Founder Stories: Werner Lanthaler, CEO of Evotec
In this interview for the Flood.bio Show, host Philip talks with Werner Lanthaler, CEO of Evotec, about the company’s evolution, its AI/ML strategy, and the broader biotech ecosystem. Lanthaler explains that Evotec has integrated AI and machine‑learning tools across every R&D division since 2017‑18, treating them as a core part of the drug‑discovery workflow rather than a siloed software offering. He quantifies the impact as a minimum 30 % efficiency gain, translating into billions of dollars saved on a typical $2 bn drug programme and faster timelines for patients. The conversation moves to Evotec’s growth from 500 to ~5,000 employees, revenue rising from €50 m to €750 m, and a market‑cap of €3‑6 bn, driven by a hybrid CRO‑plus‑drug‑development model that co‑owns ~200 assets and operates on a “shared R&D” paradigm with partners. Lanthaler highlights internal platforms – the omics‑driven discovery engine, the iPSC‑based disease models, and the new biologics infrastructure (J‑Pod) – and tools such as PanHunter that accelerate data aggregation and target prioritisation. He stresses that the real value lies not in the algorithms alone but in rapid, high‑quality data pipelines and in sharing molecular‑patient databases across the industry. The interview also touches on Evotec’s partnership strategy (e.g., with Exscientia), its stance on capital markets (VC, private‑equity, and the need for public funding), and the European biotech landscape, noting the importance of global talent hubs and a collaborative, open‑culture approach. Lanthaler reflects on his own non‑scientific background (psychology, business, former CFO of Intercell) and how his finance‑first perspective, combined with a long‑term, authentic leadership style, shapes Evotec’s culture. He describes his daily routine, the virtual management structure, and the importance of surrounding himself with experts, staying humble, and maintaining a clear, mission‑driven vision (“research never stops”). The interview concludes with practical contact information and a brief pitch for the Flood.bio podcast.
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That's why I would say a minimum of efficiency gain is north of 30% that you see by, by just implementing these tools.
That's, that's huge.
I mean, especially it's huge when you know that a drug in its development is $2 billion. And if you take 30% out of $2 billion, and if you take 30% of more than, than 12 to 14 years at this stage, then it's really reaching all these dimensions where at the end it will have true impact on costs for patients.
Hey, Philip here! Welcome to the second episode of the Flood.bio Show, where I interview the best Europeans in biotech to help you be inspired and grow. Today I'm in sunny but also a bit windy Hamburg at the headquarters of Evotec. To meet with Werner, the big boss. I've known Werner for many years, almost a decade, and we have been on stage a few times, and he's really a brilliant speaker, and not only because he's really sharp, but also because he's really friendly, accessible. You just want to talk and listen to him. For a bit of background, Werner has actually a degree in psychology and business and has no bio background, which is pretty rare in the industry. He was then CFO of Intercell, which is one of the biggest success stories in Austria, for almost 10 years. And after that, so almost 15 years ago, he became CEO of Evotec. And the company went into fast growth with him, went from 500 employees to almost 5,000, from €50 million revenues annually to now 750, and has today a market cap of between 3 and 6 million euros. And today Evotec is a mix between a CRO and drug development company. The CRO side, as Werner told me, was we can do any experiment under the sun. And on the drug development side, they co-own and co-develop close to 200 assets. That's it for now. Let's head inside to the— let's head into the building, meet with Werner and discuss many things from AI in biotech to his mind to many, many things and exciting things. Let's go! So Werner, welcome to the show.
Thank you so much for having me.
Thanks for welcoming us in wonderful Hamburg. Some sun even.
Oh, I made the sunshine for you.
It's always great to talk with you offline, online. I mean, always amazing discussions. Today, we see a lot of things we could cover, but I want to start not with the IT attack that we just had a quick talk about, but I don't think it's the most fun topic, not the most interesting, but the I think one that we can start off is AI in biotech. And if you remember last time we talked in Vienna, actually at BioEurope, I watched the video and we talked already quite a lot about AI in biotech. And that was 2019. And I will link to the video. And what's amazing is that you/EvoTech have been in advance on that topic. Quite a lot, especially in the biotech industry, which tends to lag quite a lot into IT and software. But obviously now, I mean, ChatGPT, DeepMind, AlphaFold, I mean, in the last 6 months, it's crazy what happened. So I was just wondering, like, if you can dig into it, let's say from 2019 to now, and how you integrated, let's say, the last big developments.
So first of all, thank you for recognizing us as a true leader when it comes to AI and machine learning in our industry. Why do I say this? Because we have always understood AI and machine learning as an integrated part of a new normal when it comes to drug discovery and drug development. Because a tool in itself has no value. But a tool, when it makes outputs better, has enormous value. And that's why we have decided already in 2017, '18, when we saw the first processes arriving out of machine learning and AI, that it has to be an integrated part of our drug discovery and drug development thinking, and not an isolated software-driven offering. And today I would say that every process is driven more than ever before by cost pressure and efficiency to come to drugs faster and with this more cost efficient. And that's what AI machine learning effectively does. That you can accelerate an experimental cascade to a wet lab experiment with the AI and machine learning tools, yeah, significantly faster. And that's again where I'm coming to the integrated approach of this, because isolated doesn't make sense.
And the significantly, how much are we talking about? Because I mean, is it, you know, 10%, 30%, 50% to 100%? No, depends on which approach, I guess.
But like, it really covers 3 dimensions. It covers quality of the experiments that you're doing, it covers costs, and it covers timelines. But it's important that it covers all 3 dimensions. And if you take it— and this would only be a marginal help, it wouldn't help anyone But I'm so convinced about this because it's a substantial help to make drugs more precise and faster. And that's why I think some of the experiments are only possible now. So it's not a question of make something 5% or 10% or 20% better. It's only possible because we can accelerate and analyze so much more data. And the other thing is it will have a huge acceleration aspect when it comes to, for example, prioritizing experiments. And that's why I would say a minimum of efficiency gain is north of 30% that you see by, by just implementing these tools.
That's, that's huge.
I mean, especially it's huge when you know that a drug in its development is $2 billion And if you take 30% out of 2 billion, and if you take 30% of more than, than, than 12 to 14 years at this stage, then it's really reaching all these dimensions where at the end it will have true impact on, on costs for patients.
That's amazing. And I'm curious about this integrated aspect as well. I mean, so if I summarize, instead of saying, okay, it's like you have the software division or like one kind of a software silo. The software is actually horizontal and spread across every different divisions. But, and then what I would be curious about is how you do the development/integration of tools, because I guess you don't do all the AI machine learning models necessarily yourself. There's probably some blocks that you take into. Can you go a bit over there. And I mean, and there is a huge complexity there as well, and it's a different job. I mean, probably OpenAI, it's crazy number of engineers also. Can you just go there, like, how you, how you do the development, how you integrate it, how— yeah, all these aspects. I'm curious.
I mean, very often we think that in biotech we have to reinvent every process where the tech industry has already been sometimes 3 to 5 years ago. And if you look today at the AI machine learning tools that tech companies have integrated into their search engines, into their optimization algorithms, then you can imagine that we don't have to reinvent everything. We can really accelerate our learning by learning here from many of the tech industries. Having said that, our world is significantly more complex because biology is a totally different dimension of complexity. And optimizing chemistry is a totally different dimension of complexity. But message number 1 is we don't have to reinvent all of this. We can learn what the integration means from others. Message number 2 is when you are building experimental cascades, it's always a very rigorous standardized process that you go from a target that you have identified to optimize a target. And in optimization of a target, if you can do this with an integrated algorithm and you can prioritize, for example, 10 targets in 10 dimensions via an algorithm, all of a sudden a lot of manual work falls completely away because you just will not work on the 9th priority. You will only work on the top 3 priorities. And that's, I think, how you should imagine how this works. And it's really optimizing these bottleneck processes that were up to now significantly higher manually done than what we will do in the future.
Yeah, that's interesting. And you were talking already 2019 that it's not about replacing Evotec scientists or Evotec staff, it's about augmenting them and allowing them to do many more experiments. How did that change between 2019 and now?
I mean, in total in 2019, we were probably 3,600, 3,700 scientists in the company. Now we are close to 5,000. Scientists in the company. And despite that there is a tough funding environment for biotech, we are recruiting this year quite heavily. And it's especially these processes that, that we are augmenting where we see, for example, in a, in a, in a massive effort when it comes to data aggregation and data analysis, bringing here a platform together is just doesn't exist on the planet. And that's why, for example, a tool that we have developed called PanHunter will be super important for the whole industry once we have fully rolled it out, because then people can just understand way, way, way faster where does their molecule sit in the whole universe of data analysis that they can access.
Um, yeah, I mentioned the growth of, of EOTech employees. We could touch that a bit later. It's crazy how fast you have grown and consistently and fast. Maybe to stay a bit more on this topic on here, I'm curious if you zoom out a bit. I mean, EvoTech, obviously you have it integrated. I'm curious like how it, how your stack or how your AI ML capacity compare to, let's say, others in the industry. I'm thinking about some kind of AI biotech integrated companies. I mean, Accenture comes to mind, but you've invested there, so you know pretty well what's going on. And there's probably some complementarity. Or I'm thinking about Moderna, who have also their own stack and super automated. I mean, pretty crazy even like 3, 4 years ago, what you like, everything super automated with in-house software. I was really amazed when I saw that 4 years ago. I'm curious, like, in your view, how basically, yeah, how do you, if you take a bit of zoom out approach, what's the picture basically?
First of all, it's only natural that many companies are taking the approach to understand AI and machine learning and implement their understanding into their processes. Every company will do this. Every company. So I think it's not, is Moderna doing this or not? Every company at the end will have to do this because otherwise—
who is doing it well then?
Yeah, but I think also here people will learn from the best, and then it comes down to where do you achieve the best synergies. And as you mentioned, for example, Exscientia, we are partners with Exscientia where we really have synergies in drug discovery projects where something that has to be done is way better in their hands than in our hands. But if you put it together, it makes what we always call the shared R&D paradigm really work. When it comes to AI and machine learning, one of the important aspects is, and that applies to many, many of the disease areas as well. The starting point is understanding molecular data. The starting point is who can analyze molecular data fast and precise enough to make this a starting point to feed the algorithms. So that's why we are not that much focused on optimizing the algorithm only. We are focused on how good and how well organized and how, how fast can we access biology-driven data into these algorithms. And that's where molecular patient databases are for us super important, and they will be super important for the whole industry because that's where you want to start a drug discovery campaign, at a human molecular patient data point. And not at some random, I don't know, animal data point or just an unproven target that you find somewhere.
Yeah, that's interesting. I mean, at the end, these models need huge amounts of data. I mean, some data probably are already available. And then I think you mentioned also some data when you need to generate them. I mean, ChatGPT is amazing because you can do your loops. In vitro, basically running them and then the model improves very quickly. But once you add, I guess, a wet lab experiment in there, then your loop is just so much slower.
Exactly.
But can you expand a bit there? How do you optimize this looping? I guess there's also some automation needed so then the loop is accelerated.
At the end, it's much more trivial than it sounds.
Yeah.
Because once you have built, and let's go to a simple example. Once you have built, let's say, an AI-enabled prediction of safety data on a specific organ. Yeah. Where you say, let's take DILI as a readout for kidney diseases. You want to see DILI talks as fast as possible, and you want to predict certain targets on their DILI talks profile. Every time you can add one target or one molecule where you can say this has DILI properties, of course your whole system is learning. Yeah, and, and that's why a little piece of information that is wet lab proven or that is human proven that goes back into the system makes the prediction quality significantly better. And that's why I'm always coming back to this sharing principle of our industry, because it does not make sense if only one company is optimizing targets for dilly talks. But if you are having this capabilities to predict something like that and then you are sharing this, amongst the industry, then it becomes really powerful because then really the whole process for the whole industry gets more efficient and every individual also gains by knowing that the platform that they're using is better and better and better. Yeah.
But then, yeah, that's, and that's super beneficial for Evotech, I guess, as a platform.
No, that's, that's my point. It's beneficial. For the industry. Yeah. Because if you can exclude safety liabilities, let's say a year earlier, that typically means $5 million earlier in, in the early drug discovery and drug development process. It augments your opportunity costs. Yeah. By $5 million where you are depriorizing this experiment and you go to the next experiment. So that's where really everyone wins.
Yeah, but still, if you are— I mean, still, if EvoTech is a company who has, I mean, who has a toxicity prediction platform, you will still capture some part of the value as well, even though on the total everyone will win.
This is a for-profit business and we are not naive, so let's not go there. Yeah, okay.
No, it, it, it, it makes me also think about— makes me connect to, let's say, quite some pharma outsourcing their R&D, slash even selling part of their R&D. In Evotec, you've bought at least the site in Toulouse, I think, you from Sanofi. You bought recently, I forgot which big pharma, last month. No, from Galápagos in Paris, I think.
That was not us.
Not you.
No.
Oops. I guess you were on the deal. Maybe. That's interesting. But anyway, you bought quite a few like R&D capabilities slash serial capabilities from pharma. And then you, in essence, are like you do it in-house. Yeah. Can you like expand a bit there?
Let's step back here 2 seconds. Yeah, what I always thought is the most inefficient way of trying to, to do what we all want to do in this industry. We want to solve diseases. Yeah. And we want to make medicines that matter for patients. If you have a disease which is enormously large, let's take Alzheimer's. Yeah, and everyone tries to create a silo to solve that problem. It is per se inefficient. And again, this is not naivety here where I say let's share everything. I'm totally fine with being competitive and the fastest should win and innovation premium should go to the fastest and the best in the industry. But what we all should share is information that is helpful to everyone. And that's where, if you think back to the R&D centers of pharma in the past— by the way, they now are so much better than they were 15 to 20 years ago. Now they are really high, high, high performance organizations. But if you think back, yeah, you had an R&D center which was a cost center and which was only productive to feed one pipeline of one company. That there's a match of the capacity that you have, yeah, and the capabilities that you have with what your pipeline need is, is a very rare instance and it's very hard to keep it up. And all that Evotec has been doing in the past is to say, okay, why don't we create internal cost centers and make them profit centers that are not only there for one company, but that are there for many companies. And if you follow that principle, then all of a sudden an internal R&D center from former GSK in Verona, which has enormous capacities and capabilities, and if you open that to many players, becomes not a cost center that is quote unquote seen as how can we ever make this productive, it becomes a very productive profit center for many companies. And that's why we are just as a collective industry starting to learn these principles of the shared economy. And that's why we are just at the beginning of what we are doing.
It's, yeah, it's interesting.
And it's, it's one of the rare examples patients will win, biotech companies who work with us will win, pharma companies who work with us will win, and foundations who work with us and academic institutions who work with us will win.
I'm still thinking of playing the devil on what, who will, or who, who is losing what.
You're the nicest devil I've seen so far. But, but, uh, and if the devil looks like you, then welcome to hell. Um, then we should all go Sorry, no, but again, it's, it's also something where you should never underestimate how big the non-satisfied market opportunity is. Yeah, we are— I would totally agree with you if this would be a limited world where market opportunity is very small, then of course you have many downsides because then this ends in typically collusions, this ends in price competitions, this ends in There's many, many stupid things that markets do, all understood. Yeah, I even studied this in my past. But if you're talking about wide open underserved markets, then we all have all reason to go there, especially when you know that 3,300 diseases are currently not treatable or only under very, very, uh, symptomatic versions treatable. Yeah, so that's, that's really where I think the difference in our industry is, and that's why this whole sharing economy is just at the beginning.
That's interesting. I, I'm still thinking of some parallels in some— I mean, if you take probably the car industry is very kind of very open with a lot of providers and integration, but then some players, let's say Tesla, are very integrated and have also very good at, like—
Yeah, the car industry is very complex, and I never really understood it because I don't like it so much. But there are other industries which are much simpler. Yeah, think about the oil drilling industry. No one, no one, yeah, today is stupid enough to say, I drill a hole into the ocean alone anymore. Yeah, everyone has established a value chain, yeah, where you say, okay, this is core expertise of this company, this company, this company, and even the risk to drill at the wrong position you're sharing with others. Yeah. And if you hit the right point in the ocean, everyone wins. Or think about the movie industry where not every movie is a success. Only 1 out of 100 movies is a real success, and only 1 out of 500 is a true blockbuster. So no one today goes and makes a movie alone. Yeah, but it allows you to try it much, much more often. And with this, a whole collection of companies who are in this movie world together is winning time and gaining time to come to success here.
That's interesting.
Yeah.
I'm curious about one thing. I like talking with you also because you have really a big picture view of the industry, which is great, and I think great for the audience. But after 25 years of being in this industry, I think it's about time to understand a little Yeah, you understand, but you have a clarity to explain it. And you not only— I mean, you look really at the bigger picture, maybe also from your background. We'll talk about it, from being more from a business background than a pure science. I don't know, it's— you have this, this bigger view, which I like. You— one thing that I saw recently was from the number of drugs developed by who developed the drug and then who launched it. I don't remember, I think it was a McKinsey study, which is interesting. I mean, it's been 10 years that you always hear, okay, all the biotech is a powerhouse and most of the drugs come from biotech companies and then outlicensed to pharma. But I think in 2022, I was super surprised. I think was somewhere close to half of the product launches were made by biotech, like larger biotech organizations. Which means it's not only the development now, it's also more like the commercial launch. Can you comment on this? Or do you see this also as an EvoTech working more with biotech organization or larger biotech firms versus only big pharma? How do you see that point of the industry?
I mean, this trend back to fully integrated companies launching drugs is of course a function of, um, orphan diseases to start with. And it's also a function of people who have done something and seen something very successfully happening in large pharma or in mid-sized pharma companies, and then repeating this in biotech companies, because VC is putting them— which makes a lot of sense. And if you look at the success of Alexion, or if you look at the success of Algenyx, or if you look at success of many of the companies who basically were very clear in their vision. What does it take along the value chain and what do we have to build and what don't we have to build? For example, if you are making a drug, making your own manufacturing is a very, very important question to answer because building GMP systems in manufacturing is a high hurdle to jump over. And that's why many of these companies said no, we'd rather go to do the clinical, regulatory, and then sales steps first, then creating a manufacturing infrastructure or creating a discovery infrastructure. Yeah, is also something where you say why not doing this. So that's why where Evotec is going is totally clear. We will create a multimodality— we sometimes named it Autobahn to Cures— which is a data-driven, yeah, multimodality platform where we can offer everything when it comes to optimizing a drug target to bring this into clinical situations and then manufacturing also this either small molecule or biologic or cell therapy into the future. Where Evotec will not go— we will not go into running clinical trials on our own. That will be the exception also in the future. And we will definitely not go into selling our own drugs to go commercial. And there's a very clear reason, which is not limited by that we wouldn't know how to do this, but it would change the culture of the company dramatically if you all of a sudden have a regulatory sales environment and a marketing environment from product launches, yeah, on top of the culture that we want to create. Because we are creating here a science-driven culture where the 5,000 people that we have are roughly 4,000 scientists and 1,000 people doing other things in, in SGA functions or supporting functions. But we have more than 35% of PhDs in the company. This is the highest density of PhDs in any biotech environment that I know. And I think that's going to be our key strength also into the future, to keep the science power and run the platform with the science power, and then really we go for our co-owning model with our partners, who then have the strengths in commercialization, who then have that. Having said that, of course, there's a paradigm which I completely understand. If you are one of these biotech companies who has a drug in their hands which has a targeted market, yeah, then it is today easier than ever before to also go all the way through the market. And that's why this paradigm will come back and we'll see it more often.
Yeah, that's, I mean, that's basically what the study also shows. And I guess crossed with like having more experienced pharma executives running some of the biotechs, it's also more easier to go into commercials. I have some experience.
Must be smart people at McKinsey.
Maybe sometimes. But No, it's interesting. But maybe you can reflect also what you've seen in Europe. I mean, you have quite some, I mean, a few biotechs in Europe who have made it to commercial. And usually, I mean, it's also a huge value inflection point. And also in terms of exits, sometimes you most, I mean, quite often, I mean, Argenix is a great example. I mean, I don't know where the market cap is now, but I think north of $10 billion. So very pretty, I mean, amazing. Same with Arctelion, same with Genmab. I mean, can you reflect a bit, maybe more like you yourself, how you've used industry, let's say, on the last few years, especially as a European industry? Like, yeah, bouncing on what I just said, what's like, what's—
I mean, first of all, all these companies that you mentioned don't have anything in them which is purely European or purely driven by Europe. And that's, I think, always my starting point. If you look at the successful companies, they have a global scientific lead with a global mindset to win global markets. And if you look at Jan van der Winkel and what he has made of GenMap, there is a Danish company that is a global leader. And if you look at Argenix, that's a a Belgian company that is a global leader. And that's how it should be, because there's only one disease and that's globally the same. And that's why our industry is the worst advice industry if you go to anything that is national-driven or whatever. What makes sense is you have to have scientific hubs and biotech hubs where more energy is coming together than in places where people don't understand the dynamic of this industry. And that's why I I think there's a function that we are experiencing now where Boston, San Diego, San Francisco had really this, this huge advantage about 10 to 15 years ago that a biotech hub was happening there, and that's why collective learning was faster happening than in remote places in Europe. It's a fair comment.
Yeah, it has less proportionally, has less biotech.
It's an absolutely fair comment. And that's why for us networking Hamburg into the world of drug discovery was an absolute must from the very beginning. And that's also what we have done from the very beginning. And that's why, for example, at our site in Hamburg you will hear everyone talking English to you.
Even the signs in the street, everything is in English.
Evotec is built for a global company that people can come to Hamburg and feel at home and integrated. Yeah, because otherwise there is no Hamburg-based drug that you can sell only in Hamburg that will ever make it to the market. I think that's clear to you. But, and that's why I typically don't like it to reflect on Europe. Because you have to be competitive on a global industry.
Yeah, but maybe not the, like, success, or like, I mean, I like your answer, and I mean, I share it completely. And even when I was running Labiotek, where, you know, a European slash global from day one, and very, like, always speaking English, like, and this is, I think, fundamental. But I don't think that many— I mean, not, not everyone in biotech in Europe is doing this, which is a bit surprising as well. But I think The best ones are doing it, and it seems like pretty shared among the best, either the even small biotechs, big funds, anyone is doing.
But yeah, but it's like a one-on-one recipe for everyone who starts. Yeah, and I don't say this because I, I want to be here, we know it better than others, but it, it limits you immediately in your growth. For example, if your company culture is French only. Yeah. And our people in France didn't like this at the beginning, but now they understand it. Now they totally understand it, and they understand that if we want to be competitive, then we have to be open-minded. And you will see if you go to Evotec in France, it is amazingly international.
Even in Toulouse, which is not the most intentional French city.
Which is an amazing city, by the way.
I guess it— I mean, I just looked up coming to Hamburg that you had the Airbus site really close by. So I guess the Airbus site also in Toulouse. It's kind of a connection of sites. You can share the planes.
No, we don't. Because we are data-driven. They take planes.
No, that's— but no, I mean, it's fair. But I was more thinking for Europe on how you— well, I mean, more quickly, not really looking at the success or what's the success factors or how's the company from inside, but more seeing the ecosystem.
I'm very positive. Yeah. Yeah. Because you have seen the worst funding environment in the last 2 to 3 years. In the US but also in Europe. And nevertheless, many very, very good funds have come together in Europe now. And if you look at the talent pool of the, the top VC groups in Europe, this is amazingly cool people. And on top of that, you had a cash inflow from private equity funds who understand that biotech and healthcare will be their future key playground, and they haven't been here so far. So I think there is really a flow of capital waiting to find the industry opportunities that they need to see. And here I think Europe is, is open for that because the classical VC sources are not operating. And, and that's why I'm actually here. From all the science and the science projects that we see, matching this with, with the flow of capital and also the, the newly raised funds of VCs, it could be a very, very good next 10 years coming.
I had a question on the private equity part of— because I mean, we talked with Antoine from Sofinova with some money from private equity, but still only— and open the capital to private equity, but didn't sell the fund versus some funds were sold, say LSP, let's say.
LSP became part of Equity. Equity. And you have— Abingors. Abingors became—
Carlyle, I think. Carlyle. Carlyle. Um, so like, and then I had a discussion with one, a lot of private equity were also investing in healthcare, but a bit more general, like hospitals. And, and I know that a lot of CROs also owned slash run by, by, by private equity in that. But on that side, I heard not necessarily positive, and I hear that it's like basically printing cash and doing that. So what's— I mean, I guess private equity in general, I mean, there is for sure huge influx of capital, but there can be some flip sides. Like, do you see that? Do you, like, I'm concerned?
I think it is— I'm— no, first, I'm not concerned when anyone understands that investing in healthcare is in general the best sectors that you can deploy money with because there's a real need that can be solved. And if it is solved, it creates value. Yeah. So that's why I'm always surprised that many people still have not realized how big the overall opportunity in healthcare is. Much easier in our industry, I think, to create value than in the fashion industry. Where you are competing brand versus brand and where you're competing season versus season and where you have volatility, especially from a human, like, even society value versus monetary. That's even a different topic. Yeah, but, but also don't want to go there. But I think that that's clear. And what is also clear is if you look at healthcare, that so far all these funds have only been able to dig deeper into business models that had a top line and that had a bottom line. Yeah. Of course, if you go to true innovation business models, a top line and a bottom line in that format don't exist.
Yeah.
So that's why I think you see here an evolution that private equity started to understand the CRO industry faster and better because there was a top line and bottom line. But the underlying science, Yeah, will automatically bring them earlier and earlier in the value chains. And that's why you now see these moves of the private equity funds into the venture funds as a hedge to not only take one company but take portfolios of companies. And that's, I think, a great starting point. And many people expected that this will turn on the pipe of money within a quarter or two. No, it will take 1 to 2 years, but then it will be a constant flow because that always happened when private equity entered a new industry.
Yeah, I guess they enter for like 7 to 10 years.
But it now takes, but now it takes 2 to 3 years for them to fully understand these industries and then to fully understand the dynamic of these industries. And then you will see there's a new flow of capital coming in, which will be very good for many.
That's interesting.
The flow of capital that unfortunately has stopped at this stage is public money. Yeah. And that's why I think it, it will take both for a full recovery of biotech. It will take the flow of private capital and it will take the flow of, of public money as well. Yeah, it's interesting.
I like your interesting view. Very I'm always a bit reserved, but I don't know, it's my personal feeling with private equity. But yeah, let's see. I mean, so far, at least bringing capital and still the—
I mean, I guess if it's like making return but not like outsized returns, Yeah, but I think also here, if you look at the business model of venture capitalists over the last two decades, you have to, to really look behind the curtain. Not every VC fund was, was outsizingly successful. Yeah, many of the VC funds didn't raise a second fund because they just lousy returns. Yeah, so don't be fooled by the Prada, Guccis, and Armanis, yeah, of also the VC industry who had very good successes. But then they first have to repeat the successes from fund to fund, and secondly, yeah, you should not underestimate how hard it is also for VCs to make a sustainable business model out of it.
And that's again, the VCs, um Not too worried, I guess. More from like, it's more like I've seen so many like bad examples of private equity funds who, you know, buy a company and then 5, 7 years and just half liquidated or half like dilute and extract a lot of value.
No, but that's also here, I think no one— yeah, if you go to the Roman Catholic Church, you should not be surprised. Yeah. If someone says amen in the church. So the rules are clear. Yeah, yeah. So if you're talking to private equity, the rules are clear. And if you are not certain about what the rules are, then you should stop the dialogue. But that private equity is there to make money with investments and smart guidance of companies, that's their business model. And that these are business models that have time limits That's their business model. So I think no one should be naive here, and that's also not what I'm sensing, that, that people are naive on this one.
I'm curious, uh, no, that's, no, that's, um, that's good. And enough on this topic. Maybe we can switch, uh, more to, to you yourself. Um, you, we mentioned it briefly that you're very good, like overview and understand the business landscape. What is— I mean, when we discussed, you, you don't have a bio slash biology or biotech like diploma background. I mean, you come from psychology with business. Um, how like did that— and, and when I talk to you, I feel like there is a lot of like— there is a you are talking differently than someone who has less robotic background, or like you understand very well and good enough, but it gives you also this like bigger picture and also psychology. I can sense or I can feel some things there. Like, can you walk us a bit through of like how was it to get into the industry and to like get this like expertise until now, how it helps you or how you deal with it, how you deal like currently to not necessarily have this like super deep biotech background, even though I think you probably acquired it. But can you walk a bit through that? I mean, it's pretty rare in the industry to not have really a scientific background.
So, so I'm in this industry for 25 years and I now can really say that I fell in love with this industry 25 years ago. Because before that, I was a consultant in many different industries, which already gave me the advantage that I have seen the pulp and paper industry, I've seen the railway industry, I've seen— as a consultant, I have to say— I've seen the insurance industry and I've seen the banking industry, and they are all wonderful industries. But if you can see the magic of what, for example, an antigen and an adjuvant do in making vaccines happen. And if you can be part of that, then all of a sudden all other industries to me were no longer so attractive.
Attractive.
Then I entered this industry, which is, I think, also important, via my core competence, because I'm a finance guy. Yeah, I was a CFO of Intercell and That's also then, I think, quite interesting. You can then have a different path as a CFO that you get totally fixated on the core business substance, or you try to understand the dynamic of your numbers. Yeah. And that's the beauty of our industry. The dynamic of our numbers is driven by science.. And it's not driven by interest rates. Science is a so much more powerful tool than interest rates. Yeah. And that's why I really understood probably relatively fast as a CFO that if I don't believe in the science that we are making, we will never be a successful company. Yeah. And that's why I started to simply talk to the people who do the science. And, and that's the beauty of, of my life, that I just get excited when I hear a scientist talking about his latest experiment, knowing that not all of them will work. But you can see why people are doing this, because most of the people in this industry are truly motivated by finding a drug, finding a solution. And yes, it's not always that esoteric that you are only thinking about the drug out there, but you also have to—
or just doing amazing science as well.
Exactly, yeah. But you also have to do sometimes a very tactical job, but it nevertheless feels so much better in this industry than what other people can do. And that's why it's a privilege to be in this industry.
And so over 10 years, you kind of got yourself into an understanding, I guess, was vaccines, Intercell, the vaccine science. And then how did it help you, the jump to, let's say, CEO, where you were managing much more than the finance, like, of the whole company? How does it help you today?
Like, at the end, you have to find a business model that you feel comfortable with, that you are representing. Yeah. And at Evotec, we, we are representing a high science-driven R&D model that is linked to a partnering model that ultimately will result in a large royalty pool. And I think in 2009, when we started or restarted Evotec, in a way, that was for me very clear that that's the way I want to go. But it was also very clear to me that this is the long run, yeah, because there is no royalty pool happening in 3 years. And there is no royalty pool happening without volatility along the way. And there's no royalty pool happening if you don't fail. But what was very clear to me is that it will only work if we are creating a sizable portfolio of options, yeah, to really leverage against the risk that many of these things are just not scaled enough. Yeah, and, and I think that's all it took to, to make this transition. And now it's about having an organization that, that is efficient together with partners finding drugs.
We'll go back— I mean, I think we'll continue on EvoTech as an organization, but on, on you yourself It sounds like it was the right fit for you, as in like being pretty like very knowledgeable on the business side of like, okay, sharing the royalties, making partnerships, building this while still having a science foundation versus maybe developing the next mRNA therapy and being the CEO of that kind of company.
I would not exclude that, but It's also, yeah, it's something where, um, that you are exactly there at the time of a drug where it shows that it's not only a good experiment but it will be a product that sells. That's a very, very rare moment. Yeah. And that's why, for example, it's very rare, first, that products go to the market, second, that it's a company that brings that drug to the market, which has done this from the beginning to the end. And thirdly, that the company who does this makes this in a repetitive fashion. Yeah. And, and that's where for me it was very clear, um, that it needs scale in, in a business model to have these opportunity spaces open. And that's That's why again, I'm open for many things, but what we are doing at EvoTech is just a very, very good business model.
Yeah, I'm still trying to stay on the, like, maybe not just your background, but where you are staying today of like your skills, still trying to get a picture of yourself, of your skills.
I can make good PowerPoint.
No, but still, with this, because for example, I feel like you, you have— I mean, I mean, trying to, yeah, to understand where your skills are, like where your personality and skills and how it connects to background, that maybe it's not necessarily just to your background, it's maybe how you as a person, but how Like, how do you see yourself, let's say, from a skill set, personality, to do that role, a CEO?
The biggest ability here is that you have to be able to surround yourself with people who are better than you are. Yeah. And I think that's, for me, so humbling every day that I know that I'm one of a team and I have so many people in the company who are in many, many areas so much better than I am, but I can trust them. And for example, I really have the tendency to work very long with the people who want to work with me because that's, I think, an ability that I really value a lot, that I can trust people.
You mean long, long term?
Long term, yeah. My CSO and I, Kurt Dorman, we are working together now for 11 years, or our COO and I, we're working for a decade. So there's just— because that's where you then become all of a sudden as a team efficient. Having said that, it always is important that teams don't become complacent. Yeah, so having here this dynamic that you still have a good fight, yeah, that you still have a good fight and not everything is happening at the lowest compromise. That's important to make an organization grow and to push an organization forward. And at the end, you always have to question yourself. Are you still the right leader for a company for the next phase of a company? Are you? I'm totally.
Yeah. And so maybe how did you— this question, I mean, I think, I mean, it's a very hard question, a bit challenging question, but How did you answer that question? I mean, when you got in, I guess you had already a very long-term vision, but I guess you had some milestone of, say, whatever, 3 to 5 years maybe. And then you re-iterated. I mean, now it's been 15 years. How did you go? Like, was there some big milestones, some cycles?
There was a very big milestone at the beginning where the idea of discovery can be a profitable business did not exist in 2009. Yeah, because discovery up to that point was a cost center and was a loss-making part of the industry which was highly disregarded. So that was really a first milestone to say, okay, can we make a business model happening where discovery, highest science, is appreciated as a profitable business? And that was important for, for us. And from there on, we really wanted to explore especially platform worlds where, where we are leading the field by not only going after one target or one idea, but really building a platform.
And I say this—
yes, and I start with omics-driven drug discovery and drug development, where Evotec today is building the most comprehensive systematic and unbiased world to understand proteomics, genomics, transcriptomics, and translates this via disease models, but also starting with molecular patient databases in more efficient processes than I think anyone else in the world. But we built a company that is, that is fundamentally believing in omics. Yeah. And why do I say this with all this emotion in my voice? Sorry about that. Because it was a very radical decision in 2014 to say, okay, we believe that omics will be the future where the computing power was not there, where the data was not there, but where it was clear that we will understand biology down to its single cell one day. Yeah. And that's where we were coming from. And that's what we built as Parnomics as a platform. The second platform that we built was really a full belief in a switch away from not very telling animal models to iPSCs, so induced pluripotent stem cell-driven drug discovery. And iPSC-driven off-the-shelf cell therapies. That was a decision that we made in 2012, shortly after Yamanaka got his Nobel Prize, to say, okay, we're gonna go down that path because if this is true, then many diseases will not end with symptomatic treatments anymore, but they will be able to be cured. And that was the paradigm shift. And the third platform that we have really a lot of confidence in is to build a completely new access world for biologics. And what do I mean with this? With what we're doing in just Evotec Biologics will allow us to make antibodies not only more manufacturable and more efficiently usable, but also it will allow us to make cost of goods for antibodies happening that will be first allow many disease areas also to be treated with biologics, which today is not the case, and secondly, which will allow us to make drugs at significantly different costs and price points in the future. And with this, you give wider access to biologics, and that would be just an amazing contribution of Evotec, not only for the company but also for the world.
Yeah, so if I understand well, for you yourself, there was a lot of mindset tied to the company of like, will we achieve this, will that decision bring fruits, and then this brought back to you yourself of like, okay, do I want to continue or not?
No, for me it was always, is there still enough vision in myself to go to work every day in the morning and see where we are going. And you wouldn't believe it, but we are just at the beginning. Yeah, because there is a market environment of $140 billion spent every year in research and development. EvoqTech does not even have a billion in sales at this stage, but we are owning some of the core technology platforms that, that we can bring forward in the future. And This together with our partners will be very powerful.
I still want to stick a bit more with you than you would think. But I mean, I feel it very— feel it amazing. I mean, I was meeting another CEO and he had very— I mean, he was very rapidly always going to the team and to the organization and not necessarily talking like even not that comfortable talking about himself, which I find very also a very good sign actually as a leader to see much past ourselves and very little ego, or how you want to define ego. But still, I want to understand a bit like what's behind you. Maybe that can be one point, like you, I feel like you're very I even said it in the intro, very accessible, friendly, humble as a person. It's a compliment, but I really feel that. And I'm very curious, like, if you are like, if it's just who you are, or if there's like you had like trying to maintain that? Or you're like, is there something around there or something you can share around this notion of like, because I think it's a, yeah, it's something pretty unique with, with yourself. And yeah, can you—
yeah, so first of all, thanks for saying that and for obviously, um, feeling it that way. And secondly, I just don't see any fun in pretending anything that is not authentic to me. Why should I do this? And first, it would be completely inefficient. Secondly, it's not what I want to do. And thirdly, I always hope that everyone who I'm friendly or clear to, is also friendly and clear to me. And I say this because I make decisions, yeah, a lot, and many of them aren't pleasant for an R&D project. And, and, but what I'm hopefully doing is not making decisions without rationale and not making decisions on a on a too personal basis. Yeah, and of course we all have our personal biases, but, but I try to be analytical to the decision, and then people can take decisions, and then they perceive them as not totally unfair. Or, you know, as you just mentioned it before, when you're in crisis mode, you have to have a different speed of decision. Yeah, and people will then only trust you that you're doing the right thing if they have experienced you doing the right thing also in the past. So that's a bit where I'm coming from, and that's also, I hope at least, how I behave, not only in the company but also outside of the company. I don't wear different clothes outside of the company or inside of the company. I don't talk differently. I don't, you know, for me it's maybe it's too close because I don't have this differentiation of private and business as much as probably I should have it. But, but that's why I, I'm quite balanced also on, on that front, that there's not a second, a second Werner somewhere. It's no avatar.
But is that something— I'm still curious, like, how much is that something that you had like inside of yourself, or something you cultivated, or is there something you try to work on, or is it Like kind of very natural listening to you.
You're on— I probably also, when I think back when I was 25, I had this idea of I want to have a, a big career, and big career was then associated I want to have a big car. Now that's the worst dream I can have in my life. Yeah, to just— what, why do you do it? Yeah, what's the, what's the prize at the end? Yeah. And that prize at the end has for me totally changed. Yeah. That now it's for me to say, okay, I want to build a company that has true relevance. Yeah. In this industry, to our partners and to patients. And if I'm the one who can drive this and if I'm the one who can do this together with our team here, then it's, it's a privilege to, to get the buy-in from others to do this together with you, and you even get paid for that privilege.
Yeah, that's— and the why— yeah, you sound like you're clear, clear-wise, but still, I'm still curious on the, like, on how, like, how you— yeah, how how you cultivate or not cultivate or where it comes from or how is it like?
It's a so much easier mind map to create for yourself if you are running a portfolio of 10 neuro projects. Yeah. And we do this together with BMS where you can see, okay, this could be the next generation of neuro projects. That really make a difference in a world where there's no cure. Yeah. And not even a treatment. Yeah. And if you understand that this is the core business that it's all centered around, then the rest becomes significantly less important because that's then the core. And that's where— then that's what drives me, that I say, okay, do I see the core of what we are doing or don't I see the core? And the core is not that you have a fancy dinner at some place, which I also like, by the way, but, but that's not the core of this, of the, the industry, and it's definitely not the core, the goal of the company. And that's why coming, as you want to have it personal, as long as I feel this when I go to work, that the core is exciting, then it's not, then I don't need a motivational trainer or a psychologist or anyone then science is motivating in itself.
That's amazing. That's amazing. I'm— from what I hear still, I mean, it seems very obvious to you and very deeply integrated. And I mean, probably also with experience, there is some— it brings it as well. I mean, even what you said—
I'm an old man, I do this for 25 years, and of course there is a different tone to this than 20 years ago. And I made more mistakes than many other people in my life, but at least I tried to not to repeat them too often, and I tried to learn from them. Yeah. And if you keep this ability, then, then you can always test drive yourself and say, okay, am I still doing the right thing? And that's for me not a question.
Still sounds like it's— yeah, I mean, even me personally, I reflect on this and it's— I think like I don't tend to be very humble. Like, it's something that I don't tend to be super humble already in the past 10 years.
You speak Chinese, you should be proud.
Yeah, can be proud, but I'm not necessarily super humble about it, or like And when you— well, if— yeah, anyway, it's— if something is important, how do you— can you, like, you know, like, not mimic it, but, like, make it more important, or work on it, or change some aspect of your personality? It's something that maybe also—
what clearly does not work, yeah, you cannot do something which has a long time horizon and not be authentic about it, because then it kills you. If it would for me be hard work to believe in what we are doing every day, it kills you. If for me it would be hard work to come to be convinced about the company and try to go to an investor, it would kill me. At this stage, it's not even— I perceive it as a privileged dialogue because there is no hardship There is no pain. There is— it's— and I think that's a bit where, if you want to go into advice mode here, that's a bit where I would advise anyone to go and to say, okay, you have to really believe it. Otherwise, it's too hard.
So, yeah, believe it. And it sounds like a lot of the things you do basically daily just fits really well with your whatever system, whatever value whatever your core—
and whatever challenge that comes. It fits really well because there are, in our world, there's a challenge coming every week or every day or every month where you say, "Now I'm really fed up." But if what you're doing is giving you this light at the end of the tunnel or this picture beyond that, then it's so easy to motivate yourself and then you say, "Okay, there is a drug that failed, but that should not stop 199 others. Exactly. Yeah, I guess that's why we also— and I, I really, I'm kind of proud about this, I have to say. In 2009, I wrote our, our slogan: Mission never— research never stops. Yeah. And, and that was And it's still the same tagline I would write today.
That's amazing. That was already a great fit 15 years ago.
That's great.
Maybe one thing a bit personal as well. What's from day to day, what's a typical day in Werner's shoes?
Werner gets up at about 6 o'clock in the morning. Do some push-ups. He doesn't do push-ups, but you do. Sometimes he managed to run, which I like a lot. And then I try to do emails at home. Then I go into the office where I have the idea cultivated that I try to be as much as possible outside of the office. And that doesn't mean that I'm not working, but my work is better done when I'm with partners, at conferences, when I am with investors, when I am on site of one of the 17 sites that Evotec has. So that's why I'm rarely in my Hamburg-based office, which makes me nevertheless be fully connected. And that's maybe another thing. We created a virtual management team structure way before COVID in 2015 already, which makes us also as a team be quite efficient that we can work together despite the fact that we are not on the same places all the time. And then I typically work more than 8 hours a day and most of the times end somewhere north of 12 to 14 hours a day. But I never count and would not know who to tell what I'm counting.
And you sound pretty, in your day, also pretty balanced. Or is it not like somebody will, let's say, relaxed about it? Or like very— not, not relaxed, but balanced.
I think if you don't have stress, you don't live. Yeah. If you're not excited about certain things, then they are not a good enough challenge.
It doesn't overpower you.
There are moments when you are afraid, there are moments when you're excited, and that's again reflecting about it, if you are not excited anymore, if you are not feeling kind of lampenfieber anymore when you go, I don't know, to a discussion meeting or to a negotiation, then you probably shouldn't do it anymore because then you don't have the stamina to do it anymore and the energy to do it.
It's interesting. Yeah. It rings a lot of things in my mind, but that sounds, sounds very good. From, you want to maybe, I mean, we can start to wrap up. We touched, I mean, on EvoTech, just from wrapping up, but we, you touched quite a lot of things on the different platforms you're building. I walked around the building just there, but the new IPSC Building coming.
I mean, yeah, that's a good example of something where when you take the risk—
10 years ago, it's crazy.
When you take the risk of building a new building where this— where it takes 3 years to really have from scratch a building done, how many things do we know that will happen in 3 years from now and what the experimental cascades will look like in 3 years from now? Yeah, so that world and the world looks like— yeah, yeah. But again, that's why making these long-term CapEx-driven decisions is something where I'm totally, um, alert about them. For example, we are at this stage investing into just Evotec Biologics, our J-Pod infrastructure for lowering costs for biologics. $500 million. Yeah. And, and that's a lot of money where the underlying hypothesis that this will create value and this will be highly profitable, that's a big, big, big decision. Yeah, that's a really big decision.
I guess no, like, not really miles. I mean, the go/no-go is like really— I mean, building a building is really like building a building.
Many, many but creating an authentic business plan that utilizes subchain infrastructure. Yeah, that's, that's where I get really excited and say, okay, do we do this now or not? And again, creating $500 million for novel biologics as an infrastructure and creating 600 jobs just for that is, is also the responsibility not only to your shareholders who give you that money to do this, but also to the people who you say this is going to be your future. It better be right. And not everything will work out, I'm also sure. But on Justified Politics, I'm sure that it will work out.
You sound pretty confident. I mean, also what I mean is that it's not like, let's say, in more software where you every 6 months you can reevaluate and you can pivot. I mean, here it's like a, it's really big commitment and a very long-term commitment.
And you, until you see if it works or not, it's like, and that also comes down to the business model. If you are Sanofi or BMS or whoever, you want to work with a partner who is just as long in the game and committed to the game as you are. Because otherwise, no one would be well advised to work with us if they have the feeling tomorrow they will go away, or tomorrow they will just exit, or tomorrow they will switch from this modality to that model. So this is also building the trust to our partners, and this is also the reason why once partners work with us they have a very, very high retention rate to come back to us. And they are also happy to acknowledge that by paying prices that are probably sometimes a bit premium compared to others. But then they— our people understand and our partners understand what opportunity costs are. I think that's the easy phrase for that.
Sounds like, yeah, it's a good, good, good way to, to, to, to wrap up on that. I mean, sounds like I like this very long-term vision, and I mean, crazy also how it worked from, you know, IPS in 2012 until now. It's crazy how a lot of long-term bets worked and how you yourself also think very long-term and how you yourself think also very long-term from a does it fit to yourself Like, can you, like, like, you want to add something there on the, on the, on the long-term thinking or how you cultivate it?
How you, like, I mean, IPSC is a very good example for that because I of course did not understand everything that was behind IPSCs, but I completely understood for the last years already that we as an industry are, are just not evolving if we are basing our decisions on animal models that are completely dislinked very often from the diseases that we want to solve. And if there is a model system out there which is directly from the human modeling to the human, then this is a clear evolutionary step to, to make. And I was actually totally surprised that not many more people have done it. Now I am not surprised because it is hard to do this. It's hard. It takes time. You fail a lot. But if you're getting there, then you are leading this, this, this platform. And that's why you have to, to reduce this to the simple question: do you trust an animal model more than a human model? Yeah. If this is giving you education for a drug discovery process, and that's a clear answer.
That's a good, yeah, I like that also, the shift from animal to human-based research, and it will come more and more with wrapping up on like AI/ML-enabled research. I mean, a lot of exciting times, exciting times ahead. Maybe as a finish, if people want to follow you or learn more about you or yourself or EvoTech, what's the best way to On Evotec, we are very prominent on LinkedIn.
And if you want to write me, I have a temporary email address which is werner.lantala@evotec.eu, but my permanent email address is werner.lantala@evotec.com. And I, I don't, I don't have an Instagram account or something like that, I think.
Yeah, you share on LinkedIn maybe?
I do LinkedIn, but I don't have a thing where people can follow me. I only like others on LinkedIn.
That's great. And, um, no, that's, that's good. And actually, I haven't seen many— I haven't seen any podcasts where you— where we call it any podcast. So I hope I did well, and we can do that again soon. Thanks, Lena.
Thanks a lot. My pleasure. Thank you so much.
Here again, I hope you enjoyed the conversation and thanks a lot for listening to the end. If you're keen, please hit the follow button somewhere, maybe, or the like, review, share button, share it with some connections. It would help us a lot, especially this early in the show. And before telling you more what's behind the show, I want to say big kudos and thanks to the team: Kiran, web development, Catherine in marketing, Mary-Anne, logistics, Wayne in editing. They did an amazing job and there's a lot of hard work put into the show. So now, what's behind? Flood.bio, the company, was founded in March 2022. I'm one of the founders. And previously I founded labiotek.eu. And we started the company building a marketplace for the biotech industry, but we didn't have enough product-market fit, so we decided to pivot to a content business with the first product being, being that podcast. We don't want to create, you know, yet another podcast. There's already a lot of them around, but we believe Europe needs a high-quality, long-form podcast to help both professionals and biotech enthusiasts be better informed, grow, and just be better at what, what they're doing. And so that's why we are creating the podcast. We are selecting the best Europeans in biotech we can find and We are interviewing mostly actually offline so we can have really the highest quality, both technical aspect, but most importantly on the dance and the content and the flow of the, of the internet content. We release one episode, around one episode per month on all the major platforms. Money-wise, we are financed by our own private investments, and our business model is based on advertisement, so it's the sponsored messages, slots that you see in each episode. And we are sponsored by financial support from individuals and corporates. So anyway, I will not make it longer. If you are— I hope you share our vision, and if you're keen to hear more or you want to reach out or you want to share some feedback, please shoot us an email: hi@flot.bio. Again, thanks for listening and see you in the next episode.
Bye!
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