Physiologically based pharmacokinetic modelling to predict drug–drug interactions for encorafenib. Part I. Model building, validation, and prospective predictions with enzyme inhibitors, inducers, and transporter inhibitors

Encorafenib, a potent BRAF kinase inhibitor undergoes significant metabolism by CYP3A4 (83%) and CYP2C19 (16%) and also a substrate of P-glycoprotein (P-gp). Because of this, encorafenib possesses potential for enzyme-transporter related interactions. Clinically, it's drug-drug interactions (DDI) with CYP3A4 inhibitors (posaconazole, diltiazem) were reported and hence there is a necessity to study DDI's with multiple enzyme inhibitors, inducers and P-gp inhibitors.USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors, CYP3A4 inducers were selected and prospective DDI's were simulated using Physiologically Based Pharmacokinetic Modeling (PBPK). Impact of dose (50mg vs 300mg), staggering of administrations (0-10 h) on the DDI's were predicted.PBPK models for encorafenib, perpetrators simulated PK parameters within 2-folds prediction error. Clinically reported DDI's with posaconazole and diltiazem were successfully predicted.CYP2C19 inhibitors did not result in significant DDI whereas strong CYP3A4 inhibitors resulted in DDI ratio up to 4.5. Combining CYP3A4, CYP2C19 inhibitors yielded DDI equivalent CYP3A4 alone. Strong CYP3A4 inducers yielded DDI ratio up to 0.5 and no impact of P-gp inhibitors on DDI's was observed. The DDI's were not impacted by dose and staggering of administration. Overall, this work indicated significance of PBPK modeling for evaluating clinical DDI's with enzymes, transporters and interplay.