S 55746 ((S)-N-(4-hydroxyphenyl)-3- (6-(3-(morpholinomethyl)-1,2,3,4tetrahydroisoquinoline-2-carbonyl)benzo [d][1,3]dioxol-5-yl)-N-phenyl-5,6,7,8-tetrahydroindolizine-1-carboxamide) is a new selective Bcl-2 (B-cell lymphoma 2) inhibitor developed by Servier Laboratories and used to restore apoptosis functions in cancer patients. The aim of this work was to develop a translational approach using physiologically based (PB) pharmacokinetic (PK) modeling for interspecies extrapolation to anticipate the nonlinear PK behavior of this new compound in patients. A PBPK mouse model was first built using a hybrid approach, defining scaling factors (determined from in vitro data) to correct in vitro clearance parameters and predicted Kp (partition coefficient) values. The qualification of the hybrid model using these empirically determined scaling factors was satisfactorily completed with rat and dog data, allowing extrapolation of the PBPK model to humans. Human PBPK simulations were then compared with clinical trial data from a phase 1 trial in which the drug was given orally and daily to cancer patients. Human PBPK predictions were within the 95% prediction interval for the eight dose levels, taking into account both the nonlinear dose and time dependencies occurring in S 55746 kinetics. Thus, the proposed PK interspecies extrapolation strategy, based on preclinical and in vitro information and physiologic assumptions, could be a useful tool for predicting human plasma concentrations at the early stage of drug development.
Abstract. The purpose of this study was to explore the interval censoring induced by caliper measurements on smaller tumors during tumor growth experiments in preclinical studies and to show its impact on parameter estimations. A new approach, the so-called interval-M3 method, is proposed to specifically handle this type of data. Thereby, the interval-M3 method was challenged with different methods (including classical methods for handling below quantification limit values) using Stochastic Simulation and Estimation process to take into account the censoring. In this way, 1000 datasets were simulated under the design of a typical of tumor growth study in xenografted mice, and then, each method was used for parameter estimation on the simulated datasets. Relative bias and relative root mean square error (relative RMSE) were consequently computed for comparison purpose. By not considering the censoring, parameter estimations appeared to be biased and particularly the cytotoxic effect parameter, k 2 , which is the parameter of interest to characterize the efficacy of a compound in oncology. The best performance was noted with the interval-M3 method which properly takes into account the interval censoring induced by caliper measurement, giving overall unbiased estimations for all parameters and especially for the antitumor effect parameter (relative bias = 0.49%, and relative RMSE = 4.06%). KEY WORDS: below quantification limit; interval censoring; interval-M3 method; simultaneous modeling continuous and categorical data; xenograft model.
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