{"title":"人工智能和机器学习在化妆品和个人护理配方设计关键材料中的应用","authors":"Hai Xin, Akashdeep Singh Virk , Sabitoj Singh Virk , Foluso Akin-Ige , Samiul Amin","doi":"10.1016/j.cocis.2024.101847","DOIUrl":null,"url":null,"abstract":"<div><p>The applications of artificial intelligence (AI) and machine learning (ML) approaches are rising in formula optimization, ingredient selection, performance prediction, and structure-properties analysis in formulated product development for the cosmetic industry. The present review aims to give a critical discussion regarding how AI and ML assist in the development of key component materials used in cosmetics and formulated products including surfactants, polymers, fragrances, preservatives, and hydrogels. Hydrogels are reviewed here as a promising candidate to open a new frontier for the future cosmetics and personal care product industry, due to their excellent biocompatibility, excellent drug-delivering ability, and high water content. We also discuss the use of ML for formula optimization and hazardous ingredient detection such as sensitizing and allergic components. All the research publications reviewed in the present work are accomplished in the past 4 years to reflect the current research trends and progress in ML-assisted advancement in cosmetics and personal care product development.</p></div>","PeriodicalId":293,"journal":{"name":"Current Opinion in Colloid & Interface Science","volume":"73 ","pages":"Article 101847"},"PeriodicalIF":7.9000,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applications of artificial intelligence and machine learning on critical materials used in cosmetics and personal care formulation design\",\"authors\":\"Hai Xin, Akashdeep Singh Virk , Sabitoj Singh Virk , Foluso Akin-Ige , Samiul Amin\",\"doi\":\"10.1016/j.cocis.2024.101847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The applications of artificial intelligence (AI) and machine learning (ML) approaches are rising in formula optimization, ingredient selection, performance prediction, and structure-properties analysis in formulated product development for the cosmetic industry. The present review aims to give a critical discussion regarding how AI and ML assist in the development of key component materials used in cosmetics and formulated products including surfactants, polymers, fragrances, preservatives, and hydrogels. Hydrogels are reviewed here as a promising candidate to open a new frontier for the future cosmetics and personal care product industry, due to their excellent biocompatibility, excellent drug-delivering ability, and high water content. We also discuss the use of ML for formula optimization and hazardous ingredient detection such as sensitizing and allergic components. All the research publications reviewed in the present work are accomplished in the past 4 years to reflect the current research trends and progress in ML-assisted advancement in cosmetics and personal care product development.</p></div>\",\"PeriodicalId\":293,\"journal\":{\"name\":\"Current Opinion in Colloid & Interface Science\",\"volume\":\"73 \",\"pages\":\"Article 101847\"},\"PeriodicalIF\":7.9000,\"publicationDate\":\"2024-08-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Opinion in Colloid & Interface Science\",\"FirstCategoryId\":\"92\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1359029424000657\",\"RegionNum\":2,\"RegionCategory\":\"化学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CHEMISTRY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Opinion in Colloid & Interface Science","FirstCategoryId":"92","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1359029424000657","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
摘要
在化妆品行业的配方产品开发中,人工智能(AI)和机器学习(ML)方法在配方优化、成分选择、性能预测和结构特性分析方面的应用日益增多。本综述旨在深入探讨人工智能和机器学习如何帮助开发化妆品和配方产品中使用的关键成分材料,包括表面活性剂、聚合物、香料、防腐剂和水凝胶。由于水凝胶具有良好的生物相容性、出色的给药能力和高含水量,因此有望为未来的化妆品和个人护理产品行业开辟新的领域。我们还讨论了如何利用 ML 进行配方优化和有害成分检测(如致敏成分和过敏成分)。本论文中评述的所有研究出版物都是在过去 4 年中完成的,反映了当前在 ML 辅助化妆品和个人护理产品开发方面的研究趋势和进展。
Applications of artificial intelligence and machine learning on critical materials used in cosmetics and personal care formulation design
The applications of artificial intelligence (AI) and machine learning (ML) approaches are rising in formula optimization, ingredient selection, performance prediction, and structure-properties analysis in formulated product development for the cosmetic industry. The present review aims to give a critical discussion regarding how AI and ML assist in the development of key component materials used in cosmetics and formulated products including surfactants, polymers, fragrances, preservatives, and hydrogels. Hydrogels are reviewed here as a promising candidate to open a new frontier for the future cosmetics and personal care product industry, due to their excellent biocompatibility, excellent drug-delivering ability, and high water content. We also discuss the use of ML for formula optimization and hazardous ingredient detection such as sensitizing and allergic components. All the research publications reviewed in the present work are accomplished in the past 4 years to reflect the current research trends and progress in ML-assisted advancement in cosmetics and personal care product development.
期刊介绍:
Current Opinion in Colloid and Interface Science (COCIS) is an international journal that focuses on the molecular and nanoscopic aspects of colloidal systems and interfaces in various scientific and technological fields. These include materials science, biologically-relevant systems, energy and environmental technologies, and industrial applications.
Unlike primary journals, COCIS primarily serves as a guide for researchers, helping them navigate through the vast landscape of recently published literature. It critically analyzes the state of the art, identifies bottlenecks and unsolved issues, and proposes future developments.
Moreover, COCIS emphasizes certain areas and papers that are considered particularly interesting and significant by the Editors and Section Editors. Its goal is to provide valuable insights and updates to the research community in these specialized areas.