AI model creating new antibiotics to help battle superbugs | Health & Fitness

Steve Johnson

By Sharin Hussain via SWNS

A new AI model designed to create new antibiotics could save billions of people from dangerous superbug bacteria.

Researchers have invented a new generative artificial intelligence model that can design billions of new antibiotic molecules that are inexpensive and easy to build in labs.

The team from McMaster University and Stanford University developed a new generative AI model called SyntheMol.

This can design new antibiotics to stop the spread of Acinetobacter baumannii, identified by the World Health Organisation as one of the world’s most dangerous antibiotic-resistant bacteria.

A. baumannii can cause pneumonia, meningitis and infect wounds, all of which can lead to death. Researchers say few treatment options remain.

Lead author, assistant professor Jonathan Stokes at Stanford University said: “Antibiotics are a unique medicine. As soon as we begin to employ them in the clinic, we’re starting a timer before the drugs become ineffective because bacteria evolve quickly to resist them.

McMaster University’s Jonathan Stokes is one of the researchers who developed a new generative AI model. (Georgia Kirkos/McMaster University via SWNS)

“We need a robust pipeline of antibiotics and we need to discover them quickly and inexpensively. That’s where the artificial intelligence plays a crucial role.”

The study, published in the journal Nature Machine Intelligence, developed the generative model to access tens of billions of promising molecules quickly and cheaply.

The team analyzed 132,000 molecular fragments, which fit together like Lego pieces but are all very different in nature.

They cross-referenced these molecular fragments with a set of 13 chemical reactions, enabling them to identify 30 billion two-way combinations of fragments to design new molecules with the most promising antibacterial properties.

Each of the molecules designed by this model was in turn fed through another AI model trained to predict toxicity.

The process yielded six molecules that display potent non-toxic antibacterial activity against A. baumannii.

Professor James Zou concluded: “SyntheMol not only designs novel molecules that are promising drug candidates, but it also generates the recipe for how to make each new molecule.

“Generating such recipes is a new approach and a game changer because chemists do not know how to make AI-designed molecules.”

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