Understanding CYP3A4 and P‐gp mediated drug–drug interactions through PBPK modeling – Case example of pralsetinib

Abstract

Abstract Pralsetinib, a potent and selective inhibitor of oncogenic RET fusion and RET mutant proteins, is a substrate of the drug metabolizing enzyme CYP3A4 and a substrate of the efflux transporter P‐gp based on in vitro data. Therefore, its pharmacokinetics (PKs) may be affected by co‐administration of potent CYP3A4 inhibitors and inducers, P‐gp inhibitors, and combined CYP3A4 and P‐gp inhibitors. With the frequent overlap between CYP3A4 and P‐gp substrates/inhibitors, pralsetinib is a challenging and representative example of the need to more quantitatively characterize transporter‐enzyme interplay. A physiologically‐based PK (PBPK) model for pralsetinib was developed to understand the victim drug–drug interaction (DDI) risk for pralsetinib. The key parameters driving the magnitude of pralsetinib DDIs, the P‐gp intrinsic clearance and the fraction metabolized by CYP3A4, were determined from PBPK simulations that best captured observed DDIs from three clinical studies. Sensitivity analyses and scenario simulations were also conducted to ensure these key parameters were determined with sound mechanistic rationale based on current knowledge, including the worst‐case scenarios. The verified pralsetinib PBPK model was then applied to predict the effect of other inhibitors and inducers on the PKs of pralsetinib. This work highlights the challenges in understanding DDIs when enzyme‐transporter interplay occurs, and demonstrates an important strategy for differentiating enzyme/transporter contributions to enable PBPK predictions for untested scenarios and to inform labeling.