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

We're going to get started with our next session, that is Certara. Thank you all for coming. I'm John Kreger, the analyst at William Blair, that covers Certara. Just a disclosure, if you want to see any of our conflicts of interest, please go to williamblair.com. As you've heard all week, what we're going to do is a 30-minute formal presentation here in the room, and then we will go to a breakout session upstairs on the second floor in Richardson for another 30 minutes for those of you that would like to take part in the Q&A. From the company, Bill Feehery, the CEO, is going to do the presentation in just a couple of minutes; and also Andy Schemick, the CFO, is here. He will take part in Q&A. So we're very happy to have them here. It's the first time they've been here in-person, which is great. So with that, I will turn it over to Bill.

All right. Thanks very much, John, and it's great to be here today. Thank you, everybody. Pleased to talk a little bit about Certara. We have our standard disclaimer, but I'll also start here with our mission. So our mission is to accelerate medicines to patients using biosimulation. We're a collection of now over 1,200 people with -- basically, the general idea is that by using modeling of the known biology, we can accelerate drug development. We see that drug development is important to the world, but it's also extremely expensive and fairly inefficient. So there's a lot of opportunities for improvement. I'll tell you a little bit about our flavor of how we do that. So just at a glance our business. We have actually been around for about 20 years in one form or another. We've had several private equity owners. We've gone through -- well, we have built the company over the years with quite a number of acquisitions. This chart is a little bit old, but I think we're more like 1,200 employees now. We've been growing quite rapidly. The employee workforce is quite educated. We have lots of people with drug development experience, as you might expect. So there's lots of Ph.D.s. And generally, we report our results in 2 areas, but they are really intertwined, software and technology-enabled services. I'll talk a little bit about our products and what we have there, but generally, we are a software company, but we've participated in an industry where this is highly technical software. A lot of our clients want expert help or in some cases, they want us to use the software to provide the answer to them. So we have multiple ways of delivering this technology to our customers. Our customer base is pretty large. We have about 2,000 customers. Our largest customers have been with us for usually quite a long time. We work with virtually all of the large pharma companies, and we've been adding over the years to our group of biotechs and smaller and midsized companies that we work with. There's quite a number of customers that are over $100,000 with us. And I don't have them on this chart, but we have about 55 that are over $1 million a year in spend with us as well. In terms of our financial profile, I won't read the numbers to you, but we've had a long track record of mid-teens revenue growth organically. We also do inorganic acquisitions on top of that, and we've been running the company in mid-30% EBITDA margins, and that includes investment in our future. I'll talk about what we're doing there. So what is biosimulation? The idea of time biosimulation as we have it is to use is to basically model the known biology of what happens not only in one human, but across a population of humans when you get into drug trials. I think in this crowd, you probably know a lot of the statistics about the fact that drug development is -- it's quite expensive, quite lengthy and at least the statistics in early phase of actually being successful are not really high, 7% out of Phase I, for example. What we're doing here is, we're -- what we'd like to do is, to the extent possible, do what we call In Silico trials. So really, what we're doing is, we have models, as I said, of human biology and of human populations. We'd like to be able to simulate what the results are of a clinical trial before you do it. Obviously, we will never be perfect, but you do know a lot of things going in that you don't need to run lots of patients through to find out. And if you can model that and run with that and then use your clinical trials to determine the things that you really don't know from the known biology, you can be a lot more efficient. So generally, what the economic value of this is really 1 of 3 things. We increased the probability of success or we kill the drug earlier or what is really common is, we enable the drug to be successful but use fewer human clinical trials to get there. So what we have in our flagship product, Simcyp, is a huge model of a human body. It looks on this chart like we have different models of different organs, but really like a human body, everything is interrelated. So it's one big interrelated model. This has been built up over the years. Every year, we have a new version of the model where we add more organs, more complexity to the model, and we validated it versus clinical trial data. Now I think the interesting thing of this, as I mentioned a little bit earlier, is not that we're modeling one body, but we have inputs to our model, which model the variation in human population. So in an actual clinical trial, a drug is going to encounter people obviously different sex, age, weight, different genetic heritage, different comorbidities. And so if you want to simulate what the result is of an actual clinical trial when you're out in a large population or later when the drug is out in the full population, we need to be able to account for this. So really, we're running this model over and over again with different inputs to produce a prediction of what will happen in the clinical trial. We focus most of this on the clinical stage. That's where -- frankly, that's where the money spend is, that's where the stakes are higher. But really, what we're doing is, we start early on and at each stage, we're trying to predict the next stage based on the data we have. So you saw -- maybe I'll just start with some data on what the properties of the molecule are, and we're looking at that versus what are some other drugs that have gone through and that are similar. As we start to get clinical data, we input that to the model. The model gets more accurate and starts predicting the next phase. That's generally the goal. And I think when we went public, a lot of people were kind of stunned and even in the industry, people are -- sort of say, wow, I didn't know you could do this. It has been going on for a long time. This has been something that I think the pharmaceutical industry realized maybe 20 years ago was going to be an important thing to invest in. But for a lot of reasons, it's taken some time to get to the stage where we are today. We have however built on that. You can see just some proxies for the interest in biosimulation in the industry in terms of the number of papers that are published on this. And then I haven't really talked about this, but nobody in pharmaceuticals is going to do anything that the FDA would not be supportive of. And so the FDA has been quite supportive of the use of biosimulation over the years. So you can see they put out guidances and the number of those has been growing over the years. So the FDA has been a user of our software since we're a major provider of biosimulation software, but I think more importantly, they've been encouraging the industry to use biosimulation. There's a number of reasons for that. One is because the use of this kind of software enables the FDA to ask intelligent questions about the data that's submitted. Another one is, the FDA has an interest in keeping the cost of drug development within reason. And so to the extent that this is able to -- enable people to be more efficient, that's something that they have generally been interested in. And generally, the FDA consists of a whole lot of very good scientists who are quite interested in the science behind all of this. This is an eye chart, but Simcyp software to date informed over 250 drugs. So we're actually mentioning on 250 drug labels over that for 90 drug approvals. At some point, you can -- I'm not going to read all these names of drugs that are out there that have used our software, but we believe that the point here is that each one of these customers avoided some degree of human clinical trials in the development of this. So effectively, this results in -- they've saved millions of additional man hours, costs and also, it's more ethical to use fewer human clinical trials, if you can. Our customer base is, as I mentioned, quite large. You can see some of the logos of our largest customers. We actually do serve quite a broad section of the pharmaceutical industry. We have a broad section of software and services that enables us to kind of get in early and then stay with the drug as it moves through development. In terms of the types of projects we work on, I'd like to say that Certara's current projects are a pretty good snapshot of what the pharmaceutical industry is actually working on today as a whole. So unsurprisingly, you'll see in our portfolio today a lot of rare diseases, lots and lots of oncology projects, but really, we have spent the gamut of all the therapeutic areas that pharma has been working on. And then just a little bit about our business model. So we have an integrated model of software and services. So the core really, we are a software company. We develop modeling software, and we have large groups of modelers that are really focused on using that software to develop these models of the human body, but it's tied to our services for a couple of reasons. One is, because the big pharma companies tend to buy software and they have internal groups of experts that are capable of using this kind of software. Smaller biotechs might want to be more nimble, might not want to invest in those types of things. So they would prefer us to have experts run our software and as you will, deliver the answer to them. So I look at it as you have to -- we have alternate means of delivery of the technology depending on the customer's particular circumstance. Now -- and we're not just biosimulation, it's -- because our customers are making significant regulatory decisions based -- significant decisions based on their drug development that will later come up in regulatory discussions, we need to be credible in our regulatory advice. So we added that to our company a number of years ago, and then in general, we also have an arm that is capable of doing regulatory filings because we find that a number of our customers, once we've worked on a biosimulation project for a number of years, they would -- I guess you could say, we have the inside track on getting the kind of regulatory work. So it's kind of a good service for our customers and a good way to magnify the work that we've done over the years on those projects. We've dipped our toes a little bit into some other things like market access. But in all of these cases, we have both software, and we have services groups. The services groups, the way we tend to think about this is, they work on cutting-edge projects and over time, what happens on those projects, we codify in software. So they are integrated, people move back and forth, and I think we've got a successful model there. Now our end markets in terms of our TAM are pretty large. The core market that we really need to focus on is biosimulation, which is about $2.8 billion. But if you look at the fact that we do participate in regulatory science and market access, it can add significantly to the TAM. But I'll just focus just for a second here on the biosimulation since that's what people are probably less familiar with. So the biosimulation TAM of about $2.8 billion is really consists of half software and half services. And you can see, within the software and services, the drug discovery and drug development kind of are the split. Now so our -- the bulk of our software is really in the drug development side there versus PBPK. Simcyp Simulator is our flagship product. We also have Phoenix and some other products as well there. But we've been expanding because we don't want to be just a point solution for a drug development company, we want to be someone that -- we want to be able to go in and capture a drug development project early, provide relevant products and then stay with that as they get bigger and provide the advice that they need. This just talks a little bit about the kind of a similar thing in terms of our strengths and how we built this up. Our repeat rate for software, about our renewal rate in the software is over 90%. It's actually quite rare for us to lose customers for any reason other than mergers or in the case of smaller companies, a drug that fails. Obviously, those happen and -- at some rate, but otherwise, most customers stay with us. We also have lots of academic institutions that work with us. It's kind of a part of our business model here that want us to -- we're playing on this long-term trend of increasing biosimulation. We want to make sure that people are trained, coming out of school using this. We spend a lot of time on training for both the industry and regulators as well, and so we're getting kind of a network effect there in terms of building this ecosystem. And the tech services, our repeat rate is 108% last year. our net repeat rate, excuse me, it was 108% last year. And the top 50 of our customers are basically -- have become customers for multiple products and services from us. We have a global footprint, as you might expect, given that we serve so many pharma clients. The bulk of our business and people are in North America. We've been expanding over the last couple of -- and we've been in Europe a long time, but we've been -- a couple of years ago, we were a little bit underweight there. So, we've been, over the last couple of years, building up there. And then we have a small, but rapidly growing business in Asia Pacific. We've been in Japan for a long time, and over the last couple of years, we've -- even through the pandemic, started to grow a very nice business in China. In China, we have multinationals that are there. We have Chinese companies that have drugs that they want to get approved outside. There's a lot of things going on there. It's very exciting, and hopefully, when we can actually go there a little bit more, we can even accelerate from that. In terms of our software, this is a little bit complicated. I talked about Simcyp earlier. We actually have about 15 software products within Certara that are targeted for different parts of drug development. For the purposes of this, I would say that the bulk -- the large sort of the flagship products we have in here at Simcyp, as I talked about Phoenix, which is used in pharmacokinetic modeling very widely in the industry. It's used by CROs, academics, most of the biotechs, most of the pharma companies out there. And then recently, we acquired a company called Pinnacle 21, which is the standard software for data validation to see this when you submit to the FDA or when you're transmitting data between CROs, for example, and pharma companies. We have a number of other ones that we've acquired over the years, and our strategy overall has been to: number one, increase the point solutions we can bring to the drug that are based on data and modeling; and number two, start to integrate these into a platform so that the data flows seamlessly from one to the other as the drug is going through development. So that's what we talk about our integral repository below which we're building there. This is a little bit about -- sometimes we get questions about what's the customer journey. Broadly, we have 2 segments, the large pharmaceutical companies and the biotechs. Large pharmaceutical companies have, from the beginning, viewed as a software company. They licensed biosimulation software from us and other types of software. And in a lot of cases, we do services work for them, too, because either they want something customized or we have the expert in whatever they particularly are looking at, at the time, so they want to bring that in. But generally, more software sales to them. Software sales tend to go by the number of scientists. And on the flip side, on the biotech, they tend to buy more services. Services tend to go by the drug project itself. So biotechs do buy some software, but really it's hard. In a lot of cases, this is hard for them. They don't have the large groups of people that are going to be stable and stay internally and really maximize the use of the software. So over the last couple of years since we went -- since I've been here and since we went public, we built up a pretty good arm to service that part of the market as well. In terms of -- we spent a significant amount in terms of R&D. If I look at how that works, we encourage -- we have about 350 scientists. We encourage all of them to publish. There are lots -- and I would expect in a given year, there'll be at least 150 scientific papers will come out of our group. Some of our scientists are among the most highly published slice of scientists that are out there. So we're very proud of that. It's not just for their own good, though. I mean that's -- we're marketing to the deep science part of pharma. So it's important for us to be cutting edge and to be in that conversation. We have a unique collaboration model in a lot of our software, which we call consortia. In this case, we have companies like minded companies join, and we work with them very closely on the models and on the software features themselves. The Simcyp Consortia is our -- the one that has been going on the longest for about 20 years. I don't believe any company has ever left that consortia for any reason other than a merger. So we have had a couple of our customers merge or something like that, but they drive a lot of value not because they get the software, but because every year, we launch a new version -- will be on Simcyp Version 22 this year like clockwork. In December, a new version will come out, and we'll have 6 or 7 new features. Those customers are highly involved in determining what we will pick each year. And that -- obviously, that benefits us since we have a known interest level when we invest in that. We have a proven growth strategy. We're an innovative company. So I direct a lot of our capital towards R&D and to the extent we do inorganics to thinking about how do we expand our innovative product portfolio. We've been -- as we've gotten bigger, we've been implementing what we call our land-and-expand strategy. So rather than be a set of point solutions that we go into a pharma company, we'd like to go in with a more integrated solution, and that's as we've gotten bigger in terms of our software and our services, we've been able to implement that. There's still plenty of room to expand there. The company has grown over 20 years. Well, with M&A, I think really most of that is over the last decade. Somebody said, "Wow, you guys did too much M&A." And I said, "Well, it take 10 years." So we have integrated these. They've all been successful. I've been here for 3 years. I think it's kind of remarkable. Everybody -- they've all been accretive, but I think strategically, they've been chosen well and some of them have really done very, very well in the company. We're expanding globally. So that's part of our growth story, but we need to be wherever pharma is. And the company is, as I tell our people, we are a company of people. We don't have inventories or warehouses or widgets or anything, right? It's a group of people. So we spend a lot of time thinking about why do you work here. It's not obviously people work because they get paid a competitive salary, but the best people can work anywhere. So there needs to be more. In our case, it's more around the fact that we have so many drug programs going on at any one time. You can see so much you can advance your career. And the fact that we're cutting edge in biosimulation really draws a lot of people in who have a lot of interest in this. You can switch back and forth between services and developing software, if you want. So -- and we've been -- we are fairly scattered around the world. We try to hire smart drug developers where we can find them. So that's helped us in the pandemic as everybody else went hybrid, we're kind of used to operating with lots of offices and lots of people all over the place. So it's stood us well during the last couple of years. I mentioned a little bit about our acquisitions. You can kind of see the timing of some of them. Our most recent one was Pinnacle 21, which is also our largest one. We closed it in October of last year. It's a software company, has a really excellent position in validation software and has really advanced our software capabilities. They're growing -- actually, they were -- they had a higher margin than us and a faster growth rate than us. So it's sort of accretive on every measure you get think of. And since we've gotten them, they've met all of their goals. So I've done a lot of acquisitions in my life and I know that they don't all go perfectly, but this is one of the ones that has definitely met our expectations. So we're very happy with what we've got there. In terms of our financial highlights, how would I think about this? It's an interesting company that we have predictable bookings. So we report bookings. And when we report bookings, sometimes we book multiyear things, but we don't want to report -- we report signed contracts that are going to execute over the next 12 months. We are generally -- we have visibility of about 85% on a go-forward basis at any given time. And so basically, there's -- as the company has grown, we have a big backlog. It's made -- it enables us to kind of smooth out the ups and downs as drug projects start, stop, get canceled or whatever because there is this big backlog going forward. We have really, really strong renewal rates. As I said, if you want biosimulation, we are a very, very good choice. and so our customers are rewarded with that. And our margins are good. We've run this company for -- as I said, we have a private equity -- we had several private equity owners before we went public. Our heritage is to grow a profitable business. It generates cash flow, and at the same time, to direct some of that towards investment in future opportunities. The long-term potential is good. The market is growing. We certainly haven't reached peak biosimulation by any means. There's still lots and lots of the industry that hasn't really quite digested what all the possibilities are we can do with this. And in our cases, we haven't even expanded biosimulation in all the therapeutic areas that we potentially could get into. In terms of our business models, generally in the software side, they are licenses. Mostly, the case, they are annual licenses. We are moving. We have a mixture between upfront licenses and like a SaaS model. Some of our -- there's a lot of different reasons. Some customers don't like SaaS software. Some solutions are not really quite appropriate for that. But generally, we've been moving more and more to a subscription base, and we will over time. Aggregate renewal rate of software you see is at least is always in the low 90s for a long time. Percentage of revenue, 30%. As we put Pinnacle in here, that will actually increase a little bit. So we've directed our M&A activity towards more software. On the tech-driven services, a lot of our clients have master services agreements, though we will put an agreement in place at the beginning of the year. Sometimes we're not entirely sure what the projects will be, but we know that they will -- they pretty much employ us all the time. It really depends how we charge on the project of the program, but generally, we are charging on project deliverables for that. Our net work repeat rate is 108%, and that includes sort of the price increases as well as new customers in there. So we're proud that we've -- as a newly public company, we got our inaugural ESG report out. We focus a lot on the fact that we are a company that's working to accelerate medicines through the system to patients. Our scientific leadership and the fact that we have a very diverse, engaged and highly educated employee base. Our leadership team, I won't go through all of this. I have our CFO sitting over here. We can talk at the breakout, Andrew Schemick. But we've got -- people came from a lot of background throughout CROs, pharma companies, software companies, modeling companies, it's kind of what you expect for kind of a company that's doing -- taking on some of what we're taking on. And then in terms of our investment highlights, I think I'll just summarize and say, we've got an attractive end market here. We are the technology leader in what we do. There's a significant barrier to entry to getting into biosimulation in the clinical phase, partly caused by the fact that it's a highly regulated industry and partly caused by the fact that the models are complicated. They need to be carefully validated by the industry and by the regulators. That takes a long, long time. Fortunately, we started a long, long time ago. So we've kind of gotten up that curve, but if you want to start from scratch right now, it would take quite an effort. We're pretty deeply embedded in our customers. Like I said, we've been around a lot of our customers for a long time. They -- we're always in the projects. We've got software that they depend on. There's still significant opportunities to expand that customer base. I mean it's great that we have lots of customers above $100,000, but I'm not sure why there's lots and lots of customers that should be over -- well over $1 million with us. So there's plenty of opportunity to expand the use of what we have. And we've got -- we're a disciplined company. We generate cash. When we do acquisitions, they've been successful, and we've been pretty discriminating, I think. And as a result, we've got 35% EBITDA margins, and a lot of that is a pretty good fraction of that is converted to free cash flow. So our covering analysts, you can see here. Thanks to John for the invitation today, and that concludes my talk. I look forward to meeting you some of you guys upstairs.

Excellent. Thanks, Bill. We're right at time. So that was great.