Thanks for joining us. My name is Ryan Halsted. I am the Healthcare Technology and Distribution Analyst with RBC's Healthcare Research Team. We have Certara up next. I am pleased to be joined by Jon Resnick, CEO, and John Gallagher, CFO. Certara is a tech-enabled drug development company. Welcome. Thank you, Ryan. Nice to be here. Thank you for the invite. Jon, I wanted to start with you. You've been in the CEO seat now for five months, and just wanted to get some perspectives from you on, you know, about the company since you've joined, anything that surprised you or anything that's changed. Has it really only been five months? 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 kinda scientific leadership, you know, the deep kinda 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, maybe this is a little bit of a surprise, is around the portfolio itself. You know, look, there are a number of things that the company is known for, a number of kinda market-leading assets. As you dig a little bit deeper within the company, there is just this absolute set of jewels that exist, you know, built on the deep expertise that's been accumulated over the last few decades and the kind of unrivaled suite of capabilities. You know, there are all of these opportunities to deploy our expertise in different ways. You know, with a little bit of nurture, a little bit of product development, and a little bit of evolution, you know, there's no shortage of areas to go. Great. Well, maybe following along with, you know, your background and joining Certara, you know, I noted come from a large CRO with experience with real-world evidence technology in integrating that with clinical, within clinical research. Just curious, you know, how are you kinda leveraging that experience and knowledge and expertise at Certara and bringing that to its opportunity set? Yeah. I spent over two 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 of you to pick up on that. On its face, you know, creating and running a business on real-world evidence versus, you know, a business more in the model-informed discovery and drug development space seemingly different, but the similarities and the analogs between the two 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. You know, real world in the 2010s was a very new concept that was had a ton of promise. Regulators were 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. The, you know, MIDD or MID3 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, you know, 15+ years ago, it was a very isolated science that had very specific groups, the epidemiology, biostats, health economics, outcomes researchers, very specific groups that worked on it. 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, you know, early discovery teams and the clinical trial teams to take advantage of the full depth and breadth of the real-world evidence within life sciences. I see the MIDD story as a very similar one, which is today, it is a core power science used by, you know, a handful of, you know, pharmacoeconomics groups and PBPK groups, and, you know, groups who are highly specialized. 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. Well, hopefully we'll gain some more insights on the regulatory pathway as we look further out— Yeah. —kind of adoption and acceptance of the technology. Maybe transitioning to, you know, AI in drug discovery, certainly, you know, I think there's an appreciation of the opportunities there, but also, you know, there's a perceived threat of disruption that has cast a pall on many stocks that touch on this arena. Just curious, you know, how are you thinking about Certara's competitive position against, you know, these new emerging AI technologies that may or may not be disruptive? Wow, that's, o kay, where to start on this topic? First of all, I'd say, look, we view AI as a huge enabler for the business across the board. You know, this is something, you know, three and five years, you know, three years from now, we will be known as, you know, a market leader in this space, and it'll accelerate everything that we are doing. 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, you know, accelerate the, you know, the frequency and the volume by which MIDD itself will be demanded. As we think going forward about the opportunities, you know, that exist for us, we've got this long legacy, you know, literally decades of working on successful products, hundreds of products that have included, you know, that have worked with Certara and have informed their label. 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, that are fully embedded. If you think about, you know, 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 kinda data transactions. We have, you know, computational knowledge and kinda 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 kinda expert in the loop. All of that creates this amazing foundation to take the next step with this, which is to, you know, agentify, you know, 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 kinda 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, you know, AI you think could have the impact of, you know, generating more new drug candidates and faster. That's certainly a conversation that I've been having with investors, recently, this idea that, you know, we 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 in, you know, what inning do you think we are in terms of AI and drug discovery that's gonna, you know, drive volume? Oh, boy. Early, super early innings. I mean, I think we're just scratching the surface for what can be deployed. You've seen, you know, an exponential increase over the last few years, but we're still, you know, we're still doing, you know, 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, you know, 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. We're super early in, you know, in this. We're gonna see explosion over the next 5- 10 years and, as I said, it's gonna be huge accelerant for, you know, core MIDD, which is a perfect complement to a lot of the investments that's going on today. Right. Maybe on your investments in AI, I think you've mentioned, you know, on your last call, investing in the next-generation platform. Can you talk about some of those strategic initiatives in terms of, you know, those investments, and how are you measuring success, or how are you going to measure success? I mean, I think we're already investing, so it's not, we're already, you know, we're already adding AI functionality to just about everything within our portfolio. In fact, the fastest growing products within, you know, within this quarter are AI-native products and very specific. We're seeing huge acceleration. We're working through the agentification. A lot of our next-generation workflow, our QSP and PBPK roadmaps are loaded with this. You know, we're already sitting in our, you know, in our clients' infrastructure and their workflow, and our ability to kinda 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. You know, the big models will be fantastic at kinda creating foundations. No one's competing with the big model companies in terms of their ability to, you know, build out the general models. The layer between, which is kind of this, you know, regulatory intelligence layer, or what we're calling a clinical and scientific intelligence layer, really needs someone with the deep expertise like a Certara. You know, I talked through the capabilities and the platform before, which creates a lot of distinctive capabilities. Just to give you kinda one example of why you need this kinda 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, you know, things like drug-drug interaction, pediatric trials, and increasingly going to move into pregnancy and other things. It's the only product that's certified by regulators, you know, we think, certainly in Europe and maybe in the world, to do this type of task. You know, if you think about the process to get this regulatory validated asset approved, it took two 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. 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, 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, wanted to touch on the broader customer demand landscape and environment. You know, would be curious what you're seeing in terms of, you know, just demand for either discovery or, you know, preclinical work more generally. Just, you know, any particular areas of strength that are worth highlighting amongst, you know, your customer segments or types of customers? Yeah. 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, you know, biotech funding, I look at new trial starts, I look at, you know, we talked about some of the AI discovery and the increasing kind of pipeline size. All those are, you know, really positive metrics that we track. I also look at regulator engagement and, you know, over the last few months, we've seen several, you know, regulator tailwinds from our standpoint, either, you know, pushing NAMS or, accelerated clinical trial execution or clarifying, you know, some of the role for, you know, for model-informed drug development. All of those are tailwinds as well. From a, from a market standpoint, certainly, you know, we see it after a couple rough years, over the last couple years, certainly improving. Based on the volume of questions and engagements and inquiries we're getting, from clients, we see, you know, robust market, which is just strengthening and increasing. You know, anytime you do something that pushes regulatory boundaries or kind of changes, that take, you know, takes changes in current practices, it takes time. The amount of questions we're getting about how to do things differently certainly is incredibly encouraging demand signal. That's great. Maybe I wanted to get into the regulatory landscape in a second. Before we move on from this topic, just, you know, I think much has been made about the biotech funding environment. It's been pretty healthy, companies able to access capital— Yeah. —in various ways or, you know, realize exits that give other companies confidence and perhaps maybe spend. You know, 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, you know, is still a quarter or a few quarters out in terms of trickling down into actual spend? Historically, we've looked at that. Timing of positive funding and what the pull-through is on our customer tiers, especially Tier 2 and Tier 3 customers. It generally takes about a quarter. 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. Now, as Jon was just saying, overall, it's a tailwind for our biotech customers, which would fall into that Tier 2 and Tier 3 category. We saw strong performance in Q1 in both of those categories in software. We commented that, you know, that there's some execution points that are gonna help us on the services side, and this overall market backdrop is gonna aid that effort as well. The thing I'd add is that our business model itself is set up to be flexible based on, you know, the different segments. You know, 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. The 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. As that funding improves, you know, 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, you know, wanting to see increased acceptance of things like NAMS. You know, obviously, there's some changes at the FDA, 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. Just wanted to get your thoughts. You know, what are you looking for from the FDA in terms of, you know, that further support and acceptance of NAMS? Yeah, I think I've learned a long time not to kind of forecast regulatory agencies too much. It's certainly a difficult one to do. Like, these are long-term trends. They make sense. As our computational capabilities, as our AI capabilities accelerate, as our ability to understand the human body more and more, these are the right things to, you know, to be building, not only for, you know, there's a lot of drivers in efficiency and speed and time, and the time to market is a worldwide issue. You know, I know there's a lot today of, you know, U.S. positioning versus China. We've seen a lot of money moving to China. There's lots of incentive for regulators in U.S. and Europe to accelerate timelines and speed to market. I think these trends are somewhat immutable. The rate and pace at which they're accepted may vary from administration to administration or regulator to regulator, but I don't see the fundamental trend of accelerating. It just makes too much sense. I was talking to one of our toxicology leaders yesterday. I mean, he sees huge opportunity to avoid tons of bioequivalence trials and to do a lot of, you know, tox simulation. I mean, there's just so many applications here as we push more into QSP and really, you know, mix in and not only the understanding of the human biology, but you know, real-world data and other things. There's just so much to know, and there's so much inefficiency the ways our trials are executed. 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. You know, as you're thinking about the business, plan for 2026, you know, how should we think about the timeframe to achieving that double-digit growth, and what are kind of the next key milestones to be on the lookout for? Yeah. I'll do it strategically, and then I'll turn to you, John— Yeah. —for some of the guidance around this. Look, we've taken, you know, in the first 100 days, we've done some pretty significant reorganization of the company. We set it up around two major growth, you know, hypothesis growth stories. One around what we call MID3, which is model-informed drug discovery, drug development, as we know, and we've also added discovery to that as well to drive that kind of longitudinal connection across the pipeline. You know, 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. Then the other side, we created a new group called ACE, which is Accelerated Clinical Evidence. The way to think about that is truly around the digitization, particularly around data and acceleration, the way data can be generated and can help accelerate from protocol all the way to submission. Those are two, we think, very nice growth platforms, very consistent with what the regulatory bodies around the world are looking for in terms of accelerated execution, accelerated, you know, time to market. We're excited about the room that creates for us. We're also strategically also looking, and 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, you know, our drug-drug interaction, you know, capabilities. You can apply those to clinical trial simulation. You can apply those earlier into discovery. You know, is there opportunities to do something like that in the clinic? There's a whole range of ways that you could go. We're pretty bullish about the long-term opportunities for growth, a combination of execution and kind of untapping some of these opportunities [that led us to one]. The building blocks to get there are if you look at the quarter, on the software side, we did 7% revenue growth on the quarter for software. That was above our expectations. 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. You know, 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 gonna benefit the growth rates in 2027 as well. 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. As we make these operational changes, we're expecting to see some acceleration there. 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. sticking with you, John Gallagher with a final question. Just you've maintained healthy margins, you know, 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. We hit the top end of our margin guidance last year, during a time where we were managing through some volatility. I'd say that, you know, as you look at the quarter, we put a 30% margin. It's at the bottom of our range. We did cite some choppiness in the first half. We think that'll resolve and accelerate into the second half. We're taking cost actions too. We just divested the regulatory business, which does come with some stranded cost that we're dealing with in the first half of this year. We're taking cost 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, John and Jon, for joining me. All right. Thank you for having us. Appreciate it. Yeah. Yeah. Thanks, Ryan.