AI Investor Forum: Gus Tai on AI in Healthcare (Part 7)

Sramana Mitra: So now, let’s switch a little bit to surgery. Now comes the domain of robotic surgery, which is again, a very, very important and very promising area of AI application. It could really change human’s level of access to healthcare in a very big way. However, from a startup point of view, building surgical robots is an expensive game.

So once again, if this is what you want to go after, you have to look for ways to get to maybe National Science Foundation funding, maybe work within the academic framework – teaching hospitals and research hospitals – where there is funding available to do something like this.

Getting to proof of concept without some level of funding with surgical robotics is impossible, more or less. So keep that in mind that you have to bank on your resume and your track record in science to be able to access funding. Those are the ducks that have to line up for a company to take off in this dimension.

But then again, opportunities are enormous. Opportunities are going to be at different price points. Over time, what is going to be available only to the rich in the rich world, to begin with, gradually can get much larger levels of distribution as we crack some of the pricing nuts and the cost of goods and so forth.

Monitoring is another one that is a little bit less complicated, but we have seen some of the wearable impacts. It seems to me it’s not sufficiently penetrating. I’m wondering, Gus, why is that the case?

For example, blood pressure plays havoc with healthcare, but it’s still a very archaic little machine that you have to wrap around your arm and manually take blood pressure and note it down and send it to your medical provider, etc.

So, there are opportunities for innovation in getting that to easier form factors of recording blood pressure, and then monitoring continuously and optimizing blood pressure medication. Lack of blood pressure medication optimization creates a tremendous amount of serious healthcare problems.

Gus Tai: Well, I view that dilemma as a result of affordability of device and compliance of wearing the device. It’s just a human nature thing. I think that there could be bootstrappable opportunities around the Apple watch ecosystem. Apple itself has said often that health is an enormous market opportunity, even for them. They want to participate and lead it through hardware and services.

It’s reasonable to expect them to continue to make progress with the watch. Maybe they’ll launch a ring. Of course, there’s the AA ring and others with Apple. Then can you take the information that’s being provided there if someone wears the watch and provide a different type of analysis that could be a type of service.

With great distribution, even a small percentage of the audience wanting that distribution could find it helpful.

Sramana Mitra: Very important point actually. When Apple first came out with its smartphone and opened up the iOS developer platform, a lot of interesting apps got built and a lot of entrepreneurs found ways of expressing their entrepreneurial visions through that ecosystem.

That’s an opportunity in healthcare. the combination of iOS as well as the Apple Watch ecosystem is a very important platform to keep in mind as a distribution platform and a delivery model.

So definitely, if this is the direction you’re thinking in, that Apple is a very important potential partner and potential platform to build on.

What did I miss, Gus? What have we not talked about that we should cover on this topic?

Gus Tai: Well, I think that there are trends that are much more capital intensive, just building upon your point of this drug customization. An example of great AI or intelligence applied to this area would be Hims and Hers, the public company that is compounding drugs and personalizing drugs and helping to work with the patient to try different dosages and getting feedback from the patient for titrating the amount of personalized medicine.

You could highlight that market. It’s very large, and it does require a lot of intelligence. How a bootstrappable company approaches that I don’t yet know, but I do think it’s a very large opportunity.

This segment is part 7 in the series : AI Investor Forum: Gus Tai on AI in Healthcare
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