• In a Friday interview with CNBC's Jim Cramer, Recursion Pharmaceuticals CEO Chris Gibson discussed how his company is using artificial intelligence and machine learning to create new drugs.
• Recursion Pharmaceuticals is a clinical-stage biotech company that received a $50 million investment from Nvidia last summer.

In a Friday interview with CNBC's Jim Cramer, Recursion Pharmaceuticals CEO Chris Gibson discussed how his company is using artificial intelligence and machine learning to make the process of developing drugs faster and less expensive.

Recursion Pharmaceuticals is a clinical-stage biotech company that received a $50 million investment from Nvidia last summer. Gibson said Recursion is using this new technology to generate petabytes of data and then analyze it to "find new relationships across biology and chemistry" and create medicine, especially for rare diseases.

"I think with clinical trials, there's still going to be a few years to get through the clinical trial space," Gibson said. "But, to find the drug and get it into the clinic, I think we can shorten that from five or six years and hundreds of millions of dollars into, perhaps, one or two years and just $10 million or $20 million."

Recursion is currently developing a new drug to treat cerebral cavernous malformation, a neurovascular disease that Gibson said is not widely known but affects six times as many people in the U.S. than cystic fibrosis. Before Recursion's AI-focused approach, there wasn't a clear path toward making a drug to successfully tackle this disease, he said. The new treatment is almost done with its phase two trials.

Gibson said he thinks the use of this new technology to map biology will be common in the biopharma industry in five or 10 years.

"Think of it as, like, Google Street View driving around taking pictures of everything," he said. "We have microscopes taking tens of millions of pictures of cells every week, and we're using a lot of the same AI algorithms to turn those images into mathematical representations of biology that we think could unlock some really exciting secrets."

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