Population pharmacokinetic analysis of sorafenib in patients with solid tumours

Authors


Dr William D. Figg Pharm D, Medical Oncology Branch, CCR, NCI/NIH, 9000 Rockville Pike, Building 10, Room 5A01, Bethesda, Maryland 20892, USA.
Tel.: +1 301 402 3622
Fax: +1 301 402 8606
E-mail: wdfigg@helix.nih.gov

Abstract

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

• Sorafenib is a multikinase inhibitor with activity against B-raf, C-raf, VEGFR2, PDGFRβ and FGFR1.

• Sorafenib is clinically approved for the treatment of renal cell carcinoma (RCC) and hepatocellular carcinoma (HCC).

• The pharmacokinetics (PK) of sorafenib are highly variable between subjects.

• Sorafenib exposure increases less than dose proportionally (likely due to limited solubility).

• Sorafenib undergoes enterohepatic recycling (EHC).

WHAT THIS STUDY ADDS

• This is the first study to characterize the PK of sorafenib using a model based on sorafenib's known disposition characteristics such as delayed/solubility-limited GI absorption and EHC. The parameterization of the EHC model used a square wave function to describe the gall bladder emptying.

• This study evaluated the effect of baseline bodyweight, BSA, age, gender, liver function parameters, kidney function parameters and genotype with respect to CYP3A4*1B, CYP3A5*3C, UGT1A9*3 and UGT1A9*5 on sorafenib PK. No clinically important covariates were identified.

• This model can be used to simulate and explore alternative dosing regimens and to develop exposure–response relationships for sorafenib.

AIMS To characterize the pharmacokinetics (PK) of sorafenib in patients with solid tumours and to evaluate the possible effects of demographic, clinical and pharmacogenetic (CYP3A4*1B, CYP3A5*3C, UGT1A9*3 and UGT1A9*5) covariates on the disposition of sorafenib.

METHODS PK were assessed in 111 patients enrolled in five phase I and II clinical trials, where sorafenib 200 or 400 mg was administered twice daily as a single agent or in combination therapy. All patients were genotyped for polymorphisms in metabolic enzymes for sorafenib. Population PK analysis was performed by using nonlinear mixed effects modelling (NONMEM). The final model was validated using visual predictive checks and nonparametric bootstrap analysis.

RESULTS A one compartment model with four transit absorption compartments and enterohepatic circulation (EHC) adequately described sorafenib disposition. Baseline bodyweight was a statistically significant covariate for distributional volume, accounting for 4% of inter-individual variability (IIV). PK model parameter estimates (range) for an 80 kg patient were clearance 8.13 l h−1 (3.6–22.3 l h−1), volume 213 l (50–1000 l), mean absorption transit time 1.98 h (0.5–13 h), fraction undergoing EHC 50% and average time to gall bladder emptying 6.13 h.

CONCLUSIONS Overall, population PK analysis was consistent with known biopharmaceutical/PK characteristics of oral sorafenib. No clinically important PK covariates were identified.

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