AI-Enhanced CRISPR-Cas9 Therapeutics: Advances in Precision, Safety, and Delivery

CRISPR-Cas9 genome editing has transformed biomedical research and is advancing toward clinical translation. The integration of artificial intelligence (AI) offers improved precision in guide RNA design, off-target prediction, and delivery optimization. This review synthesizes recent advances in CRISPR-Cas9 for medical applications, covering core mechanisms, engineered variants, base and prime editors, and therapeutic applications including CAR T-cell and CAR-NK engineering, genetic disorders, infectious diseases, and regenerative medicine. Delivery strategies are evaluated with emphasis on AI-driven optimization. AI applications are highlighted across deep learning architectures for guide RNA design, AI-designed nucleases such as OpenCRISPR-1, structure-guided and AI-assisted design of compact high-fidelity SaCas9 variants, reinforcement learning for pipeline optimization, and roles in CAR T-cell therapy and safety assessment. Safety challenges are examined, including off-target effects, chromosomal rearrangements, immunogenicity, and regulatory concerns. Future directions emphasize multi-scale modeling, explainable AI, clinical validation, and integration with synthetic biology, single-cell sequencing, organoids, and nanomaterials. The convergence of AI and CRISPR-Cas9 holds substantial potential for personalized medicine.

Abstract from PubMed (PMID 42987985). This entry was added automatically by our daily literature monitor because it matches the topics we follow; read the full paper at the original source.