Predicting human hepatic clearance from in vitro drug metabolism and transport data: A scientific and pharmaceutical perspective for assessing drug-drug interactions
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Camenisch, Gian P. and Umehara, Ken-Ichi (2012) Predicting human hepatic clearance from in vitro drug metabolism and transport data: A scientific and pharmaceutical perspective for assessing drug-drug interactions. Biopharmaceutics and Drug Disposition. ISSN 0142-2782
Abstract
Objectives. Membrane transporters and metabolism are major determinants of the hepatobiliary elimination of drugs. This work investigates several key questions for drug development. Such questions include which drugs demonstrate transporter-based clearance in clinics, and which in vitro methods are most suitable for drug classification, i.e. transporter- vs. metabolism-dependent compound class categories. Additional questions posed are: what is the expected quantitative change in exposure in the presence of a transporter- and/or metabolism-inhibiting drug, and which criteria should trigger follow-up clinical drug-drug interaction studies. Methods. A well-established method for (human) liver clearance prediction that considers all four physiological processes driving hepatic drug elimination (namely sinusoidal uptake and efflux, metabolism and biliary secretion) was applied. Suspended hepatocytes, liver microsomes and sandwich-cultured hepatocytes were used as in vitro models to determine the individual intrinsic clearance for 13 selected compounds with various physicochemical and pharmacokinetic properties. Results. Using this in vitro-in vivo extrapolation method a good linear correlation was observed between predicted and reported human hepatic clearances. Linear regression analysis revealed much improved correlations compared to other prediction methods. Conclusions. The presented approach serves as a basis for accurate compound categorization within the Biopharmaceutics Drug Disposition Classification System (BDDCS) and was applied to anticipate metabolism- and transporter-based drug-drug interactions using different static prediction methods. A decision tree proposal is provided and helps to guide clinical studies on active processes influencing hepatic elimination. All recommendations in this manuscript are generally intended to support early pre-clinical and clinical drug development and the filing of a new drug application.
| Item Type: | Article |
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| Additional Information: | no |
| Keywords: | clearance prediction; drug-drug interactions; metabolism; transporter; compound classification |
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| Date Deposited: | 13 Oct 2015 13:14 |
| Last Modified: | 13 Oct 2015 13:14 |
| URI: | https://oak.novartis.com/id/eprint/6547 |