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Expert Opin Drug Metab Toxicol. 2007 Oct;3(5):667-87.

Cytochrome P450 reaction-phenotyping: an industrial perspective.

Author information

1
Bristol-Myers Squibb Research and Development, Pharmaceutical Candidate Optimization, PO Box 4000, Princeton, NJ 08543, USA. Hongjian.Zhang@bms.com

Abstract

It is now widely accepted that the fraction of the dose metabolized by a given drug-metabolizing enzyme is one of the major factors governing the magnitude of a drug interaction and the impact of a polymorphism on (total) drug clearance. Therefore, most pharmaceutical companies determine the enzymes involved in the metabolism of a new chemical entity (NCE) in vitro, in conjunction with human data on absorption, distribution, metabolism and excretion. This so called reaction-phenotyping, or isozyme-mapping, usually involves the use of multiple reagents (e.g., recombinant proteins, liver subcellular fractions, enzyme-selective chemical inhibitors and antibodies). For the human CYPs, reagents are readily available and in vitro reaction-phenotyping data are now routinely included in most regulatory documents. Ideally, the various metabolites have been definitively identified, incubation conditions have afforded robust kinetic analyses, and well characterized (high quality) reagents and human tissues have been employed. It is also important that the various in vitro data are consistent (e.g., scaled turnover with recombinant CYP proteins, CYP inhibition and correlation data with human liver microsomes) and enable an integrated in vitro CYP reaction-phenotype. Results of the in vitro CYP reaction-phenotyping are integrated with clinical data (e.g., human radiolabel and drug interaction studies) and a complete package is then submitted for regulatory review. If the NCE receives market approval, information on key routes of clearance and their associated potential for drug-drug interactions are included in the product label. The present review focuses on in vitro CYP reaction-phenotyping and the integration of data. Relatively simple strategies enabling the design and prioritization of follow up clinical studies are also discussed.

PMID:
17916054
DOI:
10.1517/17425255.3.5.667
[Indexed for MEDLINE]

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