Jim Tananbaum of Foresite Capital joins Nick to discuss From Data Science to Drug Design: How AI Shifts Discovery, Target Validation, and Portfolio Construction. In this episode we cover:
- Data Science and Investment Approach
- Investment Practices and Market Conditions
- China’s Role in Biotech and Regulatory Considerations
- Impact of AI on Biotech and Healthcare
- Healthcare Adoption of AI and Preventive Measures
- Payers and Insurance Companies’ Role
- Lessons from Successful Investments
- Generating Liquidity in a Sluggish Market
- Future of GLP-1 Agonists
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0:17
Jim Tannenbaum is back on the program and joins us today from Los Angeles. He’s the founder and CEO at foresight capital, a multi stage healthcare and life sciences investment firm with over 3.5 billion. AUM, before founding foresight in 2011 he co founded gel text pharmaceuticals acquired by Genzyme for 1.6 billion and Theravance, which went public in 2004 Jim, welcome back,
0:44
Nick. It’s so great to be back. It’s hard to believe it’s been eight years finished like 30.
0:49
It does. It does. We’ve seen a lot in these past eight years. Well, it’s good to see you again. And it was fun catching up before this last we had you on the show was 2018 so bring us up to speed. You know what’s changed about foresight? What’s changed about the thesis and your focus over the past seven years?
1:05
Wow, seven years. Boy, it’s been a an eternity. So let’s see first, when we were talking back in in 18 the markets were steadily improving. We were, you know, full blown in what became a boom cycle and life science generally, was thriving, as well as biotech Life Sciences being defined as the tools that are used by researchers and developers and generating the biotech products. Then covid hit, and the world went to a screeching stop. But then it rebooted around healthcare, so, so we had a boom, then an abrupt bust, and then another boom in 20 in the second half of 20 and 21 really, anything that that touched covid, you know, got a lot of speculation. And we saw companies like moderna hit, I think, you know, 100 plus, maybe to even more billion dollar market caps. Pfizer, I think, has had its peak price all around the vaccines, and we certainly had a number of things that rose in the bubble of covid and then interest rates started, and that has just had a profoundly negative impact on our industry, and the reason for that is, anything that’s long dated, like really long data, like biotech investing or long term healthcare investing, you start applying an interest rate that is 5% that’s just so far beyond anything that anybody had ever thought about it over 10 or 15 year period of time, it changes your multiple by three to four fold. So we saw, you know, a 75 you know, plus percent compression across the boards in all of the way that people were valuing our enterprises. So so that, you know, that’s led to a lot of rethinking over the last few years about how to finance the types of companies that we work in, but also how to help the companies that were financed prior to that survive. And number of them haven’t, but number of them will, but no doubt, the very difficult financing environment will impact performance for, you know, sort of funds that are vintage year 2021, you know, that sort of run, run right into the 22, 345, you know, interest rates. And then in the background, there’s been AI. And AI has been a theme we talked about seven years ago, and, you know, it becomes a theme that I think now the world is waking up to, but we’re still incredibly early with regards to the impact that it’s going to have, even over the next few years. So I think that’s going to be a macro theme that really pervades the venture capital markets as well as the public markets, and that is yet to play out, except for at the very, very top end, with large tech companies. Good.
3:59
So I know that you’ve always had this strong data orientation as a firm in your your website even says that we use data science, a data science driven approach, to invest in companies that leverage biology and big data to transform healthcare. Tell us a bit more about that. I mean, clearly, there are advantages in this new tech wave that we’re in, but unpack a bit about this data science based approach to investing.
4:25
Well, you know, seven, eight years ago, we tried to systematically do both company sourcing as well as company analysis using a combination of in house MDS and PhDs, coupled with with tools that would help make them more efficient. The fact is that the tools back then weren’t good enough to have a huge impact on, you know, on our investment performance, and I would still say that the tools are evolving today that would have a huge impact on our investment performance, but it’s been something that we’ve aspired. To over years, and then we measure objectively, and objectively, it hasn’t led to, I don’t think, increased performance as of yet, but I think that it has led to some very, very exciting startup companies that we’re involved with that are, I think, changing the performance curve, or beginning to change their performance curves. And I do believe it will make its way into our investing framework, and we continue to revisit that. It’s just still early days. And then simultaneous with large language model tools and automation and other things that we’ve looked at internally, we also had a program where we absorbed global data and looked at genetic patterns and other things that we could pick up, and we were, I think, to the best of my knowledge, we’re the only investment firm that that that that’s set up to do that, is set up to do that, and that target validation work that comes genetically does help us gain confidence in things that we invest in, I wouldn’t say has, and actually has driven some investments that we’ve done. I wouldn’t say that it’s a dominant factor right now. But when you when you couple that with what large language models should be able to do and the type of automation that you know should be able to be done, you know, I’m hopeful that over the course of the next year or two, you know, we’ll have a new member of our team that is AI powered, but, you know, that’s still right now, something that’s that’s on the drawing boards, good.
6:24
And I know you do a share of public market investing, but what is the primary entry entry point, you know, for VC, for the firm? Are you investing mostly at series A and
6:34
B? Yeah. So we have an early practice and a late practice, and the early practice tends to go at startup level for things and helps assembles companies. We have an incubation platform called foresight Labs, which is really centered around large scale, AI, incubation works and Xera X, A, I R A, which was a product out of forsyt Labs last year, would be an example of the type of builds that they aspire, you know, to do. So we have some that we bake ourselves internally, with a bias towards internal work being done in foresight labs, and then some that we work with entrepreneurs that we’ve worked with for years as they start up companies and and, you know, there’s really nothing Nick better than a great entrepreneur to get behind when starting something up. And then there’s a late stage practice that we have that also tracks entrepreneurs that are in our network, as well as other companies that we’ve come and looked at. And that late can be, you know, pre public. It can be public. And there we’re looking for real products that we can wrap our, you know, arms around as being best in class in their respective categories, and and, and there we’ve had a very consistent record. We’ve been doing it for years and, and frankly, in this market, it’s fantastic market to be investing in that type of category, because the market’s so compressed that you’re really getting to invest in later stage, you know, sort of opportunities with a lot of risk taken out of the conversation at pricing that, you know, was was full, you know, risk, a pricing of a few years ago. And when the markets recover, and they will recover, they always do, those will be the first to to really, you know, help demonstrate returns from the cycle.
8:14
So is that the bull case on investing in biotech currently? You know, in the you you mentioned the interest rate environment. You know that’s creating some headwinds for long cycle bets. But I guess the counterpoint is it’s a good buyers market.
8:29
Yeah, it’s a great buyer’s market. It’s not just a good buyer’s market, it’s almost an unprecedented buyer’s market for later stage deals. And then there’s actually, there’s another factor that is worth mentioning as well, which is China. And China has really put together a first rate biotech effort. And, you know, one, one way that that could manifest itself is Chinese companies growing up as global pharmaceutical companies, and the Hong Kong stock exchange is starting to have a boom now, and that’s, you know, that’s, that’s possible and, but there’s another way that that could manifest itself, which is the way that it had been up until recently, which is that the assets coming out of Chinese companies can be bought by us biotech companies. And that’s been a, you know, a really interesting source of product for a venture capital industry as well as the pharmaceutical industry. And when you look at wholly bought versus licensed, yeah, I mean by the by the license the product, or, you know, wholly buy the asset, yeah, wholly buy the asset. So you own the patent, you own, you know, everything. Maybe you give back the China rights as part of the deal. But so it’s kind of like adopting a baby from China, you know, like the baby’s yours, and the baby may, you know, the parents might have visitation rights, you know, in China, you know, once a year or whatever, but, but I think the that framework is has led to just increase. Global Competitiveness for product development. But the, you know, the major capital sources for and the expertise in, you know, growing and building biotech companies still seem, you know, still is in the United States. So it’s led to, you know, a an opportunity, effectively, for those companies to buy products more efficiently than it would take to set up the build in the US, and there’s been some talk about creating regulation around that. And I personally think that would be a huge mistake for American competitiveness, because then all those products would just go to Europe and other places around the world. And there’s no stopping the innovation that’s going on in China. We’ve, they’ve, they’ve outdone us in terms of their being able to produce for, you know, you know, low single digit millions of dollars drug candidates, but, but over time, America, you know, can out compete China through AI and next generation technology and, and that’s the way the free market works. So, so hopefully, you know, the regulatory side of this, won’t, you know, get involved in confusing free market, effectively, from, you know, from, from what’s been going on.
11:07
So if you buy or or license an asset from China, does it have to go through a new set of clinical trials here in the US? Or is there a set that’s similar in China that, you know, you can get some sort of equivalency on?
11:21
Well, so China’s clinical development is always it has, has, until recently, you know, been a question. So if you’re buying something in China, you want to, you know, if you’re doing it based upon something that’s preclinical, you want to, you know, validate all the pre clinical work. But the pre clinical models and stuff that they do over there in the very best shops are now first rate. There’s still a wide variation. There’s a lot of, you know, crap all around the world. You know that that gets done, but at the very highest levels, China’s pre clinical quality control is, you know, at standard with the Best Global quality control standards. Now clinically, China, over the last year or so, has made a real concerted effort in Shanghai and a couple other places to put together very high quality phase one and phase two, clinical, you know, sort of frameworks and, and I believe they’re going to generate very good data. They have all the right quality controls around them. And, and, you know, we’ve, we’ve started to work with some of them, and been pretty impressed with what we’re getting out of it. Now, the FDA, you know, being a global, you know, will accept data globally, but, you know, wants to avoid bias. So you know, if you’re taking data from China, you have to take it from other places, and equality control standards have to be, you know, very, very high at every place that you’re taking the data from. And the FDA, you know, also needs to, you know, be able to inspect sites and other things. So there are barriers when you get into registration that make you not want to, necessarily. You know, lean into China, although some companies, some global pharmaceutical companies are now as much as maybe a quarter of their registration trials coming out of China. But again, that requires very, very strict quality control in order to pull that off. But I think the big picture trend is that China becomes a very good place to do product development through phase one, phase two, and then you can buy the assets at that stage and then develop them globally. And that’s that’s been, you know, sort of the trend over the last couple of years,
13:28
you know, I guess while we’re talking about the FDA, there’s been some turmoil there over recent years and some uncertainty. How are you thinking about underwriting, trials, commercialization, et cetera, when you know, the guard rails and the goalposts seem to be shifting
13:45
well, So first I’d say that what we’ve done across the board is just try to, you know, work with our companies to have a very high data quality standard and very high standard for registration work, and that I believe trumps everything. I happen to believe that this FDA administration is is going to be a good one and, and frankly, the you know, there’s a real chance that they end up approving products, you know, more products than you know previous administrations have done double tell, but, but you know, there’s no doubt will be variations in a way that they operate over the way that prior administrations have operated, and at the end of the day, you want to sort of get out from under that noise with quality. So I think just investing in doing things right goes a long way with the agency, and also goes a long way in between various administrations there sort of staying above the nuances of subtle changes that are
14:43
made. Jim, you’ve mentioned AI a couple times on the show. We talked about data. Talk to us about how you think it may impact different phases of risk, you know, throughout the biotech process, you know, from drug discovery to clinical trials to prevent. Care, etc. Yeah, tell us more about how you’re looking at AI and its impact there.
15:05
Well, ultimately, you know, you’ll have drugs designed completely by AI. Now, you know, are we three years away from that or 10 years away from that? I can’t tell you. You know, that’s, that’s what Zara is aspiring to, and and isomorphic. And those are very big bets. They’re very require, you know, the right level of capital investment in order to pull off the effective infrastructure that’s needed to, you know, move from the physical reality into another virtual reality and a place where, you know, there’s a lot of still art that goes on in drug discovery, but it’s our belief that with the right amount of data and the right people that have expertise and you know, can you know, the biologist and the AI engineers are on equal footing and can talk and work with each other properly, that over The course of the next, you know, you know, reasonable number of years we’re going to see drug discovery move, you know, into an AI, completely AI setting. And that will be very exciting. And what that will mean is that we’ll short circuit the, you know, the rate amount of time that’s spent testing stuff in a lab and doing all the work that gets you to a product that goes into mam you know, it’s also over time, I think going to be easier to pull out the populations that are affected by a given disease driver, and as global populations get sequenced. And you know, that’s something that’s starting at scale for the world right now. You know that that will be easier and easier to match patients with with products. It will also, as the world gets sequenced, be easier and easier to pick up disease risk at an individual level. Because you know, our genetics determine our disease risk, but then also the change in our genetics determine, you know, whether we’re developing cancer. And so those are things that can be picked up through routine blood work or and that will help pick out disease at a much earlier state, get us into a prevention framework. So we as individuals, know, you know, like, I have risk for cancer, so I need to screen more frequently, and I have risk for, you know, sort of, you know, heart attacks, so I need to lower my cholesterol, you know, more aggressively and and I think that will be the major driver for longevity across our population. And, you know, I do expect to see using these tools where you can push off disease, you know, getting to a, not, you know, 90, you know, mid 90s, you know, like, as you know, a healthy, you know, sort of target age for the population. I think we’re going to see that in our lives. And that’s, that’s huge, you know, that’s, that’s, you know, 1015, years of longevity, you know, beyond where we are right now, yeah,
17:53
what? What else needs to happen on the healthcare side there, like you’ve mentioned, sequencing population, you know, seeing how biomarkers are changing. It still feels very episodic to me. You know, if I’m good, I’m seeing my practitioners once a year and getting my test. But are we going to see kind of more consistent, persistent measurement models so that we can, in real time, identify, you know, abnormalities, yeah.
18:22
I mean, like at the end of the day, I think that, you know, it’s we now have at our disposal the tools to help us all catch disease a lot earlier. And for many diseases we can, we can eradicate the disease or push it way off if it’s caught early. So then the burden becomes, you know, a combination of, how much do we want to push ourselves to gain access to those tools as a consumer, and how much will the healthcare system, you know, make it easy for us to, you know, gain access to those tools? And, yeah, I think the latter conversation is, is going to take some time, because, you know, healthcare is very, very slow moving, and reimbursement, you know, sort of cycles are very long for healthcare, but nonetheless, it’s the right thing for the world. And the truth usually is a sticky thing. And so over the course of the next 10 years, I do believe that these tools will be increasingly adopted as part of mainstay healthcare. You know, for example, the Grail cancer test, which is now eight, $900 a test. You know, when it’s three, $400 a test, and when there’s more data that shows that it picks up half of undiagnosed cancers and is highly accretive for people that are in the higher, higher risk, you know, sort of cancer category, which you know is a very sizable amount of the population, you know, that becomes routine, you know, for people that are higher risk and and we’re still, you know, a few years away from that. But those types of things, again, will have an enormous impact on picking up cancer earlier in people and staying with heart disease. Europeans just lowered their L. LDL requirements substantially, and that’s probably the right thing for the whole population, because it there’s very little downside to lowering LDL further than the current American Heart Association guidelines. However, there’s, you know, 8% of the population that really are the ones that really need to lower their cholesterol. So, you know, over the course of the next few years, with genetic testing becoming more pervasive than like a genetic scan will be 10s of dollars. It should be part of the routine, you know, sort of healthcare data that’s collected. But then, you know, an individual will know, hey, you know, I’m at risk for heart disease. And then it, you know, becomes a combination of the burden being on the doctor and the the individual. But you don’t need to manage this on a quarterly basis, or, you know, or even a, you know, semi annual basis, you know, once a year, you know is, we’ll pick up a lot of stuff and and so then you know if you’re, if you’re not, you know if you’re, you’re just ignoring this altogether. You know that. Then, then, you know you probably, life expectancy is probably going to be more in line with where life expectancy is today. And and the world will get educated on this in the same way that they got educated on cigarette smoking and and so, you know, I think over the course of the decade or so, populations will start to adopt a different mindset, and it’s not a huge burden. So, you know, doing something once a year not a huge burden.
21:23
So I’d love to get your quick input on the payers in the insurance companies. So price per test for a variety of things is a huge factor, and as that drives down, that’s going to be a big motivator. But we’ve seen just in our portfolio, we do a fair share of healthcare, mostly software investing, we’ve seen motivation from the payers to push solutions down to their populations that really drive down overall cost of care, especially for high acuity patients. Are you seeing that as well? Is that becoming more of a strong trend in the industry, you
22:01
know, good question. I wouldn’t say that it’s a strong trend, but I would say that it is a trend, and payers are playing around with this. We’re still not seeing, you know, sort of broad early adoption, you know, of technologies that are creative effectively this system. We’re seeing, you know, barriers to demonstrate creativeness that take years to work through. But there are, you know, more and more plans that are on the early adopter side than have been. But I would say that it’s, it’s not a, it’s not a, it’s not going to change the physics, you know, of having to do very expensive, long range, you know, you know, pharmaco economic or or genetic economic, you know, sort of studies
22:45
I see, I see so you’ve, you’ve invested in many companies, some of which were big, big winners. You founded some companies that were, were big winners. You know, as you think back and look back to investments in companies like hims or tennis genomics, or veroni Pharma. Can you tease out maybe some of the lessons that these winners revealed about platform risk, reimbursement, risk, Team risk, you know? What are some of the more salient takeaways?
23:16
Okay, so, you know the first, I think the biggest takeaway as a fund manager. And I think this is a place that is a little counterintuitive. So you have a company and it’s up 10 times your money, but you love the management team, you love the growth prospects, the you think the product is best in class by far, and, and, and you know, yet the instincts are, well, I’m up 10 times for my money, I can’t get up another 10 times my money. So, you know, time to sell. And that’s the way that I think the vast majority of the of the world, you know, ends up managing things. There’s another mentality and framework which basically says, No, I I want to keep the winners. I want to hold the winners and continue to to ride those winners. Because, you know, 10 times is a good predictor. You know that there’s another 10 times again. It’s a market size conversation, but I would say that you know something, that you know those companies. For us, we’re companies where we love the management teams. The execution has been excellent. The markets have been big and and we had really great appreciation, and we just decided to hold the winner that that was a winner in the portfolio, and we were going to ride it for a while. Now, you know, when you make that type of a decision, you have to continually revisit, you know, the question are, you know, the conditions, the assumptions that I’m making all the same a management team hasn’t changed. Well, that’s a big one. But sometimes, you know, markets slow, you know. So for example, with 10x genomics, the market, you know, sort of just popped out and, you know, and then on top of that, over the last year or so, NIH funding has gone through a huge change. So there’s been a number of you know, sort of things that ultimately. Hit the upside, you know, of that company, whereas with hims and Verona, Verona is now being bought, you know. So that was, you know, sort of played out until it got bought. And, you know, I have to be careful about promoting public stocks, but, you know, at the end of the day, I think the management team at in hims has done a fantastic job growing that company and their best in class. And, you know, every quarter they continue to to beat their earnings and sometimes even adjust them up and and there’s no end in sight to the scale, you know, of that company. So, so that would be, I think those are, those are the, I’d say, the simple framework we look at, you know, when we’re trying to figure out whether or not something really gets into that winner category.
25:45
So you mentioned, like the 10x exit and, you know, hold sell. Talk to us more about how you think about generating liquidity in a, you know, overall sluggish market, and how one sort of engineers some dpi, when they have a winner, but they’re facing some of these tough decisions.
26:06
Yeah, you know. So, you know, interestingly, we, we ended up distributing so, so, first year as a fund manager, you’re also, you know, constantly weighing getting money back to people. And there’s two ways you can get money back to people. One way you can get money back to people is, is with cash. And the other way you can get money back to people is with an in kind stock distribution. We, you know, our threshold to doing in kind stock distributions are, are high and, you know, but with both 10x and Verona, while 10x was rising and Verona was rising, just over the course of this year, we did in kind stock distributions because we felt there was upside. And I think we distributed Brenna at 30% you know, where it ultimately ended up getting bought. So people held the stock, you know, they got a nice, you know, sort of reward for holding the stock. The flip side of it is, it was distributed at around, I think, 14 or 15 times cash, you know. So it was, you know, a good, a good ride for those that, you know, wanted to sell the stock, but, you know, we were dealing with a lot of uncertainty in this the first and second quarter, and something we thought was a really, you know, sort of good performing company against the backdrop of, you know, not having a lot of distributions over the last, you know, couple years or so, so, you know, we kind of decided, all right, well, the right thing to do here is to, is to distribute deep, you know, get some money back to people, but do it in a way where people can, you know, effectively, democratically decide what they, you know, what they want to do at this point. And if anybody called and asked me, I would say, I’m holding it, you know, and so, but that’s a real pressure we live under. The flip side of it is we wouldn’t be distributing that stock, you know, in the first quarter, or the, you know, the fourth quarter or the third quarter, when we were under a lot of pressure to distribute that stock. But at that point in time, it was 5x appreciated and not 15x appreciated and and we still felt that there was a huge, huge, huge, you know, way for it to run. So we have a number of public stocks in a portfolio right now that we’ve held on to for quite some time. And you know, those have been a big, you know, we feel big potential, you know, sort of upside, but yet not realize that upside. So rather than, you know, sort of taking chips off the table prematurely, you know, we’re in long term lockup vehicles. We get paid to hold stuff. And, you know, people are really looking for cash on cash returns. So that’s, that’s the way that we’re managing it, despite the fact that people are also looking to get steady returns.
28:30
When you say that the threshold for in kind distributions is high, does that mean on a multiple basis, or what exactly does that
28:37
mean? Generally? Generally, yeah. I mean, I think that if you do something in kind you’re certainly going to want a lot of volume there. So people don’t, you know, get hurt if they decide to get out of something. I see. So if we have something that doesn’t have a lot of volume and it’s time to get out of it, we’ll, we’ll spend a month or two whittling it down in a way that doesn’t affect, you know, minimizes the impact on the stock and and maximizes our, you know, our liquidity and the situation, and we’ll just get the cash back to people,
29:04
you know, Jim, I was, I was reading about 10x genomics recently, and they were flagging a tightening academic funding environment. Do you expect tool and platform companies to face face like a demand air pocket as research budgets contract?
29:20
Yeah, so I think there’s a lot of uncertainty there the research. I think that the overhead sort of conversation is going to evolve and, no doubt, go down, whether that expresses itself in other ways, so that the same tools are bought. I can’t tell you for sure.
29:36
No crystal ball over there. Jim, yeah, but
29:39
what I would say is that we’re more biased these days towards software, you know, sort of than hardware. I think, as big a player in the life you know genomics, you know tools as well as genomics data interpretation. You know, sort of products as well as other you know, sort of research and development and diagnostic. Sort of categories. But I think that stepping back from it, you know, the hardware has just been a difficult place to be and and if there are a couple players you’re, you know, in a race to the bottom, whereas the software and things that AI, you know, can do open up a lot of leverage and a lot of scale. So, you know, so we’re, we’re more biased to be looking at the software side of the conversation these days than and we are the hardware side,
30:26
you know, Jim, if, if the slowdown does materialize, like, what would you suggest for founders with regards to, you know, pricing, packaging, financing strategies in order to kind of weather that
30:40
slowdown, I think it’s going to be, it depends on, you know, where they are, but generally speaking, I think you have to take a look at the time to get to lift off, and how much money requires to get to lift off.
30:53
And is that a way of saying reducing the primary risk?
30:58
Yeah, when I guess, I guess, when I say liftoff, I mean profitability and and real growth. So like, like, you know, like, ideally exponential type growth, you know, growth where you take over a segment of the industry, and that’s, that’s a hard conversation now for life, science, tools entrepreneurs, because there’s all this friction in the market for adoption and and so maybe the markets are slower and much, much more slowly adopting. And then, you know, you’re burning cash until you get to that point. So, you know, and and time. So you know, it’s very challenging. And I think entrepreneurs need to really think through how much time, how much money is it going to take until I can get to a place where I’m I’m self sustaining and growing nicely. And I think, you know, if entrepreneurs take a hard nosed look at that, there’d be a lot less competition in those spaces. Because the, you know, the bar, you know, is really high, and then with less competition comes better outcomes for people, more capital available for the few that are doing things. So, you know. So the advice I’d give to the entrepreneur is to be patient, but to recognize that it’s going to be a slog, a long slog, and really, you know, make sure you have super high conviction, because you may have to play that conviction out over years of no love. So for if we’re
32:27
talking about long term winners, you know, I recall last time you were on the show, we were we were discussing biotech, and you talked about kind of long term value creation and building franchises that are hard to displace. I’m curious, you know, in 2025 What do you see as the pillars that sort of underpin a really successful franchise, versus just one winning drug?
32:54
For instance? Yeah, well, first, I think one winning drug can make for a very successful franchise. So fair enough, I wouldn’t discount the power of that. And you know, ultimately, you know, the winners of every generation, of every any time, are really defined by a single product that you know, that that drives, you know, their growth. So I do think that there’s no getting around you need something that’s best in class, best in the world. You know, to, you know, sustain billions of dollars of value creation. Then, you know, management obviously factors a lot into things. There’s a lot of judgment calls, decisions that that lead to that best in class product, or that lead to something being almost best in class. And almost best in class is not best in class, and there’s just a increasing spread these days between the winner and everybody else. So, you know. So I think it’s a combination of having the right, you know, hand and then playing the hand properly. So it’s the you know, combination of the asset and the management team. Now, the asset can be created the old fashioned way, and, you know, and that’s the vast majority of the assets that are, you know, now in front of us, or it can be created, you know, by a computer. You know, who’s you know, who’s developed the insights that humans haven’t developed, and that’s not yet, you know, in front of us, but it’s coming.
34:12
Jim, you know, before we wrap, give us a prediction on GLP ones, some sort of prognostication on, maybe something non obvious that you think may play out in that space over the next three to five years.
34:28
So first, I’m a big believer in GLP ones. We’ve been, we were in that, you know, sort of category going back to 2012 when we first started. Wow. So, so, you know, we’ve been a huge believer in the category and GLP one basically as a pro as a drug, it increases every cell in your body’s insulin sensitivity. So it works not only on reducing fat, but it also works on making your liver more efficient and your kidney more efficient, and nerve cells more efficient. So I think it’s being understood now that it’s a Gen. Or a longevity product. It’s a, you know, excellent, excellent product at pushing your cells back to a younger state, so to speak, or a state where they process insulin like they used to. So I think there’s a lot of upside, you know, to the product. I think you’re going to see corals come along, and I think you’re going to see it being used very pervasively in society. I think, every bit as much as you see a statin some Metformin. So I think that this still has a long, long way to go in terms of its use. Now, on the downside, there are downsides for sure, with any product and nausea and you know, and diarrhea and constipation, depending upon which side you know, of the side effects you’re on are all been reported with GLP ones. There is muscle, you know, sort of wasting that some people report. In particular, it can take fat out of places like your face. So, you know, there’s, there’s empic face, you know. So these are all, there’s some cosmetic, you know, downside to it, you know, from a, from a, from a muscle point of view, you need to, you know, really continue to, to push on your workouts. If you’re taking the product, there’s one very long term effect that has popped up through retrospective analysis, and that has to do with, I think it’s macular degeneration risk, but that’s the retrospective analysis. Are very, very hard to because they often can, you can often get full, you know, by statistics of of random things when you look retrospectively. So that’s something that’s prospectively being looked at by, you know, by regulators. But, you know, the products have been on the market for quite some time. And if there is a signal for macular degeneration, or whatever the optical issues you know are, they’re very, very, very, very small signals. And then you have to weigh them against the benefit of reduced heart disease, cardiovascular outcomes, superiority, which means you live longer on on the product and so so I think the punchline is that GLP ones are are a product that helps us live longer and healthier. And there are some drawbacks, but they’re really minor. And if there are more major drawbacks, they’re going to be in a very, very small percent of the population. So, you know, there’s something that you know always to keep an eye on. But I do think that over the next three to five years, you’ll probably see just continued growth of the product category.
37:31
What percentage of the population do you think will be on GLP ones in five years?
37:36
I think a 20% of the population over 50. Wow, it’s already quite high. Yeah, I was gonna say maybe this, maybe this a little high, but, you know, 15 20% I think that’s about right.
37:48
Yeah, interesting. Jim, what book, article or video would you recommend to listeners?
37:53
Well, I, you know, I really enjoy the all in podcast, which is done by a friend of mine, Davis Sachs, so a plug for that. But, yeah, I listen to podcasts. I don’t. I don’t do as much reading as I should these days, because I have so much technical reading that I end up doing every day.
38:10
Got it, Jim, do you have any habits or behaviors that are a secret weapon?
38:15
Well, I think I’m very persistent and and then I’m also very loyal. So I think, I think those are good, you know, sort of long range behaviors I have. Tend to have very, very long term relationships. You know, they’ve lasted forever. I’ve been married for 33 years. I have my best friends I know, from kindergarten and so, yeah, so those would be perfect. So, all right,
38:36
and then last year, what’s the best way for listeners to connect with you and follow along with foresight?
38:40
Well, you know, they can always look at our website. We do update it. I’m on LinkedIn, and I think those are probably the best ways Awesome.
38:47
Well, he is Jim Tannenbaum, the firm is foresight, Jim, it was so much fun to run it back. Thanks for joining
38:52
us. Thanks, Nick, thanks for having me again. It was a pleasure. Appreciate it.
39:00
All right, that’ll wrap up today’s interview. If you enjoyed the episode or a previous one, let the guests know about it. Share your thoughts on social or shoot them an email. Let them know what particularly resonated with you. I can’t tell you how much I appreciate that some of the smartest folks in venture are willing to take the time and share their insights with us. If you feel the same, a compliment goes a long way. Okay, that’s a wrap for today. Until next time, remember to over, prepare, choose carefully and invest confidently. Thanks so much for listening.
