Krishnan Kannan, Johanson Gunnar
Groupe de Recherche en Toxicologie Humaine, Université de Montréal, Canada.
J Environ Sci Health C Environ Carcinog Ecotoxicol Rev. 2005;23(1):31-53. doi: 10.1081/GNC-200051856.
Physiologically-based pharmacokinetic (PBPK) and toxicokinetic models are increasingly being used for the conduct of high dose to low dose and interspecies extrapolations required in cancer risk assessment. These models, by simulating tissue dose of toxic chemicals, help address the uncertainty associated with the default approaches for interspecies and high dose to low dose extrapolations. The applicability of PBPK models in cancer risk assessment has been demonstrated with a number of chemicals (e.g., acrylonitrile, 2-butoxyethanol, chloroform, 1,4-dioxane, methyl chloroform, methylene chloride, styrene, trichloroethylene, tetrachloroethylene, vinyl chloride, vinyl acetate). Recent advances in PBPK modeling facilitate the consideration of population distribution of parameter values, age-dependent changes in physiology and metabolism, multi-route exposures as well as multichemical interactions for application in cancer risk assessment. Whereas the average values for various input parameters have been used to evaluate the age-dependency of tissue dose, the Markov Chain Monte Carlo technique can be applied to address variability and uncertainty in parameter estimates, thus facilitating a more accurate estimation of cancer risk in the population. The PBPK models also uniquely facilitate the simulation of tissue dose, and thereby cancer risks, associated with multi-route and multichemical exposure situations. Overall, the recent advances reviewed in this article point to the continued enhancement of the scientific basis and applicability of PBPK models in cancer risk assessment.
基于生理学的药代动力学(PBPK)模型和毒代动力学模型越来越多地用于癌症风险评估中所需的高剂量到低剂量以及种间外推。这些模型通过模拟有毒化学物质的组织剂量,有助于解决与种间和高剂量到低剂量外推的默认方法相关的不确定性。PBPK模型在癌症风险评估中的适用性已在多种化学物质(例如丙烯腈、2-丁氧基乙醇、氯仿、1,4-二恶烷、甲基氯仿、二氯甲烷、苯乙烯、三氯乙烯、四氯乙烯、氯乙烯、醋酸乙烯酯)中得到证明。PBPK建模的最新进展有助于考虑参数值的人群分布、生理和代谢的年龄依赖性变化、多途径暴露以及多化学物质相互作用,以应用于癌症风险评估。虽然各种输入参数的平均值已用于评估组织剂量的年龄依赖性,但马尔可夫链蒙特卡罗技术可用于解决参数估计中的变异性和不确定性,从而有助于更准确地估计人群中的癌症风险。PBPK模型还特别有助于模拟与多途径和多化学物质暴露情况相关的组织剂量,进而模拟癌症风险。总体而言,本文综述的最新进展表明PBPK模型在癌症风险评估中的科学基础和适用性不断增强。