Bridging Sunitinib Exposure to Time-to-Tumor Progression in Hepatocellular Carcinoma Patients With Mathematical Modeling of an Angiogenic Biomarker

Abstract

Hepatocellular carcinoma (HCC) is third in cancer-related causes of death worldwide and its treatment is a significant unmet medical need. Sunitinib is a selective tyrosine kinase inhibitor of the angiogenic biomarker: soluble vascular endothelial growth factor receptor-2 (sVEGFR2 ). Sunitinib failed its primary overall survival endpoint in patients with advanced HCC in a phase III trial compared to sorafenib. In the present study, pharmacokinetic-pharmacodynamic modeling was used to link drug-exposure to tumor-growth-inhibition (TGI) and time-to-tumor progression (TTP) through sVEGFR2 dynamics. The results suggest that 1) active drug concentration (i.e., sunitinib and its metabolite) inhibits the release of sVEGFR2 and that such inhibition is associated with TGI, and 2) daily sVEGFR2 exposure is likely a reliable predictor for the TTP in HCC patients. Moreover, the model quantitatively links the dynamics of an angiogenesis biomarker to TTP and accurately predicts observed literature-reported results of placebo treatment.

Figure 1

Pharmacokinetic/pharmacodynamic model for sunitinib and SU12662. Drug (D) and metabolite (M) were described with two‐compartment models including linear elimination (CL_D, CL_M) and first‐order absorption from the gastrointestinal tract (ka_D, ka_M). The fraction of drug metabolized into SU12662 was fixed (f_M = 0.21). The active unbound concentration, AC_ub=f_ub,D.CD+f_ub,M.CM, with f_ub,D and f_ub,M as the free fractions of drug and metabolite, inhibits sVEGFR₂ production, which was captured with an indirect response model with a zero‐order production rate constant (k_in) and a first‐order removal rate constant (k_out). The difference of sVEGFR₂ from its baseline concentration (ΔsVEGFR₂) inhibits the growth rate constant (k_g) controlling HCC tumor progression. The symbols are defined in the Methods.

Figure 2

Visual predictive check (VPC) plots vs. time for (a) sunitinib plasma concentrations, (b) SU12662 plasma concentrations, (c) sVEGFR2 plasma concentrations, and (d) tumor volume kinetics. Solid circles represent the observed data. The gray area identifies the 5th and 95th percentiles of the predicted data, and dark solid lines represent the 50th percentile (median) of the predicted data. The gray solid line in (d) represents a model simulation of the trajectory of the tumor growth in placebo‐treated patients. The confidence interval includes the majority of the data and the median is centrally located, although the number of observations outside the predicted 90% confidence interval is slightly above the expected 10%. These VPCs show no specific deviation of predicted vs. observed data, which qualifies the model as being structurally sound and supports the veracity of the estimated parameter values and concentrations.

Figure 3

Model‐predicted TTP probabilities in patients with unresectable HCC. The solid black line represents the observed TTP probability. The solid red lines are the 5^th and 95^th percentiles of the predicted data, and the red dashed line is the 50^th percentile (median) of the predicted data in patients treated with sunitinib. Model simulated TTP probability in placebo‐treated patients is shown in green, where solid lines represent the 5^th and 95^th percentiles and the dashed line is the 50^th percentile (median).