Simon Turner, Sofinnova Partners - AMOI Studio Interview | LSI USA ‘23

Sofinnova Partners is a leading European venture capital firm in life sciences, specializing in healthcare and sustainability.
Simon Turner
Simon Turner
Partner, Sofinnova Partners


Ben Glenn  0:10  

Say hello to my guest, Simon Turner at LSI 2023. Simon, thanks for coming by the studio.


Simon Turner  0:17  

Thanks for having me, Ben.


Ben Glenn  0:19  

So tell me what's going on at LSI? What brings you out this year?


Simon Turner  0:22  

Oh, a whole host of factors. Really what brings us here, and particularly, we're coming over from Paris and the European ecosystem is to see what's going on in the US, quite frankly, you know, in terms of meeting new innovative startups, of course, on the one hand, but also looking at the CO investors, of course, that are important for our portfolio companies and helping them bridge the Atlantic and get over to the US, which is one of the main markets we see.


Ben Glenn  0:41  

I love the idea of like bridging ecosystems. So how do you bring that about? What are you looking for when you're coming here to talk to companies? Yeah,


Simon Turner  0:48  

I mean, it's, it's really looking at this, this kind of notion of we're lifesigns investors, we love getting into these early stage companies seed and series A bringing our expertise, again, we've been around for 50 years focusing in on this life science experience. What we're looking for is companies and particularly entrepreneurs, that have this, this real kind of innovation are part of this need to disrupt what they're currently seeing. So we're looking for innovative biotech medtech, digital medicine companies, where we feel not only there's a good fit with the entrepreneur, but also this ability to co create a story, something that can really change the paradigm of medicine as we see it today.


Ben Glenn  1:20  

It seems like there's a the rise of the digital aspects of healthcare. You know, one of the one of the interviews we had this morning, we began to unpack the medical device, the thing itself, then having software that is enabled by that, and then the data that's generated by that software, and then the data coming back to redesign new software, new data. Are you seeing that kind of a virtuous cycle?


Simon Turner  1:44  

Oh, yes, very much. So I mean, traditionally, we've seen a lot of investment, that kind of the med tech side of things. So again, these kind of classical hardware systems. We have, of course, this theory and ethos that you always need biotechnology always need medical devices. Now that what we're seeing is there's also a lot of data being generated either from existing legacy systems or in fact, just totally new datasets. With the advent of new computational techniques, also coming into this, suddenly, you can leverage, you know, existing data, novel approaches and things like that, to actually gain added insights. So you're going beyond just the raw data that we're able to see and able to therefore start really impacting patient outcomes, but also the healthcare system. And tackling I guess the the inefficiencies that we're kind of seeing that have been built up. COVID was really kind of a nice way of showing us that, wow, there is an enormous amount of pressure on the healthcare system, it's not always capable of dealing with things we got through that with flying colors, I want to say because, again, we have such great people in the healthcare systems. But it also highlighted how we can use data and computational techniques now to make new sense, and therefore really improve the healthcare outcomes


Ben Glenn  2:45  

inside of the European Union that would you call that European ecosystem? Are you finding the rise of data to come from some unexpected places.


Simon Turner  2:54  

So the rise of data itself, I'd say is more about finally healthcare systems, being able to digitize themselves, so suddenly, we're able to unlock these kind of mass repositories of data. What we're seeing though, however, is also the way that the computational techniques are coming about. And whereas classically, you'd almost have, let's say, the more or less biomedical sciences, doctors, physicians, healthcare practitioners developing innovation. Now suddenly, we have the rise of, for example, data scientists, as well as mathematicians and physicists, bringing in these new kind of algorithmic approaches that can really make sense of the massive amounts of data that we're seeing in healthcare. So it's really seeing this kind of confluence of not only data and data sets, but also the techniques that are being applied. And they're coming from, let's say, less classical places that we wouldn't have normally seen life science innovation happening from


Ben Glenn  3:39  

so we might have the healthcare system is being helped by the people that have never really seen themselves as healthcare entrepreneurs or healthcare innovators,


Simon Turner  3:48  

right. And we're starting to see it today. I mean, there's a lot of kind of tech entrepreneurs, successful tech entrepreneurs, which are now beginning to look into healthcare thinking, right? You know, my first startup, maybe it was more about a consumer products, maybe something that, you know, was great in terms of providing, you know, music or listening capabilities to say, Spotify, for example, or Skype. Now, suddenly, they're seeing that actually, you can take these similar approaches, and begin applying them to the healthcare sector. And we're seeing things as kind of Austin as varied as, for example, the automotive automotive industry, or even in aircraft manufacturers, for example, they've been using digital twins to basically design and simulate their engines, when will they start to fail when there's a point where you need to actually intervene to be able to then avoid a catastrophic failure. That same understanding the same mathematical approaches and modeling can now be applied to organisms, you know, to cells, but then also to much more complex biological systems. So we're seeing this type of innovation, entrepreneurship and a really there is even companies beginning to move into our fields, in fact, into healthcare, and it's bringing this mass wave of new knowledge, in fact, unlocking these incredible potentials that we see


Ben Glenn  4:52  

every day I look at like, 3d printing and 3d modeling. There was a lot of that area, you know, being able to well what if We could actually mimic the tumor, I'm picking up on your digital twin. So if we could mimic that, and then we can mimic the interaction of the drug to the tumor to oncology, all of a sudden, you know, these incredibly new pathways begin to open up


Simon Turner  5:14  

exactly. And I mean, it's, it's even maybe taking it a step more basic. In fact, it's if you're able to simulate a tumor, so from a single patient, we can start then looking at existing drugs and therapies, which would potentially be the best intervention to apply. So what we're suddenly doing is before even needing to go to the patient, say, Okay, let's try combination A, then B, then C, and D, and waiting for these long periods of time to see, are we getting a response or not, we can simulate that in silico, get to a point where we say actually, this drug one combination is not working, Harvard drug two seems to be having a great response. And if we combine that with drug three, for example, we have this incredible outcome, and almost a complete response type scenario. So what you're doing is you're tackling these inefficiencies, this delayed feedback that we otherwise have in the pathways, very similar to what I guess SpaceX was doing, when they were trying to train their their first vertical landing rockets. Again, without in silico simulations, it would take them 1000s, if not millions of tries. God knows the kind of catastrophe for breaking so many rockets, you can do it in silico. And suddenly, you can run simulation after simulation after simulation until you get to something very close to a really good outcome. So doing that, we're basically able to start getting to this personalized care approach that we've been talking about so much.


Ben Glenn  6:26  

It seems like we've got to have something to change the economic models that is going into precision health and personalized care. We simply can't have you know, it's $75,000 a dose per patient. Oh, and you need 15, you need a series of 15. Yeah, no one can do that. No. So do you think this is going to be beginning to apply these can be a gateway for us?


Simon Turner  6:48  

Absolutely. I mean, for me, this is kind of where medicine will go into the future, we need to get to a point where, you know, when we're prescribing a therapy, or when we're putting together a treatment plan to your point, you know, $75,000 a pop, but only 30% response rate, we won't know which 30% is responding until maybe six months later. That's an enormous healthcare cost. But also just detrimental to the patients, I mean, 70% will then be sitting on ineffective treatments. Whereas if we can get to a point of understanding the fundamental principles of what makes them unique as a patient, simulating what's the best treatment approach, we'd be able to actually provide an alternative therapy, it may not be the first line actually, it may be second or even third, but it will be adapted and bespoke to them and their needs versus again, normal standard patient one, for example.


Ben Glenn  7:32  

That's, that's very interesting. Just to pick up on one of the things you said is maybe the first thing we need to do is actually just mimic that patient, not the general like general human being like the biome or something. But actually, this patient, you know, your makeup, and how does your makeup interact with this


Simon Turner  7:50  

exactly right. We're going away from this one pill fits all type of approach, we're seeing in oncology, we're starting to get a bit of precision medicine coming into that. You've seen the companion diagnostics that have been developed the fact that you now start to have some treatment stratification. But I mean, the next stage is we'll eventually get to a point where we're able to integrate multiple different datasets together, we'll get to a point where we can maybe achieve multi omics type approaches, suddenly, we can get to that n equals one patient. And then it is really a to your point, it's an in silico simulation of you or I or whichever patient it is, but it's them being their own control, and hence we know what's the best for them particularly.


Ben Glenn  8:26  

So in Europe, are you seeing the this melting pot? Are you are you able to find ecosystems where you're able to bring in these other kinds of, you know, when we look at Stanford Biodesign model, right? So physician, engineer, MBA business person, well now data science, software science, biomechanics, deepening an understanding of maybe a certain disease state, are you finding that Europe has something to offer for this development?


Simon Turner  8:55  

I mean, I might be slightly biased being a European at heart. But absolutely, we're seeing these ecosystems pop up all over Europe. And in fact, you know, it goes to deep sense to say we've got expertise in genomics and genetics, but then you're starting to see, again, to your point about novel imaging techniques or even just understanding of it. So radiology, histology, all of these components are actually coming up of age very quickly. The beauty is as well, within your you have so many different clusters, again, depending on the countries regions, and the historics have that, that you're starting to see different specialities kind of combining, they're now being brought together so much more. So this kind of future of a multi ethnic based approach, I guess, which would get us eventually to personalized care, you're starting to see the first building blocks of that fundamentally kind of arriving. And that's really what we're kind of counting on to see into the future. The maybe just named just one place I mean, France, which is our home base, of course sofinnova. We've seen an enormous rise of this digital health in particularly kind of the digital medicine aspects of it in Paris, but of course and also the surrounding ecosystems around it. But if you think about it within three or four hours, you've seen many major cities and clusters, if it's the Golden Triangle, if it's what the the Helsinki ecosystem is doing, and kind of this, these new types of technology approaches, the Germans as well, in terms of what's going on and rounded by Irish ecosystems, it's creating such an easy melting pot, in fact, of bringing all these people together,


Ben Glenn  10:17  

I often coach, the people that I advise are talking with the startups, it's especially this, this idea of like, regulation is bad, I'm going to disrupt, you know, these are the exists for a very important reason. And these are major regulated industries, because they're so important to the economy and to people. Turn that into competitive advantage, embrace it, lean into it, and then you will begin to have a new idea that is completely acceptable and building on and propelling us into compliance. And then to just sort of embracing what we have to do, obviously, inside this industry, you're


Simon Turner  10:51  

100%, correct. I mean, I couldn't agree more with us even to the point where our portfolio companies occasionally we say, actually, let's push this a little bit further, let's set the new gold standard for what should be considered, you know, best practice within this, if it's the way that we treat patient data, if it's the way that we check the safety of a new AI algorithm, for example, all these components, because if and when you set that gold standard you work with, if it's the regulatory authorities, or the payers, or whoever the healthcare providers are, you've suddenly created a new benchmark by which anyone else must measure up to if you're continuously innovating on that, you'll be heralded as the gold standard, so hence, the best in the business. But also making sure that you're creating certain barriers to entry, in fact, so you're creating your own defensible moat around you by trying to be as good as you can, rather than trying to skirt the issue in many cases. And again, it's the importance of treating these things as tactical or strategic advantages potentially. And again, it's not necessarily to say that you must always go down the hardest route, but at least think about it and see what are the implications if you do or don't,


Ben Glenn  11:52  

excellence as the competitive advantage and healthcare? Anything else you want to share with us today?


Simon Turner  11:59  

No, just that we're super bullish on the entire space. I mean, again, we're we've seen so much innovation happening over the last years, particularly in biotech and medtech. Now with our new kind of evolution into this digital medicine side of things, we're really bullish on how much this will impact the entire healthcare system and services. And all I can say is for all the entrepreneurs out there, we'd love to kind of have them come and discuss with us because we see it as fantastic to gain with the experience and knowledge of biotech with med tech and of course this new digital leverage that we have.


Ben Glenn  12:28  

Thanks so much for coming by Simon.


Simon Turner  12:30  

Pleasure. Thanks very much. Simon Turner. Take one marker


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