Canadian researchers use AI to find a possible treatment for bacteria superbug

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Researchers have discovered a promising treatment for an antibiotic-resistant superbug — with the help of artificial intelligence.

Acinetobacter baumannii is a hospital-acquired pathogen that's commonly found on surfaces in clinical settings. It can cause diseases such as pneumonia, meningitis and sepsis.

According to the World Health Organization, A. baumannii is a critical threat to patients whose care requires devices such as ventilators, due in large part to its resistance against most antibiotics.

"It's remarkably challenging [to tackle]," said Jonathan Stokes, an assistant professor at McMaster University, in Hamilton, Ont., who led the research.

"When we go to search for new antibiotics, it necessitates that we start looking for chemicals, antibiotics that have brand new structures and brand new functions. You know, we have to develop a fundamentally new treatment," he told The Current's Matt Galloway.

Usually, this involves testing hundreds of thousands of chemicals to see which ones work best against the disease. But Stokes says "that's remarkably laborious and time-consuming and expensive."

That's why Stokes and the rest of the team, which included scientists at the Massachusetts Institute of Technology, turned to AI for assistance.

"Ideally, by leveraging these artificial intelligence algorithms, they can look at these chemicals much more rapidly," he said. "And by looking at a broad array of chemicals very rapidly, they can help us prioritize which experiments to run in the laboratory."

Stokes and his team published their findings in the journal Nature Chemical Biology on Thursday.

Before the AI can find a chemical that could kill A. baumannii, Stokes and his team trained it by feeding it data on bacteria-killing chemicals and chemical structures "associated with the antibacterial activity that we want," he said.

"We physically tested in the laboratory about 7,500 chemicals, looking at which ones inhibited the growth of Acinetobacter and which ones did not," he said. 

Once the AI model was trained, the team could then show it new chemicals it had never seen before. It could then predict which of those chemicals it thought were antibacterial and which ones it thought weren't.

Eventually, the AI discovered a new antibacterial compound they named abaucin. Further laboratory experiments found that it can treat A. baumannii-infected wounds in mice.