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CAESAR models for developmental toxicity

机译:CAESAR发育毒性模型

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Background The new REACH legislation requires assessment of a large number of chemicals in the European market for several endpoints. Developmental toxicity is one of the most difficult endpoints to assess, on account of the complexity, length and costs of experiments. Following the encouragement of QSAR ( in silico ) methods provided in the REACH itself, the CAESAR project has developed several models. Results Two QSAR models for developmental toxicity have been developed, using different statistical/mathematical methods. Both models performed well. The first makes a classification based on a random forest algorithm, while the second is based on an adaptive fuzzy partition algorithm. The first model has been implemented and inserted into the CAESAR on-line application, which is java-based software that allows everyone to freely use the models. Conclusions The CAESAR QSAR models have been developed with the aim to minimize false negatives in order to make them more usable for REACH. The CAESAR on-line application ensures that both industry and regulators can easily access and use the developmental toxicity model (as well as the models for the other four endpoints).
机译:背景信息新的REACH法规要求评估欧洲市场上多个端点的大量化学品。由于实验的复杂性,持续时间和成本,发育毒性是最难评估的终点之一。在REACH自身提供的QSAR(计算机)方法的鼓励下,CAESAR项目开发了几种模型。结果使用不同的统计/数学方法,开发了两种QSAR发育毒性模型。两种模型均表现良好。第一种基于随机森林算法进行分类,而第二种基于自适应模糊分区算法。第一个模型已经实现并插入到CAESAR在线应用程序中,该应用程序是基于Java的软件,每个人都可以自由使用这些模型。结论CAESAR QSAR模型的开发旨在最大程度地减少假阴性,以使其更易于用于REACH。 CAESAR在线应用程序可确保行业和监管机构都可以轻松访问和使用发育毒性模型(以及其他四个端点的模型)。

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