Hi. Thank you for your attendance at our Jefferies London Healthcare Conference. Appreciate your interest here in our healthcare company guests. I'm Dave Windley with Jefferies Healthcare Equity Research in the States. I cover drug development supply chain related, I'll call it, so CROs, CDMOs. Certara happens to be a software biosimulation-focused player, but selling exclusively into biopharma R&D and regulatory services areas. Here to represent Certara is the company's CEO, William Feehery. Bill, thanks for being here. Really appreciate your being here to talk about Certara. Let me start you off with just talking about the sales dynamics of biosimulation. I think when the company came public in 2020, late 2020, was in the throes of the pandemic, we were bringing a COVID vaccine through the pipeline very, very quickly. People viewed, you know, it was kind of a new concept to a lot of investors, biosimulation. It seemed like a tool that could facilitate continued fast development in the theme of that COVID vaccine. We'll start by just putting biosimulation in context in the drug development space and where Certara fits in that. Yeah. Thanks, Dave. For those of you who are maybe new to us, you know, we started talking about biosimulation when we went public. We've been around for about 20 years, so we have a base of people that knew about it, and then some, it was new to some people. You know, what we're doing is we're modeling the kinetics of what's happening to a drug in the human body across many different organs of the body. The purpose of doing that is to inform drug development. We're interested in questions like dosing. Our model is a population-based model, so we're looking at what happens to drugs across populations of people that vary in different ways. Obviously, you know, things like weight and sex matter, but also things like genetic markers or comorbidities are quite important when you get into a clinical trial or into a wider drug market. The fundamental reason why you do this is because if you understand a bit about the drug as you're going into clinical trials, the idea is to reduce the time, the scope, or the scale of the clinical trials. Since that's 50% of what drug companies spend money on in development, there's a significant return if you can use software instead for even a piece of that. To answer Dave's question, we tend to drive about 70% of our revenues from the clinical phase. However, we start working with drug companies much earlier than that, typically right after discovery, and they've chosen a molecule, and they're going into preclinical. The revenues tend to pick up when there's a drug that's looking pretty good and they're gonna move into clinical trials. There's a bigger budget. There's a lot more reasons to use our software. The last thing I'd say is, you know, nothing happens in pharmaceuticals without the approval and the, hopefully, the encouragement of the regulators, which has been a big piece of our story as well. The FDA has been a big proponent of the use of biosimulation, and it's spread to the other regulatory agencies around the world. I think we have our software in something like 17 regulatory agencies. The FDA in particular has hundreds of copies, and they regularly put out guidances about the use of biosimulation and generally encourage the use of it. It's obviously helped us a lot, keeps us on our toes as well because they're quite interested in exactly what's in our models, where it's sourced, why it's valid, and where else can it be used as we go forward. You know, our place in the pharmaceutical development tends to be in clinical when someone has a drug that's looking like it's gonna be successful and you're gonna have to go argue in front of the FDA that you should have your drug approved and explain exactly what you did in modeling to get that far. Excellent. Thank you. Let's take that down maybe a layer. Mm-hmm Into a few of your primary products or product categories. Phoenix, I think I understand correctly that that's in PK/PD, Simcyp, PBPK, and then QSP. Phoenix and Simcyp have been around for a while, and they seem to be in end markets that are perhaps, I don't wanna call them mature, but more well-established. Correct me if I'm wrong, but it feels like QSP is much newer. It's the Wild West. Lots of people out developing models. You're trying to figure out which ones are the right ones to really latch on to and try to scale. Maybe can you help us, again, down a layer, what are the adoption and growth characteristics of a Phoenix or a Simcyp? Separately, what does that look like for QSP? Right. I apologize for all of Dave's jargon. Yeah. I'm trying to avoid using all that. Yeah, you're trying to avoid it, and I'm sticking it in there. Sorry. You know. Alphabet soup. Generally these products, you know, when we talk about PBPK, what we're looking at is we're trying to predict the kinetics of the drug from before we've done trials. We're looking at data of similar drugs. We're looking at lab data. We're looking at, you know, maybe quantum simulations from other people's software. We're trying to predict what's gonna happen when that drug goes into the trials. Maybe a different way to say it is we're trying to predict the effect of the drug on a particular biomarker. On our Simcyp product, which is PK/PD, sorry, what you're trying to do is you're trying to use clinical trial data to pull out the kinetic model from the actual data. It's a separate piece of software. You have sort of a different user group, but also, you know, quite a good business for us. Quantitative systems pharmacology, which is the new kid on the block, as you say, Dave. What we're doing is we're modeling the, you know, the interaction of the drug with its target. That's led us into things like cell and gene therapy or, for example, some of our modeling of neurodegenerative diseases. We're looking specifically at the disease state and exactly how the drug interacts with it. It's a little bit. If you go to, you know, scientific conferences, that's what everybody wants to talk about all the time, so it's newer from that standpoint. From a business model standpoint, the trick is, you know, we generally try to avoid doing one-off models. It's not good for business. We're looking for a population of pharmaceutical companies or projects where we're gonna be able to develop, you know, invest significantly, but develop a model that we can resell. The race is kind of on in QSP among the different companies that are working in that around how do you do that? You know, what will be the software that will, you know, become the standard over time? You know, how do you sell this to the FDA? The FDA generally does not love companies coming in with bespoke models where they have to go through line by line and explain, you know, whatever, what you did there. They would like some commercially available software where everything's documented. We believe over time, we'll make inroads in that area. So thank you for that. That's helpful. Thinking business model in Phoenix and Simcyp, products that have been around for a while are used, I think, in the IPO process, we talked about, like, every drug program is using at least some biosimulation in some form or fashion. What drives growth, new company formation and new biotechs in the small tail of that sector of the industry, I'm sure is a driver. But if programs are already using that, those areas of biosimulation, where are the growth edges for those more established products? Yeah, it's a good question. We have, you know, 50% of our revenue comes from the top 50 pharma, and we have 1,800 customers, so mathematically, you know, 50% from the next 1,750. The, you know, we do add new customers every quarter, but the bulk of the growth is coming from, obviously from further penetration in the existing significant customer base we have. In order to do that, there's really two ways to attack the problem. One is we are expanding the use cases. There's plenty of areas that we could improve our models or we haven't gotten around to modeling. If we can add a therapeutic area, that adds a whole set of, use cases that you could use our product for. The second piece that we think a lot about is around the number of qualified users of the product. You know, we'd like to expand biosimulation. We'd like to expand people who understand it. You know, we are very aware that we're part of an ecosystem here. people leave Certara, they go to drug companies, they come back. The people who are hardcore users tend to evangelize the software. we're trying to encourage that. we're also trying to make it possible for, you know, these sort of non-super users to make use of the software. we're also developing versions of the software that are much more targeted. Someone who doesn't wanna spend hundreds of thousands of dollars buying a software license that they're mostly not gonna use, we can provide. You know, we're starting to think about basically, call it more focused, a little bit smaller products, where we can target specific customer bases that wanna solve one problem within that. Got it. Sticking with these products, again, in the more established areas, how does the customer choose? So thinking multifaceted here, is the basic question. I'm thinking about a GastroPlus at SLP, a NONMEM at ICON. Your products are, and this perhaps risks getting in the weeds, but are those in slightly different areas that they're not directly competitive to Phoenix or Simcyp? Or are they competitive and, you know, how does the customer choose which one he or she is gonna use? Yeah. Like, I guess, like, in a lot of early-stage markets, there's sort of a confusing overlap between competitive products that nobody's exactly direct competitors with each other. In our case, we've targeted companies that are in the clinical phase that need software that they can explain to the FDA. That's kinda what our target was. Some of the other companies that you're talking about have targeted more, you know, say, preclinical or discovery groups. You will see a lot of our customers will have some or all of the products that you've mentioned. Over time, you know, there's a lot of opportunity for the products to expand. I think you'll see, you know, maybe more competition as we go forward there. How people choose, a lot of it has to do with the differences in the software. You know, does it have a model that's accepted in the specific area you're working on? Where are you? You know, is it a model that's been accepted by the FDA, by anybody else? That's a big piece of it. We tend to win there since we have gotten more drugs by far through the FDA using this. You know, like any technology development industry, a lot of this has to do with your investment in the future of the product. You wanna bet with the long-term winner. Who's investing a significant amount, who's moving the ball forward is, I think, a big piece of what a lot of our customers think about. Okay. That actually segues nicely into my next question. You hosted a first investor day in December of 2021. Talked about at that time, incrementing your R&D spend, adding to your R&D spend by $2 million, 2022 and 2023, focused on, I think, your data platform and on QSP. I already asked you on QSP, and you talked to it a little bit, but maybe, you know, take us down a level there in terms of where that incremental R&D investment dollar is going. What are your areas of focus? Yeah. A lot of this discussion comes when we did our IPO, what we talked about was we have a fairly predictable business model where we believe that. Well, we target running our business in the mid-30s% EBITDA margin, and that gives us enough investment to continue growing our business in the mid-teens% from a top-line growth rate. And it's fairly predictable in the sense that we have, you know, our backlog of business that typically runs between 10 and 12 months, so we kinda know what's coming for the next year. A lot of people have asked us, "Well, that's great, but, you know, what if you didn't run at mid-30s% EBITDA margin? Could you grow the business faster?" We thought a little bit about that and, you know, there's been discussion around, you know, if we increase our investment in R&D, can we increase the growth rate of biosimulation? We've done some of that this year. The growth rate of biosimulation did in fact tick up this year, so we're probably running more in the high teens if you look at our business model this year. There's a lot of organic investment opportunities for us to go forward. Having said that, you know, we still believe that, you know, we've been around for 20 years. We're not in a position of a startup where we can significantly take down our profit margin. This would be more just sort of on the bubble in terms of making incremental investments from what you know, our significant internal investments are right now. In those investments in QSP, what would be the thing that we should look out for that would be the signal that you know QSP is coming of age or that the products that you've chosen to invest in have you know hit the steeper part of the S curve and are starting to accelerate? Is it a regulatory acceptance? Is it approval of a drug using those biosimulation strategies? What should we look for? Yeah. I think it's, I mean, ultimately, the success is approval of drugs that have used that during their development. It's probably a little bit early for us to make that call, but I believe in the next, you know, year or so, we'll start to be able to make those claims in QSP. Obviously, we make revenues significantly before the drug is approved, but if it's never approved, then you don't really have a, you know, an ongoing market to sell against, and you can't really claim that it's a, you know, a long-term success. I believe, though, that, you know, particularly in our neurodegenerative models, we're gonna see some quite interesting results coming out from some of our customers. I would say that in our immunogenicity and immuno-oncology models, you know, we've got some interesting things going on as well. Pharma takes a while, obviously. Pharma development takes a while. We've been doing this for a few years, and I think we'll see some pretty good successes there. Interesting. Not only what to look for, but in what areas to look for. Appreciate that. Maybe something to spend a couple minutes on is the consortium model. I think the consortium was where Simcyp started and how it was created. You're employing that, I think, with QSP as well. Talk about how that works and how that accelerates the refining of the model. What we call our consortium model, it sort of dates back to our founding history, but it kinda think of it as the club of our most avid Simcyp users. What happened in our founding was that there was a consortium of pharma companies that got together, and they wanted commercial software in biosimulation. To some extent, that they stood us up 20 years ago, and that consortium never went away. In fact, it's grown. I think it was probably 12 companies in the beginning, and it's roughly 30 right now. Those are companies that are signed up for generally multi-year contracts, multiple seats, and in addition, they have a significant say in the development of the software, what features we implement every year. Tends to get voted on. It is voted on by the consortium. Those are our users that, you know, need Simcyp for their job. You know, some pharma company hires somebody, comes with a Simcyp license, so they really care. They've helped us a ton. We get a lot of help from our customers. We get data, we get ideas, we get, obviously, test users for the for our new features. It's not our only market. We also directly license to some to a number of customers that are not in the consortium. For the sort of the smaller and the medium-sized customers that don't wanna have these internal groups of scientists that are, you know, dedicated to using our software, we have built up our own internal capability where we'll use the software and do projects for you. That's actually been a nice expansion of the use of biosimulation outside of the top, you know, the really large pharma companies and, you know, expanding it throughout the industry. I wanna move on to the non-biosim parts of your business that you refer to as Regulatory services and market access services as well. Can you talk about the business case for the company to have entered into Regulatory services and market access? It's smaller, but to the extent that you're playing there. Mm-hmm. What's the business case, and what's the longer-term differentiation strategy? Yep. It's a little bit different in both cases. We acquired a Regulatory Services business, I don't know, a number of years ago, but the logic behind it was twofold. One is our customers in biosimulation are basically doing biosimulation because they're going to take it to the regulators. They're gonna have to make a regulatory argument, and we better be really credible if we're gonna make recommendations around biosimulation. Our thought was, by having a business where we're regularly doing this type of work, that would help our credibility. Second piece is, you know, what we found is that, for a subset of our customers where we're very highly involved in their project from a biosimulation basis, typically over a number of years, we know a lot about that project. We're sometimes in a very good spot to win that work, and it can be a significant, you know, upside on the work we've done on that drug. It's not all of our customers, but it's enough that it's been quite interesting for us over the years. I'd say, you know, overall, we are a... Effectively, we're kind of a niche onshore regulatory business, fairly specialized, but also quite capable in terms of we're capable of doing anything from writing an IND or writing an NDA, you know, doing regulatory strategy, in some cases going with the customers, you know, to the regulators to make presentations. Our thought on market access was a little bit different. We have a very small market access business. But the thought there is a little bit in the longer run where we're going. We think that over, you know, really the kind of the bigger picture here is that we can use biosimulation to predict the effect of a drug on a biomarker, and we can correlate biomarkers with clinical outcomes. Then once we have some understanding what a clinical outcome is, then it kinda lends itself to doing economic modeling. So ultimately, we'd like to be able to go into a pharma company and say, "Look, you know, from the very beginning, we can start to make some predictions about what's likely to happen in this drug program and what actions you ought to take it to make it, say, more successful economically at the end of the day." Do we have all the pieces right there in place for the market access part? Not entirely, but we're headed that way. We have a nice business in that area. It does well. But you know, part of it was built for the longer-term strategy. In the Regulatory services part of the business, who are you competing against primarily? How, you know, is it the bigger CROs? Is that the primary competitor, and how, you know, how do you differentiate to win that business when, you know, they have a pretty good position because they're working on the trial? Yeah. I'd say the big CROs have a much bigger regulatory business than we do. I don't think we typically go head-to-head with them on business. The business that we tend to win, as I said before, it tends to be either customers we had in biosimulation, or it tends to be small or medium-sized customers that for some reason feel like the service they're getting from the really big CROs might not be the same level as a big pharma company might be getting. We're specialized. We're quite nimble. You know, if you only have one drug, you know, you pay a lot of attention to that. There are a few companies like ours that compete in that area. We think we have, you know, maybe 10% of the real addressable market, the part that's, you know, actually gonna consider not staying with their CRO. Okay. That business has been, in 2022, a more uneven, less smooth business for you, in your case because you're, for these projects, as I understand it, you're waiting on studies to get done. They hand you the locked database. Until that's locked, you don't start your project, and therefore, you don't start the revenue recognition. Do you feel like, one, you've gotten your arms wrapped around that? Is it getting any better? You know, is the customer environment getting any better or any worse? Well, the thing about this business is it's a bit lumpy, right? The projects in that business are fairly large by Certara's size. When you miss one or two in a quarter, it really shows up. From the beginning of the pandemic, we started talking about how we'd seen a lengthening in time for clinical trials to complete, and I think other S&P companies have also mentioned that. We have seen in our backlog a fair number of customers who have sort of 90% of their clinical trial data, but they don't. That last 10% takes a really long time, probably. Well, reasons that we don't do clinical trials, but people have talked about clinical trial enrollment slowdowns and things like that. It seems to be not just a surprise to us, but our customers in a lot of cases have signed up, and I don't think they would've signed up months and months before they expected to really need the services. You know, this has caught I think a lot of the industry a little bit by surprise. We've made some changes in our management, in our sales model, and we guided in August about what we expected to happen for that business for the rest of the year, and it is performing along that guidance. As we go into next year, we expect it to return to you know at least some kind of some sort of you know modest growth. I mean, right now, biosimulation is growing nearly 20% a year, so I don't think we're gonna get that business quite up to there. Over time, you know, we are seeing some improvement in the pipeline. Too early, I think, to make a call of a turnaround there, you know, we're feeling confident. It's a profitable business, and I said there's a strategic reason why we own it that we think is important. The improvement, have you changed your sales go-to-market at all or increased the sales intensity in this area? Like, trials could continue to be slow, but you could, you know, win more mandates and kinda make up for it that way. Yeah, yeah. Exactly. That's kind of where we're thinking about it from a- Yeah. You know, as we've started to rethink a little bit our sales model and our sales, some of our sales personnel, what we're targeting. That's in flight? Right. Yeah. Okay. I guess we've got a few minutes left. One of the bigger pieces of news here recently was this kind of change of your, you know, your lead investor. Arsenal had been invested in the company back in the mid-teens, sold a controlling interest to EQT but did keep a minority interest. EQT brought you public and has been selling and now sold the remainder of its position to Arsenal. Mm-hmm. What should investors interpret from that change? Yeah. The IPO was kind of the start of EQT's monetization of Certara. They were pretty open about it, and we've had a number of transactions over the years that people over the year and a half, I guess, that people watched. I think the interesting thing about Arsenal is they've been involved in Certara almost from the beginning. In fact, Arsenal kind of views themselves as the founders of, in some ways, of Certara if you go and ask them. You know, they were the original owners when they sold the majority stake to EQT. They didn't sell all of their stakes, so they've maintained a shareholding for about a decade now. One of their partners has been on our board for about 10 years as well. The way I think about this is, you know, we've got a big vote of confidence from an investor who really knows us quite intimately. I mean, they've been, you know, going all the way back to the beginning of time from Certara's basis. It's a significant investment for their fund. I think it's the largest one they've ever done. It's a bit unusual for a private equity firm to come into a public company, so I think, you know, that that's also important. They also locked up their shares for two years. It sort of eliminates that overhang that we had for the last chunk of the EQT shares at the end of their process. Overall, I think, you know, it's an investor we're happy to have in the company. Do you expect that the strategy, that the elements of the strategy remain the same? I don't know exactly when in the evolution the company branched out into reg services and market access and things like that, if that was, you know, more of an Arsenal, you know, origin strategy or a EQT-driven strategy, but I'm just wondering what elements might change, if any. Like I said, Arsenal's been around for 10 years involved with the company, so I'm not expecting to make any significant changes to our positioning or our strategy because they already know all that, and they've been involved in it in the beginning. I can't remember exactly when all of those acquisitions were made under which EQT, which private equity company, but I don't think it's really gonna affect the kind of what we're doing in the future here. I would view this more around they like what we're doing, and we're gonna continue doing more of that. Maybe to end, we're at time, but I'll ask you one more. You have been acquisitive, both before and after the IPO. Yeah. What's your appetite and how robust is the pipeline there? Well, we run the company on a pretty conservative basis. Our net debt right now is about a half turn of EBITDA. We do that specifically because we're in a rapidly growing market where there are interesting technologies and it's useful to be able to move when they become available, which is not all the time. We think we have plenty of internal organic investment opportunities, and we're perfectly happy doing no acquisitions. When something happens, it's important to combine it. We did one last year with Pinnacle 21. For the last nine months, we've seen private company valuations, frankly, hadn't caught up to where our public company valuations are, so we haven't really done a whole lot for the last couple months, and that's been fine. You know, we're always keeping an eye on a lot of things. Got it. Great. Thank you, Bill, for being here. Appreciate the audience's attention. Wish you a good rest of the conference. See you tomorrow. All right. Thanks.