You've managed 14 billion across your career, 40 plus years of investing across healthcare, fintech, technology, 70 plus successful exits, 15 IPOs, number one healthcare investor on the Forbes Midas list seven times. We've been looking at AI for the last decade and have not seen it produce more developable products, therapeutics. Everything's changed the last two years. With Devoted, you now have AI enter the picture. Over the last year, they've tripled the size of their company, improved their operating ratio, dramatically increased their EBITDA. In my over 30 years of investing, there's nothing been as interesting as this or seminal in terms of just realigning the entire economy.
When do you think these legacy institutions will actually take a hit?
Annie Lamont, First Lady of Connecticut and founder and managing partner of Oak HC/FT. Thank you for joining us at Sourcery.
I'm so happy to be with you.
We're here at the New York Stock Exchange. I just want to start off by your background, by the numbers, because you are a legend, as they would call it. You're an icon and a legend. You've managed 14 billion across your career. Um, 40 plus years of investing across healthcare, fintech, technology, 70 plus successful exits, 15 IPOs, number one healthcare investor on the Forbes Midas list. I think we've said seven times. Um, and uh, we'll talk about the portfolio and everything, but notable investments include Athenahealth, Devoted Health, One Medical, Carebridge, Cotivity Health, VillageMD, Main Street, Komodo, um, Chai, and a handful of others. But to start again, it's great to have you on. The last time I saw you was in Napa, which was an amazing event. So, could you explain what was going on there?
So we invited all of our CEOs and then we had a group of industry individuals and advisers and panels, but it was mostly just to create connectivity amongst our portfolio, talk about strategy, and just have a blast.
So I want to talk about Oak today. So you're notably known as the healthcare and fintech fund, and that's definitely changed over time with the proliferation of AI. But what has that tension been like for you and the evolution of the firm?
I think, um, no fundamental tension because we have invested over time in horizontal platforms that apply to healthcare and fintech. And fintech is, it's the movement of money, you know, it's sort of, it can apply to anything and everything. Um, we have invested in supply chain in the past, you know, we've invested in, you know, risk and cyber and fraud. And, um, so, and I think as you think about the new AI world and you look at horizontal platforms, what's interesting is that between our fintech and healthcare practice, it's really 50% of the economy. So we have, we know intimately a lot of the enterprises and customers these companies are selling to, and it's very hard, for example, particularly in healthcare, to sell into healthcare companies, understand the buying motion, what they're interested in, who the people are, and we know all of that. So, and it's the smallest large market you've ever seen in that it's, you know, 100 providers that matter. There are 10 large payers, and, you know, having that depth of time, experience, relationships is incredibly helpful to a lot of companies that are selling horizontal solutions that they often need to be.
I mean, what's the advantage of AI that you can create a horizontal product that actually works in a deep way with workflows or, you know, specifically in a particular industry?
So what are you seeing in the market today?
What are we not seeing? I think, um, so what are we seeing now? I would say what is interesting and changed for us. I mean, if, um, starting with healthcare, that's about 70% of what we do. Um, life sciences is something that I started my career in, in biotech, you know, with the early days with Genentech and Saffron. Um, and so we deeply understand that. We've done pharma services for a very long time. We've been looking at AI for the last decade and have not seen it produce more developable products and therapeutics. Uh, and everything's changed the last two years. Um, so we're incredibly excited with recognition of Chai Discovery investment last year, which is now creating, has amazing models and products oriented towards drug design and discovery. Um, and we are intentionally going into that space and are going to be deeper and deeper in it. We're going to be adding partners in San Francisco, building out our San Francisco office further. Uh, because so much of AI, whether it's life sciences or any other industry, that the AI is the software AI is being developed for is happening in San Francisco. I was recently speaking with Ben Lamb, who's the CEO of Colossal Biosciences, and, you know, I haven't had many health, biotech, um, life sciences conversations yet, but it's something we're going to be doing more of because it is really hitting now. It's exploding.
Um, so could you explain, like, why is it exploding? Why is AI working its way into this category so well now? Why has it matured at this point in time?
I think it was so interesting with the advent of LLMs with the infrastructure around them. You've created biological models and models around chemistry that are not LLMs. They're very specific to the industry, but people see the opportunity. Physical AI, robotics in labs. Um, there are so many opportunities to change the cumbersome process of drug design and development that it is like everything else. Every industry is being transformed, and this is one of them. And it's probably the most difficult, the most expensive industry today to develop, uh, products, the most haphazard, uh, probably the highest, uh, fail ratio, right, of any product, uh, that's being developed out there. Uh, and to be able to increase the odds of success and accelerate that drug development so you get life-transforming products into human beings, um, is just game-changing. And I think it's incredibly exciting. And it's a moment of the sciences between immunology, oncology, and some of the great research approaches that are now happening, um, that it's just a confluence of events that are all coming together to, uh, I don't know, inspire and develop therapeutics. And I think we also have a China is in the last four years, the trajectory of China and life sciences is wildly threatening to the United States of America, and for not only commerce here and our pharmaceutical industry, our biotech industry, you know, but also, um, the delivery of drugs, uh, in the US. And we found out during COVID, you don't want them producing, you know, 90% of all the ingredients for antibiotics, right? Um, it's not that companies won't partner with them here, but, you know, that pharma in the last four years has 50% of the outside dollars they're spending on research are going to China. That was not the case five years ago.
Um, and so we have an existential threat in this country, an industry that is being co-opted, and we need to, through technology and tools and investment and a complete re-engineering of our FDA and processes, um, fix that rapidly.
Yeah. Can you, can you speak to that a little bit more and lay out the field for the China situation and even drug development? I mean, I know India is a big part of that as well, but can you lay out kind of the framework and I guess the map for that?
Well, I mean, it starts with fundamental research. Uh, and I think people would say, 'Oh, there's lack of creativity in China, you know, therefore they haven't produced as many patents and everything is a me-too drug.' And the reality is, is they have a lot of me-too drugs, right? They are absolutely taking something and then maybe changing, you know, one tiny bit of it in order to, uh, be able to reintroduce it into America as a new drug. But the truth of it is that on the research side, they have as many or more patents now coming out of university and out of their research arms as we have. And that is something that, you know, we need to think about as the NIH is pulling dollars, um, from investment and research in our universities. Our universities are the bedrock of, uh, all discovery in, you know, all these products and drugs in America, right? And if we're fundamentally undermining those internationally, globally, that can come to our universities, um, that we're undermining grants to those, you know, to those individuals, we will compromise the ultimate, you know, the pipeline of drugs. Um, you know, to date, that's not a problem. I just fear it's more of a problem in the future. Um, and but from an industry, we're now like Chai is in drug design, you know, creating models, creating products that are not, you know, not just models but products that can be used very effectively by non-tech-savvy individuals within pharma, uh, to build, uh, new drugs and to, um, to improve drugs they already have.
So, it is drug design and discovery, but it's also, um, reinventing what has already been created. Um, and every step of the drug design discovery process all the way through clinical trials can be redesigned and rethought. And so much of that can be done through, um, simulation and through AI. You know, uh, as long as you test what is coming out of, um, uh, design and then compare what a wet lab result would be, right? And then animal model results and look at the molecules and realize that we now have, we're creating computational models that approximate the results in those existing models that we have been using for 40 years.
In terms of the categories of discovery that even Chai is going after, what is their roadmap like? What are their goals?
Well, the roadmap first, um, antibodies. So they've nailed that, they're nailing that, it's, you know, getting better every day, but they're incredibly productive right now, like a hundred times more productive than a lab without them. Um, and the next would be peptides and then small molecules.
So, and they're already a fairly long way in peptides. Nothing that they are ready to show customers yet, but making material progress.
Yeah. I mean, it's been awesome to see all of this proliferate because I think, and you'll, I mean, I've seen this in the headlines. You see this by the dollars being allocated in different directions for philanthropy or like those kinds of purposes, but some of the biggest names like the Zuckerbergs, like they're putting all of their time and attention into life sciences and biotech and biology, all that kind of stuff. Um, other people are as well, but I think the main narrative out of that is that science will be one of the biggest benefactors of AI and what we're having happen with AI. So as you and the firm are seeing everything shape with AI, like how do you put time kind of scales and when to go into this category, when to start researching, and what are the categories that you're looking at?
I think we have always had a diversified strategy in healthcare, and I think there are opportunities obviously in the payer, provider, um, uh, life sciences, uh, and pharma markets. And, um, I think the way we're thinking about it now is, you're right, the biggest impact is probably going to be in life sciences and drug creation. Certainly, we care about outcomes. Um, and I think those are going to be life-changing outcomes from these, um, tools as well as drugs that come out of them. So I think we have been, as I said, looking at AI for a decade in that area and felt like we are now at the precipice, we are at a point of real impact, and that's generally when we get involved. Um, I would say you still have, I think Devoted is such a fascinating example of a company that started 10 years ago, and, you know, when you talk about, you know, scaling power laws, it's interesting because what you have to also think about is not just the speed of growth but the defensibility of something, right? And the reality is, is they have created by starting with a Medicare Advantage health plan that is very expensive, um, to develop and very difficult to develop against the behemoths that own these markets, and including the Blues. And they spent time getting licensed in every state. They spent time getting a provider network in every state. Uh, go to market brokers, go to market to members. Um, all of that takes tremendous time and energy and dollars. Um, at the same time they were building their own platform, technology platform, um, that nobody else has done in the payer world. And at the same time they're building up Devoted Medical Group, which is essentially their own primary care network, which is a virtual overlay in managing their patients. But with Devoted, you have, um, you now have AI enter the picture along with them actually owning the risk and owning the member through the primary care doc and the healthcare system. Uh, and they have built over the last year, they've tripled the size of their company. Um, they have improved their operating ratio, um, they have dramatically increased their EBITDA. Um, and you have a company that is, uh, I would say almost impossible to compete against in the future, and they will be going into commercial in the future. And it is what all of us want. You know, we want somebody who, you know, virtual overlay thinking about our health in a proactive way, has an AI front end and a doctor behind the AI on the medical care caregiving, you know, side as well as your insurer, and your member experience is fairly seamless. Um, so in terms of payments and processes, it's just, it's a beautiful thing, I have to say. Like, it is definitely the most, uh, AI, uh, probably the best example of AI applied to healthcare in the world right now.
I'm not one that is generally hyperbolic, but this is true.
Okay, I'll take your word on that. I know you speak from experience. I'm curious, when do you think these legacy institutions will actually take a hit? Will they, like, does healthcare have a long lag because of how ingrained people are, the lock-in with customers, clients, patients, providers, that kind of thing? Like...
I think from our, the hospital systems and providers, they're not going anywhere. If they don't, I mean, our acute, you know, our hospitals that take care of acute care patients mostly are needed, uh, and we need them to be the best that they can be. And I do feel like we're at the very beginning of a transformation there, um, that will be helped by AI in terms of taking administrative cost and burden off of clinicians so they can focus on patients. And it's probably the first technology that's done that. I mean, electronic health records were the great organizing principle for the data that now can be used by AI. Um, and so I don't know how much that changes, but I do feel like costs should be lowered because their administrative costs are such a burden on the system. It is 25 to 30% of all healthcare costs are really administrative. Um, and on the clinical care side, there's no question that, you know, AI, I mean, just how many people are using ChatGPT to actually diagnose themselves, and it might be better than your doctor at that. Um, and taking that, you know, one next step and, you know, looking at radiological images, 30% of images are read wrong by radiologists. There's something missed, uh, and it may not be life-threatening, but sometimes it is. Um, and if you have AI behind that, radiologists making sure that nothing's missed. I mean, we're not going to eliminate radiologists. We probably need more of them. But the reality is, is that with AI behind it, you're probably not going to miss much.
Um, right. And I would want that. You would want that, right? Um, so I think there's just going to be so many ways that AI helps, um, in terms of improving care along with the drugs that it, you know, will be helping to develop faster. Um, I think it's also, you think about robotics and AI and vision, you know, these, uh, vision models, you're actually going to be able to, a surgeon will see better than he can now, uh, in terms of, and a robot will ultimately probably with the aid of a surgeon see and be able to manipulate things better in your body as they do surgeries. So all of that is changing. I mean, Da Vinci was a brute force almost compared to what we're going to see now.
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It is still crazy though. Like I recently, uh, through a friend saw like a specialist doctor. I didn't see the doctor, but I was chatting with the doctor and, uh, they do a specialist type of surgery kind of a thing. And I don't know how this even popped up, but she was like, 'Yeah, I don't think AI is going to take my job.' I'm like, 'What do you mean?' Like who ever said like AI would take your job? You do something that's like completely manual, but like I think a robot and computer vision would definitely help with the time the procedure takes because you'll be able to do things much faster. Like maybe it can be automated in some capacity if it's a repetitive function. But I was even surprised to hear that. It's like I don't think you're going to go away entirely. Like that's just not possible. Especially for something like healthcare. You want a human working on you. You do want to hear them working on you for the most part.
Yes. And I do think, I mean, just think about the discrepancy between treatment in oncology in rural environments versus if you're close to, uh, one of the leading research hospitals, right? The outcomes are dramatically worse in rural communities. And same with surgery, right? Can you get to that surgeon fast enough? Are you going to, do you have the money to actually get to the hospital, um, where the surgeon has done that particular surgery, you know, a thousand times versus somebody who's done it twice in their life. Um, and just think about the ability to remotely direct a surgeon or remotely direct robotics in these environments to, um, to do surgery that's leading edge.
This might be more of like a macro thought or comment or question, but it is interesting to think that healthcare will be such a positive benefactor of AI, but patients rarely ever will know that, like they won't know that AI is involved in the process at all because it is like so behind the scenes and in so many different layers. Like they won't know that, you know, their nurse or their clinician, whoever they're speaking with, has a better day because they're not scribing everything, or that they have like more access to tools and like they don't have all this like, you know, menial burden on top of them, or have a harder time of diagnosing something because they have access to these things. But like it is one of, it's just a really interesting paradox because it'll be the most positively affected category. But the person who, by the way, like healthcare affects all of us. We're usually very upset with the outcomes or it's not a good process. Maybe you're in the waiting room for like a very long time. Like it's such a challenging environment that will be greatly affected, uh, for the most part, I would assume. But, um, it would be the best place for people to know that the, you know, the growing negative narrative of AI is actually not bad. Like it's the only place like you have an opportunity to reset the narrative, but those patients probably won't see it.
I think the fascinating thing is they will see it in a positive way. Their clinician will not be behind a laptop now.
Right. Will not have their back turned to them while they're inputting data.
Um, and so they should actually have a better experience. But you're right, will they attribute that to AI? Will they know that the diagnosis was actually refined by AI? Will they know ultimately the surgery? You're right. No. But I think that's what's going to be fascinating about AI in general. It is going to, um, people fear it and at some level they should, but I would say in healthcare it is going to be extraordinary and in so many parts of our lives it is going to, um, it is going to make our lives better, right? Augment our lives. I mean, I already feel like I'm learning so much, so much faster, right? Um, it's not taking away insight, judgment, it's just educating me as the world, you know, moves, right? Um, it's, you know, I think it should transform education. All these things, right, that are so hard to do and so hard to customize, it can help do that. It's not going to eliminate teachers. I don't think there's anything better than a great teacher, but the customization of what the teacher is doing for that child. Maybe they should be in eighth grade math and not fourth grade math. You know, they can stay in fourth grade but also be, you know, being taught in a different way. So, I think the benefits are just going to be extraordinary to society.
How has this macro shift, we'll go into the investing lens a bit, but how has the macro shift changed how you evaluate companies? Is there like another item or two that you look for in diligence? And how do you back test, you know, claims? I'm sure people are claiming more than they were before.
Well, first it always starts with the entrepreneur, right? I mean, it really is. It's just like, do you trust that person? Are you inspired by that person? Um, are they the absolute best person to be talking to this subject and actually creating a company around it? Um, is there, I would say, intelligence and intent. You know, I have never seen a group of entrepreneurs work harder than this generation of entrepreneurs. It is truly extraordinary. And I think in part the world is moving so fast. The rate of change is so fast and so great that what is different now is the leveling up of an entrepreneur. The people you are backing have to be better than in the past. I mean, not the top 0.1 percentile, but there have to be many more entrepreneurs closer to that level in order to build these great companies, um, and compete with all the companies and all the money that, you know, is being created now, all the companies being created. So, um, I do think it's just the entrepreneur, everything centers around an entrepreneur. They have to be able to pivot, they have to be able to grow. I think they're more, there are more product-oriented and tech-oriented, you know, tech-led companies. Now, um, it's funny because people said we're not going to need engineers or these companies, everything can be done right by people who aren't product-oriented, but I don't think in the first wave that is actually happening. I think the connectivity, even in healthcare, it's always been about healthcare. One reason Devoted, you know, certainly Chai obviously, both have comp sci backgrounds in chemistry and biology. And, um, and Devoted, the CEO had a computer science major from Harvard, you know, and he'd been in healthcare for 30 years, Eddie Park and Todd Park, um, who were founders of Athenahealth. Um, and I think right now you're going to find that more entrepreneurs are, you know, particularly in every industry, are product, you know, they're product-oriented, um, and they're learning a new market. And so figuring out like, do they actually understand the go-to-market? Are they humble enough to get the right people around them, ask the right questions? Um, and then ultimately a great entrepreneur is a Pied Piper. Like I have to be excited, right? I have to walk in a room and, you know, when I met Brad Smith or Todd Park or Josh and Jack at Chai. I mean, you walk in the room and, you know, in five minutes you want to back these people.
That's just the way it is. You just know they have it. You know, they have that intensity. They have that insight. They have, you know, that intelligence. They're going to make it happen and they're going to make it happen with integrity.
And in many cases, you've backed them again. So, can you share some of the stories where you've backed founders multiple times?
Yeah. Um, of course. You know, we do back repeat founders and I think what I'm most proud of is they choose us to back them again, right? Um, and certainly with, you know, Todd Park at Athena, then Castlight, Todd was one of the founders even though he went off to the Obama administration, and then Devoted, we led the Series A. Um, and then Brad Smith, um, another Harvard guy. I keep trying to back Stanford guys and then I'm always backing Harvard guys. Um, and so Brad came, I had been looking, we had been one of the, we had actually invested in the first for-profit hospice company. Um, I had been looking for a palliative care model that made sense over 15, 20 years. And then Brad came along and he described a palliative care model that was a win-win-win. Win for the patients, win for the payers and the healthcare system, lowered cost, and yet was, you know, and it was a win for the company, but it was a win for the patients and the people who were paying the bills. And that's the perfect triad for healthcare. Um, and so we immediately backed him. You know, that was a quick win for him. And then we started the next two companies, um, together, Carebridge and Main Street, and ideated for a year on both of them. And, uh, we thought it'd be one, but they ended up both being really fascinating companies. And I think what I said to Brad, he's like, 'What do you think I'm doing that's different?' I said, 'You're building something that nobody else is doing. There's so many me-too companies. There's so many.' And that was one of the reasons, like in healthcare, we didn't do as much in the Valley at one time because somebody starts a company here and there are five other companies here, you know, and the reality was that Brad would start a company, it would be a different model that nobody else was doing. Um, and that made them unique and successful at the end of the day. Um, and so we backed him three times. Um, all quite successful, called Carebridge to...
Elevance. And so we love that because it's a durable company that has been created, that is working, and you know, inside of strategic that sometimes can destroy things. Um, and uh, yeah, and then um, I mean, I think those are two of the best examples that we have. Um, and then obviously I think it'll be interesting. You Jack and Josh, this may be a company for the ages, uh, because I think they could own a huge piece of the continuum in healthcare, in drug development design, and um, and they're on their way, and they really are, you know, they're going to have a majority soon of the uh, largest pharmaceutical companies working with them in a very deep way, and they're uh, in a, you know, building mode that is creating emotion because of the, you know, the data that they're working with. The models are evolving and developing faster than anyone else's. Um, and that's, you know, that's the true sign of a, you know, of a company that in AI that it can be differentiated and defensible and durable.
I think that's a really good point. I'm curious from your standpoint and what you're seeing because the players on the board are changing very rapidly. Like, how is the M&A landscape changing? How is the exit landscape changing for healthcare?
Yeah. Um, we're excited because it is broadening things. So we've always had, you know, the McKessons and Cardinals and all the payers. Um, mostly like five payers that usually bought things, but um, uh, and you know, provider world, they don't usually buy things. So, you know, if you created a software company, I mean, it's like ultimately Athena went public and um, you know, was been traded in the PE world, you know, now. So you can create um, you can create very positive EBITDA companies, but now you have technology like you actually have software in a world of AI where you have the frontier labs actually interested in moving into these spaces and very hard to create companies embedded in providers, I think within a lab. Um, but you know, certainly possible that they could end up wanting to own with 20% of the economy between, you know, pharma, life sciences, and um, and software and providers. Um, so they may, you know, that may be an opportunity. I mean, Microsoft tried before, you know, and they bought Nuance, which is used elsewhere, but uh, Nuance is, you know, mostly dedicated to healthcare. Um, so they could go broader and deeper. Many, a lot of these companies could. Oracle obviously um, bought uh, Cerner, and they might want to go deeper there. So I just feel like there are many more opportunities than there were before in technology because we are going to not be in a backwater that we have been in technology and in healthcare in the past. We're moving quickly, rapidly into the 21st plus century.
Yeah. I mean, the main word with M&A is synergy, but how many of these do you think are actual synergies versus, you know, a momentum play?
I think in the new world, you're also going to have so many companies with valuations where they won't be able to really start these companies. They won't have the embedded expertise. They won't have the very best people to create them, and they will have to buy them. Uh, and if they want to like keep expanding their TAM, you know, that's going to be a great way to do it.
