AI Blueprint for Global Antimicrobial Resistance

Researchers at the University of Liverpool have developed a framework for artificial intelligence (AI) to improve antimicrobial use and infection care, thereby contributing to the global antimicrobial resistance (AMR) crisis.

Their blueprint is published in The Lancet Digital Health journal.

Lead author Dr. Alex Howard said, “Different forms of AI bring many opportunities to improve health care. AIs can harness complex evolving data, inform and augment human actions, and learn from outcomes. The global public health challenge of AMR needs large-scale optimization of antimicrobial use and wider infection care, which can be enabled by carefully constructed AIs.”

The researchers emphasized that, while AIs are becoming more effective and resilient, healthcare systems continue to be difficult locations for their deployment—and that there is an implementation gap between the promise of AIs and their application in patient and population care.

With this in mind, the group has developed an adaptive implementation and maintenance framework for AIs as a learning system to improve antibiotic use and infection care. This section discusses AMR problem identification, law/regulation, organizational support, and data processing in connection to AMR-targeted AI creation, evaluation, maintenance, and scalability.

“Bridging the implementation gap between AI innovation and tackling AMR presents technical, regulatory, organizational, and human challenges. Learning systems built on integrated dataflows, governance, and technologies have the potential to close this gap. Translational expertise between AMR and AI fields will be essential to appropriately design, maintain, normalize, and globalize AMR-AIs in infection care and realize the potential for AIs to support clinician-driven AMR minimization strategies,” Dr. Howard said.

As part of the Centres for Antibiotic Optimization Network program, which brings together world-leading multidisciplinary expertise in infection and health informatics, the work articulates a vision of how data science may be exploited to combat antibiotic resistance.

For more information: Alex Howard et al, Antimicrobial learning systems: an implementation blueprint for artificial intelligence to tackle antimicrobial resistance, The Lancet Digital Health (2023). DOI: 10.1016/S2589-7500(23)00221-2