Optimizing the in vitro and clinical assessment of drug interaction risk by understanding co-medications in patient populations. (June 2013)

• Record Type: Journal Article
• Authors: Bloomer, Jackie; Derimanov, Geo; Dumont, Etienne; Ellens, Harma; Matheny, Christopher
• Is Part Of: Expert opinion on drug metabolism and toxicology. Volume 9:Number 6(2013:Jun.)
• Page Start: 737
• Page End: 751
• Publication Date: 2013-06
• Subjects: Drugs -- Toxicology -- Periodicals; Drugs -- Metabolism -- Periodicals; 615.7
• DOI: 10.1517/17425255.2013.781582
• Languages: English
• ISSNs: 1742-5255

Abstract

<abstract> <title> <x xml:space="preserve">Abstract</x> </title> <p> <bold> <italic>Introduction:</italic> </bold> Pharmacokinetic drug interactions resulting from the inhibition of drug elimination mechanisms are of concern in drug development due to the clinical risk associated with elevated drug concentrations. Advances in understanding the mechanistic basis of these drug interactions has resulted in the widespread application of mechanistic <italic>in vitro</italic> assays and the conduct of clinical drug interaction studies to predict and quantify the risks in drug development.</p> <p> <bold> <italic>Areas covered:</italic> </bold> The authors investigate co-medication prescriptions in target patient populations and characterize the mechanistic basis and clinical impact of known co-medication drug interactions. This has enabled identification of critical mechanistic <italic>in vitro</italic> studies and provided options to manage co-medication use in clinical studies. Furthermore, they demonstrate, for the pharmaceutical scientist, how improved understanding of the drug interactions risks associated with key medications in a target therapeutic area, can help prioritize the conduct of <italic>in vitro</italic> data and optimize the timing of the clinical drug interaction studies required to characterize drug interaction risks.</p> <p> <bold> <italic>Expert opinion:</italic> </bold> This approach provides a more targeted strategy to drug interaction data generation, as routine application of assays may provide limited impact on drug progression decisions. Assessing co-medications in the target patient population enables early discharge of the safety risks associated with drug interactions and reduced investment in drug interaction studies.</p> </abstract>