USE OF IN-VITRO AND IN-VIVO DATA TO ESTIMATE THE LIKELIHOOD OF METABOLIC PHARMACOKINETIC INTERACTIONS

This article reviews the information available to assist pharmacokinet icists in the prediction of metabolic drug interactions. Significant a dvances in this area have been made in the last decade, permitting the identification in early drug development of dominant cytochrome P450 (CYP) isoform(s) metabolising a particular drug as well as the ability of a drug to inhibit a specific CYP isoform. The major isoforms invol ved in human drug metabolism are CYP3A, CYP2D6, CYP2C, CYPIA2 and CYP2 E1. Often patients are taking multiple concurrent medications, and thu s an assessment of potential drug-drug interactions is imperative. A d atabase containing information about the clearance routes for over 300 drugs from multiple therapeutic classes, including analgesics, anti-i nfectives, psychotropics, anticonvulsants, cancer chemotherapeutics, g astrointestinal agents, cardiovascular agents and others, was construc ted to assist in the semiquantitative prediction of the magnitude of p otential interactions with drugs under development. With knowledge of the in vitro inhibition constant of a drug (K-i) for a particular CYP isoform, it is theoretically possible to assess the likelihood of inte ractions for a drug cleared through CYP-mediated metabolism For many a gents, the CYP isoform involved in metabolism has not been identified and there is substantial uncertainty given the current knowledge base. The mathematical concepts for prediction based on competitive enzyme inhibition are reviewed in this article. These relationships become mo re complex if the inhibition is of a mixed competitive/noncompetitive nature. Sources of uncertainty and inaccuracy in predicting the magnit ude of in vivo inhibition includes the nature and design of in vitro e xperiments to determine K-i, inhibitor concentration in the hepatic cy tosol compared with that in plasma, prehepatic metabolism, presence of active metabolites and enzyme induction. The accurate prospective pre diction of drug interactions requires rigorous attention to the detail s of the in vitro results, and detailed information about the pharmaco kinetics and metabolism of the inhibitor and inhibited drug. With the discussion of principles and accompanying tabulation of literature dat a concerning the clearance of various drugs, a framework for reasonabl e semiquantitative predictions is offered in this article.