Ramez Labib, Ripal Amin, Chris Bartlett, Lisa Hoffman
{"title":"利用综合测试战略(ITSv1)定义的方法和横向读数预测大麻二酚的皮肤致敏性","authors":"Ramez Labib, Ripal Amin, Chris Bartlett, Lisa Hoffman","doi":"10.1016/j.comtox.2023.100297","DOIUrl":null,"url":null,"abstract":"<div><p>Cannabidiol (CBD) is increasingly being used as an ingredient in cosmetics, but to date no pre-clinical studies have been published to address the skin sensitization end point. This case study investigated its skin sensitization potential for use in a face cream application at 0.3 % using Next Generation Risk Assessment (NGRA) framework. Based on chemical structure and <em>in-silico</em> prediction using Derek Nexus, CBD was predicted to be weak sensitizer with a resorcinol alert moiety. <em>In vitro</em> testing was conducted confirming it to be sensitizer, but the New Approach Methodologies (NAM) data could not provide sufficient confidence to determine a point of departure (PoD). Integrated testing strategy (ITS)v1 Defined Approach (DA), adopted in OECD Guideline No. 497, was used for skin sensitization potency categorization. However, ITSv1 DA alone is not used for further refinement of the potency prediction based on EC3 (the estimated concentration that produces a stimulation index of 3 in murine local lymph node assay) values. Therefore, the application of read-across using Derek Nexus derived a PoD derived from the LLNA EC3 of 42 %. This led to a favorable NGRA conclusion and to support use of CBD at 0.3 % in face cream application.</p></div>","PeriodicalId":37651,"journal":{"name":"Computational Toxicology","volume":"29 ","pages":"Article 100297"},"PeriodicalIF":3.1000,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Utilizing integrated testing strategy (ITSv1) defined approach and read across to predict skin sensitization of cannabidiol\",\"authors\":\"Ramez Labib, Ripal Amin, Chris Bartlett, Lisa Hoffman\",\"doi\":\"10.1016/j.comtox.2023.100297\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Cannabidiol (CBD) is increasingly being used as an ingredient in cosmetics, but to date no pre-clinical studies have been published to address the skin sensitization end point. This case study investigated its skin sensitization potential for use in a face cream application at 0.3 % using Next Generation Risk Assessment (NGRA) framework. Based on chemical structure and <em>in-silico</em> prediction using Derek Nexus, CBD was predicted to be weak sensitizer with a resorcinol alert moiety. <em>In vitro</em> testing was conducted confirming it to be sensitizer, but the New Approach Methodologies (NAM) data could not provide sufficient confidence to determine a point of departure (PoD). Integrated testing strategy (ITS)v1 Defined Approach (DA), adopted in OECD Guideline No. 497, was used for skin sensitization potency categorization. However, ITSv1 DA alone is not used for further refinement of the potency prediction based on EC3 (the estimated concentration that produces a stimulation index of 3 in murine local lymph node assay) values. Therefore, the application of read-across using Derek Nexus derived a PoD derived from the LLNA EC3 of 42 %. This led to a favorable NGRA conclusion and to support use of CBD at 0.3 % in face cream application.</p></div>\",\"PeriodicalId\":37651,\"journal\":{\"name\":\"Computational Toxicology\",\"volume\":\"29 \",\"pages\":\"Article 100297\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-12-23\",\"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/S2468111323000385\",\"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/S2468111323000385","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TOXICOLOGY","Score":null,"Total":0}
Utilizing integrated testing strategy (ITSv1) defined approach and read across to predict skin sensitization of cannabidiol
Cannabidiol (CBD) is increasingly being used as an ingredient in cosmetics, but to date no pre-clinical studies have been published to address the skin sensitization end point. This case study investigated its skin sensitization potential for use in a face cream application at 0.3 % using Next Generation Risk Assessment (NGRA) framework. Based on chemical structure and in-silico prediction using Derek Nexus, CBD was predicted to be weak sensitizer with a resorcinol alert moiety. In vitro testing was conducted confirming it to be sensitizer, but the New Approach Methodologies (NAM) data could not provide sufficient confidence to determine a point of departure (PoD). Integrated testing strategy (ITS)v1 Defined Approach (DA), adopted in OECD Guideline No. 497, was used for skin sensitization potency categorization. However, ITSv1 DA alone is not used for further refinement of the potency prediction based on EC3 (the estimated concentration that produces a stimulation index of 3 in murine local lymph node assay) values. Therefore, the application of read-across using Derek Nexus derived a PoD derived from the LLNA EC3 of 42 %. This led to a favorable NGRA conclusion and to support use of CBD at 0.3 % in face cream application.
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