“RapidTox”: A decision-support workflow to inform rapid toxicity and human health assessment

IF 2.9 Q2 TOXICOLOGY
Jason C. Lambert , Jason Brown , Hui Gong , Curtis Kilburn , Jan Krysa , Brad Kuntzelman , Janet Lee , April Luke , Joshua Powell , Asif Rashid , James Renner , Risa Sayre , Jyothi Tumkur , Carl F. Valone , Chelsea Weitekamp , Russell S. Thomas
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引用次数: 0

Abstract

Regulatory bodies such as the U.S. Environmental Protection Agency are consistently faced with decisions pertaining to potential human health impacts of a diverse landscape of chemicals encountered in exposure matrices such as water, air, and soil. For legacy chemicals or those currently in commerce, decision contexts may range from emergency response to disasters where evaluation of potential threats to human health occurs on the order of hours to days, up to site- or media-specific assessment and remediation over the course of months to years. In addition, screening and prioritization of new chemicals or emerging contaminants represents an ever-present focus area for the regulatory community. A common theme across these overarching decision contexts is the need for assembling and integrating human health relevant data such as toxicity values and associated effects information. Various activities ranging from screening and prioritization to human health risk assessment of chemicals have historically been time and resource intensive, often requiring that practitioners consult and review a variety of disparate data streams to inform a given decision. In addition, many environmental chemicals are ‘data-poor’, lacking sufficient hazard data or toxicity values applicable to a given exposure scenario. In response, decision-based workflows have been developed and deployed in the RapidTox online platform wherein available toxicity values, hazard/effects data, physicochemical properties, and new approach methods-based data (e.g., read-across; cell-based bioactivity) have been assembled into data delivery modules. To date, the user interface design and expertly scoped content have been integrated in ‘screening human health assessment’ or ‘emergency response’ workflows to support decision-making.

Abstract Image

“ RapidTox ”:为快速毒性和人体健康评估提供信息的决策支持工作流
美国环境保护署等监管机构一直面临着与水、空气和土壤等接触基质中所遇到的各种化学品对人类健康的潜在影响有关的决定。对于遗留化学品或目前在商业上的化学品,决策背景可能从紧急反应到灾害,其中对人类健康的潜在威胁的评估需要数小时到数天的时间,到针对特定场所或媒介的评估和补救需要数月到数年的时间。此外,新化学品或新出现污染物的筛选和优先级是监管界始终关注的重点领域。在这些总体决策背景下的一个共同主题是需要收集和整合与人类健康有关的数据,如毒性值和相关影响信息。从筛选和确定优先次序到化学品的人类健康风险评估,各种活动历来都是时间和资源密集型的,往往要求从业人员咨询和审查各种不同的数据流,以便为给定的决定提供信息。此外,许多环境化学品“缺乏数据”,缺乏足够的危害数据或适用于特定暴露情景的毒性值。作为回应,RapidTox在线平台开发并部署了基于决策的工作流程,其中可用的毒性值、危害/效应数据、物理化学特性和基于新方法的数据(例如,读取、基于细胞的生物活性)已组装成数据传递模块。迄今为止,用户界面设计和专业界定的内容已纳入“筛选人体健康评估”或“应急反应”工作流程,以支持决策。
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来源期刊
Computational Toxicology
Computational Toxicology Computer Science-Computer Science Applications
CiteScore
5.50
自引率
0.00%
发文量
53
审稿时长
56 days
期刊介绍: Computational Toxicology is an international journal publishing computational approaches that assist in the toxicological evaluation of new and existing chemical substances assisting in their safety assessment. -All effects relating to human health and environmental toxicity and fate -Prediction of toxicity, metabolism, fate and physico-chemical properties -The development of models from read-across, (Q)SARs, PBPK, QIVIVE, Multi-Scale Models -Big Data in toxicology: integration, management, analysis -Implementation of models through AOPs, IATA, TTC -Regulatory acceptance of models: evaluation, verification and validation -From metals, to small organic molecules to nanoparticles -Pharmaceuticals, pesticides, foods, cosmetics, fine chemicals -Bringing together the views of industry, regulators, academia, NGOs
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