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预测预制造通知化学品的易生物降解性。

Predicting ready biodegradability of premanufacture notice chemicals.

作者信息

Boethling Robert S, Lynch David G, Thom Gary C

机构信息

US Environmental Protection Agency, Office of Pollution Prevention and Toxics, Mail Code 7406, 1200 Pennsylvania Avenue, Northwest, Washington, DC 20004, USA.

出版信息

Environ Toxicol Chem. 2003 Apr;22(4):837-44.

Abstract

Chemical substances other than pesticides, drugs, and food additives are regulated by the U.S. Environmental Protection Agency (U.S. EPA) under the Toxic Substances Control Act (TSCA), but the United States does not require that new substances be tested automatically for such critical properties as biodegradability. The resulting lack of submitted data has fostered the development of estimation methods, and the BioWIN models for predicting biodegradability from chemical structure have played a prominent role in premanufacture notice (PMN) review. Until now, validation efforts have used only the Japanese Ministry of International Trade and Industry (MITI) test data and have not included all models. To assess BioWIN performance with PMN substances, we assembled a database of PMNs for which ready biodegradation data had been submitted over the period 1995 through 2001. The 305 PMN structures are highly varied and pose major challenges to chemical property estimation. Despite the variability of ready biodegradation tests, the use of at least six different test methods, and widely varying quality of submitted data, accuracy of four of six BioWIN models (MITI linear, MITI nonlinear, survey ultimate, survey primary) was in the 80+% range for predicting ready biodegradability. Greater accuracy (>90%) can be achieved by using model estimates only when the four models agree (true for 3/4 of the PMNs). The BioWIN linear and nonlinear probability models did not perform as well even when classification criteria were optimized. The results suggest that the MITI and survey BioWIN models are suitable for use in screening-level applications.

摘要

除农药、药品和食品添加剂以外的化学物质,由美国环境保护局(U.S. EPA)依据《有毒物质控制法》(TSCA)进行监管,但美国并不要求对新物质自动进行诸如生物降解性等关键特性的测试。由此导致的提交数据缺失促进了估算方法的发展,而用于从化学结构预测生物降解性的BioWIN模型在预生产通知(PMN)审查中发挥了重要作用。到目前为止,验证工作仅使用了日本国际贸易和工业部(MITI)的测试数据,且未涵盖所有模型。为评估BioWIN对PMN物质的性能,我们收集了1995年至2001年期间已提交了快速生物降解数据的PMN数据库。这305种PMN结构高度多样,给化学性质估算带来了重大挑战。尽管快速生物降解测试存在变异性,使用了至少六种不同的测试方法,且提交数据的质量差异很大,但六种BioWIN模型中的四种(MITI线性、MITI非线性、调查最终、调查初级)在预测快速生物降解性方面的准确率在80%以上。仅在四种模型达成一致时(3/4的PMN符合此情况)使用模型估算,可实现更高的准确率(>90%)。即使优化了分类标准,BioWIN线性和非线性概率模型的表现也不佳。结果表明,MITI和调查BioWIN模型适用于筛选级应用。

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