Peer-Reviewed Publication
NPJ Antimicrob Resist2025;3(1):75.September 1, 2025Journal Article
Mitigating antimicrobial resistance by innovative solutions in AI (MARISA): a modified James Lind Alliance analysis.
William J Waldock1, Hannah Thould1, Leonid Chindelevitch2, Nicholas J Croucher2, César de la Fuente3, James J Collins4,5,6, Hutan Ashrafian7, Ara Darzi1
1Institute of Global Health Innovation, Imperial College London, London, UK.
2MRC Centre for Global Infectious Disease Analysis, School of Public Health, Imperial College London, London, UK.
3Machine Biology Group, Institute for Biomedical Informatics, Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
4Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
5Broad Institute of MIT and Harvard, Cambridge, MA, USA.
6Wyss Institute, Harvard, Boston, MA, USA.
7Institute of Global Health Innovation, Imperial College London, London, UK. hutan@ic.ac.uk.
Abstract
Antimicrobial resistance (AMR) is a critical global health threat and artificial intelligence (AI) presents new opportunities for our response. However, research priorities at the AI-AMR intersection remain undefined. This study aimed to identify and prioritise key areas for future investigation. Using a modified James Lind Alliance approach, we conducted semi-structured interviews with eight expe…
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