Kinetic modeling of β-chloroprene metabolism: Probabilistic in vitro-in vivo extrapolation of metabolism in the lung, liver and kidneys of mice, rats and humans

被引:10
|
作者
Yang, Yuching [1 ]
Himmelstein, Matthew W. [2 ]
Clewell, Harvey J. [1 ]
机构
[1] Hamner Inst Hlth Sci, Ctr Human Hlth Assessment, Res Triangle Pk, NC USA
[2] EI du Pont Nemours & Co, Haskell Lab Hlth & Environm Sci, Newark, DE 19711 USA
关键词
In vitro; Kinetic modeling; Bayesian; PBPK; IVIVE; PHARMACOKINETIC MODELS; B6C3F(1) MICE; DOSE-RESPONSE; CARCINOGENICITY; (1-CHLOROETHENYL)OXIRANE; 2-CHLORO-1,3-BUTADIENE; 1,3-BUTADIENE; TOXICITY; HAMSTERS; MONOMER;
D O I
10.1016/j.tiv.2012.04.004
中图分类号
R99 [毒物学(毒理学)];
学科分类号
100405 ;
摘要
beta-Chloroprene (chloroprene) is carcinogenic in inhalation bioassays with B6C3F1 mice and Fischer rats, but the potential effects in humans have not been adequately characterized. In order to provide a better basis for evaluating chloroprene exposures and potential effects in humans, we have explored species and tissue differences in chloroprene metabolism. This study implemented an in vitro-in vivo extrapolation (IVIVE) approach to parameterize a physiologically based pharmacokinetic (PBPK) model for chloroprene and evaluate the influence of species and gender differences in metabolism on target tissue dosimetry. Chloroprene metabolism was determined in vitro using liver, lung and kidney microsomes from male or female mice, rats, and humans. A two compartment PK model was used to estimate metabolism parameters for chloroprene in an in vitro closed vial system, which were then extrapolated to the whole body PBPK model. Two different strategies were used to estimate parameters for the oxidative metabolism of chloroprene: a deterministic point-estimation using the Nelder-Mead nonlinear optimization algorithm and probabilistic Bayesian analysis using the Markov Chain Monte Carlo technique. Target tissue dosimetry (average amount of chloroprene metabolized in lung per day) was simulated with the PBPK model using the in vitro-based metabolism parameters. The model-predicted target tissue dosimetry, as a surrogate for a risk estimate, was similar between the two approaches; however, the latter approach provided a measure of uncertainty in the metabolism parameters and the opportunity to evaluate the impact of that uncertainty on predicted risk estimates. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1047 / 1055
页数:9
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