Understanding the underlying mechanisms of complex drug-drug interactions through modeling and simulation

Physiologically-based pharmacokinetic (PBPK) modeling is widely used to predict the extent of drug-drug interactions (DDI), but the approach is also valuable in investigating and identifying the underlying mechanistic determinants of drug-drug interactions.

The Simcyp® Simulator can handle drug-drug interactions involving up to four drugs plus three metabolites and accommodates simultaneous: competitive enzyme and transporter inhibition, irreversible time-based enzyme inhibition, enzyme induction, and suppression. The technology has been used to model the different and interlinking elements that contribute to an observed drug-drug interaction and account for time-dependent changes in drug concentrations and enzyme activity levels. Selected examples are presented below.

Imatinib (GleevecTM) is marketed by Novartis® for the treatment of chronic myelogenous leukemia. In response to clinical data reporting a smaller than expected role for CYP3A4 inhibition of imatinib, clinical pharmacologists at the University of Helsinki, Finland, ran in vitro studies and used simulations to investigate the underlying mechanisms behind the observations. Although initial product data suggested imatinib metabolism was mainly mediated by CYP3A4, the group identified that a second enzyme, CYP2C8, contributed to around 40% of hepatic clearance. Simulations using Simcyp showed that auto-inhibition of CYP3A4 by both imatinib and its primary metabolite reduces the proportion of CYP3A4 metabolism from 60% to around 25% on multiple dosing. As this switches the importance from CYP3A4 to CYP2C8-mediated metabolism, the researchers warn that pharmacogenetic polymorphisms in CYP2C8 and CYP2C8-related DDIs are likely to result in marked inter-individual variation in the exposure and response to imatinib.

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