The escalating global antimicrobial resistance (AMR) crisis, a significant health threat, was a key focus at ESCMID Global 2026. Research presented by Rasha Elshenawy of the University of Hertfordshire explored how Artificial Intelligence can bolster antimicrobial stewardship (AMS) in hospitals.
Elshenawy's study, conducted across two UK NHS Foundation Trust hospitals, demonstrated AI's utility in predicting prescribing appropriateness, intervention timing, and antimicrobial risk. AI systems achieved 84.7% accuracy in predicting prescribing appropriateness and flagged numerous drug interactions and dosing adjustments requiring clinical attention. These AI-driven improvements remained effective even during pandemic waves, despite increased workloads.
While AI presents a promising avenue for AMR containment, its implementation in low- and middle-income countries (LMICs) faces significant hurdles. Elshenawy highlighted severe gaps related to supply chains, resources, policy, and education. She stressed the need for cost-effectiveness analysis, patient-centered outcomes, sustainable financing, and capacity-building for LMIC-led innovation.
Crucially, Elshenawy emphasized the imperative for responsible AI use, advocating for thorough validation before clinical deployment. "We need to make sure this AI will give appropriate recommendations," she stated, underscoring that AI's significant impact on patient outcomes hinges on hospitals implementing robust testing protocols and careful validation to ensure its accuracy and clinical relevance.