Journal
BIOPHARMACEUTICS & DRUG DISPOSITION
Volume 33, Issue 4, Pages 179-194Publisher
WILEY
DOI: 10.1002/bdd.1784
Keywords
clearance prediction; drug-drug interactions; metabolism; transporter; compound classification
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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 the clinic, 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 drugdrug 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 vitroin vivo extrapolation method a good linear correlation was observed between predicted and reported human hepatic clearances. Linear regression analysis revealed much improved correlations compared with 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 drugdrug 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 paper are generally intended to support early pre-clinical and clinical drug development and the filing of a new drug application. Copyright (c) 2012 John Wiley & Sons, Ltd.
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