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Role of Artificial Intelligence (AI) in antibiotic resistance

Antimicrobial resistance( AMR) is arising as a implicit trouble to numerous lives worldwide. It’s veritably important to understand and apply effective strategies to Fight the impact of AMR and its mutation from a medical treatment point of view.

The crossroad of artificial intelligence( AI), especially deep literacy/ machine literacy, has led to a new direction in antimicrobial identification. The emergence and spread of antimicrobial resistance( AMR) is a major public health challenge presently faced by the world. AMR originates whenmicro-organisms, similar as bacteria, contagions, fungi, and spongers, come resistant to the medicines that were formerly effective in treating infections caused by thesemicro-organisms. .27 million deaths have occurred each year due to AMR. It’s also important to note that the challenge of antimicrobial resistance is limited not only to bacteria but also to Virus.

Artificial intelligence( AI) is being used to combat antibiotic resistance in a number of ways, including  :-

  • Discovering new antibiotics: AI can be used to screen large libraries of  motes for implicit antibiotic  exertion. This is a  important  briskly and more effective process than traditional  styles, which can take times to identify a single new antibiotic.  
  •  Designing new antibiotics: AI can be used to design new antibiotics with specific  parcels,  similar as targeting antibiotic- resistant bacteria or having smaller side  goods.  
  • Predicting antibiotic resistance: AI can be used to  prognosticate which bacteria are likely to be resistant to antibiotics. This information can be used to target antibiotic treatment more effectively and  help the development of resistance. overuse, which can help to  help the development of resistance.   

AI is a promising new tool in the fight against antibiotic resistance. It has the potential to speed up the discovery of new antibiotics, design more effective antibiotics, and prevent the development of resistance. However, more research is needed to fully explore the potential of AI in this area.

Here are some specific examples of how AI has been used to combat antibiotic resistance:

  • 2021, researchers at the University of California, San Diego used AI to develop a new method for predicting antibiotic resistance. This method is more accurate than traditional methods and can be used to identify bacteria that are likely to be resistant to antibiotics before they are even treated.
  • 2022, researchers at the University of Oxford used AI to design a new antibiotic that is effective against a type of bacteria (Pseudomonas aeruginosa) that is resistant to most existing antibiotics.
  • 2023, researchers at MIT and McMaster University used AI to discover a new antibiotic that can kill a type of bacteria (Acinetobacter baumannii) that is responsible for many drug-resistant infections.

These are just a few examples of the ways that AI is being used to combat antibiotic resistance. As AI technology continues to develop, it is likely that we will see even more innovative and effective uses of AI in this area.

Source :-

  • Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation (Research)
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