School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Byrom Street, Liverpool, L3 3AF, UK.
University of Tennessee, College of Veterinary Medicine, Knoxville, TN, 37996-4500, USA.
Regul Toxicol Pharmacol. 2021 Jul;123:104956. doi: 10.1016/j.yrtph.2021.104956. Epub 2021 May 9.
In silico models are used to predict toxicity and molecular properties in chemical safety assessment, gaining widespread regulatory use under a number of legislations globally. This study has rationalised previously published criteria to evaluate quantitative structure-activity relationships (QSARs) in terms of their uncertainty, variability and potential areas of bias, into ten assessment components, or higher level groupings. The components have been mapped onto specific regulatory uses (i.e. data gap filling for risk assessment, classification and labelling, and screening and prioritisation) identifying different levels of uncertainty that may be acceptable for each. Twelve published QSARs were evaluated using the components, such that their potential use could be identified. High uncertainty was commonly observed with the presentation of data, mechanistic interpretability, incorporation of toxicokinetics and the relevance of the data for regulatory purposes. The assessment components help to guide strategies that can be implemented to improve acceptability of QSARs through the reduction of uncertainties. It is anticipated that model developers could apply the assessment components from the model design phase (e.g. through problem formulation) through to their documentation and use. The application of the components provides the possibility to assess QSARs in a meaningful manner and demonstrate their fitness-for-purpose against pre-defined criteria.
在计算机安全评估中，人们利用计算机模型来预测毒性和分子特性，这一方法已在全球多项法规下得到了广泛的监管应用。本研究对之前发布的评估标准进行了合理化，根据其不确定性、可变性和潜在偏差领域，将其分为十个评估部分，或更高级别的分组。这些组成部分已映射到特定的监管用途（即风险评估、分类和标签、筛选和优先级划分的数据缺口填补），确定了每个用途可接受的不同不确定性水平。使用这些组成部分评估了十二个已发表的定量构效关系（QSAR），以确定其潜在用途。数据呈现、机制可解释性、纳入毒代动力学以及数据与监管用途的相关性等方面通常存在高度不确定性。评估组成部分有助于指导通过降低不确定性来提高 QSAR 可接受性的策略。预计模型开发人员可以从模型设计阶段（例如通过问题制定）到文档编制和使用阶段应用评估组成部分。应用这些组成部分可以以有意义的方式评估 QSAR，并根据预定义标准证明其适用性。
