Population Pharmacokinetic Modeling of Encorafenib and LHY746 In Participants with Solid Tumors in Phase 2 Studies: A Sequential Parent-Metabolite Model

Objectives: Encorafenib is a kinase inhibitor indicated for the treatment of patients with BRAF mutant melanoma and BRAF mutant metastatic colorectal cancer. Metabolism was found to be the major clearance pathway for encorafenib in humans and is predominantly mediated through N-dealkylation of the isopropyl carbamic acid methyl ester, mediated through CYP3A, to form the primary phase 1 direct metabolite LHY746.[ 1] Encorafenib exhibits net-autoinduction of CYP3A4 at steady-state, resulting in the steady-state exposure for LHY746 being approximately 6.6-fold higher compared with exposure following a single dose.[ 2] The objective of this analysis was to develop a population pharmacokinetic (popPK) model to characterize the pharmacokinetics of LHY746. Methods: This popPK analysis was based on 2 Phase 2 studies in participants with solid tumors. PopPK modeling was performed using non-linear mixed effects modeling approach (NONMEM v 7.5.0) with first order-conditional estimation with interaction. A sequential approach was used to develop a parent-metabolite model based on a popPK model for encorafenib by Yang et al.[ 3] In this analysis, individual post hoc estimates from the encorafenib popPK model were used to inform the PK of the parent compounds of this model. Stepwise covariate modeling assessed the influence of a range of covariates (e.g., age, bodyweight, albumin) on key pharmacokinetic parameters. The stochastic approximation expectation maximization estimation method was used (NONMEM v 7.5.0, Icon, Dublin Ireland) for metabolite LHY746 popPK model development. Model validation included bootstrap resampling (n = 1000) and visual predictive checks. Results: A one compartment model with a fixed fraction metabolized described the pooled LHY746 PK data (1473 concentrations from 93 subjects) from the POLARIS study (NCT05531526) and the PHAROS study (NCT03915951) well. The model parameters were estimated with good precision with a relative standard error (RSE) < 10% for the metabolite clearance (CLM) and metabolite volume (VCM). The condition number for the model was 5.254 and shrinkage for both CLM and VCM was < 30%. Final model estimates for CLM and VCM were 11.6 L/h and 188 L, respectively. Age was found to be a significant covariate on (CLM) in which older participants had a lower CLM than younger participants. Conclusions: This parent-metabolite popPK model adequately described the increase in LHY746 exposure due to net-autoinduction of encorafenib.