Certara, Inc. (CERT) Earnings Call Transcript & Summary

Thank you for your attendance at our Jefferies London Healthcare Conference. Appreciate your interest here in our health care company guests. I'm Dave Windley with Jefferies Healthcare Equity Research in States and cover drug development supply chain related, I'll call it, the CROs, CDMOs. Certara happens to be a software biosimulation focused player, but selling exclusively in the biopharma R&D and regulatory services area. So here to represent Certara is the company's CEO, William Feehery. Bill, thanks for being here. Really appreciate you being here to talk about Certara.

So 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. And people viewed -- it was kind of a new concept to a lot of investors, biosimulation, and it seemed like a tool that could facilitate continued fast development in the theme of that COVID vaccine. So maybe you could -- will start by just putting biosimulation in context in the drug development space and where Certara fits in that?

Yes. Thanks, David. So for those of you who may be new to us, we started talking about biosimulation when we went public. We obviously had a -- we've been around for about 20 years. So we have a base of people who knew about it and then it was new to some people. But 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. And the purpose of doing that is to inform drug development. So 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, 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. And 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. And 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. So the answer to David'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 are going into preclinical. But the revenues tend to pick up when there's a drug that's looking pretty good, and they're going to move into clinical trials. There's a bigger budget. There's a lot more reasons to use our software. And the last thing I'd say is nothing happens in pharmaceuticals without approval and hopefully the encouragement of the regulators, which has been a big piece of our story as well. So the FDA has been a big component of the use of biosimulation. And it's spread to the other regulatory agencies around the world. So I think we have -- our software in something like 17 regulatory agencies but 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. So our place in the pharmaceutical development tends to be in clinical when someone has a drug that's looking like it's going to be successful, and you're going to 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. So let's take that down maybe a layer into a few of your primary products or product categories. So Phoenix, I think I understand correctly that that's in PK/PD, Simcyp, PBPK, and then QSP. So Phoenix and Simcyp have been around for a while, and they seem to be in end markets that are perhaps -- I don't want to call them mature, but more well established. And then -- 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. So maybe -- can you help us, again, down a layer, what are the adoption and growth characteristics of a Phoenix or a Simcyp? And then separately, what does that look like for QSP?

Right, right. And I apologize for all of David's jargon. I'm going to avoid you in all that.

Yes, you're trying to avoid it, and I'm sticking it in there, sorry. So [indiscernible].

But generally, what we're -- generally, these products, when we talk about PK/PD, what we're looking at is we're trying to predict the kinetics of the drug from -- before we've done trials. So we're looking at data of similar drugs. We're looking at lab data. We're looking at maybe quantum simulations from other people's software and we're trying to predict what's going to happen when that drug goes into a trial or maybe a different way to say 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. So it's a separate piece of software where you have sort of a different user group, but also quite a good business for us. And then quantitative systems pharmacology, which is the new kid on the block, as you said, David. What we're doing is we're modeling 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. So 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 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 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 going to be able to develop, invest significantly, but develop a model that we can resell. And so the race is kind of on and QSP among the different companies that are working in that around how do you do that. What will be the software that will become the standard over time? And 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 whatever -- what you did there. They would like some commercially available software where everything is documented. And so we believe, over time, we'll make inroads in that area.

So thank you for that. That's helpful. In -- so thinking business model in Phoenix and Simcyp, so 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. So where's -- 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 the growth edges for those more established products?

Yes, it's a good question. So we have -- 50% of our revenue comes from the top 50 pharma, and we have 1,800 customers. So mathematically, 50% in the next 1,750. So 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. So in order to do that, there's really 2 ways to attack the problem. So one is we are expanding the use cases. So there's plenty of areas that we could improve our models or we haven't gotten around to modeling. So if we can add a therapeutic area that adds a whole set of use cases that you could use our product for. And then the second piece that we think a lot about is around the number of qualified users of the product. So we'd like to expand biosimulation. We'd like to spend people who understand it. And we are very aware that we're part of an ecosystem here. So people leave Certara, they go to drug companies, they come back, and the people who are hardcore users tend to evangelize the software. So we're trying to encourage that. And we're also trying to make it possible for these sort of non-super users to make use of the software. So we're also developing versions of the software that are much more targeted. Someone who doesn't want to spend hundreds of thousands of dollars buying a software license that they're mostly not going to use. We can provide -- we're starting to think about basically, call it, more focused, a little bit smaller products where we can target specific customer bases that want to solve one problem within that.

Got it. And sticking with these products, again, in the more established areas, how does -- how is the -- so thinking multifaceted here, how does the customer choose is the basic question. And I'm thinking about a GastroPlus at SLP, NONMEM at ICON, your products, are -- this perhaps risk 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 how does the customer choose which one he or she is going to use?

Yes. And so like, I guess, like in a lot of early-stage markets, there's sort of a confusing overlap between competitive products, nobody is 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 kind of what our target was. Some of the other companies that you're talking about have targeted more, say, preclinical or discovery groups. And so you will see a lot of our customers will have some or all of the products that you mentioned. Over time, there's a lot of opportunity for the products to expand. So I think you'll see maybe more competition as we go forward there. How people choose? A lot of it has to do with the differences in the software? Does it have the specific -- does it have a model that's accepted in the specific area you're working on? Where are you -- is it a model that's been accepted by the FDA by anybody else. It's a big piece of it. And we tend to -- we tend to win there since we have gotten more drugs by far through the FDA using this. And like any technology development industry, a lot of us has to do with your investment in the future of the product. So you want to bet with a long-term winner. So 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. At your -- you hosted a first Investor Day in December '21, talked about at that time, incrementing your R&D spend, adding to your R&D spend by a couple of million dollars, '22 and '23 focused on, I think, your data platform and on QSP. So you've talked on -- I already asked you on QSP and you talked to it a little bit, but maybe take us down a level there in terms of where that incremental R&D investment dollars are going, what are your areas of focus?

Yes. So 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 in 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 a -- we have our backlog of business that typically runs between 10 and 12 months. So we kind of know what's coming for the next year. A lot of people have asked us, well, that's great, but if you -- what if you didn't run at mid-30s EBITDA margin, could you grow the business faster. And so we thought a little bit about that and there's been discussion around, well, 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. And there's a lot of organic investment opportunities for us to go forward. Having said that, we still believe that we've been around for 20 years. We're not in a position of a start-up where we can significantly take down our profit margin. So this would be more just sort of on the bubble in terms of making incremental investments from what we're -- 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 QSP is coming of age or that the products that you've chosen to invest in have 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?

Yes. 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 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 an ongoing market to sell against, then you can't really claim that it's a long-term success. I believe, though, that particularly in our neurodegenerative models, we're going to see some quite interesting results coming out from some of our customers. I would say that in our immunogenicity and immuno-oncology models, we've got some interesting things going on as well. So pharma takes a while to, obviously, pharma development takes a while. We've been doing this for years, and I think we'll see some pretty good successes there.

Interesting. So not only what to look for, but in what areas to look for, so I appreciate that. The -- maybe something to spend a couple of minutes on is the Consortium model. So 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?

Yes. So what we call our Consortium model, it sort of dates back to our founding history, but kind of think of it as the club of our most avid Simcyp users. So what happened in our founding was that there was a consortium of pharma companies that got together and they wanted commercial software in biosimulation. And so 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. And those are companies that are signed up for generally multiyear 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 -- well, it is voted on by the Consortium. And those are our users that need Simcyp for their job. Pharma company hires somebody, comes with a Simcyp license. So they really care. And they've helped us a ton. We got 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 some to a number of customers that are not in the Consortium. And then for the sort of the smaller and the medium-sized customers that don't want to have these internal groups of scientists that are dedicated to using our software, we have built up our own internal capability where we'll use the software and do projects for you. And so that's actually been a nice expansion of the use of biosimulation outside of the top, the really large pharma companies and expanding it throughout the industry.

I want to move on to the non -- I guess, the non-biosim parts of your business that you refer to as reg services, has reg services and market access services as well. Can you talk about the kind of the business case for the company to have entered into reg services and market access is smaller, but to the extent that you're playing there. What's the -- what's the business case? And what's the longer-term differentiation strategy?

Yes. It's a little bit different in both cases. We entered into -- we acquired regulatory services business, I don't know, 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 have to make -- they're going to take it to the regulators. They're going to have to make a regulatory argument, and we better be really, really credible if we're going to make recommendations around simulation. So our thought was by having a business where we're regularly doing this type of work, that would help our credibility. Second piece is 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 projects. We're sometimes in a very good spot to win that work, and it can be a significant upside on the work we've done on that drug. So it's not all of our customers, but it's enough that it's been quite interesting for us over the years. And I'd say, overall, we are -- 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, doing regulatory strategy in some cases, going with the customers 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. So we think that over 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. And then once we can -- once we have some understanding what a clinical outcome is, then it kind of lends itself to doing economic modeling. So ultimately, we'd like to be able to go in with a pharma company and say, look, 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 like there in place for the market access part? Not entirely, but we're headed that way. We have a nice business in that area that does well but part of it was built for the longer-term strategy.

In the reg services part of the business, who are you competing against primarily? And how -- is it the bigger CROs? Is that the primary competitor? And how do you differentiate to win that business when they're -- they have a pretty good position because they're working on the trial.

Yes. I'd say the big CROs have a much bigger regulatory business than we do. So 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 and 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. And if you only have one drug, you pay a lot of attention to that. There are a few companies like ours that compete in that area. We think we have maybe 10% of the real addressable market, the part that's actually going to consider not staying with their CRO.

Okay. That business has been in 2022 a more uneven and 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 when you've gotten your arms wrapped around that, is it getting any better? And is the customer environment getting any better or any worse?

Well, the thing about this business is a bit lumpy. So the projects in that business are quite -- are fairly large by Certara size. So when you miss 1 or 2 in a quarter, it really shows up. So from the beginning of the pandemic, we started talking about how we've seen a lengthening in time for clinical trials to complete. And I think other 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% is a really, really long time, probably well, reasons that other -- we don't do clinical trials, but people 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 sign up months and months before they expected to really need the services. So 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 at least some kind of some sort of modest growth not likely to be at the -- I mean, right now, biosimulation is growing nearly 20% a year. So I don't think we're going to get that business quite up to there. But over time, we are seeing some improvement in the pipeline too early, I think, to make a call of a turnaround there, but 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.

And 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 win more mandates and kind of make up for it that way?

Yes, exactly. So that's kind of what we're thinking about it from our -- as we've started to rethink a little bit our sales model and our sales -- some of our sales personnel, what we're targeting.

So that's [indiscernible]?

Yes.

Yes. Okay. The -- 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 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, it's the remainder of its position to Arsenal. What should investors interpret from that change?

Yes. So 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 1.5 years, I guess, the people watched. The -- I think the interesting thing about Arsenal is they've been involved in Certara almost from the beginning. In fact, Arsenal kind of viewed themselves as the founders of -- in some ways of Certara, if you go and ask them. But 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. And so the way I think about this is we've got a big vote of confidence from an investor who really knows us quite intimately. I mean, they've been going all the way back to the beginning of our -- beginning of time from by Certara basis. It's a significant investment for the 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 that's also important. And they also locked up their shares for 2 years. So it sort of eliminates that overhang that we had for the last chunk of the EQT shares at the end of their process. So overall, I think it's an investor we're happy to have in the company.

Do you expect that the strategy -- 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 more of an Arsenal origin strategy or an EQT driven strategy, but I'm just wondering what elements might change if any?

So like I said, Arsenal has 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 of that, and they've been involved in it in the beginning. I can't remember exactly when all of those acquisitions are made under which private equity company, but I don't think it's really going to affect the kind of our -- what we're doing in the future here. I would view this more around they like what we're doing, and we're going to continue doing more of that.

And then maybe to end, we're at time, but I'll ask you one more. You have been acquisitive, both before and after the IPO. What are you -- what's your appetite? And how robust is the pipeline there?

Well, we run the company in a pretty conservative basis, our debt -- net debt right now is about a 0.5 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. So we think we have plenty of internal organic investment opportunities, and we're perfectly happy doing no acquisitions. But when something happens, it's important to combine it, we did one last year with Pinnacle 21. For the last 9 months, we've seen private company valuations, frankly, be -- hadn't caught up to where public company valuations are. So we didn't -- we haven't really done a whole lot for the last couple of months, and that's been fine. But 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. I'll see you tomorrow.

Thank you, Dave.