Development and Application of Inavolisib Physiologically-based Pharmacokinetic (PBPK) Model for Drug-drug Interaction (DDI) Assessment
Authors: Huang Weize , Cheeti Sravanthi , Mao Chen , Salphati Laurent , Sane Rucha , Lu Tong , Chanu Pascal , Chen Yuan , Mao Jialin 
Published: February 2025

Objectives:Inavolisib is a potent selective inhibitor of the Class I PI3K alpha isoform, and it is currently being evaluated for the treatment of patients with PIK3CA-mutated, HR+, HER2−, locally advanced or metastatic breast cancer. The in vitro data suggest that inavolisib may exhibit modest CYP3A4 time-dependent inhibition (TDI) and induction. Therefore, our objective was to develop a PBPK model of inavolisib to assess its clinical DDI risk. Methods:The PBPK model for inavolisib was first developed and verified using in vitro results, clinical PK data, and human ADME data obtained following both IV and PO administration of inavolisib in a mass balance study. The key parameters driving the perpetrator DDI risk include the CYP3A4 TDI (Kinact and KI) and induction (Emax and EC50), which were determined from experiments. The inavolisib PBPK model was further validated using independent inavolisib PK data from Phase I monotherapy. The CYP3A4 interaction component of the inavolisib PBPK model was further validated using palbociclib PK data from the Phase I combination arm (inavolisib+palbociclib+letrozole combination); Of note, palbociclib is a CYP3A4 substrate (fm,CYP3A4 > 50%). The validated PBPK model was then applied to predict the effects of inavolisib on midazolam to evaluate the magnitude of perpetrator DDI risk from inavolisib. Sensitivity analyses of different perpetrator scenarios and different hepatocyte donors were also performed. Results:The model simulations successfully recapitulated the observed inavolisib PK data, with the majority of observed data within the 90% prediction interval and the overall shape of the PK profile well captured, suggesting successful model verification. All prediction/observation (P/O) ratios of inavolisib exposure metrics (AUC, Cmax, Tmax) are within 2-fold. The PK profile of palbociclib when co-administered with inavolisib was also well-captured, indicating that the CYP3A4 interaction component of the inavolisib PBPK model was validated. For DDI prediction, the midazolam AUC and Cmax ratios (with vs. without inavolisib) were predicted using sensitivity analysis containing three scenarios: CYP3A4 TDI only, CYP3A4 induction only, and combined effect of CYP3A4 TDI and induction. When considering the combined effect of both CYP3A4 inhibition and induction, the predicted geometric mean ratio (range) of the midazolam AUC and Cmax were 0.92 (0.74 - 1.05) and 0.93 (0.80 - 1.03), respectively. The range of the prediction was generated using different hepatocyte donors.Conclusions:We have successfully developed and verified a PBPK model for inavolisib that is able to describe all inavolisib PK data and inavolisib-palbociclib interaction accurately. Using this model, inavolisib at the therapeutic dose was predicted to only have a modest effect on the PK of sensitive CYP3A4 substrates in all scenarios simulated, suggesting a low likelihood of CYP3A4-mediated DDI.Citations: N/A