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A biology-based approach for quantitative structure-activity relationships (QSARs) in ecotoxicity.

机译:一种基于生物学的生态毒性定量构效关系(QSAR)方法。

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摘要

Quantitative structure-activity relationships (QSARs) for ecotoxicity can be used to fill data gaps and limit toxicity testing on animals. QSAR development may additionally reveal mechanistic information based on observed patterns in the data. However, the use of descriptive summary statistics for toxicity, such as the 4-day LC50 for fish, introduces bias and ignores valuable kinetic information in the data. Biology-based methods use all of the toxicity data in time to derive time-independent and unbiased parameter estimates. Such an approach offers whole new opportunities for mechanism-based QSAR development. In this paper, we apply the hazard model from DEBtox to analyse survival data for fathead minnows (Pimephales promelas). Different modes of action resulted in different patterns in the parameter estimates, and therefore, the toxicity data by themselves reveal insight into the actual mechanism of toxic action.
机译:生态毒性的定量构效关系(QSAR)可用于填补数据空白并限制对动物的毒性测试。 QSAR的开发还可以根据数据中观察到的模式显示机械信息。但是,使用描述性摘要统计数据进行毒性分析(例如鱼的4天LC50)会产生偏差,并且会忽略数据中有价值的动力学信息。基于生物学的方法会及时使用所有毒性数据,以得出与时间无关且无偏倚的参数估计值。这种方法为基于机制的QSAR开发提供了全新的机会。在本文中,我们使用DEBtox的危害模型来分析黑头fat(Pimephales promelas)的生存数据。不同的作用方式导致参数估计值的模式不同,因此,毒性数据本身揭示了对毒性作用的实际机制的了解。

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