Dassault Systèmes SE (DSY) Earnings Call Transcript & Summary

Good morning. Good afternoon, everybody. Welcome to Morgan Stanley's Global Healthcare Conference. Very pleased you could join us. My name is Adam Wood. I look after European technology research at Morgan Stanley. Today, very, very pleased to have Rouven Bergmann with us, who is the COO of Medidata Solutions, which is part of Dassault Systèmes. Rouven, thank you very much for taking the time to join us at the conference.

Thank you so much, and great to be with you, Adam and everyone.

Great. But just to get the disclaimer out of the way to start off with before we move on to more interesting things. So very quickly, for important disclosures, please see the Morgan Stanley research disclosure website at www.morganstanley.com/researchdisclosures. If you have any questions, please reach out to your Morgan Stanley sales representative.

So right, Rouven, let's start talking a little bit about the business. Now it's an interesting discussion because there's going to be a lot of health care investors in the audience who are looking at the pharma companies. You're part of a technology company. And I guess the investors that are here will probably be very familiar with the clinical trial process and maybe a little bit less familiar with what Medidata and Dassault bring to that process. Could you maybe just help us to get a level playing field of understanding? Just give us a little introduction to what you're trying to solve from a technology point of view in that trial process, please.

Absolutely. Thank you, Adam. It's a great question. I think to start off with, it's -- what really unites us with the industry is that we share the mission, right? Our mission is to power smarter treatments and healthier people. and that's what was in place. It is our DNA at the start of the company over 20 years ago as Medidata. And that's still what propels us forward today. That's what has been the DNA and the foundation for the company for many years and continues to be as we think about the future. So we are very aligned with the industry and our customer as it relates to our mission and our purpose. I mean we started 20 years ago, 1999, it sounds like a crazy number, it's a long time ago, to really rethink the data capture and clinical trials with the EDC system, electronic data capture. And with that, at over 20 years ago, that was revolutionary because, traditionally, back then, the data was captured on paper. The data was captured in devices, right? There was no real-time connection. Really, with the Internet and cloud applications, we are born in the cloud, where we used the earlier days of the Internet, right, really to connect the clinical sites with our database so that you can actually -- we could centrally capture all the data and create a unified repository and database for every clinical trial that was going on in the world by our sponsors operated by various clinical sites. So we really designed our approach always from a perspective of thinking about the network, right, that needs to come together to deliver the outcome. And of course, EDC, that I think the audience is very familiar with, as a category, has evolved tremendously over time, right? What we used to have in the early days is not the same what we're doing today. So we today built, according to our perspective, the most sophisticated and advanced end-to-end solution, right, to really orchestrate the activities in clinical development from the consent process of patients, all the way to the submission of the data to the regulator -- to the authorities. And in the core of this, of course, is the ability to capture data, and the data capture has also changed. The data capture is not necessarily today only happening inside the clinic. Data capture can happen through sensors. Data capture can lead to patient reported outcomes through images. For example, we transact almost 0.5 billion images per year through our platform. So we have a massive feed of data that comes through images. We have now over 6 million patients in our clinical trial platform and have conducted over 23,000 clinical trials with about 6,000 concurrent active clinical trials that are in execution right now on our platform. So we have a massive scale, right, and reach of the overall participants in clinical trials across the industry from pharma companies to those who actually are executing clinical trials in the clinician network but also now very focused on accelerating to patients directly. So the remote component of decentral clinical trials has been an area that has significantly accelerated here, as Medidata have been, I would say, leading that technology evolution very, very early on. I might remember the audience that we made an acquisition in 2016 of Mytrus, which was an early start-up back then for electronic patient consent, which was very new. It's still very early, electronic patient consent, most of consent is paper-based. It's very hard to do because of all the data privacy requirements that you have to comply in different countries. But there's a lot of progress that has been made, and you need to invest upfront in order to then educate regulators and change the process, right? So that's always been our mindset to drive innovation to our customers. And through that process, now we see a step function change in the adoption of this technology, also driven by the effects that the pandemic has created. So -- I mean that's -- we can now dive into a lot of detail around the different capabilities we bring. But I just wanted to share at a high level the evolution, right, and how we are aligned strategically with our customers from a mission focus perspective and how we think about innovation that we bring to our audience -- to our customers and to patients, that's what's really propelling us forward, and the level of scale we have reached already.

Perfect. I mean, you're absolutely right. That gives me a lot of things that we can dig into straight away. Let me just remind investors, if there's any questions, please put them up. We'll try to get to them as we go through the session. I'll do my best. Maybe just -- so I think the 3 things I wanted to dig into are platform, data and then pace of change. Maybe let's start with platform. So it sounds to me, you started with electronic data capture, but your vision is much broader. You want to automate the entire clinical trial process, collect the data and manage that. Could you maybe just talk a little bit, are all the solutions that you need on that platform in place today? And where are we in terms of adoption from a pharmaceutical and biotech company point of view? How far have they gone in that journey with you?

That's a great question, Adam. I think our vision has always been very strong as a technology and software company to automate and simplify the clinical trial process as well as created real time and engaging, right, and data-driven, right? So the clinical trial process is a very data-centric process because of all the different granular data elements that you have to report. It's highly standardized because it's highly regulated. So it gives us a very solid understanding of the process, but it's also transforming, right, because the science is transforming and changing, right? We see that a significant amount of approvers -- of new drugs approved by the FDA are now cell gene therapies. So they're a very different paradigm than the traditional life cycle of drugs before that, right, which was more of a chemical process and more oriented for masses versus targeted populations. So -- but the reason I'm saying that is when we think about the design of the platform, you'll have to keep in mind that it's a very dynamic environment and that, when we offer our platform, our customers, irrespective in which therapeutic area they are, they use the same technology. You can configure it based on your clinical protocol, but it's pretty much the same solution. So that, I think, is an important part. It's not that in order to adopt these new types of processes, that we would have to really reinvent the way we do things. No, that's already in place. I mean in terms of high-level functionality, really, it's still -- it's from the design of clinical trial to operating the clinical trial, all of those aspects that we cover operationally running a clinical trial, including randomization, a drug supply management, risk-based management, risk analysis on your data, so electronic reported outcomes, patient reported outcomes. I mentioned decentral clinical trials are now becoming a really important component. CTMS payments to sites and even now to patients, that's the future, right, that we think of to pay patients directly from sites to patients. There's a significant shift in terms of the power that moves from sites to patients and in past patients in clinical trials. So we really think of this very holistically. And now, of course, as being part of Dassault Systèmes, we have further broadened our scope, right, in terms of upstream to research and discovery but also downstream into manufacturing and commercialization, where we have a rich set of capabilities and experiences from other industries, predominantly, in terms of simulation, optimization, management of entire supply chains to really scale production processes at highest level of quality. And we've seen through the pandemic why this is so important. So right now, we can really think of an end-to-end approach to transform from discovery all the way to commercialization. Now that is our future. That's why we are so excited about the future, right, to have all these capabilities that we can bring to our customers and gives us also the opportunity to come from different angles, right? If you go back, Medidata before, we were always meeting very narrowly our conversations, right? Now we are expanding significantly in terms of strategic relevance we have and where we can engage.

So -- and that's interesting that you mentioned the platform expansion because of the acquisition of Dassault going back into discovery and manufacturing. It actually broadens even further what you're doing. So that's a really helpful insight onto the platform side. Can we maybe then talk about data? You've talked where data has come up a huge amount in our conversations so far. Could you talk a little bit about the data that you collect, and then maybe, more importantly, what you can use and how you're starting to use it? Is that to optimize the trials? Is it actually being brought back into the discovery process to help the construction and discovery in the first place?

Yes, absolutely. That's a great question. I mean there's a lot of hype around data and AI in this sector. The reason why we are so excited and see this as a real step function change, a game changer for the industry and our ability to work with the industry is that we are in a position today with our core systems that we operate 50% of the world's commercially run clinical trials on our platform. So we are essentially providing the infrastructure, right, the parts to manage the data in clinical trials at a very high scale. And I gave you some numbers before in terms of the -- since our existence, right, kind of what we have achieved. And I talked about 23,000 clinical trials that we have run on our platform and over 6 million patients, that means that we have very, very broad data across many therapeutic areas that we can report for them, right? And so when we say reporting, there are different categories, right? There's operational reporting, but there's also the science, right, where we have the data from the clinical trials from. And so that has given us a position. It's always important we talk about the data, that we also talk about our core business model because we are not a data acquirer, right, where our -- the data comes from the core activity that we provide to the industry. And given that we are a cloud company, the data is organized in our cloud. It doesn't sit on different servers of customers, right, that are not accessible, right? So it's all in our cloud. So I think it's important to understand kind of that part of the infrastructure. We built a company for the last 20 years with the domain knowledge and expertise around the clinical trial process. We're a software company. So we bring the AI and analytical capabilities part to the table. Now you combine all of that, right? You have the data. You need to ensure that you have access to the data, which is important, right, because the data is so proprietary -- is proprietary to all of our customers. We don't own the data. We manage the data for our customers. But we work in a trusted environment with our customers that allows us to access the data as long as we de-identify, right? So it's always -- and it's always de-identifiable so that we can aggregate it. So it's never -- you can never reconcile it back to any sponsor or any patient, right? It's like totally anonymized data. But it gives us a great sense of detail in what is going on in the industry. So that's the foundation that we started to build over 10 years ago, right, when we thought about the strategic relevance of that data asset and our role in the industry to be able to aggregate the data, right, and provide that amplification of insights that we can do. And this started all as a research and science project, which is to build the foundation because you have to standardize the data. You have to make sure you can actually compare it. You have to spend a lot of time in data operations and data standardization that we did for many years to build that set of record and the level of automation that data can be standardized pretty quickly and on-the-fly. So now you need a commercial model on how you bring this to market. right? Because you want to make -- we need -- we're making money with every service that we provide, and building the applications and the repeatable model that allows us to take this to market, not on a project basis, but really as a software company that we can scale these as analytical solutions that address very specific use cases and problems of our customers. The Synthetic Control Arm is one example. But we also provide the insight into patient recruitment and site selection, so for feasibility studies, to really reduce the risk -- to ensure you work with the right sites -- with the right clinical sites that have the capabilities and the know-how to recruit the right patients, so we have a lot of data to inform this process. And as a matter of fact, the majority of the large CROs today actually use our analytical applications to provide these services to their sponsors. So we are very well connected to the industry and take a very collaborative approach as we work right through all the different parties in the industry, be it our CRO partners, all the sponsors at the end, right, our customers as well. So that's at a high level, right, our strategy. And I think, again, my point is really important that I want to make. It's not something that we were coming up with 2 years ago as we founded Acorn AI. It's something that's been existing at Medidata for a decade, right, that we have built and are now seeing the opportunity to build use cases, bring it to the market. It's early on still. It also requires you to educate regulators around the use of Synthetic Control Arms in clinical trials, which is very important. So we work with regulators. We very openly discuss and give them insights into the process and the data. And so we're really trying to position us, yes, as a technology company, but at the same point in time, the technology company that enables science. So we have to be very close to the science of our customers as well to be able to really get to this.

That's really helpful. One of the things you mentioned, you talked about rate of change. And as a software analyst, one of the things I've seen is, often, software companies can have the most phenomenal technology that you know is going to bring great returns to the industry that it targets, but one of the big challenge is waiting that industry to change because they're used to doing things in a certain way, and getting them to change those business processes and to digitize and to move forward is a big challenge. Could you maybe just talk a little bit about where you are with that? And then how has the pandemic potentially changed the willingness and openness of your customers to accelerate the pace of the transformation of their businesses?

Absolutely. I mean there are -- you're absolutely right, Adam. And it also applies to us, right? We are not -- we've been -- we've really been -- I start from -- going some time back and still today, we have been victims, I mean, after rate of change, business process change. We've been always thinking maybe sometimes a little bit too far ahead in terms of where we can take it, the process, and where we can use the data to augment, right, and make the changes that we see as providing that level of value and an opportunity for our customers. And decentral clinical trial is a great example, right? The acquisition in 2016 back then, if you had asked, we had that conversation. In 2016, my prediction would have been that electronic patient consent would be already at prime time now. And I would have been so wrong because we are still so early in the adoption cycle of an electronic patient consent process. So the same is for analytics and AI. I remember when we did the first sizing exercises of our investments into data science at Medidata knowing our capability to develop Synthetic Control Arms to what that actually means, right? If the regulators are supporting this approach, you can pretty much replace your control arm by the data that's already been recorded in other clinical trials, right? As long as we control that this control arm behaves in the same way as the actual real control arm, and we have done that statistic proof for a lot of therapeutic areas, so that also enables all the patients to get access to the drugs and solves for this problem that when patients were in a very difficult situation realize that they are on a control arm, they drop out of the clinical trial because they need access to the new treatment. And when that happens, your data set, right, is challenged and reduced, and your clinical trial is elongated, right? And it takes again longer to get a trial approved because you have to recruit more patients. So we can solve for these problems. So the value proposition is crystal clear, right? Our conviction that we can deliver it is there. Now why is it not happening faster, the adoption? But that's the education process we continue to go through with our customers to make us all familiar with these type of data science solutions, yes. But also electronic patient consent in that way could be very simple. But there are other aspects related to data privacy, data regulation. And we know that this is also a very volatile area, right, that we have to respect data privacy and patient privacy, and sponsors have to be able to adopt this in their SOPs so that they can leverage these types of applications. So all of this takes sometimes much longer than we wish, but at the same point of time, it creates future opportunities for us. We need to make sure that, conceptually, we are always -- that our strategy is well aligned with where the industry is going. And I think that has always been a very important part of our process. And I feel today, I sit here and think that going back to the best that we made years ago, that our strategy is actually working very well, and we can execute it with a lot of focus.

That is really helpful. Maybe on that rate of change question, just again to give health care investors, you may not be focused day to day on investors, can you give us a little feel of how quickly Medidata has been growing? And maybe just contrast that, give us an idea of the acceleration over the last few quarters.

Yes. So I mean, one number that we -- I think that's a really good indicator without -- before I go to the financials more and operational number, we have seen an uptick of the clinical trials on our platform by north of 25%. So that increase really reflects very nicely that we are also capturing more share of the market. We are seeing high activity levels in the industry, right? When you look at clinical trial [indiscernible] so we have a repository where the clinical trials are registered and you'd say it's not all. But in theory, that's the best data repository existing, reporting of all clinical trials in the world. That number is also up in the same percentage area, and so we see activity levels increasing. We see, at the same point in time, we take that share and we benefit of that increase in activity level. So we are, with our technology as a trusted partner of the industry, able to take advantage of this growth, right, of that step function. Now we think that a lot of those drugs that are started, they are very broad-based. They are not necessarily just driven by COVID. They're going through all the big therapeutic areas: oncology, cardiovascular and others. So we see this really broad base, which is I think it's very important to know as well. So this is -- it's a trend that we believe will continue to be strong, right? Will it be 25% growth now every 12 months? For sure not, right? But we definitely see that the activity levels are increasing. We continue to see strong investments and funding in the IPO of biotechs. We continue to see R&D investments in pharma to go upwards, right? So there's all the important metric, right, about the health of the industry are pointing into the right direction, so which gives us the conviction that we are all working on the right topics and it's -- so that's reflected in our numbers, right? We reported over 20% growth in software revenue for the last 2 quarters, which is a tremendous acceleration. Our long-term growth target is 13% to 15%, and that is still very valid if we think about this long term because some of the trends that we are talking about in the area of decentral clinical trial but also data analytics, yes, they are incremental, right? But then there is another impact of our big installed base around electronic data capture will also have some pressure over time, right? As more and more trials will be decentralized, less will be in the clinic. So really how this all is going to shape up remains to be seen. So that's why I think the 13% to 15% is a very strong growth target for us that we are -- that we feel is the right level at this point, despite seeing right now further acceleration, which is great.

No, that makes sense. That's really helpful. We've got a few minutes left. So maybe one of the final areas I wanted to touch on was around competition. And I want to -- rather than just kind of saying, well, x and y compete with us, can we maybe talk about it a little bit more broadly? So we've got AVEVA who do both CRM and trials, you're in trials. You've got the electronic medical records and management system vendors. Hospital software, you got people like CompuGroup, but also you have Cerner. The hardware players, the hyperscalers want to be here from a data point of view. Could you help us understand how do you see this industry in the mid- to long-term? I mean there's a lot of companies saying, well, okay, we can do health care tech. How broad does Medidata want to be in that process? And who would you see yourselves as the real threats to the data and really bringing value to the pharma and the biotech company sort of 5 years from now?

Absolutely. I think, Adam, that's -- I could give you a precise answer. That will be -- you wouldn't -- that's for sure not possible. I mean it's a question a lot are asking, but it's also some -- people who are familiar with the industry know that it is -- you need to bring, first of all, the domain understanding and domain knowledge to the industry in order to be relevant, right, and accept that you also need to have a long-term product, right? It's not something that you can quickly get it and make a big impact. You really have to invest long term in making changes in the health care system and with life sciences. I mean when you think about what we were just discussing, right, it's very clear that there is a need for innovation and transformation in the overall health care world, right? It's undisputed, right? So it's a very attractive space for technology companies to enter, yes? But again, you need to have a very long-term perspective to focus on the right problems where you can make an impact and come with a solution to really augment existing processes and help change -- it's a lot of people involved where behaviors need to be changed, education to occur, right? So it's not something that can be easily done quickly, right? I think that's important to understand. When we talk about clinical trials, the development of these type of programs is 10 to 15 years. So you have to be familiar with these types of cycles, right. From research to testing to approval, it could be 5 to 7 years and then you have 5 to 7 years to commercial phase. So yes. And then there are a number of very established players. Some of them you mentioned are more on the hardware side. And some of them are coming as insurance companies into the provider space because they are -- they operate with all the patients and the patient data. Everything that occurs in the real world, it has to be reimbursed, right? And they want to ensure that there's high quality of services in the system. And they all have a very important relevance, right, and a very important role to play. I think what it really comes down to is how can you connect the parts much more actively, right, to make it more seamless and less disruptive, right, more end to end. I think that's going to be the challenge. But there will always be multiple providers, multiple angles to -- and domains that have to be connected. We feel -- now strategically for us, our vision is that we -- today, where we are focused on life sciences are on med device companies. We are now expanding certainly through clinical trials but beyond that as well to the patient directly and to practitioners. So our vision is to expand to the patient and the care providers strategically over the next years, while, of course, we will execute our strategy on the end-to-end platform for life sciences as it relates to the upstream and downstream problems that need to be looked at end to end, right, and holistically to really bring that -- build that platform of transformation, right, where innovation and transformation can happen over years because it's a dynamic process. You're not doing that one time and you're done, right? It's continuously -- has to live and evolve. So that's my vision of the ecosystem and the strategy.

Perfect. But there's lots and lots of other things we could explore, but unfortunately, we're bumping up against time there. I thought that was very interesting, really useful discussion. The business sounds in great shape, but it sounds like there are huge growth opportunities for you over the next few years. So Rouven, thank you very much again for joining us. I hope the investors enjoyed the discussion as well, and hopefully, we'll catch up soon. Thank you.

Thank you, everybody. Thanks for your time.