RT Journal Article SR Electronic T1 Improving the Translation of Organic Anion Transporting Polypeptide Substrates using HEK293 Cell Data in the Presence and Absence of Human Plasma via PBPK Modeling JF Drug Metabolism and Disposition JO Drug Metab Dispos FD American Society for Pharmacology and Experimental Therapeutics SP DMD-AR-2020-000315 DO 10.1124/dmd.120.000315 A1 Christine M. Bowman A1 Buyun Chen A1 Jonathan Cheong A1 Liling Liu A1 Yuan Chen A1 Jialin Mao YR 2021 UL http://dmd.aspetjournals.org/content/early/2021/05/06/dmd.120.000315.abstract AB Accurately predicting the pharmacokinetics of compounds that are transporter substrates has been notoriously challenging using traditional in vitro systems and physiologically based pharmacokinetic (PBPK) modeling. The objective of this study was to use PBPK modeling to understand the translational accuracy of data generated with human embryonic kidney (HEK)293 cells overexpressing the hepatic uptake transporters OATP1B1/3 with and without plasma, while accounting for transporter expression. Models of four OATP substrates, two with low protein binding (pravastatin and rosuvastatin) and two with high protein binding (repaglinide and pitavastatin) were explored, and the OATP in vitro data generated in plasma incubations were utilized for a plasma model, and in buffer incubations for a buffer model. The pharmacokinetic parameters and concentration-time profiles of pravastatin and rosuvastatin were similar and well-predicted (within two-fold of observed values) using the plasma and buffer models without needing an empirical scaling factor. The dispositions of the highly protein bound repaglinide and pitavastatin were more accurately simulated with the plasma models than the buffer models, suggesting the relevance of protein-facilitated uptake. This work demonstrates that data from HEK293 overexpressing transporter cells in plasma incubations and corrected for transporter expression can successfully be used for bottom-up PBPK modeling of OATP substrates. Significance Statement This work demonstrates the bottom-up approach of using in vitro data directly without employing empirical scaling factors to predict the IV PK profiles reasonably well for multiple OATP substrates. Based on these results, using a physiologically relevant in vitro system such as HEK293 overexpressing cells in plasma and incorporating transporter quantitation for the lot in which the in vitro data were generated can help achieve more accurate prospective PK predictions.