Reaction phenotyping in drug discovery: moving forward with confidence?

Curr Drug Metab 2003 Dec;4(6):527-34

Department of Pharmacokinetics, Pfizer Global Research and Development, 2800 Plymouth Road, Ann Arbor, Michigan 48105, USA.

For the pharmaceutical industry, one of the challenges in evaluating the risk of future compound attrition at the discovery stage is the successful prediction of the major routes of clearance in humans. For compounds cleared by metabolism, such information will help to avoid the development of compounds that will exhibit large interpatient differences in pharmacokinetics via 1). routes of metabolism catalyzed by functionally polymorphic enzymes and/or 2). clinically significant metabolic drug-drug interactions, in the later stages of development. The degree of intersubject variability that is acceptable for a drug candidate is uncertain in the discovery stage where knowledge of other important factors is limited or unavailable (i.e. therapeutic index, pharmacodynamic variability, etc). Reaction phenotyping is the semi-quantitative in vitro estimation of the relative contributions of specific drug-metabolizing enzymes to the metabolism of a test compound. However, reaction phenotyping in the discovery stage of drug development is complicated by the absence of radiolabelled parent compound or metabolite bioanalytical standards relative to later stages of development. In this commentary, some of the approaches, based on published data, which can be taken to overcome these challenges are discussed. In addition, knowledge of the molecular structure (i.e. specific chemical substituents), physicochemical properties, and routes of clearance in animals can all help in making a successful prediction for the routes of clearance in humans. In combination, the objective of these studies should be to reduce to a minimum the risk of finding significant inter-patient differences in pharmacokinetics at a later stage in development due to significant metabolism by polymorphic enzymes or drug-drug interactions. Consequently, this data should be used to avoid costly late stage attrition.

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http://dx.doi.org/10.2174/1389200033489235DOI Listing
December 2003
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