Artificial intelligence in combating antimicrobial resistance

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Review Article

Author Details : Hatim Abdullah Natto, Ammar Abdul Razzak Mahmood, Sriram Thiruvengadam, Rajkumar Krishnan Vasanthi, Desh Nidhi Singh*

Volume : 10, Issue : 3, Year : 2024

Article Page : 189-195

https://doi.org/10.18231/j.ijmmtd.2024.034

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Abstract

Antimicrobial resistance (AMR) occurs when microorganisms, acquire genetic changes resistant to antimicrobial drugs, including antibiotics. Conventional techniques for combating AMR are expensive and time consuming, but Artificial intelligence (AI) is currently being developed that can rapidly scan through extensive chemical libraries and forecast possible antibacterial substances. The use of AI in medical research has significant promise, particularly in addressing multidrug-resistant (MDR) infections to battle AMR. Algorithms of AI monitors antibiotic usage, occurrences of diseases, and trends of resistance, thus influencing the development of novel drugs. Through AI, researchers can rapidly identify potential new drugs that could be effective against antibiotic-resistant bacteria, saving valuable time in the development process. By analyzing vast amounts of data, AI algorithms can also help to predict future trends in antibiotic resistance, allowing for proactive measures to be taken. With the ability to analyze data at a rapid pace, AI is revolutionizing the way researchers approach drug development, health risks and disease prevention. As technology continues to advance, the impact of AI in combating antimicrobial resistance becomes more significant. Overall, the integration of AI in medical research shows great potential in the ongoing battle against antimicrobial resistance. This review describes the application of AI to identify AMR markers, diagnosis in AMR, small molecule antibiotic development and also emphasizes emerging research domains, such as AMR detection and novel drug development, that contribute to the management of AMR.
 

Keywords: Antimicrobial Resistance, AI to identify AMR markers, Artificial intelligence, Deep Learning, Machine Language

How to cite : Natto H A, Mahmood A A R, Thiruvengadam S, Vasanthi R K, Singh D N, Artificial intelligence in combating antimicrobial resistance. IP Int J Med Microbiol Trop Dis 2024;10(3):189-195

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