their relevance for psychoactive drug use and addiction.

Science.gov (United States)

Müller, Christian P

2013-01-01

The majority of adult people in western societies regularly consume psychoactive drugs. While this consumption is integrated in everyday life activities and controlled in most consumers, it may escalate and result in drug addiction. Non-addicted drug use requires the systematic establishment of highly organized behaviors, such as drug-seeking and -taking. While a significant role for classical and instrumental learning processes is well established in drug use and abuse, declarative drug memories have largely been neglected in research. Episodic memories are an important part of the declarative memories. Here a role of episodic drug memories in the establishment of non-addicted drug use and its transition to addiction is suggested. In relation to psychoactive drug consumption, episodic drug memories are formed when a person prepares for consumption, when the drug is consumed and, most important, when acute effects, withdrawal, craving, and relapse are experienced. Episodic drug memories are one-trial memories with emotional components that can be much stronger than "normal" episodic memories. Their establishment coincides with drug-induced neuronal activation and plasticity. These memories may be highly extinction resistant and influence psychoactive drug consumption, in particular during initial establishment and at the transition to "drug instrumentalization." In that, understanding how addictive drugs interact with episodic memory circuits in the brain may provide crucial information for how drug use and addiction are established.

Episodic memories and their relevance for psychoactive drug use and addiction

Directory of Open Access Journals (Sweden)

Christian P. Müller

2013-05-01

Full Text Available The majority of adult people in western societies regularly consume psychoactive drugs. While this consumption is integrated in everyday life activities and controlled in most consumers, it may escalate and result in drug addiction. Non-addicted drug use requires the systematic establishment of highly organized behaviours, such as drug seeking and -taking. While a significant role for classical and instrumental learning processes is well established in drug use and abuse, declarative drug memories have largely been neglected in research. Episodic memories are an important part of the declarative memories. Here a role of episodic drug memories in the establishment of non-addicted drug use and its transition to addiction is suggested. In relation to psychoactive drug consumption, episodic drug memories are formed when a person prepares for consumption, when the drug is consumed and, most important, when acute effects, withdrawal, craving, and relapse are experienced. Episodic drug memories are one-trial memories with emotional components that can be much stronger than ‘normal’ episodic memories. Their establishment coincides with drug-induced neuronal activation and plasticity. These memories may be highly extinction resistant and influence psychoactive drug consumption, in particular during initial establishment and at the transition to ‘drug instrumentalization’. In that, understanding how addictive drugs interact with episodic memory circuits in the brain may provide crucial information for how drug use and addiction are established.

Interaction of Drug or Food with Drug Transporters in Intestine and Liver.

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Nakanishi, Takeo; Tamai, Ikumi

2015-01-01

Oral bioavailability (F) is determined as fraction of the drug dose absorbed through the gastrointestinal membranes (Fa), the unmetabolized fraction of the absorbed dose that passes through the gut into the portal blood (Fg), and the hepatic first pass availability (Fh), namely F is expressed as the product of Fa, Fg and Fh (F = Fa.Fg.Fh). Current evidence suggests that transporter proteins play a role in intestinal absorption and hepatobiliary clearance of drugs. Among those transporters, this review will focus on PEPT1 and OATP2B1 as influx transporter and p-glycoprotein (P-gp) and BCRP as efflux transporter in intestinal epithelial cells, and on OATP1B1 and 1B3 as influx transporter and MRP2 as efflux transporter in hepatocytes, respectively, because drug-drug (DDI) and -food (DFI) interactions on these transporter are considered to affect bioavailability of their substrate drugs. DDI and DFI may reduce systemic exposure to drug by blocking influx transporters in intestine, but increase it by modulating influx and efflux transporters in liver and efflux transporters in intestines. Namely, drug disposition and efficacy are likely affected by DDI and DFI, resulting in treatment failures or increase in adverse effect. Therefore, it is of significantly importance to understand precise mechanism of DDI and DFI. This review will present information about transporter-based DDI and DFI in the processes of intestinal absorption and hepatic clearance of drugs, and discuss about their clinical implication.

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

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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.

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)

Drug-Drug Interaction Extraction via Convolutional Neural Networks

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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%.

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

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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.

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

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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

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

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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.

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

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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.

Potential intravenous drug interactions in intensive care.

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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-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

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...

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

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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.

Detection of Potential Drug-Drug Interactions for Outpatients across Hospitals

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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.

[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.

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...

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.

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

[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.

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)

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

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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.

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.

Relationship between drug interactions and drug-related negative clinical outcomes in two community pharmacies

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Gonzalo M

2009-03-01

Full Text Available Drug interactions may represent an iatrogenic risk that should be controlled in community pharmacies at the dispensing level. Aim: We analyzed the association between potential drug-drug interactions (DDIs and negative clinical outcomes.Methods: We used dispensing data from two community pharmacies: instances where drug dispensing was associated with a potential DDI and a comparison group of randomized dispensing operations with no potential DDI. In cases where potential DDIs were detected, we analyzed the underlying negative clinical outcomes. Age and gender data were included in the analysis.Results: During the study period, we registered 417 potential DDIs. The proportion of women and age were higher in the study group than in the comparison group. The average potential DDIs per patient was 1.31 (SD=0.72. The Consejo General de Colegios Oficiales de Farmacéuticos (CGCOF database did not produce an alert in 2.4% of the cases. Over-the-counter medication use was observed in 5% of the potential DDI cases. The drugs most frequently involved in potential DDIs were acenocoumarol, calcium salts, hydrochlorothiazide, and alendronic acid, whereas the most predominant potential DDIs were calcium salts and bisphosphonates, oral antidiabetics and thiazide diuretics, antidiabetics and glucose, and oral anticoagulant and paracetamol. The existence of a drug-related negative clinical outcome was observed only in 0.96% of the potential DDI cases (50% safety cases and 50% effectiveness cases. Conclusions: Only a small proportion of the detected potential DDIs lead to medication negative outcomes. Considering the drug-related negative clinical outcomes encountered, tighter control would be recommended in potential DDIs with NSAIDs or benzodiazepines.

Interaction of amphiphilic drugs with human and bovine serum albumins.

Science.gov (United States)

Khan, Abbul Bashar; Khan, Javed Masood; Ali, Mohd Sajid; Khan, Rizwan Hasan; Kabir-Ud-Din

2012-11-01

To know the interaction of amphiphilic drugs nortriptyline hydrochloride (NOT) and promazine hydrochloride (PMZ) with serum albumins (i.e., human serum albumin (HSA) and bovine serum albumin (BSA)), techniques of UV-visible, fluorescence, and circular dichroism (CD) spectroscopies are used. The binding affinity is more in case of PMZ with both the serum albumins. The quenching rate constant (k(q)) values suggest a static quenching process for all the drug-serum albumin interactions. The UV-visible results show that the change in protein conformation of PMZ-serum albumin interactions are more prominent as compared to NOT-serum albumin interactions. The CD results also explain the conformational changes in the serum albumins on binding with the drugs. The increment in %α-helical structure is slightly more for drug-BSA complexes as compared to drug-HSA complexes. Copyright © 2012 Elsevier B.V. All rights reserved.

Electrostimulated Release of Neutral Drugs from Polythiophene Nanoparticles: Smart Regulation of Drug-Polymer Interactions.

Science.gov (United States)

Puiggalí-Jou, Anna; Micheletti, Paolo; Estrany, Francesc; Del Valle, Luis J; Alemán, Carlos

2017-09-01

Poly(3,4-ethylenedioxythiophene) (PEDOT) nanoparticles are loaded with curcumin and piperine by in situ emulsion polymerization using dodecyl benzene sulfonic acid both as a stabilizer and a doping agent. The loaded drugs affect the morphology, size, and colloidal stability of the nanoparticles. Furthermore, kinetics studies of nonstimulated drug release have evidenced that polymer···drug interactions are stronger for curcumin than for piperine. This observation suggests that drug delivery systems based on combination of the former drug with PEDOT are much appropriated to show an externally tailored release profile. This is demonstrated by comparing the release profiles obtained in presence and absence of electrical stimulus. Results indicate that controlled and time-programmed release of curcumin is achieved in a physiological medium by applying a negative voltage of -1.25 V to loaded PEDOT nanoparticles. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drug-drug interactions and adverse drug reactions in polypharmacy among older adults: an integrative review 1

Science.gov (United States)

Rodrigues, Maria Cristina Soares; de Oliveira, Cesar

2016-01-01

ABSTRACT Objective: to identify and summarize studies examining both drug-drug interactions (DDI) and adverse drug reactions (ADR) in older adults polymedicated. Methods: an integrative review of studies published from January 2008 to December 2013, according to inclusion and exclusion criteria, in MEDLINE and EMBASE electronic databases were performed. Results: forty-seven full-text studies including 14,624,492 older adults (≥ 60 years) were analyzed: 24 (51.1%) concerning ADR, 14 (29.8%) DDI, and 9 studies (19.1%) investigating both DDI and ADR. We found a variety of methodological designs. The reviewed studies reinforced that polypharmacy is a multifactorial process, and predictors and inappropriate prescribing are associated with negative health outcomes, as increasing the frequency and types of ADRs and DDIs involving different drug classes, moreover, some studies show the most successful interventions to optimize prescribing. Conclusions: DDI and ADR among older adults continue to be a significant issue in the worldwide. The findings from the studies included in this integrative review, added to the previous reviews, can contribute to the improvement of advanced practices in geriatric nursing, to promote the safety of older patients in polypharmacy. However, more research is needed to elucidate gaps. PMID:27598380

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.

Comparison of three commercial knowledge bases for detection of drug-drug interactions in clinical decision support.

Science.gov (United States)

Fung, Kin Wah; Kapusnik-Uner, Joan; Cunningham, Jean; Higby-Baker, Stefanie; Bodenreider, Olivier

2017-07-01

To compare 3 commercial knowledge bases (KBs) used for detection and avoidance of potential drug-drug interactions (DDIs) in clinical practice. Drugs in the DDI tables from First DataBank (FDB), Micromedex, and Multum were mapped to RxNorm. The KBs were compared at the clinical drug, ingredient, and DDI rule levels. The KBs were evaluated against a reference list of highly significant DDIs from the Office of the National Coordinator for Health Information Technology (ONC). The KBs and the ONC list were applied to a prescription data set to simulate their use in clinical decision support. The KBs contained 1.6 million (FDB), 4.5 million (Micromedex), and 4.8 million (Multum) clinical drug pairs. Altogether, there were 8.6 million unique pairs, of which 79% were found only in 1 KB and 5% in all 3 KBs. However, there was generally more agreement than disagreement in the severity rankings, especially in the contraindicated category. The KBs covered 99.8-99.9% of the alerts of the ONC list and would have generated 25 (FDB), 145 (Micromedex), and 84 (Multum) alerts per 1000 prescriptions. The commercial KBs differ considerably in size and quantity of alerts generated. There is less variability in severity ranking of DDIs than suggested by previous studies. All KBs provide very good coverage of the ONC list. More work is needed to standardize the editorial policies and evidence for inclusion of DDIs to reduce variation among knowledge sources and improve relevance. Some DDIs considered contraindicated in all 3 KBs might be possible candidates to add to the ONC list. Published by Oxford University Press on behalf of the American Medical Informatics Association 2017. This work is written by US Government employees and is in the public domain in the United States.

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.

Interaction of platinum drugs with clinically relevant x-ray doses in mammalian cells: A comparison of cisplatin, carboplatin, iproplatin, and tetraplatin

International Nuclear Information System (INIS)

Skov, K.; MacPhail, S.

1991-01-01

Whereas the interaction between radiation and platinum complexes has never been pronounced in radiobiological experiments (to 30 Gy in mammalian cells), there have been reports of interest in this combination in the clinic, where fractionated doses of approximately 2 Gy are used. Our studies on the marked interaction in hypoxia at the 80% survival level (1-2.5 Gy) with cisplatin have been extended to second generation platinum drugs of clinical interest. The studies in the lower radiation dose region have been facilitated by the use of the cell analyzer DMIPS to identify individual cells and follow them microscopically to assess for clonogenic ability. Chinese hamster V79 cells were used, which were exposed to drug for 1 hr prior to irradiation in hypoxia (or air). None of the drugs give an enhancement ratio (ER) greater than 1.3 in the high radiation dose region, whereas all can produce ER80% (ER calculated at iso-survival of 80%) of 2 or higher at low doses in hypoxic cells. The enhancement of radiation kill in oxic V79 cells (ER's to 1.1 at 1-2% S) disappears at low doses (ER80% = 1.0) except for tetraplatin, where a moderate ER80% (to 1.64) was measured. Comparison of the hypoxic interaction on a concentration basis suggests that cisplatin is the best drug at low x-ray doses and low concentrations, but the interaction reaches a plateau at ER80% approximately 2.0. Tetraplatin continues to give better interaction with increasing concentration (up to ER80% = 3.7 at 25 microM). Interaction of radiation with the less toxic drugs, iproplatin and carboplatin, used at around 100 microM can be improved by longer exposure times prior to irradiation. Comparison on the basis of toxicity, for which the plating efficiency was used, suggests that cisplatin gives a better interaction than the three newer drugs for a given level of toxicity in hypoxic V79 cells

Cognitive enhancers (nootropics). Part 3: drugs interacting with targets other than receptors or enzymes. disease-modifying drugs.

Science.gov (United States)

Froestl, Wolfgang; Pfeifer, Andrea; Muhs, Andreas

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. The review covers the evolution of research in this field over the last 25 years.

Online drug databases: a new method to assess and compare inclusion of clinically relevant information.

Science.gov (United States)

Silva, Cristina; Fresco, Paula; Monteiro, Joaquim; Rama, Ana Cristina Ribeiro

2013-08-01

Evidence-Based Practice requires health care decisions to be based on the best available evidence. The model "Information Mastery" proposes that clinicians should use sources of information that have previously evaluated relevance and validity, provided at the point of care. Drug databases (DB) allow easy and fast access to information and have the benefit of more frequent content updates. Relevant information, in the context of drug therapy, is that which supports safe and effective use of medicines. Accordingly, the European Guideline on the Summary of Product Characteristics (EG-SmPC) was used as a standard to evaluate the inclusion of relevant information contents in DB. To develop and test a method to evaluate relevancy of DB contents, by assessing the inclusion of information items deemed relevant for effective and safe drug use. Hierarchical organisation and selection of the principles defined in the EGSmPC; definition of criteria to assess inclusion of selected information items; creation of a categorisation and quantification system that allows score calculation; calculation of relative differences (RD) of scores for comparison with an "ideal" database, defined as the one that achieves the best quantification possible for each of the information items; pilot test on a sample of 9 drug databases, using 10 drugs frequently associated in literature with morbidity-mortality and also being widely consumed in Portugal. Main outcome measure Calculate individual and global scores for clinically relevant information items of drug monographs in databases, using the categorisation and quantification system created. A--Method development: selection of sections, subsections, relevant information items and corresponding requisites; system to categorise and quantify their inclusion; score and RD calculation procedure. B--Pilot test: calculated scores for the 9 databases; globally, all databases evaluated significantly differed from the "ideal" database; some DB performed

Role of drug transporters and drug accumulation in the temporal acquisition of drug resistance

International Nuclear Information System (INIS)

Hembruff, Stacey L; Laberge, Monique L; Villeneuve, David J; Guo, Baoqing; Veitch, Zachary; Cecchetto, Melanie; Parissenti, Amadeo M

2008-01-01

Anthracyclines and taxanes are commonly used in the treatment of breast cancer. However, tumor resistance to these drugs often develops, possibly due to overexpression of drug transporters. It remains unclear whether drug resistance in vitro occurs at clinically relevant doses of chemotherapy drugs and whether both the onset and magnitude of drug resistance can be temporally and causally correlated with the enhanced expression and activity of specific drug transporters. To address these issues, MCF-7 cells were selected for survival in increasing concentrations of doxorubicin (MCF-7 DOX-2 ), epirubicin (MCF-7 EPI ), paclitaxel (MCF-7 TAX-2 ), or docetaxel (MCF-7 TXT ). During selection cells were assessed for drug sensitivity, drug uptake, and the expression of various drug transporters. In all cases, resistance was only achieved when selection reached a specific threshold dose, which was well within the clinical range. A reduction in drug uptake was temporally correlated with the acquisition of drug resistance for all cell lines, but further increases in drug resistance at doses above threshold were unrelated to changes in cellular drug uptake. Elevated expression of one or more drug transporters was seen at or above the threshold dose, but the identity, number, and temporal pattern of drug transporter induction varied with the drug used as selection agent. The pan drug transporter inhibitor cyclosporin A was able to partially or completely restore drug accumulation in the drug-resistant cell lines, but had only partial to no effect on drug sensitivity. The inability of cyclosporin A to restore drug sensitivity suggests the presence of additional mechanisms of drug resistance. This study indicates that drug resistance is achieved in breast tumour cells only upon exposure to concentrations of drug at or above a specific selection dose. While changes in drug accumulation and the expression of drug transporters does occur at the threshold dose, the magnitude of

Valerian: No Evidence for Clinically Relevant Interactions

Directory of Open Access Journals (Sweden)

Olaf Kelber

2014-01-01

Full Text Available In recent popular publications as well as in widely used information websites directed to cancer patients, valerian is claimed to have a potential of adverse interactions with anticancer drugs. This questions its use as a safe replacement for, for example, benzodiazepines. A review on the interaction potential of preparations from valerian root (Valeriana officinalis L. root was therefore conducted. A data base search and search in a clinical drug interaction data base were conducted. Thereafter, a systematic assessment of publications was performed. Seven in vitro studies on six CYP 450 isoenzymes, on p-glycoprotein, and on two UGT isoenzymes were identified. However, the methodological assessment of these studies did not support their suitability for the prediction of clinically relevant interactions. In addition, clinical studies on various valerian preparations did not reveal any relevant interaction potential concerning CYP 1A2, 2D6, 2E1, and 3A4. Available animal and human pharmacodynamic studies did not verify any interaction potential. The interaction potential of valerian preparations therefore seems to be low and thereby without clinical relevance. We conclude that there is no specific evidence questioning their safety, also in cancer patients.

Chiral drug analysis using mass spectrometric detection relevant to research and practice in clinical and forensic toxicology.

Science.gov (United States)

Schwaninger, Andrea E; Meyer, Markus R; Maurer, Hans H

2012-12-21

This paper reviews analytical approaches published in 2002-2012 for chiral drug analysis and their relevance in research and practice in the field of clinical and forensic toxicology. Separation systems such as gas chromatography, high performance liquid chromatography, capillary electromigration, and supercritical fluid chromatography, all coupled to mass spectrometry, are discussed. Typical applications are reviewed for relevant chiral analytes such as amphetamines and amphetamine-derived designer drugs, methadone, tramadol, psychotropic and other CNS acting drugs, anticoagulants, cardiovascular drugs, and some other drugs. Usefulness of chiral drug analysis in the interpretation of analytical results in clinical and forensic toxicology is discussed as well. Copyright © 2012 Elsevier B.V. All rights reserved.

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

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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.

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.

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.

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 ...

Characterization of the interaction forces in a drug carrier complex of doxorubicin with a drug-binding peptide.

Science.gov (United States)

Gocheva, Gergana; Ilieva, Nina; Peneva, Kalina; Ivanova, Anela

2018-04-01

Polypeptide-based materials are used as building blocks for drug delivery systems aimed at toxicity decrease in chemotherapeutics. A molecular-level approach is adopted for investigating the non-covalent interactions between doxorubicin and a recently synthesized drug-binging peptide as a key part of a system for delivery to neoplastic cells. Molecular dynamics simulations in aqueous solution at room and body temperature are applied to investigate the structure and the binding modes within the drug-peptide complex. The tryptophans are outlined as the main chemotherapeutic adsorption sites, and the importance of their placement in the peptide sequence is highlighted. The drug-peptide binging energy is evaluated by density functional theory calculations. Principal component analysis reveals comparable importance of several types of interaction for the binding strength. π-Stacking is dominant, but other factors are also significant: intercalation, peptide backbone stacking, electrostatics, dispersion, and solvation. Intra- and intermolecular H-bonding also stabilizes the complexes. The influence of solvent molecules on the binding energy is mild. The obtained data characterize the drug-to-peptide attachment as a mainly attractive collective process with interactions spanning a broad range of values. These results explain with atomistic detail the experimentally registered doxorubicin-binging ability of the peptide and outline the complex as a prospective carrying unit that can be employed in design of drug delivery systems. © 2017 John Wiley & Sons A/S.

A facile drug delivery system preparation through the interaction between drug and iron ion of transferrin

International Nuclear Information System (INIS)

Zhou, Lin; Liu, Jihua; Wei, Shaohua; Ge, Xuefeng; Zhou, Jiahong; Yu, Boyang; Shen, Jian

2013-01-01

Many anticancer drugs have the capability to form stable complex with metal ions. Based on such property, a simple method to combine these drugs with transferrin, through the interaction between drug and Fe ion of transferrin, to improve their anticancer activity, is proposed. To demonstrate this technique, the complex of photosensitive anticancer drug hypocrellin A and transferrin was prepared by such facile method. The results indicated that the complex of hypocrellin A and transferrin can stabilize in aqueous solution. In vitro studies have demonstrated the superior cancer cell uptake ability of hypocrellin A–transferrin complex to the free hypocrellin A. Significant damage to such drug-impregnated tumor cells was observed upon irradiation and the cancer cells killing ability of hypocrellin A–transferrin was stronger than the free hypocrellin A within a certain range of concentrations. The above results demonstrated the validity and potential of our proposed strategy to prepare the drug delivery system of this type of anti-cancer drugs and transferrin

A facile drug delivery system preparation through the interaction between drug and iron ion of transferrin

Energy Technology Data Exchange (ETDEWEB)

Zhou, Lin [Nanjing Normal University, Jiangsu Key Laboratory Biofunctional Materials, Key Laboratory of Applied Photochemistry, Analysis and Testing Center, College of Chemistry and Materials Science (China); Liu, Jihua [China Pharmaceutical University, Department of Complex Prescription of TCM (China); Wei, Shaohua; Ge, Xuefeng; Zhou, Jiahong, E-mail: zhoujiahong@njnu.edu.cn [Nanjing Normal University, Jiangsu Key Laboratory Biofunctional Materials, Key Laboratory of Applied Photochemistry, Analysis and Testing Center, College of Chemistry and Materials Science (China); Yu, Boyang, E-mail: boyangyu59@163.com [China Pharmaceutical University, Department of Complex Prescription of TCM (China); Shen, Jian [Nanjing Normal University, Jiangsu Key Laboratory Biofunctional Materials, Key Laboratory of Applied Photochemistry, Analysis and Testing Center, College of Chemistry and Materials Science (China)

2013-09-15

Many anticancer drugs have the capability to form stable complex with metal ions. Based on such property, a simple method to combine these drugs with transferrin, through the interaction between drug and Fe ion of transferrin, to improve their anticancer activity, is proposed. To demonstrate this technique, the complex of photosensitive anticancer drug hypocrellin A and transferrin was prepared by such facile method. The results indicated that the complex of hypocrellin A and transferrin can stabilize in aqueous solution. In vitro studies have demonstrated the superior cancer cell uptake ability of hypocrellin A-transferrin complex to the free hypocrellin A. Significant damage to such drug-impregnated tumor cells was observed upon irradiation and the cancer cells killing ability of hypocrellin A-transferrin was stronger than the free hypocrellin A within a certain range of concentrations. The above results demonstrated the validity and potential of our proposed strategy to prepare the drug delivery system of this type of anti-cancer drugs and transferrin.

EXPLORING THE PATTERN OF POLYPHARMACY AND PROPORTION OF DRUG TO DRUG INTERACTIONS AND ADVERSE DRUG REACTIONS IN THE ELDERLY

Directory of Open Access Journals (Sweden)

Vijayashree Thyagaraj

2017-07-01

Full Text Available BACKGROUND The geriatric population is increasing as a result of advanced medical facilities. This population also faces a number of medical health challenges. They tend to receive multiple medications often leading to Drug-Drug Interactions (DDIs Adverse Drug Reactions (ADRs and other clinical consequences, which compromises their quality of life if not endangering it as well. There are few Indian studies focusing on this problem. Hence, this study was undertaken with the aim to assess the polypharmacy pattern, proportion of DDIs and adverse drug reactions in the geriatric population in a tertiary care hospital. MATERIALS AND METHODS This was a cross-sectional study wherein data from 201 geriatric inpatient’s prescriptions were collected. The prescriptions were assessed for demographic details such as age, gender, comorbidities and drugs prescribed. All prescriptions were evaluated for polypharmacy, DDIs and ADRs. DDIs were assessed using Micromedex software. Patients were stratified into groups and DDIs were compared between the groups, gender and also with number of drugs used. RESULTS There were 201 patients with a mean age of approximately 70 years. Polypharmacy occurred in 73.63% of them with mean number of drugs being 6.23. The number of drugs used increased significantly with age (p=0.0001. Hypertension was the most common comorbidity. Polypharmacy was strongly associated with hypertension and dyslipidaemia. A total of 129 (64.17% patients accounted for 425 potential DDIs. The most common drug involved in DDIs was aspirin. A subset analysis of ADRs showed an occurrence of 50.68% with 10.81% being definitely avoidable. CONCLUSION Elderly individuals are at increased risk of being on polypharmacy. This comes with the risk of several potential DDIs, which in turn may lead to adverse drug reactions, which results in morbidity. Doctors involved in the care of the elderly should be aware of these facts and exercise caution while adding any

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.

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.

Inhibitory effects of drugs on the metabolic activity of mouse and human aldehyde oxidases and influence on drug-drug interactions.

Science.gov (United States)

Takaoka, Naoki; Sanoh, Seigo; Okuda, Katsuhiro; Kotake, Yaichiro; Sugahara, Go; Yanagi, Ami; Ishida, Yuji; Tateno, Chise; Tayama, Yoshitaka; Sugihara, Kazumi; Kitamura, Shigeyuki; Kurosaki, Mami; Terao, Mineko; Garattini, Enrico; Ohta, Shigeru

2018-04-17

As aldehyde oxidase (AOX) plays an emerging role in drug metabolism, understanding its significance for drug-drug interactions (DDI) is important. Therefore, we tested 10 compounds for species-specific and substrate-dependent differences in the inhibitory effect of AOX activity using genetically engineered HEK293 cells over-expressing human AOX1, mouse AOX1 or mouse AOX3. The IC 50 values of 10 potential inhibitors of the three AOX enzymes were determined using phthalazine and O 6 -benzylguanine as substrates. 17β-Estradiol, menadione, norharmane and raloxifene exhibited marked differences in inhibitory effects between the human and mouse AOX isoforms when the phthalazine substrate was used. Some of the compounds tested exhibited substrate-dependent differences in their inhibitory effects. Docking simulations with human AOX1 and mouse AOX3 were conducted for six representative inhibitors. The rank order of the minimum binding energy reflected the order of the corresponding IC 50 values. We also evaluated the potential DDI between an AOX substrate (O 6 -benzylguanine) and an inhibitor (hydralazine) using chimeric mice with humanized livers. Pretreatment of hydralazine increased the maximum plasma concentration (C max ) and the area under the plasma concentration-time curve (AUC 0-24 ) of O 6 -benzylguanine compared to single administration. Our in vitro data indicate species-specific and substrate-dependent differences in the inhibitory effects on AOX activity. Our in vivo data demonstrate the existence of a DDI which may be of relevance in the clinical context. Copyright © 2018 Elsevier Inc. All rights reserved.

Diclofenac hypersensitivity: antibody responses to the parent drug and relevant metabolites.

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Andrea Harrer

2010-10-01

Full Text Available Hypersensitivity reactions against nonsteroidal antiinflammatory drugs (NSAIDs like diclofenac (DF can manifest as Type I-like allergic reactions including systemic anaphylaxis. However, except for isolated case studies experimental evidence for an IgE-mediated pathomechanism of DF hypersensitivity is lacking. In this study we aimed to investigate the possible involvement of drug- and/or metabolite-specific antibodies in selective DF hypersensitivity.DF, an organochemically synthesized linkage variant, and five major Phase I metabolites were covalently coupled to carrier proteins. Drug conjugates were analyzed for coupling degree and capacity to crosslink receptor-bound IgE antibodies from drug-sensitized mice. With these conjugates, the presence of hapten-specific IgE antibodies was investigated in patients' samples by ELISA, mediator release assay, and basophil activation test. Production of sulfidoleukotrienes by drug conjugates was determined in PBMCs from DF-hypersensitive patients. All conjugates were shown to carry more than two haptens per carrier molecule. Immunization of mice with drug conjugates induced drug-specific IgE antibodies capable of triggering mediator release. Therefore, the conjugates are suitable tools for detection of drug-specific antibodies and for determination of their anaphylactic activity. Fifty-nine patients were enrolled and categorized as hypersensitive either selectively to DF or to multiple NSAIDs. In none of the patients' samples evidence for drug/metabolite-specific IgE in serum or bound to allergic effector cells was found. In contrast, a small group of patients (8/59, 14% displayed drug/metabolite-specific IgG.We found no evidence for an IgE-mediated effector mechanism based on haptenation of protein carriers in DF-hypersensitive patients. Furthermore, a potential involvement of the most relevant metabolites in DF hypersensitivity reactions could be excluded.

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.

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 ...

Exploring drug-target interaction networks of illicit drugs

OpenAIRE

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

2013-01-01

Background 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 dru...

Clinical relevance of drug binding to plasma proteins

Science.gov (United States)

Ascenzi, Paolo; Fanali, Gabriella; Fasano, Mauro; Pallottini, Valentina; Trezza, Viviana

2014-12-01

Binding to plasma proteins highly influences drug efficacy, distribution, and disposition. Serum albumin, the most abundant protein in plasma, is a monomeric multi-domain macromolecule that displays an extraordinary ligand binding capacity, providing a depot and carrier for many endogenous and exogenous compounds, such as fatty acids and most acidic drugs. α-1-Acid glycoprotein, the second main plasma protein, is a glycoprotein physiologically involved in the acute phase reaction and is the main carrier for basic and neutral drugs. High- and low-density lipoproteins play a limited role in drug binding and are natural drug delivery system only for few lipophilic drugs or lipid-based formulations. Several factors influence drug binding to plasma proteins, such as pathological conditions, concurrent administration of drugs, sex, and age. Any of these factors, in turn, influences drug efficacy and toxicity. Here, biochemical, biomedical, and biotechnological aspects of drug binding to plasma proteins are reviewed.

Drug-drug Interactions of Statins Potentially Leading to Muscle-Related Side Effects in Hospitalized Patients.

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Bucsa, Camelia; Farcas, Andreea; Leucuta, D; Mogosan, Cristina; Bojita, M; Dumitrascu, D L

2015-01-01

The associations of drugs that may interact with the statins resulting in elevated serum concentration of the statins are an important risk factor for statin induced muscle disorders. We aimed to determine the prevalence of these associations in all hospitalized patients that had been prescribed statins before/during hospitalization and to find out how often they are associated with muscle-related side effects. This prospective, non-interventional study performed in two internal medicine departments included patients with statin therapy before/during hospitalization. Data on each patient demographic characteristics, co-morbidities and treatment was collected from medical charts and interviews. We evaluated patients' therapy for the targeted associations using Thomson Micromedex Drug Interactions checker and we ranked the identified drug-drug interactions (DDIs) accordingly. Each patient with statin treatment before admission was additionally interviewed in order to identify muscular symptoms. In 109 patients on statin treatment we found 35 potential (p) DDIs of statins in 30 (27.5%) patients, most of which were in the therapy before admission (27 pDDIs). The pDDIs were moderate (20 pDDIs) and major (15 pDDIs). Of the total number of pDDIs, 24 were targeting the muscular system. The drugs most frequently involved in the statins' pDDIs were amiodarone and fenofibrate. Two of the patients with pDDIs reported muscle pain, both having additional risk factors for statin induced muscular effects. The prevalence of statins' pDDIs was high in our study, mostly in the therapy before admission, with only a small number of pDDIs resulting in clinical outcome.

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.

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.)

A review of pharmacokinetic drug-drug interactions with the anthelmintic medications albendazole and mebendazole.

Science.gov (United States)

Pawluk, Shane Ashley; Roels, Craig Allan; Wilby, Kyle John; Ensom, Mary H H

2015-04-01

Medications indicated for helminthes and other parasitic infections are frequently being used in mass populations in endemic areas. Currently, there is a lack of guidance for clinicians on how to appropriately manage drug interactions when faced with patients requiring short-term anthelmintic therapy with albendazole or mebendazole while concurrently taking other agents. The objective of this review was to systematically summarize and evaluate published literature on the pharmacokinetics of albendazole or mebendazole when taken with other interacting medications. A search of MEDLINE (1946 to October 2014), EMBASE (1974 to October 2014), International Pharmaceutical Abstracts (1970 to October 2014), Google, and Google Scholar was conducted for articles describing the pharmacokinetics of albendazole or mebendazole when given with other medications (and supplemented by a bibliographic review of all relevant articles). Altogether, 17 articles were included in the review. Studies reported data on pharmacokinetic parameters for albendazole or mebendazole when taken with cimetidine, dexamethasone, ritonavir, phenytoin, carbamazepine, phenobarbital, ivermectin, praziquantel, diethylcarbamazine, azithromycin, and levamisole. Cimetidine increased the elimination half-life of albendazole and maximum concentration (Cmax) of mebendazole; dexamethasone increased the area under the plasma concentration-time curve (AUC) of albendazole; levamisole decreased the Cmax of albendazole; anticonvulsants (phenytoin, phenobarbital, carbamazepine) decreased the AUC of albendazole; praziquantel increased the AUC of albendazole; and ritonavir decreased the AUC of both albendazole and mebendazole. No major interactions were found with ivermectin, azithromycin, or diethylcarbamazine. Future research is required to clarify the clinical relevance of the interactions observed.

Analysis of Drugs Interaction among Pediatric Inpatients at Hospital in Palu

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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.

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

Science.gov (United States)

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

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

Drug development in neuropsychopharmacology.

Science.gov (United States)

Fritze, Jürgen

2008-03-01

Personalized medicine is still in its infancy concerning drug development in neuropsychopharmacology. Adequate biomarkers with clinical relevance to drug response and/or tolerability and safety largely remain to be identified. Possibly, this kind of personalized medicine will first gain clinical relevance in the dementias. The clinical relevance of the genotyping of drug-metabolizing enzymes as suggested by drug licensing authorities for the pharmacokinetic evaluation of medicinal products needs to be proven in sound clinical trials.

Prevalence and typology of potential drug interactions occurring in primary care patients.

Science.gov (United States)

Lopez-Picazo, Julio J; Ruiz, Juan C; Sanchez, Jose F; Ariza, Angeles; Aguilera, Belen; Lazaro, Dolores; Sanz, Gonzalo R

2010-06-01

To investigate the prevalence and types of potential drug interactions in primary care patients to detect risky prescriptions as an essential condition to design intervention policies leading to an improvement in patient safety. Cross-sectional descriptive study. Two areas in Spain comprising 715,661 inhabitants. 430,525 subjects with electronic medical records and assigned to a family doctor regularly updating them. On a random day, 29.4% of the population was taking medication. Of these, 73.9% were at risk of suffering interactions, and these were found in 20.6% of them. The amount of interactions was higher among people with chronic conditions, the elderly, females and polymedicated patients. From the total of interactions, 55.1% belonged to the highest clinical relevance 'A' level, and 28.3% should have been avoided. The active ingredients primarily involved were hydrochlorothiazide and ibuprofen and, when focusing on those that should be avoided, omeprazole and acenocoumarol. The most frequent 'A' interaction that should be avoided was between non-conjugated excreted benzodiazepines and proton-pump inhibitors, followed by some NSAIDs and diuretics. 1 in 20 Spanish citizens is currently undergoing a potential drug interaction, including a high rate of clinically relevant ones that should be avoided. These results confirm the existence of a serious safety issue that should be approached and where all parties involved (physicians, health services, medical societies and patients) must do our bit to improve. Health services should foster the implementation of prescription alert systems linked with electronic medical records including clinical data.

Targeting molecular networks for drug research

Directory of Open Access Journals (Sweden)

José Pedro Pinto

2014-06-01

Full Text Available The study of molecular networks has recently moved into the limelight of biomedical research. While it has certainly provided us with plenty of new insights into cellular mechanisms, the challenge now is how to modify or even restructure these networks. This is especially true for human diseases, which can be regarded as manifestations of distorted states of molecular networks. Of the possible interventions for altering networks, the use of drugs is presently the most feasible. In this mini-review, we present and discuss some exemplary approaches of how analysis of molecular interaction networks can contribute to pharmacology (e.g., by identifying new drug targets or prediction of drug side effects, as well as listing pointers to relevant resources and software to guide future research. We also outline recent progress in the use of drugs for in vitro reprogramming of cells, which constitutes an example par excellence for altering molecular interaction networks with drugs.

Thermodynamic Studies for Drug Design and Screening

Science.gov (United States)

Garbett, Nichola C.; Chaires, Jonathan B.

2012-01-01

Introduction A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. Areas covered This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 – 2011 using the Science Citation Index and PUBMED and the keywords listed below. Expert opinion The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically-driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development towards an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design. PMID:22458502

Thermodynamic studies for drug design and screening.

Science.gov (United States)

Garbett, Nichola C; Chaires, Jonathan B

2012-04-01

A key part of drug design and development is the optimization of molecular interactions between an engineered drug candidate and its binding target. Thermodynamic characterization provides information about the balance of energetic forces driving binding interactions and is essential for understanding and optimizing molecular interactions. This review discusses the information that can be obtained from thermodynamic measurements and how this can be applied to the drug development process. Current approaches for the measurement and optimization of thermodynamic parameters are presented, specifically higher throughput and calorimetric methods. Relevant literature for this review was identified in part by bibliographic searches for the period 2004 - 2011 using the Science Citation Index and PUBMED and the keywords listed below. The most effective drug design and development platform comes from an integrated process utilizing all available information from structural, thermodynamic and biological studies. Continuing evolution in our understanding of the energetic basis of molecular interactions and advances in thermodynamic methods for widespread application are essential to realize the goal of thermodynamically driven drug design. Comprehensive thermodynamic evaluation is vital early in the drug development process to speed drug development toward an optimal energetic interaction profile while retaining good pharmacological properties. Practical thermodynamic approaches, such as enthalpic optimization, thermodynamic optimization plots and the enthalpic efficiency index, have now matured to provide proven utility in the design process. Improved throughput in calorimetric methods remains essential for even greater integration of thermodynamics into drug design. © 2012 Informa UK, Ltd.

Oscillatory Shear Rheology in Examining the Drug-Polymer Interactions Relevant in Hot Melt Extrusion

DEFF Research Database (Denmark)

Aho, Johanna; Edinger, Magnus; Botker, Johan

2016-01-01

The flow properties of drug-polymer mixtures have a significant influence on their processability when using techniques such as hot melt extrusion (HME). Suitable extrusion temperature and screw speed to be used in laboratory scale HME were evaluated for mixtures containing 30% of paracetamol (PRC...... of the drug substances. Consecutively, the mixtures were extruded, and the maximum plasticizing weight fraction of each drug was determined by means of rheological measurements. IBU was found to have an efficient plasticizing functionality, decreasing the viscosity of the mixtures even above its apparent...

Hospitalization due to Adverse Drug Reactions and Drug Interactions before and after HAART

Directory of Open Access Journals (Sweden)

Michelle M Foisy

2000-01-01

Full Text Available OBJECTIVE: To characterize and compare the rates of adverse drug reactions (ADRs and interactions on admission in two, one-year periods: pre-highly active antiretroviral therapy (HAART (phase 1 and post-HAART (phase 2.

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.

Radiopharmaceuticals drug interactions: a critical review

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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

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

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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.

An introduction to predictive modelling of drug concentration in anaesthesia monitors.

Science.gov (United States)

DeCou, J; Johnson, K

2017-01-01

A significant amount of anaesthetists' work involves the prediction of drug effects and interactions to produce a smooth general anaesthetic that minimises drug side effects and promotes rapid emergence. Successfully managing this process requires a basic understanding of drug effects, experience and inevitably some guesswork, since it is difficult (and in some cases impossible) to anticipate all relevant patient and surgical factors. Although data are generally available to allow calculation of plasma drug and effect site concentrations, this is often difficult to apply in complex clinical contexts, particularly when multiple drug types are used. In recent years, manufacturers have developed and incorporated into anaesthetic workstations technologies that use drug pharmacodynamic and pharmacokinetic data to predict drug effects and interactions. Such systems can predict the duration and effects of drugs during anaesthesia and assist the anaesthetist to understand complex drug interactions. With this information available, different drug types, doses and combinations may be tailored in a scientific way to maximise useful effects whilst minimising overdose and side-effects, particularly in high-risk patients. Examples are used to illustrate how such systems can be used in practice, and how drug effects and interactions can be simulated to "rehearse" an anaesthetic before any drugs are actually administered. At present only a small number of anaesthetic workstations use this technology, and as yet they are not able to manage all drugs used in anaesthetic practice. However, such systems have the potential to help anaesthetists manage the complexity of their work, and to provide information on predicted drug effects in a way that is useful and relevant to both experienced anaesthetists and trainees. © 2017 The Association of Anaesthetists of Great Britain and Ireland.

Drug-Drug/Drug-Excipient Compatibility Studies on Curcumin using Non-Thermal Methods

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Moorthi Chidambaram

2014-05-01

Full Text Available Purpose: Curcumin is a hydrophobic polyphenol isolated from dried rhizome of turmeric. Clinical usefulness of curcumin in the treatment of cancer is limited due to poor aqueous solubility, hydrolytic degradation, metabolism, and poor oral bioavailability. To overcome these limitations, we proposed to fabricate curcumin-piperine, curcumin-quercetin and curcumin-silibinin loaded polymeric nanoformulation. However, unfavourable combinations of drug-drug and drug-excipient may result in interaction and rises the safety concern. Hence, the present study was aimed to assess the interaction of curcumin with excipients used in nanoformulations. Methods: Isothermal stress testing method was used to assess the compatibility of drug-drug/drug-excipient. Results: The combination of curcumin-piperine, curcumin-quercetin, curcumin-silibinin and the combination of other excipients with curcumin, piperine, quercetin and silibinin have not shown any significant physical and chemical instability. Conclusion: The study concludes that the curcumin, piperine, quercetin and silibinin is compatible with each other and with other excipients.

Drug-mineral interactions

International Nuclear Information System (INIS)

Kramer, L.

1986-01-01

The effect of drugs such as glucocorticoids and thyroid extract on calcium metabolism is unknown. However, several other medications affect the excretion and intestinal absorption of calcium. A controlled study was carried out to investigate these aspects. Urinary calcium was determined for 3 months during the long-term intake of the antituberculous drug isoniazid (INH) and of the antibiotic tetracycline. The effect of the diuretics furosemide and hydrochlorothiazide, of several aluminum-containing antacids, of thyroid extract and of corticosteroids was also studied. Metabolic balances of calcium, phosphorus, magnesium and zinc were determined, as well as the intestinal absorption of calcium using Ca 47. Plasma levels, urinary and fecal excretions of Ca 47 were determined. All drugs tested increased urinary calcium except for the diuretic hydrochlorothiazide. Regarding the effect of corticosteroids: the intestinal absorption of calcium was unchanged after the short-term use and was very high after long-term use. The studies have shown that several commonly used drugs induce an increase in urinary calcium excretion which may contribute to calcium loss, if this increase persists for prolonged periods of time. Urinary excretions of phosphorus, magnesium and zinc increased in some of the studies

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

Science.gov (United States)

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

2017-10-10

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

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…

Impact of the CYP2C8 *3 polymorphism on the drug-drug interaction between gemfibrozil and pioglitazone.

Science.gov (United States)

Aquilante, Christina L; Kosmiski, Lisa A; Bourne, David W A; Bushman, Lane R; Daily, Elizabeth B; Hammond, Kyle P; Hopley, Charles W; Kadam, Rajendra S; Kanack, Alexander T; Kompella, Uday B; Le, Merry; Predhomme, Julie A; Rower, Joseph E; Sidhom, Maha S

2013-01-01

The objective of this study was to determine the extent to which the CYP2C8*3 allele influences pharmacokinetic variability in the drug-drug interaction between gemfibrozil (CYP2C8 inhibitor) and pioglitazone (CYP2C8 substrate). In this randomized, two phase crossover study, 30 healthy Caucasian subjects were enrolled based on CYP2C8*3 genotype (n = 15, CYP2C8*1/*1; n = 15, CYP2C8*3 carriers). Subjects received a single 15 mg dose of pioglitazone or gemfibrozil 600 mg every 12 h for 4 days with a single 15 mg dose of pioglitazone administered on the morning of day 3. A 48 h pharmacokinetic study followed each pioglitazone dose and the study phases were separated by a 14 day washout period. Gemfibrozil significantly increased mean pioglitazone AUC(0,∞) by 4.3-fold (P gemfibrozil administration was significantly influenced by CYP2C8 genotype. Specifically, CYP2C8*3 carriers had a 5.2-fold mean increase in pioglitazone AUC(0,∞) compared with a 3.3-fold mean increase in CYP2C8*1 homozygotes (P = 0.02). CYP2C8*3 is associated with decreased pioglitazone plasma exposure in vivo and significantly influences the pharmacokinetic magnitude of the gemfibrozil-pioglitazone drug-drug interaction. Additional studies are needed to evaluate the impact of CYP2C8 genetics on the pharmacokinetics of other CYP2C8-mediated drug-drug interactions. © 2012 The Authors. British Journal of Clinical Pharmacology © 2012 The British Pharmacological Society.

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...

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.

Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives.

Science.gov (United States)

Nath, Abhigyan; Kumari, Priyanka; Chaube, Radha

2018-01-01

Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug targets and their interactions can be very useful for drug repurposing. Supervised machine learning methods have been very useful in drug target prediction and in prediction of drug target interactions. Here, we describe the details for developing prediction models using supervised learning techniques for human drug target prediction and their interactions.

Industry Perspectives on Market Access of Innovative Drugs: The Relevance for Oncology Drugs

OpenAIRE

Pauwels, Kim; Huys, Isabelle; Casteels, Minne; Simoens, Steven

2016-01-01

Key Points - Representatives of the pharmaceutical industry call for a broader recognition of value within the assessment and appraisal of innovative drugs - Focus on value within the assessment and appraisal of drugs is jeopardized by financial drives as the side of industry and at the side of the payers - A well–considered value-framework, with attention for patient reported outcomes, societal preferences and dynamic approach on the drug life cycle, needs to be incorporated in ass...

Drug cocktail optimization in chemotherapy of cancer.

Directory of Open Access Journals (Sweden)

Saskia Preissner

Full Text Available BACKGROUND: In general, drug metabolism has to be considered to avoid adverse effects and ineffective therapy. In particular, chemotherapeutic drug cocktails strain drug metabolizing enzymes especially the cytochrome P450 family (CYP. Furthermore, a number of important chemotherapeutic drugs such as cyclophosphamide, ifosfamide, tamoxifen or procarbazine are administered as prodrugs and have to be activated by CYP. Therefore, the genetic variability of these enzymes should be taken into account to design appropriate therapeutic regimens to avoid inadequate drug administration, toxicity and inefficiency. OBJECTIVE: The aim of this work was to find drug interactions and to avoid side effects or ineffective therapy in chemotherapy. DATA SOURCES AND METHODS: Information on drug administration in the therapy of leukemia and their drug metabolism was collected from scientific literature and various web resources. We carried out an automated textmining approach. Abstracts of PubMed were filtered for relevant articles using specific keywords. Abstracts were automatically screened for antineoplastic drugs and their synonyms in combination with a set of human CYPs in title or abstract. RESULTS: We present a comprehensive analysis of over 100 common cancer treatment regimens regarding drug-drug interactions and present alternatives avoiding CYP overload. Typical concomitant medication, e.g. antiemetics or antibiotics is a preferred subject to improvement. A webtool, which allows drug cocktail optimization was developed and is publicly available on http://bioinformatics.charite.de/chemotherapy.

DRUG POLICY AND DRUG ADDICTION IN TURKEY

OpenAIRE

İLHAN, Mustafa Necmi

2018-01-01

The NationalStrategy Document on Drugs and Emergency Action Plan started with thecontributions of all the relevant institutions within the year of 2014 wasprepared and after that in accordance with the Prime Ministry Notice entitledFight Against Drugs published within this scope, the committees for FightAgainst Drugs were established (under the presidency of Deputy Prime Ministerand with the help of Ministry of Health, Ministry of Justice, Ministry of Laborand Social Security, Ministry of Fam...

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

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

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.

Novel Methods for Drug-Target Interaction Prediction using Graph Mining

KAUST Repository

Ba Alawi, Wail

2016-08-31

The problem of developing drugs that can be used to cure diseases is important and requires a careful approach. Since pursuing the wrong candidate drug for a particular disease could be very costly in terms of time and money, there is a strong interest in minimizing such risks. Drug repositioning has become a hot topic of research, as it helps reduce these risks significantly at the early stages of drug development by reusing an approved drug for the treatment of a different disease. Still, finding new usage for a drug is non-trivial, as it is necessary to find out strong supporting evidence that the proposed new uses of drugs are plausible. Many computational approaches were developed to narrow the list of possible candidate drug-target interactions (DTIs) before any experiments are done. However, many of these approaches suffer from unacceptable levels of false positives. We developed two novel methods based on graph mining networks of drugs and targets. The first method (DASPfind) finds all non-cyclic paths that connect a drug and a target, and using a function that we define, calculates a score from all the paths. This score describes our confidence that DTI is correct. We show that DASPfind significantly outperforms other state-of-the-art methods in predicting the top ranked target for each drug. We demonstrate the utility of DASPfind by predicting 15 novel DTIs over a set of ion channel proteins, and confirming 12 out of these 15 DTIs through experimental evidence reported in literature and online drug databases. The second method (DASPfind+) modifies DASPfind in order to increase the confidence and reliability of the resultant predictions. Based on the structure of the drug-target interaction (DTI) networks, we introduced an optimization scheme that incrementally alters the network structure locally for each drug to achieve more robust top 1 ranked predictions. Moreover, we explored effects of several similarity measures between the targets on the prediction

Evaluation of transporters in drug development: Current status and contemporary issues.

Science.gov (United States)

Lee, Sue-Chih; Arya, Vikram; Yang, Xinning; Volpe, Donna A; Zhang, Lei

2017-07-01

Transporters govern the access of molecules to cells or their exit from cells, thereby controlling the overall distribution of drugs to their intracellular site of action. Clinically relevant drug-drug interactions mediated by transporters are of increasing interest in drug development. Drug transporters, acting alone or in concert with drug metabolizing enzymes, can play an important role in modulating drug absorption, distribution, metabolism and excretion, thus affecting the pharmacokinetics and/or pharmacodynamics of a drug. The drug interaction guidance documents from regulatory agencies include various decision criteria that may be used to predict the need for in vivo assessment of transporter-mediated drug-drug interactions. Regulatory science research continues to assess the prediction performances of various criteria as well as to examine the strength and limitations of each prediction criterion to foster discussions related to harmonized decision criteria that may be used to facilitate global drug development. This review discusses the role of transporters in drug development with a focus on methodologies in assessing transporter-mediated drug-drug interactions, challenges in both in vitro and in vivo assessments of transporters, and emerging transporter research areas including biomarkers, assessment of tissue concentrations, and effect of diseases on transporters. Published by Elsevier B.V.

Comparative evaluation of the drug interaction screening programs MediQ and ID PHARMA CHECK in neurological inpatients.

Science.gov (United States)

Zorina, Olesya I; Haueis, Patrick; Semmler, Alexander; Marti, Isabelle; Gonzenbach, Roman R; Guzek, Markus; Kullak-Ublick, Gerd A; Weller, Michael; Russmann, Stefan

2012-08-01

The comparative evaluation of clinical decision support software (CDSS) programs regarding their sensitivity and positive predictive value for the identification of clinically relevant drug interactions. In this research, we used a cross-sectional study that identified potential drug interactions using the CDSS MediQ and the ID PHARMA CHECK in 484 neurological inpatients. Interactions were reclassified according to the Zurich Interaction System, a multidimensional classification that incorporates the Operational Classification of Drug Interactions. In 484 patients with 2812 prescriptions, MediQ and ID PHARMA CHECK generated a total of 1759 and 1082 alerts, respectively. MediQ identified 658 unique potentially interacting combinations, 8 classified as "high danger," 164 as "average danger," and 486 as "low danger." ID PHARMA CHECK detected 336 combinations assigned to one or several of 12 risk and management categories. Altogether, both CDSS issued alerts relating to 808 unique potentially interacting combinations. According to the Zurich Interaction System, 6 of these were contraindicated, 25 were provisionally contraindicated, 190 carried a conditional risk, and 587 had a minimal risk of adverse events. The positive predictive value for alerts having at least a conditional risk was 0.24 for MediQ and 0.48 for ID PHARMA CHECK. CDSS showed major differences in the identification and grading of interactions, and many interactions were only identified by one of the two CDSS. For both programs, only a small proportion of all identified interactions appeared clinically relevant, and the selected display of alerts that imply management changes is a key issue in the further development and local setup of such programs. Copyright © 2012 John Wiley & Sons, Ltd.

Variable Linezolid Exposure in Intensive Care Unit Patients-Possible Role of Drug-Drug Interactions.

Science.gov (United States)

Töpper, Christoph; Steinbach, Cathérine L; Dorn, Christoph; Kratzer, Alexander; Wicha, Sebastian G; Schleibinger, Michael; Liebchen, Uwe; Kees, Frieder; Salzberger, Bernd; Kees, Martin G

2016-10-01

Standard doses of linezolid may not be suitable for all patient groups. Intensive care unit (ICU) patients in particular may be at risk of inadequate concentrations. This study investigated variability of drug exposure and its potential sources in this population. Plasma concentrations of linezolid were determined by high-performance liquid chromatography in a convenience sample of 20 ICU patients treated with intravenous linezolid 600 mg twice daily. Ultrafiltration applying physiological conditions (pH 7.4/37°C) was used to determine the unbound fraction. Individual pharmacokinetic (PK) parameters were estimated by population PK modeling. As measures of exposure to linezolid, area under the concentration-time curve (AUC) and trough concentrations (Cmin) were calculated and compared with published therapeutic ranges (AUC 200-400 mg*h/L, Cmin 2-10 mg/L). Coadministered inhibitors or inducers of cytochrome P450 and/or P-glycoprotein were noted. Data from 18 patients were included into the PK evaluation. Drug exposure was highly variable (median, range: AUC 185, 48-618 mg*h/L, calculated Cmin 2.92, 0.0062-18.9 mg/L), and only a minority of patients had values within the target ranges (6 and 7, respectively). AUC and Cmin were linearly correlated (R = 0.98), and classification of patients (underexposed/within therapeutic range/overexposed) according to AUC or Cmin was concordant in 15 cases. Coadministration of inhibitors was associated with a trend to higher drug exposure, whereas 3 patients treated with levothyroxine showed exceedingly low drug exposure (AUC ∼60 mg*h/L, Cmin linezolid is highly variable and difficult to predict in ICU patients, and therapeutic drug monitoring seems advisable. PK drug-drug interactions might partly be responsible and should be further investigated; protein binding appears to be stable and irrelevant.

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.

Metabolic drug interactions - the impact of prescribed drug regimens on the medication safety.

NARCIS (Netherlands)

Fialova, D.; Vrbensky, K.; Topinkova, E.; Vlcek, J.; Soerbye, L.W.; Wagner, C.; Bernabei, R.

2005-01-01

Background and objective: Risk/benefit profile of prescribed drug regimens is unkown. Over 60% of commonly used medications interact on metabolic pathways (cytochrom P450 (CYP450), uridyl-glucuronyl tranferasis (UGT I, II) and P-glycoprotein (PGP) transport). Using an up-to-date knowledge on

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

Science.gov (United States)

Gressl, Corinna; Brunsteiner, Michael; Davis, Adrian; Landis, Margaret; Pencheva, Klimentina; Scrivens, Garry; Sluggett, Gregory W; Wood, Geoffrey P F; Gruber-Woelfler, Heidrun; Khinast, Johannes G; Paudel, Amrit

2017-12-04

Understanding properties and mechanisms that govern drug degradation in the solid state is of high importance to ensure drug stability and safety of solid dosage forms. In this study, we attempt to understand drug-excipient interactions in the solid state using both theoretical and experimental approaches. The model active pharmaceutical ingredients (APIs) under study are carvedilol (CAR) and codeine phosphate (COP), which are known to undergo esterification with citric acid (CA) in the solid state. Starting from the crystal structures of two different polymorphs of each compound, we calculated the exposure and accessibility of reactive hydroxyl groups for a number of relevant crystal surfaces, as well as descriptors that could be associated with surface stabilities using molecular simulations. Accelerated degradation experiments at elevated temperature and controlled humidity were conducted to assess the propensity of different solid forms of the model APIs to undergo chemical reactions with anhydrous CA or CA monohydrate. In addition, for CAR, we studied the solid state degradation at varying humidity levels and also under mechano-activation. Regarding the relative degradation propensities, we found that variations in the exposure and accessibility of molecules on the crystal surface play a minor role compared to the impact of molecular mobility due to different levels of moisture. We further studied drug-excipient interactions under mechano-activation (comilling of API and CA) and found that the reaction proceeded even faster than in physical powder mixtures kept at accelerated storage conditions.

[Food-drug interactions: an underestimated risk].

Science.gov (United States)

Sönnichsen, A C; Donner-Banzhoff, N; Baum, E

2005-11-03

With only few exceptions, administration of medicaments should, in principle, be independent of food intake (at least half an hour before or two hours after eating). This ensures uniform and assessable bioavailability. However, it also entails the risk that the patient is more likely to forget to take medication postponed to 2 hours after a meal, than when it is directly coupled to a meal. Certain foodstuffs or food constituents, such as, for example, grapefruit, Seville orange juice, red wine, alcoholic drinks in general, or large quantities of caffeine and garlic should be avoided during drug treatment. In addition, specific interactions with certain drugs must also be taken into account (e.g. MAO inhibitors and tyramine, curamine and vitamin K).

Drug Reactions

Science.gov (United States)

... problem is interactions, which may occur between Two drugs, such as aspirin and blood thinners Drugs and food, such as statins and grapefruit Drugs and supplements, such as ginkgo and blood thinners ...

Possible drug-drug interaction between pregabalin and clozapine in patients with schizophrenia

DEFF Research Database (Denmark)

Schjerning, O; Lykkegaard, S; Damkier, P

2015-01-01

INTRODUCTION: Pregabalin is an antiepileptic drug with anti-anxiety properties and is approved for treatment of generalized anxiety disorder. Anxiety is common in patients with schizophrenia and pregabalin has been suggested as an off-label add-on treatment. METHODS: Pregabalin was added...... patient was less clear. DISCUSSION: This short report discusses the possible mechanism of a pregabalin-clozapine interaction....

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

NARCIS (Netherlands)

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

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

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.

Drug safety and the impact of drug warnings

DEFF Research Database (Denmark)

Hostenkamp, G.; Fischer, K. E.; Borch-Johnsen, K.

2016-01-01

Objective To analyse the impact of drug safety warnings from the European Medicines Agency (EMA) on drug utilisation and their interaction with information released through national reimbursement bodies. Methods Insurance claims data on anti-diabetic drug prescriptions in primary care in Germany...

Modulation of electrostatic interactions to improve controlled drug delivery from nanogels

Energy Technology Data Exchange (ETDEWEB)

Mauri, Emanuele; Chincarini, Giulia M.F.; Rigamonti, Riccardo; Magagnin, Luca; Sacchetti, Alessandro, E-mail: alessandro.sacchetti@polimi.it; Rossi, Filippo, E-mail: filippo.rossi@polimi.it

2017-03-01

The synthesis of nanogels as devices capable to maintain the drug level within a desired range for a long and sustained period of time is a leading strategy in controlled drug delivery. However, with respect to the good results obtained with antibodies and peptides there are a lot of problems related to the quick and uncontrolled diffusion of small hydrophilic molecules through polymeric network pores. For these reasons research community is pointing toward the use of click strategies to reduce release rates of the linked drugs to the polymer chains. Here we propose an alternative method that considers the electrostatic interactions between polymeric chains and drugs to tune the release kinetics from nanogel network. The main advantage of these systems lies in the fact that the carried drugs are not modified and no chemical reactions take place during their loading and release. In this work we synthesized PEG-PEI based nanogels with different protonation degrees and the release kinetics with charged and uncharged drug mimetics (sodium fluorescein, SF, and rhodamine B, RhB) were studied. Moreover, also the effect of counterion used to induce protonation was taken into account in order to build a tunable drug delivery system able to provide multiple release rates with the same device. - Highlights: • The design of nanogels as drug delivery systems based on electrostatic interaction among drug and polymers is proposed. • Nanogels can be synthetized tuning their positive charge density, according to the protonation of PEI at different pH. • No biorthogonal chemistry strategies are applied to the polymers or drugs. • Drug release is efficiently modulated by charge density of PEI chains. • The effect of counterion on nanogel synthesis is investigated and allows controlling the drug release.

Pharmacokinetic drug interactions of morphine, codeine, and their derivatives: theory and clinical reality, part I.

Science.gov (United States)

Armstrong, Scott C; Cozza, Kelly L

2003-01-01

Pharmacokinetic drug-drug interactions with morphine, hydromorphone, and oxymorphone are reviewed in this column. Morphine is a naturally occurring opiate that is metabolized chiefly through glucuronidation by uridine diphosphate glucuronosyl transferase (UGT) enzymes in the liver. These enzymes produce an active analgesic metabolite and a potentially toxic metabolite. In vivo drug-drug interaction studies with morphine are few, but they do suggest that inhibition or induction of UGT enzymes could alter morphine and its metabolite levels. These interactions could change analgesic efficacy. Hydromorphone and oxymorphone, close synthetic derivatives of morphine, are also metabolized primarily by UGT enzymes. Hydromorphone may have a toxic metabolite similar to morphine. In vivo drug-drug interaction studies with hydromorphone and oxymorphone have not been done, so it is difficult to make conclusions with these drugs.

Cell physiology based pharmacodynamic modeling of antimicrobial drug combinations

OpenAIRE

Hethey, Christoph Philipp

2017-01-01

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

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.

Development of description framework of pharmacodynamics ontology and its application to possible drug-drug interaction reasoning.

Science.gov (United States)

Imai, Takeshi; Hayakawa, Masayo; Ohe, Kazuhiko

2013-01-01

Prediction of synergistic or antagonistic effects of drug-drug interaction (DDI) in vivo has been of considerable interest over the years. Formal representation of pharmacological knowledge such as ontology is indispensable for machine reasoning of possible DDIs. However, current pharmacology knowledge bases are not sufficient to provide formal representation of DDI information. With this background, this paper presents: (1) a description framework of pharmacodynamics ontology; and (2) a methodology to utilize pharmacodynamics ontology to detect different types of possible DDI pairs with supporting information such as underlying pharmacodynamics mechanisms. We also evaluated our methodology in the field of drugs related to noradrenaline signal transduction process and 11 different types of possible DDI pairs were detected. The main features of our methodology are the explanation capability of the reason for possible DDIs and the distinguishability of different types of DDIs. These features will not only be useful for providing supporting information to prescribers, but also for large-scale monitoring of drug safety.

The interaction of encapsulated pharmaceutical drugs with a silica matrix.

Science.gov (United States)

Morais, Everton C; Correa, Gabriel G; Brambilla, Rodrigo; Radtke, Claudio; Baibich, Ione Maluf; dos Santos, João Henrique Z

2013-03-01

A series of seven drugs, namely, fluoxetine, gentamicin, lidocaine, morphine, nifedipine, paracetamol and tetracycline, were encapsulated. The encapsulated systems were characterized using a series of complementary techniques: Fourier-transform infrared spectroscopy (FT-IR), diffusive reflectance spectroscopy in the UV-vis region (DRS) and X-ray photoelectron spectroscopy (XPS). According to the DRS spectra, most of the encapsulated systems showed a band shift of the maximum absorption when compared with the corresponding bare pharmaceutical. Additionally, after encapsulation, the drugs exhibited infrared band shifts toward higher wavenumbers, which in turn provided insight into potential sites for interaction with the silica framework. The amine group showed a band shift in the spectra of almost all the drugs (except nifedipine and tetracycline). This finding indicates the possibility of a hydrogen bonding interaction between the drug and the silica via electron donation from the amine group to the silica framework. XPS confirmed this interaction between the pharmaceuticals and the silica through the amine group. A correlation was observed between the textural characteristics of the solids and the spectroscopic data, suggesting that the amine groups from the pharmaceuticals were more perturbed upon encapsulation. Copyright © 2012 Elsevier B.V. All rights reserved.

Drug Reactions - Multiple Languages

Science.gov (United States)

... PDF Drug Interactions - HIV medicines, part 6 - English MP3 Drug Interactions - HIV medicines, part 6 - 简体中文 (Chinese, Simplified (Mandarin dialect)) MP3 Drug Interactions - HIV medicines, part 6 - English MP4 ...

Routine drug and food interactions during antihelminthic treatment of neurocysticercosis: a reason for the variable efficacy of albendazole and praziquantel?

Science.gov (United States)

Romo, Matthew L; Carpio, Arturo; Kelvin, Elizabeth A

2014-04-01

Neurocysticercosis (NC) or infection of the central nervous system with Taenia solium larvae is a leading cause of preventable seizures and epilepsy in endemic regions across the globe. Albendazole and praziquantel are commonly used antihelminthic agents to treat NC; however, viable cysts persist in the majority of patients, putting them at risk for future seizures and other neurological complications. Because of their pharmacokinetic profiles, albendazole and praziquantel have the potential to interact with many different drugs. During antihelminthic treatment, antiepileptic drugs and corticosteroids are commonly co-administered to manage seizures and cerebral edema; however, the most commonly used agents from these drug classes are known to significantly alter plasma concentrations of albendazole and praziquantel. The overarching issue with drug interactions during the treatment of NC is whether or not they have clinical relevance, as the plasma concentrations of albendazole and praziquantel have not been directly linked with eradication of viable cysts. Future studies should attempt to evaluate the validity of a causal relationship between antihelminthic plasma concentrations and outcomes so that drug interactions can be better understood and managed and so that treatment can be optimized. © 2014, The American College of Clinical Pharmacology.

Drug Interaction between Sirolimus and Ranolazine in a Kidney Transplant Patient

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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.

Extent of poly-pharmacy, occurrence and associated factors of drug-drug interaction and potential adverse drug reactions in Gondar Teaching Referral Hospital, North West Ethiopia

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Endalkachew Admassie

2013-01-01

Full Text Available The aim of this study was to assess the extent of poly-pharmacy, occurrence, and associated factors for the occurrence of drug-drug interaction (DDI and potential adverse drug reaction (ADR in Gondar University Teaching Referral Hospital. Institutional-based retrospective cross-sectional study. This study was conducted on prescriptions of both in and out-patients for a period of 3 months at Gondar University Hospital. Both bivariate analysis and multivariate logistic regression were used to identify risk factors for the occurrence of DDI and possible ADRs. All the statistical calculations were performed using SPSS; software. A total of 12,334 prescriptions were dispensed during the study period of which, 2,180 prescriptions were containing two or more drugs per prescription. A total of 21,210 drugs were prescribed and the average number of drugs per prescription was 1.72. Occurrences of DDI of all categories (Major, Moderate, and Minor were analyzed and DDI were detected in 711 (32.6% prescriptions. Sex was not found to be a risk factor for the occurrence of DDI and ADR, while age and number of medications per prescription were found to be significant risk factors for the occurrence of DDI and ADR. The mean number of drugs per prescription was 1.72 and hence with regard to the WHO limit of drugs per prescription, Gondar hospital was able to maintain the limit and prescriptions containing multiple drugs supposed to be taken systemically. Numbers of drugs per prescription as well as older age were found to be predisposing factors for the occurrence of DDI and potential ADRs while sex was not a risk factor.

Adverse effects and Drug Interactions Associated with Inhaled Recreational and Medical Marijuana

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Maisha Kelly Freeman

2016-06-01

Full Text Available Objectives: To provide an overview of the addiction potential; adverse effects (e.g., cardiovascular, immune dysfunction, respiratory system, mental health disorders; drug interactions; effects of accidental exposure; crime statistics; and pharmacist’s considerations for the use of inhaled medical marijuana. Methods: A PubMed search was conducted from 1966 to March 2016 to identify articles in which the safety of inhaled medical marijuana was assessed. Key MeSH search terms included medical marijuana with a subheading for adverse effect. Only articles in adult patients were considered. In addition, medical marijuana or cannabis plus one of the following search terms were searched: drug interactions, herb-drug interactions, drug-related side effects and adverse drug reactions, substance-related disorders, addiction, and abuse. A free-text search was also conducted to identify articles not included in the MeSH term search. A bibliographic search was also conducted. Articles were included if they addressed adverse effects of medical marijuana for the treatment of a condition. Meta-analyses, randomized controlled clinical trials, and case reports were included in the review if the primary focus of the article related to the adverse effect profile of inhaled medical marijuana. Medical marijuana efficacy studies were not assessed. In the absence of this information, case reports or reports of inhaled recreational marijuana use was used. Studies were excluded if published in languages other than English. In addition, studies highlighting mechanisms of action, studies of pharmacodynamics or pharmacokinetic effects were excluded, unless these effects were due to drug-drug interactions. Prescription products containing marijuana or derivatives were excluded from evaluation. An Internet search was conducted to locate the most up-to-date information on the laws concerning medical marijuana. Key findings: A PubMed search revealed 58 articles and 28 of

Interactions between traditional Chinese medicine and western drugs in Taiwan: A population-based study.

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Chen, Kuan Chen; Lu, Richard; Iqbal, Usman; Hsu, Ko-Ching; Chen, Bi-Li; Nguyen, Phung-Anh; Yang, Hsuan-Chia; Huang, Chih-Wei; Li, Yu-Chuan Jack; Jian, Wen-Shan; Tsai, Shin-Han

2015-12-01

Drug-drug interactions have long been an active research area in clinical medicine. In Taiwan, however, the widespread use of traditional Chinese medicines (TCM) presents additional complexity to the topic. Therefore, it is important to see the interaction between traditional Chinese and western medicine. (1) To create a comprehensive database of multi-herb/western drug interactions indexed according to the ways in which physicians actually practice and (2) to measure this database's impact on the detection of adverse effects between traditional Chinese medicine compounds and western medicines. First, a multi-herb/western medicine drug interactions database was created by separating each TCM compound into its constituent herbs. Each individual herb was then checked against an existing single-herb/western drug interactions database. The data source comes from the National Health Insurance research database, which spans the years 1998-2011. This study estimated the interaction prevalence rate and further separated the rates according to patient characteristics, distribution by county, and hospital accreditation levels. Finally, this new database was integrated into a computer order entry module of the electronic medical records system of a regional teaching hospital. The effects it had were measured for two months. The most commonly interacting Chinese herbs were Ephedrae Herba and Angelicae Sinensis Radix/Angelicae Dahuricae Radix. Ephedrae Herba contains active ingredients similar to in ephedrine. 15 kinds of traditional Chinese medicine compounds contain Ephedrae Herba. Angelicae Sinensis Radix and Angelicae Dahuricae Radix contain ingredients similar to coumarin, a blood thinner. 9 kinds of traditional Chinese medicine compounds contained Angelicae Sinensis Radix/Angelicae Dahuricae Radix. In the period from 1998 to 2011, the prevalence of herb-drug interactions related to Ephedrae Herba was 0.18%. The most commonly prescribed traditional Chinese compounds were

From Imitation to Innovation: A Study of China’s Drug R&D and Relevant National Policies

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Jinxi Ding

2011-06-01

Full Text Available Research & Development (R&D plays an increasingly important role in China’s pharmaceutical industry. To gain a competitive edge in the global pharmaceutical market, the current national strategy of China forcefully pushes for independent drug innovations. This article investigates the historical, legal, and institutional contexts in which China’s drug R&D has evolved. Based on an analysis of the drug R&D evolution and national policies in China, it predicts the future trend of China’s policies relevant to drug innovations. This paper helps to understand the impact of national policies on drug R&D in China, which can be used to inform decision-making on investments in China’s pharmaceutical market or conducting technology trade and international cooperation with Chinese partners.

The Prevalence of Potential Drug Interactions Among Critically Ill Elderly Patients in the Intensive Care Unit (ICU

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Hossein Rafiei

2012-01-01

Full Text Available Objectives: The aim of the research was to determine prevalence of potential drug interactions among elderly patients in the Shahid Bahonar ICU in Kerman. Methods & Materials: In this cross sectional study, data about all elderly patients who were admitted in the intensive care unit from 1/4/2009 to 1/4/2010 were retrieved from medical records and evaluated with regard to the number and type of drug interactions, the number of drugs administered, age, sex, length of stay in the ICU, and the number of doctors prescribing medications of medications administered. The extent and number of drug interactions were investigated based on the reference textbook Drug Interaction Facts and in order to analyze the data collected, using SPSS 18 and according to study goals, a descriptive test, Pierson's correlation test, an independent T-test and a one-way ANOVA were used. Results: In total, 77 types of drugs and 394 drugs were prescribed with a mean of 5.6(SD=1.5 drugs per patient. A total of 108 potential drug interactions were found related to drugs prescribed during the first twenty-four hours. In terms of the type of drug interactions, delayed, moderate and possible types comprised the highest proportion of drug interactions. The four major interactions were between cimetidine and methadone, furosemide and amikacine, phenytoin and dopamine, and heparin and aspirin. The results of Pierson's correlation test were inicative of a positive correlation between the number of potential drug interactions and that of the drugs prescribed (r=0.563, P<0.05. Results of a one-way ANOVA showed that the mean number of potential drug interaction were significantly higher in those who died than in other patients (P<0.05. Conclusion: Elderly patients who are admitted to the intensive care unit are at a high risk of developing drug interactions and better care must be taken by medical team members.

Guidance for nuclear medicine staff on radiopharmaceuticals drug interaction

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Ralph Santos-Oliveira

2009-12-01

Full Text Available 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.Diversos casos de interações medicamentosas com radiofármacos ocorrem diariamente na rotina hospitalar, contudo muitos deles não são notificados ou mesmo percebidos. Informações a respeito desse tipo de reação não é abundante e os profissionais da medicina nuclear muitas vezes estão assoberbados por essas informações. De modo a entender esse tipo de reação e auxiliar a medicina nuclear a lidar com essa situação uma revisão da literatura foi realizada. Os resultados mostraram que a totalidade dos radiofármacos comercializados no mundo apresentam interação medicamentosa com uma enorme variedade de outros medicamentos. Dessa forma sugere-se que revisões sobre radiofármacos inclua um capítulo sobre efeitos adversos. Além disso, um esforço mundial para notificar efeitos adversos deve ser realizado, pois somente

Adherence to drug label recommendations for avoiding drug interactions causing statin-induced myopathy--a nationwide register study.

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Jennifer Settergren

Full Text Available To investigate the extent to which clinicians avoid well-established drug-drug interactions that cause statin-induced myopathy. We hypothesised that clinicians would avoid combining erythromycin or verapamil/diltiazem respectively with atorvastatin or simvastatin. In patients with statin-fibrate combination therapy, we hypothesised that gemfibrozil was avoided to the preference of bezafibrate or fenofibrate. When combined with verapamil/diltiazem or fibrates, we hypothesized that the dispensed doses of atorvastatin/simvastatin would be decreased.Cross-sectional analysis of nationwide dispensing data. Odds ratios of interacting erythromycin, verapamil/diltiazem versus respective prevalence of comparator drugs doxycycline, amlodipine/felodipine in patients co-dispensed interacting statins simvastatin/atorvastatin versus patients unexposed (pravastatin/fluvastatin/rosuvastatin was calculated. For fibrates, OR of gemfibrozil versus fenofibrate/bezafibrate in patients co-dispensed any statin was assessed.OR of interacting erythromycin versus comparator doxycycline did not differ between patients on interacting and comparator statins either in patients dispensed high or low statin doses (adjusted OR 0.87; 95% CI 0.60-1.25 and 0.92; 95% CI 0.69-1.23. Interacting statins were less common among patients dispensed verapamil/diltiazem as compared to patients on amlodipine/felodipine (OR high dose 0.62; CI 0.56-0.68 and low dose 0.63; CI 0.58-0.68. Patients on any statin were to a lesser extent dispensed gemfibrozil compared to patients not dispensed a statin (OR high dose 0.65; CI 0.55-0.76 and low dose 0.70; CI 0.63-0.78. Mean DDD (SD for any statin was substantially higher in patients co-dispensed gemfibrozil 178 (149 compared to patients on statin monotherapy 127 (93, (p<0.001.Prescribers may to some extent avoid co-prescription of statins with calcium blockers and fibrates with an increased risk of myopathy. We found no evidence for avoiding co

Basic principles of drug--excipients interactions.

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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.

Frequency of potential interactions between drugs in medical prescriptions in a city in southern Brazil

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Genici Weyh Bleich

Full Text Available CONTEXT AND OBJECTIVE: Drug interactions form part of current clinical practice and they affect between 3 and 5% of polypharmacy patients. The aim of this study was to identify the frequency of potential drug-drug interactions in prescriptions for adult and elderly patients. TYPE OF STUDY AND SETTING: Cross-sectional pharmacoepidemiological survey in the Parque Verde housing project, municipality of Cascavel, Paraná, Brazil, between December 2006 and February 2007. METHODS: Stratified cluster sampling, proportional to the total number of homes in the housing project, was used. The sample consisted of 95 homes and 96 male or female patients aged 19 or over, with medical prescriptions for at least two pharmaceutical drugs. Interactions were identified using DrugDigest, Medscape and Micromedex softwares. RESULTS: Most of the patients were female (69.8%, married (59.4% and in the age group of 60 years or over (56.3%, with an income less than or equal to three minimum monthly salaries (81.3% and less than eight years of schooling (69.8%; 90.6% of the patients were living with another person. The total number of pharmaceutical drugs was 406 (average of 4.2 medications per patient. The drugs most prescribed were antihypertensives (47.5%. The frequency of drug interactions was 66.6%. Among the 154 potential drug interactions, 4.6% were classified as major, 65.6% as moderate and 20.1% as minor. CONCLUSION: The high frequency of drug prescriptions with a potential for differentiated interactions indicates a situation that has so far been little explored, albeit a reality in household surveys.

Methamphetamine-alcohol interactions in murine models of sequential and simultaneous oral drug-taking.

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Fultz, Elissa K; Martin, Douglas L; Hudson, Courtney N; Kippin, Tod E; Szumlinski, Karen K

2017-08-01

A high degree of co-morbidity exists between methamphetamine (MA) addiction and alcohol use disorders and both sequential and simultaneous MA-alcohol mixing increases risk for co-abuse. As little preclinical work has focused on the biobehavioral interactions between MA and alcohol within the context of drug-taking behavior, we employed simple murine models of voluntary oral drug consumption to examine how prior histories of either MA- or alcohol-taking influence the intake of the other drug. In one study, mice with a 10-day history of binge alcohol-drinking [5,10, 20 and 40% (v/v); 2h/day] were trained to self-administer oral MA in an operant-conditioning paradigm (10-40mg/L). In a second study, mice with a 10-day history of limited-access oral MA-drinking (5, 10, 20 and 40mg/L; 2h/day) were presented with alcohol (5-40% v/v; 2h/day) and then a choice between solutions of 20% alcohol, 10mg/L MA or their mix. Under operant-conditioning procedures, alcohol-drinking mice exhibited less MA reinforcement overall, than water controls. However, when drug availability was not behaviorally-contingent, alcohol-drinking mice consumed more MA and exhibited greater preference for the 10mg/L MA solution than drug-naïve and combination drug-experienced mice. Conversely, prior MA-drinking history increased alcohol intake across a range of alcohol concentrations. These exploratory studies indicate the feasibility of employing procedurally simple murine models of sequential and simultaneous oral MA-alcohol mixing of relevance to advancing our biobehavioral understanding of MA-alcohol co-abuse. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

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

Clinically significant drug–drug interactions involving opioid analgesics used for pain treatment in patients with cancer: a systematic review

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Kotlinska-Lemieszek A

2015-09-01

Full Text Available Aleksandra Kotlinska-Lemieszek,1 Pål Klepstad,2,3,6 Dagny Faksvåg Haugen2,4,5 1Palliative Medicine Chair and Department, University Hospital of the Lord’s Transfiguration, Karol Marcinkowski University of Medical Sciences, Poznan, Poland; 2European Palliative Care Research Centre, Faculty of Medicine, Norwegian University of Science and Technology,Trondheim, Norway; 3Department of Anaesthesiology and Intensive Care Medicine, St Olavs Hospital, Trondheim, Norway; 4Regional Centre of Excellence for Palliative Care, Haukeland University Hospital, Bergen, Norway; 5Department of Clinical Medicine K1, University of Bergen, Bergen, Norway; 6Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway Background: Opioids are the most frequently used drugs to treat pain in cancer patients. In some patients, however, opioids can cause adverse effects and drug–drug interactions. No advice concerning the combination of opioids and other drugs is given in the current European guidelines. Objective: To identify studies that report clinically significant drug–drug interactions involving opioids used for pain treatment in adult cancer patients. Design and data sources: Systematic review with searches in Embase, MEDLINE, and Cochrane Central Register of Controlled Trials from the start of the databases (Embase from 1980 through January 2014. In addition, reference lists of relevant full-text papers were hand-searched. Results: Of 901 retrieved papers, 112 were considered as potentially eligible. After full-text reading, 17 were included in the final analysis, together with 15 papers identified through hand-searching of reference lists. All of the 32 included publications were case reports or case series. Clinical manifestations of drug–drug interactions involving opioids were grouped as follows: 1 sedation and respiratory depression, 2 other central nervous system symptoms, 3 impairment of pain

Neostigmine interactions with non steroidal anti-inflammatory drugs.

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Miranda, Hugo F; Sierralta, Fernando; Pinardi, Gianni

2002-04-01

1. The common mechanism of action of non-steroidal anti-inflammatory drugs (NSAIDs) is the inhibition of the enzyme cyclo-oxygenase (COX), however, this inhibition is not enough to completely account for the efficacy of these agents in several models of acute pain. 2. It has been demonstrated that cholinergic agents can induce antinociception, but the nature of the interaction between these agents and NSAIDs drugs has not been studied. The present work evaluates, by isobolographic analysis, the interactions between the cholinergic indirect agonist neostigmine (NEO) and NSAIDs drugs, using a chemical algesiometric test. 3. Intraperitoneal (i.p.) or intrathecal (i.t.) administration of NEO and of the different NSAIDs produced dose-dependent antinociception in the acetic acid writhing test of the mouse. 4. The i.p. or i.t. co-administration of fixed ratios of ED(50) fractions of NSAIDs and NEO, resulted to be synergistic or supra-additive for the combinations ketoprofen (KETO) and NEO, paracetamol (PARA) and NEO) and diclofenac (DICLO) and NEO administered i.p. However, the same combinations administered i.t. were only additive. In addition, the combinations meloxicam (MELO) and NEO and piroxicam (PIRO) and NEO, administered either i.p. or i.t., were additive. 5. The results suggest that the co-administration of NEO with some NSAIDs (e.g. KETO, PARA or DICLO) resulted in a synergistic interaction, which may provide evidence of supraspinal antinociception modulation by the increased acetylcholine concentration in the synaptic cleft of cholinergic interneurons. The interaction obtained between neostigmine and the NSAIDs could carry important clinical implications.

Pharmacokinetic drug interactions of morphine, codeine, and their derivatives: theory and clinical reality, Part II.

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Armstrong, Scott C; Cozza, Kelly L

2003-01-01

Pharmacokinetic drug-drug interactions with codeine, dihydrocodeine, hydrocodone, oxycodone, and buprenorphine are reviewed in this column. These compounds have a very similar chemical structure to morphine. Unlike morphine, which is metabolized chiefly through conjugation reactions with uridine diphosphate glucuronosyl transferase (UGT) enzymes, these five drugs are metabolized both through oxidative reactions by the cytochrome P450 (CYP450) enzyme and conjugation by UGT enzymes. There is controversy as to whether codeine, dihydrocodeine, and hydrocodone are actually prodrugs requiring activation by the CYP450 2D6 enzyme or UGT enzymes. Oxycodone and buprenorphine, however, are clearly not prodrugs and are metabolized by the CYP450 2D6 and 3A4 enzymes, respectively. Knowledge of this metabolism assists in the understanding for the potential of drug-drug interactions with these drugs. This understanding is important so that clinicians can choose the proper dosages for analgesia and anticipate potential drug-drug interactions.

A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents.

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Segura-Bedmar, Isabel; Martínez, Paloma; de Pablo-Sánchez, César

2011-03-29

A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The increasing volume of the scientific literature overwhelms health care professionals trying to be kept up-to-date with all published studies on DDI. This paper describes a hybrid linguistic approach to DDI extraction that combines shallow parsing and syntactic simplification with pattern matching. Appositions and coordinate structures are interpreted based on shallow syntactic parsing provided by the UMLS MetaMap tool (MMTx). Subsequently, complex and compound sentences are broken down into clauses from which simple sentences are generated by a set of simplification rules. A pharmacist defined a set of domain-specific lexical patterns to capture the most common expressions of DDI in texts. These lexical patterns are matched with the generated sentences in order to extract DDIs. We have performed different experiments to analyze the performance of the different processes. The lexical patterns achieve a reasonable precision (67.30%), but very low recall (14.07%). The inclusion of appositions and coordinate structures helps to improve the recall (25.70%), however, precision is lower (48.69%). The detection of clauses does not improve the performance. Information Extraction (IE) techniques can provide an interesting way of reducing the time spent by health care professionals on reviewing the literature. Nevertheless, no approach has been carried out to extract DDI from texts. To the best of our knowledge, this work proposes the first integral solution for the automatic extraction of DDI from biomedical texts.

Cunninghamella Biotransformation--Similarities to Human Drug Metabolism and Its Relevance for the Drug Discovery Process.

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Piska, Kamil; Żelaszczyk, Dorota; Jamrozik, Marek; Kubowicz-Kwaśny, Paulina; Pękala, Elżbieta

2016-01-01

Studies of drug metabolism are one of the most significant issues in the process of drug development, its introduction to the market and also in treatment. Even the most promising molecule may show undesirable metabolic properties that would disqualify it as a potential drug. Therefore, such studies are conducted in the early phases of drug discovery and development process. Cunninghamella is a filamentous fungus known for its catalytic properties, which mimics mammalian drug metabolism. It has been proven that C. elegans carries at least one gene coding for a CYP enzyme closely related to the CYP51 family. The transformation profile of xenobiotics in Cunninghamella spp. spans a number of reactions catalyzed by different mammalian CYP isoforms. This paper presents detailed data on similar biotransformation drug products in humans and Cunninghamella spp. and covers the most important aspects of preparative biosynthesis of metabolites, since this model allows to obtain metabolites in sufficient quantities to conduct the further detailed investigations, as quantification, structure analysis and pharmacological activity and toxicity testing. The metabolic activity of three mostly used Cunninghamella species in obtaining hydroxylated, dealkylated and oxidated metabolites of different drugs confirmed its convergence with human biotransformation. Though it cannot replace the standard methods, it can provide support in the field of biotransformation and identifying metabolic soft spots of new chemicals and in predicting possible metabolic pathways. Another aspect is the biosynthesis of metabolites. In this respect, techniques using Cunninghamella spp. seem to be competitive to the chemical methods currently used.

Allosteric cross-talk in chromatin can mediate drug-drug synergy

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Adhireksan, Zenita; Palermo, Giulia; Riedel, Tina; Ma, Zhujun; Muhammad, Reyhan; Rothlisberger, Ursula; Dyson, Paul J.; Davey, Curt A.

2017-03-01

Exploitation of drug-drug synergism and allostery could yield superior therapies by capitalizing on the immensely diverse, but highly specific, potential associated with the biological macromolecular landscape. Here we describe a drug-drug synergy mediated by allosteric cross-talk in chromatin, whereby the binding of one drug alters the activity of the second. We found two unrelated drugs, RAPTA-T and auranofin, that yield a synergistic activity in killing cancer cells, which coincides with a substantially greater number of chromatin adducts formed by one of the compounds when adducts from the other agent are also present. We show that this occurs through an allosteric mechanism within the nucleosome, whereby defined histone adducts of one drug promote reaction of the other drug at a distant, specific histone site. This opens up possibilities for epigenetic targeting and suggests that allosteric modulation in nucleosomes may have biological relevance and potential for therapeutic interventions.

Correlation between drug–drug interaction-induced Stevens–Johnson syndrome and related deaths in Taiwan

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Fu-Jen Cheng

2016-04-01

Full Text Available Concomitant use of some drugs can lead to interactions between them resulting in severe adverse effects. To date, there are few reports of incidences of Stevens-Johnson syndrome (SJS associated with combination drug administration. Therefore, we studied the relationship between drug combinations and SJS-related mortality, with the hope that a retrospective study of this nature would provide information crucial for the prevention of future drug-drug interaction related deaths attributable to SJS. This retrospective longitudinal study used mortality cases from 1999 to 2008 that were diagnosed as erythema multiforme (International Classification of Diseases, Ninth Revision, Clinical Modification 695.1 from the National Health Insurance database in Taiwan. Statistical comparisons of the results were performed using analysis of variance (ANOVA, independent sample t-tests, and odds ratio (OR. In this way, the relationship between combinations of SJS-inducing drugs and mortality could be determined. A total of 111 patients who had died, including 63 males and 48 females (66.0 ± 20 and 70.0 ± 17.7 years, respectively, were suspected of having experienced drug-drug interaction-related adverse effects. The associated drug combinations included allopurinol and ampicillin (p = 0.049, carbamazepine and sulfamethoxazole/trimethoprim (TMP (p < 0.0001, carbamazepine and phenytoin (p < 0.0001, sulfamethoxazole/TMP and phenytoin (p = 0.015, sulfadoxine and piroxicam (p = 0.045, phenobarbital and cephalexin (p < 0.0001, ampicillin and erythromycin (p < 0.0001, erythromycin and minocycline (p < 0.0001, and vancomycin and ethambutol (p < 0.0001 administered 1 month before the patients' deaths. Caution should be exercised when administering any drugs that may possibly induce SJS. In addition, attention should be paid to ensure prompt identification of possible drug-drug interactions, and patients should be closely monitored. Furthermore

Fragmentation of toxicologically relevant drugs in positive-ion liquid chromatography-tandem mass spectrometry.

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Niessen, W M A

2011-01-01

The identification of drugs and related compounds by LC-MS-MS is an important analytical challenge in several application areas, including clinical and forensic toxicology, doping control analysis, and environmental analysis. Although target-compound based analytical strategies are most frequently applied, at some point the information content of the MS-MS spectra becomes relevant. In this article, the positive-ion MS-MS spectra of a wide variety of drugs and related substances are discussed. Starting point was an MS-MS mass spectral library of toxicologically relevant compounds, available on the internet. The positive-ion MS-MS spectra of ∼570 compounds were interpreted by chemical and therapeutic class, thus involving a wide variety of drug compound classes, such benzodiazepines, beta-blockers, angiotensin-converting enzyme inhibitors, phenothiazines, dihydropyridine calcium channel blockers, diuretics, local anesthetics, vasodilators, as well as various subclasses of anti-diabetic, antidepressant, analgesic, and antihistaminic drugs. In addition, the scientific literature was searched for available MS-MS data of these compound classes and the interpretation thereof. The results of this elaborate study are presented in this article. For each individual compound class, the emphasis is on class-specific fragmentation, as discussing fragmentation of all individual compounds would take far too much space. The recognition of class-specific fragmentation may be quite informative in determining the compound class of a specific unknown, which may further help in the identification. In addition, knowledge on (class-specific) fragmentation may further help in the optimization of the selectivity in targeted analytical approaches of compounds of one particular class. Copyright © 2011 Wiley Periodicals, Inc.

Population Impact of Drug Interactions with Warfarin: A Real-World Data Approach.

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Martín-Pérez, Mar; Gaist, David; de Abajo, Francisco J; Rodríguez, Luis A García

2018-03-01

 To investigate the population impact of previously reported interactions between warfarin and other drugs on international normalized ratio (INR) levels.  Using The Health Improvement Network (THIN), a United Kingdom primary care database, a cohort of warfarin users between 2005 and 2013 ( N  = 121,962) was followed until the first qualifying prescription for the potential interacting drugs was evaluated. Sixteen sub-cohorts, one for each study drug, and a control sub-cohort of warfarin were ascertained. Short-term changes in INR levels were assessed by comparing INR values measured before and after initiation of the interacting drug with paired Student's t -test. We also evaluated the proportion of patients with INR values outside the therapeutic range (INR: 2-3).  Miconazole use was associated with the highest mean increase in INR (+3.35), followed by amiodarone (+1.28), fluconazole (+0.79), metronidazole (+0.75) and nystatin (+0.65). After subtracting the natural INR variation observed in the control sub-cohort, supra-therapeutic levels (INR > 3) were found in 53.2% (miconazole), 45.5% (amiodarone), 23.3% (metronidazole), 23.2% (fluconazole) and 17.6% (nystatin) of patients initiating treatment with these drugs. Carbamazepine use was associated with a mean INR decrease of -0.63 and infra-therapeutic levels (INR < 2) were observed in 46.2% of patients initiating carbamazepine. For all other drugs, the change was small to moderate, in absolute INR units (+0.23 to +0.55) and in the proportion of patients with INR levels out of therapeutic range (<16%).  Clinically potentially important interactions were observed in several study drugs. The majority of them, although confirmed, had little impact after adjusting for standard INR variability in the general population of warfarin users. Schattauer GmbH Stuttgart.

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

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

2016-01-01

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. PMID:26927160

Forensic relevance of glucuronidation in phase-II-metabolism of alcohols and drugs.

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Kaeferstein, Herbert

2009-04-01

Forensic toxicology means detecting toxic or pharmacologically active substances in body fluids and organs and the evaluation and judgement of the respective results. In the legal judgement, not only the taken in active drugs, but also their metabolites are to be included. Regarding metabolism one distinguishes phase-I- and phase-II-metabolism. In the phase-I-metabolism, active substances are converted by oxidation, reduction or hydrolysis, but influencing the polarity of more lipophilic substances often not decisively. The pharmacological activity is often preserved or even increased. In phase-II-metabolism a highly hydrophilic substance--mostly glucuronic acid--is coupled to the active substances or the respective phase-I-metabolites. This reaction step decisively increases hydrophilicity of lipophilic substances, thus enhancing renal elimination and often also abolishing pharmacologically and/or toxicologically effects. Nevertheless the interaction of different drugs and alcohols in glucuronidation and the glucuronides of phase-II-metabolism still do not play a substantial role in the forensic-toxicological analysis and interpretation of results so far. However, in vitro investigations since 1999 in our lab show that such interactions are not unlikely. For valid interpretation of complex cases in the future it may become necessary not only to quantify drugs and the phase-I-metabolites but also the phase-II-metabolites and discuss possible interactions in the metabolism.

AtriplaR/anti-TB combination in TB/HIV patients. Drug in focus

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Semvua Hadija H

2011-11-01

Full Text Available Abstract Background Co-administration of anti-tuberculosis and antiretroviral therapy is often inevitable in high-burden countries where tuberculosis is the most common opportunistic infection associated with HIV/AIDS. Concurrent use of rifampicin and several antiretroviral drugs is complicated by pharmacokinetic drug-drug interaction. Method Pubmed and Google search following the key words tuberculosis, HIV, emtricitabine, tenofovir efavirenz, interaction were used to find relevant information on each drug of the fixed dose combination AtriplaR Results Information on generic name, trade name, pharmacokinetic parameter, metabolism and the pharmacokinetic interaction with Anti-TB drugs of emtricitabine, tenofovir, and efavirenz was obtained. Conclusion Fixed dose combination of emtricitabine/tenofovir/efavirenz (ATRIPLAR which has been approved by Food and Drug Administration shows promising results as far as safety and efficacy is concerned in TB/HIV co-infection patients, hence can be considered effective and safe antiretroviral drug in TB/HIV management for adult and children above 3 years of age.

Clinically important drug interactions with zopiclone, zolpidem and zaleplon.

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Hesse, Leah M; von Moltke, Lisa L; Greenblatt, David J

2003-01-01

Insomnia, an inability to initiate or maintain sleep, affects approximately one-third of the American population. Conventional benzodiazepines, such as triazolam and midazolam, were the treatment of choice for short-term insomnia for many years but are associated with adverse effects such as rebound insomnia, withdrawal and dependency. The newer hypnosedatives include zolpidem, zaleplon and zopiclone. These agents may be preferred over conventional benzodiazepines to treat short-term insomnia because they may be less likely to cause significant rebound insomnia or tolerance and are as efficacious as the conventional benzodiazepines. This review aims to summarise the published clinical drug interaction studies involving zolpidem, zaleplon and zopiclone. The pharmacokinetic and pharmacodynamic interactions that may be clinically important are highlighted. Clinical trials have studied potential interactions of zaleplon, zolpidem and zopiclone with the following types of drugs: cytochrome P450 (CYP) inducers (rifampicin), CYP inhibitors (azoles, ritonavir and erythromycin), histamine H(2) receptor antagonists (cimetidine and ranitidine), antidepressants, antipsychotics, antagonists of benzodiazepines and drugs causing sedation. Rifampicin significantly induced the metabolism of the newer hypnosedatives and decreased their sedative effects, indicating that a dose increase of these agents may be necessary when they are administered with rifampicin. Ketoconazole, erythromycin and cimetidine inhibited the metabolism of the newer hypnosedatives and enhanced their sedative effects, suggesting that a dose reduction may be required. Addition of ethanol to treatment with the newer hypnosedatives resulted in additive sedative effects without altering the pharmacokinetic parameters of the drugs. Compared with some of the conventional benzodiazepines, fewer clinically important interactions appear to have been reported in the literature with zaleplon, zolpidem and zopiclone. The