Andrea Gissi , Olga Tcheremenskaia , Cecilia Bossa , Chiara Laura Battistelli , Patience Browne
{"title":"经合组织 (Q)SAR 评估框架:提高计算方法监管普及率的工具","authors":"Andrea Gissi , Olga Tcheremenskaia , Cecilia Bossa , Chiara Laura Battistelli , Patience Browne","doi":"10.1016/j.comtox.2024.100326","DOIUrl":null,"url":null,"abstract":"<div><p>There is international interest in using alternatives to animal testing, including (Q)SARs, in chemical hazard assessments. The regulatory acceptance of alternative methods requires principles for considering the scientific rigour of methods and their results. The OECD (Q)SAR assessment Framework (QAF) was developed as guidance for regulators when considering (Q)SAR models and predictions in chemical evaluation. The QAF builds on existing principles for evaluating models and, learning from the longstanding regulatory experience in assessing (Q)SAR predictions, establishes new principles for evaluating predictions and results from multiple predictions. Assessment elements, identified for all principles lay out criteria for assessing the confidence and uncertainties in (Q)SAR models and predictions, while maintaining the flexibility necessary to adapt to different regulatory contexts and purposes. Using the QAF, assessors can consistently and transparently evaluate and decide on the validity of (Q)SARs, and model developers and users have clear requirements to meet. The publication of the QAF is expected to increase the regulatory use and acceptance of (Q)SARs and may become an example to build<!--> <!-->similar prescriptive frameworks for other new approach methodologies (NAMs). This article provides an overview of the main scientific aspects of the QAF guidance and provides context for how this guidance can promote the use of alternative methods in chemical assessments.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"31 ","pages":"Article 100326"},"PeriodicalIF":3.1000,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2468111324000288/pdfft?md5=33fd8494c056a68ddf66c8e90efb5151&pid=1-s2.0-S2468111324000288-main.pdf","citationCount":"0","resultStr":"{\"title\":\"The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches\",\"authors\":\"Andrea Gissi , Olga Tcheremenskaia , Cecilia Bossa , Chiara Laura Battistelli , Patience Browne\",\"doi\":\"10.1016/j.comtox.2024.100326\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>There is international interest in using alternatives to animal testing, including (Q)SARs, in chemical hazard assessments. The regulatory acceptance of alternative methods requires principles for considering the scientific rigour of methods and their results. The OECD (Q)SAR assessment Framework (QAF) was developed as guidance for regulators when considering (Q)SAR models and predictions in chemical evaluation. The QAF builds on existing principles for evaluating models and, learning from the longstanding regulatory experience in assessing (Q)SAR predictions, establishes new principles for evaluating predictions and results from multiple predictions. Assessment elements, identified for all principles lay out criteria for assessing the confidence and uncertainties in (Q)SAR models and predictions, while maintaining the flexibility necessary to adapt to different regulatory contexts and purposes. Using the QAF, assessors can consistently and transparently evaluate and decide on the validity of (Q)SARs, and model developers and users have clear requirements to meet. The publication of the QAF is expected to increase the regulatory use and acceptance of (Q)SARs and may become an example to build<!--> <!-->similar prescriptive frameworks for other new approach methodologies (NAMs). This article provides an overview of the main scientific aspects of the QAF guidance and provides context for how this guidance can promote the use of alternative methods in chemical assessments.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":\"31 \",\"pages\":\"Article 100326\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-08-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000288/pdfft?md5=33fd8494c056a68ddf66c8e90efb5151&pid=1-s2.0-S2468111324000288-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111324000288\",\"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/S2468111324000288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
The OECD (Q)SAR Assessment Framework: A tool for increasing regulatory uptake of computational approaches
There is international interest in using alternatives to animal testing, including (Q)SARs, in chemical hazard assessments. The regulatory acceptance of alternative methods requires principles for considering the scientific rigour of methods and their results. The OECD (Q)SAR assessment Framework (QAF) was developed as guidance for regulators when considering (Q)SAR models and predictions in chemical evaluation. The QAF builds on existing principles for evaluating models and, learning from the longstanding regulatory experience in assessing (Q)SAR predictions, establishes new principles for evaluating predictions and results from multiple predictions. Assessment elements, identified for all principles lay out criteria for assessing the confidence and uncertainties in (Q)SAR models and predictions, while maintaining the flexibility necessary to adapt to different regulatory contexts and purposes. Using the QAF, assessors can consistently and transparently evaluate and decide on the validity of (Q)SARs, and model developers and users have clear requirements to meet. The publication of the QAF is expected to increase the regulatory use and acceptance of (Q)SARs and may become an example to build similar prescriptive frameworks for other new approach methodologies (NAMs). This article provides an overview of the main scientific aspects of the QAF guidance and provides context for how this guidance can promote the use of alternative methods in chemical assessments.
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