Suppr超能文献

支持风险评估的总体暴露途径

Aggregate Exposure Pathways in Support of Risk Assessment.

作者信息

Tan Yu-Mei, Leonard Jeremy A, Edwards Stephen, Teeguarden Justin, Paini Alicia, Egeghy Peter

机构信息

National Exposure Research Laboratory, U.S. Environmental Protection Agency, Durham, North Carolina 27709, United States.

Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37831, United States.

出版信息

Curr Opin Toxicol. 2018 Jun;9:8-13. doi: 10.1016/j.cotox.2018.03.006. Epub 2018 Mar 29.

Abstract

Over time, risk assessment has shifted from establishing relationships between exposure to a single chemical and a resulting adverse health outcome, to evaluation of multiple chemicals and disease outcomes simultaneously. As a result, there is an increasing need to better understand the complex mechanisms that influence risk of chemical and non-chemical stressors, beginning at their source and ending at a biological endpoint relevant to human or ecosystem health risk assessment. Just as the Adverse Outcome Pathway (AOP) framework has emerged as a means of providing insight into mechanism-based toxicity, the exposure science community has seen the recent introduction of the Aggregate Exposure Pathway (AEP) framework. AEPs aid in making exposure data applicable to the FAIR (i.e., findable, accessible, interoperable, and reusable) principle, especially by (1) organizing continuous flow of disjointed exposure information;(2) identifying data gaps, to focus resources on acquiring the most relevant data; (3) optimizing use and repurposing of existing exposure data; and (4) facilitating interoperability among predictive models. Herein, we discuss integration of the AOP and AEP frameworks and how such integration can improve confidence in both traditional and cumulative risk assessment approaches.

摘要

随着时间的推移,风险评估已从确定单一化学物质暴露与由此产生的不良健康结果之间的关系,转变为同时评估多种化学物质和疾病结果。因此,越来越需要更好地理解影响化学和非化学应激源风险的复杂机制,从其源头开始,到与人类或生态系统健康风险评估相关的生物学终点结束。正如不良结局途径(AOP)框架已成为一种深入了解基于机制的毒性的手段一样,暴露科学界最近也引入了累积暴露途径(AEP)框架。AEP有助于使暴露数据符合FAIR(即可查找、可访问、可互操作和可重用)原则,特别是通过(1)组织不连贯的暴露信息的连续流动;(2)识别数据缺口,以便将资源集中于获取最相关的数据;(3)优化现有暴露数据的使用和重新利用;以及(4)促进预测模型之间的互操作性。在此,我们讨论AOP和AEP框架的整合,以及这种整合如何提高对传统和累积风险评估方法的信心。

相似文献

1
Aggregate Exposure Pathways in Support of Risk Assessment.支持风险评估的总体暴露途径
Curr Opin Toxicol. 2018 Jun;9:8-13. doi: 10.1016/j.cotox.2018.03.006. Epub 2018 Mar 29.

引用本文的文献

6
Public data sources to support systems toxicology applications.支持系统毒理学应用的公共数据源。
Curr Opin Toxicol. 2019 Aug;16:17-24. doi: 10.1016/j.cotox.2019.03.002. Epub 2019 Mar 11.
8
Evolving Science and Practice of Risk Assessment.风险评估的科学与实践的发展。
Risk Anal. 2021 Apr;41(4):571-583. doi: 10.1111/risa.13647. Epub 2020 Dec 8.

本文引用的文献

3
Modeling Exposure in the Tox21 in Vitro Bioassays.Tox21体外生物测定中的暴露建模
Chem Res Toxicol. 2017 May 15;30(5):1197-1208. doi: 10.1021/acs.chemrestox.7b00023. Epub 2017 Apr 24.
4
The virtual cell based assay: Current status and future perspectives.基于虚拟细胞的检测法:现状与未来展望。
Toxicol In Vitro. 2017 Dec;45(Pt 2):258-267. doi: 10.1016/j.tiv.2017.01.009. Epub 2017 Jan 18.
5
A framework for cumulative risk assessment in the 21st century.21 世纪累积风险评估框架。
Crit Rev Toxicol. 2017 Feb;47(2):85-97. doi: 10.1080/10408444.2016.1211618. Epub 2016 Aug 11.
6
Integrated Approaches to Testing and Assessment.测试与评估的综合方法。
Adv Exp Med Biol. 2016;856:317-342. doi: 10.1007/978-3-319-33826-2_13.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验