Artificial intelligence and CRISPR-based approaches for targeted delivery of bacteriophages

The rapid emergence of Multidrug-Resistant (MDR) bacteria has increased interest in bacteriophage therapy as a promising alternative to conventional antibiotics. Bacteriophages are host-specific bacterial viruses that selectively infect and destroy pathogenic bacterial strains. Recent developments in artificial intelligence (AI) and Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based technologies offer innovative approaches to address challenges such as narrow host range, rapid immune clearance, phage instability, bacterial resistance, and biofilm penetration barriers. By integrating AI-driven structural modeling with CRISPR-mediated genome editing, these methods enable the targeted delivery of bacteriophages. This review focuses on next-generation approaches that combine AI-assisted phage identification, host prediction, and therapeutic optimization with CRISPR-based genome engineering for targeted phage delivery and improved safety. Overall, this review highlights the potential of AI- and CRISPR-assisted phage therapy for the treatment of MDR bacterial infections. It will also provide a systematic overview of bacteriophage biology, life cycle, and mechanisms of action, while focusing on the influence of phage morphology on therapeutic performance, recent advances, current clinical, preclinical studies, and future perspectives. Although phage therapy shows considerable potential against MDR bacterial infections, several challenges related to delivery, safety, and clinical translation remain. The integration of AI and CRISPR technologies has the potential to improve phage selection, targeting specificity, and therapeutic performance. However, continued research, clinical validation, and regulatory development will be essential for translating these advances into practical antimicrobial therapies.