AI-enabled Engineering of Nanoparticles for Skin Cancer Therapy: A Mini‑Review and Practical Roadmap

Artificial intelligence (AI) and machine learning (ML) are accelerating the design, optimization, and translation of nanoparticle (NP) therapeutics. For skin cancer — where localized delivery, photothermal/photodynamic therapy (PTT/PDT), and intralesional immunomodulation are clinically promising — AI-driven workflows reduce trial-and-error, speed up discovery via active learning and self-driving labs, and enable predictive models for formulation and biological performance. This mini-review synthesizes recent advances in AI-assisted NP engineering relevant to skin cancer, highlights representative case studies, discusses challenges and regulatory considerations, and provides a practical roadmap and checklist for researchers seeking to publish or translate AI-designed nanotherapeutics.