Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands.
Center for Safety of Substances and Products, National Institute of Public Health and the Environment, Bilthoven, The Netherlands.
Environ Toxicol Chem. 2022 Jun;41(6):1439-1450. doi: 10.1002/etc.5322. Epub 2022 Apr 8.
The conventional Hill equation model is suitable to fit dose-response data obtained from performing (eco)toxicity assays. Models based on quasi-quantitative structure-activity relationships (QSARs) to estimate the Hill coefficient ( were developed with the aim of predicting the response of the invertebrate species Daphnia magna to exposure to metal-based nanomaterials. Descriptors representing the pristine properties of nanoparticles and media conditions were coded to a quasi-simplified molecular input line entry system and correlated to experimentally derived values of . Monte Carlo optimization was used to model the set of values, and the model was trained on the basis of reported dose-response relationships of 60 data sets (n = 367 individual response observations) of 11 metal-based nanomaterials as obtained from 20 literature reports. The model simulates the training data well, with only 2.3% deviation between experimental and modeled response data. The technique was employed to predict the dose-response relationships of 15 additional data sets (n = 72 individual observations) not included in model development of seven metal-based nanomaterials from 10 literature reports, with an average error of 3.5%. Combining the model output with either the median effective concentration value or any other known effect level as obtained from experimental data allows the prediction of full dose-response curves of D. magna immobilization. This model is an accurate screening tool that allows the determination of the shape and slope of dose-response curves, thereby greatly reducing experimental effort in case of novel advanced metal-based nanomaterials or the prediction of responses in altered exposure media. This screening model is compliant with the 3Rs (replacement, reduction, and refinement) principle, which is embraced by the scientific and regulatory communities dealing with nano-safety. Environ Toxicol Chem 2022;41:1439-1450. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.
传统的 Hill 方程模型适用于拟合进行（生态）毒性测定获得的剂量-反应数据。基于准定量构效关系（QSAR）来估计 Hill 系数（ 的模型是为了预测模式生物大型溞对金属基纳米材料暴露的反应而开发的。用于编码表示纳米颗粒原始特性和介质条件的描述符被编码到准简化分子输入线进系统，并与实验得出的 值相关联。蒙特卡罗优化用于对 组值进行建模，该模型是基于 20 份文献报告中 11 种金属基纳米材料的 60 个数据集（n = 367 个个体反应观察值）的报告剂量-反应关系进行训练的。该模型很好地模拟了训练数据，实验和模型反应数据之间的偏差仅为 2.3%。该技术被用于预测 15 个额外数据集（n = 72 个个体观察值）的剂量-反应关系，这些数据集来自 10 份文献报告的 7 种金属基纳米材料，模型开发中未包括，平均误差为 3.5%。将模型输出与中值有效浓度值或从实验数据中获得的任何其他已知效应水平结合使用，可以预测大型溞固定的全剂量-反应曲线。该模型是一种准确的筛选工具，可以确定剂量-反应曲线的形状和斜率，从而大大减少了新型先进金属基纳米材料的实验工作量或在改变的暴露介质中预测反应的工作量。该筛选模型符合科学和监管纳米安全领域所采用的 3R（替代、减少和优化）原则。Environ Toxicol Chem 2022;41:1439-1450. © 2022 作者。环境毒理化学由 Wiley Periodicals LLC 代表 SETAC 出版。
