Detection Of Drug Interactions Research Articles

PP.35.09

Objective: Analysis of arterial hypertension therapy for detection of drug interactions in routine ambulatory practice. Design and method: 402 case records of ambulatory hypertensive patients with comorbidity were analyzed. Evaluation of drug combinations from 27 agents with well-known metabolism each of them were conducted. Results: The mean number medications using by one comorbidity patient are 9,5 (from 5 to 14). The total number of used drugs are 95 (42 international nonproprietary names). Twenty two drug combinations (5,53%) were subsumed to major category. This category means the clinical significant drug interaction, and risk of drug adverse event exceeds them benefits. Most of major drug combinations were: simvastatine + amlodipine (0,73% among total medications, 13,2% among major combinations), simvastatine + itraconazole (0,44% and 8,09%, respectively), spironolactone + perindopril (0,57% and 10,34%, respectively). Besides that, combinations with amiodarone, spironolactone, simvastatin, amlodipine, diltiazem and clopidogrel are major drug combinations in 28,3%, 27,3%, 15%, 13%, 12,5% and 9% cases among total medical combinations. Twenty four drug combinations (5,73%) were subsumed to moderate category. This category means the moderate risk of drug adverse event development. Most of moderate drug combinations were: omeprazole + simvastatin (0,6% among total medications, 11,5% among moderate combinations), enalapril + medazolam (0,47% and 9,1%, respectively), fluvoxamine + losartan (0,44% and 8,5%, respectively). Fourteen percents of drug combinations with enalapril were subsumed to moderate category. Drug combinations with nifedipine, amiodarone and fluvoxamine were detected as moderate in 36%, 15,9% and 47,1% cases of total medical combinations. Conclusions: Drug administration for treatment of comorbidity patients in routine ambulatory practice usually performs without evaluation of possible drug interactions caused by changes of activity cytochrome P450 isozymes. About 11% of drug combinations which prescribes to ambulatory comorbidity patients are potential dangerous. In order to prevention of drug adverse event development in comorbidity patients is strongly effort to avoid combinations of drugs which have major or moderate profile.

Need of advance clinical pharmacy services: A case study from Pakistan

Clinical pharmacists play a key role in health-care by providing drug information to other health-care professionals, pharmaceutical care to individual patients and developing clinical guidelines and standard treatment protocols for treating various medical conditions in day-to-day practice. A clinical pharmacist offers valuable support in the development of a final prescription with improved patient management and better safety. Increasingly, clinical practice is becoming a team effort with a specialized skill matrix, concentrating on comprehensive support for patient management. A physician definitely leads the team, comprised of a professional and skillful clinical pharmacist, among others, with skill sets to detect drug interactions, adverse effects, and therapeutic incompatibilities to facilitate the health-care team to achieve therapeutic outcomes on a case-by-case basis. We described ten cases of patients diagnosed with tuberculosis, drug related problems identified during the study period and strategies suggestion for improvement of the pharmacy profession.

Designing Decision Support System to Detect Drug Interactions Type 2 Diabetes.

Background and Aim:Type II Diabetes is the most common diseases of metabolic disorders and the treatment of oral anti-diabetic drug use takes place But The problem of using multi-drug and interactions at the same time is an issue that has always been a major challenge And diagnosis of drug interactions, particularly in Diabetic patients due to the problem with the disease is very important. The purpose of this studying is, to design a clinical assistant decided to use this approach to determine the type II diabetes drug interactions this makes it easy for those who are active in the field.Materials and Methods:Study is Developmental that to determine the content of the system a self-made checklist was used. Checklist Validity and reliability has been confirmed by four professors. The Research community to determine the content of the system was country endocrine that are 124 people. The sample size was calculated using Cochran that was 57 people. The Score of checklist was calculated in SPSS version 20 .finally, the checklist was approved by at least 70% points. The system by using Microsoft SQL server 2008 and visual Studio 2012 development environment was designed in C#.net. In the end, In order to evaluate the software to determine the level of satisfaction, usability and ease of use, designed systems sharing with all Medical Informatics students of Tehran University of Medical Sciences. For this purpose a self-made questionnaire was used. Questionnaire Validity has been confirmed by four professors and reliability was assessed by Cronbach method.Results:The results of the survey are showing that the majority of students found out and believed the software is useful and easy to use and generally expressed their satisfaction software.Conclusions:The methodology provides a suitable approach for analysis and modeling of data in the medical field and the performance is good.

Pharmacoepidemiological study of drug-drug interactions in onco-hematological pediatric patients.

Onco-hematological patients are particularly susceptible to drug-drug interactions (DDIs) because they often undergo multiple combined treatments. Some studies have analyzed the frequency of DDIs in adult patients with cancer; however, the prevalence of DDIs in children, and especially among pediatric cancer patients, remains unknown. To determine the prevalence of DDIs in treatment sheets comparing two commonly used drug interaction databases, to describe the most common clinically relevant DDIs (CR-DDIs) and to investigate the risk factors associated with them. An onco-hematological pediatric unit from a tertiary hospital in Spain. A prospective, observational and descriptive study was carried out from November 2012 to February 2013. Twice a week, every patient's treatment sheet was collected. Each medication list was screened through two databases: Thomson Micromedex™ and Drug Interaction Facts™. All identified DDIs were graded by their level of severity. Summary statistics were used to describe patient and disease characteristics, most often prescribed drugs, and frequency, types and classification of CR-DDIs. Multivariate analysis was used to identify risk factors associated with CRDDIs. Prevalence of CR-DDIs was measured as percentage. A total of 506 potential DDIs were detected in 150 treatment sheets. The prevalence of CR-DDIs by Micromedex database and Drug Interaction Facts database were 44.7 and 51.3% respectively. Amikacin, azole antifungals, antiemetics and cyclosporine were the most frequent drugs involved in CR-DDIs. In multivariate analysis, the main risk factor associated with increased odds for CR-DDIs was a higher number of drugs. The frequency of potential DDIs was related to a higher number of drugs, being immunosuppressant and azole antifungal agents the most commonly involved drugs. The lack of agreement between different databases enhances the complexity to detect drug interactions in clinical practice.

A case report on the significance of clinical pharmacy services in India.

Key Clinical MessageA clinical pharmacist offers invaluable support in the development of a final prescription with better patient management and enhanced safety. Increasingly, medical practice is becoming a team effort with a specialized skill matrix, concentrating on multifaceted support for patient management. A physician undoubtedly leads the team, comprised of a specialist and skilled clinical pharmacist, among others, with skill sets to detect drug interactions, adverse effects, and therapeutic incompatibilities to enable the health-care team to achieve therapeutic outcomes on a case-by-case basis.

Use of Mobile Phones for Monitoring Adverse Drug Reaction in Pharmacy and Drug Stores in Ishaka, Uganda - a Pilot Assessment of Willingness to Report

Aim: We investigated reporting of Adverse Drug Reaction (ADR) following use of drugs purchased from open system pharmacy (OSP) and drug stores, and the effectiveness of mobile phones for reporting drug reactions and detection of drug interactions. Study Design: The study was descriptive and inceptional. Place and Duration of Study: Selected Pharmacies and drug stores in Ishaka Municipality, Bushenyi, Uganda, between January and April 2012. Methodology: A total of 190 participants purchasing prescription and non prescription drugs in the drug outlets were enrolled and drug purchases documented. Structured interviews were used to assess any existing system of ADR tracking. Possible interactions were assessed using electronic checkers software on drug combinations prescribed or purchased. Mobile phone calls were used to monitor the reporting potential, use of medication and events or reactions following drug use for ADRs. Results: No formalized pre-study system was found for tracking ADR in the OSP and drug stores studied. Participants purchased 420 different medications with 55.8% without prescription. Antibiotics, analgesics and antimalarials ranked most purchased medications. All participants carried at least a functional mobile phone and demonstrated interest to report ADRs. Mean Effective Mobile Phone Contact Ratio (MEMPCR) for ADR monitoring was 0.91+0.2 and follow-up was 96% (n=183) and 89.5% on days 0 and 4 respectively. Interactions predicted were in 24.8% (31). Significant reporting of at least one of 404 reactions occurred within 72hr compared to 96-120hr (P=0.003). Two participants had reaction leading to discontinued use of Cotrimoxazole. Conclusion: Use of mobile phones and drug interaction checker software may avail early detection of ADR and reporting. Facilitated toll free- call service may be an effective means of extending the scope of ADR tracking in addition to Yellow Card scheme, and augment involvement of pharmacists and consumers in safe use of drugs.

Fast detection of drug interaction in Mycobacterium tuberculosis by a checkerboard resazurin method

Tuberculosis (TB) is a health public problem and a long combination therapy is necessary to treat patients. In recent years, some drugs, not routinely used in treatment of TB, have appeared as promising new anti-TB therapies in patients with resistance to classical drugs. The aim of this study was: (i) to evaluate a modified checkerboard assay, Resazurin drugs combination microtiter assay (REDCA) to detect drugs interaction in Mycobacterium tuberculosis; (ii) to evaluate the interaction between isoniazid (INH) or ethambutol (EMB) with levofloxacin (LEVO) in susceptible and resistant M.tuberculosis Brazilian clinical isolates. M.tuberculosis H37RV ATCC 27294 and 19 clinical isolates (10 resistant and 9 susceptible) were tested. The fractional inhibitory concentration index (FICI)≤0.5 was considered synergistic. Synergism in M.tuberculosis H37RV and resistant M.tuberculosis Brazilian isolates was observed with EMB vs. LEVO. No synergism was observed with INH vs. LEVO by both assays. No statistical difference was observed by the two assays studied. REDCA showed to be a simple assay for detecting synergism between drugs in M.tuberculosis. The results with EMB vs. LEVO are promising and it can be a new option in future investigations of drugs interactions against M.tuberculosis with the view to reduce EMB adverse effects.

Application of a drug-interaction detection method to the Korean National Health Insurance claims database

Drug interactions (DIs) constitute a serious problem and are considered to contribute to 6–30% of all adverse events (AEs). The use of existing data, including claims data, is expected to be helpful in detecting unknown DIs by complementing conventional spontaneous reporting systems. In the present study, an ‘Ω shrinkage measure’ was applied to the Korean National Health claims database to test the potential of the claims database as a DI surveillance resource. A well-known DI between non-steroidal anti-inflammatory drugs (NSAIDs) and diuretics was analyzed using the model. International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10) codes related to DIs were assigned to the AEs of the DIs: I50, I50.0, I50.1, I50.9, R60, R60.1, R60.9, and J81. An elevated occurrence of AEs versus the expected level was observed using a two-sided 95% lower credibility interval limit above zero, Ω025=0.245, which was the screening limit. The result was consistent with the actual DI between the two drugs. The finding indicates that the claims data have the potential to be used as a DI surveillance resource and that the Ω shrinkage measure may be a promising tool for detecting DIs in claims data.

GRP-058 Establishment of a Programme to Detect Drug Interactions Complementary to Electronic Prescriptions

BackgroundOurs is a 110-bed regional hospital with electronic prescribing throughout. The electronic prescription programme offers allergy alert systems and the need for dosage adjustment in renal and hepatic impairment. However,...

The Anthropology of Health for Human Development

Introduction: Clinically significant drug-drug interactions reduce effectiveness of drugs or cause fatal adverse events. Although harmful drug interactions are preventable, clinicians’ recognition and detection of drug interactions is not optimal. Objective: To assess prevalence, clinical significance and factors associated with potential drug-drug interactions at medical ward of Ayder Referral Hospital, Ethiopia. Methods: A cross-sectional study was conducted to determine potential drug-drug interactions. A total of 204 patients’ medical records were analyzed for drug-drug interaction using Micromedex drug interaction software. Data were analyzed using SPSS version 16. Results: We identified 135 interacting-combinations in a total of 266 potential drug-drug interactions (pDDIs) with a mean of 1.3 pDDIs per patient. Of these, 30.1% and 53.7% of patients had at least one major and one moderate pDDIs respectively. The most common pDDIs involved were concurrent use of clarithromycin with simvastatin, aspirin with heparin and dexamethasone with rifampin which have contraindication, major and moderate severity respectively. There was significant association of occurrence of pDDIs with polypharmacy (p<0.01). Conclusion: Potential drug-drug interactions were common at the medical ward of our hospital.

Web Science in Medicine and Healthcare

Medical social-media provide a new source of information within information gaining contexts. Facts, experiences, opinions or information on behaviour can be found in the medical web and could support a broad range of applications. The intention of this Focus Theme is to bring the existing research together and to show the possibilities, challenges and technologies for Web Science in medicine and healthcare. This editorial provides an overview on the landscape of medical social-media and their possibilities in supporting healthcare. Further, it summarizes the three papers included in this Focus Theme. The three papers of this Focus Theme consider different aspects of Web Science in medicine which are 1) detection of drug interactions from social media, 2) inferring community structures from online forums and 3) improving access to online videos through assignment of SNOMED CT terms. All three papers show the potential of medical social-media in supporting health information gathering processes from the web. However, several issues still need to be addressed in future: Methods are necessary for identifying high quality information from the medical web as well as for processing the language that is used by social media users to report about their symptoms, diseases and other health issues.

Detection of drug interactions between protease inhibitors and prescribed treatment in primary care

BackgroundDrug interactions between protease inhibitors and treatment prescribed in primary care may compromise the efficacy of antiretroviral treatment or cause serious adverse reactions.PurposeTo identify potential interactions that may occur in...

Antiretroviral Drug Interactions: Overview of Interactions Involving New and Investigational Agents and the Role of Therapeutic Drug Monitoring for Management

Antiretrovirals are prone to drug-drug and drug-food interactions that can result in subtherapeutic or supratherapeutic concentrations. Interactions between antiretrovirals and medications for other diseases are common due to shared metabolism through cytochrome P450 (CYP450) and uridine diphosphate glucuronosyltransferase (UGT) enzymes and transport by membrane proteins (e.g., p-glycoprotein, organic anion-transporting polypeptide). The clinical significance of antiretroviral drug interactions is reviewed, with a focus on new and investigational agents. An overview of the mechanistic basis for drug interactions and the effect of individual antiretrovirals on CYP450 and UGT isoforms are provided. Interactions between antiretrovirals and medications for other co-morbidities are summarized. The role of therapeutic drug monitoring in the detection and management of antiretroviral drug interactions is also briefly discussed.

Assessment tool for pharmacy drug–drug interaction software

ObjectivesTo assess the performance of pharmacy clinical decision support (CDS) systems for drug–drug interaction (DDI) detection and to identify approaches for improving the ability to recognize important DDIs. Practice descriptionPharmacists rely on CDS systems to assist in the identification of DDIs, and research suggests that these systems perform suboptimally. The software evaluation tool described here may be used in all pharmacy settings that use electronic decision support to detect potential DDIs, including large and small community chain pharmacies, community independent pharmacies, hospital pharmacies, and governmental facility pharmacies. Practice innovationA tool is provided to determine the ability of pharmacy CDS systems to identify established DDIs. It can be adapted to evaluate potential DDIs that reflect local practice patterns and patient safety priorities. Beyond assessing software performance, going through the evaluation processes creates the opportunity to evaluate inadequacies in policies, procedures, workflow, and training of all pharmacy staff relating to pharmacy information systems and DDIs. ConclusionThe DDI evaluation tool can be used to assess pharmacy information systems’ ability to recognize relevant DDIs. Suggestions for improvement include determining whether the software allows for customization, creating standard policies for handling specific interactions, and ensuring that drug knowledge database updates occur frequently.

The use of CD spectroscopy for preliminary detection of drug bioavailability and interaction

The use of CD spectroscopy for preliminary detection of drug bioavailability and interaction

Potential drug interactions in patients admitted to cardiology wards of a south Indian teaching hospital.

The potential drug-drug interaction (pDDI) increases as the number of concomitant medications increases. Patients with cardiovascular disorders are at higher risk for drug- drug interactions because of the types and number of drugs they receive. While drug interactions are reported to be common, there is no published report of the prevalence of such interactions among Indian cardiac patients. The aim of the present study was to identify the pattern of pDDI and document any observed interaction. It was also planned to evaluate the demography of patients and correlate it with the drug-drug interactions. A prospective observational study from Oct 2007 to Apr 2008 was carried out in 'cardiology department' of a hospital in South India. Those patients who were taking at least two drugs and had a hospital stay of at least 48 hours were included in the study. The medications of the patients were analyzed for possible interactions. Factors associated with pDDI were studied. The actual interactions that were observed during the hospital stay in the study subjects were documented. A total of 812 patients were included in the study. 388 pDDIs were identified among 249 patients. The incidence of pDDI was 30.67%. The most common potential interactions were between aspirin & heparin (29.38%), and clopidogrel & heparin (7.21%). Drug classes most commonly involved were antiplatelets, anticoagulants and diuretics. Majority of interactions were of moderate severity, delayed onset, and pharmacodynamic in nature. Total 68 actual interactions were observed in the observed cases. The present study identified pDDIs and also documented interactions in cardiovascular patients. Factors which had correlation with adverse drug interactions were identified. This study highlights the need for screening prescriptions of cardiovascular patients for pDDIs and proactive monitoring of patients who have identified risk factors; this helps in detection and prevention of possible adverse drug interactions.

Detecting Medication Errors in the New Zealand Pharmacovigilance Database

Despite the traditional focus being adverse drug reactions (ADRs), pharmacovigilance centres have recently been identified as a potentially rich and important source of medication error data. To identify medication errors in the New Zealand Pharmacovigilance database (Centre for Adverse Reactions Monitoring [CARM]), and to describe the frequency and characteristics of these events. A retrospective analysis of the CARM pharmacovigilance database operated by the New Zealand Pharmacovigilance Centre was undertaken for the year 1 January-31 December 2007. All reports, excluding those relating to vaccines, clinical trials and pharmaceutical company reports, underwent a preventability assessment using predetermined criteria. Those events deemed preventable were subsequently classified to identify the degree of patient harm, type of error, stage of medication use process where the error occurred and origin of the error. A total of 1412 reports met the inclusion criteria and were reviewed, of which 4.3% (61/1412) were deemed preventable. Not all errors resulted in patient harm: 29.5% (18/61) were 'no harm' errors but 65.5% (40/61) of errors were deemed to have been associated with some degree of patient harm (preventable adverse drug events [ADEs]). For 5.0% (3/61) of events, the degree of patient harm was unable to be determined as the patient outcome was unknown. The majority of preventable ADEs (62.5% [25/40]) occurred in adults aged 65 years and older. The medication classes most involved in preventable ADEs were antibacterials for systemic use and anti-inflammatory agents, with gastrointestinal and respiratory system disorders the most common adverse events reported. For both preventable ADEs and 'no harm' events, most errors were incorrect dose and drug therapy monitoring problems consisting of failures in detection of significant drug interactions, past allergies or lack of necessary clinical monitoring. Preventable events were mostly related to the prescribing and administration stages of the medication use process, with the majority of errors 82.0% (50/61) deemed to have originated in the community setting. The CARM pharmacovigilance database includes medication errors, many of which were found to originate in the community setting and reported as ADRs. Error-prone situations were able to be identified, providing greater opportunity to improve patient safety. However, to enhance detection of medication errors by pharmacovigilance centres, reports should be prospectively reviewed for preventability and the reporting form revised to facilitate capture of important information that will provide meaningful insight into the nature of the underlying systems defects that caused the error.

Extracting drug-drug interactions from biomedical texts

Background A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The detection of drug interactions is an important research area in patient safety since these interactions can become very dangerous and increase health care costs. Although there are different databases supporting health care professionals in the detection of drug interactions, this kind of resources is rarely complete. Drug interactions are frequently reported in journals of clinical pharmacology, making medical literature the most effective source for the detection of drug interactions. However, the increasing volume of the literature overwhelms health care professionals trying to keep an up-to-date collection of all reported DDIs. The development of automatic methods for collecting, maintaining and

Validation of a differential in situ perfusion method with mesenteric blood sampling in rats for intestinal drug interaction profiling

The present study explored the feasibility of a differential setup for the in situ perfusion technique with mesenteric cannulation in rats to assess drug interactions at the level of intestinal absorption. In contrast to the classic, parallel in situ perfusion setup, the differential approach aims to identify intestinal drug interactions in individual animals by exposing the perfused segment to a sequence of multiple conditions. First, the setup was validated by assessing the interaction between the P-glycoprotein (P-gp) inhibitor verapamil and the transport probes atenolol (paracellular transport), propranolol (transcellular) and talinolol (P-gp mediated efflux). While transport of atenolol and propranolol remained constant for the total perfusion time (2 h), a verapamil-induced increase in talinolol transport was observed within individual rats (between 3.2- and 5.2-fold). In comparison with the parallel setup, the differential in situ perfusion approach enhances the power to detect drug interactions with compounds that exhibit strong subject-dependent permeability. This was demonstrated by identifying an interaction between amprenavir and ketoconazole (P-gp and CYP3A inhibitor) in five out of seven rats (permeability increase between 1.9- and 4.2-fold), despite high inter-individual differences in intrinsic permeability for amprenavir. In combination with an increased throughput (up to 300%) and a reduced animal use (up to 50%), the enhanced power of the differential approach improves the utility of the biorelevant in situ perfusion technique with mesenteric blood sampling to elucidate the intestinal interaction profile of drugs and drug candidates.

Primary care practices and determinants of optimal anticoagulation management in a collaborative care model

In a collaborative care model (CCM) for managing oral anticoagulant therapy, patients are followed at a pharmacist-managed anticoagulation service and, once stabilized, are transferred to their primary care physician. The objective of this study was to describe physicians' clinical practices and the practice characteristics associated with better international normalized ratio (INR) control in a CCM. A telephone questionnaire about their practices was administered to 121 physicians exposed to a CCM. The physicians followed 121 patients for a mean of 14.5 weeks. The percentage of time within the exact INR target range was computed and dichotomized (> or = or < median time within target range). Determinants of better INR control were identified using logistic regression models. The survey revealed that, after discharge from the pharmacist-managed anticoagulation service, patients are followed mainly by physicians and their secretaries. Physicians do not often consult other health professionals. Few report using technological resources to obtain INR results (39.7%), document medical follow-up (6.6%), or detect drug (32.2%) and food (9.9%) interactions. The median percentage of time within the exact INR target range was 84%. Determinants of better INR control include using computerized support to monitor patients (odds ratio [OR] 9.16, 95% CI 1.77-47.4) and detect drug interactions (OR 3.49, 95% CI 1.71-7.10) and consulting specialists (OR 5.92, 95% CI 1.49-32.48). Primary care physicians are poorly supported by technological and human resources to monitor patients on oral anticoagulant. Even in a CCM, interprofessional collaboration and better technological support may be associated with optimal INR control.