This review examines challenges in CAR-T therapies and how AI innovations improve outcomes, suggesting future directions.
As chimeric antigen receptor (CAR)‐T cell therapy has expanded rapidly to meet the growing global cancer burden; many challenges have emerged as a critical factor influencing its efficacy. However, due to the complicated mechanisms of CAR‐T cells, human interference alone was insufficient to optimize the outcomes. In parallel, artificial intelligence (AI) has begun to intersect with CAR‐T cells, offering novel computational interferences that can refine therapeutic mechanisms. The literature is still lacking a comprehensive investigation that merges CAR‐T cell mechanistic biology and limitations with the advancing abilities of AI to meet these barriers. This review provides an overview of the mechanistic foundations of CAR‐T cell. It also investigates the various challenges facing the current CAR‐T therapies including toxicity, resistance, and accessibility issues. On this basis, we examined the way AI‐based innovations are being utilized to optimize the CAR‐T engineering and clinical management. Finally, we examined clinical studies and case studies incorporating AI elements, emphasizing both therapeutic mechanisms and outcomes of the study. By integrating mechanistic biology with computational innovation, this review provides a unified unique perspective that can guide the development of safer and more effective CAR‐T therapies.
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Adly et al. (2026) studied this question.
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