In silico occupational exposure banding framework for data poor compounds in biotechnology.

IF 1.7 4区 医学 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Andrey Massarsky, Ernest S Fung, Veneese Jb Evans, Andrew Maier
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引用次数: 0

Abstract

Occupational exposure limits (OELs) and occupational exposure bands (OEBs) provide quantitative benchmarks for worker health protection. If empirical toxicology data are insufficient to derive an OEL, an OEB is often assigned using partial toxicology data along with other relevant hazard information. There is no consensus methodology to assign OEBs for chemicals lacking any empirical toxicology data. Thus, this study developed an in silico framework for OEB assignment of data poor compounds. It relies upon computational tools to evaluate standard toxicological end points and to assign reliability ratings, which are then used to assign Global Harmonization System (GHS) hazard categories. Subsequently, the hazard categories are entered into the National Institute for Occupational Safety and Health (NIOSH) occupational exposure banding tool to assign bands for individual end points as well as an overall OEB. As a proof-of-concept, five compounds with established OELs (i.e., "knowns") were evaluated. The knowns were assigned to overall OEBs C, D, or E, four of which were equal to or lower than the OEBs based on actual harmonized GHS categories as well as established OELs, indicating that the OEBs assigned using this framework are likely to be protective. Subsequently, five compounds with little to no experimental data and no established OELs from any U.S. agency or consensus OEL-setting organizations were evaluated (i.e., "unknowns"). The unknowns were assigned to overall OEBs D or E. It was concluded that the proposed framework can be used to assign protective OEBs to compounds with little to no toxicology testing data. As additional data become available, the compound may be de-risked, and a precautionary OEB (or an OEL) can be assigned. The proposed framework provides an example of a practical methodology to evaluate data poor compounds and shows that the output of this framework is expected to be protective of worker health.

生物技术中数据贫乏化合物的硅学职业接触带框架。
职业接触限值(OEL)和职业接触带(OEB)为工人健康保护提供了量化基准。如果经验毒理学数据不足以得出 OEL,则通常使用部分毒理学数据和其他相关危害信息来指定 OEB。对于缺乏任何经验性毒理学数据的化学品,目前还没有达成共识的 OEB 分配方法。因此,本研究为数据贫乏的化合物制定了一个 OEB 分配硅学框架。该框架依靠计算工具来评估标准毒理学终点并分配可靠性等级,然后利用可靠性等级来分配全球统一制度(GHS)的危害类别。然后,将危害类别输入美国国家职业安全与健康研究所(NIOSH)的职业接触带工具,为单个终点和整体 OEB 分配带。作为概念验证,评估了五种已确定 OEL 的化合物(即 "已知化合物")。已知化合物被分配到总体 OEB C、D 或 E,其中四种等于或低于基于实际协调的 GHS 类别和既定 OEL 的 OEB,表明使用此框架分配的 OEB 可能具有保护作用。随后,对五种几乎没有实验数据,也没有任何美国机构或共识 OEL 制定组织制定的 OEL 的化合物(即 "未知化合物")进行了评估。得出的结论是,建议的框架可用于为几乎没有毒理学测试数据的化合物指定保护性 OEB。随着更多数据的获得,该化合物可被降低风险,并可分配预防性 OEB(或 OEL)。建议的框架提供了一个实用方法的范例,用于评估数据贫乏的化合物,并表明该框架的结果有望保护工人的健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.50
自引率
5.30%
发文量
72
审稿时长
4 months
期刊介绍: Toxicology & Industrial Health is a journal dedicated to reporting results of basic and applied toxicological research with direct application to industrial/occupational health. Such research includes the fields of genetic and cellular toxicology and risk assessment associated with hazardous wastes and groundwater.
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