Artificial Intelligence in Cosmetic Formulation: Predictive Modeling for Safety, Tolerability, and Regulatory Perspectives

Artificial intelligence (AI) and machine learning (ML) are increasingly transforming the landscape of cosmetic formulation, enabling the development of safer, more effective, and personalized products. This article explores how AI-driven predictive modeling is applied across various components of cosmetic products, including surfactants, polymers, fragrances, preservatives, antioxidants, and prebiotics. These technologies are employed to forecast critical properties such as texture, stability, and shelf-life, optimizing both product performance and user experience. The integration of computational toxicology and ML algorithms also allows for early prediction of skin sensitization risks, including the likelihood of adverse events such as allergic contact dermatitis. Furthermore, AI models can support efficacy assessment, bridging formulation science with dermatological outcomes. The article also addresses the ethical, regulatory, and safety challenges associated with AI in cosmetic science, underlining the need for transparency, accountability, and harmonized standards. The potential of AI to reshape dermocosmetic innovation is vast, but it must be approached with robust oversight and a commitment to user well-being.

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Publication Details

Journal
Cosmetics
Published
2025-07-24
DOI
https://doi.org/10.3390/cosmetics12040157
Citations
7
Primary Topic
Safe Handling of Antineoplastic Drugs
Type
article
Field-Weighted Citation Impact
40.41
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article

Artificial Intelligence in Cosmetic Formulation: Predictive Modeling for Safety, Tolerability, and Regulatory Perspectives

Giovanni Pellacani, Carmen Cantisani, Annunziata Dattola, Federica Trovato et al.
7 citations
Cosmetics
Safe Handling of Antineoplastic Drugs
40.41
article

Artificial Intelligence in Cosmetic Formulation: Predictive Modeling for Safety, Tolerability, and Regulatory Perspectives

Giovanni Pellacani, Carmen Cantisani, Annunziata Dattola, Federica Trovato, Antonio Di Guardo, Alessia Paganelli, Steven Paul Nisticò
article en
7 citations

Abstract

Artificial intelligence (AI) and machine learning (ML) are increasingly transforming the landscape of cosmetic formulation, enabling the development of safer, more effective, and personalized products. This article explores how AI-driven predictive modeling is applied across various components of cosmetic products, including surfactants, polymers, fragrances, preservatives, antioxidants, and prebiotics. These technologies are employed to forecast critical properties such as texture, stability, and shelf-life, optimizing both product performance and user experience. The integration of computational toxicology and ML algorithms also allows for early prediction of skin sensitization risks, including the likelihood of adverse events such as allergic contact dermatitis. Furthermore, AI models can support efficacy assessment, bridging formulation science with dermatological outcomes. The article also addresses the ethical, regulatory, and safety challenges associated with AI in cosmetic science, underlining the need for transparency, accountability, and harmonized standards. The potential of AI to reshape dermocosmetic innovation is vast, but it must be approached with robust oversight and a commitment to user well-being.

CosmeticsVol. 12(4)
Istituti di Ricovero e Cura a Carattere Scientifico (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 0%
Safe Handling of Antineoplastic Drugs
40.41
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Artificial Intelligence in Cosmetic Formulation: Predictive Modeling for Safety, Tolerability, and Regulatory Perspectives — Giovanni Pellacani, Carmen Cantisani, et al. · Cosmetics (2025) | TGRS Research Map | TGRS