"AI Will Cure Cancer, But Not Tomorrow" Dr. Ron Razmi

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1:34Hello, I'm Anthony Scaramucci, and this is Open Book, where I talk to some of the brightest minds about everything surrounding the written word. That's everything. That's from authors and historians to figures in entertainment, political activists, and of course, Wall Street. Before we dive in, make sure to follow or subscribe wherever you get your podcasts. And don't forget to leave a review. Good or bad, I want to hear from you. I want to hear whether you're enjoying it or where we can improve. And I can take the hits. So let me know. If you don't like something, say it straight. Now let's get into it.

2:17Okay. So joining us now on Open Book is Dr. Ron Razmi. He's the co-founder and managing director of Zoi Capital. But the book is fascinating. And thank you for coming on, sir, because I want to talk to you a lot about what you're doing. Title of the book is AI Doctor, The Rise of Artificial Intelligence in Healthcare. And so I've read a lot about AI over the course of my life, the perils and pitfalls of AI. But this part of AI, I find to be completely amazing. And this could be quite transformative for the next generations of citizens of the world for that matter. But before we get there, Doc, tell us a little bit about your background before we frame out what you're working on.

3:02Sure. Thank you for having me on. And I'm a big fan and actually listened to the podcast and some great episodes and insightful discussions. Really the long form where you can get into that story behind the story is great, especially if you're dealing with something like AI and healthcare, which are complicated and there are a lot of layers. I started out my career as a cardiologist. I was doing my training at the Mayo Clinic and I got involved in technology development to improve delivery of healthcare. And that ignited my interest to be on the technology and entrepreneurial side of healthcare.

3:49So I went back to business school, and after business school, I joined McKinsey. So I worked in the healthcare group at McKinsey for a number of years before I saw the digital health revolution coming. And the digital health revolution was right after iPhone was released. You have smartphones, now you have health apps, you have smartwatches and so forth. So those of us with a background in healthcare and technology got excited that we can change how healthcare is delivered more efficiently and more effectively using modern technologies like smartphones and digital wearables and all of that good stuff.

4:33So it's been more challenging than we thought to say the least. And we'll get into some of those reasons. But AI is now giving us a reason to be optimistic that we could improve quality, improve convenience, and lower costs at the same time. But not overnight. I mean, one of the things you say, which I totally agree with, the machine has no emotion. So the machine is analyzing data. I think it's the quintessential objectivity. There's no, you know, and it's also, it's so powerful that it can think of thousands and thousands and thousands of different permutational outcomes of what something could be, which could help you from a diagnostic perspective, rule things out and rule things in.

5:25But my question to you, though, sir, is that given the overall space, what is the real impact? Is it cost savings? Is it drug discovery? Is it prescription, meaning going to give the precise prescription to the person pursuant to exactly what they have and what their blood type is and all that other stuff? Or is it all of it? Or what do you think we're going to – what's the first mover for healthcare AI that's going to get everybody looking around saying, this is it, we've got to use this all the time? So I was on Power Lunch on CNBC a couple weeks ago. The first question that Tyler asked was Jamie Dimon said on this network an hour ago that AI is going to cure cancer.

6:17What say you? You have the book. What do you say? I said, well, yes, but not tomorrow. So it is really a foundational technology. AI is really a technology that goes through a lot of data and information and figures out what it means. That's what AI is. So when you're dealing with healthcare, you're dealing with a lot of information. A human body has billions of genes, trillions of microbiomes. We don't really know how all of this stuff works. We've made progress. Life expectancy has gone from around 35 to 80 in the last 150 years. However, all of that is in light of the fact that we really don't know how a human body works.

7:01We almost know nothing about the brain. That's why we don't have anything for dementia and a lot of the brain diseases. So now we're coming into this fight with this powerful tool that helps us find relationships between our genes and our immune system and the foods that we eat and all of this stuff. So there are magnificent things ahead for us. But just like I told Tyler, it's not a year or two out. It might be a decade or two out for the really lofty, ambitious stuff like curing cancer and figuring out the secrets of the human body. However, there are immediate use cases around administration of healthcare, improving patient experience, home-based diagnostics that can make an impact in the next few years and provide a step forward.

8:01But the book is almost 370 pages long. There are 14 chapters in there, each that break down AI and diagnostics, AI and therapeutics, AI and drug discovery. So when you have a foundational technology, the use cases are many. It's just that some are going to be more doable in the short term. And those are also the investable use cases. Okay, so Elon Musk and Google and these guys have been working for the last 10 years on self-driving cars. And, you know, they've got some cool technology. The car comes out of the parking spot and comes to greet you in front of the store. That one seems to be working okay.

8:48But the, in general, driving, getting on and off the highway, they seem to be having a problem with. Should we be concerned about AI not having that human touch and potentially hurting us somehow, making a mistake, crashing the car metaphorically? You know, in 2017, there were five FDA approved AI products. Now there are almost a thousand. So there's been an explosion in AI for healthcare products. However, almost all of them are classified as human assistants. So a radiologist still needs to review an image that an AI solution reads. So humans are going to be included in this process for the foreseeable future.

9:50AI makes errors. AI doesn't have judgment. There are things that you can train an AI model to do a lot of things, and it does it consistently. It doesn't get tired. It probably does it much more precisely than humans. but there are things that evaluating the cost of making a mistake is not something that AI can do. So you and I can have all the data telling us to do something, but our instinct tells us there's a guy with a machete behind the door that we're about to open up. AI doesn't have that ability to calculate the cost of making an error. So it's going to need human supervision, but you can offload a tremendous amount of activities onto AI that are being done manually right now in healthcare.

10:49Healthcare, the number one problem in healthcare is the shortage of resources. We have a massive shortage of resources in the US. I was in the Middle East as part of my book tour. I went to Bahrain, I went to Saudi Arabia, I went to UAE. Everybody was complaining that they don't have enough doctors, they don't have enough nurses, they don't have enough hospitals, and we're suffering from exactly the same problem. So AI is not going to be a luxury for us. We're going to need AI to help us do the massive amount of things that need to be done to provide health care to people. Well, if you an oil refinery in a hospital could have the same operating budget, but an oil refinery has 12 people working in it.

11:35A hospital has thousands of people. I want to I want to get to I mean, I think I think it's fascinating, but I want to get to the government. So I'm going to make you the czar. You're now the guy in charge of all health care related to AI, AI related to health care. So forget about Democrats or Republicans. Forget about left-leaning strategies or right-leaning strategies. What is the right policy? What would you be promulgating? Yeah. I mean, government is critical in this. It's important to keep in mind working on a follow-on book that talks about supply-side economics. And you ask what the supply-side economics have to do in AI and healthcare.

12:20I've been writing about economics, macroeconomics for years. But one of the things, one of the outputs of supply side economics that started in the early 80s was tax cuts, which supposedly would cause economic growth and there would be prosperity for everybody and so forth. And to say it hasn't worked out like that is really understating it. What's happened is when you do tax cuts, you have that budget deficits. We haven't seen the growth that these tax cuts, you see a short term bump in growth, but you don't see a long term increase in growth. And as a result of it, you start cutting government expenditures and R &D expenditure is one of the first areas to go.

13:10It's important to realize almost all the technologies we're using today were developed using public sector funding, decades of research in universities, and then they end up becoming commercial ready. So AI has been developed through public sector funding over the last few decades till it reached the point where it was ready for Google and Amazon and everybody else to use the foundational technology and apply it for commercial use. So if I'm the health AI czar, first thing I do is make sure there's robust government funding to continue working on the very basic issues that need to be solved in order for everybody else to have the right tools to put their ideas on top of those tools and create commercial products that improve health care, transportation, manufacturing, and so forth.

14:15So government funding for basic R &D is one of my pet peeves. And that's why sort of writing about economic issues is critical because they're so closely tied together. But also, a lot of the data, the way we collect data today in healthcare doesn't yield itself to easy AI analysis. so the data is written in narrative formats there are no standards it's hard to analyze that data we need to come up with new standards on how we collect health care data in order to make it easy for ai to analyze since ai can take over a lot of the analysis and follow up with patients and create the opportunity for us to do proactive health rather than reactive health.

15:14Going upstream and figuring out what are the infrastructure things we need to do in terms of aggregating everyone's data in one place. I mean, like I had an accident by George Washington Bridge last year where they had to bring an ambulance and they took me to Harlem Hospital. you know, I'm semi-unconscious. They have none of my records. I get my primary care at Weill Cornell downtown in Tribeca near where I live. When I went in a few months later for my annual physical, they did not have a record of my accident. This is not good. We're talking about one city, New York City, and my records reside in several different medical centers.

16:02You can't really use AI if one person's data is so fragmented. So we need national guidelines to consolidate the data. We need certification of the quality of these AI products by independent agencies. So when a hospital is considering buying something, they have assurances that it's high quality, that it's going to perform. You and I can walk into a CVS. We buy a bottle of Tylenol. We feel confident that Tylenol has been approved. The manufacturing process is being monitored by the government. And that makes that commercial transaction frictionless. It's good for CVS. It's good for you. It's good for government.

16:54They collect their tax dollars and so forth. We need something similar in AI where the buyers can be confident that they're buying quality products. And that's that's another area where government could step in and create the frameworks. So government does have a big role and I hope they become very proactive with it. Does it ever feel like you're a marketing professional just speaking into the void? But with LinkedIn ads, you can know you're reaching the right decision makers, a network of 130 million of them, in fact. You can even target buyers by job title, industry, company, seniority, skills, and did I say job title?

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18:15Yeah. Okay. Give us some predictions. Wrote a great book. It's five or 10 years out from the date that the book was published. What's going on in the world? Am I going to a doctor still? Am I talking into a computer about my symptoms? Are they sending me a remote test kit at home to check my vital signs? Do I have a general practitioner? A couple of things. Do I need my psychologist? Can the AI be my shrink? Great questions. First of all, I would say, given the strain that providing health care is putting on government budgets in all advanced economies, U.S., Europe, Japan, and so forth, being able to dial AI up as soon as possible to lower cost of care and improve quality and so forth.

19:13Talk about addressing budget deficits and improving government's ability to deal with an aging population. AI is really the answer. So if we have AI that can interact with someone who has chronic heart disease or diabetes and manage them, help manage them so they have better outcomes, then you're going to have, you're going to have, you're going to lower cost of care. because a lot of times the cost of care is tied to people going to the emergency room hospitals and so forth. So AI could actually be the answer to these massive budget deficits that are forecasted for us and other advanced economies.

20:01And a lot of it is due to Medicare, Medicaid, what government spends on health care. It's a big part of our federal budget. So with that in mind, we are, as an investment firm, we're right now investing in administrative and operational use cases. There is, for example, Ambien documentation. It's a use case where you turn on the microphone when a doctor is visiting with the patient, listens to the conversation, and does the documentation for the doctor. The doctor doesn't need to take notes. When I was a practicing physician, it's one of the things I hated about my jobs was taking notes and doing the documentation.

20:45That's a prime use case that's here and now. Investors who are lucky to invest in companies like Abridge and DeepScribe a couple of years ago when they were worth$20,$30 million and they were just getting started, Abridge just raised$150 million at$2.5 billion valuation. These are low-hanging fruits that are going to create 1 ,000x your money if you know which use case and which companies to invest in. We're looking at technologies for coding. The doctor has to do coding in order to submit for reimbursement. It's also used for public health and so forth. AI could read the doctor's note and do the coding for them.

21:31Another really pain in the ass, busy work. there are there is now ai on your smartphone that if you feel like you might have a urinary tract infection something that's very common in females you can pick up a kit from the drugstore and do a strip at home and hold your smartphone and it tells you if you have a urinary tract infection so you're gonna have administrative and operational use cases you're gonna have use cases, for example, a chat bot that listens to you mention your complaints and connects you with the right level of care. It's not going to replace your doctor, but it's going to direct you more efficiently to the right level of care and help that doctor take care of you a lot more efficiently.

22:24Those are the immediate, the next five-year type things. Okay. All right. At this point in the podcast, I have five words that I read out to my authors. And then I ask them to respond to the five words sort of tied to their books. And so I'm going to say the word, whatever comes to your mind, you talk to me about it. Okay, ready? Sure. So I say the word health care. You think what? Responsible for 30 % of all economic growth since the Industrial Revolution, according to McKinsey. Yeah, and I agree. And that's the 35 to 85 move that you were discussing, right? That's led to the higher quality of life for this little animal on this planet called humans, right?

23:11Exactly. And you'll either improve productivity or more people working to have GDP growth. No question. I say the word patient. What do you think? That's a tougher one because there are so many angles. I would say less than ideal experience with health care. Okay. I mean, if you think about hospitality, a lot of the other parts of the economy, since the digital revolution, our experience has improved so much. But health care is still very frustrating. Okay. People are, they don't know where to get care. They get handed off. They have to navigate a very complicated sector. AI could help with that.

23:59Okay. I'm going to say the word doctor. Burned out. Okay. All right. So the AI may help that, right? So let me say the word AI. What do you say when I say AI? Promising with the right safeguards. Okay. How about AI doctor? Transforming healthcare from reactive to proactive. But really a game changer. Absolutely. Absolutely a game changer. I try not to. I mean, I mentioned in the preface in the book, I make no prognostication or what's going to happen in three or five years. Because five years ago, a lot of this stuff that was forecasted for AI, none of it has happened. There are business model misalignments.

24:46There are data issues. As I mentioned, there are workflows that are hard to change. There are real barriers to bringing this technology into mainstream. So the world is going to belong to people who are good at doing upfront analysis, figuring out the right use cases, figuring out how to design a product that dances around these barriers. And that was my motivation to write the book because I've been on the clinical, technical business side of health care. I've had a 360 view of these issues. I've built a company and seen how difficult it is to bring a digital product into the health care environment.

25:37I've learned I've learned that this is more difficult than people think. However, I also appreciate the immense potential if we solve for these barriers, if we make the data more consolidated, if the healthcare infrastructure is upgraded and the way we collect the data makes it easier to analyze, then we're going to start seeing all kinds of benefits because it's going to make medical research much faster. We're going to find new treatments on an accelerated timeline. It's going to allow us right now. The reason wearables and apps haven't really changed the paradigm is because the data they generate, you don't have anybody that can analyze that data on an ongoing basis and combine it with all your other data that sits in probably several different electronic health records.

26:37and figure out what needs to be done. AI can start doing that heavy lifting for us. And if we start managing patients with chronic diseases in their home environment rather than the emergency room and hospitals, we're going to lower the cost of care dramatically. That's what I was talking about in terms of the impact on federal budget deficits and so forth. But you can see there are issues that need to be solved before that's possible. So in the book, I go into these issues in great depth and try to create a realistic, paint a realistic picture for the entrepreneurs, for people developing these products, for people who are considering buying those for their medical centers or for their research companies.

27:35And for investors on how do you evaluate the opportunity? This is one where you need to have a cross-functional view of things to make the right decisions. I mean, it's incredible what's happening. And I'm very, very grateful to you, doctor, for coming on because so many people are behind the curve in terms of understanding the quantum leap, that healthcare, many other sectors of the economy, but healthcare. And as you said, if we can get the healthcare right, it leads to unbelievable positive externalities for the quality of our lives and their economy, the economic growth, et cetera. So I really appreciate you joining us today on Open Book.

28:17Thank you. Thank you for having me. Before I let you go, so I just want to repeat the title again. The title of the book is AI doctor, The Rise of Artificial Intelligence in Healthcare. Dr. Ron Razmi, thank you very much for coming on Open Book with us. Thank you for having me. I am Anthony Scaramucci, and that was Open Book. Thank you so much for listening. If you like what you hear, tell your friends and make sure you hit follow or subscribe wherever you listen to your podcasts. While you're there, please leave us a rating or review. If you want to connect with me or chat more about the discussions, it's at Scaramucci on X or Instagram.

28:59I'd love to hear from you. I'll see you back here next week.

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