Kevin M. Crofton , Arianna Bassan , Mamta Behl , Yaroslav G. Chushak , Ellen Fritsche , Jeffery M. Gearhart , Mary Sue Marty , Moiz Mumtaz , Manuela Pavan , Patricia Ruiz , Magdalini Sachana , Rajamani Selvam , Timothy J. Shafer , Lidiya Stavitskaya , David T. Szabo , Steven T. Szabo , Raymond R. Tice , Dan Wilson , David Woolley , Glenn J. Myatt
{"title":"集成计算机方法的神经毒性危害评估框架的现状和未来方向","authors":"Kevin M. Crofton , Arianna Bassan , Mamta Behl , Yaroslav G. Chushak , Ellen Fritsche , Jeffery M. Gearhart , Mary Sue Marty , Moiz Mumtaz , Manuela Pavan , Patricia Ruiz , Magdalini Sachana , Rajamani Selvam , Timothy J. Shafer , Lidiya Stavitskaya , David T. Szabo , Steven T. Szabo , Raymond R. Tice , Dan Wilson , David Woolley , Glenn J. Myatt","doi":"10.1016/j.comtox.2022.100223","DOIUrl":null,"url":null,"abstract":"<div><p>Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including <em>in silico</em> approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. <em>In silico</em> approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of <em>in silico</em> methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"22 ","pages":"Article 100223"},"PeriodicalIF":3.1000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches\",\"authors\":\"Kevin M. Crofton , Arianna Bassan , Mamta Behl , Yaroslav G. Chushak , Ellen Fritsche , Jeffery M. Gearhart , Mary Sue Marty , Moiz Mumtaz , Manuela Pavan , Patricia Ruiz , Magdalini Sachana , Rajamani Selvam , Timothy J. Shafer , Lidiya Stavitskaya , David T. Szabo , Steven T. Szabo , Raymond R. Tice , Dan Wilson , David Woolley , Glenn J. Myatt\",\"doi\":\"10.1016/j.comtox.2022.100223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including <em>in silico</em> approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. <em>In silico</em> approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of <em>in silico</em> methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":\"22 \",\"pages\":\"Article 100223\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Toxicology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2468111322000111\",\"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/S2468111322000111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Current status and future directions for a neurotoxicity hazard assessment framework that integrates in silico approaches
Neurotoxicology is the study of adverse effects on the structure or function of the developing or mature adult nervous system following exposure to chemical, biological, or physical agents. The development of more informative alternative methods to assess developmental (DNT) and adult (NT) neurotoxicity induced by xenobiotics is critically needed. The use of such alternative methods including in silico approaches that predict DNT or NT from chemical structure (e.g., statistical-based and expert rule-based systems) is ideally based on a comprehensive understanding of the relevant biological mechanisms. This paper discusses known mechanisms alongside the current state of the art in DNT/NT testing. In silico approaches available today that support the assessment of neurotoxicity based on knowledge of chemical structure are reviewed, and a conceptual framework for the integration of in silico methods with experimental information is presented. Establishing this framework is essential for the development of protocols, namely standardized approaches, to ensure that assessments of NT and DNT based on chemical structures are generated in a transparent, consistent, and defendable manner.
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