PhD Candidate University at Buffalo, SUNY, United States
Disclosure(s):
Se Jin Kim, PharmD: No financial relationships to disclose
Objectives: Translational PK/PD modeling can support early drug development by enhancing the identification of drug- and system-specific factors that govern drug responses[1]. This study assesses the translational performance of preclinical models to anticipate enzalutamide clinical efficacy in prostate cancer using a cross-species physiologically-based pharmacokinetic (PBPK)-pharmacodynamic (PD) model.
Methods: Published enzalutamide preclinical and clinical PK/PD data were collected, and a PBPK model in mice was developed and translated to rats and humans. The mouse PBPK model was linked to a tumor growth inhibition (TGI) model to describe tumor volume profiles in 5 cell line-derived and 3 patient-derived xenografts. Estimated preclinical PD model parameters were fixed to simulate clinical PFS using the human PBPK model and a calculated prostate cancer tumor growth rate[2]. Simulated PFS curves were compared to observed profiles. Tumor static concentrations (TSCs) were also calculated and assessed relative to a standard dosing regimen. Model fitting and simulations were performed in R using the Ubiquity package (v2.0.0.)[3] to obtain the maximum likelihood estimates of parameters.
Results: Estimated model parameters were precise with CV% less than 15% and 45% for most PK and PD parameters, and the estimated hepatic intrinsic clearance was comparable to conventional allometry with an allometric exponent of 0.722. The 8 TSC values were near or below the simulated steady-state plasma drug concentration (18,000 ng/mL) achieved with a standard enzalutamide regimen [TSC range 168–20,743 ng/mL]. In contrast, the traditional TGI model failed to predict clinical PFS unless a tumor heterogeneity model with sensitive and resistant tumor cell populations[4,5] and individually calibrated growth rates were explicitly incorporated.
Conclusions: A PBPK model for enzalutamide was successfully developed for mice, rats, and humans. The standard clinical enzalutamide regimen appears to cover a range of preclinical TSCs. A simple preclinical TGI model failed to predict clinical PFS, and one hypothesis is that tumor heterogeneity is required to better mimic human tumor biology and translate preclinical PD parameters.
Citations: [1] Mager DE, Jusko WJ. Development of translational pharmacokinetic-pharmacodynamic models. Clin Pharmacol Ther. 2008 Jun;83(6):909-12 [2] Kay K, Dolcy K, Bies R, Shah DK. Estimation of Solid Tumor Doubling Times from Progression-Free Survival Plots Using a Novel Statistical Approach. AAPS J. 2019 Feb 8;21(2):27 [3] Harrold JM, Abraham AK. Ubiquity: a framework for physiological/mechanism-based pharmacokinetic/pharmacodynamic model development and deployment. J Pharmacokinet Pharmacodyn. 2014 Apr;41(2):141-51. [4] Cerou M, Thai HT, Deyme L, Fliscounakis-Huynh S, Comets E, Cohen P, Cartot-Cotton S, Veyrat-Follet C. Joint modeling of tumor dynamics and progression-free survival in advanced breast cancer: Leveraging data from amcenestrant early phase I-II trials. CPT Pharmacometrics Syst Pharmacol. 2024 Jun;13(6):941-953. [5] Otani Y, Zhao Y, Wang G, Labotka R, Rogge M, Gupta N, Vakilynejad M, Bottino D, Tanigawara Y. Modeling serum M-protein response for early detection of biochemical relapse in myeloma patients treated with bortezomib, lenalidomide and dexamethasone. CPT Pharmacometrics Syst Pharmacol. 2024 Dec;13(12):2124-2136.
