Novartis CEO on the Future of Medicine | a16z Full Interview

We unlocked almost $180 billion of value. Took this company that was a conglomerate and we turned it into four companies. We had these other businesses, but it was never really the core of kind of who we are. We were misallocating capital. Spinning off companies sounds easy in retrospect. Actually spinning off three public companies is a massive, massive undertaking. You can rewind a disease or completely in some cases almost create a functional cure for patients. One of our sentinel patients was an individual in bed all the time receives our cell therapy. 6 months later, no sign of disease. I mean, this is extraordinary. Cell therapies and immunology alongside immune reset, bispecifics, trispecifics. That is going to be a whole renaissance for cell therapy.

It's great to be back. Thank you.

Yeah, absolutely. So Novartis is a 250-year-old company that's been a conglomerate for most of its history, but I think we'll talk about it over the last 10 years. We really focused it down as a pure play medicines company. We reach about 300 million patients around the world. We operate in over 100 countries, over roughly $55 billion in sales, nearing a $300 billion market cap. And we really focus on four core therapeutic areas: oncology, immunology, neuroscience, and cardio-renal. And we're really into platform technologies. I've really tried to pivot the company into leading platform technologies. Myself, I'm a physician scientist by training. I grew up mostly doing R&D work and public health work at the company, and with some business roles became CEO in 2018. And in that period of time, we've spun off a lot of businesses, focused down. I think that'll be a lot of what we talked about today.

Yeah, absolutely. So Novartis formed out of the merger of Sandoz and Ciba-Geigy in 1996, and the focus at the time was becoming broadly diversified in healthcare, which was common I think for many of the main players. So Novartis at the time we were in consumer health, animal health, vaccines, Gerber baby food and nutritionals, pharmaceuticals, and so we had this pretty broad range of businesses. Then we acquired Alcon in 2009 to get even further diversified. But I think there was a realization, at least as I started to oversee R&D at the company and then eventually became CEO. I really took the view that we would be better served to focus down as a pure play company, focus only on biopharmaceuticals, and even within biopharmaceuticals try to focus on therapeutic areas we think would really matter. And so what we did over the last years is we did a really pretty radical rethink of the company. We exited our consumer health business in a joint venture with GSK. Now it's a standalone public company. We spun off Alcon, now standalone public company. We spun off Sandoz, standalone public company. We sold our Roche stake. And so we took this company that was a conglomerate and we turned it into four companies. And it's not, of course, perfect math, but when you look at it, we unlocked almost $180 billion of value by doing that.

Yeah. And you know the underlying logic to being diversified as a pharmaceutical company is you have these patent expiries and you say if I can get into more stable businesses, those businesses can kind of create a base of growth that will help you stem those ups and downs. That's the thesis, right? And I think that was one reason why Novartis did this, but in actual fact what I observed was we were misallocating capital. When you look at it, the return on capital varies tremendously between a consumer health business, a generics business, a device business, and a pharmaceuticals business, and we were often forced to say we have to suboptimize the pharmaceutical business to invest in the other businesses, or I'd have to say no to very good decisions for this Sandoz business to support the pharmaceuticals business. So I think there was this kind of strategic misallocation of capital. But then the second thing is you ask what is a company fundamentally great at? I mean Novartis is really good at discovering and developing novel medicines. We had these other businesses. We were investing to build them, but it was never really the core of who we are. When you go to Basel, you'll see we have chemists and technologists, and that's really where I think we're most successful. So it kind of felt like the right cultural fit right from a capital allocation standpoint. Of course investors, as you know, prefer that they get to decide how to diversify. They don't want us to diversify. And so for all those reasons it felt like the right thing to do. Now it took six years. Spinning off companies sounds easy in retrospect. Actually spinning off three public companies is a massive, massive undertaking. I can say from experience.

My instinct is to say this is where we need to focus. I think we can look at consumer platforms to provide access to our innovation, but the way I think about it is there's already, and you know this well from all your investments, already so much that you need to undertake to be diversified within the world of biomedicine. So many new technologies, and anytime you take on a new whole business area, you're going to distract the energy of the management team, the capital that you have to deploy, and also you have to learn a whole new space that you may not actually be very good at to really manage. So I think of it as how can we maybe use these consumer platforms or direct to patient channels to augment the core, but I don't see a reason at the moment at least to really diversify too far away from that core biomedical effort.

Yeah, the way I think about it is obviously small molecules and biologics are the core of every large company of our scale. You have to have that, and of course we've had those technologies for either 100 years, 100 plus years, or in the case of biologics 50 years. But we focus on three core technologies. We focused on cell and gene therapies first. We were the first company to have a licensed cell therapy, the first company to have in effect a widely used gene therapy with Zolgensma. Second, we made a relatively significant investment in RNA therapeutics. We've actually now acquired multiple companies, and we can definitely get to that. And then radioligand therapies. These are the three core technology platforms that we try to apply across those core therapeutic areas, hopefully to find better solutions for patients. And we're always asking ourselves, are those the right ones? Of course, you could get into DNA editing. You could be much bigger on antibody drug conjugates, but at least for now, those are the focus areas.

Yeah, this has been a tough one. I think I would say right now punching below their potential, but I think it's going to change and I'll explain why. First, when we talk about cell therapies, of course the focus after our initial discoveries and then other companies Kite, Juno, then later BMS and Gilead, Bluebird also was in there successfully bringing forward cell therapies were primarily focused on B cell cancers, right? And I think very successful, but the business was not hugely successful mostly because complexity, cost of goods, profitability challenges. Now I think what's really interesting is, and we could have never predicted it, but because of the work of Georg Schett in Erlangen, Germany, we've suddenly learned that you can actually use these therapies to reset the immune system. And I think this is going to be a huge opportunity. Just remarkable. And when you look at this data sets, as you know, very rare that you see data like this. Very rare that you can rewind a disease or completely in some cases almost create a functional cure for patients with end-stage immunological disease. These are the autoimmune diseases that have been very life-impacting chronic conditions, chronic debilitating with very bad options. I mean, the story I like to tell is one of our sentinel patients was an individual in bed all the time, not able to walk his children to school. He receives our cell therapy, strong results, two months, six months later no sign of disease. He has gone from almost a near-death situation to normal life. I mean, this is extraordinary, this is like Lazarus-like things. So we've now taken that forward into four pivotal studies. We have, I think, six more programs in early stage clinical, other companies as well. And I think cell therapies and immunology is going to be a huge, huge area alongside immune reset, bispecifics, trispecifics. That is going to be a whole renaissance for cell therapy. And alongside that, what also happened is we figured out how to make the manufacturing factors less costly. I think that's the other part of that story. If we were just doing immunology but with the same cost structure, super expensive bespoke manufacturing, but now that we're all working on rapid platforms that take two days in the factory, 8 days vein-to-vein time, this is changing the game. So I think there now, as has often happened, there was the hype, then we went through the valley, and now we're coming back out the other end. I'm not sure any of us would have predicted that would have been in immunology and not cancer, but hey, so be it. I think gene therapies is a tough one at the moment, as you know, with the safety. Zolgensma has been hugely successful. We think a remarkable drug, amazing. The story for your listeners: this is for a terrible pediatric disease called spinal muscular atrophy. These children would face a certain death at two years of age, or if they have a less severe form, they live a life in wheelchairs and really debilitated. And Zolgensma, one-time gene therapy, if given early enough, can almost let children lead a normal life. So it's been a success story. Now, we had hoped we would have a whole series of those behind it, and as you know, it's one success story but it's an end of one story. This is not platformized yet. I think because a combination of factors: one, the trafficking of these gene therapies to the right cell type, getting the expression as you hope, safety profile, all of these things turned out to be much more of a puzzle, and there wasn't as plug-and-play as I think we initially expected. That said, I still think that for certain diseases, if you could get a one-time therapy, it would be hugely beneficial, particularly in children. And I still think there's more to do, there are more opportunities here. We acquired some companies around this, so let's see. But that one is still to be proven, whereas I think cell therapy is really maturing now.

No, I think that is my view, and I think it's an extraordinary story when you look at it. The idea here is that you can use small sequences of RNA, a smaller chain of RNA, to silence the mRNA inside the cells to prevent the protein from expressing. That sounds like a simple thing, but actually the work goes back to the early 80s, decades of work. Alnylam and Ionis and other companies worked on these technologies for a long time, struggled, and then there was an unlock around 2015, 2016 where they figured out how to traffic that RNA fragment in a relatively efficient way into the cell, have relatively high specificity, and that led to really impressive data. So we went in primarily for cardiovascular disease at first. Our first medicine is a PCSK9 siRNA that allows you to take down PCSK9 for high cholesterol with a drug that you give every six months, and it works amazing. Right now it's doing extremely well, particularly in China. But it's really amazing. Now the opportunity is with that kind of technology you can get to once yearly dosing. People are working on more and more targets in cardiovascular disease. I personally think we're going to be at a place within the next 5 to 7 years where you could get a single injection that covers HMG-CoA reductase, which is the statin pathway, PCSK9 to knock down that other pathway for cholesterol, and probably if it works, Lp(a), another major cardiovascular factor. So one once yearly injection. Think about that from a public health standpoint, it's unbelievable. But the siRNA story was all about liver-directed targets. Everything we were doing was targeting everything to the liver, and we were seeing these impressive results. And then I think what's happened now more recently is we figured out how, at least starting to see, we'll see how the data plays out, can you traffic these siRNAs into other parts of the body, into the muscle, into the brain, into the heart. We recently made a proposed acquisition around this to try to see if we can actually get those siRNAs into the muscle. But this is opening up the field even more broadly. Can you traffic them to the kidney? So you can have all of these opportunities to have less frequently administered, high efficacy drugs. So I think this is a mature platform.

Yeah, and you know this is a topic not just for RNA, it's also in gene therapy as you know as well. It's a global comment. I think a couple of areas for us are interesting. One is synthetic capsid design. This has been around, but I think we're getting better at can you synthetically create a capsule, like a synthetic virus, instead of using the AAV virus which is often used, and use that to traffic. Of course, there's been a lot of work done on certain receptors in the nervous system that can basically draw into the central nervous system. I think that's obviously the transferrin receptor in particular, but there have been others as well. Antibodies conjugated to the siRNA, or antibodies conjugated to an ASO, so then the antibody takes it to the target cell. So I think these are all in play. I think it's all maturing quickly. There's also more, all kinds of other technologies. You would probably know better. We can lipid conjugate. We actually acquired a company that also can lipid conjugate to get into certain cell types. So I think a lot of activity happening, and the key is can you find the right address and can you hit that address with high specificity and not have the RNA go to all kinds of other places? Because depending on what you're delivering, if you don't want to hit the heart and you only want to hit the kidney, but you still hit the heart at even small levels, you'll get the side effect profile that you don't want.

Yeah, absolutely. So I think the listeners likely know radiation in cancer care has been around for decades, but the idea that a company we first acquired in 2019 called Advanced Accelerator Applications was actually a spin out from CERN, the particle accelerator outside of Geneva. The idea was could you actually bring a small radioactive particle right next to the cancer cells to basically have the cancer cells killed. Very elegant idea. Took many years again for them to actually mature. Kind of a fringe idea when Novartis first acquired it, but it turns out to be very effective. So the idea is you link a drug that is very specific to either the cancer cells you're trying to target or the area around the cancer cells. You link it to a radioactive particle, and then the drug brings the radioactive particle near the cancer. Relatively small doses, reasonably effective. And we have two drugs now. One of our drugs for prostate cancer for a target called PSMA, over $2 billion in sales. The other for neuroendocrine tumors, approaching a billion dollars in sales, launched globally. Very challenging technology in that after you activate the drug, you have between 4 and 5 days from the factory to the patient. So the supply chain here is very, very complex.

It's got a half-life and dedicated supply chain. We've had to figure this out. It's taken us I think seven years, but we've now done it at scale. We have launched these products globally and are 99.9% on time on every dose, which has taken a huge effort.

So validated. So for the given isotope, in the case of the one we've scaled, lutetium, which is a beta emitter, now I think it is platformized. We just have to find, of course, and that turns out as always not as easy as it sounds, but finding another target, the next target after PSMA is what we're looking for, but within our manufacturing network. Yes. Now it gets much more complicated if you want to switch to another isotope. So if you want to switch to actinium, an alpha emitter, there's terbium, there's kind of alpha-beta mixed emitters, and so those are much more complex because you would have to build a slightly or radically different supply chain. So those are not plug-and-play, but within lutetium, and that's what we do now. We have eight or nine projects now in the clinic all with lutetium tied to another targeting different cancer types to try to see if we can be successful.

Yeah. So I think we do a lot more thinking now at Novartis, I'm sure at other companies as well, on not just the target product profile, which is kind of what a clinician would say who's maybe a science-based clinician. We think about the patient profile. I'll come back to that. We even think about the kind of physician adoption profile because it's not always straightforward. What seems obvious to us when we're sitting in our company is when it actually goes into practice, is that something that a physician actually wants to deal with? And these practical considerations are really important. I think the first lesson is there's no one-size-fits-all. What we find is that there are segments of patients, let's say in the case of siRNA, who prefer a less frequently administered medicine. Others are okay with a daily oral because they don't like an injection. These siRNAs are injected. We even see geographical differences. I mentioned in Asia there's huge interest in siRNA-based technologies for cardiovascular disease. In the US it's still building and we're still working through it. I think the other thing I'd say on cancer is that we've moved away from an era where it was all about efficacy at all costs. One of the interesting things about radioligand therapy, and to juxtapose it to another technology, antibody drug conjugates, which we also are in but not as big as radioligand therapy, is that the safety profile is often very attractive to patients. When they can have relatively high efficacy but a short course of radioligand therapies, four to six doses usually, and then you stop, with a reasonable safety profile, that's more attractive than chronically feeling sick over time. That's a shift. We used to just go as a hammer, go as hard as we can, try to knock down the cancer, and not worry about the safety profile. That's another shift. So I think you have to think through that there are going to be different patient segments with different needs. And then I think you have to be comfortable. But it's interesting with our radioligand therapy portfolio. I'm often asked, but there are all these orals coming. For us to be successful, if we just get 20% market share of every one of those cardiovascular categories, we have huge medicines, and because these medicines are in the US context under the medical benefit, not the pharmacy benefit, it's quite economically attractive. So I think you have to be comfortable with those ambiguities.

Yeah. And there were several deals announced where a large pharma company is partnering with an AI-first startup, which I think in and of itself is fascinating. The other thing I thought was fascinating is that the sort of flavor of deals is pretty varied. In some cases it's a partnership, in some cases it's a license, in some cases they want to get access to a specific model. So we're actually seeing not only technology innovation, but a little bit of business model innovation where pharma is willing to transact on AI in a number of different ways. So that to me was just a fascinating thing to see, and in a lot of ways an exciting one given where we sit and where we spend our time.

Yeah. So we actually have the full gamut. We have the full spectrum in our portfolio. We just recently announced an investment in a company called Boltz. Boltz bio came out of an open source project at MIT.

Pure platform investment. And you know our hope is that a lot of the pharmaceutical companies that are interested in integrating AI will use those rails if you will um to do that.

On the other end of the spectrum we have several biotechnology companies that are AI first and they're using their internal AI capabilities to develop their own pipeline of drugs. And a lot of times what that will look like is, you know, they'll partner with a company like Novartis on a program or on a discovery project.

And then you're starting to see sort of a couple of flavors in the middle

So they do a little bit of both. They're not an investment of ours, but a company called Noetic announced a partnership with GSK around JP Morgan where GSK is getting access to their software on a specific model to really be analyzed I think for lung cancer patients. So that's like a model access partnership which is really interesting and then you have other flavors in between. So we're starting to really see a lot of this happening and so we're trying we believe that this is going to look like a spectrum and so we want to have investments across that spectrum and back entrepreneurs that are pursuing different opportunities. So that makes sense.

Yeah. So, I see it as kind of an enabling technology across all of that matrix that you described. I'm not sure if I see it as its own technology platform yet, but I do see it as a powerful enabler. You know when I think about when people always ask me what can the impact be, I generally say in R&D it'll take 7 to 10 years because that's just how long it takes to develop drugs and that the things we have to be watching is how much does it shorten the overall time from when we have a target in the lab to when we get a drug license which can be 12 to 14 years. Can we bring that down by 2 to 4 years and that already would have a huge impact and can you move the probability of success number meaningfully from where we are today? You know as you know from the research it's 10 out of 1,000 when we get into the clinic, it's 10 out of 100. If you can move that meaningfully even a little bit, frankly the compounding effect is huge. And I think that should all be well within hand. I mean the way we approach it at Novartis is we break down the whole R&D value chain and we say what are the technologies we need in target discovery, candidate identification, candidate optimization, pre-clinical safety, PKPD modeling, phase one trial optimization, so on and so forth all the way through document work, protocol optimization, can you get automatically from the protocol to the CSR? And basically try to find the right technology companies to support us across all of that. And now we're trying to integrate that much better and say can we actually have more of an integrated platform across? And I think over time we are now starting to see the benefit. And I would agree we're at a point now where you could actually say that this will have an impact. I think the hard part is that whenever we set expectations high, people expect it to happen within two years, and really the first purely AI generated candidate by definition cannot come out the other end for 8 to 10 years. It's going to be a long time. We just don't know, right? But I think it's really interesting. I mean, we do work with Isomorphic Labs on what we call undruggable targets. So we give them undruggable targets we've not been able to drug ourselves. We think are interesting. They're working on drugging them using AlphaFold 3. I mean, Bolts also, being a similar kind of technology that could be used for that. You have others that are using quantum technologies to say can they better model the protein protein interactions to find these weak interactions and better drug design. So I see all of this happening and again it's going to be one of those things where all of these little gains are suddenly going to compound to a really big gain and that's where we're going to see my expectation at the other end. Yeah, and I would agree with that and I think that it's probably fair to say that the first AI generated drug candidate is somewhere in a pipeline at the moment. So we will see it emerge or debut in a couple of years.

Yeah, absolutely. I think it comes back to I also want to answer you how do I use AI and I'll come back to that. But yes, we have a very systematic approach and we are trying to scale it now across the whole company. I think we have one of the highest numbers of AI licenses for Microsoft Copilot with all the different model options that you have there. We're one of the lead partners for Palantir in terms of all our R&D data goes into a data lake powered by Foundry. And so, you know, we really tried that these are all things we did like six years ago, right? And we really weren't sure how it's going to pay off. And now I have 3,000 scientists on the Foundry platform, picking the right models to actually just go into our data lake and extract data. It used to take six months and now it takes minutes. I mean, the power here is incredible. So we are absolutely scaling it. How I'm using it and it's part of our general push. One of the big opportunities in companies like us is not the high-end biotech side of things, it's just all the ways we could automate very rudimentary things that we do. I mean regulated industry, so much document management, so much review. All of this with large language models can now be done super fast. So, you know, I can create a podcast to listen to my integrated financial report to prepare for my earnings call. I mean, this kind of stuff, who would have thought it's possible? Or we can draft a press release pretty quickly or with a quote in my voice. I have an agent, right? And you can just basically say, 'Please look at all of my historical comments and please draft it in my voice' and it'll do it pretty well. We have agents that look at all of our historical decisions in R&D and then as a chair of a lot of these committees, I can use those agents to inform my next decision, whereas I'm not just relying on my memory. I can actually go into the agent every single time we saw a situation like this, what were the key issues that we identified, and that makes you have a better next decision. So all of that is now happening even on my desk every day.

Uh, January of 2018. Yeah.

Yeah, I think this has to now sharpen the competitive edge that we have in US biotech because I think what we see in China is very talented scientists who are now leveraging a lot of knowhow they've learned over many years also in our labs and in our companies to move extremely quickly. And I think it started off as more fast follower working around biologic patents and that continues at scale, but it's slowly morphed now into when you look at an example like bispecifics, I mean a huge number of bispecifics now happening in China, cell therapies and related technologies. I think last year at least from my understanding of the data, I think China had more licensing or exits than US biotech or somewhere close to that. So it just gives you a sense of the speed and the scale. So I think a couple of things for US biotech: I think clearly now speed is of the essence and part of that is also going to have to be regulatory frameworks. I mean the NMPA simply moves incredibly fast for a first in human study. It's under a month now, and that I think enables those companies to generate human data incredibly fast. The NMPA being the China regulator. And I think that's one enabler. The second, and this is as you know been a long-term challenge, is just the speed of trial bureaucracy in the United States. Again, China is able to leverage these very large integrated centers, these China biotechs, and they generate that data extremely fast. So they get that de-risking phase one data and they get that proof of concept data, and then they can go market themselves much more quickly. So I think we have to now tackle how can you get more scale and speed in US clinical trials or even European clinical trial centers as well. And then Europe has historically been a bit faster. Belgium, Australia, you can go very fast. But even Belgium and Australia are not as fast now as the way China's moving. So that's going to be a second topic for sure. And then I think, as you know, we have to continue to support NIH and the things that make the US bio. I was really heartened to see that the Senate Finance Committee fully supported NIH funding because I think that's going to be really important in the long run because that is something unique. I think that other countries including China haven't fully figured out how to replicate and that ecosystem that goes from universities to biotech is incredibly unique. But those other elements we're going to have to tackle, I think. And so, to the FDA's credit, the current administration has demonstrated that there is a very high willingness to figure out ways to have the necessary reform so we can accelerate the path to getting these medicines to patients. So there's a will and I think the question is what's the right way?

Well, I think a lot of it actually is making sure we have talent and capabilities and really ensure that FDA is enabled to hire the scientists they need at scale and can then review these IND applications really quickly. Um, you know, I have two minds right and it's a tricky one because do you want to reduce the IND requirements? Because I do think in China you do have a leaner package to get to that first in human, and is that a good thing in the long run when you need to maintain trust with society to be able to do this work? Um, but if you just want to optimize for speed, you could look at the size of the pre-clinical package. Again, I think to be debated, I would say is that the right thing or not in the long run. Fair. And I think that's something we'll have to consider for sure. Um, and then I think outside of the FDA's purview, I mean, I think we have to come up now with a more streamlined approach to IRB reviews, common contracts, all of the stuff that can really slow down your ability to get a trial started up in the US. If we could get more platforms in place where you could just go right in in a particular disease without having to recontract and redo everything, I think you could generate the data a lot faster and I think those kind of networks now need to get scaled if the US wants to remain competitive.

I would say it's too early to say and that's to say it might be happening. I may not just have visibility into it, right? But at least I have not seen it. I am sometimes concerned that the effort turns into how do we block China innovation from being accessed by global biotech companies or all of the efforts to do that, because I think in the long run better to actually, as you know, history would show us that we would want to have more competitive industries. We don't want to be able to say there's a beautiful discovery in Shanghai, let's not use it because it was discovered in Shanghai, right? I think important though, however, to make sure we have global clinical trials that reflect the ethnic diversity playing fields, all of those things. For sure.

Yeah. I think first, baselining for the audience, I think some of the facts that get lost in this discussion: over 90% of scripts in the US are generic. Generic drugs in the US are the cheapest in the OECD. So, I think the system works insofar as innovation is rewarded during your IP and then it's radically taken down in price and it effectively becomes a public good. And that's why actually the innovative medicine spend share of US healthcare expenditures is actually going down, and net prices in the US are only growing at single digit level. We have certain population groups now, very US focused at the moment, that have a challenge in affording medicines, but actually for most people out-of-pocket costs are quite manageable and many policies are in place to drive them down. I just wanted to say that as context. Now, to your point on these one-time therapies, they present a unique challenge. What was interesting is Zolgensma even at that price point is reimbursed in 48 countries around the world. The reason for that is that the cost effectiveness is so high. When any government around the world sees that the cost of caring for one of these patients is more like $10 million for their life, and if you intervene early and the child lives a normal life, then all of that cost saving comes back to the system. So I think that story has to be told well. Now, if you have many one-time therapies, clearly then there's a phasing issue and then you would have to come up with new approaches. I have to say with Zolgensma, we were not successful in moving to those models where you phase payment out because the systems just aren't ready for it. And we've been talking about this forever. This whole idea of value based medicine: will you get reimbursed if the drug doesn't work? Can you phase cost over time? The franchise model, very difficult so far. Is it honest truth? Just very hard to get there. Yeah, it's just very hard because the systems are designed for annual payments and not tracking patients over time, right? And that is reality at the moment. Now, would I get tipped if you had 10 of these? Maybe, but that's still the unknown. I think your question on the preventative therapies is the one long-term question we have to keep grappling with from a number of different perspectives. One, these trials take a long time. If you have a policy like the IRA in the United States that caps our ability to recoup investments at nine years, you can't run the long trial. Second, you need continued innovation on endpoints because if you're going to wait for outcomes and then you're going to do these preventive studies, you're never going to actually get to the outcome within your life. It'll take forever. So we need to innovate on outcomes. And then you think about payment models because now you're going to have to treat a lot of people, many of whom will never get the disease in order to prevent. So it's a number needed to treat problem. And so we're going to have to come up with new payment models. And then of course the system is designed to care for the sick, not to prevent. So I don't have the solution, but I do think this is something we want to look at more systematically, especially because our medicines are getting better and better at going early and preventing the cancers from recurring. And I worry that the system right now if it doesn't start adapting, we just won't be able to systematically do that. Starting with the IRA, but also now if you think about FDA regulations that require an overall survival benefit, doing that in an early stage cancer study, it's not possible, right? So I think there's a lot of thinking that needs to happen in each one of those areas to make preventative medicine a reality.

I think we've come a long way now. There's always a long way to go when you think about culture in a huge organization like us. But when I go around the company now, this idea of inspired, curious, unbossed — inspired by purpose, curious about yourself and the outside world, and empowered by the unboss philosophy — I think it's taken hold. Now, one of the things that's interesting about unboss I learned is it just always creates a conversation about culture. And if your organization is always talking about what is the culture we want to have, actually the culture kind of naturally improves because people are aware that they drive the culture, that this is something we all have to own. So I really see, I mean we have all of the survey data that shows that engagement and all these things have gotten to a higher place. But when I just look at the results, the innovation performance has been outstanding. We're number two in TSR. We're the best non-obesity company in the sector. So, as I like to say, because we don't have an obesity portfolio, but there's a lot of diseases outside of obesity that also need to get treated. So I think we're doing pretty well on that front. So I think not only do I see it, but I also see it in the performance. I see it in the R&D engine working well. So I'm pretty pleased with where we are.

So there's a boring one I always reflect on. It sounds so dull but it affects every single trial in a company that does hundreds of trials every year. Every time we do a clinical trial, the study nurse has to record what is happening for the patient in a case report form that's done usually on paper in the clinic. And then has to input that into our source data, called the source data, input it into our electronic case report form, may have to also put information into an electronic health record, and all of this has to happen and then we have people coming to check that the source data matches what's in the case report form. And we've been trying to innovate around this, and the fact that with all the magic of AI and blockchain, there's got to be a way to make this super streamlined for all of these clinical trial sites around the world. But with all the EHR fragmentation and all the companies having different systems and all the hospitals having different documentation, it just hasn't happened. It is a pain point and it's why we have unfortunately a huge amount of effort to check all of that on an ongoing basis. On the bigger picture, I think we still have to crack, and I'm not sure it's a startup, but we still have to crack how can we use various early biomarkers for large scale prevention. I mean the fact that we still treat disease as late as we do when we know, whether it's immunologic disease through atopic march or in certain cases or in cancer, that if you treat early you're going to win, and the fact that we have not solved this problem at scale is the next great opportunity for us in healthcare.

Yeah, I think a couple things. One, I think that there's a huge value in intellectual honesty about where does your drug really fit into the treatment paradigm or your concept fit into the treatment program. That'd be one. And just really doing the hard work to understand that upfront. I think second is to do the killer experiments because often when we're doing due diligence, we're looking for those killer experiments. That's in the pre-clinical setting to really prove that your target is doing what you say it does or your drug is doing what you say it is doing, the pre-clinical safety work. It's tempting to cut corners on that early stuff, but often that's why we have to walk away just because we're looking for that validation, particularly when we're going to enter with relatively large upfronts on a drug. And my third, which is my biggest pet peeve on all of these due diligences we do, is all around technical development and manufacturing. The CMC work we consistently see is underinvested in, and what that means is tremendous rework on our side or that we just may walk away just because we can't be sure we can actually scale the production process.

So I suspect it's a mix of both, but I do wonder if it's a knowhow issue. I've often thought, I've talked to some of the VCs that I've met with over the years, should we just create a CMC boot camp for biotech startups? So they at least know the right questions to ask, because there's so many avoidable things that happen. Yes. And if you just did those things right, you might get an exit faster and we would certainly get the medicine to patients much more quickly than having to redo a huge amount of work to do the next trial and ultimately scale the process. So I think CMC, it seems like such a side topic, that thing you don't want to deal with probably in your executive committee or in your board meetings, but it has such a huge impact on whether or not we can actually accelerate these innovations.

We can do it as a joint venture.