Okay. Good morning, everybody. Thank you for being here. I'm Dave Windley with Jefferies Healthcare Equity Research in the States. Cover the pharmaceutical services supply chain, and I like to think of it as services, technology, manufacturing, you know, kind of if you sell to pharma R&D, I'm interested. So we have here with us Certara and William Feehery, the company's CEO. Thank you for being here. Thanks, David. I think that I can't remember if this is your first time at this conference, or maybe first or second, but nonetheless, we're glad to have you here. Thank you very much. I wanted to start off, I want to get into the kind of guts of the business, but I did want to start off with your third quarter results and maybe more so the reaction that you saw since then and what, you know, were you surprised by that? I guess, what have been your conversations? It sounds like you've had a number of meetings with investors. What have been your conversations with investors, and what do you think perhaps the market is misunderstanding about where the company stands and what your near-term opportunities are? Yeah, great. All right, thanks. Good question to start off with there. Going into the, you know, going into the end of the third quarter and the beginning of the fourth quarter, we did see a slowdown in bookings, which I think has alarmed the market. You know, the estimates for our bookings that were out there were higher than we thought was reasonable, and we wanted to signal that. I think maybe the reaction was a little bit stronger than we thought. What I'd say about that is, you know, we still, what we saw there was we've got very good results with what we call tier three with biotechs. We've been very successful with our strategy of focusing on venture capital companies that have large portfolios of them, and that's been paying off. In our regulatory business, we did see actually fairly weak bookings in the third quarter, to be honest. That's a business which has been volatile for the last couple of years. It doesn't do that many transactions in a quarter, so, you know, what we see is that, you know, if they get delayed or if we miss one or two, it can really affect it in the quarter, and we did see that. Biosimulation bookings were a little bit soft, but not alarmingly so. Tier one clients, we saw a notable slowdown in the rate of closing. We don't believe we lost any business. We still have a very strong pipeline. It's just a question around when business is closing. The only thing I'll say is I think what we saw, someone has been interpreted as being different than what other companies have reported. My view is that a lot of the CROs saw similar things in the second and the third quarter. You know, at the end of the day, said more positive things about where fourth quarter is going. What I'd say about that is we've seen an increase in our closing rate as we've gone on in the fourth quarter. We have a very healthy pipeline. You know, I'd say we're not inconsistent with that either. Okay. I think you said the tier one, you know, so tier three, it sounds like was stronger. Tier one, I think you were talking about, is where you saw that slowdown in close rate. The improvement that you're highlighting in the fourth quarter is also in that tier one category, or is it more broad than that? Yeah, it is. So it's in tier one as well. We just, we have a lot of deals to close in every fourth quarter. This one's, you know, maybe a little bit more, you know, more intense as we go into the second, you know, the second half of that. But, you know, we have a good pipeline. We have seen some, you know, improvement in the closing rate. The other thing I'll just point out is, you know, we have a very, very, we don't really report on it, but I would say we have a very, very healthy backlog. At this current rate of closing, you know, we can maintain our business for quite a while. Got it. To kind of pause on the regulatory business, you've had that business under review and looking at taking some action there for about a year. The business, I think, in 2Q saw a little bit of, you know, maybe picked its head up a little bit and then reversed course. Anything you can, any color you can add in terms of what's going on in the environment or maybe specifically in the business? Yeah, look, we've had that business under strategic review for a year now. That's honestly longer than we thought that would happen. It's, I think, number one, the business has been volatile, and we see some of that. The other thing that's been not particularly helpful as we've been reviewing that business is the current disruption at the FDA has sort of caused questions around, you know, the short-term prospects around bookings and revenues on that business. You know, we're expecting that, you know, that will sort itself out as we go into 2026, but it is a factor as we've thought about that. You know, what we've said about this business is the same. It's a profitable business. It's not, we don't believe it's of the same strategic importance to the company as it once was. You know, bookings have been volatile and of a concern to a lot of investors for a long time. There are good reasons for the strategic review. You know, having said that, it's not a business where you just wind it up or give it away for free. It's got some value. You know, as we've kind of gone through this process and thinking about the process of price discovery, that's kind of where we hope to get some clarity soon, and we said we'll report by the end of the year. Yeah. Yeah. As a segue back into BioSim, I think one of the keys that you've highlighted to me in the past in terms of driving adoption of broader BioSim is to have pretty high-level regulatory experts in your organization to, for lack of a better phrase, handhold the clients through decisions around, you know, should we rely on biosimulation for this case or not. Do those high-level experts sit within this regulatory business, or are they? What's in this business is primarily medical writers. Most of our business, we call it onshore, but it's in North America or in Western Europe. It's kind of a high-end medical writing business that focuses on writing INDs and NDAs and other documents that would go to a regulator. It particularly does a lot of work in things like patient narratives and things like that. Yes, from, you know, one of the reasons we owned it was because we viewed that at the time it gave us credibility in regulatory. Right now, we feel pretty good about our position in biosimulation. We have a lot of regulatory experts that are not part of this business, that are not doing the actual writing, but providing the advice and providing the strategy around biosimulation in particular. That's why I said it's not of the same, you know, strategic importance to us that maybe it was when we bought it 10 years ago. Okay. That's helpful. Thank you. As promised, switching back to biosimulation and the point that you just made, which is very true that Certara sits in a pretty sizable leadership position in the area of biosimulation. It seems like an area that is a beneficiary of some of the, you know, efforts of the administration to push more streamlined and, you know, say, less animal-intensive approaches to drug development. How do you see, before I get into details around the quarter, how do you see some of that administration push percolating into your sales funnel? Yeah, great question. What you're referring to is the FDA leadership last, I guess, in the spring report, you know, pushed an initiative to reduce the number of animal, the amount of animal testing that's done. You know, we, in particular, they cited monoclonal antibodies, but then a desire to go beyond that over time. Our view of this is that this is a perfect example of what is actually possible today with modeling. Our QSP business has built up a significant amount of business about doing things like first-in-human dosing. What we found, for example, in our monoclonal antibody customers, they are doing that type of modeling work in parallel with all of the animal testing. They're doing the modeling work because we actually get better data out of what the first dose ought to be in humans than you would get from animals. They're doing the animal testing because the FDA has not yet put out the guidance of exactly how do you go to the FDA and not have animal testing. Good news is the technology's there. We're doing this type of work for a number of customers. When the FDA puts out this and makes it, you know, kind of lays out the regulatory guidance of the details of how you do this, it will be a benefit for Certara overall. This will expand. There's more that we can do as you go past monoclonal antibodies and you go into other areas where animals are used. You know, overall, we think it's a positive. Sure. You know, we're expecting more from the FDA in 2026. Got it. So that I'm not surprised by what you're describing, the running these approaches in parallel. Does that even predate these announcements by the administration? In other words, were clients already thinking this way? The thing about monoclonal antibodies is you're giving a non-human antibody. There have always been questions about the utility of some of that data. Yes, the general idea and the technology that we've developed with some of our customers does predate that. It certainly increased the, you know, the short-term interest just sort of as companies are thinking about the long-term strategy. You know, a lot of our customers believe the FDA will sort this out over the next year, but their drug developments are going to span the next seven, eight, nine years. They are thinking long-term about where they want to go here. Got it. Then coming back into a little bit the here and now, you have some of these broader tectonic shifts, but the current environment, a little challenging. In particular, the services bookings were softer. Maybe help me make sense of tier threes were stronger. They would typically, you know, lean into services, I think, because they are less able to do that stuff internally, but the services bookings were challenged. Yeah. I look at this in two ways. One is the tier three services were good and have been good all year. There's, I think that's a good sign for the prospects and the view of biosimulation because, you know, it used to be, you know, a few years ago, the smaller companies had never heard of biosimulation and never heard of us. As biosimulation has become more standard and expected, it's, you know, they're seeking that out. Now, we've also made a few changes in the way we've approached the market. You know, one of the problems for us with biotechs is there's just so many of them, just the marketing expense of finding them. There's a lot of churn in the market as well. They come and they go. Some of them obviously get big and successful. We've really focused a lot on the financial sponsors. We have a number of, you know, larger VCs and funds that basically become important customers for us. As they've had portfolios, it's made that part of the business sort of easier for us to find a stable base. We still find lots of other ones as well. In the tier ones, you know, we've got kind of multiple things going on in the services. We have a lot of them are buying our software. All of them have internal groups that do this. What you have is they bring us in for services for two reasons. One of them has to do specifically with the software. You want extensions to the software or you want some specific experts that only Certara has that wrote the models or wrote the software. The second piece of it, honestly, is, well, when they get busy, then they call us for help. It tends to be, you know, hard to turn down your best customers who need work. That we are kind of at the bottom of the cycle. As we look forward, you know, there have been a lot of layoffs in big pharma. At some point, they are going to get into the category, as they always do, where, you know, they do not have enough people and this will come back. That can come very quickly. Does not need, you know, we can see that come back very quickly. We have a very large backlog of work. A lot of our work goes on for years with pharma. That's why I said earlier in your first question, you know, we think that maybe we signaled a little, the market reaction was more than we intended to signal around where we really think we are right now. Got it. On that, keen on that bottom of the cycle point, a little bit of slowness in bookings. I think Certara has typically had pretty good pricing power. The products that you provide are pretty unique. How is the current pricing environment compared to, say, normal history? In this kind of environment, it's a little bit slower and weaker. Obviously, we exercise our pricing power less than we might otherwise. You know, we typically get, you know, mid-single-digit pricing increases on our software products. And we've continued to do that, you know, maybe a little bit tempered compared with when inflation was higher, you know, a year or two ago and things like that. Given the market environment, I'm more focused right now on growing the usage of biosimulation, the number of seats we can sell, the penetration in more types of drugs, and the sale of our new software than I am on just trying to eke out an extra 1% or 2% of price at the moment though. On that point about more types of drugs, the biologics capabilities in Simcyp are something that you've expanded. I think you expanded into large molecule capabilities, and then you kind of streamlined that to make it price-appropriate for that smaller customer. Well. A couple of years ago. Yeah. I think we're referring to, we launched some new versions of Simcyp. One of them we called Simcyp Discovery, which I guess confusingly is actually targeted towards preclinical. We're looking at people who have, you know, they're either going to go from discovery right into humans or if they have animal data, then translating that data into human data. It's targeted to that one preclinical field. That's a, you know, it's a narrow group of people. They don't need the full version of the software. They need a more targeted version at a different price point. The second one is Simcyp Biopharmaceuticals, which is targeted towards formulation scientists. There we're looking at, okay, we know that we're going to take the drug forward, but we're tailoring the formulation for whatever it is, absorption or something like that. It's a different group in pharma. Again, slightly different needs, different price point. It kind of goes along with our thinking about how we're going to expand biosimulation in pharma, right? If we were going to be limited to just the kind of our core, you know, uber users, which we love, then there are so many of them. As we can get into these other groups and we can make modeling more accessible to other parts of the drug development organizations that maybe are not going to go into the literature and write all these models, but they do want to use them and they want to understand them, they want to understand the implications, you can sell a lot more seats. This is kind of the trend that we're pursuing there. Another consistent with what you just described, another area where I think you're trying to push that is new, opens up new use cases is QSP. You acquired Applied Biomath, which I think is predominantly a service, was a service platform. Yeah. You are now evolving to an industrializable software offering in QSP. Right. So this was a strategy that we set out when we acquired Applied Biomath roughly, I don't think it was 18 months ago. I don't remember the exact date, but we and they had significant QSP groups. The QSP is a growing trend in biosimulation, particular, it is not limited to large molecules, but a lot of the questions in large molecules are addressed in QSP. So it's a growing, we know that's a growing trend. The technology is advancing pretty quickly in QSP as well. It is important for us to be in it. The reason why we bought Applied Biomath was not to create, not necessarily just to create a big services group, but it was because we saw an opportunity to create a standard software product in a market that doesn't have one right now. Kind of think about this in terms of what we did in Simcyp over the years, where we kind of created the standard PBPK product that's accepted by regulators and has a huge amount of support by modeling scientists across the industry. There's an opportunity to do that in QSP as well. I'm pleased to say we just did put out our first product. It's called Certara IQ, and that's the modeling platform that we believe can become the standard in QSP like we did with Simcyp. It's kind of too early for me to tell you. We've had lots of revenues in a couple of weeks, but I will tell you that there was, you know, a tremendous amount of interest at the conferences of the scientists where we've launched this. There's really nothing out there. People use MATLAB. People use Python, C. It's kind of all over the place. What that software does for us, for that business is, number one, it makes our quite large group of internal people much more productive. Number two is it makes us more able to resell models, right? We put out models in specific therapeutic areas, like for example, we've got them in immunogenicity. We have one in early development. We have things in radioligands, things like that. We can resell them much more easily. Number three, as you know, as companies go to the FDA as regulators, now it makes these models much more understandable to regulators, much more usable. You know, we have AI embedded in this product. You know, as you're looking at, you know, the FDA is interested in not just the model. They're interested in what's in the model. Where did you get it? What did you consider? What did you, maybe you considered and you discarded it? There is a large regulatory file that has to go along with any model that it also enables. That is why we think that this is a, you know, an important part for the company. I think it could be a really good product as we go forward. Should we think of Certara IQ and QSP as selling into a different and, I guess, earlier phase or selling into a different modality, like a large molecule or both? Where's the applicability in the early uptake? It tends to be, you can take QSP in a lot of directions because what you're doing is you're modeling how the drug actually interacts with the target. However, the business uptake that we're seeing tends to be in preclinical. It tends to be in large molecule because a lot of the questions that people are asking, they're not really PBPK. They're more questions around, for example, I'll give you an example. One, you know, we have a, we've developed an immunogenicity model, right? Now we're interested in basically how fast does the body produce antibody drug reaction to whatever protein you're giving. That affects dosing. It affects the populations you'll go into. It affects the selection of the molecule. That tends to be in preclinical. That's a specific question that really only exists mostly around large molecules. There's other ones like that too. While we're on relatively new products, so you're trying to evolve the software product portfolio into the cloud, single sign-on access, portal access. Phoenix Cloud, I think, is a second iteration of attempt on kind of cloudizing Phoenix. How is that effort, that broader effort of driving customers to your portal evolving? The portal's going well. All of our products have been migrated to work on the portal. That's really, I would call that kind of like phase one in our larger vision around pulling these products together in a platform structure so that we can deploy them at bigger scale across pharma. The first thing we had to do is get us all the products, you know, you sign on and they're starting to work together. The second phase is what we're doing as we go into 2026 around using AI to create the connectors between all of these things. You could actually deploy, for example, our discovery level products around ChemAxon and D360 along with Simcyp, for example. There's a bigger strategy, you know, the products I said we launched in Q3, that's certainly not the end of the story. We've got a lot of R&D that we've built up over the last two years or so that's starting to pay off there. How long, if there are multiple steps to this long-term evolution, what's your time horizon on deploying? First phase, talked about three products we just launched. I didn't talk about all of them, but we've launched three significant ones. They will, we expect to have, you know, an acceleration in revenue in software as we go into 2026 from them. They've all, they're not, you know, it's important as we go into big pharma. Obviously, we have to get in the capital cycle, but we will be in that as we go into 2026. We have additional products coming out. One of the things we, I'll just mention it, but you know, we bought ChemAxon last year. We have a product called D360 in discovery and we're creating them. We're basically going to launch a new version of that, which is designed to create a fourth platform for Certara. Right now we have Simcyp, Phoenix, Pinnacle 21, just about 80% of our software. We believe that this one's going to create a fourth one as we go into 2026 and 2027, for example. Okay. If I back away in the last minute, you have this environmental catalyst in the form of, one, just regular, just kind of well-known ROI pressure on R&D at pharma. Added to it, an administration in the U.S. that's saying we need to move away from certain ways of doing things and try to be faster and more streamlined and animal-friendly and a lot of things in that basket that would seem to push clients in your direction. The economic realities that they face being what they are, how do you overcome, you know, that hesitation to spend when your products would seem to offer significant efficiency and productivity enhancement? I think that the main problem right now in the pharma area, it's not that they won't spend, it's that we're kind of caught in the middle. For example, what we talked about in the animal testing, you know, the government's indicated what direction they want to go, but they haven't completed the next phase. It has caused some uncertainty about when will that happen. There are other uncertainties going on from a macro and pharma around what types of drugs, you know, will be favored or disfavored. That has caused the short-term kind of hesitancy in closing deals. That's what I think is really going on. I think we're not the only ones that have seen that. However, as you go forward, that is going to resolve itself. You know, there's tons of pressure for them to, you know, sort out a lot of these details. We have already seen some positive signs, you know, it is far away from us, but, you know, things like, you know, the new negotiations with pharma companies have kind of put some more certainty there, which is helpful. I think there will be more of that. As we go in the long run, you know, pharma is pretty inefficient. There are price pressures. It will drive even more interest in modeling, which is fundamentally, you know, more cost-effective than anything else you can do in pharma. If we can, which I believe we can, if we can change the probability that a drug makes it from discovery to approval by even a small amount, the amount that is available economically to us is pretty significant. Yeah. I appreciate that. Thank you for being here. Thanks to the audience for your attention and wish you a good conference. Thanks.