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DATE
Thursday, April 9, 2026 at 5 p.m. ET
CALL PARTICIPANTS
- Chief Executive Officer — Shawn O'Connor
- Chief Financial Officer — William Frederick
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TAKEAWAYS
- Total Revenue -- $24.3 million, up 8% with both Software and Services showing growth.
- Software Revenue -- Increased 9%, comprising 60% of total revenue, driven by Discovery (up 19%) and Development (up 12%) segments.
- Discovery Revenue -- Accounted for 19% of Software revenue; trailing 12-month growth was 6%.
- Development Revenue -- Made up 78% of Software revenue; trailing 12-month growth was 3%.
- Clinical Operations Revenue -- Decreased 54%; contributed just 3% of Software revenue.
- Services Revenue -- Increased 8% and represented 40% of total revenue.
- Development Services -- Rose 12%, making up 77% of Services revenue, while trailing 12 months declined 3%.
- Commercialization Services -- Fell 1% for the quarter but increased 66% on a trailing 12-month basis; constituted 23% of Services revenue.
- Ending Backlog -- $24 million, up 18% from $20.4 million, supported by 199 total services projects during the quarter.
- Gross Margin -- Total gross margin was 66%, with Software at 89% and Services at 33%; prior period margins were 59%, 81%, and 25%, respectively.
- Adjusted EBITDA -- $8.7 million, equating to a 36% margin.
- Adjusted Diluted EPS -- $0.35, in line with internal expectations.
- Average Commercial Client Metrics -- 297 clients, average revenue per client was $124,000 and a 91% renewal rate; trailing 12-month average per client was $148,000 with an 87% renewal rate.
- Top Customer Concentration -- Top 25 customers supplied 46% of Software revenue, with 100% logo retention and over 90% gross revenue retention.
- AI Strategy Execution -- Management reported ongoing “strategic collaboration programs with 3 large pharmaceutical companies to advance AI workflows across drug development life cycle.”
- Guidance for Fiscal 2026 -- Total revenue projected at $79 million to $82 million; growth of 0%-4%; Software mix between 57%-62%; adjusted EBITDA margin between 26%-30%; adjusted diluted EPS of $0.75 to $0.85, reflecting a higher effective tax rate.
- Revised Effective Tax Rate -- Now expected at 23%-25%, raised from a previous 12%-14% expectation, due to changes in discrete items and jurisdictional mix.
- Q3 2026 Outlook -- Anticipated revenue of $20 million to $22 million, adjusted EBITDA margin of 27%-33%, and adjusted diluted EPS between $0.20 to $0.27.
- Cash Position -- $41.8 million in cash and short-term investments, with no debt.
- Client Retention by Segment -- 100% logo retention for top 20 pharma, 90% for $1 billion-plus pharma; most churn occurred among smaller commercial pharma and precommercial biotech clients.
- Sales Model Reorganization -- Management highlighted a transition from product-focused to regional account-based sales, stating it will “provide increased visibility into software retention and cross-sell expansion opportunities.”
- AI Monetization -- Management commented, “not anticipated in fiscal year '26, significant contribution from this arena,” pointing to fiscal 2027 for potential impact.
SUMMARY
Management confirmed that Simulations Plus (SLP +3.00%) exceeded prior top-line guidance, reporting gains in both Software and Service lines while noting substantial backlog growth. Explicit emphasis was placed on the integration of artificial intelligence into product development through collaborations with three large pharmaceutical partners, positioning the company for evolving industry standards and workflows. The updated guidance reflects a notable increase in the effective tax rate, impacting adjusted diluted EPS projections for the balance of the year, while management signaled no material contribution from AI monetization until at least fiscal 2027.
- Management stated that “AI-related competitive concerns have weighed on their valuations across most software-based business models,” though they highlighted biosimulation fundamentals as “strong and durable.”
- O'Connor clarified that the new pharmaceutical collaborations are extensions of preexisting relationships, focusing on tailoring AI capabilities to specific pharma workflows.
- William Frederick noted a decline in software renewal rates but highlighted meaningful cross-sell opportunities among clients with software revenue greater than $100,000.
- The company pointed out a substantial improvement in gross margins across both Software and Services due to revenue mix and reduced amortization expenses post-impairment.
- Management referenced the regulatory environment, mentioning further clarification of “new approaches methodologies or NAMS guidance,” and highlighted growing client interest attributed to these updates and easing macro headwinds.
INDUSTRY GLOSSARY
- NAMS (New Approach Methodologies): Regulatory-guided methods promoting the use of innovative, often non-animal, approaches to assess drug safety and efficacy in pharmaceutical development.
- PBPK (Physiologically Based Pharmacokinetic): Modeling technique simulating drug absorption, distribution, metabolism, and excretion in the body using physiological parameters.
- PK/PD (Pharmacokinetics/Pharmacodynamics): Integrated modeling of drug concentrations (PK) and pharmacological effects (PD) to optimize drug development and dosing strategies.
- QSP (Quantitative Systems Pharmacology): Computational modeling approach capturing the interplay between drug action and biological systems to predict efficacy and safety.
- ADMET Predictor: Simulations Plus proprietary software that predicts absorption, distribution, metabolism, excretion, and toxicity properties from molecular structures using AI.
- MonolixSuite: Software platform for population PK/PD modeling and simulation, acquired by Simulations Plus, focused on analyzing clinical trial data.
- GILTI (Global Intangible Low-Taxed Income): U.S. tax provision taxing certain foreign income, impacting companies with international operations.
- FITI (Foreign-Derived Intangible Income): U.S. tax benefit for income from serving foreign markets, affecting tax rates for multinational companies.
Full Conference Call Transcript
Shawn O'Connor: Thank you, and welcome, everyone. We exceeded the top line guidance that we communicated to you last quarter and delivered $24.3 million in revenue during second quarter with growth in both our Software and Service segments. Adjusted EBITDA was $8.7 million, reflecting a 36% margin and adjusted diluted EPS was $0.35, in line with our internal expectations. Turning to the macro environment. We continue to see encouraging market conditions globally, supported by ongoing most favored nation pricing agreements, easing tariff concerns and a more supportive funding environment for our customers. On the regulatory front, the new approaches methodologies or NAMS guidance issued late last year was further clarified with an additional update last month.
Against this backdrop, we're seeing a pickup in client spending reflected in solid software renewal rates, increased new logo activity and strengthened service bookings. Overall, we're pleased with our first half fiscal 2026 performance and encouraged by the momentum that it is building across the business. Next, I want to address the broader discussion around artificial intelligence and its impact on software companies, including our own. Over the past quarter, AI-related competitive concerns have weighed on their valuations across most software-based business models, and biosimulation has not been entirely immune to that sentiment. That said, we believe it's important to separate short-term market perception from long-term fundamentals. From our perspective, ongoing advances in AI are a net positive for biosimulation.
AI is accelerating the industry's transition to a data-driven drug development workflows and, importantly, enhancing the value of trusted and validated scientific engines rather than replacing them. We have been an early adopter of AI for decades, beginning with the introduction of ADMET Predictor in the late 1990s, and we continue to lead in its practical application today. Beyond using machine learning for property prediction or to improve software development efficiency, we are embedding AI across our product roadmap, improving compute performance, interoperability between scientific engines, data management and duration, automation of repetitive modeling tasks and making our tools more accessible across organizations.
While certain software models may face disruption from AI, we believe the core value of our scientific engines, including property predictions, PBPK, PK/PD and QSP modeling functionality and science remains strong and durable. These capabilities are built on decades of scientific investment deep domain expertise, validated methodologies and integration into customer workflows and regulated environments. In contrast to black box approaches, our solutions are trusted, auditable and difficult to replicate. That is why we have long been the preferred choice for commercial drug developers even during a period of significant investment in AI-driven discovery companies, and a number of open source applications.
At our Investor Day in January, we outlined the road map focused on further leveraging AI across our ecosystem and we continue to make solid progress executing against that plan. Just a few weeks ago, we announced strategic collaboration programs with 3 large pharmaceutical companies to advance AI workflows across drug development life cycle. The close collaboration between Simulations Plus and leading pharmaceutical organizations will provide direct insight into how AI will be integrated into real-world environments, in forming product direction, workflow standardization and for future commercial models. The programs will utilize Simulations Plus' major software platforms, including GastroPlus, MonolixSuite, ADMET Predictor and Thales.
Participating companies will integrate our internally developed AI agents directly into model inform direct development workflows, enabling natural language interaction, automation of data processing coordination of simulations across multiple modeling engines and generation of interoperable outputs from complex multistep pipelines. These programs represent an important step in moving us and our partners beyond experimentation and into practical implementation as we advance our software and services into a unified modeling ecosystem. Finally, it's important to emphasize that our customers are not looking to replace biosimulation engines. Instead, they are looking to enhance their value using AI to improve efficiency, broaden deployment and accelerate drug discovery and development.
Furthermore, cost benefits accrue at any point that Simulations Plus can help us simplify and shorten the drug development process or mitigate costly miscalculations. This approach aligns closely with our strategy to be a key partner in our clients' AI journey and supports our long-term growth plans. With that, I'll turn the call over to Will.
William Frederick: Thank you, Shawn. To recap our second quarter performance, total revenue increased 8% to $24.3 million. Software revenue increased 9%, representing 60% of total revenue and Services revenue increased 8%, representing 40% of total revenue. Turning to software highlights for the quarter. Discovery revenue, primarily from ADMET Predictor, increased 19% for the quarter and 6% for the trailing 12-month period. The contribution as a percentage of total software revenue was 19% during the quarter and 18% for the trailing 12 months. Development revenue, primarily from GastroPlus and MonolixSuite increased 12% for the quarter and 3% for the trailing 12-month period. The contribution was 78% of total software revenue for both the quarter and the trailing 12 months.
Clinical operations revenue primarily from proficiency declined 54% for the quarter and 58% for the trailing 12-month period. The contribution during the quarter was 3% of total software revenue and 3% for the trailing 12 months. We ended the quarter with 297 commercial clients, achieving an average revenue per client of $124,000 and a 91% renewal rate for the quarter. On a trailing 12-month basis, we achieved average revenue per client of $148,000 and our renewal rate was 87%. While we've seen a decline in software renewal rates, it's worth diving a bit deeper into the patterns we've seen. For top 20 pharma clients, we've historically had 100% logo retention.
For $1 billion-plus pharma, defined as companies generating over $1 billion in global revenue, we've seen 90% logo retention. Churn has predominantly been with other commercial pharma defined as biopharma companies with at least 1 approved product and less than $1 billion in revenue and precommercial biotech defined as biotech companies without an approved therapy. This is consistent with historically more episodic versus recurring demand as pipelines progress with the challenging early-stage biopharma market backdrop over the last few years. Our top 25 customers represent about 46% of overall software revenue and these customers are highly stable with 100% logo retention and 90% plus gross revenue retention.
As we continue to assess software renewal rates and advance our sales team reorganization from product-focused selling to a regional account-based model centered on deepening client relationships, we plan to provide increased visibility into software retention and cross-sell expansion opportunities. For example, in fiscal 2025, we saw the following from clients with software revenue greater than $100,000: 50% purchased 2 software products, 23% purchased 3 software products and 15% purchased 4 or more products. We believe this creates meaningful cross-sell and upside opportunities as reflected in the continued growth of average software revenue per client. We look forward to providing additional insight into these performance metrics over time. Turning to services highlights for the quarter.
Development services, which includes our biosimulation services, increased 12% for the quarter and declined 3% for the trailing 12-month period. The contribution during the quarter was 77% of total services revenue and 75% for the trailing 12 months. Commercialization Services, which includes our MedChem services, declined 1% for the quarter and increased 66% for the trailing 12-month period. The contribution during the quarter was 23% of total services revenue and 25% for the trailing 12 months. Total services projects worked on during the quarter were 199 and ending backlog increased 18% to $24 million from $20.4 million last year. Overall, we have a healthy pipeline of services projects.
Total gross margin for the second quarter was 66%, with Software gross margin of 89% and Services gross margin of 33%. On a comparative basis, total gross margin for the prior period was 59% with Software gross margin of 81% and Services gross margin of 25%. The increase in Software gross margin was primarily driven by increased software-related revenue, particularly from Development and Discovery Solutions and lower software-related costs largely reflecting reduced amortization expense following the impairment charge in the third quarter of fiscal 2025. Other income was $0.3 million for the quarter compared to $0.8 million last year.
The prior year amount included the gain on the change in fair value of contingent consideration related to the Immunetrics holdback liability. Income tax expense was $1.4 million compared to $0.4 million last year our effective tax rate was 23% compared to 12% last year. The increase in the tax rate is primarily due to the result of favorable discrete item in the prior year that did not recur in the current year, a less favorable jurisdictional mix of earnings between the U.S. and France, increased unfavorable global intangible low-taxed income, or GILTI, impacts driven by higher French taxable income, and a lower foreign-derived intangible income or FITI benefit.
In addition, certain items affecting the current year effective tax rate relate to accelerated deductions elected under the One Big Beautiful Bill Act. These deductions are expected to be favorable to cash flows as they accelerate the timing of tax benefits and reduce near-term cash tax payments. As a result, we now expect our effective tax rate for fiscal 2026 to be between 23% to 25% as compared to our previous expectation of 12% to 14%. Moving to our balance sheet. We ended the quarter with $41.8 million in cash and short-term investments. We remain well capitalized with no debt and strong free cash flow as we continue to execute our growth and innovation strategy.
Our guidance for fiscal 2026 remains relatively unchanged from what we previously provided. Total revenue between $79 million to $82 million, year-over-year revenue growth between 0% to 4%, software mix between 57% to 62%, adjusted EBITDA margin between 26% to 30%. Adjusted diluted earnings per share is now expected to range between $0.75 to $0.85, which reflects the change in our effective tax rate we just discussed. For the third quarter of 2026, we anticipate revenue to be between $20 million to $22 million, adjusted EBITDA margin of 27% to 33% and adjusted diluted EPS between $0.20 to $0.27. I will now turn the call back to Shawn.
Shawn O'Connor: Thank you, Will. As I mentioned before, we're pleased with our first half performance and remain excited about the opportunities ahead. Simulations Plus is transitioning from a set of innovative modeling tools into an integrated AI-driven biosimulation ecosystem, supporting the full drug development life cycle, from discovery through commercialization. Our core purpose remains unchanged, empowering our clients to deliver safer, more effective therapies through science-driven innovation. What's accelerating and is how we execute against that mission. By combining our validated scientific engines with enhanced cloud capabilities, AI-powered workflows and a coordinated road map we're delivering greater speed, consistency and interoperability to our clients. Thank you for joining the call today. And with that, we'll open the call for questions.
Operator: [Operator Instructions] And our first question comes from the line of Matt Hewitt with Craig-Hallum.
Matthew Hewitt: Obviously, it's nice to hear we're starting to see some positive impact from the changes that we started to see last fall. Maybe first up, I was hoping we could dig in a little bit on the 3 large pharma customers that you announced here a couple of weeks ago kind of coming in and adopting the 4 major platforms. Could you walk through exactly how that's going to work? What does that -- what do those contracts look like? Is it cross-selling that's already occurring? Just any more color there, I think, would be helpful.
Shawn O'Connor: Sure, Matt. Yes, we announced a few weeks ago the collaborations with 3 large pharma accounts. Those collaborations have been underway for a longer period of time. These are not new relationships beginning. They've been involved in our product road map development for some time, prior to our unveiling of that to the Investor Day meeting in January.
Each of the collaborations has a little bit different focus across the scientific engines, but the tougher collectively, all of our scientific engines, collaboration is 1 of working together to ensure that we've got good visibility to their needs, their workflows, internal to their organizations so that we can match the development of the AI capabilities to meet their needs and fit into their environments. It's good to have 2 or 3 of these relationships so that every company is unique as to how they're deploying their efforts on the AI side. So it allows us to develop our solutions in a way that can be tailored to different needs across the pharma companies.
So we're engaging with them on a product development basis. There has been some financial component to at least 1 of the relationships already. The financial relationship going forward with each of the parties is in discussion right now as to what the long-term takedown across the technology platform will be and what the financial circumstances will be around that. But very important relationships for us. It's similar to what we've done through our lifetime as a company. Our scientific engines have been developed in a series of collaborations with our clients, with regulatory bodies. It's what's made them on target in terms of the needs of drug development and good to see that's continuing through our AI developments today.
Matthew Hewitt: That's super helpful. And then maybe a follow-up question. You noted you're having some success with cross-selling already. And you also mentioned that during the quarter, you won some new logos. I'm just curious, are those new logos customers that maybe hadn't adopted your software services before? Are these competitive conversions, like you're winning business or taking share? Just any other color there would be helpful as well.
Shawn O'Connor: Yes, as new logos, the nonexisting customers that are taking down solutions for the first time. So they're new to us in terms of the competitive situation in terms of their selection of our product, we have to go through each and every one. And as Will described, in terms of the stability of our client base at certainly the large top 20 as well as the billion-dollar large pharma companies. New logo opportunities are going to be at the lower end of the environment or size of the clients. So those customers can be clients that are just initially starting up in internal capabilities for biosimulation. But in some cases, they may be movement from competitive scenarios.
Operator: And our next question comes from the line of Constantine Davides with Citizens.
Constantine Davides: Just a couple of questions here. First, I noticed a large sequential uptick in the commercial portion of the services backlog. And I just wanted to get a sense for maybe the proficiency pipeline in both software and services, size of deals that you're seeing and then any seasonality we should consider as we think about that business over the back half of the year?
Shawn O'Connor: Sure. The backlog is as a reminder, entirely service revenue based. So that's driven -- 75% of our service business is in the development space, the 25% is in the [ kinetic ] communications space, that revenue service revenue stream that came to us through the acquisition of proficiency. We started to see good pipeline activity and closure as we exited and saw a good delivery in terms of service revenue in the first quarter, and that's continued into the second quarter here. So that side of our business is slowing quite nicely right now. Turning to the proficiency question.
All the backwards leverage off of the service, Med Communications service business through the halfway point of the year is up nicely. They had a very good first quarter. Second quarter growth was not as high on a percentage basis but a good contribution and certainly cumulatively through the midpoint of the year, they're performing quite nicely. On the Software side, that performance has gone as anticipated. To recall, beginning of the '25 post acquisition of Proficiency, their first couple of quarters, delivered good revenue, clinical trial step back in the back half of '25, certainly brought that run rate of software revenue contribution down. That's continued into the first half of the year.
It stabilized at a good sort of starting point, if you will, and we look for reasonable growth on a go-forward basis for the efficiency from this point forward.
Constantine Davides: Great. And then just -- I appreciate the added color on some of the product update. I think you said 50% of your customers have 2 or more and some other metrics around that. I guess when you think about upsell, Shawn, where is the biggest opportunity? Is it getting single product customers to 2? Is it getting some of the 2 product customers to 3? Just how should we think about sort of progress in that metric over time and what's feasible?
Shawn O'Connor: Yes, it's an opportunity exists in all of those levels, taking a claim from 1 to 2 and 2 to 3 and beyond. We historically have seen good linkage between ADMET Predictor and GastroPlus often our 2 product customers might start with those 2. Obviously, the Monolix product that came to us through acquisition 1.5 years ago now. It is a nice complement in the PK/PD space for our clients to reach out and bring on board. And we've seen over the last number of years, very strong growth. And our revenue from the Monolix PK/PD platform. So opportunity exists across all the machinations there in terms of which products.
And I think the opportunity here is for that to accelerate driven by, a, our reorganization of our business development organization from sellers, if you will, at each of the point solutions independently, so to speak, or quoted by product to an environment in which we are geographically and then to count organized with quotas that our business development people carry that are quotas for our clients as opposed to go to quotas for specific products. I think that focus will help in terms of our cross-selling efforts. Secondly, the development and delivery of our ecosystem, as we've described, it enhances the interoperability across the scientific engines tremendously.
And as well, putting it into the cloud offers more opportunity for the smaller and medium-sized entities out there taking access. So that may be a new logo opportunity, but that new logo opportunity then rolls into cross-selling opportunities. So from both an organizational and our sales approach perspective as well as our product road map, I think we are very focused on our cross-selling efforts going forward and the opportunity certainly is quite large there.
Operator: And our next question comes from the line of Max Smock with William Blair.
Max Smock: Wondering if you can discuss kind of where you're at right now halfway through the year relative to your expectations when you gave your initial guide at the end of last year? Just trying to get a sense for the level of conservatism that's embedded in the guide in light of your bullish macro commentary and the growing interest in NAMs. Just kind of looking at the numbers, revenue up 3% in 1H, but I think guidance imply was basically flat revenue in the second half off of what looks like easier comps.
So if you can just maybe level set and help us understand the thought process behind not taking up to guide on the back of the really strong results we saw here in the second quarter?
Shawn O'Connor: Sure, Max. Not a surprising question. We -- each quarter, each opportunity we report, take a look at the guidance opportunity to adjust as warranted. I'd say we're operating still in an environment that fragile might be a reasonable term to use. We see a lot of momentum, good spending in part of our clients. But we've got macro issues in terms of global politics as well as the more specific pharma-related scenarios that could raise their head. And so a cautious approach to this based upon our experience over the last 24 months drives us pretty strongly here.
That being said, yes, the momentum seems to be building on that delivered quite nicely in the first couple of quarters here. And certainly, it puts us moving into the back half of the year with greater confidence in terms of the guidance that we've got out there. But a relatively cautious approach in terms of let's not take a 1 or 2 quarter drive it into a trend just yet.
Max Smock: That's really helpful. And maybe just following up on that, particularly your comment around the fragile environment. I know it's probably hard to tell to some extent, but just wondering if you can bifurcate a little bit between the momentum you're seeing, whether how much of that is coming from just an overall recovery in the macro environment and biopharma spend more broadly versus how much of do you think -- how much of that recovery do you think is more a function of just increasing interest and growing adoption of NAM specifically?
Shawn O'Connor: I'd say broadly, I mean when we say NAMs, some people might jump and say, boy, is that the animal testing announcement, and I would say the momentum built here is certainly, that's on the horizon and -- but it's a horizon still a couple of years out. So in general, the support for biosimulation for in silico methodologies for AI is strong broadly from the regulatory perspective. I think our clients shifted in '25 to AI investment strategy, which was a partnership with other AI discovery companies. That shift is now causing them to take a look at internal implementation of AI.
I think there's a lot of momentum building out of those endeavors, circling in the large pharma environment. So I think it's pretty broad based, but we operated in an industry that is somewhat fragile in the sense of external announcements and macro issues.
Operator: And our next question comes from the line of Jeff Garro with Stephens.
Jeffrey Garro: I want to ask a little bit more on cross-selling. You just kind of hit the macro versus micro part of that topic. But I was hoping you could dive a little bit further on evaluating your progress to reach multiple buyers within your clients' organizations getting kind of beyond the modeling department with these clients?
Shawn O'Connor: That's a good question, Jeff. Getting as much of your targeted budget as you can as an objective, but also looking for other pockets of budget within our clients has always been something that has been at the forefront here. Our efforts in terms of the proficiency acquisition opened up our reach into clinical trial operation projects. And so that is certainly presents more TAM at a macro level. And specifically, a network can do another part of our client organizations and new budget dollars. I'd say the most predominant 1 again, is in the arena of the AI budget within our clients.
And I think in that regard, the collaborations that we've announced, those collaborations have served well, our ability to leverage our very strong modeling and simulation relationships, leverage that into relationship build with the leaders within those collaborative clients, building that relationship and in fact, opportunity for the funding of our ecosystem and our AI functionality to be sourced outside the traditional modeling and simulation budget. And I think that bodes well. And when I step back and looked at it and we sort of estimate growth of modeling and simulation budgets you really need to open up your eyes and see that, that growth is incremental when you look at the AI budgets alongside the modeling and simulation budgets.
And certainly, the AI spend those budgets in our clients is broad-based across the full continuum from patient recruitment to all kinds of investments of AI that a pharma company may be making. But a portion of that AI budget is it's in the biosimulation space. And so when we look for budget growth and modeling and simulation, they receive the traditional momentum picking up there, but the icing on the cake, a very thick icing, can be found in the AI budgets within large pharma as well.
Jeffrey Garro: Excellent. I appreciate all those comments. And probably a nice segue to the other question I wanted to ask on AI monetization. You said that we should have kind of low to minimal expectations for AI monetization this year. You mentioned that discussions are really still ongoing on the economic model with your labor collaborative partners that you recently announced, but I still want to ask just kind of a what timing is on when AI monetization starts to show in the P&L? How we should think about the pacing of those discussions?
And maybe just more broadly, what we can look to as potential proof points that AI is generating incremental value outside from the likely aid that it will provide to renewal and retention efforts?
Shawn O'Connor: Yes, good question. That discussions are underway with those collaborators, which will just as they are proving the path forward on the technology development, they will prove the path forward in terms of monetization. And I'd say at this stage that the recognition of the value of the incremental technology is very visible and accepted on the part of our clients. And -- so the groundwork, if you will, in terms of value and monetization is there. The mechanics of how that rolls out is where the discussions lie right now. we certainly not anticipated in fiscal year '26, significant contribution from this arena at all in our guidance per se.
And inevitably, is also tied to commercial delivery of this technology. And so I would look out to this being a contributor to fiscal year '27.
Operator: And our next question comes from the line of David Larsen with BTIG.
David Larsen: Are any of the sort of large AI companies, clients of yours, like Google DeepMind comes to mind or any of these other organizations?
Shawn O'Connor: Yes. I mean, yes, the historical drug discovery, primarily AI entities, the Recursions, the DeepMinds, relevant AIs of the world. Yes, generally, there's -- it's not 100% coverage, but a good percentage of those are licensing some footprint of our software, yes.
David Larsen: So you're generating revenue from the AI market already supporting these AI organizations. And I would imagine they need SLP because of your data dictionaries, because of the training of your scientists, because of all of the data that you -- and models that you've built over the past decades, that they can then search that, is that right?
Shawn O'Connor: Ultimately, they have evolved into drug development companies. They are all, for the most part, in discovery, some have reached early clinical status with a program or two. And so historically, to date, primarily the opportunity, our discovery platform is ADMET Predictor. So it's ADMET Predictor and its utility in terms of property prediction is what is the value to them now as they move into the clinic. The scientific engines of GastroPlus and Monolix and Thales become candidates for their use in the development -- clinical development cycle of their development of drugs.
Operator: And our next question comes from the line of Brendan Smith with TD Cowen.
Brendan Smith: Maybe first, just on some of the services metrics that you show, I think it's on Slide 13, if I'm not mistaken. I just want to make sure I'm understanding correctly. I guess how should we think about kind of the relative decline, albeit minimal in total projects year-over-year kind of versus the increase in backlog there specifically. Is that kind of a function more of the types of projects you're moving into, the customers themselves? Or I guess, are there any other dynamics at play there?
Shawn O'Connor: Yes. A number of projects can evolve over time, we can have projects that are consuming a good percentage of our staff in a particular quarter, and other quarters where we're working on smaller or medium-sized projects and whatnot. So that can kind of ebb and flow quite a bit. The backlog growth is nice getting back to prior year levels here in terms of our total backlog, and it's good measurement in terms of our pipeline on service as it's closing ahead of actual performance of those projects.
Brendan Smith: Okay. Got it. Helpful. And then maybe a second one, just looking at kind of Slide 9, I think you -- where you had the comparison of as Q2 versus trailing 12 months and just looking at the breakdown of software solutions as a percent of software revs. I mean it looks pretty stable over the last year. But I guess I'm just wondering if you expect any meaningful shift in that segment breakdown over the next 12 months? Kind of as some of these new rollouts and broader sector interest starts to evolve? And I guess if not, with maybe just underpinning some of those assumptions, presumably, I guess, based on your recent conversations.
Shawn O'Connor: The assumption under -- Brendan, I'm sorry, but just to clarify the assumption in terms of software and service mix, is that what you're referring to?
Brendan Smith: Actually, just within the software. I guess what I'm really asking is it looks like the kind of relative breakdown of which software solutions you have over the last year is pretty consistent with what we saw in Q2. I'm just curious if you're expecting any shift in that just between kind of discovery, development and clinical ops over the next year, just kind of given the push to get new logos signed and kind of expanding within kind of the sector interest into the space?
Shawn O'Connor: Yes. Okay. I understand now. Clearly, our development solutions of Monolix and GastroPlus are the key drivers in terms of our software revenue with ADMET Predictor contributed the proficiency training platform providing contribution, but the smallest piece of the pie there. The cross-selling opportunities would support both somewhat in the ADMET Predictor and GastroPlus space, but significantly in terms of Monolix, seeing more of the large $1 billion plus pharma plus top 20 clients take on Monolix as their preferred platform in the PK/PD space. That slice could grow. It's growing faster in terms of percentage growth than the other solutions for the last couple of 3 years. So seeing grow would not surprise me.
New logos, often the starting point there is going to be the GastroPlus or Monolix if it's a development company that's a pre-product biotech company. If they're in discovery and probably an ADMET Predictor. So I think we've seen some stability in the pie chart there contribution. I think that stability will remain pretty much the same with perhaps Monolix taking a little bit of incremental piece of that pie.
Operator: And with that, there are no further questions at this time. I'd like to turn the call back over to Shawn O'Connor any closing remarks.
Shawn O'Connor: Very good. Okay. Over the next few months, we've got a number of investor conferences, including the RBC Global Healthcare Conference, Craig-Hallum Conference, TD [ Life Science ] Tools and Diagnostic Revolution and the Citizens Medical Devices and Health Care Services Forum. Hopefully we can see many of you there. Otherwise, I appreciate the opportunity to deliver this quarter's results to you and look forward to speaking again next quarter. Take care, everyone.
Operator: And with that, ladies and gentlemen, this does conclude today's teleconference. We thank you for your participation, and you may now disconnect your lines, and have a wonderful day.
