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在《化学品注册、评估、授权和限制法规》(REACH)下进行持久性、生物累积性和毒性(PBT)评估及优先排序的整合计算机模拟策略。

Integrated in silico strategy for PBT assessment and prioritization under REACH.

作者信息

Pizzo Fabiola, Lombardo Anna, Manganaro Alberto, Cappelli Claudia I, Petoumenou Maria I, Albanese Federica, Roncaglioni Alessandra, Brandt Marc, Benfenati Emilio

机构信息

IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Department of Environmental Health Sciences, Laboratory of Environmental Chemistry and Toxicology, Via La Masa 19, 20159 Milan, Italy.

IRCCS - Istituto di Ricerche Farmacologiche "Mario Negri", Department of Environmental Health Sciences, Laboratory of Environmental Chemistry and Toxicology, Via La Masa 19, 20159 Milan, Italy.

出版信息

Environ Res. 2016 Nov;151:478-492. doi: 10.1016/j.envres.2016.08.014. Epub 2016 Aug 24.

DOI:10.1016/j.envres.2016.08.014
PMID:27567352
Abstract

Chemicals may persist in the environment, bioaccumulate and be toxic for humans and wildlife, posing great concern. These three properties, persistence (P), bioaccumulation (B), and toxicity (T) are the key targets of the PBT-hazard assessment. The European regulation for the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) requires assessment of PBT-properties for all chemicals that are produced or imported in Europe in amounts exceeding 10 tonnes per year, checking whether the criteria set out in REACH Annex XIII are met, so the substance should therefore be considered to have properties of very high concern. Considering how many substances can fall under the REACH regulation, there is a pressing need for new strategies to identify and screen large numbers fast and inexpensively. An efficient non-testing screening approach to identify PBT candidates is necessary, as a valuable alternative to money- and time-consuming laboratory tests and a good start for prioritization since few tools exist (e.g. the PBT profiler developed by US EPA). The aim of this work was to offer a conceptual scheme for identifying and prioritizing chemicals for further assessment and if appropriate further testing, based on their PBT-potential, using a non-testing screening approach. We integrated in silico models (using existing and developing new ones) in a final algorithm for screening and ranking PBT-potential, which uses experimental and predicted values as well as associated uncertainties. The Multi-Criteria Decision-Making (MCDM) theory was used to integrate the different values. Then we compiled a new set of data containing known PBT and non-PBT substances, in order to check how well our approach clearly differentiated compounds labeled as PBT from those labeled as non-PBT. This indicated that the integrated model distinguished between PBT from non-PBT compounds.

摘要

化学物质可能会在环境中持久存在、生物累积并对人类和野生动物产生毒性,这引发了人们的极大关注。持久性(P)、生物累积性(B)和毒性(T)这三个特性是PBT危害评估的关键目标。欧洲化学品注册、评估、授权和限制法规(REACH)要求对在欧洲生产或进口量每年超过10吨的所有化学品进行PBT特性评估,检查是否符合REACH附件XIII中规定的标准,因此该物质应被视为具有高度关注特性。考虑到有多少物质可能受REACH法规管辖,迫切需要新的策略来快速且低成本地识别和筛选大量物质。一种有效的非测试筛选方法来识别PBT候选物质是必要的,作为耗时耗钱的实验室测试的有价值替代方法,并且由于可用工具很少(例如美国环境保护局开发的PBT分析器),这也是进行优先级排序的良好开端。这项工作的目的是提供一个概念框架,用于基于化学品的PBT潜力,使用非测试筛选方法来识别化学品并对其进行优先级排序,以便进一步评估,如有必要还可进行进一步测试。我们将计算机模拟模型(使用现有的并开发新的模型)整合到一个最终算法中,用于筛选和排列PBT潜力,该算法使用实验值和预测值以及相关的不确定性。多标准决策理论(MCDM)被用于整合不同的值。然后我们汇编了一组新的数据,其中包含已知的PBT和非PBT物质,以检查我们的方法能多好地将标记为PBT的化合物与标记为非PBT的化合物清晰区分开来。这表明整合模型能够区分PBT和非PBT化合物。

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