Antimicrobial resistance (AMR) innovations: Phage therapy, antimicrobial peptides, and AI-driven drug discovery

Antimicrobial resistance (AMR) has emerged as one of the most urgent global public health threats, driven by inappropriate antibiotic use, rapid microbial evolution, and limited development of new antimicrobials. Recent innovations are reshaping the AMR mitigation landscape through novel, precision-targeted, and computationally optimized therapeutic strategies. Among these, bacteriophage therapy, antimicrobial peptides (AMPs), and AI-driven drug discovery platforms have garnered significant attention for their ability to overcome limitations of traditional antibiotics. Phage therapy offers host-specific bio control strategies capable of targeting multidrug-resistant (MDR) pathogens, while AMPs provide broad-spectrum antimicrobial activity with low propensity for resistance. Concurrently, advances in artificial intelligence (AI), machine learning, and deep learning have accelerated discovery of novel antibacterial compounds, resistance prediction, and optimization of lead molecules. This review synthesizes recent progress in these three innovation domains, highlights emerging challenges, and evaluates their translational potential in combating AMR on a global scale.