Application of physiologically based pharmacokinetic (PBPK) modelling for prediction of complex drug-drug interactions (DDIs) involving OATP1B1-mediated uptake and cytochrome P450 (CYP) metabolism and multiple inhibitors

BACKGROUND: Repaglinide is actively taken up by OATP1B1 into liver and metabolized by CYP3A4 and CYP2C8. PBPK modeling was used to predict complex DDIs involving inhibition of both transporter- mediated uptake and metabolism of repaglinide. METHODS: Prior in vitro data on metabolism, protein binding and physicochemical characteristics of repaglinide were obtained from the literature and incorporated into a PBPK model within the Simcyp Simulator (Version 11). While there are in vivo data to support OATP1B1- mediated hepatic uptake of repaglinide, in vitro parameters describing this transport were not available to us. Hence, we combined a top-down fitting approach (in vivo concentration-time profile of repaglinide (Niemi et al., 2000)) with bottom-up extrapolation of all prior in vitro data within the Parameter Estimation module of the Simcyp Simulator to obtain an estimate of 282 µl/min/million cells for hepatic uptake clearance of repaglinide via OATP1B1. DDIs involving repaglinide and the inhibitors, cyclosporine (OATP1B1), clarithromycin (CYP3A4) and trimethoprim (CYP2C8) were predicted and compared with observed data. RESULTS: Inclusion of hepatic uptake via OATP1B1 improved the model fit to the in vivo data. However, more importantly, predicted increases in plasma AUC₍0-∞₎ of repaglinide during co-administration of trimethoprim (1.3 fold; 160 mg qd), clarithromycin (1.4 fold; 250 mg bid) or cyclosporine (2.0 fold; 100 mg bid) were consistent with observed values of 1.6-, 1.4- and 2.4-fold. Finally, co-administration of all 3 inhibitors with repaglinide in our virtual clinical trial was associated with a 5.6- fold increase in AUC₍0-∞₎. CONCLUSION: Combining PBPK modeling with a fitting approach and reliable in vitro data, allowed prediction of enzyme and transporter related DDIs and provided insight into the potential outcome of complex combinations involving multiple inhibitors. Niemi et al. (2000) Clin Pharmacol Ther; 68: 495-500.