Department for Ecosystem Analysis, Institute for Environmental Research (Biology V), Aachen Biology and Biotechnology (ABBt), RWTH Aachen University, Aachen 52074, Germany.
Toxicology Centre, University of Saskatchewan, Saskatoon S7N 5B3, Canada.
Environ Sci Technol. 2021 Jul 6;55(13):9109-9118. doi: 10.1021/acs.est.1c02055. Epub 2021 Jun 24.
Standardized laboratory tests with a limited number of model species are a key component of chemical risk assessments. These surrogate species cannot represent the entire diversity of native species, but there are practical and ethical objections against testing chemicals in a large variety of species. In previous research, we have developed a multispecies toxicokinetic model to extrapolate chemical bioconcentration across species by combining single-species physiologically based toxicokinetic (PBTK) models. This "top-down" approach was limited, however, by the availability of fully parameterized single-species models. Here, we present a "bottom-up" multispecies PBTK model based on available data from 69 freshwater fishes found in Canada. Monte Carlo-like simulations were performed using statistical distributions of model parameters derived from these data to predict steady-state bioconcentration factors (BCFs) for a set of well-studied chemicals. The distributions of predicted BCFs for 1,4-dichlorobenzene and dichlorodiphenyltrichloroethane largely overlapped those of empirical data, although a tendency existed toward overestimation of measured values. When expressed as means, predicted BCFs for 26 of 34 chemicals (82%) deviated by less than 10-fold from measured data, indicating an accuracy similar to that of previously published single-species models. This new model potentially enables more environmentally relevant predictions of bioconcentration in support of chemical risk assessments.
标准化的实验室测试,使用有限数量的模式物种,是化学风险评估的一个关键组成部分。这些替代物种不能代表所有本地物种的多样性,但在大量物种中测试化学品在实践和伦理上存在反对意见。在之前的研究中,我们开发了一种多物种毒代动力学模型,通过结合单物种基于生理学的毒代动力学(PBTK)模型,来推断化学物质在物种间的生物浓缩。然而,这种“自上而下”的方法受到完全参数化的单物种模型的可用性的限制。在这里,我们提出了一种基于加拿大 69 种淡水鱼类的现有数据的“自下而上”多物种 PBTK 模型。使用从这些数据中得出的模型参数的统计分布,对稳态生物浓缩因子(BCF)进行了蒙特卡罗式模拟,以预测一组经过充分研究的化学品。1,4-二氯苯和滴滴涕的预测 BCF 分布与经验数据有很大的重叠,尽管存在高估实测值的趋势。当以平均值表示时,34 种化学物质中的 26 种(82%)的预测 BCF 与实测数据的偏差小于 10 倍,表明与以前发表的单物种模型的准确性相似。这种新模型有可能支持化学风险评估,更能准确地预测生物浓缩。