香料吸入风险评估的化学品分组工作流程评估:选定含呋喃的化学品作为案例研究

IF 3.1 Q2 TOXICOLOGY Computational Toxicology Pub Date : 2023-05-01 DOI:10.1016/j.comtox.2023.100269
Amanda N. Buerger , Andrey Massarsky , Anthony Russell , Nicole Zoghby , Carole Hirn , Daniel Mucs , Irene Baskerville-Abraham , Andrew Maier
{"title":"香料吸入风险评估的化学品分组工作流程评估:选定含呋喃的化学品作为案例研究","authors":"Amanda N. Buerger ,&nbsp;Andrey Massarsky ,&nbsp;Anthony Russell ,&nbsp;Nicole Zoghby ,&nbsp;Carole Hirn ,&nbsp;Daniel Mucs ,&nbsp;Irene Baskerville-Abraham ,&nbsp;Andrew Maier","doi":"10.1016/j.comtox.2023.100269","DOIUrl":null,"url":null,"abstract":"<div><p><span><span>Read-across and chemical grouping approaches are increasingly utilized in risk assessment and regulatory submissions. The European Food Safety Authority (EFSA) has established Chemical Group (CG) 14, which contains furfuryl and furan derivatives both with and without side-chain substituents; however, the rationale for this grouping is not available based on current EFSA documentation. Therefore, this study aimed to identify the chemicals belonging to CG14, evaluate the constituent chemicals for metabolic, biological, and toxicological properties via clustering tools, and apply existing chemical grouping workflows for identifying representative chemicals for this group to support testing strategies. Membership to CG14 was difficult to identify, and varied by EFSA source (e.g., published reports, OpenFoodTox database). Based on predictions from the Organisation for Economic Co-operation and Development (OECD) </span>Quantitative Structure Activity Relationship (QSAR) Toolbox, ChemACE, SMARTCyp, and WhichCyp, as well as data extracted from the U.S. Environmental Protection Agency’s (EPA’s) Toxicity Forecaster (ToxCast) on CompTox Chemicals Dashboard and the European Chemicals Agency (ECHA) Dossier, no suitable metabolic, toxicological, structural, or mechanistic </span>clustering method was identified for CG14. Biological effect data were too sparse to refine the chemical subgroupings within CG14 with confidence based on existing read-across principles for chemical grouping. This paucity of data limits the development of a tiered testing strategy in which more complete testing would be conducted for selected representative CG14 compounds only. Therefore, efforts to generate key pieces of data (e.g., mode of action [MOA], metabolism) for chemical grouping and read-across are needed to apply this workflow to EFSA CG14.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluation of chemical grouping workflows for flavor inhalation risk assessment: Selected furan moiety-containing chemicals as a case study\",\"authors\":\"Amanda N. Buerger ,&nbsp;Andrey Massarsky ,&nbsp;Anthony Russell ,&nbsp;Nicole Zoghby ,&nbsp;Carole Hirn ,&nbsp;Daniel Mucs ,&nbsp;Irene Baskerville-Abraham ,&nbsp;Andrew Maier\",\"doi\":\"10.1016/j.comtox.2023.100269\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span><span>Read-across and chemical grouping approaches are increasingly utilized in risk assessment and regulatory submissions. The European Food Safety Authority (EFSA) has established Chemical Group (CG) 14, which contains furfuryl and furan derivatives both with and without side-chain substituents; however, the rationale for this grouping is not available based on current EFSA documentation. Therefore, this study aimed to identify the chemicals belonging to CG14, evaluate the constituent chemicals for metabolic, biological, and toxicological properties via clustering tools, and apply existing chemical grouping workflows for identifying representative chemicals for this group to support testing strategies. Membership to CG14 was difficult to identify, and varied by EFSA source (e.g., published reports, OpenFoodTox database). Based on predictions from the Organisation for Economic Co-operation and Development (OECD) </span>Quantitative Structure Activity Relationship (QSAR) Toolbox, ChemACE, SMARTCyp, and WhichCyp, as well as data extracted from the U.S. Environmental Protection Agency’s (EPA’s) Toxicity Forecaster (ToxCast) on CompTox Chemicals Dashboard and the European Chemicals Agency (ECHA) Dossier, no suitable metabolic, toxicological, structural, or mechanistic </span>clustering method was identified for CG14. Biological effect data were too sparse to refine the chemical subgroupings within CG14 with confidence based on existing read-across principles for chemical grouping. This paucity of data limits the development of a tiered testing strategy in which more complete testing would be conducted for selected representative CG14 compounds only. Therefore, efforts to generate key pieces of data (e.g., mode of action [MOA], metabolism) for chemical grouping and read-across are needed to apply this workflow to EFSA CG14.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111323000105\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"TOXICOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Toxicology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468111323000105","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

跨读和化学分组方法越来越多地用于风险评估和监管提交。欧洲食品安全局(EFSA)建立了化学组(CG) 14,其中包含糠酰和呋喃衍生物,有或没有侧链取代基;然而,根据目前的EFSA文件,这种分组的基本原理是不可用的。因此,本研究旨在识别属于CG14的化学物质,通过聚类工具评估组成化学物质的代谢、生物学和毒理学特性,并应用现有的化学分组工作流程来识别该组的代表性化学物质,以支持测试策略。CG14的成员很难确定,并且因EFSA来源(例如,已发表的报告,OpenFoodTox数据库)而异。根据经济合作与发展组织(OECD)定量结构活性关系(QSAR)工具箱、ChemACE、SMARTCyp和哪个cyp的预测,以及从美国环境保护署(EPA)的毒性预测器(ToxCast)在CompTox化学品仪表板和欧洲化学品管理局(ECHA)档案中提取的数据,没有确定适合CG14的代谢、毒理学、结构或机械聚类方法。生物效应数据过于稀疏,无法基于现有的化学分组读取原则自信地细化CG14内的化学亚组。这种数据的缺乏限制了分层检测策略的发展,其中仅对选定的具有代表性的CG14化合物进行更完整的检测。因此,需要努力生成用于化学分组和读取的关键数据片段(例如,作用模式[MOA],代谢),以便将该工作流应用于EFSA CG14。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Evaluation of chemical grouping workflows for flavor inhalation risk assessment: Selected furan moiety-containing chemicals as a case study

Read-across and chemical grouping approaches are increasingly utilized in risk assessment and regulatory submissions. The European Food Safety Authority (EFSA) has established Chemical Group (CG) 14, which contains furfuryl and furan derivatives both with and without side-chain substituents; however, the rationale for this grouping is not available based on current EFSA documentation. Therefore, this study aimed to identify the chemicals belonging to CG14, evaluate the constituent chemicals for metabolic, biological, and toxicological properties via clustering tools, and apply existing chemical grouping workflows for identifying representative chemicals for this group to support testing strategies. Membership to CG14 was difficult to identify, and varied by EFSA source (e.g., published reports, OpenFoodTox database). Based on predictions from the Organisation for Economic Co-operation and Development (OECD) Quantitative Structure Activity Relationship (QSAR) Toolbox, ChemACE, SMARTCyp, and WhichCyp, as well as data extracted from the U.S. Environmental Protection Agency’s (EPA’s) Toxicity Forecaster (ToxCast) on CompTox Chemicals Dashboard and the European Chemicals Agency (ECHA) Dossier, no suitable metabolic, toxicological, structural, or mechanistic clustering method was identified for CG14. Biological effect data were too sparse to refine the chemical subgroupings within CG14 with confidence based on existing read-across principles for chemical grouping. This paucity of data limits the development of a tiered testing strategy in which more complete testing would be conducted for selected representative CG14 compounds only. Therefore, efforts to generate key pieces of data (e.g., mode of action [MOA], metabolism) for chemical grouping and read-across are needed to apply this workflow to EFSA CG14.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
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
期刊最新文献
Evaluation of QSAR models for tissue-specific predictive toxicology and risk assessment of military-relevant chemical exposures: A systematic review From model performance to decision support – The rise of computational toxicology in chemical safety assessments Development of chemical categories for per- and polyfluoroalkyl substances (PFAS) and the proof-of-concept approach to the identification of potential candidates for tiered toxicological testing and human health assessment The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches A developmental and reproductive toxicity adverse outcome pathway network to support safety assessments
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1