Artificial Intelligence in Cosmetic Formulation: Predictive Modeling for Safety, Tolerability, and Regulatory Perspectives
Antonio Di Guardo, Federica Trovato, Carmen Cantisani, Annunziata Dattola, Steven Paul Nisticò, Giovanni Pellacani, Alessia Paganelli
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.