Freshwater planarian Dugesia japonica has a critical ecological importance owing to its unique properties. This study presents for the first time an in silico approach to determine a priori the acute toxicity of contaminants of emerging concern towards D. japonica. Quantitative structure-toxicity/toxicity-toxicity relationship (QSTR/QTTR) models provided here allow producing reliable information using the existing data, thus, reducing the demand of in vivo and in vitro experiments, and contributing to the need for a more holistic approach to environmental safety assessment. Both models are promising for being notably simple and robust, meeting rigorous validation metrics and the OECD criteria. The QTTR model based on the available Daphnia magna data might also contribute to the US EPA Interspecies Correlation Estimation web application. Moreover, the proposed models were applied on hundreds of environmentally significant chemicals lacking experimental D. japonica toxicity data and predicted toxicity values were reported for the first time. The models presented here can be used as potential tools in toxicity assessment, screening and prioritization of chemicals and development of risk management measures in a scientific and regulatory frame.

由于其独特的特性，淡水涡planar在日本具有重要的生态意义。这项研究首次提出了一种计算机方法，用于先验确定新兴关注的污染物对粳稻的急性毒性。此处提供的定量结构-毒性/毒性-毒性关系（QSTR / QTTR）模型允许使用现有数据生成可靠的信息，从而减少了体内和体外的需求实验，并为环境安全评估提供了一种更全面的方法。两种模型都有望变得非常简单和健壮，并满足严格的验证指标和OECD标准。基于可用的水蚤（Daphnia magna）数据的QTTR模型也可能有助于美国EPA种间相关性估计Web应用程序。此外，提出的模型被应用于缺乏实验性日本粳稻的毒性数据的数百种对环境有重大影响的化学物质，并且首次报道了预测的毒性值。此处介绍的模型可用作科学和法规框架中的毒性评估，化学物质的筛选和优先级划分以及制定风险管理措施的潜在工具。