The extrapolation of effects from controlled standard laboratory tests to real environmental conditions is a major challenge facing ecological risk assessment (ERA) of chemicals. Toxicokinetic–toxicodynamic (TKTD) models, such as those based on dynamic energy budget (DEB) theory, can play an important role in filling this gap. Through the years, different practical TKTD models have been derived from DEB theory, ranging from the full “standard” DEB animal model to simplified “DEBtox” models. It is currently unclear what impact a different level of model complexity can have on the regulatory risk assessment. In the present study, we compare the performance of two DEB–TKTD models with different levels of complexity, focusing on model calibration on standard test data and on forward predictions for untested time-variable exposure profiles. The first model is based on the standard DEB model with primary parameters, whereas the second is a reduced version with compound parameters, based on DEBkiss. After harmonization of the modeling choices, we demonstrate that these two models can achieve very similar performances both in the calibration step and in the forward prediction step. With the data presented in the present study, selection of the most suitable TKTD model for ERA therefore cannot be based alone on goodness-of-fit or on the precision of model predictions (within current ERA procedures for pesticides) but would likely be based on the trade-off between ease of use and model flexibility. We also stress the importance of modeling choices, such as how to fill gaps in the information content of experimental toxicity data and how to accommodate differences in growth and reproduction between different data sets for the same chemical–species combination. Environ Toxicol Chem 2024;43:440–449. © 2023 ibacon GmbH. Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

中文翻译：

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使用能源预算模型进行环境风险评估：两种不同复杂度模型之间的比较

将受控标准实验室测试的影响外推到真实环境条件是化学品生态风险评估（ERA）面临的主要挑战。毒代动力学-毒动力学（TKTD）模型，例如基于动态能量预算（DEB）理论的模型，可以在填补这一空白方面发挥重要作用。多年来，从 DEB 理论衍生出不同的实用 TKTD 模型，从完整的“标准”DEB 动物模型到简化的“DEBtox”模型。目前尚不清楚不同级别的模型复杂性会对监管风险评估产生什么影响。在本研究中，我们比较了两种不同复杂程度的 DEB-TKTD 模型的性能，重点关注标准测试数据的模型校准和未经测试的时变暴露曲线的前向预测。第一个模型基于具有主要参数的标准 DEB 模型，而第二个模型是基于 DEBkiss 的具有复合参数的简化版本。在协调建模选择之后，我们证明这两个模型可以在校准步骤和前向预测步骤中实现非常相似的性能。因此，根据本研究中提供的数据，选择最适合 ERA 的 TKTD 模型不能仅基于拟合优度或模型预测的精度（在当前的农药 ERA 程序内），而可能基于易用性和模型灵活性之间的权衡。我们还强调建模选择的重要性，例如如何填补实验毒性数据信息内容的空白，以及如何适应同一化学物种组合的不同数据集之间的生长和繁殖差异。环境毒理学2024；43：440–449。© 2023 ibacon GmbH。拜耳公司和作者。《环境毒理学和化学》由 Wiley periodicals LLC 代表 SETAC 出版。