SHEDS-HT: An Integrated Probabilistic Exposure Model for Prioritizing Exposures to Chemicals with Near-Field and Dietary Sources
SHEDS-HT: An Integrated Probabilistic Exposure Model for Prioritizing Exposures to Chemicals with Near-Field and Dietary Sources
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DOI：
10.1021/es502513w
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发表时间：
2014-11-04
影响因子：
11.4
通讯作者：
Oezkaynak, Haluk
中科院分区：
文献类型：
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作者：
Isaacs, Kristin K.;Glen, W. Graham;Oezkaynak, Haluk
美国环境保护署（USEPA）的研究人员正在开发一种基于高通量（HT）的ExpoCast计划下化学品优先级的策略。这些新的建模方法，用于评估化学品的基础上，其潜在的生物相关的人类接触将告知毒性测试和优先级的化学品风险评估。基于概率方法和算法开发的随机人体暴露和剂量模拟模型的多媒体，多途径化学品（SHEDS-MM），一个新的机制建模方法已被开发，以适应高通量（HT）评估的暴露潜力。在这个SHEDS-HT模型中，SHEDS-MM的居住和饮食模块已经在操作上进行了修改，以减少用户负担，输入数据需求和高层模型的运行时间，同时保持影响暴露的关键功能和输入。该模型已在R中实现;建模框架将化学品与消费品类别或食物组（以及暴露情景）联系起来，以预测HT暴露和摄入剂量。最初，SHEDS-HT已应用于与消费品和农业农药相关的2507种有机化学品。这些评估采用了美国环保局最近的数据，以描述各种消费品的使用情况（流行率、频率和幅度）、化学成分和接触情况。在模拟来自近场源的间接暴露时，SHEDS-HT采用了基于逸度的模块来估计室内环境介质中的浓度。浓度估计值，沿着与相关的暴露因素和人类活动数据，然后由模型快速生成近场间接暴露的概率人口分布，通过皮肤。非饮食摄入和吸入途径。还对消费品近场直接暴露的特定途径估计进行了建模。将食物中发现的各种化学品的人群膳食暴露量与相应的特定化学品近场暴露量预测相结合，以得出总体人群暴露量估计值。2507化学品案例研究的估计摄入剂量率（毫克/千克/天）跨越13个数量级。SHEDS-HT成功地再现了较高等级SHEDS-MM针对案例研究农药的途径特异性暴露结果，并产生了显著相关的中位摄入剂量（p
United States Environmental Protection Agency (USEPA) researchers are developing a strategy for high-throughput (HT) exposure-based prioritization of chemicals under the ExpoCast program. These novel modeling approaches for evaluating chemicals based on their potential for biologically relevant human exposures will inform toxicity testing and prioritization for chemical risk assessment. Based on probabilistic methods and algorithms developed for The Stochastic Human Exposure and Dose Simulation Model for Multimedia, Multipathway Chemicals (SHEDS-MM), a new mechanistic modeling approach has been developed to accommodate high-throughput (HT) assessment of exposure potential. In this SHEDS-HT model, the residential and dietary modules of SHEDS-MM have been operationally modified to reduce the user burden, input data demands and run times of the higher-tier model, while maintaining critical features and inputs that influence exposure. The model has been implemented in R; the modeling framework links chemicals to consumer product categories or food groups (and thus exposure scenarios) to predict HT exposures and intake doess. Initially, SHEDS-HT has been applied to 2507 organic chemicals associated with consumer products and agricultural pesticides. These evaluations employ data from recent USEPA efforts to characterize usage (prevalence, frequency and magnitude), chemical composition, and exposure scenarios for a wide range of consumer products. In modeling indirect exposures from near-field sources SHEDS-HT employs a fugacity-based module to estimate concentrations in indoor environmental media. The concentration estimates, along with relevant exposure factors and human activity data, are then used by the model to rapidly generate probablistic population distributions of near-field indirect exposures via dermal. nondietary ingestion, and inhalation pathways. Pathway-specific estimates of near-field direct exposures from consumer products are also modeled. Population dietary exposures for a variety of chemicals found in foods are combined with the corresponding chemical-specific near-field exposure predictions to produce aggregate population exposure estimates. The estimated intake dose rates (mg/kg/day) for the 2507 chemical case-study spanned 13 orders of magnitude. SHEDS-HT successfully reproduced the pathway-specific exposure results of the higher-tier SHEDS-MM for a case-study pesticide and produced median intake doses significantly correlated (p