{"title":"A developmental and reproductive toxicity adverse outcome pathway network to support safety assessments","authors":"","doi":"10.1016/j.comtox.2024.100325","DOIUrl":null,"url":null,"abstract":"<div><p>Developmental and reproductive toxicity (DART) are key regulatory endpoints for the protection of human health. DART assessments require large numbers of animals, are expensive and often run at late stages of drug development. Therefore, new approach methodologies (NAMs) are being developed to transition away from animal testing. These NAMs (including <em>in silico</em> models) can be used to screen for DART hazards at the early stages of compound development and may in the future be used for regulatory DART assessments. Due to the implications of a mischaracterised developmental toxicant, both high confidence and understanding of the assessments made using NAMs will be required; it is likely that multiple NAMs will be needed in order to replace the current animal-based assessments. Adverse outcome pathways (AOPs) serve as a pragmatic tool for documenting mechanisms of toxicity. NAMs can be associated to key events (KEs) along an AOP, providing context to their outputs, and therefore increasing confidence in their use. It is likely that networks of pathways will be required for a specific toxicity endpoint in order to confidently apply an AOP-based approach to safety assessments. An insufficient number of DART AOPs are currently described within the public domain; therefore, using a literature-based approach, a network consisting of 340 KEs (including 68 MIEs) was developed. This foundation of pathways was made chemically aware through the association of relevant assays, data and expert rule-based structural alerts to appropriate KEs. The use of the network as a hazard screening tool was assessed, and the application of this to aid an ICH S5 workflow investigated. The knowledge captured within this AOP network can also guide the further development and use of DART-relevant NAMs and integrated approaches to testing and assessments (IATAs).</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-08-08","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/S2468111324000276","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
Abstract
Developmental and reproductive toxicity (DART) are key regulatory endpoints for the protection of human health. DART assessments require large numbers of animals, are expensive and often run at late stages of drug development. Therefore, new approach methodologies (NAMs) are being developed to transition away from animal testing. These NAMs (including in silico models) can be used to screen for DART hazards at the early stages of compound development and may in the future be used for regulatory DART assessments. Due to the implications of a mischaracterised developmental toxicant, both high confidence and understanding of the assessments made using NAMs will be required; it is likely that multiple NAMs will be needed in order to replace the current animal-based assessments. Adverse outcome pathways (AOPs) serve as a pragmatic tool for documenting mechanisms of toxicity. NAMs can be associated to key events (KEs) along an AOP, providing context to their outputs, and therefore increasing confidence in their use. It is likely that networks of pathways will be required for a specific toxicity endpoint in order to confidently apply an AOP-based approach to safety assessments. An insufficient number of DART AOPs are currently described within the public domain; therefore, using a literature-based approach, a network consisting of 340 KEs (including 68 MIEs) was developed. This foundation of pathways was made chemically aware through the association of relevant assays, data and expert rule-based structural alerts to appropriate KEs. The use of the network as a hazard screening tool was assessed, and the application of this to aid an ICH S5 workflow investigated. The knowledge captured within this AOP network can also guide the further development and use of DART-relevant NAMs and integrated approaches to testing and assessments (IATAs).
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