We developed a read-across workflow using the OECD QSAR Toolbox for the prediction of skin irritation and corrosion. In the workflow, we gathered analogues using an improved profiler for skin irritation and corrosion to define valid categories. In addition, we refined categories by removing chemicals based on melting points and structural features. Finally, prediction results were obtained using our self-determined rule for read-across. In this rule, we decided the number of analogues from which the read-across is performed, analogue selection criteria (i.e. high similarity vs. near log P_ow) and prediction rule (i.e. majority vs. unanimity). We created a program for the optimization of read-across workflows. We applied this program to 313 chemicals in the training set and sought the optimized workflows among >1000 possible choices of profilers and ways of subcategorization and data gap filling. Use of the optimized workflows provided highly accurate, unbiased, user-independent and reproducible read-across predictions. The prediction results obtained from read-across workflows can be used for the selection of in vitro test methods or as part of the weight-of-evidence approaches in the Integrated Approach on Testing and Assessment for skin irritation and corrosion. Moreover, these results can be used for screening purposes and/or preliminary hazard assessment.

我们使用OECD QSAR Toolbox开发了一个跨区域工作流程，用于预测皮肤刺激和腐蚀。在工作流程中，我们使用改进的探查器收集了类似物，以刺激皮肤和腐蚀皮肤，以定义有效的类别。此外，我们通过根据熔点和结构特征去除化学物质来细化类别。最后，使用我们自己确定的交叉读取规则获得了预测结果。在此规则中，我们决定类似物的数目从其中读跨越执行，类似物的选择标准（即，高相似度与邻近日志P_流）和预测规则（即多数与一致）。我们创建了一个用于优化跨工作流的程序。我们将此程序应用于培训集中的313种化学品，并在超过1000种可能的分析器选择以及子分类和数据缺口填充方式中寻求了优化的工作流程。优化工作流程的使用提供了高度准确，无偏见，用户独立且可重复的跨读预测。从交叉阅读的工作流程中获得的预测结果可用于选择体外测试方法，或作为皮肤刺激和腐蚀综合测试和评估方法中证据权重方法的一部分。此外，这些结果可用于筛选目的和/或初步危害评估。