Dataset Information

Drug-drug-gene interactions and adverse drug reactions.

ABSTRACT: The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug-drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug-drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited published studies on impact of genetic variation on drug-drug interactions. In this review, we establish a detailed classification for pharmacokinetic drug-drug-gene interactions, and give examples from the literature that support this approach. The increasing availability of real-world drug outcome data linked to genetic bioresources is likely to enable the discovery of previously unrecognized, clinically important drug-drug-gene interactions.

SUBMITTER: Malki MA

PROVIDER: S-EPMC7253354 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Drug-drug-gene interactions and adverse drug reactions.

Malki Mustafa Adnan MA Pearson Ewan Robert ER

The pharmacogenomics journal 20191203 3

The economic and health burden caused by adverse drug reactions has increased dramatically in the last few years. This is likely to be mediated by increasing polypharmacy, which increases the likelihood for drug-drug interactions. Tools utilized by healthcare practitioners to flag potential adverse drug reactions secondary to drug-drug interactions ignore individual genetic variation, which has the potential to markedly alter the severity of these interactions. To date there have been limited pu ...[more]

PMID: 31792369

Similar Datasets

Project description:BackgroundNumerous observational studies suggest that preventable adverse drug reactions are a significant burden in healthcare, but no meta-analysis using a standardised definition for adverse drug reactions exists. The aim of the study was to estimate the percentage of patients with preventable adverse drug reactions and the preventability of adverse drug reactions in adult outpatients and inpatients.MethodsStudies were identified through searching Cochrane, CINAHL, EMBASE, IPA, Medline, PsycINFO and Web of Science in September 2010, and by hand searching the reference lists of identified papers. Original peer-reviewed research articles in English that defined adverse drug reactions according to WHO's or similar definition and assessed preventability were included. Disease or treatment specific studies were excluded. Meta-analysis on the percentage of patients with preventable adverse drug reactions and the preventability of adverse drug reactions was conducted.ResultsData were analysed from 16 original studies on outpatients with 48797 emergency visits or hospital admissions and from 8 studies involving 24128 inpatients. No studies in primary care were identified. Among adult outpatients, 2.0% (95% confidence interval (CI): 1.2-3.2%) had preventable adverse drug reactions and 52% (95% CI: 42-62%) of adverse drug reactions were preventable. Among inpatients, 1.6% (95% CI: 0.1-51%) had preventable adverse drug reactions and 45% (95% CI: 33-58%) of adverse drug reactions were preventable.ConclusionsThis meta-analysis corroborates that preventable adverse drug reactions are a significant burden to healthcare among adult outpatients. Among both outpatients and inpatients, approximately half of adverse drug reactions are preventable, demonstrating that further evidence on prevention strategies is required. The percentage of patients with preventable adverse drug reactions among inpatients and in primary care is largely unknown and should be investigated in future research.

Dataset Information

Drug-drug-gene interactions and adverse drug reactions.

Publications

Drug-drug-gene interactions and adverse drug reactions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets