UTC, Technological University of Compiegne, Chair of Mathematical Modelling for Systems Toxicology, Royallieu Research Centre, BP 20529, 60205 Compiegne Cedex, France.
Toxicology. 2010 Dec 30;278(3):256-67. doi: 10.1016/j.tox.2010.06.007. Epub 2010 Jun 30.
Generic PBPK models, applicable to a large number of substances, coupled to parameter databases and QSAR modules, are now available for predictive modelling of inter-individual variability in the absorption, distribution, metabolism and excretion of environmental chemicals. When needed, Markov chain Monte Carlo methods and multilevel population models can be jointly used for a Bayesian calibration of a PBPK model, to improve our understanding of the determinants of population heterogeneity and differential susceptibility. This article reviews those developments and illustrates them with recent applications to environmentally relevant questions.
通用的基于生理的药代动力学模型（PBPK）适用于大量物质，与参数数据库和定量构效关系（QSAR）模块相结合，可用于预测环境化学物质在吸收、分布、代谢和排泄方面的个体间变异性。当需要时，可以联合使用马尔可夫链蒙特卡罗方法和多层次群体模型，对 PBPK 模型进行贝叶斯校准，以提高我们对群体异质性和易感性差异决定因素的理解。本文综述了这些进展，并结合最近在与环境相关的问题上的应用进行了说明。
