AI Investor Forum: Gus Tai on AI in Healthcare (Part 2)

Sramana Mitra: Google’s AlphaFold is a good example of a model. A lot of scientists have been given access to it at an affordable price point. The impact it is having on scientific discovery and research is humongous. Somewhere in this continuum, I see that there’s a missing area where there is no Platform as a Service (PaaS) like AlphaFold that scientists can tap into to do drug discovery work using AI.

This is an opportunity, but the size of that opportunity is TBD. I think what I’m hearing you say is that the platform opportunity is not a humongous one. The drug that comes from that platform may be a very large opportunity, but the platform opportunity itself is not very large, which prevents investors from investing in it.

Gus Tai: What comes to mind as you were saying that Sramana is that it would be like the computer gaming industry before AI. There were teams that would develop or outsource the physics engines. They would develop the art and outsource people to fill in the details of art in immersive games.

Perhaps a bootstrapped area would be if you had people who are very facile at using Alpha Mind and other platforms, a drug discovery company may have some preliminary hypotheses and say, ‘Hey, can you run these simulations for me to round out different testing of vectors or characteristics from a computer modeling standpoint of a drug?’

I think that could be a bootstrapped type of business where the customer would pay for those services. As that company becomes more skillful at providing these services, it could then convert into a platform for more robust drug development.

So, I think there could be those types of service opportunities evolving over time.

Sramana Mitra: The other possibility is that a company like Atomwise, which is already providing these kinds of platforms to large pharmaceutical companies, could start a business catering to smaller entrepreneurial efforts and make that infrastructure available at an affordable price point.

Gus Tai: Yes, and just to be clear, the dilemma here is that most multi-billion dollar drug companies develop drugs in the US, and the process of getting approval is very capital intensive. If you have a platform here, you could go to a company like Pfizer, and they would want that company to have a lot of heft.

That’s the dilemma. There aren’t thousands of small drug development companies because that’s just not the nature of the ecosystem today, but it could develop in that direction. We’ll see.

Sramana Mitra: So I think the net of all this is that AI enabled drug discovery is a capital intensive game. Whichever way you cut this problem, it is a capital intensive game.

The bottom line is that if you are going into this, you need a resume that can raise capital. This is concept financing. You won’t really get very far without doing concept financing. To attract concept financing, you need a resume to get to that. That’s probably the net of this discussion.

This segment is part 2 in the series : AI Investor Forum: Gus Tai on AI in Healthcare
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