Human Pharmacokinetic and CYP3A Drug–Drug Interaction Prediction of GDC-2394 Using Physiologically Based Pharmacokinetic Modeling and Biomarker Assessment

Physiologically based pharmacokinetic (PBPK) modeling was used to predict the human pharmacokinetics and drug-drug interaction (DDI) of GDC-2394. PBPK models were developed using in vitro and in vivo data to reflect the oral and intravenous PK profiles of mouse, rat, dog, and monkey. The learnings from preclinical PBPK models were applied to a human PBPK model for prospective human PK predictions. The prospective human PK predictions were within 3-fold of the clinical data from the first-in-human study, which was used to optimize and validate the PBPK model and subsequently used for DDI prediction. Based on the majority of PBPK modeling scenarios using the in vitro CYP3A induction data (mRNA and activity), GDC-2394 was predicted to have no-to-weak induction potential at 900 mg twice daily (BID). Calibration of the induction mRNA and activity data allowed for the convergence of DDI predictions to a narrower range. The plasma concentrations of the 4