RT Journal Article SR Electronic T1 Application of a Physiologically-Based Pharmacokinetic Model to Assess Propofol Hepatic and Renal Glucuronidation in Isolation; Utility of In Vitro and In Vivo Data JF Drug Metabolism and Disposition JO Drug Metab Dispos FD American Society for Pharmacology and Experimental Therapeutics SP dmd.112.050294 DO 10.1124/dmd.112.050294 A1 Katherine L Gill A1 Michael Gertz A1 J. Brian Houston A1 Aleksandra Galetin YR 2013 UL http://dmd.aspetjournals.org/content/early/2013/01/09/dmd.112.050294.abstract AB A physiologically-based pharmacokinetic (PBPK) modeling approach was used to assess the prediction accuracy of propofol hepatic and extrahepatic metabolic clearance and address previously reported under-prediction of in vivo clearance based on static in vitro-in vivo extrapolation methods. The predictive capacity of propofol intrinsic clearance data (CLint) obtained in human hepatocytes, liver and kidney microsomes was assessed using the PBPK model developed in Matlab. Microsomal data obtained by both substrate depletion and metabolite formation methods and in the presence of 2% BSA were considered in the analysis. Incorporation of hepatic and renal in vitro glucuronidation clearance in the PBPK model resulted in under-prediction of propofol clearance regardless of the source of in vitro data, as the predicted value did not exceed 35% of the observed clearance. Subsequently, propofol clinical data from three dose levels in intact patients and anhepatic subjects were used for the optimization of hepatic and renal CLint in a simultaneous fitting routine. Optimization process highlighted that renal glucuronidation clearance was under-predicted to a greater extent than liver clearance, requiring empirical scaling factors of 17 and 9, respectively. The use of optimized clearance parameters predicted hepatic and renal extraction ratios within 20% of the observed values, reported in an additional independent clinical study. This study highlights the complexity involved in assessing the contribution of extrahepatic clearance mechanisms and illustrates the application of PBPK modelling, in conjunction with clinical data, to assess prediction of clearance from in vitro data for each tissue individually.