Artificial intelligence and infectious diseases: tackling antimicrobial resistance, from personalised care to antibiotic discovery
2
Issued Date
2025-01-01
Resource Type
ISSN
14733099
eISSN
14744457
Scopus ID
2-s2.0-105018111417
Pubmed ID
40972630
Journal Title
Lancet Infectious Diseases
Rights Holder(s)
SCOPUS
Bibliographic Citation
Lancet Infectious Diseases (2025)
Suggested Citation
Howard A., Reza N., Green P.L., Yin M., Duffy E., Mwandumba H.C., Gerada A., Hope W. Artificial intelligence and infectious diseases: tackling antimicrobial resistance, from personalised care to antibiotic discovery. Lancet Infectious Diseases (2025). doi:10.1016/S1473-3099(25)00313-5 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/112614
Title
Artificial intelligence and infectious diseases: tackling antimicrobial resistance, from personalised care to antibiotic discovery
Corresponding Author(s)
Other Contributor(s)
Abstract
Antimicrobial resistance (AMR) is an intractable problem that has the potential to significantly limit advances in human health. Recently, the UN General Assembly (UNGA) High-Level Statement on AMR defined targets for addressing the impact of resistance on human, animal, and environmental health. For human health, the discovery and development of new antibiotics, antimicrobial stewardship programmes, antimicrobial surveillance, and infection control and prevention are all key areas. Artificial intelligence (AI) is ideally placed to help achieve the UNGA targets via its role in revealing patterns in data that are clinically indiscernible, and using that information to build clinical decision support systems. However, significant barriers remain in terms of necessary infrastructure, know-how, and the implementation of AI approaches. In this Series paper, we consider the potential applications of AI in combatting the AMR problem through drug discovery and development, antimicrobial stewardship, diagnostics, and surveillance, and their use in public health. We then discuss the technical, infrastructure, regulatory, ethical, and policy challenges that affect these domains.