Diala Haykal, Brigitte Dréno
Oncology is undergoing a profound transformation driven by the convergence of artificial intelligence (AI), RNA-based vaccines, and chimeric antigen receptor T-cell (CAR-T) therapies. Individually, these technologies have advanced cancer diagnosis, treatment, and patient stratification. AI-driven approaches enhance drug discovery, optimize clinical trial design, and enable personalized therapeutic decision-making. RNA vaccines provide a flexible platform for encoding tumor-specific neoantigens, while CAR-T therapies enable targeted immune-mediated tumor cell elimination. Early-phase clinical trials, particularly those combining RNA vaccines with immune checkpoint inhibitors, have demonstrated promising improvements in recurrence-free survival (RFS) and immunogenicity. However, evidence supporting direct combinations of RNA vaccines and CAR-T therapies remains largely preclinical or limited to early-phase investigation and should therefore be interpreted with caution. This review explores how AI facilitates neoantigen discovery, RNA vaccine optimization, and CAR-T cell engineering, and examines the emerging interplay between these modalities. While their integration represents a compelling framework for personalized oncology, significant challenges remain, including clinical validation, scalability, regulatory oversight, and equitable access.