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How AI and Deep Learning Could Remake Global Healthcare

Christopher Bouton, molecular neurobiologist turned entrepreneur, sees a lot of potential for artificial intelligence and deep learning algorithms in the healthcare sector.
Christopher Bouton, PhD, a molecular neurobiologist turned entrepreneur, is all in on artificial intelligence and deep learning algorithms in the healthcare sector.
Christopher Bouton, PhD, a molecular neurobiologist turned entrepreneur, is all in on artificial intelligence and deep learning algorithms in the healthcare sector.

Christopher Bouton, PhD, a self-described molecular neurobiologist turned entrepreneur, had such a positive experience starting and running a company that he decided to do it twice.

After a five-year stint at pharmaceutical/biotech giant, Pfizer, the Johns Hopkins grad started a company called Entagen, which developed semantic-based analytics for the healthcare sector. After five years running Entagen, Thomson Reuters acquired the company in what Dr. Bouton called a “successful exit.”

Dr. Bouton spent a few years under the Thomson Reuters umbrella, but the entrepreneurial itch soon returned. “[In] 2016 while I was sort of contemplating what to do next, I started to take note of all of these deep learning approaches that were starting to be talked about. What everyone’s talking about is [artificial intelligence]. The reason that they’re talking about AI is because of these deep learning algorithms. And so I got interested in what they were and how they worked.”

That’s how Vyasa Analytics, Bouton’s latest venture, came to be in early 2017. The company provides deep learning software and analytics for the healthcare and life sciences industry. Bouton spoke to Chief Executive about Vyasa, how running a tech company means catering to people’s creative side, the potential of AI and big data in the healthcare sector, and more.

Below are excerpts from the interview.

The name Vyasa and the story behind that name is kind of interesting. How did you come up with that name?

I spent four years in India as a boy and I love India. I actually remember that time in my life better than I do [the] three or so years afterwards. It’s just such a vibrant, incredible place, and Vyasa is the name of ancient Hindu sage. He was referred to as the compiler of knowledge and he wrote the “Mahabharata,” which is a very famous text. He compiled many of the Vedas, which are the basis of much of the Hindu knowledge base. And so I love this idea of a compiler who pulls together knowledge. I saw these AI approaches as sort of similar in capability, and thus got excited about the name.

What did you learn from being the CEO of Entagen and how have you applied those lessons to your current role at Vyasa?

That’s a great question. One of the key learnings and one of the things that I love most about running a company is building a team and [learning] how to foster that team, how to grow that team, how to give that team the tools and resources that they need to operate effectively. And so, I really see my job as supporting the members of the company and learning how to do that effectively. [I’m] learning that software development or technology development on the cutting edge is really, in part an art form. And these are very creative acts that the people on these teams are performing.

And so, you have to foster creativity and arts as part of your job with running a team like this. I brought that to Vyasa as well, we’re attempting to address really big challenging problems, but trying to do so for the sake of really advancing technologies and approaches that are important for humanity. And so, it’s a place that’s really exciting to be.

What kind of potential do you see from the healthcare perspective for AI and big data?

Yeah, that’s a great question. So, I see big data and the big data phase as the beginning of our interest and ability to just grapple with the amount of digital information we’re all creating now. There’s this sort of digital tsunami, let’s say, that we’ve all created and the big data phase was when we needed to just figure out how to handle it, how to store it, how to run analytics against it. You know, all the plumbing, all the infrastructure necessary to just handle lots of data.


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