Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy.
ALTEX. 2013;30(1):19-40. doi: 10.14573/altex.2013.1.019.
Leading QSAR models provide supporting documentation in addition to a predicted toxicological value. Such information enables the toxicologist to explore the properties of chemical substances as well as to review and to increase the reliability of toxicity predictions. This article focuses on the use of this information in practice. We explore the supporting documentation provided by the EPISuite, T.E.S.T. and VEGA platforms when evaluating the bioconcentration factor (BCF) of three example compounds. Each compound presents a different challenge: to recognize high reliability, analyze complex evidence of reliability, and recognize uncertainty. In each case, we first describe and discuss the supporting documentation provided by the QSAR platforms. We then discuss the judgments on reliability across sectors from 28 toxicologists who used this supporting information and commented on the process. The article demonstrates both the use of QSAR models as tools to reduce or replace in vivo testing, and the need for scientific expertise and rigor in their use.
领先的定量构效关系（QSAR）模型除了提供预测的毒理学值外，还提供支持文档。此类信息使毒理学家能够探索化学物质的特性，以及审查和提高毒性预测的可靠性。本文重点介绍在实践中使用此类信息。我们探讨了在评估三个示例化合物的生物浓缩因子（BCF）时，EPISuite、T.E.S.T. 和 VEGA 平台提供的支持文档。每个化合物都提出了不同的挑战：识别高可靠性、分析可靠性的复杂证据以及识别不确定性。在每种情况下，我们首先描述和讨论 QSAR 平台提供的支持文档。然后，我们讨论了 28 位毒理学家对不同领域的可靠性判断，这些毒理学家使用了这些支持信息并对该过程发表了评论。本文既展示了 QSAR 模型作为减少或替代体内测试的工具的使用，也展示了在使用这些模型时对科学专业知识和严谨性的需求。
