A Quantitative Source-to-Outcome Case Study To Demonstrate the Integration of Human Health and Ecological End Points Using the Aggregate Exposure Pathway and Adverse Outcome Pathway Frameworks

不良结局途径 毒物动力学 背景(考古学) 结果(博弈论) 暴露评估 人类健康 构造(python库) 环境科学 毒物动力学 计算机科学 生态学 计算生物学 生物 生物信息学 医学 环境卫生 数学 古生物学 数理经济学 药代动力学 程序设计语言
作者
David E. Hines,Rory B. Conolly,Annie M. Jarabek
出处
期刊:Environmental Science & Technology [American Chemical Society]
卷期号:53 (18): 11002-11012 被引量:11
标识
DOI:10.1021/acs.est.9b04639
摘要

Exposure to environmental contaminants can lead to adverse outcomes in both human and nonhuman receptors. The Aggregate Exposure Pathway (AEP) and Adverse Outcome Pathway (AOP) frameworks can mechanistically inform cumulative risk assessment for human health and ecological end points by linking together environmental transport and transformation, external exposure, toxicokinetics, and toxicodynamics. This work presents a case study of a hypothetical contaminated site to demonstrate a quantitative approach for implementing the AEP framework and linking this framework to AOPs. We construct an AEP transport and transformation model and then quantify external exposure pathways for humans, fishes, and small herbivorous mammals at the hypothetical site. A Monte Carlo approach was used to address parameter variability. Source apportionment was quantified for each species, and published pharmacokinetic models were used to estimate internal target site exposure from external exposures. Published dose–response data for a multispecies AOP network were used to interpret AEP results in the context of species-specific effects. This work demonstrates (1) the construction, analysis, and application of a quantitative AEP model, (2) the utility of AEPs for organizing mechanistic exposure data and highlighting data gaps, and (3) the advantages provided by a source-to-outcome construct for leveraging exposure data and to aid transparency regarding assumptions.
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