Dassault Systèmes SE (DSY) Earnings Call Transcript & Summary

Hi. My name is Stacy Pollard. I'm with JPMorgan, one of the equity research analysts here, also with Sterling Auty. We cover software and IT services companies. And specifically, we have today a company which is a bit of a crossover between IT and health care, a very interesting angle. We have Medidata, which is part of Dassault Systèmes. And we'll start with about a 20-minute presentation, and then we'll have about 20 minutes of Q&A. That is the format. [Operator Instructions] Now we'll -- I will hand over to our presenters who are Sastry Chilukuri, he is the Founder and President of Acorn AI, which is now part of Medidata and Dassault; and then Rouven Bergmann, who's the COO, CFO of Medidata. Sastry, I hand it over to you.

Great. Thank you so much, Stacy. Hi, everyone. Good morning, good afternoon. Welcome to the first virtual JPMorgan. It does feel pretty surreal to be able to talk to you virtually here. We're really excited to talk you through our company strategy this morning and then take any questions after the presentation. So the first slide talks to our mission. We are a mission-driven company. And what we are really focused on is providing tools and services and solutions to life science customers to help them truly solve the impossible. And if you go to Slide 2, this impossible challenge really came to fore in 2020 during the COVID-19 crisis. What we were able to do as an industry to be able to bring the vaccines and the therapies and record time to market truly changed health care and the perception of health care. We're proud about the role our company played in bringing these COVID therapies to market. If you look at the numbers on Slide 2, we supported over 500 clinical trials associated with COVID. Each of these trials involved hundreds to thousands of patients. Some of these megatrials involved as much as 30,000 patients. The operations of these clinical trials was at record pace with a 50% to 60% reduction in the time to recruitment. In parallel, we also helped stand up one of the world's largest real-world evidence database to truly understand what the long-term effect of COVID is as well as better understand what individual patient fingerprints are associated with the disease progression. This included 75 billion records from over 250 million patients that was stood up in our environment. And we provided tools for researchers to be able to run all kinds of real-world evidence research on top of it. And currently 350-plus researchers worldwide are accessing this environment. Moving on, if you go to Slide 4. Here is where we see the world headed. The basis of competition is really changing, and COVID served as a crucible to be able to prove a lot of these concepts that we've all been talking about for the last decade. The first is precision medicine platforms have come to the forefront, be it platforms like the mRNA platforms that delivered the first vaccines or CRISPR or cell therapy and gene therapy. They're all coming of age and bringing precision medicine to life. In parallel, digital and AI therapies continue to evolve rapidly. We are starting to see everything from companion diagnostics and companion algorithms to the widespread use of AI and digital across all aspects of research as well as care. It's truly becoming ubiquitous. And then finally, as these therapies and these treatments start to come to the forefront, value-based care becomes absolutely critical. And central to all of this, if you go to Page 5, is the patient. Increasingly, the patient continues to move to the center of this ecosystem. And it's both of these trends that we believe we're uniquely positioned to capitalize on going forward as a company. And we'll talk with some of the work that we're doing around it. I'm now on Slide 6, where we'll talk a little bit of our company. If you go to Slide 7, this is a snapshot of who we are and what we do. We're the #1 market share in life sciences as a combined Dassault Systèmes BIOVIA and Medidata entity with 8,000-plus active customers, which includes all of the top 20 biopharma and medtech companies as well as all of the top 10 CROs, with 4,000 professionals that are dedicated on a daily basis to our mission. Over 50% of new drugs are designed with our solutions, and 50% of clinical trials are supported on our platform. And all of this creates an incredible data environment for us to build our AI solutions on top of. With 22,000 clinical trials, 6-plus million patients, 22,000 facilities and 400-plus million images, we have a unique training data set that nobody else in the industry has to power our AI algorithms and our AI solutions. If you go to Slide 8, this has been a journey in the making for 2 decades. BIOVIA on the Dassault Systèmes side was created through a series of acquisitions with Accelrys and BioIntelligence as well as additional investments, which covers the research and the manufacturing sides of the value chain. Medidata over the last 2 decades has gone from being an EDC and a clinical company that's starting to make investments in Acorn AI, which is the data science business, and the AI business as well as myMedidata, which is the Patient Cloud and the patient-centric business. With both of these combined, we are uniquely positioned to cover the entire value chain in this era of precision medicine as well as AI and digital and patient engagement. If you go to Slide 9, it starts to give you a flavor for what this end-to-end platform looks like. It's truly the industry's first that covers the entire value chain, starting from discovery and research through medical device development, clinical trials, evidence generation, patient engagement, manufacturing and supply chain as well as commercialization. Let me now talk through a few examples from last year that we are really excited about that start to show where really our company is headed as well as, honestly, the market is headed. If you look at Slide 10, this was, for us, a massive breakthrough. The FDA agreed to use a synthetic control arm designed using our data for rGBM. This was a press release that was put out by Medicenna, and you can release the -- and you can reference the entire press release and the link in the document. But what makes this truly unique is that for the first time, the FDA actually approved the use of this hybrid synthetic control arm. We were able to repurpose data from historic clinical trials to construct a synthetic control arm that was able to meet the regulatory bar. That is a truly breakthrough achievement. What it allows you to do is to be able to get the drug to patients faster because it's fewer patients that you have to recruit as well as it has massive patient implications because these are patients that no longer have to be treated via standard of care but are actually eligible to get direct access to the experimental treatment in an incredibly difficult disease like rGBM. And this is just the tip of the spear. We currently have 5 more of these synthetic control arms currently under review with multiple global agencies, and we see our pipeline continuing to grow around this. The next example I want to talk about on Slide 11 is how patients are moving to the center of the COVID-19 vaccine. This was our work jointly with Moderna in the vaccine that they brought to market for the COVID-19 -- for COVID-19. And it's one of the fastest recruiting trials in the history of Medidata, with over 30,000 patients that were recruited in a matter of a few months. And the complexity of this trial was truly astounding, where about 13,000 devices were provisioned directly to patients, and the patients also were able to bring in their own devices. And all of this is used to capture patient data directly. This is truly the patient moving into the center of care, where they're connected every way from right upfront, where they start to get involved in screening as well as getting enrolled in clinical trials, all the way through being engaged throughout their overall clinical trial experience, contributing data along the way as well as at the end, when post market, it allows you to be able to continue to connect with the patient. This is something that we are excited about as a company because we are truly uniquely positioned and one of a kind to be able to execute this, bringing together this joint hybrid between the actual physical clinical trial as well as the virtual trial components. If you go to Slide 12, this is the next generation of analytics associated with clinical trials. Back in March when COVID broke out, we started to track the impact of COVID on clinical trials. Large number of patients weren't able to go into facilities for visits. We were starting to see a significant drop in screening procedures that allowed you to reduce the amount of patients that were actually getting diagnosed. The analytics that we were putting out, having this unique view across 6,000 clinical trials that were going live, caught the attention of the industry. And these numbers were widely referenced by everyone who were operating their clinical trials. We were also covered by New York Times around this. This was also the time when we did our work jointly with PPD, which is an industry-leading CRO, in terms of the use of our analytics to be able to change how they manage their portfolio as well as they manage their clinical trials. We've built a series of analytic algorithms as well as dashboards that allowed them to be able to both drive their trial operations better as well as be able to respond more actively and quickly and agilely to changes in the market. And some of the impact from these algorithms are starting to be seen as we start to execute on these clinical trials. And finally, when you go to Slide 13, this is the work that we've been doing on the BIOVIA side of the portfolio related to manufacturing and supply chain. CAR-T therapies, as we know, are highly personalized therapies, and they involve multiple steps and complex procedures. By being able to bring these tools and algorithms that allow you to connect the dots, all the way from when you get the sample from the patient to the creation of the therapy, to bringing that sample and the treatment back to the patient is something that the solution has been able to solve. And it allowed them to be able to reduce the batch processing time by 15% to 20%. And as we see the future of these precision medicines as well as these personalized therapies grow, we start to see solutions like these that allow you to connect to the patient and all the way back into manufacturing and back to the patient continue to grow. And as we showed earlier in our end-to-end platform, we are uniquely positioned to be able to connect the dots across all of these steps. These are a few examples of what we've been up to in 2020 and where we see the growth in the coming years. Now I'll turn it over to Rouven, who can talk us through the operational and financial ambitions of our joint company.

Great. Thank you, Sastry. My name is Rouven Bergmann. I'm the COO and CFO of Medidata. Thank you, Sastry. We're turning from Page 14 to Page 15 to talk about our financial metric and growth levers for our combined business. You heard from Sastry the innovation and capabilities we bring to market, of course, with Medidata inside Dassault Systèmes at the center of our strategy but also expanding into other parts of research discovery with BIOVIA and also leveraging the very strong capabilities and core capabilities of Dassault Systèmes in the area of manufacturing, simulation and supply chain management that we bring to work and focus in the life sciences space. So when we look at this opportunity combined, we -- our financial ambition is to grow our business in the life sciences sector by 13% to 15% on average year-over-year. Our ambition, and Pascal Daloz, the CFO of Dassault Systèmes, presented that at the just recent Capital Market Day, is to achieve $2 billion in revenue by 2025. Of course, we are running a very profitable business. And at Medidata, we have always been looking at profitable growth. And we outlined this as -- once we announced the acquisition, that the ambition for Medidata as being part of Dassault Systèmes is to improve profitability year-over-year. And we stick to our commitment. So the Medidata business will deliver 200 basis point of margin improvement on average year-over-year to the Dassault Systèmes company as well. And of course, aligned with this, with our operating margin expansion and our business growth, we will deliver growth in operating cash flow. And that's a very important part of our business strategy, to generate large streams of cash flow that we can reinvest into our business to fuel our future growth. The growth levers, Sastry has walked through, but I want to take this approach here to really summarize it in 5 dimensions that we are looking at. Of course, the first I'd mention is what we have done and done very well at Medidata over the years: to drive growth and adoption of our core transaction system to build that system of record for clinical development with our Rave database. And around the Rave database, we've been able to attach more capabilities and products to gain a broader share of wallet and grow our business and fuel our growth. That's number one. We continue to be focused on gaining market share and taking advantage of the macro trends as we see more clinical trials and more investments across geographies but also across new scientific innovation that has expanded the growth of clinical development, which is absolutely a trend for us to win more market share and drive our core business growth. Second, Sastry touched on this. As we really think about what happened during the COVID crisis, is an acceleration of a site-centric approach to a patient-centric approach. So our opportunity is to connect and use our huge installed base, to expand that installed base to connect to patients directly through the myMedidata platform. That's our second level of growth. That drives the relationships -- expands the relationships and connects us directly to patients and creates and expands our network. Thirdly, you heard the examples and proof points that Sastry talked about, our Acorn AI story, our data analytics with our unique data set that we've built during the Medidata times. But now we have the opportunity to actually expand that through the entire life cycle of life sciences, which makes it even more powerful and relevant. And that leads me to the fourth point, which is our end-to-end platform for life sciences. This, as I started my part of the presentation, is really to combine and connect all the parts from research and discovery through clinical testing, so the Medidata capabilities, all the way to manufacturing and commercialization, to really look at an end-to-end process and start the journey of a digital enterprise for life sciences by bringing this all together, where we have all the assets and the capabilities under one company. And we are uniquely positioned to do that. That's the fourth lever. And then, of course, as we are -- we joined forces, as everyone would expect, we are leveraging the capabilities and footprint of Dassault Systèmes and the infrastructure and have a much better handle on resource allocation optimization across the globe. Next slide, Slide 16. Slide 16 outlines the level of scale that we have achieved, now focusing and zooming in on Medidata, because I think it's really important for investors to understand the level of scale we have within the Medidata business. So this slide summarizes that every hour across -- every hour, we are managing more than 6,000 concurring active clinical trials. And through this activity, there's over 1 million requests and cards to our Medidata platform. So it's a real large-scale cloud operation and data hub that we orchestrate and coordinate, with over 275,000 CRF page requests and over 45,000 medical images per hour that we process and receive through our -- within our systems. And that has now led to a decade of growth of customer expansion, where we are now looking at a customer record or customers within the Medidata business of over 1,600. And you heard Sastry talk about the larger scale of our customers within life sciences, but that's really focused on Medidata and our core Medidata business. Next slide, Slide 17, is a really important aspect of our business and our philosophy of how we run the business. We are highly committed to protect data privacy and protect patient and customer privacy. We all know we're going through times of a lot of volatility and risks that require us to be extremely cautious and thoughtful in the way we run our business. And we protect the assets of our customers, the IP and the data privacy. So when you look at all the investments we have taken over decades to protect that in terms of privacy, security and the regulatory relationships we have, we believe that we are, by far, the industry leaders in this category of data security and privacy to protect our customers' and patients' data. And then I would like to turn on to Page 18 to very briefly cover on our 1-year journey as Medidata being a Dassault Systèmes company. We have done 4 things as we have started off with a very strong functional alignment, where we are looking at synergies, and we are looking at connecting the dots in the supporting functions to begin working together immediately and to ensure that we have enterprise-wide transparency around all the activities we are running. Systems integration. It's very important to really operate in real time and be well connected. And here, the 3DEXPERIENCE platform across HR and finance systems, we have really been from day 1 focused on making sure that those are well working together. And of course, at the third point, we have worked together, as you've seen in Sastry's presentation and the parts that I talked about, in aligning our strategy to really go after the -- into the industry with a much broader value proposition and a bigger set of capabilities to help our clients to become a truly digital enterprise and advance their businesses forward. And we are scaling for the future. As I said before, we are now part of a very large company that has a footprint across the world in all -- almost all countries in the world and geographies, of course, that allows us to be much closer to our customers and leverage these capabilities without having to invest and build it ourselves. That's a massive investment -- a massive advantage for us as being a part of Dassault Systèmes. And of course, it brings us closer to realize our vision to really truly expand also from life sciences into the broader health care ecosystem. And with that, I'd like to turn it back to the operator.

Hi, Rouven, Sastry, thank you very much for the presentation. We've got Sterling Auty joining us visually here as well. Let me start just on the Q&A, and we do have a few questions in from the audience as well. My first question is similar to an audience question. So I'm going to try to combine these 2. So my question was [indiscernible] through your TAM and industry trends. I know Dassault has given a TAM for their Life Sciences & Healthcare division of $8 billion. And they were talking about a 5-year CAGR of 9% for the market, but then talking about how Dassault can grow 13% to 15%. So maybe just talk us through how and why you're going to outgrow that market. And then to add a little component from the client as the investor as well, he's asked a similar question and saying, "Please parse that out where possible based on volume, price, mix and white space." So I know it's one massive question, but if we can start with that.

Okay. All right. Thank you, Stacy. Yes. I think when you look at our TAM, our TAM calculation, the $8 billion, really based on the actual software spend in the life sciences industry according to the IDC framework. And if you really look at this data, as Sastry mentioned before, we are number one, ahead of Oracle, SAP and Veeva. But now when we -- and that goes to the second part of your question. When you now really think about what the opportunity looks like, we know that it's actually much larger as the way the market share is reflected with the actual software spend because we are looking at innovation and transformation. And we see that opportunity, I would say, to simplify it at 3 levels, right? And I think I will try to touch base on the white space as I go through those 3 levels. The first level, I would position it -- that's the Medidata level, which is really about reinventing the gold standard of clinical trials and clinical development. And here we are -- as I said before, we are expanding from a site-centric approach to a virtual trial setup that connects to patients directly. And that's a significant opportunity. And because it allows us to really build that -- expand that network to patients and people in real time. And we are the market leader in the database -- in our cloud-based database technology for Medidata with Rave. Think about this as our system of record. That's the back-end infrastructure. And now you expand that with the myMedidata Patient Cloud platform, you really build the front end and the back end and bring it together, and it allows you really to scale and decentralize the process. That's, to me, is the number one -- is the first level of step-up and opportunity expansion, right, in our strategy when we think about the TAM. The second part is this real large notion and strategy of the end-to-end platform for life sciences that combines the strategic assets of Dassault Systèmes with Medidata in clinical development and then the manufacturing, simulation, supply chain capabilities of Dassault Systèmes that we are now taking and bringing that really focused into the life sciences sector. And that's a very large opportunity because there's nobody else who has all those capabilities, where we have the unique -- we are uniquely positioned to really bring those assets together. We're the market leader in all those different categories through BIOVIA, Medidata and Dassault Systèmes on the manufacturing and supply chain management side. And you think about what really has happened in the industry with the tremendous change and the pressure through COVID and how time lines have changed and how important it is to connect the different parts across the platform. And then the third part really points on these use cases and insights that Sastry provided around AI and data analytics, right? We have that proprietary data set in the Medidata clinical cloud, but we are expanding it through real-world data and the workflows we are building across the end-to-end platform. So the data analytics and AI and Acorn opportunity is bigger than just Medidata. It's really life sciences because it now gives us this end-to-end platform to build this system of engagement insights on top. So I think a lot of what I talk about is really white space and growth opportunity. It's business transformation. It's long term oriented, right? It's something that we'll -- I'm sure it's a vector into the next decade that this provides us. And that really is -- when you think about 9% growth as reflected in the actuals versus the 13% to 15% that I was talking about, that's our opportunity that -- with the combined capabilities and these 1, 2, 3 levels that we are monetizing.

Just along those lines, and you've talked about your Life Sciences division. Maybe just give us -- you've hinted at various components of it. So put that into the framework of how you think really long term. And then what would you expect to do or need to do with regards to M&A, more M&A, more acquisitions to bolster all the components that you want? Or would you be doing more around self-development? And even maybe what areas would you be focusing on?

Yes. Why don't I start with that, Rouven, and then you can comment. We are actively looking at potential tuck-in acquisitions, and we continue to look at what complementary capabilities are out there. We still haven't found anything that we like. So we are following this on both tracks of both doing our own organic build while we continue to talk, continue constantly about to partners in terms of what these potential targets could look like. And if you look at the press, we put out a series of partnership agreements that we did last year. This is a frothy space. Nobody has really figured it out. So we think running these partnerships is a good way for us to both understand what's out there as well as figure out where the right fits are.

Yes. And I would add to kind of the broader -- beyond M&A. I think, if I understand your question correctly, around our broader vision, right, in terms of timing, what's really short term and here and now is that what I outlined is this level 1, is the expansion from site-centric to patient-centric. That's an opportunity that is here and now that's -- it is -- it's one of the key questions our customers come, how do they connect to patients faster? How do they speed up enrollment? How do they get to outcomes quicker, right? And so we have the technology to provide and help them do that. And in connecting across the platform, Medidata, BIOVIA Dassault Systèmes, with AI on top, right, that is our vision that we are working on with our customer base in some areas today. It's early, right, it's -- in those conversations. But these are, of course, life cycles and relationships that we will expand over time and grow. And we'll also become much smarter as we do that in terms of what are the needs from an M&A perspective, as Sastry just outlined, as we are engaging into those conversations because the best ideas for M&A in our history have been those that actually our customers have pointed us to and said, "Can you help us with these things?" And we started to really become smart around figuring out what we need to do, right? And I think that's what's going to be critical.

Right.

So I'm just going to jump in with a couple here. So maybe Rouven and Sastry, for those that are not as familiar with Medidata, it's fantastic to see the Synthetic Control Arm support from the FDA. But help investors that are newer to the story understand. Where is the data set that you've been able to compile? Where did you get it? And is there any other comparable data sets out there in the industry that you have to compete with?

That's a fantastic question. So let me answer that. So the founders of the company had the foresight about 10 years ago to start to ask customers for secondary use rights on the data going through our SaaS systems. So we don't resell the data that we have, but we have secondary use rights to be able to build analytic products on top of it. And the Synthetic Control Arm that you saw is one of those analytic products, where we're building it off of the control arms of some of these historic clinical trials that are closed and complete. Over the course of the last decade, we've been able to assemble this unrivaled data set of 22,000 clinical trials and 6 million patients. And there isn't really anything that's comparable out there in terms of quality as well as size. And let me give you 2 points, right? The first is if you look at all of these other RW data sets that are out there, we all know that the real-world data is messy and it has limitations, and it can't really be used to be able to draw conclusions; whereas what we have is truly regulatory-grade data that has been used by other sponsors in the past to be able to submit regulatory submissions. This is monitored. This is verified. This is clean. And that's really the data foundation we're working off of. And in terms of size, we were recently asked this question because we have this operational data set of 22,000 sites and how they perform to benchmark against some of these others that are out there to say, how big is your data set and how live is your data set compared to the others out there. And the nearest competitor is 1/3 of our size in terms of volume, and their data is probably a year old. And in the case of COVID, we needed a view on a weekly basis to understand what's happening on an operational level on a site. And a year is absolutely irrelevant because you're going back to a time before COVID was even there. So it is truly unique and one of a kind. And what we've done over the last few years with Acorn is, a, start to build this capability to be able to cleanse this data and make it usable and as well as build pipelines that allow you to link this data with other data sources that are both public as well as real-world data sources to be able to enrich that data set and make it much more valuable.

And how do you monetize the data? So what is the commercial agreement that you have with the customer?

Yes. So we do not sell data. It's not ours to sell, and we do not sell data. What we do is, for the customers that have given us access to their data, we offer them the opportunity to be able to buy the AI solutions that are built on top of this data. This is a very unique data set with a very unique trading capability, and we start to build products on top of it. And we think AI is the basis of competition, and having access to these solutions for our customers who actually entrust us with their data gives them a basis to compete against those that are not part of this program.

That makes a lot of sense. Rouven, you brought up Rave. Maybe -- can you peel back the onion a layer in and talk a little bit about where your core strengths are along the clinical stack of EDC, CTMS, eTMF? And what are you seeing in terms of the competitive landscape in that clinical stack?

Sure. Sure. So Rave EDC is our cloud-based database, which is the market leader today by far. I talked about the 6-plus thousand concurrent clinical trials that are running in this database. I think what really stands out, it scales across all the dimensions of the market, from small biotech firms to the largest pharma companies that run the most complex portfolios as well as all the therapeutic areas. So from Phase I, very controlled small trials to very, very large trials. We talked about the COVID trials, right, which have tens of thousands of patients. So I think that's a very, very unique characteristic. We developed a pricing model that we can actually position it across all those dimensions. And then also important, it's a sell-to-direct business as well as sell-through to the partners. So the core -- the 10 of the 10 top CROs in the world, who essentially serve the entire life sciences industry in developing new drugs, are standardizing on our Rave technology, right? That's the back-end infrastructure where the data resides. And now to Sastry's point, right, that data has tremendous value, upstream and downstream, as we are optimizing the whole entrant process, right? We're bringing this -- together, we are able to aggregate it because we can de-identify it, and we have the secondary use rights, as Sastry pointed to. So I think that, to me, is really important to take that point -- bring that point across that Rave is nothing that I would put -- it isn't a mature product, but it is very, very innovative and cutting edge, right, and continues to take market share and grow, right? So when I get asked about competitive landscape within that core component, I would still point to Oracle, which is a large incumbent that has a legacy system in the market, that we have been, over the years, chipping away the market share and been growing our footprint and taking more customers. I mentioned the 1,600 customers. We're far -- we're above that 1,600, was a Q3 number that we presented at our Q3 call, we talked about. So we are continuously growing, right? The momentum continuously to expand the win rates are actually at the highest levels we have seen it consistently while we've been able to really protect our high level of -- our pricing power because of the market share we have and the complexity that we can deal with. And time matters to our customers, as Sastry just pointed out, around COVID, right? So all of those vectors are supporting that core technology. The second part I would point to, Sterling, is really the expansion to the patient, myMedidata and Patient Cloud. That has really in the recent, I would say, 18 months, has become our second core asset in terms of expanding our share of wallet and growth, right? When I think about uptick a dollar of Rave, I add another dollar in our Patient Cloud technology on top and that double the price by expanding that technologies. That is relevant now to a large set of clinical trials, right? So because you want to connect to the patients directly, the engagement is critical. And then the third part, our other capabilities to really operate the clinical trial, which is randomization trial supply management; which is the medical coding; which is the connectivity to the safety gateway; which is risk-based monitoring and data analytics and identifying if there is risk in the data and really looking to queue the data, right, as we can. That's really important. There is a competitor, which is [ Blue.Point. ] I don't want to give them too much credit, but they are a point solution. They're not a platform -- they're not sitting on a platform as we do, right, to bring it end to end. Then we have CTMS, where we run into Veeva, right? I would say it's a 2-horse race in that area. But I think that sums it up from a perspective of Medidata and avenues of growth. Yes, we have payments, right? We run the largest engine of payment calculation to clinical sites to reimburse those sites for all of the services that they provide as part of the clinical trial because we have all the data, the operational data in our Rave database so we can actually use this data to accurately assess what the reimbursement levels are in a very automated way. So we are really using all those, starting from the data, the data-centric approach, to put that into Software as a Service solutions to help scale and automate the process.

Yes. Rouven, let me jump in here. Another question from the audience. We have about 2 or 3 minutes left in the session. He wants you to elaborate a bit on your biosimulation software and how that compares to the competition as well.

Sastry, do you want to take that question?

Yes. This is out of our BIOVIA portfolio. And we have a long history here. And I do think our capabilities are really differentiated against the competition. And increasingly, as we start to see these new precision therapies come in where the connectivity between discovery and manufacturing and clinical and manufacturing as well as the patient and manufacturing are absolutely paramount, we think that will allow us to differentiate ourselves because the margin of error is 0 in all of these cases because each treatment is truly personalized to a patient. And we believe both the core capability of our biosimulation software as well as this ability to be able to connect it across all of these various parts of the value chain make us one of a kind in the industry.

And then maybe one more from my side. Not too long ago, you partnered with Apple for [ Apple HealthKit ] and kind of looked at that connectivity out to the patient. What's some of the update of what you're seeing on some of those initiatives?

Yes. I think COVID was, again, a watershed moment in terms of patient engagement and patient connectivity. The number of patients who got involved in clinical trials is unprecedented. The speed of recruitment that happened around COVID was unprecedented. And we believe going forward, we're going to see a lot more of patient engagement and clinical trials. And as we start to think about both the evolution of our Rave platform as well as our AI solutions, how do we start to bring all of these various feeds around the patient into the platform and start to build analytics and predictive capabilities around it is going to become a core part of what we do. And then secondly, what gets us even more excited is you don't want these insights generated in isolation. So how do you take these insights and start to feed them back into the research part of the value chain and back into the early discovery is again what is going to accelerate treatments to patients.

Great. Well, I'm getting the time warning. I hate to do it because I know Sterling and I could ask another 50 questions, and I'm sure the audience as well. But we very much appreciate your time today. And we look forward to monitoring how things go over the next 6, 12, 18 months. Thanks to both of you.

Great.

Thanks, everyone, for joining.

Thank you, Stacy. Thank you, Sterling.

Thank you.

Bye-bye.

Thank you.