All right, folks. Thanks for joining us. Dave Wendley with Jeffries Healthcare Equity Research. We're here at Jeffries' 2026 Global Healthcare Conference. And on the Wednesday afternoon, I'm glad to be joined by Sertara and the team's John. John Resnick, newly joined, recently joined CEO, and John Gallagher, the company's CFO. So thanks very much for being here. Glad to to see you and great to have you. John Resnick, I wanted to start us off with a question on the realignment of the company, which I thought was interesting and, you know, maybe intuitive for a guy like me after the fact, but I might not have thought of it myself. So talk about your MID3 and your ACE, I think you're calling it, realignment of the segments and what implications
that has. Okay, well, thank you, Dave, for having us here today. It's great to, it's great to be with you. So, you know, organizationally, we did announce some changes. It's been a pretty active first few months within Sertara. I started January 1st. We've been very focused strategically on how we set ourselves up for broader growth opportunities. So, I spent a lot of time talking the customers around what's on top of their mind to regulators in terms of trends and growth trajectory, and then did a fair amount of work with our internal teams trying to understand where some of the distinctive opportunities exist. So in essence, our mission within the company is to disrupt clinical trials or transform clinical trials, clinical development for good. And so what we wanted to set up around was kind of two, these two kind of strategic growth engines that would provide a fair amount of runway to, you know, to get going. So the first one is ACE. ACE is around accelerating clinical evidence. And if we look at both the EMA and the FDA and we look, you know, very squarely at what our clients are struggling with, it's how do they manage data from protocol to submission? How do they improve efficiency? How can they unlock data quicker? you know with our Phoenix and our pinnacle assets and co-author and global submit we have a range of things that are already there in play we're looking at a range of other transformative things that can help accelerate it MID3 is a thing that we're probably best known for which is model informed drug development and through this we call out discovery as well which is an area where we've made significant investment and we think opportunity for growth you know to simplify, MID3 is really around kind of transforming the way clinical development is done. It's moving away from traditional approaches and using computational biology and bio simulation to accelerate the rate and pace of execution.
So on the, maybe you could help distinguish for me because for the time that I've known the company, Phoenix and SimSip get talked about as pretty close, you know, brothers or sisters. Yeah. but you're calling Phoenix more of a evidence asset and not a modeling asset, maybe distinguish for me?
Yeah, it's a well studied question. So Phoenix actually has two components to it. It's got a piece which is a computational engine, which is very tied to kind of PBPK analysis. I'm sorry, PK PD analysis, POPPK, which is a computational engine. It also has a broader application suite, which has more to do with data management and computational mechanics. So it actually plays both those apps. So we are going to be linking the POPPK scientists and those teams more directly with one application, but the bulk of the Phoenix customers will be, you know, working through the data management side.
Got it. Okay.
But from a client standpoint, look, these are two growth engines for us. We also have taken steps to ensure that, you know, if you're a smaller company or a mid-sized company, you're looking more broadly to transform. These aren't two independent threads. These are two engagement paths, but we can look holistically.
So it wasn't that far off. It does have a leg in both buckets, it sounds like.
Yeah, it has two distinct applications.
And then from an alignment standpoint, maybe we could drill into this a little bit on kind of an operational vector and a sales vector. So operationally first, does much change in terms of you've aligned these businesses into these two categories? How much operationally changes as a result?
There's, look, historically this has been spread out among a number of different groups. My biggest objective and goal was creating clarity, strategic growth, and accountability. So this should dramatically simplify our operations over time. There's some real realignment of our go-to-market teams so that there could be more specialty led engagement. There should be more subject matter expert or scientist engagement directly with our clients who are looking for that type of engagement as opposed to general engagement. And from an operating flow standpoint, there should be a range of kind of simplification. We're going directly to the businesses to talk about everything from, you know, sales execution to, you know, to thought leadership and innovation to delivery execution. So there's much more clarity internally. There's a little bit of change, a little bit of shift that happens any time you move an organization around. That creates a little bit of dust. But we're, you know, certainly focused on how can we drive, you know, mid-term, you know, significant growth in this business. And this should position us better for that.
And we view it, just to add on to that, too, we view it as an opportunity to unify some of our disparate operations. So we were able to take this as a chance to unify, which is also sort of the backbone of some of the operating metrics that we've been looking at that are going to help drive growth for the organization as we look toward the second half of this year.
Got it. Okay. I'm going to hold that. I'm going to placeholder on that, John. I may come back to that. On the sales alignment, John Resnick, you touched on this. Maybe let's drill in on that a little bit more and help us to understand, in your efforts, you know, the goal to stimulate midterm growth. Do you think of that as new logos, new users within current accounts, same people but using more products? You know, this is a kind of an esoteric space for a lot of us, and we don't understand exactly how biosimulation works and who does it. So help us understand how you get more people to use your products.
Yeah. It's a thread of a question you've asked me a couple times. Yes, yes, yes, yes. So, look, there's a $230 billion addressable clinical trial market. It's a massive number. And if we think about the way clinical programs have been run, it hasn't fundamentally changed that much over the, you know, over the decades. You know, we see huge tailwinds coming from regulators in terms of their openness to new approaches. You know, we've seen things like drug-to-drug interaction and kind of dosing optimization become pretty standard in the PACs for biosimulation. We see significant opportunity to expand beyond things like drug-to-drug interaction and move into pediatrics and pregnancy and lactation and organ impairment, et cetera, there's lots of new applications that regulators are certainly open to, and we're partnering with regulators around shaping. To your specific question about how do we drive this, I think one of the key things here is going to be scientific to scientific engagement. You know, when we lose, we don't necessarily lose to competitors. We don't necessarily lose on price. we lose because our clients opt to do traditional approaches. So for us, this highest single indicator of success is can I get our, or can we get, I should say, our scientists out directly engaged with the decision makers across different companies. And through our realignment, can we have those strategic conversations in a way in which the client brings the problem and I'll take the MID3 example. We now have our POPPK teams, our QSP teams, and our PBPK, all of our initials in one spot, and our technology in one spot where we can say, look, there are multiple ways to help you. So we believe that it should lead to new use cases. We believe that it should eventually lead to handoffs within our organization to bring new offerings within those new logos and new opportunities as we continue to drive regulatory innovation.
and and so practically speaking does that show up as you put these scientists together in a room and a client clinical pharmacologist has an aha moment that they have they've known simsip and they're using simsip but if i if i staple on from this kind of my layman's terms but if i if i staple on something qsp or if i use your qsp consulting that complements what i was already doing is i'm trying to bring to life how these conversations evolve yeah so depending on the product depending
on the you know the therapeutic area depending on the situation they're facing their needs may change and you know where our scientists were distributed throughout the organization they had different kind of go-to-market cycles this will allow us to go in and engage directly on what's the challenges you're facing as you move forward the problem might be a pbpk problem it might be something that's more of a, you know, a POPPK question or a QSP question, there are different disciplines that now working together will be able to drive it. We're also, from an incentive standpoint, remove the barriers which would keep the technology working independently and the services independently, and we're now playing to much more of a fly wheel effect where the scientists and the technologists will be working together hand in hand. So, yes, it's going to be a client, you know, what is your number one challenge and then And how do we bring the best of Sertara to ensure that we provide you, whether it's a technology product or a service product or a different model, the best answer to meet your challenge?
John Galler, coming back to you as promised, you've talked on the call about cost avoidance, cost outs or cost avoidance. And you mentioned a minute ago this unifying disparate operations, which sound like those things could intersect. Can you elaborate on that a little bit?
Yeah, one of the important things we want to do is keep the investment in R&D that we've talked about and you saw show up in our Q1 expense numbers intact while we simultaneously get some cost out of the organization. So to your point, Dave, we continue to go after about $10 million of cost out, and we believe that we can make the investment in R&D and take that cost out, mainly through some of the efforts that we're trying to find efficiencies in the organization. That might be in the cost of sales, certainly in G&A. We've looked at sales and marketing. We've certainly had a lot of spend increase in sales and marketing over the last few years, and we see that more growing at the rate of sales at this point. So there is opportunity as we look at operating efficiencies and we look at commercial go-to-market and execution changes. What comes with that is some unification of some of the back office functions.
Okay. Let's talk about AI a little bit. So it's a big question. It's a kind of existential threat concern in investors' minds for some, at least. It seems to me that, you know, through the consortia that you work with, the history of the company, you have some access to and and ownership of some pretty deep and valuable data assets that are, you know, supposedly the lifeblood for what AI needs to run on. How do you see Sertara, you know, contributing to, benefiting from, operating in this kind of post-AI new world? So I think firstly, we agree with you
in terms of, like, the frontier models are going to be excellent in terms of creating reasoning and logic, there is a whole lot of work that needs to be done within the vertical stack around, you know, the actual last mile of execution. And Sertara's capabilities, data in part, but also, you know, two-sided, you know, market penetration, workflow, embeddedness, you know, thousands of publications that we've done over time, domain expertise, you know, the ability to make the connection between the scientists and experts all provide a very unique position to help reinforce that vertical stack. So we're incredibly focused on not only enhancing things that we have today, existing products that we have in terms of creating new modules and accelerating what we do to embed AI capabilities, But also thinking more broadly about native AI products and how we play into this kind of frontier ecosystem, whether it's through unification of our core products or through gentrification and APIs into broader work. We believe that there's a range of options open to us, and we're strategically pursuing a few of them.
Okay. You hit there at the end on where I wanted to go next, which is more specifically how AI kind of infiltrates your business model. We had a conversation with a quantitative sciences person at a pharma not too long ago that really offered that using AI to, say, replicate a SIMSIP didn't make a lot of sense. and instead AI to perhaps organize the data or visualize the data on the back end, you know, the output on the back end was more likely to be value added to what existed. I guess, you know, does that comport with how you think about the world? Where does AI add quick value, I guess I'll call it?
Yeah, it's definitely consistent with the way we're looking at things i think in the last earnings call i told the story of simsip certification with uh with it with the ema you know it was a two-year journey it's not only getting approval or certification through the ema you actually had to work with 25 member countries you had to walk through 20 years of history so the execution model attached to it is not easily attainable. There's an awful lot of work. So I agree with that individual's assessment that it would be tough to replicate and I think it'd be inefficient for anyone to replicate. You know, I think where we're focused and where clients are asking us to go is how do we take that know-how on the regulatory end of things and help to leverage that and unify it into other things that we're doing to help inform other decision-making and other decision points along that chain. So how do we take the know-how that we have at the point of regulatory submission and inject that, you know, earlier and earlier into the lifecycle so that we can help optimize the assets that are being developed?
Got it. You also touched on one of your, in your prior answer about identifying product areas. So one of the early ones, the company acquired Vyasa, brought in some AI capabilities, I think quickly developed co-author, which, you know, that's something I can actually, I think most of us can wrap our heads around. I'm like, I can ask AI to write me a document or write me the draft of a document. That one I can understand. What other product area, you know, kind of dirt up, ground up product creation with AI do you anticipate or are you looking at?
Yeah, and that's going to become a harder and harder question to answer because it's very difficult to increasingly delineate between products that have and don't have AI capability because it's being injected into everything we do. So to answer your question around kind of native AI products, we have Sertar IQ, which we've talked about a lot, which is in the QSP space. We have Codex, which is a data component that we're using. We have D360, which is being re-platformed. We have some cloud-based initiatives that are kind of native AI. Our existing products have, you know, like most software organizations, we've completely rethought the way we're building and engineering products. We've got huge acceleration in our roadmaps and huge acceleration in our software development. So Phoenix, as an example, has built a whole range of reporting capability, which is in our cloud version, which is AI-centric. So increasingly it's going to get harder and harder to pinpoint because it's being injected into everything we do. I think where you're going with it beyond the near term is also where does this go long term? And that's the existing play. The Vyasa acquisition has been incredibly good in creating that entrepreneurial kind of AI-first mindset within the organization. We have asked them, and we formally announced that Dr. Chris Batam was named the chief AI officer in the last earnings call. His mandate is not only to kind of transform the organization around kind of the AI-native approach and more of his agile entrepreneurship, but also to work on what is kind of the biggest initiative we have, which is this kind of unifying asset that will allow our software products and our technology products to communicate with each other at the data layer more holistically. So tangible example, you mentioned SimSep before. SimSep, which has this regulatory kind of great power for submissions. How do we get earlier indications into discovery? So how you're making gate decisions whether to fund a product or not fund a product? Do we get inputs from the PBPK analysis into things like Camaxone? So Chris is heading up an initiative that will be what's looking specifically at how do you optimize and unify across the data layer of our underlying
technology products interesting okay let's move uh move into more typical questions on demand how would you characterize what you're seeing from customers in the market and perhaps you know if
they're different across tiers highlight that yeah i mean look the overall end markets are in uh are in good shape right the biotech funding environment with the exception of a little blip we saw yesterday has been positive. So that's a tailwind. The overall spend environment by Big Pharma, we think, is also in a good spot. We have seen volatility in our results, right? We've seen software down in Q4, up in Q1, and vice versa with services. So the look through on that is really to focus on TTM so you got to look at trailing 12 months bookings and that gives you a better sense of you know where are we seeing stabilization and where would we expect to see some acceleration on the acceleration side of course you know through our q1 results we saw an increase in TTM software and And you saw that show up also on the revenue line with a 7% revenue growth in software in Q1, which was above our expectations and now has us thinking that the plan for the year is a bit better in software, as we said on the Q1 call. On services, on the other hand, when you look at the TTM bookings on services, even though there's been a lot of volatility, when you look at Q4, way up, Q1 was down, the look through on that is is low single digits and we said that there'd be some some choppiness in the first half of the year on on services and you know the way that we look at the plan right now it continues to be playing out in line with our expectations okay john resnick on the so you've
you've focused the sales force instead of having one overarching sales force you're pushing sales into the two segments that we talked about earlier, what indicators are you looking at to show that that change is driving traction short of the bookings that you're going to tell us, and are you seeing movement in those indicators?
So there's two metrics that I have the team predominantly focused on. One is ARR on software, which will be a much better predictor, which is something we're working on as a team to be able to provide externally is kind of a future indicator of where we are. So I've got the team focused on new software and new software sales. We've changed the incentive structure to reinforce this. And Q1, obviously, was a super strong result on that side of things. We have continued momentum on that side. So that's been not beneficial. And we have rallying cries daily, weekly, around that metric. with internal targets around where we'd like to be by the end of the year. On the services side, you know, our focus is going back to a little bit of basics around kind of opportunity generation and pipeline generation. So we've, you know, flipped it around, both broke the disincentives for teams, you know, across teams to work together, and, you know, secondly, have put a handful of programs in place to get the scientific teams back into market and directly engaging with subject matter experts from peer-to-peer level. My dominant focus on that right now is pipeline generation and opportunity assessment, which is where not a metric that we provide externally, but we're extremely pleased with what we've seen over the last six weeks since we've started to roll that out. That won't be an immediate result. That's not a Q2 impact going back to opportunity generation, but it's the kind of thing that will lead to long-term sustained growth, and we'll maintain our focus on that side of things.
On the call, on this last topic, on the call, you, I think, highlighted, in general terms, some execution challenges that led to softer services bookings in 1Q. Can you describe what those were or what you've alleviated there?
Yeah, I can, and we're still, you know, these things don't get done overnight. They're, you know, they're cultural. And I, you know, I kind of joke, it's always difficult, it's always easy to come into a company and to kind of point out things that are changed, you know, that you would have done differently. Look, I think kind of akin to what you said before, which is we broke unintentionally a lot of that pair-to-pair engagement from scientist to scientist, what leads to that innovation, what leads to that growth. we launched a commercial model and kind of shifted commercial function and shifted responsibility for sales to that function alone. So you had a sales side, a demand generation, and a delivery side. I've been around here for a few decades now and I've seen that model doesn't work long term. So what we've done is we've asked the business leaders, again, to get directly involved in opportunity generation, have equal accountability to the commercial team for that generation. We've got the scientists directly involved and are increasingly rolling out models that incentivize and encourage them to talk to clients and to work directly with their peers and folks they got their PhDs with and folks they see at conferences, which will help to kind of neutralize that. And also some of the incentive programs themselves were making sure that those are market standard and reward the behaviors that we want to see. and you know to get in front of your next question the stuff doesn't happen in a day or a week it takes a couple quarters to burn through but we're really happy with what we're seeing so far good
fantastic let's topically let's move to kind of molecular modality I suppose so small molecule large molecule pipeline is clearly moving toward large molecule there's a bunch of similar launches coming out as well how do you view the the product portfolio to be positioned as the pipeline you know shifts to a more dominant large molecule environment so you asked this to
me in the last call and i didn't have my answer so i am ready for your answer excellent so uh look i i think the historical perception that sartar was a small molecule i think is less relevant today. It's hard to kind of pull apart definitively, but roughly speaking, about 60% of our business is small molecule, about 40% is large molecule. We have a range of products which are pretty agnostic to small or large, the Phoenixes and the Pinnacles, and that suite of things are completely independent. SIMSIP, which historically you would think of as a The small molecule is probably 30 percent large molecule today, 70 percent small molecule. Things like QSP, which is something we've talked a lot about, is a new emerging, you know, regulatory area and scientific discipline is almost exclusively, if not exclusively, a biologic area. Things like D360 and camaxone also have had a lot of innovation and have now, you know, certainly much more large molecule focused, you know, the change in things like monoclonal antibodies and ADC's also has opened up, you know, a biologic is not a biologic. So there's, you know, clear opportunities for us to, you know, to execute and change modules and already have built functionality to address some of that peptides, nucleotides.
Got it. Super. In terms of regulatory environment, guidance in March, FDA guidance in March is encouraging faster biosimilar development through a number of mechanisms. including analytical modeling approaches that seem like they point in your direction um are you seeing
any engagement around that we are uh look the you know since i've joined it's announcement after announcement literally plays into certara's strengths right you know whether they're industry setting bodies ema fda announcement after announcement is really encouraging and incentivizing increased, you know, adoption of these mechanisms. What we've noted over the last, you know, couple of months and years as the regulatory stance becomes clear is the frequency and the volume of inbound requests. There's always a little bit of a lag between inbound requests and people, you know, changing the way that they're doing studies that they've always done. We outlined a little earlier all the areas from NAMS to, you know, to pregnancy to pediatric where we see incremental opportunities uh you know we think uh you know as you as you move forward the demand for this is only going to increase i think us getting our scientists back in front of customers and kind of leading that direct peer-to-peer engagement is going to be critical in faster adoption as well as direct continued leadership and engagement with regulatory bodies
I'm going to wrap here, coming back to you, John Gallagher, on operating costs. We touched on this a little bit. You started that answer with we want to keep our R&D, you know, budget R&D commitment in place. I think we sized that at about 10% to 11% of sales now. Should we think of that as a percent of sales type commitment, and is that the right range to think about?
Yeah, that range is in the right spot, because if you think about it, yes, we're putting investment there, but we're also finding efficiencies. We talked about AI. AI can be used within our teams, not only within the R&D team, but in the finance team, the HR team, the IT team. So we do believe we can find some productivity using AI tools ourselves as a partial offset to some of the investment that we've been putting into the R&D line item. So I think what you described as 10% or 11% of sales is a good placeholder when we look at this year.
Okay, and then conceptually, John Resnick, the innovation for Sertara has come through both R&D investment but also acquisition of capabilities. Sertara has been pretty acquisitive. Is that a path that we should expect to continue?
That's not the near-term priority. The return priority is around getting the organic investment clean. I mean, I think, as John noted, we've seen significant increase in our investment over the last couple of years. You know, the question I had coming in here is where's the return? So we put a lot more discipline into the process, and we expect to get a lot more return. I've outlined a number of those concepts. There are a range of other ideas we haven't got into today or things that we're moving forward. So we think there's plenty of organic space to run. If something made sense, which was, you know, an opportunity to accelerate, you know, a near adjacent market or to do something, we wouldn't not do it. But it's not the priority. The priority is getting our, you know, our team cranking and as much return as we can possibly off the investments we already have.
Excellent. That brings us to time. Thanks to the audience for your attention and attendance at the conference. And I hope you have a good rest of the conference. Thank you, Dave.