Review
Nature Reviews Drug Discovery 4, 825-833 (October 2005) | doi:10.1038/nrd1851
Predicting in vivo drug interactions from in vitro drug discovery data
Larry C. Wienkers1 & Timothy G. Heath2 About the authors
Abstract
In vitro screening for drugs that inhibit cytochrome P450 enzymes is well established as a means for predicting potential metabolism-mediated drug interactions in vivo. Given that these predictions are based on enzyme kinetic parameters observed from in vitro experiments, the miscalculation of the inhibitory potency of a compound can lead to an inaccurate prediction of an in vivo drug interaction, potentially precluding a safe drug from advancing in development or allowing a potent inhibitor to 'slip' into the patient population. Here, we describe the principles underlying the generation of in vitro drug metabolism data and highlight commonly encountered uncertainties and sources of bias and error that can affect extrapolation of drug–drug interaction information to the clinical setting.
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Author affiliations
- Amgen, 1201 Amgen Court West, Seattle, Washington 98119, USA.
- Pfizer, 700 Chesterfield Parkway West, Chesterfield, Missouri 63017, USA.
Correspondence to: Larry C. Wienkers1 Email: wienkers@amgen.com
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