TY - JOUR T1 - Calibrating the in vitro-in vivo correlation for OATP mediated drug-drug interactions with rosuvastatin using static and PBPK models JF - Drug Metabolism and Disposition JO - Drug Metab Dispos DO - 10.1124/dmd.120.000149 SP - DMD-AR-2020-000149 AU - Rucha Sane AU - Kit Wun Kathy Cheung AU - Péter Kovács AU - Taleah Farasyn AU - Ruina Li AU - Annamaria Bui AU - Luna Musib AU - Emese Kis AU - Emile Plise AU - Zsuzsanna Gáborik Y1 - 2020/01/01 UR - http://dmd.aspetjournals.org/content/early/2020/10/09/dmd.120.000149.abstract N2 - Organic anion transporting polypeptide (OATP) 1B1/3 mediated drug-drug interaction (DDI) potential is evaluated in vivo with rosuvastatin (RST) as a probe substrate in clinical studies. We calibrated our assay with RST and estradiol 17-β-D-glucuronide (E217βG)/ cholecystokinin-8 (CCK8) as in vitro probes for qualitative and quantitative prediction of OATP1B-mediated DDI potential for RST. In vitro OATP1B1/1B3 inhibition using E217βG and CCK8 yielded higher AUC ratio (AUCR) values numerically with the static model, but all probes performed similarly from a qualitative cutoff-based prediction, as described in regulatory guidances. However, the magnitudes of DDI were not captured satisfactorily. Considering that clearance of RST is also mediated by gut breast cancer resistance protein (BCRP), inhibition of BCRP was also incorporated in the DDI prediction if the gut inhibitor concentrations were 10 x IC50 for BCRP inhibition. This combined static model closely predicted the magnitude of RST DDI with root mean square error values of 0.767-0.812 and 1.24-1.31, with and without BCRP inhibition, respectively for in vitro-in vivo- correlation of DDI. Physiologically-based pharmacokinetic (PBPK) modeling was also used to simulate DDI between RST and rifampicin, asunaprevir, and velpatasvir. Predicted AUCR for rifampicin and asunaprevir was within 1.5-fold of that observed, whereas that for velpatasvir showed a 2-fold under-prediction. Overall, the combined static model incorporating both OATP1B and BCRP inhibition provides a quick and simple mathematical approach to quantitatively predict the magnitude of transporter-mediated DDI for RST for routine application. PBPK complemented the static model and provides a framework when a dynamic model is needed. Significance Statement Using 22 drugs, we show that a static model for OATP1B1/1B3 inhibition can qualitatively predict potential for DDI using a cut-off based approach as in regulatory guidances. However, consideration of both OATP1B1/3 and gut BCRP inhibition provided a better prediction of the magnitude of the transporter-mediated DDI of these inhibitors with rosuvastatin. Based on these results, we have proposed an empirical mechanistic-static approach for a more reliable prediction of transporter-mediated DDI liability with rosuvastatin that drug development teams can leverage. ER -