Certara, Inc. ($CERT)

Thanks for joining us. My name is Ryan Halsted. I am the health care technology and distribution analyst with RBC's healthcare research team, and we have Certara up next. And I am pleased to be joined by Jon Resnik, CEO; and John Gallagher, CFO. Certara is a tech-enabled drug development company. So welcome.

Thank you, Ryan. Nice to be here. Thank you for the invite.

So John, I wanted to start with you. You've been in the CEO seat now for 5 months. And just wanted to get some perspectives from you on -- about the company since you joined, anything that surprised you or anything that's changed?

It really only been 5 months. So I don't know if anything surprised me per se. I think there are some areas where maybe I underestimated just how strong of a franchise it was. I mean, specifically around kind of scientific leadership, the deep kind of regulatory expertise, methodological leadership, the closeness between the relationship, between the companies and the work that they do with regulators. I knew that was a core part of the value proposition, but it's really truly in the DNA. Maybe the second area, and maybe this is a little bit of a surprise is around the portfolio itself. But there are a number of things that the company is known for, a number of kind of market-leading assets. But as you dig a little bit deeper within the company, there is just this absolute set of jewels that exist built on the deep expertise that's been accumulated over the last few decades and the kind of unrivaled suite of capabilities. There are all of these opportunities to deploy our expertise in different ways with a little bit of nurture, a little bit of product development and a little bit of evolution. There's no shortage of areas to go.

Well, maybe following along with your background and joining Certara, I noted, come from a large CRO with experience with real-world evidence technology and integrating that within clinical research. Just curious, how are you kind of leveraging that experience and knowledge and expertise at Certara and bringing that to its opportunity set?

Yes. I spent over 2 decades at one of the larger CROs, had a range of roles over time. I think the real-world one is an interesting one. I think it's pretty intuitive for you to pick up on that. On its face, trading and running a business on real-world evidence versus a business more in the model informed discovery and drug development space seemingly different. The similarities in the analogs between the 2 are pretty remarkable. I ran the real-world business early 2010s. And I think the state of maturity, I'd say, both from a regulatory framework standpoint, regulatory acceptance from a technology standpoint and a democratization standpoint were a pretty similar situations. Real world in the 2010s was a very new concept that was -- had a ton of promise. Regulators are asking a lot of questions about how they could get -- how they could deploy it more frequently and more accurately to save clinical trial expenditures to prove up to make trials smarter. And the MIDD, MID 3 world is very similar. It's this unbelievable set of computational and biosimulation capabilities. And the regulatory frameworks and the regulatory agencies themselves are just catching up with the range of things that can be done. The second thing, when I picked up the real-world business 15-plus years ago, it was a very isolated science that had very specific groups, epidemiology, biostat health economics, ups researchers, very specific groups that worked on it. And the value that was untapped over the course of a long period of time was kind of democratizing those capabilities in a different way and allowing the commercial teams and the early discovery teams and the clinical trial teams to take advantage of the full depth and breadth of real-world evidence within life sciences. And I see the MIDD story is a very similar one, which is today, is a core power science used by a handful of pharmacoeconomics groups and PBPK groups and groups who are highly specialized. But the power of what the platform creates really can be democratized and it can be used early in discovery to make good decisions. It can be used in clinical trials to make good inclusion, exclusion decisions and there are a range of other applications. I see a ton of similarities in building off the set of experiences from that time.

That's great. Hopefully, we'll get -- gain some more insights on the regulatory pathway as we look further out kind of adoption and acceptance of that technology. Maybe transitioning to AI in drug discovery. Certainly, I think there's an appreciation of the opportunities there, but also there's a perceived threat of disruption that has passed a pall on many stocks that touch on this arena. But just curious, how are you thinking about Certara's competitive position against these new emerging AI technologies that may or may not be disruptive?

That's -- okay, where to start on this topic. So first of all, I'd say, look, we view AI as a huge enabler for the business across the board. This is something 3 and 5 years, 3 years from now, we will be known as a market leader in the space, and it will accelerate everything that we are doing. The raw -- first of all, from an underlying fundamental standpoint, most of the money that's going in today is going in a little bit deeper into discovery, which is going to drive more compounds to market, which is going to help to accelerate the frequency and the volume by which MIDD itself will be demanded. And as we think going forward about the opportunities that exist for us, we've got this long legacy, literally decades of working on successful products, hundreds of products that have included -- that have worked with Certara and have informed their label. We've got thousands of scientific publications, hundreds of PhDs that work within the company. We've got some of the leading software products in the world that are fully embedded. And if you think about those core enablers, that's really a capability that we've created over time. That's one to build off in the AI space. It embeds us within workflows. We're working on billions of kind of data transactions. We have computational knowledge and kind of scientific depth of application that is second to none. You have this relationship between the technology, which is in the day-to-day workflow, not only of our clients and regulators, but also in us, in what we do. So you have this kind of expert in the loop. All of that creates this amazing foundation to take the next step with this, which is to identify a bunch of the workflow that exists to help build new applications, to help create a powered future, which will do exactly what we were talking about earlier, which is kind of democratize the use across the full life cycle, accelerate the insights, power the way that this type of research can get done.

That's great. You mentioned AI, you think could have the impact of generating more new drug candidates and faster. That's certainly a conversation that I've been having with investors recently, this idea that could be seeing a much greater influx of clinical drug development and a pipeline of new candidates. Just curious, following up on that comment, where do you think we are? And what inning do you think we are in terms of AI and drug discovery that's going to drive volume?

Super early innings. I mean I think we're just scratching the surface for what can be deployed. You've seen an exponential increase over the last few years, but we're still doing super, super early days on this. Look, as I said before, I'm encouraged. Most of the big press releases that are out there today are around kind of product identification and product early-stage discovery components, which to me will just accelerate the market. The more products that are developed, the more opportunity there is for us to bring kind of our domain expertise and knowledge around the way products computationally work in humans. So we're super early in this. We're going to see explosion over the next 5 to 10 years. And as I said, it's going to be a huge accelerant for core MIDD, which is a perfect complement to a lot of the investments that's going on today.

Right. And maybe on the -- your investments in AI, I think you mentioned on your last call, investing in the next-generation platform. Can you talk about some of those strategic initiatives in terms of those investments? And how are you measuring success? Or how are you going to measure success?

Yes. I mean I think we're already investing. So it's not -- we're already adding AI functionality just like everything within our portfolio. In fact, the fastest-growing products within this quarter, our AI native products are very specific. So we're seeing huge acceleration. We're working through the identification. A lot of our next-generation workflow, our QSP and PBPK road maps are loaded with this. We're already sitting in our clients' infrastructure and their workflow and our ability to kind of power them to do more quicker is core to what we do. You mentioned the next-generation platform. I think what we see and what we've already kind of built and already actively engaging clients on is this opportunity to play the role. The big models will be fantastic at kind of creating foundations and no one is competing with the big model companies in terms of their ability to build out the general models. But the layer between, which is kind of this regulatory intelligence layer or what we're calling a clinical and scientific intelligence layer really needs someone with the deep expertise like a Certara. I talked through the capabilities and the platform before, which creates a lot of distinctive capabilities. Just to give you kind of one example of why you need this kind of last mile and this AI infusion from this last mile. We have one product, Simcyp, which is a market leader in terms of helping to support label for things like drug-to-drug interaction, pediatric trials and increasingly in pregnancy and other things. It's the only product that's certified by regulators, we think, certainly in Europe and maybe in the world to do this type of task. And if you think about the process to get this regulatory validated asset approved, it took 2 years. Not only did you have to get approved by the EMA, you had to get it approved by the 25 member countries as well. You had leading scientists out actively engaging. And this know-how is embedded into our workflow and increasingly will be into our kind of AI scientific and clinical discovery. It's a perfect complement to what exists out there in some of the structural models to bring that last mile into development and really make sure that regulated space gets the credibility, the validation, the transparency it needs.

Maybe just taking a step back, I wanted to touch on the broader customer demand landscape and environment. Would be curious what you're seeing in terms of just demand for either discovery or preclinical work more generally? And just any particular areas of strength that are worth highlighting amongst your customer segments or types of customers?

Yes. Look, I think overall, we see what others are reporting. We see market health. If I look at core things like funding, I look at biotech funding, I look at new trial starts, I look at -- we talked about some of the AI discovery and increasing kind of pipeline size, all those are really positive metrics that we track. I also look at regulator engagement. And over the last few months, we've seen several regulator tailwinds from our standpoint, either pushing NAMs or accelerated clinical trial execution or clarifying some of the role for model-informed drug development. All of those are tailwinds as well. So from a market standpoint, certainly, we see it after a couple of rough years over the last couple of years, certainly improving. And based on the volume of questions and engagements and inquiries we're getting from clients, we see robust market, which is just strengthening and increasing -- any time you do something that pushes regulatory boundaries or kind of changes -- that takes changes in current practice, it takes time. But the amount of questions we're getting about how to do things differently certainly incredibly encouraging demand signal.

That's great. Maybe before -- I wanted to get into the regulatory landscape in a second. But before we move on from this topic, just I think much has been made about the biotech funding environment. It's been pretty healthy. Companies able to access capital in various ways or realized exits that give other companies confidence and perhaps maybe spend. How should investors think about how that funding can translate into your business spending in the areas that will drive your business from like a timing perspective? Is this something that is still a quarter -- a few quarters out in terms of trickling down into actual spend?

So historically, we've looked at that. So timing of positive funding and what the pull-through is on our customer tiers, especially Tier 2 and Tier 3 customers. And it generally takes about a quarter. By the time the funding -- so you see the funding environment get better, capital allocation decisions are happening inside of these biotechs. And of course, our commercial team is targeting those that are getting funding. And now, as Jon was just saying, overall, it's a tailwind for our biotech customers, which will fall into that Tier 2 and Tier 3 category. We saw strong performance in Q1 in both of those categories in software. And we commented that there's some execution points that are going to help us on the services side and this overall market backdrop is going to be -- is going to aid that effort as well.

And the thing I'd add is that our business model itself is set up to be flexible based on the different segments. We have the ability to sell only software technology where clients are looking just to do the technology. We have the ability to sell technology with wraparound expert services, and we've realigned the business to ensure we fortified that. And then third, on the biotech side, where they won't have kind of large scientific teams and know-how, we have the integrated capability to run entire programs for them. So as that funding improves, those real full-service opportunities are very much what we're building towards.

Great. Okay. Well, I wanted to move on to the regulatory landscape. You mentioned wanting to see increased acceptance of things like NAMS. And obviously, there are some changes at the FDA, but I think we were talking a little bit about this earlier. I'd like to think that the FDA will continue to be a supporter of things like NAMS. So just wanted to get your thoughts. What are you looking for from the FDA in terms of that further support and acceptance of NAMS?

Yes. I think I've learned a long time not to kind of forecast regulatory agencies too much. It's a different -- it's certainly a difficult one to do. I don't see -- look, these are long-term trends. They make sense. As our computational capabilities, as our AI capabilities accelerate, our ability to understand the human body more and more, these are the right things to be building not only for -- there's a lot of drivers in NAMS, efficiency and speed and time and the time to market is a worldwide issue. I know there's a lot today of U.S. positioning versus China. We've seen a lot of money moving to China. So there's lots of incentive for regulators in U.S. and Europe to accelerate time lines and speed to market. So I think these trends are somewhat immutable. The rate and pace at which they're accepted may vary from administration to administration and regulator to regulator, but I don't see the fundamental trend of accelerating. It just -- it makes too much sense. I was talking to one of our toxicology leaders yesterday. I mean you see huge opportunity to do avoid a ton of bioequivalence trials and you do a lot of tox simulation. I mean there's just so many applications there as we push more into QSP and really mix in not only the understanding of the human biology, but real-world data and other things. It's just so much to know and there's so much inefficiency the way the trials are executed. So I think the day-to-day kind of ups and downs of things are probably less relevant than the long-term trend, which will be to deploy these things more and more often.

Okay. Great. I think you set forth a goal of driving double-digit growth. So as you're thinking about the business plan for 2026, how should we think about the time frame to achieving the double-digit growth? And what are kind of the next key milestones to be on the lookout for?

Yes. So let me -- I'll do it strategically, and then I'll turn it to you, John, for some of the guidance on this. But look, we've taken -- in the first 100 days, we've done some pretty significant reorganization of the company. We set it up around 2 major growth hypothesis growth stories, one around what we call MID3, which is model-informed drug discovery, which every drug development, as you know, we've also added discovery to that as well to drive that kind of longitudinal connection across the pipeline. We've put all of our scientists and our technology systems together to create kind of that expert-based flywheel and really accelerate that business, both in terms of engagement with regulators, thought leadership, but also software build. And then the other side, we created a new group called ACE, which is accelerated clinical evidence. And the way to think about that is truly around the digitization, particularly around data and acceleration of the data can be generated and can help accelerate from protocol all the way to submission. So those are 2, we think, very nice growth platform, very consistent with what the regulatory bodies around the world are looking for in terms of accelerated execution, accelerated time to market. So we're excited about the room that, that creates for us. We're also strategically also looking -- I mentioned the platform before that we've created with all these decades of experience and the know-how and the workflow and the IP and everything that sits on top of it. The other thing we're looking for is a whole range of growth areas. Those growth areas are things where we can deploy our core expertise like our drug-to-drug interaction capabilities. You can apply those to clinical trial simulation. You can apply those earlier into discovery. Is there opportunities to do something like that in the clinic? And there's a whole range of ways that you could go. So we're pretty bullish about the long-term opportunities for growth, a combination of execution and kind of untapping some of these opportunities on [ that ACE ] front.

Yes. And so the building blocks to get there, if you look at the quarter, we did -- on the software side, we did 7% revenue growth on the quarter for software. So that was above our expectations. And then we said that software -- given the visibility that we have for software for the year, we think the software business will perform at the top or even above the top end of the range. And there are some execution changes as we described as well as just better visibility through the deferred revenue that we think will accelerate the ARR as we exit the year, and that's going to benefit the growth rates in 2027 as well. So on the software side, we feel good about that. On services, we talked about execution. There's some operational, there's commercial changes, all of which are execution-oriented with a backdrop of favorability. The market is better than what we've seen. We talked about capital markets funding being better. Overall, we think the backdrop for pharma spending is better. And as we make these operational changes, then we're expecting to see some acceleration there. So that's the setup for -- that's the setup is -- better visibility in software, exiting the year with a stronger ARR and making some operational changes to services, all under the backdrop of a better market environment.

Great. And sticking with you, John Gallagher, with the final question, just -- you've maintained healthy margins. So as you're thinking about accelerating growth, anything you would add in terms of how you're thinking about the margin profile?

I mean we're being disciplined, right? We've done that before. So we hit the top end of our margin guidance last year. And during a time where we were managing through some volatility, I'd say that if you look at the quarter, we put a 30% margin. It's at the bottom of our range. But we did cite some choppiness in the first half. We think that will resolve and accelerate into the second half. And we're taking cost actions, too. We just divested the regulatory business, which does come with some stranded costs that we're dealing with in the first half of this year. But we're taking costs out. We're seeing some revenue acceleration in the back half, and that's going to help us stay inside the range.

Great. Well, I think that does it for time. Thank you, Jon and John, for joining us.

Thank you for having us. Appreciate it.

Thanks.