By: Dale Arasa
11 hours ago

Scientists have used artificial intelligence to discover a new antibiotic drug that can kill a deadly superbug. They created an experimental antibiotic called abaucin to beat Acinetobacter baumannii or A. baumannii. It often infects hospitals, so the antibiotic AI drug could become a significant boon to healthcare facilities around the world.

We often see AI applied to consumer electronics and software. However, AI improves many areas that most people don’t notice. This AI antibiotic discovery is an example of this technology that could save millions of lives.

This groundbreaking proves that AI is more than chatbots and generative programs. So, this article will discuss how researchers used AI to create a drug for an antibiotic-resistant superbug. I will discuss its widespread implications for medical research later.

How did researchers create an antibiotic drug for AI?

Researchers from McMaster University and the Massachusetts Institute of Technology lead this monumental study. They posted their findings on the Nature Chemical Biology website, but the BBC put them in layman’s terms.

The British News said the scientists started by training their AI system. They chose thousands of drugs with known chemical structures and tested them on Acinetobacter baumannii to find out which one could slow or eliminate it.

Then, the researchers unleashed their AI on a list of 6,680 compounds with unknown efficacy. It took an hour and a half to produce a shortlist.

Next, the scientists tested 240 of them in the lab and found nine potential antibiotic treatments. The incredibly powerful antibiotic abaucin was one of them.

Lab tests showed it could heal infected wounds in mice. More importantly, it could kill A. baumannii samples from patients. However, McMaster University’s Dr Jonathan Stokes told BBC correspondent James Gallagher: This is when the work begins.

Researchers have to perfect medicine in the laboratory and perform clinical trials. Dr Stokes predicts the first batch could take until 2030, until it’s ready for prescriptions.

The best thing about this antibiotic medicine for AI is that it only works on A. baumannii. Conversely, other antibiotics kill bacteria indiscriminately, promoting the creation of drug-resistant germs.

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Researchers say that abaucin may lead to fewer side effects. His discovery could help eliminate one of the bacteria that requires antibiotic treatments.

The World Health Organization has included A. baumannii in its list of priority pathogens. This bacterium has innate abilities to resist antibiotics and make other bacteria resistant to drugs.

The Guardian reports that the superbug can live on shared environmental surfaces and equipment for extended periods. As a result, it significantly threatens hospitals.

How does the AI ‚Äč‚Äčantibiotic study affect healthcare research?

The McMaster University website shared an article about its researchers’ latest discovery. He says traditional methods are too time consuming, expensive and have limited scope for developing new treatments against A. baumannii.

The scholarly article also shared the statements of lead researcher Dr. Jonathan Stokes. This work validates the benefits of machine learning in the search for new antibiotics.

Using artificial intelligence, we can rapidly explore vast regions of chemical space, significantly increasing the chances of discovering fundamentally new antibacterial molecules.

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We know that broad-spectrum antibiotics aren’t optimal, and that pathogens have the ability to evolve and adapt to every trick we throw at them.

AI methods present us with the opportunity to greatly increase the rate at which we discover new antibiotics, and we can do it at a reduced cost. This is an important avenue of exploration for new antibiotic drugs.

James J. Collins, a member of Dr. Stokes’ team, says AI approaches to drug discovery are here to stay and will continue to be refined. We know that algorithmic models work. Now it’s a question of broadly adopting these methods to discover new antibiotics more efficiently and less expensively.

Conclusion

AI has helped university researchers create a treatment for a notorious drug-resistant bacteria. As a result, they could eliminate one of the pathogens on WHO’s urgent list.

Dr Jonathan Stokes explained that AI methods could significantly improve drug research. We may soon find new treatments for previously incurable diseases at record speed and at low cost.

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