分子信息学平台在支持下一代风险评估方面的作用

IF 3.1 Q2 TOXICOLOGY
Chihae Yang , James F Rathman , Bruno Bienfait , Matthew Burbank , Ann Detroyer , Steven J. Enoch , James W. Firman , Steve Gutsell , Nicola J. Hewitt , Bryan Hobocienski , Gerry Kenna , Judith C. Madden , Tomasz Magdziarz , Jörg Marusczyk , Aleksandra Mostrag-Szlichtyng , Christopher-Tilman Krueger , Cathy Lester , Catherine Mahoney , Abdulkarim Najjar , Gladys Ouedraogo , Mark T.D. Cronin
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引用次数: 1

摘要

化学信息学已经成功地通过各种监管计划应用于安全性评估,这些计划接受来自数据库的信息以及包括计算方法在内的预测方法。一个例子是欧盟化妆品法规,为此,欧洲化妆品(CE)的非动物方法研究活动由长期科学战略(LRSS)计划管理。愿景是利用现有非动物方法的机制方面以及新方法方法(NAMs)来证明可以使用硅和体外数据的组合来进行化学品的安全性评估。为此,ChemTunes•ToxGPS®已被采用作为安全评估系统的基础,并提供了一个整合数据和知识的平台,并实现了与化妆品行业相关的毒性预测和安全评估。ChemTunes•ToxGPS®平台提供基于实验和预测的化学、生物和安全数据,以及交互式/可定制的跨读取平台。安全评估工作流程使用户能够编制合格的数据源,量化其可靠性,并使用基于决策理论的证据权重方法将它们组合起来。通过一个用例,该平台通过毒理学关注阈值(TTC)、计算机预测(QSAR和结构规则)和总体安全性定量读取(qRAX)评估的工作流程对紫苏进行安全评估,展示了该平台的强大功能。该系统将知识中心内的工作流程数字化,在这个人工智能时代利用先进的硅工具。下一代风险评估(NGRA)系统的进一步设计是由工作组和国际监管实体之间的互动科学指导的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The role of a molecular informatics platform to support next generation risk assessment

Chemoinformatics has been successfully employed in safety assessment through various regulatory programs for which information from databases, as well as predictive methodologies including computational methods, are accepted. One example is the European Union Cosmetics Products Regulations, for which Cosmetics Europe (CE) research activities in non-animal methods have been managed by the Long Range Science Strategy (LRSS) program. The vision is to use mechanistic aspects of existing non-animal methods, as well as New Approach Methodologies (NAMs), to demonstrate that safety assessment of chemicals can be performed using a combination of in silico and in vitro data. To this end, ChemTunes•ToxGPS® has been adopted as the foundation of the safety assessment system and provides a platform to integrate data and knowledge, and enable toxicity predictions and safety assessments, relevant to cosmetics industries. The ChemTunes•ToxGPS® platform provides chemical, biological, and safety data based both on experiments and predictions, and an interactive/customizable read-across platform. The safety assessment workflow enables users to compile qualified data sources, quantify their reliabilities, and combine them using a weight of evidence approach based on decision theory. The power of this platform was demonstrated through a use case to perform a safety assessment for Perilla frutescens through the workflows of threshold of toxicological concern (TTC), in silico predictions (QSAR and structural rules) and quantitative read-across (qRAX) assessment for overall safety. The system digitalizes workflows within a knowledge hub, exploiting advanced in silico tools in this age of artificial intelligence. The further design of the system for next generation risk assessment (NGRA) is scientifically guided by interactions between the workgroup and international regulatory entities.

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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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