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Hierarchy of evidence in interpretation of clinical significance of drug interactions

DOI: 10.2298/mpns1202045n

Keywords: Drug Interactions , Polypharmacy , Drug Therapy , Combination + adverse effects , Evidence-Based Medicine + standards , Access to Information , Follow-Up Studies

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Abstract:

Introduction. Since drug interactions may result in serious adverse effects or failure of therapy, it is of huge importance that health professionals base their decisions about drug prescription, dispensing and administration on reliable research evidence, taking into account the hierarchy of data sources for evaluation. Clinical Significance of Potential Interactions - Information Sources. The sources of data regarding drug interactions are numerous, beginning with various drug reference books. However, they are far from uniformity in the way of choosing and presenting putative clinically relevant interactions. Clinical Significance of Potential Interactions - Interpretation of Information. The difficulties in interpretation of drug interactions are illustrated through the analysis of a published example involving assessment made by two different groups of health professionals. Systematic Evaluation of Drug-Drug Interaction. The potential for interactions is mainly investigated before marketing a drug. Generally, the in vitro, followed by in vivo studies are to be performed. The major metabolic pathways involved in the metabolism of a new molecular entity, as well as the potential of induction of human enzymes involved in drug metabolism are to be examined. In the field of interaction research it is possible to make use of the population pharmacokinetic studies as well as of the pharmacodynamic assessment, and also the postregistration monitoring of the reported adverse reactions and other literature data. Conclusion. In vitro and in vivo drug metabolism and transport studies should be conducted to elucidate the mechanisms and potential for drug-drug interactions. The assessment of their clinical significance should be based on well-defined and validated exposure-response data.

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