SALT LAKE CITY — Chris Gibson is a really big thinker. The kind of thinker who strives to become an M.D. and a Ph.D at the same time.

That was his plan a few years ago when he was in the University of Utah's dual degree program studying to become a cardiothoracic surgeon and a researcher. It was in the process of pursuing those degrees when he found himself in a laboratory working with Dr. Dean Li, one of the pre-eminent researchers at the school.

"I had a background in bioengineering, and was working on bringing the engineering mentality to his more traditional biology and genetics lab," Gibson said. It was during that time when they were working on one disease when he made a discovery.

"I noticed that when you modeled that disease in human cells, the disease cells looked really different," he explained. The difference was how the cells morphed into something that was totally unlike their original composition.

That relatively minor recognition eventually became the impetus for launching a new kind of biotechnology company that combines information technology and biological research.

"That's where we came up with this idea to use computer vision and machine learning to automate the way we quantify the differences," Gibson said.

In November 2013, Gibson — along with Li and college friend Blake Borgeson, a computer scientist — co-founded Recursion Pharmaceuticals. The company's platform merges biological science with advanced computational algorithms to search for new therapeutic treatments for rare genetic diseases.

"If you could train a computer to look at billions of (cells), it could come back and tell you here are the thousand differences," he said. "That's essentially what we've decided to do with human cells."

Most scientific research for disease treatment takes place focusing on one disease at a time and can take years to reach any significant breakthroughs. But Gibson said the way his team uses scientific research with data analysis and computer technology allows a much broader scope of potential discovery, increasing efficiency and costing much less than traditional methods.

Today, the company has a goal of treating 100 diseases in 10 years, which is far beyond what traditional methods have been able to attain. The company's labs are able to analyze hundreds of samples each week, he noted, making that long-range dream a very reasonable potential reality.

Gibson decided to move directly into business after receiving his doctorate and taking a leave of absence from his medical school program. He said the decision was made easier when he realized how much good could be done on a much larger scale than as an individual doctor.

"I'm trying to build a company that ultimately — I hope — will be more impactful than I ever could have been as a physician," he said. "I estimated that I would have directly affected about 10,000 patients during my career (as a doctor), but at Recursion we have the potential for treatments to affect over 100,000 people."

In the best-case scenario, a treatment for a disease like Alzheimer's could end up impacting millions of people in the long run, he noted.

​​The company employs people with diverse experience in fields such as medicine, computer science, engineering, molecular biology and business. He said they use state-of-the-art biological tools to construct scores of unique cellular disease models, then images of thousands of cells per model are extracted to reveal nearly 1,000 structural features from every cell.

Those features are used to develop proprietary cellular “fingerprints” — trademarked Phenoprint — of healthy and diseased cells. The Phenoprint is then analyzed to determine if any known drug restores diseased cells back to health.

Gibson said the technology takes advantage of advanced imaging to provide rich datasets quickly and inexpensively. Just as patients with certain genetic diseases may have a specific phenotype — a set of observable characteristics — cells modeling genetic disease often display specific structural signatures that can help direct more effective treatment strategies, he explained.

Rather than the traditional inefficient strategy of studying a single molecular target related to a specific disease, researchers combine the latest in biology, artificial intelligence and information technology, he explained.

Gibson said he believes the work the company is doing may one day be able to "fundamentally change the world."

He noted that currently there are 7,000 diseases known to medical science. And last year, the U.S. Food and Drug Administration approved just 22 new drugs for treatment of various ailments, meaning there is a long way to go to be able to treat a huge variety of diseases, he said.

"There is a lot of room for improvement here," Gibson said. "Biology is really, really complex. What we're hoping is that by leveraging computers, (we) can train a computer to look at a million images, something that might take a person years to do ... a computer can do in 10 minutes."

He said the advances happening in today's technological environment give him great optimism that companies in the biotech sector will create powerful drugs that will treat some of the most challenging genetic diseases of our time. Similar to the way computers, mobile devices and automobiles are advancing so quickly today.

"Five years from now, half the cars driving down the road ... nobody's going to be touching the steering wheel. That's pretty incredible in a short period of time, so I'm pretty excited about what technology will do," Gibson said. "If we find one drug for one set of patients, that would be amazing. If we're shooting for the moon for 100 treatments by 2025, and we end up failing and only identify one, two or 10 treatments, that is profound and what a great way to fail."