AI Summary
The content highlights a new generative artificial intelligence model called SyntheMol that can design billions of new antibiotic molecules, focusing on stopping the spread of antibiotic-resistant bacteria like Acinetobacter baumannii. The ability to rapidly and inexpensively discover new antibiotics is crucial in addressing the urgent need for effective drugs in the fight against drug-resistant bacteria.
Researchers at McMaster University and Stanford University have invented a new generative artificial intelligence model which can design billions of new antibiotic molecules that are inexpensive and easy to build in the laboratory.
The worldwide spread of drug-resistant bacteria has created an urgent need for new antibiotics, but even modern AI methods are limited at isolating promising chemical compounds, especially when researchers must also find ways to manufacture these new AI-guided drugs and test them in the lab.
In a new study, published today in the journal Nature Machine Intelligence, researchers report they have developed a new generative AI model called SyntheMol, which can design new antibiotics to stop the spread of Acinetobacter baumannii, which the World Health Organization has identified as one of the world’s most dangerous antibiotic-resistant bacteria.
Notoriously difficult to eradicate, A. baumannii can cause pneumonia, meningitis and infect wounds, all of which can lead to death. Researchers say few treatment options remain.
“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,” says Jonathan Stokes, lead author on the paper and an assistant professor in McMaster’s Department of Biomedicine & Biochemistry, who conducted the work with James Zou, an associate professor of biomedical data science at Stanford University.
“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,” he says.
Researchers developed the generative