Okay. Welcome everybody. My name is Stan Berenshteyn. I cover digital health at Wells Fargo. With me today is Shawn O'Connor. He's the CEO of Simulations Plus. How are you?
I'm doing great, Stan. Thanks for the invite.
Yeah, absolutely. Happy you can make it. So before we begin, for those less familiar with the story, can you just give us a brief overview of what Simulations Plus does, what end markets it serves, and ultimately how does it help clients succeed?
No, absolutely. We, at Simulations Plus, celebrate our 30th year of existence, this coming calendar year, and have been, in, the world of modeling and simulation in support of drug development, through our lifetime. Modeling and simulation in support of drug development, what does that mean? Boy, you know, AI today is the buzzword that gets everyone's attention. Our first product, back in the mid-1990s, was a ADMET Predictor, a product that's used in discovery based upon machine learning developed algorithms to predict characteristics of molecules that have never been synthesized before. Modeling and simulation in support of drug development means a lot of things. It is not one tool, one approach.
It's a number of approaches that basically use a combination of the sciences of computer science, mathematics, and statistics, along with the sciences of chemistry, physics, and biology to develop algorithms, predictive techniques, models of drugs, models of biological processes, that allow our drug sponsors, our clients, to do a number of things and affect a number of decisions, beginning in early discovery, when you're searching and prioritizing lead optimization of molecules that you wanna take to the clinic to molecular drug candidates, in preclinical studies, fashioning plans in terms of animal testing, taking it into the clinic, through the human clinical trial process, formulations, manufacturing components of those drugs, all the way through to drug approval, and even beyond, post-approval in terms of changes to formulations and other decisions that might be relevant afterwards.
So, this drug development process that on average is a 10-12-year cycle to develop a drug, a $1 billion-$2 billion price tag in terms of developing that drug, we are positioned to help our clients make better decisions, make the process more efficient, leading to more targeted investment in drug programs that have more likely success criteria and moving through this long process in a more efficient, targeted way. The drug industry today, the development process, is unfortunately achieving less ROI than it ever has in terms of our large pharma clients. Their investment in R&D spend is not producing the outcomes at the rate they have in the past.
While we may get into dynamics in terms of the industry, cost constraints, reduced funding, underlying all of those challenges that they face is the basic problem of today, a business model that in the past allowed for sporadic large blockbuster drug discoveries to pay for a relatively inefficient process to deliver those drugs. The blockbuster opportunities are few and far between, more scarce. They need to develop a more targeted development program, more efficient, to deliver approved drugs at the end of the day that may have smaller market sizes than those that they've enjoyed in the past. Changing and retooling their drug development process is high on their need list. We at Simulations Plus are one of those methodologies that allow them to achieve those objectives.
So I think that's a great lead-in to my next question, which is you I think a year ago you acquired a company called Pro-ficiency. I think, based on what I've read, it doubled your TAM from $4 billion to $8 billion. Can you just walk us through where your TAM was, what you were addressing, and what this opens up for an opportunity for you?
Yeah, absolutely. We have, to date, prior to the acquisition, focused all of our efforts in the biosimulation market, a market of using tools, modeling and simulation capabilities, in support of the drug development process. Our reach into clinical operations with the acquisition of Pro-ficiency was an opportunity for us to expand, increase our opportunity, and very targeted in terms of our acquisition in the clinical operations space, which is ripe for the adoption of new technologies and modernization, quite frankly, in a very complex process of translating a protocol, a game plan for a clinical trial, and efficiently undertaking it to a positive outcome. Our theme in terms of the acquisition was predictive analytics, and our acquisition of Pro-ficiency brought a platform into our portfolio that is displacing an old approach in terms of translating and training sites on the protocol.
The number one citation from the FDA at the end of the clinical trial is lack of adherence to the protocol, which disrupts and adds cost to the clinical trial, and most importantly, screws up, to use the technical term, the statistical outcome of that clinical trial. Either lack of adherence leads to recruiting more patients and increasing the time and cost of the clinical trial, or it disrupts the statistical analysis that allows for an approval by the FDA based upon the results of the clinical trial. Pro-ficiency's platform allows the drug sponsor to A, train the sites and the participants in the clinical trial in a more sophisticated fashion, not a PowerPoint presentation that the participants walk away with a hope that they retained it, but a more interactive training process.
Secondly, most importantly, tracks the performance of those taking the training and allows the drug sponsor to anticipate where which sites are more likely than not to adhere to the protocol and either reinforce training to improve that site or redirect patient recruitment to other sites that are more likely to adhere to that protocol. Using predictive analytics to allow drug sponsors to prevent problems from happening was the key strategic component of the Pro-ficiency acquisition.
So, training usually, I think, typically comes bundled with, you know, CTMS software and, you know, companies that dabble in that space would be like Medidata and Veeva. Is that who you compete against? And why would somebody go with, I guess, a standalone product versus what they're offering?
Yeah, the primary competitors are PowerPoint presentations, quite frankly, either provided by the CROs that are undertaking that clinical trial, or an abundance of small third-party training organizations. There are solutions that sit in the hands of Medidata, Veeva, and those players. But they represent relatively small market share in that space, at this point in time. You know, our solution is unique in the content of its training as well as in its tracking and management capabilities in the hands of the drug sponsor.
Okay. And in your core offering, you mentioned, you know, you do biosimulation. Can you just make a distinction between what is the difference between biosimulation versus what I think a lot of people have been focused on recently, which is AI-led drug discovery or?
Mm-hmm.
Identifying certain candidates for drugs using AI? What's the difference between what you do versus what that?
Yeah. No, fair enough. I mean, AI is a tool. It's a tool that allows for the search, the interrogation, of data, that data accumulation is critical to the developing of models. We've used it in the past from its early days. Certainly, a wave of capital investment in drug discovery applications of AI and the development thereof probably began two, three years ago. The Atomwises of the world, Valo Health, BenevolentAI, long list of entities that targeted how can we identify molecular structures through the use of these data management capabilities and search and find the identification of biomarkers, all focused on the lead optimization process. What, what molecules should we take into the clinic? Our coverage in that space rep is represented by our ADMET Predictor product, which I mentioned earlier. Yeah, boy, certainly a lot of upfront competitive concern expressed.
But you know, these companies, years forward since their initial investments, some have made some progress and some have developed some candidates that are moving into the clinic. Some of them have gone by the wayside. The tool is one thing. The knowledge, the science, the biology, chemistry, and physics is another, and as these entities focused in on developing these tools, they by necessity got very focused in terms of specific targets, specific therapeutic areas, and today most of them have not become competitors to Simulations Plus. None have, really. They've become customers of Simulations Plus. They've become drug companies. By necessity, the payback on the capital investment there, a drug success is necessary to pay back the capital they've taken on, and what really distinct and as they've matured, they have become ADMET Predictor license holders, customers of Simulations Plus.
And as they've matured into the clinic, they've become customers of our other biosimulation tools. So, you know, I see them as, you know, early discovery companies and, not competitors, in the marketplace. And, our customer list includes many of them, today.
Okay. I wanna talk about, you know, more recently, pertaining to revenue and market demand. So I think you've seen some reduction in your expectations versus where they were at the start of the year. Can you just walk us through what you're seeing, related to the end market and how that's translating into top-line growth for you?
Yeah. Oh, absolutely. Boy, the industry, it's not a recent phenomenon. Last couple three years, really, you know, the cost constraint has been the buzzword in large pharma, lack of funding in the biotech world. These challenges have tightened their belts. Biosimulation, a market that has historically grown at a 15% CAGR, fell below that over the last couple of three years. We've executed well in that environment and organically have grown 10% the last couple of years. As we entered our fiscal year 2025, which is with an August year-end, it ended last Friday. The budgeting process last year seemed to be going relatively well. I think our industry, the drug development industry, handles known issues of you know, patent expiration and the challenges that existed before the year. They don't respond well to surprises.
And as they entered the calendar year of 2025, their budgets looked not robust. I wouldn't have labeled them robust, but pretty firm and positioned to allow us to continue executing to a 10% growth. Tariffs, Most Favored Nation and pricing, FDA reductions, a whole host of new surprises came to them in the early part of the calendar year of 2025. Our third quarter was impacted by that. We saw our clients' pipeline activity still very robust and active, but a lot of bottleneck at that end point of project proposal, agreed to contract, negotiated, how about a signature? A lot of staleness at that last step, so bookings were down in the third quarter. Number of delays in terms of projects, clients pushing off, managing their budgets. Let's hold off till next quarter to do that.
And significantly, we had a project cancellation. A client with relatively material contract value, scheduled to be performed in revenue for us in the back half of the year, got bad readouts on the two programs under the contract and canceled those programs. It happens. Delays happen, but all of this came together in the third quarter and impacted revenue mess and guidance adjustment. Our business is about 60% software licensing and about 40% consulting services. The software side of our business relatively not impacted. This is an infrastructure acquisition on the part of our clients, building their internal capabilities. And while they've tightened their belt and maybe aren't growing those departments as fast, they're not shedding modelers. And so our software license side of our business is doing quite well.
The consulting side of the business is the area in the budget of modeling departments that they have some flexibility on in terms of opening up the purchasing cycle, or slowing it down. And we've certainly been impacted by that. You know, that carries forward into the fourth quarter in terms of a lower backlog. But anticipate that these new factors that came to the table in 2025 will be part of their budgeting cycle for 2026. And we'll get back to a more steady flow of project requests and project signatures, etc., into our fiscal year 2026, which began this week. You know, the market, will it get back to 15% growth? Hey, some of these dynamics do have to change.
But our ability to execute to a 10% organic growth, as we have done in this sort of environment for the last couple of three years. We fully expect our ability to get back on track when that week.
Okay. You mentioned some idiosyncrasies related to a canceled project, but if you think about broadly across your customer base, you're saying software is steady. Can you just comment on the renewal rates? Do you expect that to stabilize, you know, excluding this, this client departure here, and how should we think about the next fiscal year?
Yeah, and that client cancellation impacted the service side, not the software side of the business. Our renewal rates run at a pretty consistent 90% plus level. It impacts the differential there, who doesn't renew, companies that go bankrupt, and consolidations, acquisitions within our client base. Client A acquires client B, and they rationalize sites or organization in some fashion. And so if you look back over time, our 90% fluctuates, but you know, I mean, trailing 12 months or you know, and our expectation going forward, that 90% holds pretty firm, traditionally. And you know, the software side of our business is our focus. We're pretty committed to that 60/40 split in terms of software and services, as a result of the benefits, not only in terms of stability and recurring nature and margin.
Service will always be part of our business. Our clients expect us to be able to undertake their capacity needs when required. Our involvement on the service side doing this work provides great input into our software development programs on a go-forward basis. Very important piece of the business, but we're very focused on keeping the software side at 60% and growing that as a percentage of our total revenues over time.
Okay. And you did mention a few headwinds related to tariffs, cuts at the FDA. I wanted to ask you about some tailwinds. So, you know, one of the things that has happened over the past couple of years is the FDA is moving away directionally from animal models. You are in the business of doing simulations. Can you just talk about how that has been a tailwind or potentially an improving tailwind for you going forward?
Yeah. No, absolutely. A very positive announcement by the FDA in its regard to biosimulation. And yet another example of biosimulation's growth has been underpinned by a series and continuous expansion of the use cases of biosimulation. I'll compare it to several years ago. The change in a formulation of a drug would, in the old way, require a clinical trial to test that new formulation of the drug. The FDA came out and said, "Hey, you know, we believe the reliability of the technology, the predictive analytics, in this area was sufficient that we wanna eliminate having to go back to clinical trial for formulation changes." After a period of study and defining the bar that one had to get over, today bioequivalence waivers for formulation changes are pretty common.
An area that relies upon biosimulation to achieve those waivers, which eliminated a costly and time-consuming clinical trial process. The animal testing announcement similar sort of situation. Now everyone sees an announcement like that, and it's an oil tanker industry. It takes a while for change to take place. This will develop over time and become a great use case for biosimulation in the future. We're very active in that area already. Our tools and techniques are used in the evaluation of early stage drug candidates, in defining the protocols for animal testing. They're used in order to minimize patient populations animal testing populations. GastroPlus has a dozen different animal species models in the platform to do those sorts of evaluations. The bar has now been raised.
The bar previously was, how do we make these animal tests most efficient and, you know, lower cost and quicker timeframes? That bar is now, what's the threshold we have to get to in order to eliminate animal testing? A lot of debate, scientifically, is that a bar that can be achieved. Is the answer going to be complete elimination of animal testing, or will it be some combination of biosimulation and reduced footprint of animal testing? This is the process the FDA and industry is going through right now. Typically takes a year, or more, then takes some trial programs to be evaluated before it can become mainstream. So, yet another example, a great example of what underpins the ongoing runway of growth for biosimulation into the future. And yet, be patient in terms of activity. Will be abundant.
Contribution to revenue will accrue over time.
I wanted to ask you about your growth formula. So you mentioned, you know, the market for biosimulation was growing at 15%. Now it's more of a 10% grower. If we think about the factors in terms of new clients versus existing clients contributing to growth.
Yep.
Can you talk about that? And can you also talk about the expectation of the mix? So I think you said you expect software to be a faster growth than services going forward.
Yeah. Yeah. Our software revenue, a typical quarter is 80% sourced in renewals, 10% sourced in upsells or cross-selling, clients who take on more of the same product or take on, you know, more of our product portfolio, and 10% new logos. So 80/10/10 is sort of a typical contribution to our software revenue, on that side. We've seen the opportunity, on cross-selling, the upsell side, to, you know, be one of our focuses, quite frankly. Modeling and simulation sort of developed in its silos of techniques, PK/PD, PBPK, QSP, not to throw acronyms, but these are the differing approaches of modeling and simulation for which we have tools and service that support those. Those kind were introduced and looked at in their own silos independently.
From a science point of view, we're seeing the value of utilizing these different techniques in the same area, on the same problem, in the development of protocols, in the answering of efficacy, toxicity, decision-making. We're seeing a lot more integrated effort in terms of these distinct tools or historically distinct tools. What that leads to is more benefit in terms of integration of these tools, a single platform in which the scientist, the client can trade and share models within these approaches. As that leads to go-to-market strategies, our products, they are integrated, perfectly integrated. I wouldn't say that, but integrated and share data and can share models, but can the scientist easily move throughout them? This is an area of product development for us.
And it begins this month with our introduction of GastroPlus, which helps in the process of product integration and adds some pretty extensive AI technology to the platform. But you know, I can come back to what that is. But in the context of cross-selling, we think our clients are more ready to be looking at the full portfolio as opposed to buying them from a point perspective. And we've also reoriented our go-to-market strategy and our sales force from a salesperson carrying a quota for a single product to an account management perspective where our salespeople own accounts and sell all of our products into that account. The opportunity on cross-sell is tremendous.
You did touch on, I think to a certain extent, some new products coming to market. I believe you're developing a cloud-based platform. Can you just tell us what's the timeline for launch of this and what does it open up in terms of functionality?
Yeah. Yeah. The timeframe is pretty quick. GastroPlus, as I said, will be released at the end of this month. It brings to the table two key technology components into our products. Cloud technology, you know, our products, our clients install on-premise to the tune of about 90% of our licenses. We do host on a cloud basis for a small sliver. The industry itself has not been a quick adopter of cloud-based solutions and have preferred to keep within their IT walls these products, keeping their data within their environment. That's opened up of late. The cloud technology introduced this month will be rolled out to our other platforms during the course of the year and allows for a cloud delivery of our products.
We anticipate that that will be taken up by our large pharma clients over time, not with an open cloud, if you will, but they are developing their internal cloud environments to host their various applications. And so it wouldn't change our business model, if you will, in terms of licensing. It will open up to smaller clients that wanna use it on a cloud basis to see more cloud engagement in that world.
Is there any difficulty moving from one platform to the other?
One of the key focuses is to make them interchangeable and easy to translate. So, you know, I believe it'll be relatively easy for them. The challenge will be internal to their environment, not in terms of the use.
Okay. And I do wanna end on just one question regarding, you know, is there anything that you would say is most misunderstood or underappreciated part of your story? I mean, you've been around for a long time. I'd love to get your sense of what the market views Simulations Plus as and what it may be misunderstanding in terms of the story.
Yeah. I don't know that they're misunderstandings, as much as an understanding that, you know, I often get the question, several questions, but first, you know, where's the hockey stick? If this is so good, how come it's not fully adopted and applied by every drug company on every drug program in every way that it could? A host of reasons for that. One that has, you know, lessened in terms of its impact is, you know, the scientific community that was trained in this area was always a gating item, less so today than in the past, but you know, the other factor is it's a world of scientific adoption, so as new use cases, we talked about the FDA and the animal testing, the timeframe for these use cases to come forward.
It's also a, an environment, a scientific environment where, you know, scientists, drug companies like to see 50 publications on the use of that technique before they're ready to adopt it, as well, so those things creep in. The flip side of the positive of that is that the growth opportunity after 30 years at Simulations Plus, consistent growth at 10%-15%, that growth for the runway for that growth continues into the future. The penetration level of modeling and simulation is, is, still ahead of us, and provides support for us to continue to be a very consistent grower, on a go-forward basis. You know, the other area is operating in a world of AI.
And certainly the view in terms of is AI competitive? Is it a value supporting the, you know, AI is a tremendous tool, and we use that tool as well to deliver capabilities to our client and our experience, our know-how, our access to data. These are all advantages that we leverage off of, on a go-forward basis into the future.
Awesome. Well, we have a couple of minutes here. If anybody has any questions, happy to take questions. If not, we can end it here.
Yeah.
Why don't I hand this to you? Okay. Go, go ahead. Sure.
I can hear you.
Nothing really. That's all that matters. Would it be a fair understanding to place your clients in a sort of pre-clinical trial prior to undertaking trials? Is that a fair understanding? Are you still seeing your acquisition as a pain point for your ability as a subject?
Those are areas, yeah, you know, our biosimulation tools run the full gamut from discovery through phase three and into drug approval. But the linkage in terms of the Pro-ficiency acquisition, you know, we do a lot of biosimulation work that provides input into that protocol. And so we understand the reasons for those steps in the protocol, and linking our ability to input into the protocol and then deliver the training and reinforcement down the road is critical to the strategy. Our building of our footprint, not just with training, but in other site selection, patient recruitment, those sorts of things, our potential increases to our footprint of capabilities, the guiding link there will be where can we apply predictive analytics, and help our clients solve problems, correct them before they are incurred down the road.
And then a follow-up, there are certain factors very much on the end stage that would have been for launching education. How would you try to address that?
Yeah. The training platform has been utilized quite extensively, and it's the multi-site, multi-cultural environment that, you know, a simple clinical trial is not the best ROI for our product. The more complex it is, the better it is. We've utilized technology, AI technology of a different simulation sort. Our training programs are built, and with the flip of a button, the avatar is now speaking a different language. And so, you know, the environment of drug development has the diversity, and the seeking of patient populations around the world is a growing factor appropriately into the future.
Thank you, everybody.
Thank you. Take care.