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REVIEW article

Front. Artif. Intell.

Sec. Medicine and Public Health

Volume 8 - 2025 | doi: 10.3389/frai.2025.1660356

This article is part of the Research TopicArtificial Intelligence-based Multimodal Imaging and Multi-omics in Medical ResearchView all 8 articles

Cosmetogenomics Unveiled: A Systemic Review of AI, Genomics, and the Future of Personalized Skincare

Provisionally accepted
DIALA  HAYKALDIALA HAYKAL1*Frédéric  FlamentFrédéric Flament2David  AmarDavid Amar2Hugues  CartierHugues Cartier3Arianne Shadi  KouroshArianne Shadi Kourosh4Dong Hun  LeeDong Hun Lee5Christopher  Rowland PayneChristopher Rowland Payne6
  • 1Centre Médical Laser Palaiseau, Palaiseau, France
  • 2L'Oréal Research and Innovation, Clichy, France
  • 3Centre Médical Saint Jean, Arras, France
  • 4Associate Professor of Dermatology, Harvard Medical School, Boston, United States
  • 5Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
  • 6The London Clinic, London, United Kingdom

The final, formatted version of the article will be published soon.

Abstract Introduction The integration of genomics, proteomics, and artificial intelligence (AI) is shaping the approach to personalized skincare and aesthetic dermatology, moving from generalized protocols toward precision-based interventions. Objective To systematically review the emerging field of cosmetogenomics, focusing on how AI and multi-omics technologies are enabling personalized dermatologic treatments, and to critically evaluate the strength, scope, and limitations of current evidence. Methods We conducted a systematic review in accordance with PRISMA 2020 guidelines. PubMed, Scopus, and Embase databases were searched for articles from January 2012 to April 2025 using Boolean combinations of terms including ["cosmetogenomics" OR "AI in dermatology" OR "personalized skincare" OR "multi-omics dermatology"] AND ["SNP" OR "genomics" OR "proteomics"]. Eligible studies included peer-reviewed clinical or ex vivo research involving human subjects and reporting measurable dermatologic outcomes related to genomics, single nucleotide polymorphisms (SNPs), AI tools, or proteomics. Study quality was assessed using the JAMA Users' Guides to the Medical Literature quality scheme. Results From 403 screened articles, 74 met inclusion criteria. Of these, 22 were randomized controlled trials (RCTs, Level I evidence), 35 observational studies (Level II), and 17 conceptual or expert opinion papers (Level III). AI and genomics were found to enhance skincare personalization by identifying SNPs associated with collagen degradation, oxidative stress, and inflammation. AI-powered platforms integrate these insights with imaging, lifestyle data, and digital twins to optimize interventions ranging from topical regimens to laser and injectable treatments. However, a significant proportion of studies were exploratory, with limited geographic diversity and underrepresentation of darker skin phototypes. No quantitative synthesis (meta-analysis) was performed due to heterogeneity in outcome measures, though hydration, elasticity, and pigmentation outcomes may permit such analysis in future work. Conclusion AI-driven cosmetogenomics is advancing dermatology into a predictive, personalized era. While the evidence base is expanding, clinical translation requires stronger validation, ethical safeguards, and regulatory oversight. This field holds significant promise for enhancing treatment efficacy, patient satisfaction, and long-term skin

Keywords: Genomics, Proteomics, predictive analysis, precision medicine, artificial intelligence, Skin Aging

Received: 05 Jul 2025; Accepted: 30 Sep 2025.

Copyright: © 2025 HAYKAL, Flament, Amar, Cartier, Kourosh, Lee and Rowland Payne. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence: DIALA HAYKAL, docteur.haykal@gmail.com

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