Liverpool John Moores University, School of Pharmacy and Biomolecular Sciences, Liverpool, England, United Kingdom.
European Commission, Joint Research Centre (JRC), Ispra, Italy.
Regul Toxicol Pharmacol. 2019 Aug;106:90-104. doi: 10.1016/j.yrtph.2019.04.007. Epub 2019 Apr 24.
Improving regulatory confidence in, and acceptance of, a prediction of toxicity from a quantitative structure-activity relationship (QSAR) requires assessment of its uncertainty and determination of whether the uncertainty is acceptable. Thus, it is crucial to identify potential uncertainties fundamental to QSAR predictions. Based on expert review, sources of uncertainties, variabilities and biases, as well as areas of influence in QSARs for toxicity prediction were established. These were grouped into three thematic areas: uncertainties, variabilities, potential biases and influences associated with 1) the creation of the QSAR, 2) the description of the QSAR, and 3) the application of the QSAR, also showing barriers for their use. Each thematic area was divided into a total of 13 main areas of concern with 49 assessment criteria covering all aspects of QSAR development, documentation and use. Two case studies were undertaken on different types of QSARs that demonstrated the applicability of the assessment criteria to identify potential weaknesses in the use of a QSAR for a specific purpose such that they may be addressed and mitigation strategies can be proposed, as well as enabling an informed decision on the adequacy of the model in the considered context.
为了提高对定量构效关系(QSAR)毒性预测的监管信心和接受度,需要评估其不确定性,并确定不确定性是否可接受。因此,确定 QSAR 预测中潜在的不确定性至关重要。基于专家评审,确定了与毒性预测的 QSAR 相关的不确定性、可变性和偏差的潜在来源,以及影响因素。这些因素被分为三个主题领域:与 1)QSAR 的创建、2)QSAR 的描述和 3)QSAR 的应用相关的不确定性、可变性、潜在偏差和影响,同时也展示了其使用的障碍。每个主题领域总共分为 13 个主要关注点,共有 49 个评估标准,涵盖了 QSAR 开发、文件编制和使用的各个方面。进行了两个不同类型的 QSAR 的案例研究,这些研究表明,评估标准可用于确定在特定目的下使用 QSAR 的潜在弱点,以便解决这些弱点,并提出缓解策略,同时能够在考虑到的背景下对模型的充分性做出明智的决策。