Artificial Intelligence (AI) in Skin Fibroblast Research: Revolutionizing Drug and Cosmetic Development

Skin fibroblasts play a central role in maintaining dermal structure, mediating wound healing, and influencing the outcomes of drug and cosmetic interventions, thereby representing a critical target in dermatological innovation. Despite their importance, the heterogeneity and plasticity of fibroblasts, along with variable patient responses, have presented significant challenges to the development of effective and individualized skin therapies. This review aims to systematically synthesize emerging applications of artificial intelligence (AI) and machine learning (ML) in the discovery, screening, and personalization of drugs and cosmetic products based on human skin fibroblasts. Relevant literature published between ۲۰۱۹ and ۲۰۲۵ was identified through comprehensive searches of PubMed, Google Scholar, and advanced AI-powered tools, prioritizing high-impact studies on AI, ML, and deep learning in skin science. Key themes addressed include the evolution from traditional experimental methods to AI-enabled high-throughput screening, the integration of multi-omics and digital pathology for predictive modeling, and the implementation of personalized skin therapies using advanced data analytics. Remaining limitations relate to data quality, privacy, and translational barriers, underscoring unresolved questions about clinical adoption and equity. These insights highlight AI’s transformative potential for advancing skin health and underscore the need for interdisciplinary collaboration and robust validation in future research and practice.

کلیدواژه ها:

Artificial Intelligence ، Skin Fibroblasts ، Drug Discovery ، Cosmeceuticals ، Personalized Dermatology