Thank you for standing by. Welcome to Schrödinger's conference call to review First Quarter 2025 Financial Results. My name is Calvin, and I’ll be your operator for today's call. Please be advised that today's call is being recorded at the company's request. Now, I would like to introduce your host for today's conference, Ms. Jaren Madden, Senior Vice President of Investor Relations and Corporate Affairs. 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 first quarter 2025 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. Here with me on our call today are Ramy Farid, Chief Executive Officer; Geoff Porges, Chief Financial Officer; and Karen Akinsanya, President of R&D Therapeutics. Following our prepared remarks, we'll open the call for Q&A. 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 financial outlook for the full year 2025 and the second quarter 2025, our plan to accelerate the growth of our software business and advance our collaborative and proprietary drug discovery programs, the timing of initiation of and readouts from our clinical trials, the clinical potential and properties of our compounds, 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 considerations described in the Risk Factors section and elsewhere in the filings we make with the SEC, including our Form 10-K for the year ended March 31, 2025. 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. And with that, I'd like to turn the call over to Ramy.

Thanks, Jaren, and thank you, everyone, for joining us today. We are pleased with our progress during the first quarter, which builds on the positive momentum from 2024. Our software and drug discovery revenue demonstrated strong growth. We are confident about our revenue outlook for the year and are reiterating our full-year financial guidance. We are having productive discussions with customers and are encouraged about the opportunities for increased adoption of our software, even with the potential challenges of the macroeconomic environment. Total revenue for the quarter was $59.6 million. Software revenue was $48.8 million, representing 46% growth. Drug Discovery revenue for the quarter was $10.7 million, with growth driven by milestones from collaborative programs and the recognition of upfront revenue from our collaboration with Novartis. We are encouraged by the FDA's recently stated goal to reduce preclinical animal testing. We have been pioneering computational molecular discovery for nearly 35 years and continue to develop new solutions that integrate physics with machine learning to accelerate the discovery of safer drugs. We already offer our customers solutions that can be used to reduce the potential for toxicity associated with binding to off-targets. We're also continuing to advance our predictive toxicology initiative. We have structurally enabled more than 50 off-targets and have been leveraging this technology within our collaborative and proprietary programs with highly encouraging results. We expect to proceed with a beta release of this solution to select customers later this year and expect to make it broadly available to customers once beta testing is completed. We are optimistic about its potential to contribute meaningfully to our long-term revenue growth trajectory. We are also continuing to advance the science underlying other aspects of our platform. This week, we released our second software update of the year. Major enhancements include new crystal structure prediction software to identify stable crystal polymorphs, which has important applications for drug formulation. And we have also expanded support for protein degrader modeling and launched new capabilities to enable machine learning-based T cell receptor structure prediction, which is important for biologics discovery. We are also continuing to advance our collaborative and proprietary pipeline. We look forward to sharing initial Phase I data from our three lead clinical programs, starting this quarter with SGR-1505, our MALT1 inhibitor. Overall, we are well-positioned to advance all aspects of our business in 2025. This is a pivotal year for the company, and we look forward to providing updates throughout the year. I will now turn the call over to Geoff.

Thank you, Ramy, and good afternoon, everyone. We're very happy with our financial results for Q1. Software revenue growth was robust and drug discovery revenue was higher than last year as we benefited from the recognition of revenue from our collaboration with Novartis as well as the recent expansions to other collaborations. Our operating expenses declined year-over-year, and our cash position was boosted by collections from contracts closed late in Q4, including receipt of the upfront payment from Novartis. Our financial position is very strong, and our business is relatively protected from the turmoil that we are seeing in the capital markets and across many parts of the economy. Our technology continues to prove its value. And even in these challenging conditions, our customers are increasing their investment in our platform, enabling them to meet their innovation goals at lower costs with better outcomes. We remain very positive about the outlook for the year and are excited to be advancing towards our first clinical data disclosure this quarter. For Q1, total revenue was $59.6 million, an increase of 63% compared to Q1 2024. The increase was driven by higher software and drug discovery revenue. Software revenue was $48.8 million and increased by 46% compared to Q1 2024. The increase was driven by increased revenue from larger customer renewals in Q4 that were partially recognized in Q1 as well as early expansions and additions to pre-existing multiyear contracts and the increasing contribution of recurring revenue from hosted software contracts. As expected, most of the growth in our software revenue came from the increasing scale of deployments at global accounts. The growth contribution from new accounts and small and emerging biotech customers was minimal. On-prem software increased by 44% to $25.4 million, and hosted revenue grew by 52% to $10.9 million. Maintenance revenue increased by 15%, and growth was lower due to the continued effect of the transition from on-prem to hosted contracts in prior periods. Professional services revenue declined by 31% as service contracts from prior periods were completed, and contribution revenue was $3.8 million this quarter as we continue to recognize revenue from the Gates-funded Predictive Tox project. Drug discovery revenue was $10.7 million, compared to $3.2 million in Q1 last year. Revenue this quarter was increased based on recognition of the upfront payment from the Novartis collaboration and from other recently expanded collaborations. Software cost of revenue was $13.5 million in Q1, compared to $8 million in Q1 of 2024. The increase was due to the expenses associated with the Gates Predictive Tox Initiative. We also recognized increases in royalties associated with the Novartis software license and collaboration. Our software gross margin was 72%, compared to 76% in Q1 2024. The lower gross margin was due to the change in revenue mix associated with the Gates grant. Apart from this effect, software gross margin would have been consistent with the prior year. Drug discovery cost of revenue increased from $9.7 million to $14.9 million, with the increase being driven by the higher costs associated with the initiation of work on the projects in the Novartis collaboration, as well as increased allocation of research staff to collaborations overall. Our overall gross margin was 52% and was very similar to the overall gross margin in Q1 2024. R&D expense declined from $50.6 million in Q1 last year to $46 million in Q1 2025. The decrease was due to the shift in allocation of staff from proprietary drug discovery to collaborations, and also lower preclinical CRO expenses for proprietary programs that have advanced to the clinic, all being discontinued. Sales and marketing expenses increased by 2% to $10.4 million based on slightly higher FTE expenses. G&A increased by 1% to $25.8 million, driven by slight increases in professional services. Total operating expenses were $82 million, compared to $86 million in Q1 2024. The reduction was mainly due to lower R&D. There were no gains in equity method investments in the quarter, and the change in fair value of equity method investments was a loss of $13 million based on the mark-to-market of our shareholding in structured therapeutics. This compares to a gain in value of $8 million in Q1 of 2021. Other income was $4.2 million in Q1, compared to $5 million in Q1 2024. The lower other income was due to a lower cash balance and lower yields, partially offset by a favorable effect of currency fluctuations on foreign currency balances. Total other expense was a loss of $8.9 million compared to a gain of $13 million in Q1 last year. Taxes were minimal, resulting in a net loss after taxes of $60 million or $0.82 a share, compared to a net loss after tax of $54.7 million or $0.76 per diluted share in Q1 2024. The fully diluted share count for Q1 was $73 million, compared to $72.3 million in 2024. Our net operating cash flow was $144 million in Q1, compared to cash use of $39 million in Q1 2024. The reversal of our quarterly cash burn was driven by the receipt of the upfront payment from Novartis in Q1, as well as collections of other receivables that were outstanding at year-end. Accounts receivable declined by $215 million between year-end and March 31st, and as a result, our cash marketable securities balance increased from $367 million on December 31st to $512 million at the end of Q1. Current liabilities decreased by 14% and total deferred revenue declined by 5% and remains at $210 million. I'll now provide some comments on the risks and opportunities for our business associated with the ongoing political and economic uncertainty. Schrödinger's technology and business is built on a licensing and use platform. As such, at the present time, we do not expect any direct impact on our revenue outlook from US tariffs. It is unclear what form of tariffs or trade barriers could have, and for that reason, it's impossible to forecast if or when they could have a meaningful impact in the future. We are aware of the risks of new tariffs being applied to the pharmaceutical industry and the impact they could have on industry profitability. At this stage, we are not encountering resistance or reluctance to purchase in our customer conversations. But of course, we are watched carefully for new policies or regulations that might affect the industry's outlook and R&D investments. Our direct exposure to revenue from China is small, with low single-digit percentages of our revenue for software in 2024 coming from entities based in China. Although our software is ubiquitous in academic institutions, our revenue from that segment is also small, with US academic institutions and government-affiliated organizations, such as the NIH, contributing less than 4% of software revenue in 2024. Additionally, we are encouraged by the FDA's public statements about the importance of adopting alternative approaches, including computation for drug discovery and development, and believe that our technology is uniquely suited to supporting these goals. While the uneven treatment of biologics and small molecules has been a headwind for our software sales in certain accounts in recent years, that headwind could also be reduced by the executive order regarding the duration of the non-negotiation period for Medicare Part D. Finally, currency has been a drag on our reported revenue growth from ex-US markets for several years. And with the changing exchange rate, we could see some modest benefit to our reported sales from international markets later in the year. Overall, the effect of these variables is hard to quantify at this stage, and they are largely excluded from our financial guidance for the year, although our quarterly guidance reflects our latest and highest confidence expectations for the near-term trends and outlook. Looking ahead, our financial guidance for the full year 2025 is unchanged. We still expect our software revenue growth to be 10% to 15%, and we expect drug discovery revenue to be in the range of $45 million to $50 million. We continue to expect our full year software gross margin to be in the range of 74% to 75% and expect our operating expense growth to be less than 5% for the year. Our cash burn this year is expected to be significantly below our cash burn last year and remain very confident about our current capital position and our long-range financial outlook. We expect software revenue in Q2 to be in the range of $38 million to $42 million. We expect that the majority of the year's remaining software revenue will be recognized in Q4, with the balance of drug discovery revenue likely to be approximately evenly distributed through the remaining quarters. To conclude, we had an excellent Q1 with strong financial performance, building on the positive announcements from Q4 and early in Q1; we remain very confident about the outlook for the year and see our business being relatively protected from the volatility and uncertainty affecting capital markets and other businesses and industry segments. We are excited about our approaching clinical data presentations and look forward to talking to you all about the first of those presentations in the coming weeks. With that, I'll turn the call over to Karen to discuss our therapeutics R&D.

Thank you, Geoff, and good afternoon, everyone. Our therapeutics team continues to advance our pipeline of collaborative and proprietary medicines. Across our collaborations, we are making important progress in the discovery of preclinical and clinical candidates for several high-value targets. We are pleased with the growing number of emerging new medicines designed using our platform across programs initiated at companies we cofounded, such as Nimbus, Morphic, Ajax, and Structure. As Ramy mentioned, this is a pivotal year for Schrödinger, with initial Phase 1 clinical data expected across three proprietary programs. Beginning with SGR-1505, our MALT1 inhibitor, our Phase 1 trial in patients with relapsed refractory B-cell malignancies is progressing, and we look forward to reporting initial clinical data from this study at the European Hematology Association Meeting in mid-June. As a reminder, this is an open-label dose escalation study. We plan to provide initial data describing the clinical profile of SGR-1505. This data cut will include safety, pharmacokinetic, and pharmacodynamic data across doses and schedules, as well as PK/PD relationship and preliminary efficacy data from patients across a number of B-cell malignancies and dose levels. We look forward to sharing the abstract when the EHA embargo lifts next week. The EHA poster will include additional data collected after the cut-off date for the abstract submission. Following EHA, we will also present data at the International Conference on Malignant Lymphoma taking place later in June. In the second half of this year, we expect initial data readouts from the ongoing Phase 1 clinical studies of our CDC7 inhibitor, SGR-2921, and of our Wee1/Myt1 co-inhibitor SGR-3515. SGR-2921 is advancing in a dose escalation study in patients with acute myeloid leukemia or myelodysplastic syndrome. We are also evaluating SGR-3515 in patients with advanced solid tumors predicted to be sensitive to Wee1/Myt1 inhibition, including ovarian, uterine, and breast cancer as well as other solid tumors. These studies are progressing well with multiple dose escalation steps completed. As with the SGR-1505 Phase 1 trial, the goal of the 291 and 3515 studies is to evaluate safety, tolerability, preliminary clinical activity, and to determine the recommended Phase 2 dose and schedule. We look forward to updating you on the progress of these studies later this year. Last week at the Annual American Association for Cancer Research Meeting, we presented preclinical data demonstrating that SGR-3515 showed improved anti-tumor activity in preclinical models compared with other known Wee1/Myt1 inhibitors. We also presented preclinical data showing how the dosing schedule for SGR-3515 can be optimized to preserve efficacy while also allowing for complete recovery from target-related side effects. Additionally, at AACR last week, we reported preclinical data for SGR-4174, our SOS1 inhibitor, demonstrating differentiated potency, selectivity, and drug-like properties, as well as evidence of monotherapy and additive activity in combination with MEK inhibitors or G12C KRAS inhibitors. These data, along with the well-tolerated profile of SGR-4174 in GLP tox studies support further development potential. Over the past three years, we have advanced several programs into the clinic and partnered some of our early-stage programs. We continue to see additional opportunities for value creation from our portfolio through out-licensing, new ventures, and collaborations. 2025 is poised to be an exciting year for Schrödinger. We expect broad pipeline progress and are very much looking forward to sharing Phase 1 data from all three clinical programs throughout the year. I'll now turn the call back to Ramy.

Thank you, Karen. As you heard, we are off to a strong start in 2025. I'm optimistic about the rest of the year and look forward to updating you on our progress. At this time, we'd be happy to take your questions. Operator, can you queue up the questions?

Operator, if you're speaking or somebody else is speaking, we can't hear anybody on our end.

Operator, can you allow us to speak, and we will read out the questions as they are submitted to us by email.

Thank you for your patience. We will now begin the Q&A session. The first question is from Michael Yee with Jefferies. Please go ahead.

Hi, guys. Great. Thanks for taking two questions. One is thinking about your first-ever presentation of your wholly on Drug Mall 1 coming up soon, maybe we'll guess which conference it is. But could you right-size our expectations around any meaningful single-agent activity? Do you expect it? What is good? Or is this about safety in combination with other therapies in lymphoma? Maybe talk a little bit about what is more important and what should we think about in terms of what is great? And the second question is financial maybe for Jeff. You've given guidance on cash burn this year, which is fantastic. If you continue to want to push forward on R&D for your cancer drugs, should we expect that to be a consideration for growing expenses and growing burn? Or would you consider other options? And when is the right time to partner? So, those are two important questions as we come up on this data. Thank you.

So, first of all, on the 1505 update, we are very pleased that we have both EHA and ICML abstracts. So, with respect to what we plan to share, we're really excited to share an update on the profile of SGR-1505. As you asked, we are providing an initial update of the dose escalation study. This is a dose escalation in a variety of B-cell malignancy patients, where we've been exploring safety, PK, PD, and initial science for activity. We're excited to present that. And we'll be providing an initial part of the data, which will be an abstract, and then obviously an update once the poster is presented in the middle of June.

And then, Mike, to your question about cash burn. We haven't guided to cash flow for next year. But I really think that we're in a position where we're maintaining optionality with respect to all three of the leading programs. As Karen pointed out, these are interim looks at ongoing Phase 1 studies, and those Phase 1 studies don't finish at the end of the calendar year. So, I don't see a scenario in which our cash burn goes up substantially next year. And we still have a lot of options with respect to those programs. So, without giving a specific guidance or range for next year, I think that we're in very good shape. And I don't see a significantly higher draw on cash next year than the investment we're making in expenses this year.

Perfect. Thank you.

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

Great. Thanks for taking the questions, everyone, and congrats on the quarter. I just want to actually ask about the upcoming predictive tox model that you referenced a few times now. So when you look at what the FDA is initiating with the new animal testing guidance and kind of the broader implications there, how should we think about potential points of differentiation for your offering versus maybe some of the other preclinical non-animal simulators that are out there today? And just any thoughts on how you might price this software relative to existing offerings that you have? Thanks.

Yes. Yes, we're obviously very excited about the FDA's goal of reducing animal testing. We're also, of course, excited about the solution that we've been working on that we've been using actually in a very prospective way, and our collaborative and proprietary programs. And what's differentiated is the same thing that I think differentiates almost everything that we do in our platform: we're developing highly accurate models that leverage both physics and machine learning, where we have the benefit of physics-based methods in the form of accuracy, very high accuracy in predicting binding to off-targets, and the benefits of machine learning, which is about being able to do it on a large scale. So we think that's what the differentiation is, accuracy, and it's the key.

Okay. Great. And any thoughts on how you might price it relative to what you do today?

Yeah, we have not talked about pricing as we often do with solutions like this is first get feedback from customers on the level of accuracy, on the impact, and then we make determinations on the price after that. As we said in our prepared remarks, we are going to be releasing it in a beta form to customers this year. So we will start to get that feedback and make a determination on the pricing following the results of the beta testing.

Got it. Okay. Makes sense. Thanks, guys.

Thanks.

The next question comes from the line of Mani Foroohar with Leerink Partners. Please go ahead.

Thanks for taking the question. Congrats on another great quarter. A couple of quick ones. Some of your competitors admittedly are more levered towards late-stage elements of drug development, have reported challenges with customer dynamics. They've pointed to large pharma companies delaying decision-making and some smaller players facing budget constraints hasn't shown through in your numbers. Could you elaborate a little bit on the trends you've observed year-to-date? And how you'd compare these dynamics versus what you're seeing where you play? And then I have a quick follow-up.

Sure. Yeah. Obviously, we're paying close attention to what's going on in the marketplace with all the noise, and I highlighted my preferred remarks. The small sort of emerging biotech segment, that's not growing. I think we're sort of level-pegging in terms of the customers that are growing, which is offsetting the customers that are declining. The new customers are offsetting the customers who are terminating their contracts and scaling back on their R&D. So I'd say we're holding our ground there, and then the growth is being driven by the large accounts. Interestingly, we are not seeing any bumps or pushback on our renewals, and that includes the software contracts that we have with some of the largest companies in the industry. They're actually going through restructuring, not just in response to all the issues that we're seeing right now, but for their own reasons because of their portfolio status and things. So we think that the level of spend on our software is small compared to the scale of their R&D budgets. I think they generally view this as necessary to have, not nice to have. And for those reasons, we aren't seeing that pushback, and that's consistent with the guidance that we maintain. So hopefully, that's helpful.

That is. And you have told me approximately 1,100 times that Schrödinger is not an AI company, but is a company that natively uses AI. That being the case, obviously, we've seen a lot of concerns around the incumbent industry being disrupted by AI fast followers, et cetera, even companies as large as Google and Apple in today's news. How do you think about threats that you might face from companies that are also native AI users? And how do you think about threats to your base business or growth, and what metrics do you follow to make sure that you are defending yourself from these emerging threats most effectively?

Thank you for the question. First of all, there is currently no evidence of any threat. We are very aware of what others are working on. It's also important to note that we have a deep understanding of the domain where AI can be applied, including its advantages and limitations. We have tens of thousands of users of our software and numerous internal programs, giving us a solid grasp of what is needed to advance these programs and make accurate predictions. Our fundamental belief is that machine learning is only as strong as its training set, and that will not change. This is a basic fact of machine learning that applies to technologies like ChatGPT, large language models, self-driving cars, image processing, and chemistry. No one can magically create a training set that will surpass the accuracy achieved with the physics-based methods we've developed over the past 35 years. Therefore, it’s crucial to maintain a deep understanding of the technology while ensuring we always utilize the most advanced techniques in both physics and machine learning.

Thanks, guys. I'll hop off. I know you've got a lot of other questions in the line.

The next question comes from the line of Evan Seigerman with BMO Capital Markets. Please go ahead.

Hi, guys. Thank you so much for taking my question. I want to follow up on some comments that you made, Geoff, around your conversations with your pharma partners. Let me ask differently; what could break their sentiment and maybe change their approach to investing in a platform like yours? Like what are they really looking for? And secondarily, when you look at the FDA guidance on reducing animal testing, can you just remind us what you guys have done in this space that contributes to this goal? Thank you so much.

What are customers looking for? We'll start there. What they're looking for is impact: is the technology allowing them to design better molecules with a higher success probability. And that takes a little bit of time to determine that and it requires using the technology on a really large scale, as we've talked about many times. So there's a little bit of a chicken-and-egg problem, where you have to be sort of convinced that the technology will have an impact in order to scale up the usage. But in order to scale up your usage, you need to be convinced that that's going to have an impact. So what we're finding is, of course, we succeeded in doing that quite a number of times, but what we're finding now is that something new is happening, which is the companies that are taking a little bit longer than other companies are to sort of break that cycle and start using the technology at a large scale are listening to those other companies. These companies now that are using the technology at scale and seeing this enormous impact are starting to talk about the impact of technologies having more widely. And we think that's going to start to have a really big impact on transforming the industry how companies deploy this technology at scale. But that's what it is: its impact, and that can either come internally from them using it themselves or, of course, by attending scientific conferences and seeing the impact that other companies that have scaled up are willing to talk about it. And that's just happening right now. So I think the other question you asked was about predictive talk, but I don't remember.

FDA animal testing. FDA's guidance on animal testing and what we have already versus that....

Yes, we believe that our focus on the predictive toxicity initiative will have a significant impact. We are already observing considerable effects on both our collaborative and proprietary programs. The success of preclinical studies, animal trials, and clinical outcomes is influenced by many molecular properties. We have multiple solutions addressing these aspects, including bioavailability, oral bioavailability, solubility, and efficacy. Efficacy, in particular, plays a crucial role in determining the therapeutic window, which will greatly influence success in both preclinical and clinical studies. Regarding predictive toxicity linked to off-target binding, we have solutions available for several critical off-targets. For example, we published findings on HERG, an ion channel that has caused significant disruptions in preclinical and clinical trials due to binding. We already have predictive solutions for avoiding major off-targets, and the goal of the predictive toxicity project is to expand from the one or two off-targets we currently address to hundreds.

And it seems that there are no further questions at this time. That concludes today's question-and-answer session in today's conference call. You may now disconnect your lines at this time.