Schrödinger, Inc. (SDGR) Q3 2026 Earnings Report, Transcript and Summary

Hello, everyone. Thank you for joining us and welcome to Schrodinger's conference call to review third quarter 2026 financial results. [Operator Instructions] Please be advised that this call is being recorded at the company's request. Now I would like to introduce your host for today's conference, Ms. Jared Madden, Chief Corporate Affairs Officer and Head of Investor Relations. Please go ahead.

Thank you, and good afternoon, everyone. Welcome to today's call during which we will provide an update on the company and review our third quarter 2026 financial results. Earlier today, we issued a press release summarizing our financial results and progress across the company, which is available on our website at schrodinger.com. During today's call, management will make statements that are forward-looking and made pursuant to the safe harbor provisions of the Private Securities Litigation Reform Act of 1995, including, without limitation, statements related to our outlook for the full year 2026, our plans to accelerate the growth of our software business and advance our therapeutics portfolio, the capability and potential advantages of Bunsen, our Agentic AI co-scientist, the clinical potential and properties of our compounds and those of our collaborators, the use of our cash resources as well as our future expenses. These forward-looking statements reflect our current views about our plans, intentions, expectations, strategies and prospects, which are based on the information currently available to us and on assumptions we have made. Actual results may differ materially due to a number of important factors, including the considerations described in the Risk Factors section and elsewhere in the filings we make with the SEC, including our Form 10-Q for the quarter ended September 30, 2026. These forward-looking statements represent our views only as of today, and we caution you that, except as required by law, we may not update them in the future, whether as a result of new information, future events or otherwise. Also included in today's call are certain non-GAAP financial measures. These non-GAAP financial measures are not prepared in accordance with generally accepted accounting principles and should be considered only in addition to and not a substitute for or superior to GAAP measures. Please refer to the tables at the end of our press release, which is available on our website for reconciliations of these non-GAAP measures to the most directly comparable GAAP measures. This afternoon, Ramy Farid, our CEO, will review our recent progress. Then Richie Jain, Chief Financial Officer, will discuss our financial results and 2026 guidance. Karen Akinsanya, President, Head of Therapeutics R&D and Chief Strategy Officer, Partnerships, will provide an update on our therapeutics portfolio. Pat Lorton, our Chief Technology and Chief Operating Officer, will join us for the Q&A. And with that, I will turn the call over to Ramy.

Thanks, Jaren, and thank you, everyone, for joining us today. Our third quarter results reflect sustained commercial momentum and strong progress towards the long-range goals we outlined earlier this year. ACV grew 17% or 24% excluding contribution ACV. The key drivers of this growth were broader adoption within large pharmaceutical accounts, the introduction of new products, including Bunsen, our Agentic AI co-scientist, growth among biotech and material science customers and addition of new customers. Our discovery team continues to generate and contribute to high-value programs, which our partners and co-founded companies will advance through clinical development. During the quarter, we received a milestone payment associated with the clinical progress of Structured Therapeutics oral small molecule amylin program. On the strength of this performance, we are raising our full year guidance for both ACV and drug discovery revenue. Looking across the molecular discovery landscape, biopharma and materials organizations are increasingly shifting toward a predict-first computational approach to increase the probability of success and shorten discovery timelines. As industries prioritize spending on the most high-impact solutions, our platform remains critical to molecular discovery, enabling us to deliver durable growth. While the promise of AI in molecular discovery is immense, models remain fundamentally constrained by the quality of their training data. Our competitive advantage lies in first principles, physics simulations that generate the accurate ground truth data needed to train truly predictive AI models. With the introduction of Bunsen, we are now deploying Agentic AI to orchestrate our computational platform to increase efficiency and broaden user adoption across life sciences and material science. Customer interest has been very strong, and the feedback from our early access program has been enthusiastically positive with multiple customers in the process of evaluating the solution. Within Schrodinger, Bunsen has rapidly become the primary interface for discovery workflows and now handles approximately 80% of our high throughput calculations on our internal compute cluster. Our predictive toxicology solution also continues to be an important part of our strategy to expand the capabilities of our platform. Moving from traditional safety testing to computational screening represents a significant paradigm shift that can save time and increase the probability of success. We are continuing to scale the scope of our predictive toxicology solution and can now evaluate more than 80 potential off-target proteins computationally. Commercial evaluations are progressing well. We expect the adoption curve to follow the path of our foundational tools like FEP+, where thorough customer benchmarking requires diligence upfront, but ultimately establishes deeply integrated, highly entrenched software adoption that endures as the industry standard. We are very pleased with the progress we are making in material science. Customers across a broad range of industries, including chemicals, energy storage, semiconductors and electronics are increasing their use of our platform. By using our platform, scientists can accurately predict critical properties such as stability, connectivity and mechanical performance prior to physical testing. Material science is an important long-term growth driver that significantly expands our software market beyond drug discovery. We continue to make scientific advancements in this area. Last month, we published breakthrough research in nature that revealed critical insights in the fundamental chemistry of lithium batteries. Using our machine learning force field, our team simulated battery electrolytes at unprecedented accuracy, paving the way for the computational design of higher capacity, faster charging and longer-lasting batteries. Additionally, our researchers recently published a novel method for accurately predicting the stability of organic electronic materials for OLED displays. These advancements highlight how our platform enables materials innovators to replace experimental trial and error with rapid predictive computational design. We are pleased to see continued success across our collaborative portfolio as partnered assets reach important clinical and regulatory milestones. Takeda's new drug application for zasocitinib, the TYK2 inhibitor we co-invented with Nimbus was accepted under priority review. Approval is expected early next year, further reinforcing our track record of success. During the quarter, we launched Tectora, a discovery stage company funded with $55 million for NEA and RA Capital and anchored by two programs originated by our therapeutics team. Tectora is the latest company built through our co-founding strategy, which has already produced a number of clinical successes and allows us to share in long-term value through equity, milestones and royalties. We feel confident about the direction of the company and our momentum heading into the end of the year. Tackling complex computational challenges takes immense dedication, and I want to thank our entire team for their hard work.

I'll now turn the call over to Richie to review our financial results. Thank you, Ramy, and good afternoon. Our third quarter results highlight the ongoing momentum across our business, marked by strong ACV growth, continued transition to hosted licenses, progress in our drug discovery business and disciplined expense management. Third quarter ACV was $44.7 million, which represents 17% growth year-over-year and $214 million on a trailing four quarter basis. Third quarter growth, excluding contribution ACV was 24%. ACV growth was broad-based, driven by our top 20 pharma customers as well as biotech and material science customers. Total revenue for the third quarter of 2026 was $64.5 million, a 19% increase. Software revenue was $38.2 million, of which hosted revenue was $17.2 million, a 49% increase. Hosted revenue represented 45% of the software total compared to 32% in the third quarter of 2025. On a trailing four-quarter basis, hosted revenue increased to 32% of the software total from 23% in Q3 2025. We are pleased with our progress in transitioning customers to hosted licensing. As a reminder on revenue recognition, transitioning customers from on-premises to hosted licensing temporarily moderates our reported software revenue because hosted contracts are recognized ratably over the life of the contract. Every 1% increase in hosted revenue results in an approximate $2 million to $3 million reduction in reported revenue depending on contract length and renewal timing. Software gross margin was 75% for the quarter compared to 77% in Q3 2025, reflecting our ongoing transition to hosted software licensing. Drug discovery revenue was $24.2 million compared to $13 million in Q3 2025. The increase was primarily driven by a milestone payment associated with Structure's oral amylin program. Total operating expenses for Q3 were $64 million, a decrease of 13% compared to $74 million in Q3 2025. The decrease was primarily driven by lower clinical CRO costs and headcount-related expenses. Total other expense was $11.4 million, primarily due to changes in the mark-to-market value of our public equity positions. Net loss for the quarter was $38 million compared to $33 million in the third quarter of 2025. We ended the quarter with $373 million in cash and marketable securities. The fully diluted share count was 74.9 million. Turning to our full year 2026 guidance. We now expect full year 2026 ACV to be in the range of $222 million to $232 million, representing 12% to 17% growth over 2025 and reflecting our year-to-date performance and outlook for the remainder of the year. We now expect drug discovery revenue to be in the range of $75 million to $85 million compared to our prior expectation of $65 million to $75 million due to the recognition of a milestone payment from Structure. Our operating expenses are still expected to be less than 2025. In summary, our third quarter results show that software demand is strong, our integrated business model is working and our spending remains disciplined. With our excellent year-to-date progress and visibility into our fourth quarter, we have raised expectations for the full year and remain confident in our financial trajectory. I would now like to hand the call over to Karen to provide an update on our therapeutics portfolio.

Thank you, Ritchie. Our experienced team of drug discovery scientists leverages our computational platform at scale to design development candidates for high-value targets with the goal of advancing programs through co-founded companies and collaborations. Through previously co-founded companies like Nimbus, Norfolk, Structure and Ajax, we have demonstrated a clear track record of translating computational drug discovery into successful clinical programs and generating substantial value. In September, we co-founded Tectora Therapeutics alongside NEA and Ari Capital, marking the first time we have built a new company directly around assets discovered in our internal pipeline. We contributed two early-stage immunology and inflammation programs, SDGR-4594 and SDGR-8139. In exchange, we received an equity stake in Tectora and are eligible for future development and commercial milestones as well as royalties on sales. Our team will continue to work closely with Tectora, deploying our computational platform and drug discovery expertise to advance both programs towards the clinic. The collaboration with Tectora enables these promising programs to move forward with dedicated capital while allowing us to retain significant upside. Across our maturing collaboration portfolio, we are seeing significant progress of clinical stage programs. In September, Takeda announced that the FDA accepted its new drug application for zasocitinib under priority review. We co-invented zasocitinib with Nimbus and remain eligible for sales-based milestones. Zasocitinib was acquired by Takeda from Nimbus in 2023. We also received a milestone payment from Structure Therapeutics, a company we co-founded following initial dosing in the multiple ascending dose portion of the Phase I/IIa study of ACCG-2671, an oral amylin molecule in development as a potential treatment for obesity. Zotemtegrast, formerly known as LY-4268989 or MORF-057, which was discovered during our collaboration with Morphic is currently in multiple Phase II studies. This includes a combination study, TOPAZ-UC with Lilly's mirikizumab in patients with ulcerative colitis. Dose escalation in the Phase I study for our MALT1 inhibitor, zilemaltib or SGR-1505 is now complete, and our abstract was accepted as an oral presentation at the upcoming American Society of Hematology Annual Meeting. The presentation will detail the favorable safety profile and clinical activity observed in patients with relapsed/refractory B-cell malignancies. We look forward to presenting these results in December. In summary, we are seeing strong progress across our entire therapeutics portfolio from our early-stage discovery programs to our partnered and co-founded company assets. We entered the final quarter of the year with excellent momentum and look forward to keeping you updated on our progress. I will now turn the call back to Ramy.

Thank you, Karen. With strong commercial demand for our software, continuous platform innovation and excellent progress across our therapeutics portfolio, we head into year-end with immense confidence in our trajectory. At this time, we are happy to take your questions.

[Operator Instructions] Your first question comes from the line of Craig Hettenbach with Morgan Stanley.

Regarding the Q4 sales pipeline and activity, beyond what looks like a healthier backdrop across pharma and biotech, what are some of the company-specific things that are resonating most with your clients?

Yes. Thanks for the question. I think one of the most important things that's resonating with customers is that the technology is actually working. This is a field that is -- has been around for a long time. People have been trying to use computation to replace experiment and it turned out to be a very hard problem. It took a long time to get the technology to work. And it took a long time to get companies and users to accept the results of a calculation. And that's something that has been really transformative in this field. And now there's this confidence that when they run a calculation and they get a result that there's a very, very, very high probability that the result will be correct. I think there finding that out or they're discovering that from their own use of the technology, but also our track record is becoming quite compelling. Our track record of success in some of the companies we mentioned today in the prepared remarks and in a number of the collaborations we have with pharma has really been overwhelming and it's sort of further validation of the quality of the science. Anything, Pat, you think to add to that in your interactions with?

Yes. I mean the only thing it's kind of doubling down on what you're saying in terms of now that the platform is fully validated, and I think there's an environment where speed matters more than ever. There's a lot of pressure coming from AI and new international markets entering the space them embracing the fully validated platform to attempt to accelerate their programs is more important than ever to our customers.

That's helpful. And then maybe just a quick follow-up for Richie. Company has done a good job of kind of reining expenses here. As you begin the budget planning process for '27, how are you thinking about OpEx in terms of maybe some areas where you're looking to invest versus areas to drive additional cuts or efficiencies?

Yes. Thanks for the question, Craig. We're kind of early for '27 thinking at this point. But one thing that we've said pretty consistently is that we are building out the platform and building out our capabilities to grow and bring new products to customers. So, we'll continue to look for those opportunities. Our team, I'd say we -- we're basically at scale at this point. We have a team here that can deliver on our 3-year objectives. But we will continue to look for opportunities to invest to facilitate top line growth.

Your next question comes from the line of Matt Hewitt with Craig-Hallum.

Congratulations on all the progress. Maybe first up, a lot has been mentioned over the past quarter or two regarding the funding environment and how -- especially the smaller pharma and biotech companies have been able to garner better funding and therefore, hopefully starting to invest. I guess the first question is, are you starting to see some of that? Or at this stage of the game, is it still the large pharma that's primarily coming in with new orders and new contracts?

Yes. We're definitely seeing that. It's a great question. One of the things that's so obvious this year compared to last year that's a reflection of what you're saying is that we're just not seeing the sort of difficulty that biotech companies were having last year in raising money and investing in their research efforts. That's very different this year. Very, very few companies running into that sort of problem that they were running into before, which is obviously the result of them being able to raise money and continue to focus on their pipeline, not just on the one clinical asset that they might have. So, we're definitely seeing it, and it is a major contributor to the results that we presented today.

Got it. And then maybe a follow-up question, a little bit different angle, but you mentioned the material science business a couple of times in your prepared remarks. You obviously had a nice press release here recently regarding the Nature article. I'm just curious, how big of a contributor is that market today for you? And how should we be thinking about that over the medium and longer term? Do you see that becoming a much bigger driver?

You mean all of material science, not just the sector that's covered by the Nature paper, correct?

Correct. Yes. Yes, just beyond pharma and biotech, yes.

Good. Yes, yes, yes. So, I think you know we reported at the end of -- well, at the end of '25, we reported what fraction of our revenue was material science already. But we see material science, we're still -- material science companies are a little bit behind pharma biotech companies with regard to adoption of computation, but that's changing. That's definitely changing. We can clearly see -- I think it's possible, by the way, that material science companies are seeing the success of deploying computation in drug discovery, and they're increasingly adopting sort of predict first, calculate first mindset, and we're seeing that. So, we believe that the TAM for the business is quite large, and we're still sort of in the early days of fully realizing that TAM. Pat, do you want to add something?

Yes. I think it's also really important to note that because they're earlier in the technological adaptation, we spend a lot more time early on in services, helping them predict the exact properties they want. It's not quite as cookie cutter as life science. But this is a place actually where Bunsen can be really transformative because they'll potentially be able to get more done with off-the-shelf solutions, whereas in the past, to predict a novel property in the giant world of materials, you might have to spend months with us on services. And now Bunsen might be able to help you put together a workflow and build that property very quickly.

That make a lot of sense.

Your next question comes from the line of Evan Seigerman with BMO Capital Markets.

This is on for Evan. Just one from us. So, you described Bunsen as initially including a number of tokens and customers potentially having to purchase additional tokens as they launch more programs. As the beta progresses, what are you learning about token consumption and customers' willingness to pay and the potential revenue opportunity relative to the traditional software model?

I missed a few of those words. What asking about Bunsen?

The questions are on Bunsen -- engagement with customers and -- monetization model.

Yes. Okay.

I mean I can say that the engagement is going great so far, but I don't think we have anything we're comfortable disclosing in terms of increased token utilization or their comfort for paying more tokens or anything like that. It's just not something we can disclose at this time. But just to repeat how we're thinking about it is Bunsen will allow the customers to have more throughput and because we have throughput-based pricing, it will lead to more usage of our platform and our licenses.

Exactly. Did we answer your question?

Yes, that's fine.

Your next question comes from the line of Brendan Smith with TD Cowen.

Congrats on the quarter here. I appreciate all the color on the customer end market breakdown between drug development and material science in particular. So maybe just kind of a follow-up to one of the earlier questions here. Even maybe qualitatively, how much of that kind of 10% to 15% growth over the next couple of years, would you expect at least at this point to come from material science customers versus drug development if we kind of just draw some of those bigger buckets? And can you also -- as kind of a second question related to this, but you mentioned pretty solid growth from biotech and material science. But can you speak a bit more to any trends you're seeing kind of within that top 20 pharma bucket specifically? And just if there's any notable differences in order patterns from those guys versus the other customers?

Yes. I think you're hearing from us, of course, optimism about the future growth of material science. We see this as a huge opportunity for us. As we said, we're sort of still relatively early days with regard to the whole industry's adoption of computation, but we're very optimistic about what we're seeing. But we're not prepared right now to guide to what fraction of the growth will come from material science and life science. So -- but let me answer your question about the top 20 customers. We are -- even though we're talking about here growth from material science and growth from biotech companies who are in a better funding environment, there's certainly still significant enthusiasm among the top 20 pharma companies in broader adoption -- sort of bigger deployment of the technology. Bunsen has played a big role. There's a lot of excitement around Bunsen among the top 20 pharma customers. And as we've talked about before, there's still a fair discrepancy between the spend of -- annual spend among the 20 pharma customers. So, we still see big opportunities to get pharma companies that are maybe on the sort of lower half of that spend up to where our top handful or 10 pharma customers are. Richie, anything to add to that?

Your next question comes from the line of Scott Schonehausse with KeyBanc Capital Markets.

This is Steve on for Scott. Just maybe a little bit more color on where you are in the ramp, number of users for both Predictive Tox and Bunsen.

Sure. Yes. I mean we can't disclose the exact number. What we can tell you is, first of all, Bunsen, remember that we're still in the early access program. We expect to have the open beta this year. So -- as we said, that's going really well. A lot of enthusiasm, maybe more enthusiasm than we've seen for a really long time with the new technology. With regard to Predictive Tox, we've had quite a number of companies evaluating the technology. It has contributed already to ACV this year, predictive tox. One of the things that we're really excited about is the advancement of the method itself. As we reported today, we've increased the number of off targets to 80, which is approaching the goal that we actually had for this time period. We think that there is a sort of critical mass of off targets that are required in the sort of off-target Tox panel where we see that once you have a certain -- you have enough, then there is a much higher chance that the off target that's a potential issue will be in our panel and that we've enabled enough targets to have a sort of complete solution. So yes, so that's great to see the improvements to the technology and the quality of the results that customers are getting when they're testing it and that it's already contributing to ACV. But that's as much as I think we can say at this time.

[Operator Instructions] Your next question comes from the line of Kevin Caliendo with UBS.

This is Tucker Remmers on for Kevin Caliendo. I first wanted to ask about drug discovery revenues. And I think you've had a couple of guidance raises because of some milestone payments through the year, the most recent one being from Structure. So, my question is really, how can we model the drug discovery upside more effectively on a go-forward basis? And maybe you can point to some programs that you can see on the horizon where you have some upside drivers to your current expectation.

Yes. Thanks for the question. We outlined a 3-year view on this, which is $150 million of revenue over the next 3 years. Obviously, there's a baseline there kind of roughly $50 million a year. Some of this year's performance, as you noted, has been driven by some milestones. We had a milestone associated with the Ajax sale and a milestone associated with structures advancement of the amylin program. So that is kind of the way that we think about it. We are executing across our collaborations that creates a baseline revenue expectation for us. The milestones are harder for us to have visibility into, but we obviously had a track record of our equity positions and our milestones kind of contributing to drug discovery. So that is the way that we build it out in our minds. It's worth noting that business development activity is a contributor to our overall drug discovery revenue outlook. Tectora is not only a company that we form but is also contributing to drug discovery revenue because we are collaborating with Tectora to advance the programs there. So that's kind of how we think about the building blocks around that.

Yes, nothing to add. I mean I think on Slide 15 and 16, you can see the portfolio and there's a bunch of preclinical programs and clinical programs, and it's really hard for us to say when those milestone events are going to discussed.

Yes. Fair enough. And then my other question would just be on the predictive toxicology. So, when I think about your solution in the broader context of like think of like a Charles River that's a big Safety Assessment toxicology player, is the road map really that you can take a large swath of that market away from the in animal in model testing? How far away are you from that? Or is it -- is your solution more of, hey, we're going to kind of middle on bits and pieces of that market?

Yes, that's a really good question. No, we don't see -- we don't see the solution in that way. This is a solution that's meant to be used way earlier in drug discovery programs than what's typically done using experiment and what's done with Charles River. What happens now is that drug discovery projects because it's very expensive to be testing every -- the toxicity of every molecule sort of progress through lead optimization to a point where the molecule is potent enough and has all the properties that are good enough to start testing it. And you get pretty far in project years actually into a project. And then the toxicity is tested. And if it's discovered to be toxic, that's it. Go back to the starting point. The idea of this technology is to use it way earlier in drug discovery as part of the optimization of a molecule so that when you get to the end, when you get to close to a development candidate or a development candidate, you're much, much more likely to have a molecule that's actually safe when it goes into the experimental testing that Charles River and other companies perform. So, this is really creating a new market for a solution that didn't exist before. There was no way to, on a very large scale, test the potential toxicity of molecules early in discovery. That's what is so -- what is exciting the industry around our solution. I hope that makes sense.

Yeah, understood. That is very helpful. Thanks for taking the questions.

There are no further questions at this time. This concludes today's call. Thank you for attending. You may now disconnect.