Investigating the Utility of Humanized Pregnane X Receptor-Constitutive Androstane Receptor-CYP3A4/7 Mouse Model to Assess CYP3A-Mediated Induction.

Clinical induction liability is assessed with human hepatocytes. However, underpredictions in the magnitude of clinical induction have been reported. Unfortunately, in vivo studies in animals do not provide additional insight because of species differences in drug metabolizing enzymes and their regulatory pathways. To circumvent this limitation, transgenic animals expressing human orthologs were developed. The aim of this work was to investigate the utility of mouse models expressing human orthologs of pregnane X receptor, constitutive androstane receptor, and CYP3A4/7 (Tg-Composite) in evaluating clinical induction. Rifampin, efavirenz, and pioglitazone, which were employed to represent strong, moderate, and weak inducers, were administered at multiple doses to Tg-Composite animals. In vivo CYP3A activity was monitored by measuring changes in the exposure of the CYP3A probe substrate triazolam. After the in vivo studies, microsomes were prepared from their livers to measure changes of in vitro CYP3A4 activity. In both in vivo and in vitro, distinction of clinic induction was recapitulated as rifampin yielded the greatest inductive effect followed by efavirenz and pioglitazone. Interestingly, with rifampin, in vivo CYP3A activity was approximately 4-fold higher than in vitro activity. Conversely, there was no difference between in vivo and in vitro CYP3A activity with efavirenz. These findings are consistent with the report that, although rifampin exhibits differential inductive effects between the intestines and liver, efavirenz does not. These data highlight the promise of transgenic models, such as Tg-Composite, to complement human hepatocytes to enhance the translatability of clinical induction as well as become a powerful tool to further study mechanisms of drug disposition. SIGNIFICANCE STATEMENT: Underprediction of the magnitude of clinical induction when using human hepatocytes has been reported, and transgenic models may improve clinical translatability. The work presented here showcases the human orthologs of pregnane X receptor, constitutive androstane receptor, and CYP3A4/7 model, which was able to recapitulate the magnitude of clinical induction and to differentiate tissue-dependent induction observed with rifampin but not with efavirenz. These results not only foreshadow the potential application of such transgenic models in assessing clinical induction but also in further investigation of the mechanism of drug disposition.

Calibrating the In Vitro-In Vivo Correlation for OATP-Mediated Drug-Drug Interactions with Rosuvastatin Using Static and PBPK Models.

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-ß-D-glucuronide (E217ßG)/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 E217ßG and CCK8 yielded higher area under the curve (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 × 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 underprediction. 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 complements the static model and provides a framework for studying molecules when a dynamic model is needed. SIGNIFICANCE STATEMENT: Using 22 drugs, we show that a static model for organic anion-transporting polypeptide (OATP) 1B1/1B3 inhibition can qualitatively predict potential for drug-drug interaction (DDI) using a cutoff-based approach, as in regulatory guidances. However, consideration of both OATP1B1/3 and gut breast cancer resistance protein 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.