transcript

Speaker 1:
[00:00] Some software companies try to maximize your time on their app to juice engagement. Ramp does the exact opposite. Ramp understands that no one wants to spend hours chasing receipts, reviewing expense reports and checking for policy violations. So they built their tools to give that time back, using AI to automate 85% of expense reviews with 99% accuracy. And since Ramp saves companies 5%, it's no wonder that Shopify runs on Ramp, Stripe runs on Ramp, and my business does too. To see what happens when you eliminate the busy work, check out ramp.com/invest. OpenAI, Cursor, Anthropic, Perplexity, and Vercell all have something in common. They all use Work OS. And here's why. To achieve enterprise adoption at scale, you have to deliver on core capabilities like SSO, SCIM, RBAC, and audit logs. That's where Work OS comes in. Instead of spending months building these mission-critical capabilities yourself, you can just use Work OS APIs to gain all of them on day zero. That's why so many of the top AI teams you hear about already run on Work OS. Work OS is the fastest way to become enterprise-ready and stay focused on what matters most, your product. Visit workos.com to get started. Felix by Rogo is a personal finance agent that turns a single prompt into finished client-ready work using your firm's own templates, context, and standards. Send Felix an email like, take these comments and turn them for me, or update my tracker with the context of these emails, or run the ability to pay math on this buyer, and Felix sends back finished PowerPoint decks, Excel models, and sourced research. Felix works the way your team already does, delivering work quickly and accurately around the clock. Learn more at rogo.ai/felix. Hello and welcome everyone. I'm Patrick O'Shaughnessy, and this is Invest Like the Best. This show is an open-ended exploration of markets, ideas, stories, and strategies that will help you better invest both your time and your money. If you enjoy these conversations and want to go deeper, check out Colossus, our quarterly publication with in-depth profiles of the people shaping business and investing. You can find Colossus along with all of our podcasts at colossus.com.

Speaker 2:
[02:00] Patrick O'Shaughnessy is the CEO of PositiveSum. All opinions expressed by Patrick and podcast guests are solely their own opinions and do not reflect the opinion of PositiveSum. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions. Clients of PositiveSum may maintain positions in the securities discussed in this podcast. To learn more, visit p-s-u-m dot v-c.

Speaker 1:
[02:27] My guest today is Alex Karnal. Alex is probably the most talented bio and healthcare investor that I've ever met. As you'll see, he is an encyclopedia of all things going on in life sciences. Alex has been teaching me this topic for more than five years, and every single one of our conversations is about as deep as this one that you hear today. We cover every single aspect of what makes today's life sciences world so interesting. Starting with this concept of the health stack, the things that we can do both offensive and defensive to extend our life based on the evidence that he sees in the most exciting companies of today. We talk about cardiovascular disease, neurodegenerative disorders, metabolic disorders, cancers and beyond, and finally, we finish with his remarkable personal story. I hope you enjoy this great conversation. You and I have had these conversations now for many, many years. We've been partners and friends for a long time, and so it's hard to know where to begin the conversation because, I suspect, we'll go for hours talking about drugs and bio and healthcare and outcomes and a million things that affect us all. You have this cockpit-like view into what's going on in the state of medicine today. How would you describe the state of the union, the daily cockpit view that you get of the whole industry? Give us a dispatch from that room. What do you see today?

Speaker 3:
[03:44] When I look at this moment in terms of where we are in medicine, and I look back over my 20 years of building and backing biotech companies, I would say that 2025 was probably the single most exciting year in my entire journey. So to unpack that, what we're seeing is GLP-1 medicines are showing us what happens when we get to the root of disease. These medicines have the potential to do everything from protect us from being diabetic, after being pre-diabetic, all the way through lowering our risk of having a heart attack or a stroke, protecting our kidneys, and soon we're going to see the opportunity to protect us from developing addictions to alcohol and drugs. So a profoundly important single medicine. Of course, because these medicines are incredibly powerful and they can do wonders for people's long-term health, what we're seeing is that the adoption of these medicines have exceeded almost everyone's expectations, including my own, which were pretty darn high. I think it's easy now to conclude that this is a class of medicines will easily be in excess of $100 billion a year in revenue. And so what gets me fired up about that is not necessarily this once-in-a-decade $100 billion revenue opportunity that exists within GLP-1s. What gets me fired up is that it's actually the first commercial proof that we are ready for what I think we're going to look back on in time as a once-in-a-lifetime trillion-dollar revolution in all of public health. In order for that to be true, there's going to be layers of attack that are needed to help us live our longest and best lives. I think one of the things a lot of people don't appreciate when I meet them and we start talking about where medicine is and what it can do is that incredible scientists have already cracked the code on most of the medicines we need to protect us from most of the diseases that will claim most of our lives. That's a really important point because what that means is that there are tons and tons of people that have traveled through all different mazes to arrive at the biological target and come up with a medicine against that target that can help us to live longer and better lives. And so when we think about what is the gap that exists in the world today between the reality that when we look at any expected lifespan charts, they haven't budged in decades. The last major advancement we had in inflection was decades ago on the back of antibiotics, vaccines and better hygiene. We've gone nowhere since then. The gap is not necessarily needing more medicines. It's actually pointing those medicines at the impact that they can have. What I'm excited about about the GLP-1 opportunity is we're seeing the first commercial proof that we're ready to head in that direction. The reason that those sales have exceeded our expectations is people are taking into their own hands their future. People are basically voting with their feet saying, I'm done waiting to reactively go and treat myself for the diseases that I backward-lookingly manifest. I'm ready to go get after and help myself to live longest and fullest.

Speaker 1:
[06:59] I wanted to zoom in on a concept that you and I have been riffing on a lot recently, which we're calling health stack. Stack is a term in technology like your tech stack is all the various components that you use to create your overall thing. We thought this idea could be applied to health. We're all interested in our own health. It's a universal interest and concern. Maybe riff a little bit to begin on this notion of the modern evolving and emerging health stack.

Speaker 3:
[07:23] What a health stack looks like has a couple of different elements to it. It has elements of offense and defense, and on the offensive side of the equation, are some of the basics that we all know about. It's everything from proper nutrition, strength training, proper monitoring and testing, and doing those activities in a systematic way and tracking that data and building off of it over time. Later on, we could talk about how AI can play a big role in enabling that to reach its final chapter of what it takes for impact. What I find most interesting about it is, if we think about five core dimensions, not only are they within our hands to be able to be proactive about protecting ourselves, but we have the medicines to do that. To me, the five key layers are lipid optimization, its cardiometabolic health, it is neurocognitive health, it is inflammatory health, and our blood pressure. When we think about the lipid optimization, we have in our bodies produce cholesterol. And there's a type of cholesterol called your LDL cholesterol that's really dangerous. And it's dangerous because this cholesterol builds up in our bodies over time and it's slowly accumulating in our vasculature. And as it accumulates, it gets to a point where it causes a blockage. That's a heart attack and a stroke. And we have medicines today, whether they're statins, the PCSK9 inhibitors, that can do wonders to reduce our level of cholesterol. And most middle-aged men and women walking around have somewhere between a 30% and a 50% probability of having a heart attack and a stroke, sometime between the time that they turn 40 and the time that they turn 80. And to me, that's tragic because we have the medicines that exist that can help us to dramatically lower that risk to sub 10%. Looking at the next layer in cardiometabolic health, what we're talking about is the glycemic environment in our bodies combined with visceral fat. These are two major drivers or impediments to our long-term health. To give you an intuition for these, basically, the higher the level of glucose in our bodies, think about it, like the more brittle it's making our vasculature. And so, if you are both having lipids accumulate in your body and your vasculature is getting more brittle, you're only force-multiplying the risk that you ultimately have one of those horrific heart attacks or strokes. But we can do something about that. We've got amazing GLP-1 medicines that I started with that, from clear data out of Eli Lilly, show a 94% reduction in your risk of moving from being pre-diabetic to diabetic. We see amazing data in terms of what it does to both help us to lose weight and have category shifts going from obese to overweight, from overweight to normal weight. It's a game changer in terms of our long-term health. Moving down to neurocognitive health, the data is not out yet, but later on this year, we're going to see the next step for what are called anti-amyloid medicines. Medicines that can go right at the heart of the accumulation of plaques, this time not in our vasculature, but in our brains that lead to all sorts of damage and cognitive decline. We've got medicines today that can go right at those plaques and bust them. What Lily is going to probably show later on this year, it's my guess, but I think the data really supports it and we'll see. What they're going to show is that getting at those plaques earlier, before they accumulate significantly, is going to show dramatic effects on protecting us from developing Alzheimer's. Moving on to inflammatory health, one of the things I think people don't appreciate is that the food we eat is actually quite inflammatory. And because we have, over time, moved from being hunters and gatherers to being able to have as much access to pop tarts as we want, I love them too, you don't get one, you get two, we overeat to a point where it drives an inflammatory response in our bodies. You can think about that whole equation of if we have both lipids accumulating, and our body has a high glycemic environment making our vasculature brittle, and the same food that we're eating is driving an inflammatory environment around it, oh my goodness, it's like a ticking time bomb for all of that to go off. And not only is the inflammatory environment of our body implicated in driving an increase in cardiovascular events, strokes, and heart attacks, but also a whole set of inflammatory diseases that span everything from atopic dermatitis to ulcer of carotid and Crohn's disease. Finally, blood pressure. And maybe this one's very intuitive to people, but you can imagine that both if we are living high stress lives, if we're not working out, if we are developing obesity, we have this high glycemic environment, so our vasculature is brittle, our LDL is mounting. And on top of that, the pressure going through that system is going higher and higher as we're aging and doing nothing about it. Oh my God, that's just another force multiplier. So all of these axes that I define as the five key layers to the defensive side of a health stack, each of them has medicines available to help us control our fate. Each of them has medicines available that if we could get on them early and be proactive about where we're going with our health, they will undoubtedly add an extra decade of life to our expected lifespan and have the potential to take curves that have been dead flat for decades and drive one of the first inflections ever.

Speaker 1:
[12:47] I want to spend a little bit of time at each, maybe not all five, but at least four of the five levels to let you explain what you're seeing and learning, especially from your perch as an investor. One of the things that I think makes you so unique is that ultimately you're trying to make money on all this stuff and you're doing so with extreme care and precision and a very sophisticated team and lots of data. There's money on the line here. You're not someone that is reading something and trying something. It comes out on a scoreboard. I want to start with GOP1s because it's obviously the thing everyone understands the most, it's visceral. Maybe to begin would be for you to tell us what specifically you're seeing in 25 and 26 that is so exciting. These things have been around for a little while. People are starting to get on them earlier than that. What is the inflection? Then I want to get into the actual mechanics of how it works, the one that's about to come out next year, which seems maybe even more revolutionary than semaglutide and triseptide. What happened recently that has you so extra excited about them?

Speaker 3:
[13:46] Maybe one of the things most people don't realize is that there are a couple different injectable GOP1s that are on the market today, and we have some of the first orals that are coming to the market now and more that are coming. These medicines exist at lots of different doses. And I think one of the most interesting discoveries that I made over the past year, in just looking at all of the data that we get to consume as investors, I wanted to know the answer to, Wall Street is very focused on the next GLP-1, having more weight loss and more weight loss and more weight loss. And I'm sitting back and thinking to myself, I don't know if that's the right focal point. One of the most interesting findings from diving into the data is people are not solving for this massive bazooka. People are solving for something that helps them to lose some weight, stabilize and be there. I think that's really interesting because what that means to me is that what people really want is something that's going to give them a health advantage, but it's going to be incredibly tolerable. And what we find is that you go higher and higher in doses, the unintended consequence of that is, yeah, you're going to have more weight loss. There's going to be a whole host of other side effects that come with it. That is different than in most medicines where we're trying to maximize the efficacy of the medicine, really where Wall Street mind typically tends to go. What people are maximizing for here is like, how do I get on these things and then stay on them? So that to me was one of the big unlocks for 2025, was this idea that people want to protect themselves. If you marry that with the next big discovery from 2025 is that typically the way medicines are commercialized is you have big pharmaceutical companies, Eli Lilly, Nova Nordisk, that have armies of sales reps, that are out everywhere calling on doctors, making sure they know about their medicines, pitching the attributes and why they're the best in the class, and why there's no other option that their patients should be pursuing than their medicine. As you can imagine, that's a very capital intensive exercise, it's a very human talent intensive exercise. And what we saw, interestingly, is that Eli Lilly, pretty early on last year, pushed more aggressively into a non-traditional way to get these medicines into the hands of people. They added to their legions of salespeople a digital front end in Lilly Direct that allowed people to get a prescription from their doctor and go get the medicine direct from Eli Lilly. It was one of the first big insights that the consumers want to be able to get these medicines themselves and not have to go through traditional means to get them. As you fast forward towards the end of 2025, what we started to see was that, oh my goodness, more than half of the new people joining are coming in directly. So hold that with the third point that comes from 2025, which was all sorts of theater and dramatics around compounded GLP-1s. What we learned from the compounded GLP-1s was that, not only do people want something that's going to defend them and be tolerable, not only do they want something that they can get through all the frictions of the system and just hit a button and have it come to their homes, a real consumer-like product, but price matters a ton. Through most of 2025, the average monthly cost of a GLP-1 was north of $400 or $500. Thanks to our administration, whose prices are coming down, and I think that's really good. And it's particularly good because what we learned from the compounded versions of GLP-1s was that there is massive price elasticity in this market. Compounded GLP-1s cost about half as much per month as the traditional approved GLP-1s by Lillian Novo. We were collecting data that was suggesting to us somewhere between 15 to 20 percent of the market that you couldn't capture through scripts was actually flowing through groups like Hymns and Hers and other sources where people knew they wanted the benefits and wanted to be proactive about their health. They wanted to get these GLP-1s, but they couldn't possibly afford $400 or $500 a month, but they could afford $200 or $250 a month. And so to me, that's profound because you've got a compounded version that hasn't gone through any clinical trials. You know nothing about the manufacturing, but you know that these medicines are so important to your health that you're willing to take the risk, not only the safety risks of the medicine, but all these risks of these unknowns of where this is even coming from. And because you can afford it, go take it. And so I left 2025 thinking to myself, oh my goodness, we're finally starting to see people step up and vote with their feet. They're saying, I want the benefits of these medicines. And now you get to 2026, and this is the absolute game changer. In 2026, we now have an oral version of Vigovia. And this medicine has launched over the last couple months. We are seeing every week, the oral version of Vigovia is setting record after record after record. And you might think, yeah, of course, like who wants to inject themselves once a week for the rest of their life? I don't really think that's what's driving. An almost 4x relative launch cycle for the oral Vigovia versus the most recent injectable launches at bound. People that want these medicines, then the lowest end of the curve, that doesn't cost 500 a month, it doesn't cost 250 a month, it costs $150 a month. And so now we've seen that the lower end of the curve, if we get to an $1,800 a year cost, these medicines fly off the shelves. And to put that in context, prior to the launch of the Oral Wigovie, just a few months ago, the GLP-1 market was moving at about 200,000 recorded new scripts per week, 200,000 new people getting on these medicines per week. The most recent data that I looked at this past Friday says that that has now moved from 200,000 a week to 300,000 a week in just a few months' time. We have to take these incredible learnings from the commercialization of GLP-1s and the most logical conclusion is that people are ready and people do want to go and be proactive and arming them with the stack that can help us to all live an extra decade, really focusing on hard on what does it take to close that gap between invention and impact. When I say this trillion-dollar revolution, what that means really is this trillion-dollar reduction in our annual healthcare spend. And I think that that's really possible.

Speaker 1:
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Speaker 3:
[21:53] A lot of people don't realize these medicines have actually been around for 20 years. Some of my first exposure to GLP-1 as a drug class actually happened in my early days entering the industry as a young biotech investor back in 2005. With Amlin Pharmaceuticals, having what we thought at the time was the most miraculous breakthrough. GLP-1 is a hormone that our bodies naturally produce. The problem with this naturally produced hormone is that once it's produced by our bodies, it only lasts for about two minutes before it's gone. So if you just pause there, what does that mean practically? Okay, if you were to take human GLP-1 and we would be injecting it, we'd have to inject ourselves 30 times an hour for the rest of our lives to get the benefit of what we can today with either one pill a day or one injection a week. The science behind moving from a protein that lasts for two minutes to a protein that can last over a week is a dramatic transformation. So what's good about that is it is a hormone that's already in our bodies and it's a medicine that we've got data on for over 20 years. And so we know a remarkable amount about it, not just because it's been around for 20 years, but it's now been in millions and millions of people. What happens is when we eat food, at some point that food makes its way to our small intestine. And when food gets to our small intestine, it's what triggers the release of GLP-1 in our bodies naturally. That GLP-1 molecule travels all over our bodies. It interacts with receptors in our stomachs that helps to slow the digestion of food. It also interacts with receptors in our brains that help us to feel fuller, longer, to feel satiated. The combination of those two mechanisms of action are what allow us to turn off the food noise, that allow us to seek out and consume far fewer calories than we've ever done before. In addition to that, it does an important role in regulating the production of our insulin. It interacts with receptors on our pancreas that triggers the release of insulin. It plays a big role in not just having that sugar not affect our vasculature, but also making sure that that sugar is not destroying our kidneys. The mechanism and the science behind it is actually pretty well elucidated. Biologically, we know how it's produced, we understand all the different places in the body that it interacts. When you think about all the places in the body that it interacts, it then becomes no surprise that it's had such an incredible range of effects, both from protecting us from becoming diabetic, to reducing the risk of having heart attacks and strokes, to lowering our level of inflammation because we're consuming less food, and so we're having less of an inflammatory response to that, all the way through to helping us to lose weight, which is a bit of a virtuous cycle in terms of lowering our blood pressure. So when you look across the five axes, the five layers of defense that are mission critical for us maximizing the number of years that we can live and having the most life in those years, I fundamentally believe there's no molecule that's more important than GLP-1 across that entire axis. When we think about the different forms that it's available to us in, we've already cracked the most important code which is moving from something impractical, 30 shots an hour, to the early days with AMLIN Pharmaceuticals of a twice a day shot, to where we are today, which is not just longer acting, once a week versions, but far more potent, meaning we need far less of it and it actually starts to get to levels that we can inject that have incredible pharmaceutical properties to them. The next axis to think about is not just the form by which you get it, oral or injectable, and not just the duration of the dosing, orals we take every day. Today, we take injectables once a week. There's some amazing ones that Pfizer just acquired that look like it might be a once a month. Amgen is also working on a once a month, might be once a quarter. The duration of time between those doses is really important because the easier it is to take a medicine, the more likely it will be to stay on these medicines and have the longest term benefit from them. The next important axis to then focus in on is, how do we think about dose and the tradeoffs between semaglutide and terzepatide, semaglutide being Ozempic and Wigolvi, terzepatide being Zepbound and Manjaro. Our team's fundamental perspective is that they all achieve the same goals. They were just novel IP strategies to achieve those same goals. They're all pretty much interchangeable. That leads to the question of, how do we think about them from an investment perspective and a human impact perspective? Both of those perspectives come together because when we think about investing in medicine, the key question that we're focused on is, why doesn't medicine have a right to win? Of course, for medicine to have a right to win, what we're essentially saying is that this medicine is going to really have a differential impact for people such that people should choose it. The right to win analysis comes down to also the different segments of the market that we're thinking about. To put a framework around this, we always think about the obesity market as having three main segments. People that are overweight, which are basically BMI's between normal, roughly 25 and 30. Obese, which is between 30 and 40. And morbidly obese, which is north of 40. When we look at the aperture from a BMI of 25 up to a BMI of just under 40, that's where most of the patients are today that require reactive treatment. I would argue in the future, we could talk about why GLP-1's might be appropriate for just about everyone. And that's because the reality of it is, as you go from your adolescents to your 50s and 60s, on average people are going to pick up about five BMI points. Being able to take a medicine even at low doses, even though they haven't been tested in those populations, I'm willing to bet, would help protect people from that five point increase that puts them in harm's way and puts that to bed. But when we look at the market today, pretty much from that BMI of 25 to 39, they are well served with any of the available options on the market. I think where we still need some help and I think where there's a right to win is really in that BMI zone of 40 and above. Sadly, these people are at a level of body weight that requires incredibly long titration to get up to these high levels of the hormone, and they need to have much more dramatic reduction in their food noise to be able to bring their weights down from a zone that is incredibly dangerous. Just given the amounts of visceral fat that they're carrying around, down to levels that are going to give them much more sustainable life.

Speaker 1:
[28:28] Would there be any difference in outcomes if we simply ate the same exact input that we eat on these medicines? If instead of taking the medicine, I just ate exactly what I would eat on them, but figured out a psychological way to deal with the food noise and just not eat when I'm hungry, effectively, is there any difference, do we think, in outcomes? And I'm especially thinking here about alcohol addiction as seems to be one of the things that gets addressed by these drugs. That seems unrelated to how much I eat. So it seems like an independent thing that's being positively affected by the drug beyond just which calories I'm putting into my body. Is there something else going on here beyond just literally what I'm eating as a result of taking these drugs?

Speaker 3:
[29:10] Eating is definitely a part of it and it's a major part of it. So, look, if we could all be disciplined and we could all get on a proper diet where we're selecting the right foods, eating the right amounts of them and staying disciplined, you wouldn't really need these medicines for the purposes of managing our weight. But I think that's only going to cut at the weight part of it. I think unfortunately, if your biology is wired such that you have a family history of diabetes and you are pre-diabetic and on the precipice of turning diabetic, we're starting to be in a place where we're just not producing the insulin that's required to be able to take up that glucose that's coming from the food that we're eating. Yes, by consuming fewer calories and less food, we can hit part of that. I think it's unknown as to whether that will be enough to be able to undo your progression to diabetes and so I might say, you probably still need those medicines for that. I think on the other side of the equation, connected to that has to do with addiction. Some sense you could say that food is a form of addiction. While consuming fewer calories will help protect us from the vicious cycle of over-consuming food, in terms of the addiction data that will start coming out over the next year or so, you would lose that benefit. You would lose the free gift of protecting yourself from being addicted to drugs, alcohol, or gambling. There's an open question on what just consuming food would do for cardiovascular outcomes. We've got compelling data right now at Anova Nordisk over the last year that basically shows that by taking GLP-1 medicines, there is a north of 20 percent reduction in our risk of having a heart attack or a stroke. What I thought was pretty profound about the full data that they put out is that, that was independent of weight loss. That speaks to me that there's just another axis and another biological driver that's driving this cardioprotective result. We might forfeit that, but without a doubt, if we could actually get access to great food and we can eat the right amount of it and stay disciplined, that would take us a long way.

Speaker 1:
[31:15] It seems like summarized, there is more going on than just that. The data seems to suggest that even if I could perfectly eat, I might still re-benefits in these other ways from these drugs. To really drive home the point of existing drugs, before we get to all the exciting new stuff, which we'll talk about as well, that there are existing drugs which could have radical impact if everyone was on them. Anything else on GLP-1 that you feel like is especially notable that we haven't talked about?

Speaker 3:
[31:43] The other aspect to it is we want to start chipping away at, well, what are the layers that exist in between that could prevent people from actually getting the benefit of GLP-1s? When I think about that continuum and I think about that gap, there are basically three different dimensions that are preventing people from getting maximal benefit of breakthrough medicine that exists and is right here for all of us. Those break up into, in my mind, complexity, cost, and convenience. I started on my journey like two years ago and to practically have to deal with our health system, all of the different branches that it took from recognizing that I had a cholesterol problem to two years later finally getting access to the medicine that could help protect me from that problem. It's everything from you want to go see a doctor because you get a blood test that says, hey, I got a problem, to learning that, well, the next appointment is only six weeks out. And then I go and of course, I want to redo the blood test. The friction in our system mounts and mounts and mounts. And eventually, I think a lot of people just give up. It is really hard to navigate that system. Given what we're seeing with GLP-1 medicines and what we're seeing that the direct-to-consumer side of that is driving most of the adoption today, I think we have to start asking ourselves, why is it that I can go on my iPhone, I can go to Amazon, I click a button, and the next day I can have toothpaste. But it takes me an incredible journey, hundreds of phone calls, multiple doctor visits, being pricked and prodded multiple times, just to protect myself from having a heart attack. That doesn't make sense. I think we have to balance the opportunity for health impact of this amazing medicine that we have with just the reality of how darn complicated it is to navigate through our system. Next is cost. Most medicines that we need to be on for the rest of our lives that are going to be providing the chronic care, the different layers of that defensive health stack that will protect us from these diseases, those medicines today are priced as similarly to acute treatments, yet they need to be taken over decades. So, we have a timeline problem, we have a horizon problem, and I think that there's a lot of innovation that can occur around pricing models if the world is moved from where we are today, which is waiting until there's a problem, waiting until it's almost too late and reactively treating it, to proactively getting out ahead of disease. The final part of that is compliance, and we alluded to that a little bit, but the reality of it is we all know that medicine only works if we take it. And it turns out that because of the complexity of the system and getting it, because of how expensive these things are, and at the end of the day, because we're all human, the more frequently we have to take a medicine, the harder it is to go get it, the more times we have to go to the pharmacy, the more times we have to make that decision. Over the course of the year, the higher the probability we're just going to quit. And that's just human nature, myself included. Your compliance is like this invisible barrier to all of us realizing our best health outcome. On one hand, wow, I mean, GLP-1 medicines is an example. It's miraculous. We went from twice a day to once a week, and now we've got versions that are once a month, maybe once a quarter. That's a huge unlock, in my opinion.

Speaker 1:
[35:04] Maybe now is the time to tell a second drug story, a far less well-known one than GLP-1, which is PCSK9. I find this story to be so interesting for so many different reasons, but maybe most of all because it seems closest to a free lunch drug that exists, and because it helps deal with cardiovascular disease, which is something that everyone's, you know, in their family or themselves probably dealt with at some point. It seems incredibly important, close to as important as the first one we talked about. Can you tell the story of this specific drug, what it does, how it works, the impact it might have?

Speaker 3:
[35:38] The headline here is PCSK9 medicines are amazing because what they do is they today can lower our bad cholesterol, that LDL cholesterol by 50% and we now have outcome studies in patients at different degrees of having a high cholesterol, having significant protection from ever developing and having a heart attack or a stroke. And so in patients that have previously had a heart attack or stroke, we can reduce that risk by over 20% in the future. And for people that are at high risk of having a heart attack or a stroke, the medicines that are approved and on the market today can lower that risk by about 25%. And so these are incredible medicines, particularly because heart disease is still the number one killer in the US today. These medicines are profound because they hit right at the heart of the biological driver of high cholesterol. The way these medicines were discovered is from human genetics. What we can do from a human genetic perspective is go around the world and look at different populations of people and study what are some of the attributes and some of the advantages of different populations. It turns out that there's a population of people in the world that have a genetic mutation that conveys a massive advantage. They have a mutation in their PCSK9 gene, which means they don't produce the PCSK9 protein. Now, what we've learned from both observing that village and understanding the cardioprotective nature of that genetic defect, what we learned is that the production of this PCSK9 protein interferes with our body's own ability to clear LDL cholesterol. And so what happens is the more PCSK9 we're producing, the fewer particles of LDL that we can clear, the higher our cholesterol grows over time, the more those little particles are invading our vasculature and starting to mount up until we get to a point where there's a blockage. Recognizing the import of that PCSK9 protein driven from the observation of human genetics and from data that showed in these populations of people, with longitudinal studies over 15 years, the fact that they were genetically deficient in the production of the PCSK9 protein led to them having an 88 percent reduction in the risk of ever developing cardiovascular disease. That was miraculous. What the pharmaceutical industry saw to do was, how can we replicate this? Exactly. How do we get that advantage into the hands of people? They came up with injectable biologic medicines at first, that you can inject and would go and find their way in your body to that PCSK9 protein and bind to it and make it so that protein couldn't bind to your LDL receptor. That was the beginnings of those medicines. But what innovators then sought to do next was, how do we make it easier for people to take those medicines and get the benefit? And so the next big innovation in that space was moving from injectable biologics or monoclonal antibodies to what's a new modality called RNA interference. And what these are is another form of subcutaneously injected medicine that makes its way down into your liver. And it had the attributes of these being very long duration molecules and made it so that we didn't have to inject ourselves 26 times a year, but maybe only twice.

Speaker 1:
[39:05] It's incredible when you think about seeking out a population that has a natural advantage, figuring out what it is and then conferring it to others through a drug like this. The dramatic reduction in cardiovascular incidence of people, of course, the genetic group 88%, but also the people that take this drug is so interesting. I always wonder, the body is such a complex system. There seems to be very few things in biology that just are one use or one explanation. There's all sorts of stuff going on. What are the trade-offs? I'm interested in both PCSK9 and GLP1 since we've talked about both. It just seems like there's always a trade-off. There really aren't usually free lunches in markets and nature and in biology. What's the skeptic's point of view? Like if I could somehow fly in the smartest data-driven scientific skeptic of the use of these drugs, what would that person say?

Speaker 3:
[39:53] I think PCSK9s are very much more that free lunch than GLP1s. GLP1s have real toxicity associated with them. We see in the clinical studies, significant rates of nausea, vomiting and diarrhea are the first symptoms that emerge that cause a lot of people to quit these medicines early. If you look past that and you look to people that have been on these medicines for longer and longer periods of time, you look at the labels of these medicines in the clinical studies, there's risk of the development of gallstones and pancreatitis. Of course, these are issues that would emerge just from having weight loss in general, which adds to that muscle decline as well. These are all consequences of losing weight and losing weight quickly over a period of time. But when you look at the other side of the equation, the benefit that you get, the fact that these are so protective across so many different axes and the data is pretty clear. Not only will they protect us from developing diabetes, obesity and cardiovascular disease, when you look at the implication of those diseases on expected human lifespan, we're talking about the aggregate of those diseases costing us five to 10 years. It's very much well worth it for people to take the risk of developing these other sub liabilities that you can do something about by just stopping the medicine for the benefit. There is a real trade-off without a doubt. It is not a free lunch for GLP-1s. But for PCSK9, it's pretty much a free lunch. There was a ton of concern in the early days. What happens if your LDL goes down to zero?

Speaker 1:
[41:20] Does an LDL do good things?

Speaker 3:
[41:21] Exactly.

Speaker 1:
[41:22] It's there for some reason.

Speaker 3:
[41:23] It turns out that LDL is produced in lots of different places in our bodies. It turns out that you can basically pin that PCSK9 bad protein down to zero. The best we can do in terms of reduction of our LDL from, really not even in humans but in animal models, is something in the 80-90 percent zone. Because we have people that are walking around with mutations where they don't produce any PCSK9 and they live incredibly long healthy lives and don't have the vicious fate of having a heart attack or stroke, I think we've got the combination of animal model evidence that suggests, we really can't get LDL to zero, combined with the fact that we've got genetically advantage people walking around that aren't even producing the protein to the same degree as others, that this one is very much a free lunch.

Speaker 1:
[42:09] Do you think everyone in the world will be on this particular drug at some point?

Speaker 3:
[42:13] That would be a dream for me. A big dream for me is that everybody anywhere who wants to have the maximum level of cardioprotection could get access to this medicine and could stay on it. Because it is more asymmetric, it is more in the degree of that free lunch. I would argue that if you just project down the road longer term, this medicine should be far bigger in terms of the number of people that are on it and the revenues that are associated with it than GLP1s. That is not what is playing out right now. And it is not playing out right now really for two reasons. One, GLP1s have this amazing attribute to them that you take them and very quickly, you start to have some side effects so you know you are on them and you start to see the benefits. When you compare the two, it is easier for medicines where there is an acute, clear, easily measurable benefit for people to stay on them. Unfortunately, in the setting of cardiovascular disease and particularly thinking about bad cholesterol, this is to me the most dangerous setup because you don't feel anything if you have a high level of bad cholesterol. You could think of it as a silent killer that is working in the background, slowly accumulating in our bodies. You can be doing everything right and being at your peak physical shape and then all of a sudden in the nowhere, you can have a heart attack or a stroke because if we don't pay attention to the levels of this bad cholesterol in our body, they can sneak up on us and claim our lives. To me, because the reward is so asymmetrically favorable versus the risk, because the earlier we can intervene with the accumulation of cholesterol in our body and keep that at bay, the greater the likelihood is that we're going to get through the rest of our lives, even if other things manifest like diabetes or high inflammation or our blood pressure goes up, we're going to be able to be right at the core of the problem and keep that as low as possible, meaning that we've got the lowest level of accumulation across our vasculature.

Speaker 1:
[44:10] I think the number three and four killers, we talked about metabolic disorders and cardiovascular are neurodegenerative and cancers. I'd love to spend a couple of minutes on each of those. Neurodegenerative in particular, Alzheimer's drugs, seems to have been this wasteland. We really don't understand what's going on. As a result, we haven't made a lot of progress at either protecting against or treating something like dementia Alzheimer's. What is going on in the world of science and in the business of pharmaceuticals to address this specific problem?

Speaker 3:
[44:41] It's been a wasteland for decades. I think we finally cracked the beginning of the code, but not the full answer. What we found today is in patients that have confirmed levels of plaques that have developed over decades in their brains, we now have medicines that people can take that will start to break up those plaques and remove them. Unfortunately, and this will be intuitive, if you get to the patient that late in the disease, a lot of damage to the brain has already happened, because you can imagine these plaques are building, they have to go somewhere, they're causing death and destruction of the tissue around them. Today, we've got some amazing medicines that are both Biogen and Eli Lilly, that if you are late in the disease progression of Alzheimer's, you can start to slow the decline, and we can slow that decline by about 30 percent. So intuitively, it just gives us a lot more years at the baseline level of cognition that we have versus declining much more rapidly. It turns out that if we can identify a patient that's at risk for Alzheimer's disease earlier and earlier and earlier, if we have a test available to do that, well, then it makes perfect sense that if we can start giving people these medicines as early as possible, not only will you be there in the early stages before a lot of damage is done, but you can think about it as turning off the faucet. So as these new amyloid plaques are produced, you can be attacking them with a medicine that helps to accelerate their clearance. Oh my goodness, maybe that has a dramatic effect on long-term decline. Maybe it reduces those rates by 40, 50 or more percent over a longer period of time, which means the earlier we can get them and the better those medicines are at interacting with those plaques. The easier it is for the people to stay on those medicines, we might be able to wake up in a world where we live without this disease. We know that that's possible with GLP-1s for diabetes and obesity. If you take them early enough, you will not become diabetic, you will not become obese. We know that's possible for cardiovascular disease. If you start taking a PCSK9 inhibitor earlier in your life, which by the way, I think the risk reward is actually even more favorable than statins in terms of human health. But we know that you won't progress to cardiovascular disease. The same is true for Alzheimer's.

Speaker 1:
[46:59] So up to this point, we can imagine a future world, as I know you do, where everyone could enjoy the benefits of protective defensive measures in our health stack for these three specific killers. What about cancer? Cancer is the last one that in some ways feels the most visceral and the scariest. You hear you have cancer or someone has cancer, it feels like this death knell or just terrifying piece of news. I think we've made huge strides in treating cancer, but I'm curious how you would frame up the problem that is dealing with preventing, treating all different kinds of cancer.

Speaker 3:
[47:33] If we are successful in mobilizing people around a health stack, and we can move from reactively treating a disease to helping people be as proactive about their health as possible, I think the unintended consequence of that is people live longer. Eventually, something's going to get us. The incidence of cancer being the issue that brings us down, the disease that brings us down could rise. I think the unfortunate reality is that cancer is hard, both because we often identify it too late, and then when we do, cancer is like a sneaky devil. You might have an angle of attack to go and beat that cancer that presents itself early, and as soon as you're making progress with a medicine against that angle of attack, all of a sudden, the cancer has a survival instinct and it redirects. Now, a medicine that was working incredibly well, that had shrunk a tumor completely to zero, is having no effect because while that medicine eliminated the cells that were most vulnerable to the medicine, guess what? The cells that were left behind, even if it's just a few, now had the advantage in growing rapidly and causing a new set of harm and setting a patient on a horrific direction. And so, it's hard because we tend to identify cancer too late, and then when we do, it's shifting. Now, there's also the opportunity for optimism around it, and I think it gets to the topic you and I have spent some time talking about, which is testing. The areas of testing today that I find most exciting are across being proactive and early identification of the risk, and then once a cancer emerges, what do we do about it? And so, talking maybe across both of those modalities, and then come back to the medicines that are associated with that. In terms of identifying cancer early, there are companies like Exact Sciences and Garden Health that have gone really hard at breakthrough innovations to help us screen for colorectal cancer. Now, of course, we have the gold standard that's available, which is a colonoscopy, and I have to go get one next year. But none of us are ever looking forward to that, because it's something people don't look forward to, even though everybody should be getting them, and with the regular periodicity, most people don't. And I think that's really tragic, because by not getting your colonoscopy, you're putting yourself at risk for colon cancer, which is an incredibly slow growing cancer, if you just got the colonoscopy. I think we could very much live in a world today with very low incidence of colorectal cancer. Garden Health and Exact Sciences went directly at this problem. Exact Sciences has a stool-based test, has incredible ability to predict people being at risk of cancer. Same thing for Garden Health. Garden Health took it to the next step in terms of knowing that you can go after markers that would predict colorectal cancer, but recognizing that the commercial model around being able to get people to not just receive the prescription for a stool-based test, but the complexity of people being able to complete the test and get that sample back, was one that just could never have the scale as a simple blood test. So Garden Health learned from Exact Sciences' advancement and then came up with the next-gen version as a simple blood test that you can get done just about anywhere. It's amazing to see that not only are both of those markets continuing to grow, but the blood test is inflecting. That to me is exciting because it means that again, people care, doctors care, people care, they're getting it done and that means we're going to be safer and safer from these. But I think it's important for people to realize that not all tests are created equally. When I look at a new diagnostic in the space, I care deeply about two metrics. One is the sensitivity and the other is specificity. One of them tells us of all the people that could have cancer, what percentage of those samples are we actually getting back that is an accurate diagnosis of cancer? So if there are 100 cancers in a sample, what percentage of them actually get picked up as cancer? That's the sensitivity. Then the specificity is if there's 100 samples that don't have cancer, what percentage of those give us a false positive saying that you have cancer and when you don't? I think both of those are really important metrics. And at the same time, I think that there's a whole other industry around multi-cancer early detection that's evolving right now and unfolding right before our eyes. These are companies moving from not just having single cancer tests, but having multi-cancer tests across large numbers of tumor types that can be really dangerous. When you think about how I described the offensive and defensive side of the health stack, the defensive medicines that we can take to keep us maximally protected, what's not in there is anything to protect us directly from cancer. But that's because I tried to attack cancer from the screening perspective and made that part of offensive. Over time, I think at a minimum, people should be doing a colonoscopy. I think that the next best in class version of that is colonoscopy married with either a blood test or a stool-based test with some regular periodicity to it. And I think over the next three to five years, particularly with how AI and the evolution of these tests are really converging to help them to move faster and faster and to be better and better, I think we're going to wake up within the next five years with really awesome multi-cancer early detection tests. And when we have them, then shame on us if we're not getting them and shame on us for that not acting on the learnings that come from them. This will be obvious, but the earlier we know that we have a cancer, the greater the range of options are for us to go do something about it. And I think we're finding that across lots of different cancers, there's opportunities to have amazing results. Sadly, my brother-in-law's father passed from multi-myeloma maybe almost a decade ago. If he had been diagnosed today with multi-myeloma, his outcome, his prognosis is dramatically different because not only is our ability to test and identify that people are developing cancers, getting better. Not only do we have other types of tests that we can look at, what are the mutational drivers of that cancer that help to connect not just cancer, but the type of cancer to the best medicine that we have today to go treat it. But the medicines are getting better and better. While cancer medicines began, as many medicines do with just pills and injectable biologics, today we have an entirely new class of medicines that are these CAR T-cells that are either cells that we take out of a patient's body and arm them with the ability to go attack the cancer directly, or companies like Capstan just came up with the next-gen version of that where they can inject on an IV basis that can attack the cancer cells directly without having to even take cells out of a patient's body and have that happen within the patient's own body. And what we're seeing from these medicines is dramatic efficacy. So we're seeing that they have the potential to reduce tumors by 100% and to do that in 70% plus of patients and to keep them at bay for really long periods of time. While we haven't yet cured cancer, to me, I think the slope of the line is really exciting, both from the testing angle and the earlier we can identify these cancers and from the increasing range of modalities and options that we have to go after and destroy them.

Speaker 1:
[54:49] What about imaging, both skin imaging, interesting companies doing that, like NECO, deep body imaging? Companies like Pernuvo, it's quite expensive, but as I think about the health stack as something that we could do that's preventative, how do you feel about those technologies, which are relatively new, but do try to take a picture worth a thousand words inside your body and identify a tumor early or something like that? Do you think that's worth it?

Speaker 3:
[55:12] To me, more data is worth it so long as you could put it in the right context. When we get the result of a colorectal cancer test, screening test, we know the context for that and we actually know whether we have something that's useful or not. The pictures that we can get from groups like Pronovo and others are powerful because we can see progression over time and we can use that data, and particularly as AI is going to increasingly become our medical home, arming our AI system with that information will be super helpful. The thing that I worry about though is as you measure more and more different dimensions with each of them having a material false positive rate, the odds that you come out of that experience with a false positive that can be disruptive in life becomes material. It's not to discourage anybody from doing these. It's just to make sure that any data that we're collecting, make sure we put it into the right context set so that we can have a framework for how we deal with whatever information comes from taking that test. So for me personally, I'm not yet pursuing those. I'm very much focused on areas where if we're going to go and do a test, it's going to have a high probability of capturing what I'm testing for and a low probability of giving me a false reading. I think the more information that we can accumulate with really high fidelity, the better we'll be at being proactive about our health.

Speaker 1:
[56:31] Everything we talked about today was discovered and developed by incredibly talented people, both scientists, people in the medical field, but then business builders that turn these things into great products and great companies. Maybe just describe, so as not to take it for granted, what that process is in the first place. Back to biology is complicated. It is unfreaking believable. We can do the things you've been describing so far in this conversation. And then we're on a trajectory to the granularity with which we can make edits, for lack of a better term, into what's going on in biology is probably just going to continue to accelerate. So I want to understand that process itself, and then we can talk about how AI figures into that discovery process.

Speaker 3:
[57:07] First of all, what are the two key ingredients for discovery to happen? You need scientific instinct married with tremendous amounts of capital, and I think you need both of those to converge in order for there to be a breakthrough that allows us to live healthier and longer lives. Let's break those into their pieces with the science of medicine and the business of medicine, because I think they're both independently interesting. Oftentimes, what ends up happening to discover a medicine is a scientist, for whatever reason in their journey gets inspired to spend their lives trying to crack the code in a certain disease. What tends to happen is you've identified a problem that you want to solve, just like in any consumer or tech product. What's the problem we're trying to solve? You then have to go through a tremendous amount of research to understand every single thing you can about that problem, and most importantly, what could be driving it. What's developed over time is a method, probably one of the most important methods in the history of humanity called the scientific method, which is the systematic way by which a scientist moves from focusing on a problem they want to solve to actually solving it. There's a couple of discrete steps in that scientific method and tremendous amount of iteration that leads to cracking that code. Once you've identified the problem that you want to solve, the first step to solving that is come up with a hypothesis for what could be driving that disease. The way scientists tend to do that is everything from like the PCSK-9 example where scientists are observing nature. Where are their populations of people that have an advantage? Okay, let's go figure that out. That's cool. Let's go understand it. All the way through to like combing through thousands and thousands of pages of the literature to understand what people have tried to crack a code that still exists today that you want to go crack. And that's a deep literature review. So fortunately, there are tons of papers that exist on successes or tiny steps to successes that exist and are available for anybody. The unfortunate part of the literature is that what's often missing is all the failures, which would be even more informative than successes. So generally speaking, when a scientist wants to go solve that problem, they're gonna observe a population, they're gonna start reading a ton of research, they're gonna probably put both of those insights together and use that foundation to form their first hypothesis for what could be the solution to the problem. So from having a hypothesis, then the amazing scientists can then go figure out what experiments do I need to run to test that hypothesis and even more, what's my prediction for what should happen in those experiments? And those are really important steps because the design of the experiment and the quality of the data that comes out from that experiment will either confirm your hypothesis and you move forward or it will reject your hypothesis and then you go back through and you loop to your next hypothesis and your next set of experiments and you continue to loop and loop and loop. So, what scientific method generally looks like is hypothesis, experimental design, execution of that experimental design, review of the data that comes from that experiment reading out, test that data result versus original hypothesis, either confirm the hypothesis or re-loop and re-loop and re-loop and re-loop. And so, there's this iterative process that tends to begin its journey from the literature very quickly move into what we call in vitro experiments or experiments that are done in petri dishes. And as we start to develop evidence and support for a hypothesis in cell-based experiments, it tends to move on to small animals and then larger animals. And then it gets to the point where the totality of the data and evidence that you've collected from a hypothesis perspective to cell-based experiments, to the animal-based experiments. You put that all together in a beautiful package that you present to regulators and you say, I think I've cracked the code. I think I can move us forward against disease A, B or C. And here's the hypothesis that we had. Here's how we tested it. Here's all the data we've generated. That helps me, the scientific team, to believe that we might have cracked this code. And now, we would like your approval to go start and agree on what studies should look like to test how toxic or how dangerous this breakthrough could be for somebody. And if we can show that there's good margin between really high doses and where that toxicity starts to come in and the doses that we've proven from our experiments are likely to help somebody live a longer, better, healthier life, we want your permission to then go and actually test that in a person for the first time. This is incredible and that process that I just described, you can imagine most of them fail. But for the ones that do succeed and get the chance to then go into toxicity studies and ultimately into humans, those are the ones that get really excited. But they take years and years of iterating and looping to go from that beginning idea through the literature ultimately to the animal study that makes you believe you've actually cracked that code. And then, of course, from there, this is so much of a marathon than a sprint because you've spent years trying to crack the code and now that you have, guess what? Now you've got another five to seven years worth of clinical studies you have to do to prove that in people, the idea you had for medicine actually has the effect that it's intended to and that, per our discussion earlier, that benefit-to-risk equation is favorable to the point that regulators should approve it and let it come to the market.

Speaker 1:
[62:39] I have two questions here. The process itself is beautiful and has driven so much discovery and progress, not just in medicine but scientific method-driven progress everywhere. But I'm curious about two dimensions of shortening that feedback loop or increasing the velocity of new discoveries and progress. One is AI and the second is what I'll call citizen pharmacology, which is people. This is becoming really prevalent in what I'll call the peptide community. People love talking about peptides these days. GOP1 is a peptide, Collagen is a peptide. There's well-known things that are peptides, but there's this whole class of things that we can talk about. But it seems like if you take to Reddit, for example, you will find groups of people organizing to test new things on themselves outside of the normal RCT, FDA approved process. If you shorten it, you probably increase the danger, but you decrease the time to learning or something. You've got both of these things as interesting aspects to study of what will drive forward progress in drug discovery. Riff on each, maybe starting with AI, what is real already? What do you think will become real by virtue of the increasing skill level or reasoning level of the models?

Speaker 3:
[63:51] Absolutely. So I think what you're basically describing on the AI side is our quest to try to get to a level of scientific super intelligence. You can imagine that from an AI perspective, if scientists are armed with an agentic infrastructure that has a scientific intelligence that's like at an Einstein level or multiple of Einstein level, the force multiplication that can occur between a superstar scientist armed with that agentic resource means that they will do science faster and with higher probability for lower cost and have greater impact. So that is important conceptual framing and so then practically, how does that manifest and why does it matter? Well, you can imagine that any human scientists on their own, tinkering in the way that I just described scientific method and that wheel of science spinning and spinning and spinning, us as human scientists are always going to be constrained by what we can retain in our human minds and constrained by our ability to use our human hands to go run those experiments. There are super talented, incredibly smart people that can retain volumes and volumes of scientific papers. Can't retain all of them. AI can. If humans are running experiments, not AI driven robotics, there's just a certain throughput that is going to be limited by human hands, that would be unlimited if you had an agentic robotically driven system. At the simplest level, AI coming into the discovery of medicines is one of the biggest unlocks that we will see in the history of medicine. Because it means that we're no longer constrained by our minds, we're no longer constrained by our hands. We can generate not just a few hypotheses for what the answer can be from the total sample set of knowledge that exists, we can identify all n number of hypotheses that could exist and should exist, and then figure out what is the greatest and best next experiment to go run, run that and run those in real time 24 hours a day, seven days a week. The sheer ability to be more comprehensive and complete in our hypothesis set, and then the sheer ability to run experimentation at a scale that's unprecedented, I think practically means we are going to be able to speed breakthroughs from timelines that would typically take three to five years to timelines that can take less than a couple of years. The other important element when we think about AI and its impact on drug development is not just the potential of what could be from that conceptual frame, but where are we today? I think it's really exciting. Today, I would say we're in the early innings of being able to discover novel targets and I would say that we have not yet in a systematic way been able to discover a target that didn't exist yet. But what we can do is for targets that we know exist, but that we have really struggled to be able to develop medicines against those targets, we're starting to see that code be broken by AI and AI being a big force multiplier to enabling that to happen. What we have today are companies that can go from what would historically been running these massive screens that are incredibly time consuming to doing all of that screening work in Silico and can go from model to molecule and what would have taken a couple years time in a month. That's already true today. There are companies like Lila Sciences, Enabla. These are companies that you can basically ask the agentic system to develop you a molecule against a certain target. It can crack that code and give us something that we can work with and start running an experiments in a month's time.

Speaker 1:
[67:33] Is it your impression that this is just going to happen? There's no major risk left that AI will not have a major impact on this entire, both target and therapeutic discovery process. Are we now on a curve that just feels inevitable to you?

Speaker 3:
[67:47] To me, we're on that curve.

Speaker 1:
[67:48] When did that flip? How recently?

Speaker 3:
[67:50] Very recently. For most of my career, there's been some version of machine learning and the hopes of AI really driving drug discovery and the development of novel medicines against those discoveries. I always worried that in order for that paradigm to be true, it required data that didn't actually exist in any easy place. If all you do is train AI models based on the research that's available, you unfortunately have a paradigm of a lot of garbage in, garbage out. I think one of the things that people don't appreciate when I start talking to them about what data exists is that unfortunately, a lot of the recorded literature is actually incorrect, and there's been tons of studies that show if you go try to replicate the experiments that are in the literature, you don't even get the same results. Definitionally, if that is true, and these AI companies don't have a source of creating novel data, what are you going to do? How are you going to train? We've seen just how powerful LLMs have been and how impactful they are across so many different areas of life, because they've been trained on trillions and trillions of novel tokens. So data ends up being a big part of what drives to advanced levels of intelligence and drives an intelligence revolution. Well, the same has to be true in science, and so the AI companies that I believe are going to be most set up for success are the companies that have incredible AI talents, have access to significant amounts of capital, and can combine both of them with a novel way by which they can generate science tokens that don't exist in the public domain. In fact, the generation of those tokens becomes a big driver of their moat, not only the driver of the moat, but actually what enables them to be able to get to an increasing and increasing level of scientific intelligence that starts to separate from that with which can be achieved with the LLMs without having the benefit of those tokens. And we're starting to see that. And so we've got one company that we're really close to today that's actually starting to show the bending of that curve and helping us to see that the idea of getting to scientific super intelligence is one that is likely to follow a pretty deterministic set of scaling loss.

Speaker 1:
[69:59] Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions. Nobody's watching. Ramp puts guardrails on spending before it happens. Real time limits, automatic rules, zero firefighting. Try it at ramp.com/invest. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest. Every investment firm is unique and generic AI doesn't understand your process. Rogo does. It's an AI platform built specifically for Wall Street, connected to your data, understanding your process and producing real outputs. Check them out at rogo.ai/invest. The best AI and software companies from OpenAI to Cursor to Perplexity, use Work OS to become enterprise ready overnight, not in months. Visit workos.com to skip the unglamorous infrastructure work and focus on your product. Ridgeline is redefining Asset Management Technology as a true partner, not just a software vendor. They've helped firms 5X in scale, enabling faster growth, smarter operations and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. I think it was OpenAI that came out with this announcement, maybe working with Ginkgo or somebody, where they've created like a closed loop automated lab and discovery process of not just models, but physical world testing as well. If you close your eyes and think five, seven, 10 years from now, what's your best guess, knowing what you know, at what the discovery process will look like at that point?

Speaker 3:
[71:29] I think it will be completely automated. I was up at Lila Sciences the other day, and you go into their labs, and what you see is all of these robotic arms, and you see Petri dishes that are moving around in an automated fashion moving from one spot to the next spot. To me, I think what that means is the scale of data that's going to be required to be able to train these models, the trillions of tokens that are required, has got to move beyond the constraints of human hands because it would just cost so much money to do it in a human capital driven manner. It has to be done robotically, and for that to be done, it has to have an agentic engine behind it, and needs to produce data at a scale that's kind of unprecedented. What I think the future of discovery looks like is agentic systems that can drive robots to do most of the experimentation that we're doing today with human hands. And I think that's a big unlock for the ability to crack those.

Speaker 1:
[72:24] That's the top of funnel.

Speaker 3:
[72:25] Exactly. And so now, superstar, brilliant, amazing scientists who go down their life journey to become a scientist that wants to fight against disease, wants to do work that matters, is no longer going to spend two-thirds of their career at the side of a bench pipetting all day long. He's going to have all that time back to point their energy and their enthusiasm, their optimism towards trying to figure out, how do I use the systems and machines that I have, and point them in the right direction at the codes that we should be cracking. That's really enabled when you have the combination of brilliant human scientists force multiplied by the agentic power of these systems that are being built, and the more those agentic systems can be fully automated, where all of that lab experimentation is happening in real time, and without the need for human interaction, I think the quicker and quicker can scale, and I think the quicker and quicker we can achieve that level of scientific super intelligence.

Speaker 1:
[73:17] What do you make of this whole peptides plus citizen pharmacology side of things? I think they just came out and said there's gonna be 14-something peptides that are allowed to be compounded, and it seems to be deregulation of sorts happening in this space. People say peptides, I think not really knowing what that even means, so maybe define it. I'm just curious what you think of this. It really plays to your earlier point about these generations, these younger generations especially, seem to be a new attitude towards all of this stuff, which is like, I want to own this. And part of owning it is a willingness to take risks that are above and beyond what is mandated or regulated I'm allowed to take. This subculture is fascinating to me. You read about BPC 157, I think that's the number, all these interesting different things that are being tried. Do you have a take on the impact that this will have?

Speaker 3:
[74:06] I think it's hard to know, whether it's the commercial success of GLP-1s or you look to the massive movement around peptides. Honestly, it's not even limited to just peptides. If you go on Reddit, you can see people are experimenting across all sorts of different dimensions. I think what's happened is we live in a world where people want to go and figure things out that help other people. Now, we've got platforms that allow people to share that. We see the creation of groups that can exist today, that couldn't exist in the future before we had the technology like we have today in the communities that can get formed. Whether you're looking at it from the perspective of people coming together under shared missions, that's happened throughout the history of all of humanity. This is a shared mission where people are saying like, I want to take my future health into my own hands. And I'm not willing to wait for scientists to go take on this problem independently for to go down the traditional pathways. Like, I don't have the time. I need to know the answers now. Because I think for myself, this is going to really matter. And people have a hypothesis for this and they want to test it. And so they're fighting really hard to go and get those hypotheses tested. At the same time that you see what I would call like grass roots peptide movement, you also have a recognition by the FDA that we've got to move a lot faster. So long as we have all these frictions in the system of going from a hypothesis for a medicine to the testing of a medicine in people and then ultimately in approval, disease is going to keep winning. I think we're seeing under Marty McCarrey, real leadership to want to go and try to break down those barriers and those frictions that are making the drug discovery and the drug development process be incredibly time consuming and incredibly complex. And some of the manifestation of the real world impact of that spans everything from Marty brought in an AI system to help them be able to comb through the thousands of pages of filings that sponsors behind medicines have to submit in record time versus the armies of people that would have to comb through that and the days and days of days of time that are wasted, all the way through to starting to challenge every aspect of, OK, well, in what settings do we not need nearly as much evidence in animals and we can rely on cell based experiments? In what settings do we no longer need multiple redundant studies that show us the same thing? We can cut through it with one study. I think across anywhere you look, we are seeing a movement to be able to do things more efficient, faster and having a greater impact. And in some ways that circles back to where I began. To me, 2025 was such an exciting year because we saw not just amazing medicines doing amazing things for people's health, but we saw real movements across the consumerization of this medicine, across people wanting to take health into their own hands, and across every layer of what we just described. What we see is people wanting to be far more proactive about their health than has ever been true before.

Speaker 1:
[76:57] I've had this experience with you countless times where I'll introduce you to somebody, we'll have a conversation like this, and somewhere between 30 minutes in and 230 minutes in, the person has a thought which they rarely say which is, who the hell is this guy? We've done the same thing yet again, which has gone hours into the conversation without laying any groundwork for your background. Can you just tell us your personal story a little bit?

Speaker 3:
[77:22] I've just been super lucky. Reflecting back on my childhood, I guess my parents were training me to be a biotech builder and investor since the time I was five, but I had the greatest childhood ever. Grew up in a typical American home. My dad was this relentless entrepreneur. He was the type of person that worked harder than anybody I knew, and he was so all-in in any business endeavor. He was pursuing like our entire family was all-in on it. Mom was doing the billing. My brother and I were in the garage refinishing furniture. Grew up around business by being around my dad, and he was just such an inspirational force in my life. Despite the fact that he was such a relentless businessman, he was never successful really at any of those, and I think if he were sitting here today, sadly he passed the Parkinson's over a decade ago. One of the things he told me in those last few days is that, he felt like he never stuck with anything long enough to see it through over the tougher moments, and would just quickly move on to the next thing and the next thing. So I learned that lesson from watching him in real life and being in business with him. But you pair my dad with my mom, who's been an absolute force in my life, my mom is this incredible ever optimist. From my earliest memories of my mom, I can remember her drilling into my mind. We always commit and we never quit. She pretty much convinced me that I could do anything I wanted if I put my mind to it. And so I feel like from my dad, I got to experience and see what it means to take risk and that you can fail and life goes on. And from my mom, I developed this sense of resilience. And I think both of those attributes are very much probably connected to why when I found medicine, I fell in love with it, particularly the discovery and the development of it. So from that early childhood, I was the first in my family that got a chance to go to college. I graduated from MIT and had just an amazing experience there. For me, being at MIT and learning more and more about business and economics and science and connecting it back to my early days of working alongside my dad and getting a chance to, at the time, not realizing, but put money into some of the deals that my dad was doing. I could put $2 into a rocking chair that we bought. And if we sold it for 200 bucks, I thought that was amazing. And if we didn't sell it, I was pissed. I didn't realize I was learning in these early days about risk and reward from my dad. And then when you get to a place like MIT and you start to see the black and white version of the equations associated with that, it was a real major step forward for me that inspired me to want to then go on to New York City and to Wall Street. I thought to myself, no better place to really learn about business and how capital connects to business and what it takes than to come to the epicenter of that here in New York City. And so I ended up at Merrill Lynch and had some amazing mentors that were really inspiring to me. I had two major stops at Merrill, one on the capital market side. And then after doing that for a while, I wanted to go see how these crazy securities, derivative securities traded. And so I had a chance to move to the Merrill Lynch derivatives desk. I think what was just so fun for me about reflecting back on that time is, I actually never picked Biotech. When I got moved over to the derivative desk, I was just put into Biotech. I was assigned to the Biotech subgroup of the derivatives desk and knew nothing about it. But I fell in love with it so quickly because the risk reward in that setting was about life and death. And when I was looking at what was going on in companies that I needed to be understanding to be able to price risk, it was like wild to me what was going on. I had no idea about this entire field of the development of medicine. I had no real appreciation for just the sheer capital that's required to move it forward. And here I am through total serendipity, I find myself at the epicenter of needing to understand these companies deeply enough to price risk and getting a chance to be in front of all of the buy side investors that are building and backing companies that I became inspired by the work that they were all doing. I was so inspired by it that in my seat, I got to be out with these people a lot because they were curious what activity was going on in the trading desk and what it meant for them and their investments. And I was always interested in learning more about how did they build and back these companies. And what I came to quickly realize in talking to all these people from all these different investment firms was that their strategies were actually very similar. I said, knowing what I know about derivative securities and that I had learned from my days at MIT, my time at Merrill Lynch and recognizing that most people in the life science investment role were just using equity securities, it struck me that there was a better way to build these portfolios and select securities, ways in which we might be able to either maintain the type of return that they needed for their investors but at lower risk or maintain the risk and produce a higher rate of return. I went off and I spent my nights and weekends writing this beautiful deck that I thought really cracked the code on what portfolios needed to look like in the life sciences sector would allow a scale of capital to get behind these amazing medicines that had never before been achieved. When it was done, I could not wait to send it out. I remember telling my roommate, Dom, I was like, Dom, I'm ready to send this out. I'm going to send it to everybody and you just watch. My phone is going to be ringing off the hook. Everybody in the world is going to want to do this and put this strategy to work. My days at Merrill Lynch are numbered. I'm going to be out of here soon enough. I sent it out, crickets. I didn't get one single response and I couldn't believe it. I was like, how does nobody want to do this? How does nobody want to run a portfolio that can produce the same amount of reward but with lower risk or produce more reward? It didn't make any sense to me. It turns out that months went by before my phone finally rang, but then one day it did and it was just today, a dear friend of mine and mentor, Jeff Kaplan who was the head of trading at that time in 2005, a tiny little firm named Deerfield Management. In its early days where Jim Flynn had just taken over as general partner. Jim was a really unique leader of Deerfield because one of the things that I learned from spending time with him was he obsessed over, what is every which way by which our investment firm can have every type of advantage in producing our returns so that we can attract more and more capital and have more and more impact on the future of human health. How do we create advantages that would allow Deerfield to become the epicenter of capital to move innovation? I got lucky. I found the one person in the world who cared about the things that I had to say. After going and presenting on my ideas there for what at that point, which was a tiny team of about 12 people, I got hired to join Deerfield and I spent then the next 15 years of my career helping to build Deerfield into that dream state of being the go-to source of capital for the industry. I didn't realize it at the time, but I guess I was 24 when I joined and I think the next youngest person at the firm was probably 40. These are all people that were super seasoned, had incredible experience and I think I was a bit of a novelty in the room because I would ask almost a thousand questions every single day and these amazing people would spend the time to teach me. And so the apprenticeship that I was able to get from my time at Deerfield was like nothing I could have ever imagined. And I was all fully in love with investing in building and backing anything, whether it was a medical device, a diagnostic, a medicine, anything that could move human health forward. That spanned everything from helping these companies figure out how to finance their innovation, all the way through to spending time with our team on, how do we design and help a company design a clinical study in a way that would give them an advantage to showing something that's really special. That stayed true for about the first decade of my time at Deerfield and then something just really, really tragic happened. At Deerfield, we were constantly building capabilities and constantly wanting new sources of data. And one of the sources of data that we had acquired and had built out was now taking us deeper and deeper into understanding a patient's journey from the moment where they are prescribed the medicine to where they actually get the insurance approval to get that medicine and then how long they stay on the medicine. And of course, we all know medicine only works if we take it. And what I was quickly learning about a decade into my obsession for all the amazing work that was going on around me is that, yes, medicine only works if people take it, but they weren't. That was a really dark period for me in my own journey because as I was reflecting on all the time and effort and capital that I was a part of putting behind innovation, it became pretty quickly evident to me that you have to start asking the questions, for what purpose, if people need to be on a medicine for the rest of their lives, and they're taking it for a year on average and then quitting, are we just optimizing for maximum expected returns but no impact on public health? I had been married at the time. I got married in 2012, so I'd been married for some number of years and I started thinking about, what does my life mean and how am I as a partner to my wife if I'm spending my time just focus on making money and not actually doing something that can move the world forward? We had had our first baby at that point and I was reflecting on just how impactful my parents were in terms of teaching me, and what they armed me with as I went forward and was like, well, what lessons would I be teaching my daughters? I got to the point where the combination of thinking across all of those dimensions made me the question, am I just doing the wrong thing? Do I need to go in a different direction? The answer was no. What I needed to do was take the innate entrepreneurial energy that comes from my upbringing and from my childhood, the skill set that I was able to develop from this amazing apprenticeship that I had at Deerfield, and be able to point those talents not just at the discovery side of being able to have invention, but be able to point that at the impact that's required to actually see these medicines have the impact that they're intended to have. A lot of that was my inspiration for leaving Deerfield and wanting to go build Braidwell. I'm so fortunate because one of our dear friends, Brian Kreider, who's an incredible person, he's an amazing husband, father, incredibly talented business person, was also just as inspired as I was about where we found ourselves in the world and the type of impact that could happen but wasn't yet happening. He was the Chief Operating Officer for Bridgewater. I was co-running Deerfield and we decided to spend some really deep time trying to put our lessons learned and our insights together and try to design from a first principles perspective, what would the operating system for human health look like and what could we do to be the driving force behind making that happen? How could we be the force that is not just okay with a once in a decade, $100 billion GLP-1 revolution, but how do we be the force behind making sure that this once in a lifetime, trillion-dollar cost savings revolution happens because we can be the force behind medicines, having their moment where they can prevent diseases that are already preventable today. That really inspired us and after seeing it, we couldn't unsee it and then we spent many more months thinking about, well, how do we go do it? How do we build it? That became Braidwell, where I'm spending my time today and we're having the most fun that we've ever had.

Speaker 1:
[88:38] If you could sum up the investment approach in its simplest form, how would you do it?

Speaker 3:
[88:43] I think I just bring you into what we call our morning meeting. At Braidwell, we get together the team every morning from 9.15 until we're done. I want you to imagine, so you're in this room, you've seen it, so you're in this room, it's a big room and we've got an amazingly talented team of scientists, biostatisticians, commercial experts, AI experts, investors, operating people, traders, structured finance people. We have a pretty significant team. Everybody on the team has some special superpower that they contribute to us trying to figure out what companies have amazing technologies that we should be getting behind and backing and helping them to go as fast as possible to have human impact. That cuts at some of those big unlocks that would be the difference between having something and having it have its impact. And then as we get to look across the ecosystem of everything that is moving forward today, where do we also see the major gaps where medicine should exist, but they don't yet? To me, being in that room is the most fun part of the day. And I think it very much epitomizes what our philosophy is, which is that in order to be a great backer of innovation, we essentially need to be able to answer three questions. Are the innovations we're getting behind going to work or fail? Are they ultimately going to be relevant from a market potential or not? And is there a way by which we could back this company, invest in this company, enable this company to move forward faster with capital that produces a return that's attractive enough for the investors that are trusting us with their capital? We want to bring together the most talented minds at each of those different areas of domain expertise to give us an advantage that we can in a replicable manner deploy day after day after day to both be backing the companies that should be moving forward faster and making exist the companies that don't but should.

Speaker 1:
[90:33] It's an incredible room to be in. It makes me wonder if everyone could design their own room to be in from 9.15 to whenever every day. It'd be a fun exercise. I know you're also a builder. We'll save that discussion for another time. Unfortunately, we're out of time. I have pages of notes. You and I do this every time we talk. We set aside an hour. We should set aside a day. I'll go to my traditional closing question for this session. I'm sure we'll do this many times together over the years to come. What is the kindest thing that anyone's ever done for you?

Speaker 3:
[90:59] That's my wife. I'm pretty darn hard at it every day. Every minute of the day, I can be hard at it. That drives me to different levels of stress, and I could be so myopically deep down trying to figure something out, that I just lose track of everything else around me. My wife, Cass, has this amazing ability to just know when I'm at that, just on the precipice of that breaking point, and she could find some way to distract me, make me laugh, and get me back to neutral. And I think that's a big force and an advantage for me, because I don't have to worry about going so hard, because I've got a partner that's right there by my side, that can help make sure that I could not just be going after the things I really care about doing, but having some fun along the way.

Speaker 1:
[91:40] Knowing Cass, I know that's true. Alex, thanks so much for your time.

Speaker 3:
[91:43] Thank you, I had a great time.

Speaker 1:
[91:45] If you enjoyed this episode, visit colossus.com. You'll find every episode of this podcast complete with hand edited transcripts. You can also subscribe to Colossus, our quarterly print, digital and private audio publication, featuring in-depth profiles of the founders, investors, and companies that we admire most. Learn more at colossus.com/subscribe. Your finance team isn't losing money on big mistakes. It's leaking through a thousand tiny decisions nobody's watching. Ramp puts guardrails on spending before it happens. Real time limits, automatic rules, zero firefighting. Try it at ramp.com/invest. As your business grows, Vanta scales with you, automating compliance and giving you a single source of truth for security and risk. Learn more at vanta.com/invest. Ridgeline is redefining asset management technology as a true partner, not just a software vendor. They've helped firms 5X and scale, enabling faster growth, smarter operations, and a competitive edge. Visit ridgelineapps.com to see what they can unlock for your firm. Every investment firm is unique and generic AI doesn't understand your process. Rogo does. It's an AI platform built specifically for Wall Street, connected to your data, understanding your process and producing real outputs. Check them out at rogo.ai/invest. The best AI and software companies, from OpenAI to Cursor to Perplexity, use Work OS to become enterprise ready overnight, not in months. Visit workos.com to skip the unglamorous infrastructure work and focus on your product.