Advantages and limitations of large language models for antibiotic prescribing and antimicrobial stewardship
- PMID: 40016394
- PMCID: PMC11868396
- DOI: 10.1038/s44259-025-00084-5
Advantages and limitations of large language models for antibiotic prescribing and antimicrobial stewardship
Abstract
Antibiotic prescribing requires balancing optimal treatment for patients with reducing antimicrobial resistance. There is a lack of standardization in research on using large language models (LLMs) for supporting antibiotic prescribing, necessitating more efforts to identify biases and misinformation in their outputs. Educating future medical professionals on these aspects is crucial for ensuring the proper use of LLMs for supporting antibiotic prescribing, providing a deeper understanding of their strengths and limitations.
© 2025. The Author(s).
Conflict of interest statement
Competing interests: Outside the submitted work, Matteo Bassetti has received funding for scientific advisory boards, travel, and speaker honoraria from Cidara, Gilead, Menarini, MSD, Mundipharma, Pfizer, and Shionogi. Outside the submitted work, Daniele Roberto Giacobbe reports investigator-initiated grants from Pfizer, Shionogi, BioMérieux, Menarini, Tillotts Pharma, and Gilead Italia, travel support from Pfizer, and speaker/advisor fees from Pfizer, Menarini, BioMérieux, Advanz Pharma, and Tillotts Pharma. Alberto Malva was previously an employee of GlaxoSmithKline and is the founder of MedQuestio, an LLM-based support tool for Italian general practitioners. The other authors have no conflicts of interest to disclose.
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