Harnessing AI to counteract antimicrobial resistance: A new frontier

Gulumbe, Bashar Haruna; Yusuf, Abbas Bazata; Abdulrakib, Abdulrahim; Liman, Umar Usman

doi:10.21608/mid.2023.250773.1675

Harnessing AI to counteract antimicrobial resistance: A new frontier

Document Type : Mini-review article

Authors

¹ Department of Microbiology, Federal University, Birnin Kebbi, Nigeria

² Department of Biochemistry and Molecular Biology, Faculty of Science, Federal University Birnin Kebbi, Nigeria

10.21608/mid.2023.250773.1675

Abstract

Background: The burgeoning crisis of antimicrobial resistance (AMR) poses a grave threat to global health, necessitating innovative solutions that transcend traditional therapeutic approaches. This piece explores the transformative potential of artificial intelligence (AI) as a multifaceted tool in combating AMR. Utilizing advanced algorithms, AI offers promising avenues for predicting antibiotic resistance patterns, expediting drug discovery, optimizing treatment regimens, and enhancing data mining and surveillance. However, the integration of AI into AMR research is fraught with challenges, including ethical quandaries, data integrity issues, algorithmic opacity, resource limitations, and translational obstacles. Through a comprehensive review of existing literature and a detailed analysis of challenges and strategic recommendations, the piece serves as both an overview and a call to action. It advocates for a multi-disciplinary, collaborative approach to harness the untapped potential of AI in the fight against AMR. As we stand on the cusp of a post-antibiotic era, the paper concludes that the responsible and effective integration of AI could be a paradigm shift in global health, offering a compelling impetus for concerted research efforts in this critical area.

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