Application of physiologically based toxicokinetics models in risk assessment of chemicals

毒物动力学 风险评估 基于生理学的药代动力学模型 环境科学 生化工程 计算机科学 风险分析(工程) 工程类 业务 药理学 生物 药代动力学 计算机安全
作者
Shuying Zhang,Zhongyu Wang,Jingwen Chen
出处
期刊:Kexue tongbao [Science in China Press]
卷期号:62 (35): 4139-4150 被引量:3
标识
DOI:10.1360/n972017-00886
摘要

External exposure concentrations were conventionally employed used to quantify toxicological effects of chemicals in their risk assessment. However, internal concentrations are more suitable for understanding the toxicological effects and conducting risk assessment. It is necessary for accurate risk assessment of chemicals to predict the internal exposure of chemicals from the external exposure, and to know distribution of chemicals in different target tissues/organs (e.g. liver, kidney) of organisms. Experimental determination can hardly get high-throughput acquisition of target concentrations due to analytical limitations and expensive cost for in vivo animal tests. Alternatively, physiologically based toxicokinetics (PBTK) models that can quantitatively predict absorption, distribution, metabolism and excretion (ADME) processes of chemicals in biota are particularly useful. PBTK models could be used to predict the target concentrations, and to relate the environmental exposure concentrations with the target concentrations. Development of PBTK models can be divided into five steps. (1) Specify the general model structure. Portal of entry, target organ, lipophilicity and metabolism of chemicals are basic factors that should be considered. (2) Determine the set of ordinary differential equations representing the ADME processes of chemicals by the organism. All of these equations are mass balance equations. (3) Define model parameters, including physiological parameters, partition coefficients, biochemical rate constants and environment parameters. (4) Solve the ordinary differential equations with proper software. (5) Validate the model. Simulation results should be compared with corresponding experimental data to evaluate whether the model is accurate enough. Sensitivity, uncertainty and variability analysis should be performed to further optimize the model. Originating as a tool for serving pharmaceutical industry, PBTK models are now used in risk assessment of chemicals. PBTK models can also relate the in vivo toxicity thresholds with the in vitro toxicity thresholds. The in vitro-in vivo extrapolation can facilitate the utilization of the vast volume of high-throughput in vitro data. Traditional in vivo tests only focus on a limited number of the diverse species residing within an ecosystem. PBTK models can provide a promising cross-species solution by establishing physiologically relevant models for various species. Besides, classical indicators for hazard assessment such as bioconcentration factors could be re-evaluated by PBTK models with upgraded accuracy and details. Furthermore, it is possible to simulate the risk of chemicals that exerted on organisms over the entire lifetime of organisms with a sequence of PBTK models representing different developmental stages of the species. The combination of PBTK models and toxicodynamics (TD) models, i.e. PBTK/TD models, can further realize the simulation of the dynamic distribution of xenobiotics as well as the effects simultaneously. The power of PBTK models intended for ecological risk assessment of chemicals is yet to be fully exploited. Current PBTK models mainly apply to chemicals of neutral states. However, the molecular structures of many organic pollutants have carboxylic, phenolic groups, etc. Thus, these compounds can ionize under environmental pH conditions. A compound with different ionized states could possess different intake pathways. Thus, certain modifications of the mathematical form of the PBTK models are necessary. Another major obstacle is that the sophisticated parameters of PBTK models cannot be easily collected. Therefore, schemes for a high-throughput acquisition of the relevant parameters (e.g. quantitative structure-activity relationship models) would be highly useful. Furthermore, PBTK models should be extended to more species of ecological importance.
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