Use of Artificial Intelligence against the Superbug

Context: Scientists from the United States and Canada have found a new antibiotic abaucin powerful enough to kill a superbug Acinetobacter baumannii using artificial intelligence(AI).

What are Superbugs?

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  • Superbugs are bacteria that are resistant to several types of antibiotics. 
  • Acinetobacter baumannii: The World Health Organization (WHO) identified this bacterium as one of the world’s most dangerous antibiotic-resistant bacteria and difficult to eradicate.
  • It can cause pneumonia, meningitis and infect wounds, all of which can lead to death.
  • It is usually found in hospital settings, where it can survive on surfaces for long periods.
  • Each year these drug-resistant bacteria infect more than 2 million people in the US and kill at least 23,000, according to the US Centers for Disease Control and Prevention (CDC).

How do bacteria become resistant to drugs?

  • Antibiotics are medicines used to prevent and treat bacterial infections. Antibiotic resistance occurs when bacteria change in response that is genetic changes or acquires resistance genes to the use of these medicines. This ultimately threatens the ability of medicines to treat common infectious diseases.
  • There are several ways in which bacteria can acquire resistance like overuse and misuse of antibiotics, gene transfer, mutation, etc.
  • Microbial resistance to antibiotics has made it harder to treat infections such as pneumonia, tuberculosis (TB), blood poisoning (septicaemia), and several food-borne diseases
  • AMR also imposes a huge health cost on the patient in the form of longer hospitalisation, health complications, and delayed recovery.

How did researchers use AI against the superbug?

  1. Narrowing down the right antibacterial chemicals against bacteria can be a long, difficult process. This is where algorithms come in because the concept of AI is based on the process of machines being given large amounts of data and training themselves on identifying patterns and solutions based on them.
  2. The researchers tested about 7,500 different chemical compounds on A. baumannii which was cultivated in a lab dish to determine which ones could slow the bacterium’s development.
  3. Then they fed the structure of each molecule into the machine-learning model. They also told the model whether each structure could prevent bacterial growth or not. This allowed the algorithm to learn chemical features associated with growth inhibition.
  4. Once the model was trained, the researchers used it to analyse the compounds. This analysis took less than two hours and yielded a few hundred results. 
  5. The researchers chose a few compounds with structures that were different from those of existing antibiotics for the experiment.

Nine antibiotics were discovered as a result of those investigations, one of which was extremely strong and successful at eliminating A. baumannii. Abaucin is the name given to the antibiotic.

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