An artificial intelligence platform to simulate chemistry? UC San Diego scientists have created a new tool in the fight against cancer.

A team of researchers at UCSD have developed a machine learning algorithm that simulates the chemistry involved in the earliest phases of drug discovery, according to a UCSD Health press release.

The AI platform – called POLYGON – could streamline and shorten the usually-lengthy process and lead to novel treatments, as explained in the team’s paper, published May 6 in Nature Communications. 

The researchers used the new tool to synthesize 32 new drug candidates for cancer.

“A few years ago, AI was a dirty word in the pharmaceutical industry, but now the trend is definitely the opposite, with biotech startups finding it difficult to raise funds without addressing AI in their business plan,” said senior author Trey Ideker, professor in UCSD’s School of Medicine and adjunct professor of bioengineering and computer science at UCSD’s Jacobs School of Engineering.

“AI-guided drug discovery has become a very active area in industry, but unlike the methods being developed in companies, we’re making our technology open source and accessible to anybody who wants to use it,” Ideker said in the press materials.

POLYGON is unique among AI tools for drug discovery in that it can identify molecules with multiple targets, while existing drug discovery protocols currently prioritize single target therapies.

Multi-target drugs mean the potential to deliver the same benefits as combination therapy, in which several different drugs are used together to treat cancer, but with fewer side effects.

“It takes many years and millions of dollars to find and develop a new drug, especially if we’re talking about one with multiple targets.” Ideker said. “The rare few multi-target drugs we do have were discovered largely by chance, but this new technology could help take chance out of the equation and kickstart a new generation of precision medicine.”

Once candidate drugs are identified with POLYGON, the scientists’ job is far from over, Ideker cautioned, as “you still need to do all the other chemistry it takes to refine those options into a single, effective treatment.”

 “We can’t and shouldn’t try to eliminate human expertise from the drug discovery pipeline, but what we can do is shorten a few steps of the process.”