Artificial Intelligence for Understanding Mechanisms of Antimicrobial Resistance and Antimicrobial Discovery
Yashaswi Dutta Gupta, Suman Bhandary · 2024
Antimicrobial resistance (AMR) presents an escalating global health crisis, characterized by bacteria's growing resistance to conventional antibiotics. Understanding AMR mechanisms and developing innovative antimicrobials demand harnessing powerful tools such as artificial intelligence (AI) as potent solutions for this crisis. The chapter's primary objective is to underscore AI's battle against AMR via a twofold analysis—by highlighting AI's predictive potential in deciphering factors that foster AMR proliferation and outlining emerging prospects like AI-empowered diagnostic tools and AI-optimized personalized treatment strategies. We aim to critically assess diverse AI methodologies in demonstrating their efficacy in deciphering extensive bacterial genetic datasets. Along with AI's predictive powers for estimating the likelihood of drug resistance, it enables the identification of previously unidentified targets for antimicrobial action. This chapter meticulously merges an exploration of AI techniques with their practical deployment, furnishing a panoramic view of the field's present landscape and underlining AI's burgeoning role in combating AMR. In addition to assessing the current state, we also aim to review and identify the future areas of potential research in this field. Ultimately, this chapter accentuates AI's capacity as a cornerstone in ongoing efforts to mitigate AMR's impact, transcending boundaries and catalyzing a transformative shift in healthcare approaches.