Advances in the applications of machine learning for cosmetic formulation development

2026/02/24 by Wen Jiang, Lu Yao, Lingyun Yao +2 · 1 voice
Agricultural and Biological Sciences · Biochemistry, Genetics and Molecular Biology · Medicine · #Sensory Analysis and Statistical Methods #Skin Protection and Aging #melanin and skin pigmentation

paper · doi:10.1007/s11696-026-04696-7

crossref issued 2026/02/24 · crossref published 2026/02/24 · crossref published-online 2026/02/24 · openalex publication_date 2026/02/24 · crossref created 2026/02/24 · openalex created_date 2026/02/25 · crossref published-print 2026/05/01 · crossref deposited 2026/06/30 · crossref indexed 2026/06/30 · openalex updated_date 2026/07/29

Citations

• The SCCS Notes of Guidance for the testing of cosmetic ingredients and their safety evaluation, 11th revision, 30–31 March 2021, SCCS/1628/21
• iSKIN: Integrated application of machine learning and Mondrian conformal prediction to detect skin sensitizers in cosmetic raw materials
• Research progress in the development of 3D skin models and their application to in vitro skin irritation testing
• Basic validation procedures for regression models in QSAR and QSPR studies: theory and application

Discussions

• Machine learning is reshaping cosmetic formulation development, from ingredient screening and QSAR/QSPR modeling to quality control and personalization. This review highlights the opportunities and th [bsky, 0 points, 0 comments]