Surveillance, Detection and Therapeutic Innovation in Antimicrobial Resistance in the Age of Polycrisis: From Genomic and Digital Innovation to One Health Integration

Abstract

Antimicrobial resistance (AMR) surveillance is increasingly strained by interconnected global crises, i.e., pandemics, climate change, armed conflicts, population mobility, and health inequalities, that disrupt healthcare delivery, diagnostic capacity, and laboratory infrastructure. In parallel, artificial intelligence (AI), machine learning, whole-genome sequencing, metagenomics, and digital surveillance offer the potential to shift from reactive reporting to predictive intelligence that anticipates resistance threats, although current implementations remain sector-specific, retrospective, and project-funded. Environmental surveillance, particularly wastewater monitoring coupled with genomic epidemiology, provides early warnings at population and ecosystem levels. The future integration of AI across human, animal, and environmental sectors could enable unified One Health intelligence; no such integrated platform is currently operational. This review focuses primarily on bacterial AMR. It examines how global drivers strain surveillance, how genomic, metagenomic, digital, and AI-enabled technologies reshape AMR detection and prediction, and the emerging non-antibiotic therapeutic landscape, including bacteriophage therapy, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based antimicrobials, antimicrobial peptides, microbiota-directed interventions, nanomedicine, host-directed therapies, photodynamic therapy, and vaccines. It then explores how these innovations can be integrated within a One Health framework to support coordinated global preparedness. Addressing the AMR crisis will require not only technological innovation but also equitable implementation, interdisciplinary collaboration, and resilient systems.