Number Of Drug-drug Interactions Research Articles

Clinicians' Preferences for Sphingosine-1-Phosphate Receptor Modulators in Multiple Sclerosis Based on Clinical Management Considerations: A Choice Experiment.

Four sphingosine-1-phosphate receptor (S1PR) modulators are currently available in the USA for treating relapsing forms of multiple sclerosis (MS). These S1PR modulators have similar efficacy. Clinicians may therefore consider other factors, such as clinical management considerations, when distinguishing among treatments. This study estimated which S1PR modulator clinicians would choose on the basis of a treatment's clinical management and quantified how individual aspects of clinical management might drive this choice. A multi-criteria decision analysis (MCDA) was conducted on the basis of clinical management preferences elicited in a discrete choice experiment (DCE) and real-world clinical management profiles of the S1PR modulators currently available to treat relapsing forms of MS (fingolimod, ozanimod, ponesimod, siponimod). The DCE was completed by neurologists in the USA experienced in treating MS and included eight clinical management attributes: first-dose observations, genotyping, liver function tests, eye exams, drug-drug interactions, interactions with antidepressants, interactions with foods high in tyramine, and immune system recovery time. Attribute levels were selected on the basis of S1PR modulator product labels. In the MCDA, partial MCDA scores were created for each attribute and summed to produce an overall MCDA score for each S1PR modulator. The DCE was completed by 200 neurologists. The overall MCDA score was highest for ponesimod (4.78 points), followed by siponimod (4.10 points), fingolimod (3.61 points), and ozanimod (2.38 points). Having fewer drug-drug interactions contributed most to the overall scores (up to 1.56 points), followed by having no first-dose observations (0.95 points), the shortest immune system recovery time (0.94 points), and not interacting with foods high in tyramine (0.86 points). When considering clinical management convenience, the average US-based neurologist treating MS is likely to choose ponesimod over siponimod, fingolimod, or ozanimod. The strongest driver of preferences was the number of drug-drug interactions. This information can help inform recommendations for the treatment of MS and facilitate shared decision-making between clinicians and patients.

Patients' Preferences for Sphingosine-1-Phosphate Receptor Modulators in Multiple Sclerosis Based on Clinical Management Considerations: A Choice Experiment.

Several sphingosine-1-phosphate receptor (S1PR) modulators are available in the US for treating relapsing forms of multiple sclerosis (RMS). Given that these S1PR modulators have similar efficacy and safety, patients may consider the clinical management characteristics of the S1PR modulators when deciding among treatments. However, none of the S1PR modulators is clearly superior in every aspect of clinical management, and for some treatments, clinical management varies based on a patient's comorbid health conditions (e.g., heart conditions [HC]). This study aimed to determine which S1PR modulator patients with relapsing-remitting multiple sclerosis (RRMS) would prefer based on clinical management considerations, and to estimate how different clinical management considerations might drive these preferences. Preferences were explored separately for patients with and without comorbid HC. A multicriteria decision analysis was conducted on S1PR modulators approved to treat RMS: fingolimod, ozanimod, siponimod, and ponesimod. Clinical management preferences of patients with RRMS were elicited in a discrete choice experiment (DCE) in which participants repeatedly chose between hypothetical S1PR modulator profiles based on their clinical management attributes. Attributes included first-dose observations, genotyping, liver function tests, eye examinations, drug-drug interactions, interactions with antidepressants, interactions with foods high in tyramine, and immune system recovery time. Preferences were estimated separately for patients with HC and without HC (noHC). Marginal utilities were calculated from the DCE data for each attribute and level using a mixed logit model. In the multicriteria decision analysis, partial value scores were created by applying the marginal utilities for each attribute and level to the real-world profiles of S1PR modulators. Partial value scores were summed to determine an overall clinical management value score for each S1PR modulator. Four hundred patients with RRMS completed the DCE. Ponesimod had the highest overall value score for patients both without (n=341) and with (n=59) HC (noHC: 5.1; HC: 4.0), followed by siponimod (noHC: 4.9; HC: 3.3), fingolimod (noHC: 3.4; HC: 2.8), and ozanimod (noHC: 0.9; HC: 0.8). Overall, immune system recovery time contributed the highest partial value scores (noHC: up to 1.9 points; HC: up to 1.2 points), followed by the number of drug-drug interactions (noHC: up to 1.2 points; HC: up to 1.7 points). When considering the clinical management of S1PR modulators, the average patient with RRMS is expected to choose a treatment with shorter immune system recovery time and fewer interactions with other drugs. Patients both with and without heart conditions are likely to prefer the clinical management profile of ponesimod over those of siponimod, fingolimod, and ozanimod. This information can help inform recommendations for treating RRMS and facilitate shared decision making between patients and their doctors.

Methodology for Creating a Risk Management System for Drug-Drug Interactions

Drug-drug interactions (DDIs) are a major cause of hospital admissions, accounting for 16.6% of ADRs and about 1% of all hospital admissions. Polypharmacy is on the rise, with a Swedish population-based study of people aged ;;;75 years showing that the prevalence of polypharmacy increased from 27% in 1988 to 54% in 2001 and to 65% in 2006. The aim of the study was to analyze the databases on DDI and to assess the possibility of their use in managing the risks of pharmacotherapy in the Russian Federation and the EAEU. Results. The main DDI databases are characterized. The degree of inconsistency in data on the number of DDI, severity and clinical recommendations was determined. The basic requirements for the completeness of information in databases are formulated. The necessity to harmonize approaches to providing information about DDI, as well as the need to create local databases for medical organizations were revealed. A computer program has been created to minimize the risks of DDI in clinical practice, for expert and scientific purposes. Conclusions. Databases and programs for DDI have different goals, a different set of data on DDI with varying degrees of evidence, differences in assessment of severity, likelihood of occurrence, clinical recommendations for treatment and correction of DDI. The variability of information is due to the lack of a unified system for assessing the severity and likelihood of potential negative consequences of DDI; different purposes for creation; difference in budgets at creation. This situation leads to warning redundancy and physician fatigue from insignificant or unproven DDIs. Based on the identified requirements for local databases, a computer program for modeling rational pharmacotherapy for lower respiratory tract infections was created and received a certificate of state registration.

Aile Hekimliği Yaşlı Hasta İzlemi Kapsamında Polifarmasinin Değerlendirilmesi

Çalışmamızın amacı Sağlık Bakanlığı Hastane Medulla Sistemi kullanılarak polifarmasiye maruz kalan 65 yaş ve üstü hastalarda, ilaç-ilaç etkileşimlerinin belirlenip, ciddi etkileşimleri olan hastalarda klinik önlem alınması için farkındalık yaratmaktır. Çalışmamız Gebze 1 nolu Aile Sağlığı Merkezi’nden hizmet almakta olan 65 yaş üstü, Hasta Yönetim Platformu veri tabanında yer alan 188 hasta üzerinde yapılmıştır. Lexicomb® ilaç etkileşimi modülü ile hastaların kronik olarak kullandıkları ilaçlar listelenerek etkileşim düzeyleri değerlendirilmiştir. Bununla birlikte yaşlılarda uygunsuz ilaç kullanımı değerlendirilmesinde kullanılan kriterler üzerinde de durulmuştur. Çalışma sonuçlarımıza göre, 167 hastada toplamda 529 potansiyel ilaç-ilaç etkileşimi görüldü. Bu etkileşimlerin 52’sinde (%9,8) bilinen bir etkileşim saptanmadı ve risk kategorisi A olarak tespit edildi. B, C, D ve X risk kategorilerinde ilaç-ilaç etkileşimi sayıları sırasıyla, 74 (%13,9), 363(%68,6), 33 (%6,2) ve 7 (%1,3) idi. Çalışmadaki hastaların %54’ünde esansiyel hipertansiyon tanısı mevcuttu. En çok kullanılan ilaç ise asetilsalisilik asit (%26)’di. C kategorisinde ilaç-ilaç etkileşim potansiyelinin verilerimize göre anlamlı oranda yüksek çıkması, hastaların tedavisinin daha düzenli ve etkili bir şekilde monitorize edilmesinin gerekliliğini vurgulamaktadır. D ve X kategorisinde saptanan ilaç-ilaç etkileşimleri en fazla nonsteroidal antiinflamatuar ilaçlar, antihipertansif ilaçlar, antipelet ilaçlar ve santral sinir sistemi ilaçlar arasında meydana gelmiştir. Bu ilaçların takibine özellikle dikkat edilmelidir.

Prevalence of potential drug − drug interactions in the cardiothoracic intensive care unit patients in a Chinese tertiary care teaching hospital

BackgroundWith an increasing number of reviews describing clinically significant drug–drug interactions (DDIs), the scope and severity of interactions involving commonly used drugs in cardiothoracic intensive care units (CCUs) remain unclear. This study aims to identify risk factors and determine the incidence of potential DDIs in intensive care units.MethodsDDIs were identified based on the profile of the prescribed drug and classified according to the Micromedex drug interaction database. Potential risk factors associated with DDIs have been identified.ResultsA total of 3193 medication episodes were evaluated, and 680 DDIs (21.3%) were found. A total of 203 patients were recruited into the study, with an average of 3.4 DDIs per patient [95% confidence interval (3.2 − 3.6)]. A total of 84.2% of the patients experienced at least one DDI. Anticoagulant and antiplatelet agents were involved in 33.5% (228/680) of the potential drug − drug interactions in the CCU. Univariate analysis and multiple logistic regression analysis showed that the age of the patient and the number of medications prescribed were significantly correlated with the occurrence of DDIs. In multiple linear regression analysis, the number of DDIs had a significant correlation only with the number of prescription drugs.ConclusionsA high prevalence of DDIs was observed, especially in intensive care units without pharmacist intervention and computerized drug monitoring systems, highlighting the need for active surveillance to prevent potential adverse events.

Drug-drug interactions in atrial fibrillation patients receiving direct oral anticoagulants

Polypharmacy is common in patients with atrial fibrillation (AF), making these patients vulnerable to the occurrence of potential drug-drug interactions (DDIs). We assessed the risk of ischemic stroke and major bleeding in the context of concomitant treatment with potential DDIs in patients with AF prescribed direct oral anticoagulants (DOACs). Using the common data model (CDM) based on an electronic health record (EHR) database, we included new users of DOACs from among patients treated for AF between January 2014 and December 2017 (n = 1938). The median age was 72 years, and 61.8% of the patients were males, with 28.2% of the patients having a CHA2DS2-VASc score in category 0–1, 49.4% in category 2–3, and 22.4% in category ≥ 4. The CHA2DS2-VASc score was significantly associated with ischemic stroke occurrence and hospitalization for major bleeding. Multiple logistic regression analysis showed that increased risk of ischemic stroke and hospitalization for major bleeding was associated with the number of DDIs regardless of comorbidities: ≥ 2 DDIs was associated with ischemic stroke (OR = 18.68; 95% CI, 6.22–55.27, P < 0.001) and hospitalization for major bleeding (OR = 5.01; 95% CI, 1.11–16.62, P < 0.001). DDIs can cause reduced antithrombotic efficacy or increased risk of bleeding in AF patients prescribed DOACs.

Prevalence of drug interactions in hospitalised elderly patients: a systematic review

Background: The prevalence of drug–drug interactions (DDIs) in hospital settings is variable, and elderly patients are considered a high risk population for DDIs. There are no systematic reviews describing the prevalence of DDIs in hospitalised elderly patients. Objectives: To assess and summarise the available data on the prevalence of DDIs in hospitalised elderly patients and to describe which drugs, drug classes and drug combinations are most commonly involved in DDIs. Data source: A systematic electronic literature search was conducted on Medline/PubMed, Embase, Lilacs, SciElo, Web of Science, Cinahl, Scopus, Cochrane, OpenGrey, Capes Thesis Bank, OasisBR, OpenAire and abstracts from scientific events, without limitation on language or period of publication. Study selection was completed on 21 September 2018. Study eligibility criteria, participants and interventions: Original observational studies that reported the prevalence of actual or potential DDIs during hospitalisation in patients aged 60 years or older were included. The main outcome measure was prevalence of DDIs and number of DDIs per patient. Subgroup analysis was performed in studies that reported the prevalence of DDIs in geriatric units. Study appraisal and synthesis methods: Study quality was assessed using the Agency for Healthcare Research and Quality methodological checklist for cross sectional and prevalence studies. Results: 34 studies were included, involving 9577 patients. The prevalence of DDIs ranged from 8.34% to 100%. In studies conducted in geriatric units, the prevalence ranged from 80.5% to 90.5%. The number of DDIs per patient ranged from 1.2 to 30.6. Single drugs most commonly involved in DDIs were furosemide, captopril, warfarin and dipyrone. Drug classes mostly involved were potassium sparing diuretics and angiotensin converting enzyme inhibitors. Limitations: The main limitation is the heterogeneity between the included studies that precluded a metaanalysis. Several different methods were used to identify DDIs, majorly, and potential DDIs. Few studies have reported measures to control the quality of the collected data. Conclusions and implications of key findings: The prevalence of DDIs ranged widely, and the variation may reflect differences in the conditions of the elderly patients and level of attention (or complexity of care), as well as methodological differences, especially the methods and/ or software used to identify DDIs.

Evaluation of a specialty hepatitis C virus telephone pharmacy service.

Direct-acting antivirals (DAAs) used to treat hepatitis C virus (HCV) infection are associated with significant drug-drug interactions (DDIs). Pharmacists are well positioned to identify and mitigate these DDIs. Data to guide assessment of the impact of HCV specialty pharmacy services on identifying and addressing DDIs with DAAs are lacking. The overall purpose of the study described here was to determine the incidence and severity of DDIs identified by specialty pharmacists among patients treated with DAAs prior to and 1 month into therapy. An observational, retrospective study was conducted to evaluate the impact of specialty pharmacy services in mitigating DDIs associated with use of DAAs. Adult patients with HCV infection (n = 200) who received DAAs and were enrolled with a specialty pharmacy service over a 1-year period were included. Endpoints included number, severity, and type of DDIs and DDIs per patient at baseline and 1 month into therapy, pharmacists' interventions, and safety and clinical outcomes. Fifty-nine percent of patients had at least 1 DDI. A total of 170 DDIs were identified (137 at baseline and 33 at 1-month follow-up), and the mean number of DDIs per patient significantly decreased from baseline to 1-month follow-up (from 1.38 to 0.16, P < 0.0001). The rate of "potentially clinically significant" or "critical" interactions was significantly lower at 1-month follow-up vs baseline assessment (69.6% vs 81.7%, P < 0.0001). The most commonly identified DDIs involved acid suppressive medications (49.6% and 66.6% of DDIs at baseline and follow-up assessment, respectively) and cardiovascular medications (26.2% and 21.2%, respectively). Total number of DDI interventions was 131, with an acceptance rate of 85%. Most common intervention was patient education and monitoring. Approximately 60% of patients had DDIs with DAAs. Implementing HCV specialty pharmacy services significantly decreased DDIs while maintaining SVR12.

Antibiotic therapy under polypragmatic conditions: a course to safety

Prescribing safe and effective drug therapy is becoming increasingly challenging. Recently, there has been an upward trend in the number of patients experiencing polypragmasy. Thus, according to epidemiological analysis of 180,815 outpatient records in Scotland, 4–9 medications were simultaneously prescribed in 16.9% of cases, 10 or more drugs – in 4.6% of cases. As the number of medications taken by an individual patient increases, so does the likelihood of drug-drug interactions which have clinically important consequences. The number of drug-drug interactions is increasing as new drugs are approved, different metabolic pathways and drug transporters are discovered, and co-prescribing recommendations emerge. This article provides an overview of principles and mechanisms of drug-drug interactions and describes pharmacokinetic and pharmacodynamic interactions associated with antibiotic therapy.

Antibiotic therapy under polypragmatic conditions: a course to safety

Prescribing safe and effective drug therapy is becoming increasingly challenging. Recently, there has been an upward trend in the number of patients experiencing polypragmasy. Thus, according to epidemiological analysis of 180,815 outpatient records in Scotland, 4–9 medications were simultaneously prescribed in 16.9% of cases, 10 or more drugs – in 4.6% of cases. As the number of medications taken by an individual patient increases, so does the likelihood of drug-drug interactions which have clinically important consequences. The number of drug-drug interactions is increasing as new drugs are approved, different metabolic pathways and drug transporters are discovered, and co-prescribing recommendations emerge. This article provides an overview of principles and mechanisms of drug-drug interactions and describes pharmacokinetic and pharmacodynamic interactions associated with antibiotic therapy.

Proactive inter-disciplinary CME to improve medication management in the elderly population.

The absence of collaboration between health professionals is known to influence prescriptions' quality, also disadvantaging elderly frail patients' polytherapies. This study aims to improve the adherence to medications of elderly patients suffering from multiple diseases through interpersonal continuing medical education (CME). The CME was organized for general practitioners (GPs) by hospital pharmacists (HPs) from a Territorial Pharmaceutical Centre of Piedmont, in collaboration with pharmacists from the Drug Science and Technology Department of the University of Turin, to enhance awareness on the management of chronic therapies and de-prescription. Pharmacists set face-to-face lessons for GPs between April 2018 and November 2018, while therapies' reconciliation and delivery of the Illustrated Therapy Schedules (ITS) lasted until September 2019. Polytherapies were evaluated by pharmacists and GPs in terms of appropriateness (number of potentially inappropriate prescriptions - PIPs according to 2019 Beers Criteria) and number of drug-drug interactions (DDIs), using a clinical decision support system (CDSS - NavFarma©) to help health professionals dealing with the process of review, reconciliation and individuation of possible adverse reactions. From the CME organization it emerged that the collaboration between health professionals supported by a CDSS could improve the quality of elderly patients polytherapies. Two-hundred fifteen patients were enrolled by GPs; patients included were aged - results reported as average (sd) - 76.4 (6.3), mostly men (54.9%), number of daily medications per patient was 8.1 (2.4); 2.1 (1.8) DDIs per patient were individuated, 12.9% of which were solved thanks to the CME. Average number of PIPs found was 2.5 (1.4) per patient. The CME represented a proactive approach by HPs to the management of elderly patients' polytherapies. Moreover, clinicians' engagement is a mean to enhance quality, safety, professionalism and communication in health processes.

Potentially Inappropriate Medications, Drug-Drug Interactions, and Anticholinergic Burden in Elderly Hospitalized Patients: Does an Association Exist with Post-Discharge Health Outcomes?

Polypharmacy is very common in elderly patients and is associated with detrimental outcomes. Our objective was to evaluate the associations between a large panel of therapy quality indicators, including explicit lists of potentially inappropriate medications (PIMs; Beers criteria and Screening Tool of Older Persons' potentially inappropriate Prescriptions [STOPP] criteria), the Anticholinergic Cognitive Burden (ACB) score, and the number of drug-drug interactions (DDIs), with respect to mortality, rehospitalization, and physical function decline within 3months from hospital discharge in a cohort of hospitalized elderly patients. We studied 2631 individuals aged ≥ 65years (median age 79.6; males 48.6%) enrolled in the REPOSI registry. The relationships with mortality and rehospitalization were evaluated using Cox regressions, and relationships with functional status change (as percentage variation of Barthel Index [BI]) were evaluated using mixed linear models. None of the studied indicators was associated with mortality and rehospitalization. Conversely, only ACB was associated with physical function decline, even after correction for confounders (adjusted mean BI variation of -7.55%; 95% confidence interval [CI] -12.37 to -2.47). The number of medications at discharge, particularly polypharmacy (more than five drugs daily), were the only therapy-related factors associated with mortality (adjusted hazard ratio [aHR] 1.05 [95% CI 1.01-1.10] and 1.70 [95% CI 1.12-2.58], respectively) and rehospitalization (aHR 1.05 [95% CI 1.01-1.08] and 1.31 [95% CI 1.01-1.71], respectively). Polypharmacy, a very simple measure, outperformed sophisticated PIM and DDI indicators of quality of therapy as a correlate of primary clinical outcomes, whereas ACB was associated with physical function decline. Thus, innovative approaches to the definition and research of PIMs and DDIs are eagerly awaited from the perspective of averaging the quantitative burden and qualitative interaction of drugs.

ISCMF: Integrated similarity-constrained matrix factorization for drug–drug interaction prediction

Drug–drug interaction (DDI) prediction prepares substantial information for drug discovery. As the exact prediction of DDIs can reduce human health risk, the development of an accurate method to solve this problem is quite significant. Despite numerous studies in the field, a considerable number of DDIs are not yet identified. In the current study, we used Integrated Similarity-constrained matrix factorization (ISCMF) to predict DDIs. Eight similarities were calculated based on the drug substructure, targets, side effects, off-label side effects, pathways, transporters, enzymes, and indication data as well as Gaussian interaction profile for the drug pairs. Subsequently, a non-linear similarity fusion method was used to integrate multiple similarities and make them more informative. Finally, we employed ISCMF, which projects drugs in the interaction space into a low-rank space to obtain new insights into DDIs. However, all parts of ISCMF have been proposed in previous studies, but our novelty is applying them in DDI prediction context and combining them. We compared ISCMF with several state-of-the-art methods. The results show that It achieved more appropriate results in five-fold cross-validation. It improves AUPR, and F-measure to 10% and 18%, respectively. For further validation, we performed case studies on numerous interactions predicted by ISCMF with high probability, most of which were validated by reliable databases. Our results provide support for the notion that ISCMF might be used unequivocally as a powerful method for predicting the unknown DDIs. The data and implementation of ISCMF are available at https://github.com/nrohani/ISCMF .

Medication regimen complexity is associated with pharmacist interventions and drug‐drug interactions: A use of the novel MRC‐ICU scoring tool

AbstractBackgroundClinical pharmacists are established members of the interprofessional patient care team, but limited guidance for the optimal utilization of pharmacy resources is available. Objective measurement of medication regimen complexity offers a novel process for evaluating pharmacist activity. The purpose of this study was to evaluate the relationship between medication regimen complexity, as measured by a novel medication regimen complexity scoring tool (MRC‐ICU), and both pharmacist interventions and drug‐drug interactions (DDIs).MethodsThis was a multi‐center, prospective, observational study. The electronic medical record was reviewed to collect patient demographics, patient outcomes, and MRC‐ICU and modified MRC‐ICU (mMRC‐ICU) score at 24, 48 hours, and at discharge. Pharmacist interventions were recorded during the patients' intensive care unit (ICU) stay. DDIs were also evaluated at 24, 48 hours, and at discharge. Spearman's rank‐order correlation was used to determine any correlation between the MRC‐ICU score at each time point and the number of pharmacist interventions and DDIs.ResultsA total of 153 patients were evaluated from both centers. The median MRC‐ICU at 24 hours was 11 (interquartile range [IQR] 7‐15). MRC‐ICU at 24 hours was correlated with interventions at 24 hours (rs .439, P &lt;.001). Furthermore, MRC‐ICU was correlated with total DDIs (rs .4, P &lt; .001). A modified version of the MRC‐ICU was also correlated with number of pharmacist interventions (P &lt; .001) and DDIs (P &lt; .001).ConclusionsMedication regimen complexity showed a relationship with number of pharmacist interventions and number of DDIs.

Polypharmacy in an Elderly Population: Enhancing Medication Management Through the Use of Clinical Decision Support Software Platforms.

IntroductionPolypharmacy is a growing problem in the United States. The use of multiple medications increases the likelihood that a patient will experience potential drug interactions and adverse drug reactions (ADRs). Those individuals with dementia or Alzheimer’s disease (AD) are at greater risk, due to age, comorbidities, and an increased likelihood of being on a greater number of neuroactive medications.MethodsuMETHOD Health (uMH) has developed a precision medicine platform to address dementia and mild AD through the creation of personalized, multidomain treatment plans. Many interactions and ADRs may be observed, such as drug–drug interactions (DDIs), drug–gene interactions (DGIs), anticholinergic cognitive burden (ACB), and depression-inducing drugs (DIDs). uMH’s algorithms can parse these interactions, rate them based on input from open-source databases, and then record all these interactions in a generated treatment plan. A total of 295 individuals aged 65 and older were included in this analysis.ResultsOf 295 individuals, 97.59% were on at least one medication, with an overall mean of 11.5 medications per person; 83.66% were on five or more medications. A total of 102 DGIs, 3642 DDIs, and one high-priority DDI were found in this population. There was a significant increase in the number of DDIs as medications per person increased (P value < 0.0001). Of the population, 65.86% were on one or more anticholinergic drugs. There was a significant difference in the ACB score between individuals with cognitive decline and those without. In total, 60.98% of the overall population were on DIDs, with a mean of 1.19 medications per person.ConclusionsThe results of this work show that older populations have a high medication burden. With the growing elderly and AD populations, medication management for polypharmacy is a need that grows direr every year. uMH’s platform was able to identify a multitude of polypharmacy problems that individuals are currently facing.FundinguMETHOD Health.

Incidence of Drug-Drug Interactions among Patients Admitted to the Department of General Medicine in a Tertiary Care Hospital

<p style="text-align: justify;"><strong>Background:</strong> Drug-Drug Interactions (DDIs) contribute to increased rate of morbidity and mortality increasing the need for intense monitoring of patient safety which can be achieved by detecting and preventing morbidities associated with DDIs. <strong>Objective and Methodology:</strong> The present work was a prospective study carried out for a period of six months, to assess the incidence of DDIs in patients admitted to the Department of General Medicine at a tertiary care hospital. <strong>Results:</strong> Prescriptions of 411 patients were analysed, out of which 165 (40.15%) prescriptions were identified with potential DDIs whereas clinical manifestations of actual DDIs were observed and reported in 23 (5.6%). A total of 657 DDIs were observed of which 6 (0.9%), 240 (36.5%), 374 (56.9%) and 33 (5.6%) were of contraindicated, major, moderate and minor severity respectively. Based on the mechanism 310 (47.2%) of the identified DDIs were pharmacodynamic and 243 (36.9%) were pharmacokinetic interactions. There was a positive correlation between the number of DDIs and risk factors such as length of hospital stay, number of drugs prescribed and co-morbidities. <strong>Conclusion:</strong> This study concludes that awareness on the most prevalent DDIs can help the practitioners to prescribe drugs with a low risk for DDIs and prevent the concomitant use of dangerous drug combinations. <p style="text-align: justify;"><strong>Key words:</strong> Drug-drug interactions, General medicine, Pharmacodynamic, Pharmacokinetic, Severity, Risk factors.

STUDY OF DRUG-DRUG INTERACTION IN THE INPATIENTS OF A TERTIARY CARE HOSPITAL AT CALICUT

Objective: The study was conducted to monitor the potential drug-drug interactions in the prescriptions of inpatients in a tertiary care hospital based on the mechanism and severity.Methods: This prospective observational study was conducted by collecting the prescriptions containing two or more drugs. The interactions were checked using an interaction checker and were categorized into pharmacokinetic and pharmacodynamic interactions on the basis of mechanism of action and severity based on the risks or consequences of the interactions.Result: Among 150 randomly collected prescriptions, 123 (82%) prescriptions had 396 drug-drug interactions. The pharmacodynamic drug interactions (77.27%) were more common when compared to pharmacokinetic drug interactions (22.73%). There was high prevalence of drug-drug interactions among the patients above the age of 60 years (56.09%). The moderate drug-drug interactions (81.81%) were found to be more when compared to the major (10.61%) and minor (7.58%) interactions. The neurology department prescriptions were observed to have more number of drug-drug interactions (26.01%).Conclusion: A systematic approach and close monitoring of the medication chart is necessary to identify the potential drug-drug interactions. The clinicians and other health-care professionals at the study site require an awareness program in regard to identification and management of drug-drug interactions. Clinical pharmacist can play an important role in the monitoring and management of drug-drug interactions.

DrugBank 5.0: a major update to the DrugBank database for 2018.

DrugBank (www.drugbank.ca) is a web-enabled database containing comprehensive molecular information about drugs, their mechanisms, their interactions and their targets. First described in 2006, DrugBank has continued to evolve over the past 12 years in response to marked improvements to web standards and changing needs for drug research and development. This year’s update, DrugBank 5.0, represents the most significant upgrade to the database in more than 10 years. In many cases, existing data content has grown by 100% or more over the last update. For instance, the total number of investigational drugs in the database has grown by almost 300%, the number of drug-drug interactions has grown by nearly 600% and the number of SNP-associated drug effects has grown more than 3000%. Significant improvements have been made to the quantity, quality and consistency of drug indications, drug binding data as well as drug-drug and drug-food interactions. A great deal of brand new data have also been added to DrugBank 5.0. This includes information on the influence of hundreds of drugs on metabolite levels (pharmacometabolomics), gene expression levels (pharmacotranscriptomics) and protein expression levels (pharmacoprotoemics). New data have also been added on the status of hundreds of new drug clinical trials and existing drug repurposing trials. Many other important improvements in the content, interface and performance of the DrugBank website have been made and these should greatly enhance its ease of use, utility and potential applications in many areas of pharmacological research, pharmaceutical science and drug education.

Interações medicamentosas em prescrições para idosos hospitalizados com Síndrome Coronariana Aguda

Objetivou-se determinar a taxa de interações medicamentosas potenciais teóricas em prescrições para idosos diagnosticados com Síndrome Coronariana Aguda em um hospital de ensino. Estudo descritivo exploratório com análise de 607 prescrições através de bases de dados informatizadas para identificar e classificar as interações de acordo com a intensidade (maior, moderada ou menor), mecanismo (farmacocinético ou farmacodinâmico) e relevância da documentação. Foram detectadas 10.162 interações, distribuídas entre 554 tipos de combinações diferentes dentre os medicamentos prescritos, e 99% das prescrições apresentaram pelo menos uma e máximo de 53 interações, destacando-se a prevalência de maiores e moderadas. Houve correlação entre o número de interações e o número de medicamentos prescritos e o tempo de hospitalização. Este estudo contribui para a delimitação do padrão de prevalência das interações medicamentosas em prescrições para Síndrome Coronariana Aguda, além de subsidiar a importância da implantação efetiva da Farmácia Clínica em hospitais de ensino.

A cooperation project between hospital pharmacists and general practitioners about drug interactions in clinical practice

Objectives(1) To evaluate drug–drug interactions (DDIs) in general practitioners’ (GPs) prescriptions; (2) to implement a cooperation project between pharmacists and GPs to improve DDI management and patient care.MethodsIn 2013, pharmacists...