AI in Drug Discovery for Antimicrobial Resistance: Combating the Silent Pandemic

Abstract

Antimicrobial resistance (AMR) is a serious threat to global health and could render efforts aimed at keeping antibiotics working and killing millions of people each year ineffective. The presence of these weaknesses and our deficiencies in predicting potential drug targets opens new machine-learning fronts to the field of drug discovery, and they will likely deliver novel antibiotic drug leads (as well as repurposing of existing drugs). AI combating AMR: This study applies to algorithmic identification of effective compounds, prediction of resistance patterns, and computational drug repurposing. The results show that AI can do a lot to bring the discovery process and spending to an optimum state while improving specificity in combating AMR. We can integrate AI into drug discovery to slow the silent AMR pandemic.