We report new consensus models estimating acute toxicity for algae, Daphnia and fish endpoints. We assembled a large collection of 3680 public unique compounds annotated by, at least, one experimental value for the given endpoint. Support Vector Machine models were internally and externally validated following the OECD principles. Reasonable predictive performances were achieved (RMSE_ext = 0.56–0.78) which are in line with those of state-of-the-art models. The known structural alerts are compared with analysis of the atomic contributions to these models obtained using the ISIDA/ColorAtom utility. A benchmarking against existing tools has been carried out on a set of compounds considered more representative and relevant for the chemical space of the current chemical industry. Our model scored one of the best accuracy and data coverage.

Nevertheless, industrial data performances were noticeably lower than those on public data, indicating that existing models fail to meet the industrial needs. Thus, final models were updated with the inclusion of new industrial compounds, extending the applicability domain and relevance for application in an industrial context. Generated models and collected public data are made freely available.

我们报告了新的共识模型，估计藻类，水蚤和鱼类终点的急性毒性。我们组装了3680种公共独特化合物的大集合，这些化合物至少以给定终点的一个实验值进行注释。支持向量机模型是根据OECD原则进行内部和外部验证的。实现了合理的预测性能（RMSE _ext = 0.56-0.78），与最新模型一致。将已知的结构警报与对使用ISIDA / ColorAtom实用程序获得的这些模型的原子贡献的分析进行比较。已对一组化合物进行了基准测试，这些化合物被认为更具代表性，并且与当前化学工业的化学空间相关。我们的模型获得了最佳的准确性和数据覆盖率之一。

但是，工业数据性能明显低于公共数据，这表明现有模型无法满足工业需求。因此，最终模型进行了更新，其中包含了新的工业化合物，从而扩展了在工业环境中的适用范围和相关性。生成的模型和收集的公共数据可免费获得。