Roberts D W, Aptula A O, Cronin M T D, Hulzebos E, Patlewicz G
School of Pharmacy and Chemistry, Liverpool John Moores University, England, UK.
SAR QSAR Environ Res. 2007 May-Jun;18(3-4):343-65. doi: 10.1080/10629360701306118.
As part of a European Chemicals Bureau contract relating to the evaluation of (Q)SARs for toxicological endpoints of regulatory importance, we have reviewed and analysed (Q)SARs for skin sensitisation. Here we consider some recently published global (Q)SAR approaches against the OECD principles and present re-analysis of the data. Our analyses indicate that "statistical" (Q)SARs which aim to be global in their applicability tend to be insufficiently robust mechanistically, leading to an unacceptably high failure rate. Our conclusions are that, for skin sensitisation, the mechanistic chemistry is very important and consequently the best non-animal approach currently applicable to predict skin sensitisation potential is with the help of an expert system. This would assign compounds into mechanistic applicability domains and apply mechanism-based (Q)SARs specific for those domains and, very importantly, recognise when a compound is outside its range of competence. In such situations, it would call for human expert input supported by experimental chemistry studies as necessary.
作为欧洲化学品管理局一项合同的一部分，该合同涉及对具有监管重要性的毒理学终点的（定量）构效关系进行评估，我们已对皮肤致敏的（定量）构效关系进行了审查和分析。在此，我们根据经合组织原则考量了一些最近发表的全球（定量）构效关系方法，并对数据进行了重新分析。我们的分析表明，旨在具有广泛适用性的“统计”（定量）构效关系在机制上往往不够稳健，导致失败率高得令人无法接受。我们的结论是，对于皮肤致敏而言，机制化学非常重要，因此目前适用于预测皮肤致敏潜力的最佳非动物方法是借助专家系统。该系统将把化合物分配到机制适用域，并应用针对这些域的基于机制的（定量）构效关系，而且非常重要的是，识别化合物何时超出其能力范围。在这种情况下，如有必要，它将要求人类专家投入，并辅以实验化学研究。
