Leveraging Artificial Intelligence to Combat Antimicrobial Resistance: Spectrum of Application and Impact on Patients’ Care

Antimicrobial resistance (AMR) is recognized as one of the most urgent threats to global health due to its capacity to render once-effective treatments obsolete, prolonging illnesses and increasing mortality rates. The complexity and adaptability of microorganisms, combined with overuse and misuse of antimicrobials, drive the swift progression of resistance. Artificial intelligence (AI), with its capacity for advanced pattern recognition, data integration, and automation, holds the potential to revolutionize AMR research and practice by predicting trends and accelerating novel intervention pathways.

This Research Topic seeks to narrow the persistent gap between the emergence of resistance and the development of viable medical countermeasures. By integrating AI into the full spectrum of AMR research, including the prediction of resistance evolution, discovery of novel antimicrobials, advancements in rapid diagnostics, and the deployment of comprehensive surveillance systems, this Research Topic aspires to deliver actionable insights and frameworks that can be translated into practice, thus reducing mortality and morbidity associated with drug-resistant infections.

We welcome submissions that critically examine the role of AI in tackling AMR from a multidisciplinary perspective. We particularly encourage contributions on (but not limited to):
- Predictive modeling of the evolution and spread of AMR
- AI methods in the discovery and repurposing of antimicrobial agents
- Real-time resistance monitoring using AI-powered surveillance systems
- Development and implementation of rapid, AI-driven diagnostic tools
- Ethical, regulatory, and data privacy considerations in AI-enabled AMR research

This collection aims to foster dialogue across disciplines and inform policy, epidemiology, clinical practice, and technological innovation related to AMR.

Topic Editor Dr. Aarthi Ravikrishnan is the scientific advisor to CELLDZYNE LIFE SCIENCES Pvt. Ltd. The other Topic Editor reports no competing interests related to this Research Topic.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Editorial
• FAIR² Data
• FAIR² DATA Direct Submission
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review

Keywords: AMR, Microbes, Genomics, Pathogen surveillance, Disease control, Artificial Intelligence

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.