Population pharmacokinetic‐pharmacodynamic modeling of serum biomarkers as predictors of tumor dynamics following lenvatinib treatment in patients with radioiodine‐refractory differentiated thyroid cancer (RR‐DTC)

Abstract

AbstractLenvatinib is a receptor tyrosine kinase (RTK) inhibitor targeting vascular endothelial growth factor (VEGF) receptors 1–3, fibroblast growth factor (FGF) receptors 1–4, platelet‐derived growth factor receptor‐α (PDGFRα), KIT, and RET that have been implicated in pathogenic angiogenesis, tumor growth, and cancer. The primary objective of this work was to evaluate, by establishing quantitative relationships, whether lenvatinib exposure and longitudinal serum biomarker data (VEGF, Ang‐2, Tie‐2, and FGF‐23) are predictors for change in longitudinal tumor size which was assessed based on data from 558 patients with radioiodine‐refractory differentiated thyroid cancer (RR‐DTC) receiving either lenvatinib or placebo treatment. Lenvatinib PK was best described by a 3‐compartment model with simultaneous first‐ and zero‐order absorption and linear elimination from the central compartment with significant covariates (body weight, albumin <30 g/dL, ALP>ULN, RR‐DTC, RCC, HCC subjects, and concomitant CYP3A inhibitors). Except for body weight, none of the covariates have any clinically meaningful effect on exposure to lenvatinib. Longitudinal biomarker measurements over time were reasonably well defined by a PK/PD model with common EC50, Emax, and a slope for disease progression for all biomarkers. Longitudinal tumor measurements over time were reasonably well defined by a tumor growth inhibition Emax model, which in addition to lenvatinib exposure, included model‐predicted relative changes from baseline over time for Tie‐2 and Ang‐2 as having significant association with tumor response. The developed PK/PD models pave the way for dose optimization and potential prediction of clinical response.