GDC-0810 Pharmacokinetics and Transporter-Mediated Drug Interaction Evaluation with an Endogenous Biomarker in the First-in-Human, Dose Escalation Study

GDC-0810 (Cheeti et al., 2018) is an orally bioavailable, selective estrogen receptor (ER) degrader developed to treat ER-positive breast cancer. A first-in-human (FIH) dose escalation phase I study (n = 41) was conducted to characterize the pharmacokinetics (PK) of GDC-0810 and its two major metabolites. GDC-0810 demonstrated linear PK from 100 to 600 mg given once daily. The mean terminal half-life following a single 600 mg dose was approximately 8 hours. Since GDC-0810 is a potent in vitro inhibitor of organic anion transporting polypeptide (OATP) 1B1/3, the kinetic profile of coproporphyrin I (CPI), a promising endogenous biomarker for OATP1B1/3, was analyzed retrospectively in a subset of the plasma samples collected in the same FIH study. CPI exhibited a GDC-0810 dose-dependent increase, suggesting in vivo inhibition of OATP1B transporters. To quantitatively predict the magnitude of OATP1B-mediated drug-drug interactions (DDIs) with pravastatin (a known OATP1B substrate), the in vivo unbound inhibition constant was first estimated using a one-compartment model, and then incorporated to a physiologically based pharmacokinetic model. The model showed some underestimation of the magnitude of the DDI when compared with a clinical DDI study result, while prediction had a relatively large uncertainty due to the small effect size, limited sample size, and variability in CPI kinetics. In conclusion, this study characterized the pharmacokinetic profiles of GDC-0810 in breast cancer patients and demonstrated the utility of CPI in detecting OATP1B-mediated DDIs of a new molecular entity as early as FIH study. Endogenous biomarkers of transporters have recently been shown to be promising tools in evaluating the risk of clinical transporter-mediated DDIs. This is the first study to report a pharmacokinetic interaction between an investigational molecule and a transporter biomarker in a first-in-human study. The observed interaction and model-based analysis and the prediction provide important insights on the novel approach to quantitatively predict transporter-mediated DDIs as early as FIH studies in the clinical development.