Steven Kane, Dan Newman, David J. Ponting, Edward Rosser, Robert Thomas, Jonathan D. Vessey, Samuel J. Webb, William H.J. Wood
{"title":"开发和验证可对毒性和效力做出决策的跨读工作流程:亚硝胺案例研究","authors":"Steven Kane, Dan Newman, David J. Ponting, Edward Rosser, Robert Thomas, Jonathan D. Vessey, Samuel J. Webb, William H.J. Wood","doi":"10.1016/j.comtox.2024.100300","DOIUrl":null,"url":null,"abstract":"<div><p>To reach conclusions during chemical safety assessments, risk assessors need to ensure sufficient information is present to satisfy the decision criteria. This often requires data to be generated and, in some cases, insufficient knowledge is present, or it is not feasible to generate new data through experiments. Read-across is a powerful technique to fill such data gaps, however the expert-driven process can be time intensive and subjective in nature resulting in variation of approach. To overcome these barriers a prototype software application has been developed by Lhasa Limited to support decision making about the toxicity and potency of chemicals using a read-across approach. The application supports a workflow which allows the user to gather data and knowledge about a chemical of interest and possible read-across candidates. Relevant information is then presented that enables the user to decide if read-across can be performed and, if so, which analogue or category can be considered the most appropriate. Data and knowledge about the toxicity of a compound and potential analogues include assay and metabolism data, toxicophore identification and its local similarity, physico-chemical and pharmacokinetic properties and observed and predicted metabolic profile. The utility of the approach is demonstrated with case studies using <em>N</em>-nitrosamine compounds, where the conclusions from using the workflow supported by the software are concordant with the evidence base. The components of the workflow have been further validated by demonstrating that conclusions are significantly better than would be expect from the distribution of data in test sets. The approach taken demonstrates how software implementing intuitive workflows that guide experts during read-across can support decisions and how validation of the methods can increase confidence in the overall approach.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"29 ","pages":"Article 100300"},"PeriodicalIF":3.1000,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing and validating read-across workflows that enable decision making for toxicity and potency: Case studies with N-nitrosamines\",\"authors\":\"Steven Kane, Dan Newman, David J. Ponting, Edward Rosser, Robert Thomas, Jonathan D. Vessey, Samuel J. Webb, William H.J. Wood\",\"doi\":\"10.1016/j.comtox.2024.100300\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>To reach conclusions during chemical safety assessments, risk assessors need to ensure sufficient information is present to satisfy the decision criteria. This often requires data to be generated and, in some cases, insufficient knowledge is present, or it is not feasible to generate new data through experiments. Read-across is a powerful technique to fill such data gaps, however the expert-driven process can be time intensive and subjective in nature resulting in variation of approach. To overcome these barriers a prototype software application has been developed by Lhasa Limited to support decision making about the toxicity and potency of chemicals using a read-across approach. The application supports a workflow which allows the user to gather data and knowledge about a chemical of interest and possible read-across candidates. Relevant information is then presented that enables the user to decide if read-across can be performed and, if so, which analogue or category can be considered the most appropriate. Data and knowledge about the toxicity of a compound and potential analogues include assay and metabolism data, toxicophore identification and its local similarity, physico-chemical and pharmacokinetic properties and observed and predicted metabolic profile. The utility of the approach is demonstrated with case studies using <em>N</em>-nitrosamine compounds, where the conclusions from using the workflow supported by the software are concordant with the evidence base. The components of the workflow have been further validated by demonstrating that conclusions are significantly better than would be expect from the distribution of data in test sets. The approach taken demonstrates how software implementing intuitive workflows that guide experts during read-across can support decisions and how validation of the methods can increase confidence in the overall approach.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":\"29 \",\"pages\":\"Article 100300\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-01-29\",\"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/S2468111324000021\",\"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/S2468111324000021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Developing and validating read-across workflows that enable decision making for toxicity and potency: Case studies with N-nitrosamines
To reach conclusions during chemical safety assessments, risk assessors need to ensure sufficient information is present to satisfy the decision criteria. This often requires data to be generated and, in some cases, insufficient knowledge is present, or it is not feasible to generate new data through experiments. Read-across is a powerful technique to fill such data gaps, however the expert-driven process can be time intensive and subjective in nature resulting in variation of approach. To overcome these barriers a prototype software application has been developed by Lhasa Limited to support decision making about the toxicity and potency of chemicals using a read-across approach. The application supports a workflow which allows the user to gather data and knowledge about a chemical of interest and possible read-across candidates. Relevant information is then presented that enables the user to decide if read-across can be performed and, if so, which analogue or category can be considered the most appropriate. Data and knowledge about the toxicity of a compound and potential analogues include assay and metabolism data, toxicophore identification and its local similarity, physico-chemical and pharmacokinetic properties and observed and predicted metabolic profile. The utility of the approach is demonstrated with case studies using N-nitrosamine compounds, where the conclusions from using the workflow supported by the software are concordant with the evidence base. The components of the workflow have been further validated by demonstrating that conclusions are significantly better than would be expect from the distribution of data in test sets. The approach taken demonstrates how software implementing intuitive workflows that guide experts during read-across can support decisions and how validation of the methods can increase confidence in the overall approach.
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