Institut National de l'Environnement Industriel et des Risques (INERIS), Models for Ecotoxicology and Toxicology Unit, Parc ALATA, BP2, 60550 Verneuil-en-Halatte, France; Analytica Laser, 3 rue de l'arrivée, 75015 Paris, France; Institut National de l'Environnement Industriel et des Risques (INERIS), UMR-I 02 SEBIO, Parc ALATA, BP2, 60550 Verneuil-en-Halatte, France.
Institut National de l'Environnement Industriel et des Risques (INERIS), Models for Ecotoxicology and Toxicology Unit, Parc ALATA, BP2, 60550 Verneuil-en-Halatte, France.
Sci Total Environ. 2019 Feb 15;651(Pt 1):516-531. doi: 10.1016/j.scitotenv.2018.09.163. Epub 2018 Sep 15.
One of the goals of environmental risk assessment is to protect the whole ecosystem from adverse effects resulting from exposure to chemicals. Many research efforts have aimed to improve the quantification of dose-response relationships through the integration of toxicokinetics. For this purpose, physiologically-based toxicokinetic (PBTK) models have been developed to estimate internal doses from external doses in a time-dependent manner. In this study, a generic PBTK model was developed and adapted for rainbow trout (Onchorhynchus mykiss), zebrafish (Danio rerio), fathead minnow (Pimephales promelas), and three-spined stickleback (Gasterosteus aculeatus). New mechanistic approaches were proposed for including the effects of growth and temperature in the model. Physiological parameters and their inter-individual variability were estimated based on the results of extensive literature searches or specific experimental data. The PBTK model was implemented for nine environmental contaminants (with log k from -0.9 to 6.8) to predict whole-body concentrations and concentrations in various fish's organs. Sensitivity analyses were performed for a lipophilic and a hydrophilic compound to identify which parameters have most impact on the model's outputs. Model predictions were compared with experimental data according to dataset-specific exposure scenarios and were accurate: 50% of predictions were within a 3-fold factor for six out of nine chemicals and 75% of predictions were within a 3-fold factor for three of the most lipophilic compounds studied. Our model can be used to assess the influence of physiological and environmental factors on the toxicokinetics of chemicals and provide guidance for assessing the effect of those critical factors in environmental risk assessment.
环境风险评估的目标之一是保护整个生态系统免受因接触化学物质而产生的不利影响。许多研究旨在通过整合毒代动力学来提高剂量-反应关系的定量。为此，开发了基于生理的毒代动力学 (PBTK) 模型，以随时间推移的方式从外剂量估算内剂量。在这项研究中，开发并适应了虹鳟鱼 (Onchorhynchus mykiss)、斑马鱼 (Danio rerio)、黑头软口鱼 (Pimephales promelas) 和三刺棘鱼 (Gasterosteus aculeatus) 的通用 PBTK 模型。提出了新的机制方法来将生长和温度的影响纳入模型。生理参数及其个体间变异性是根据广泛的文献搜索或特定的实验数据来估计的。PBTK 模型被用于九种环境污染物（log k 从-0.9 到 6.8），以预测全身浓度和各种鱼类器官中的浓度。对亲脂性和亲水性化合物进行了敏感性分析，以确定哪些参数对模型输出的影响最大。根据数据集特定的暴露情景，将模型预测与实验数据进行比较，结果准确：对于九种化学物质中的六种，有 50%的预测在 3 倍因子内，对于研究的三种最亲脂性化合物中的三种，有 75%的预测在 3 倍因子内。我们的模型可用于评估生理和环境因素对化学物质毒代动力学的影响，并为评估这些关键因素在环境风险评估中的影响提供指导。
