RT Journal Article
SR Electronic
T1 Mechanistic Pharmacokinetic Modelling for the Prediction of Transporter-mediated Disposition in Human from Sandwich Culture Human Hepatocyte Data
JF Drug Metabolism and Disposition
JO Drug Metab Dispos
FD American Society for Pharmacology and Experimental Therapeutics
SP dmd.111.042994
DO 10.1124/dmd.111.042994
A1 Hannah M Jones
A1 Hugh A Barton
A1 Yurong Lai
A1 Yi-an Bi
A1 Emi Kimoto
A1 Sarah Kempshall
A1 Sonya C Tate
A1 Ayman El-Kattan
A1 Brian Houston
A1 Aleksandra Galetin
A1 Katherine S Fenner
YR 2012
UL http://dmd.aspetjournals.org/content/early/2012/02/16/dmd.111.042994.abstract
AB With efforts to reduce CYP450-mediated clearance (CL) during the early stages of drug discovery, transporter-mediated CL mechanisms are becoming more prevalent. However, the prediction of plasma concentration-time profiles for such compounds using physiologically based pharmacokinetic (PBPK) modeling is far less established in comparison to compounds with passively mediated PK. In this study, we have assessed the predictability of human PK for seven organic anion transporting polypeptides (OATP) substrates (pravastatin, cerivastatin, bosentan, fluvastatin, rosuvastatin, valsartan and repaglinide) where clinical intravenous (i.v.) data were available. In vitro data generated from the sandwich culture human hepatocyte (SCHH) system were simultaneously fit to estimate parameters describing both uptake and biliary efflux. Use of scaled active uptake, passive distribution and biliary efflux parameters as inputs into a PBPK model resulted in the over-prediction of exposure for all seven drugs investigated, with the exception of pravastatin. Therefore, fitting of in vivo data for each individual drug in the dataset was performed to establish empirical scaling factors to accurately capture their plasma concentration-time profiles. Overall, active uptake and biliary efflux were under- and over-predicted, leading to average empirical scaling factors of 58 and 0.061, respectively; passive diffusion required no scaling factor. This study illustrates the mechanistic and model-driven application of in vitro uptake and efflux data for human PK prediction for OATP substrates. A particular advantage is the ability to capture the multiphasic plasma concentration-time profiles for such compounds using only pre-clinical data. A prediction strategy for novel OATP substrates is discussed.