Thank you. Good afternoon. I'm Michael Yee, Senior Biotechnology Analyst at Jefferies, and I'm really pleased to have members of the executive team of Schrödinger up here. I believe in order here down on the far left, there is Karen Akinsanya. Many of you know her as s he's President R&D at Therapeutics, and we're going to talk a little bit about some data on MALT1 and what could be coming in the pipeline,. O bviously, Margaret Dugan, CMO. We're going to ask her a little bit about the plans as well for the development. And then Richie Jain, who's the CFO of Schrödinger. I'm going to ask you lots of good questions about software and where the business is going. Maybe, I don't know, maybe we can start off with Richie first.
I mean, Richie, you're now in the role, you've been at Schrödinger, but now obviously in the former role of CFO. Maybe you could just tell us a little bit as an introduction to Wall Street about your experience at Schrödinger and particularly what you're going to focus on here in the seat as CFO, newly appointed CFO at Schrödinger here in the middle of the year and how you're feeling about the business this year.
Great. Thanks, Mike, and thanks for hosting us at the Jefferies Healthcare Conference. Yeah, I've been the CFO for a few weeks. I joined Schrödinger last year in 2024, previously an investment banker at Morgan Stanley in their M&A and healthcare business. To your question, Mike, from my time at Morgan Stanley, I've made a lot of relationships across the pharmaceutical industry and been able to leverage those relationships as I've joined Schrödinger. My previous role was focused on business development and strategic finance. This role obviously is a bit broader. Yeah, we're focused on executing against the year. We're really excited about our ability to grow the software business and some of the new initiatives we have around predictive toxicology.
Fantastic. As I was reminded too, since I think you're kicking off, there were some slides you wanted to review too. We can do that, and I think you have the clicker.
Okay, great.
I think he might be loading them, but.
Can I just get up here a second?
Oh, they were up there.
Just one second.
One second. While they're loading that too, maybe just an introduction too, while we get that loaded. Obviously, Karen and Margaret, I think Margaret, this is the first time we've done a fireside together too. Maybe some introductions would be great too while they're loading up the slides. How long have you been at Schrödinger?
Can I press?
You're welcome.
Oh, Margaret Dugan, CMO at Schrödinger for the past two years. Prior to that, maybe 30 years in industry doing early and late phase drug development. Currently the CMO and responsible for the three proprietary phase I agents that are in the clinic.
Okay. And then Karen as well. Many know you, but.
Yeah. Karen Akinsanya, I'm President of R&D for Therapeutics, and I recently took on a chief of strategy role for Partnering.
Fantastic. Okay, perfect. We have the slides up now, so we should be able to give an overview and some of the key highlights as well.
Okay, great. Yeah, we'll just do a couple of quick minutes and then we can get back to Q&A. We'll skip the forward-looking statements and just refer you to our filings. So we're a digital chemistry lab for molecular discovery. This is broadly applicable to the life science and material science end markets and customers. Our approach is based on a physics-based methods approach, which is really what we feel is the best way to understand how a molecule interacts with a target in various situations. This approach is very accurate, but it's not the fastest way to do it. Combined with AI and ML tools, when you combine the accuracy and the speed, this is what allows you to extrapolate into novel chemical space and predict highly optimized molecules. The platform is the main asset of the company that we continue to invest in.
We have a multi-pronged approach to monetize that platform, and we've seen really impressive proof points in each of these three elements of the business. Our software is broadly utilized by the entire pharmaceutical and material science industries. We continue to roll out new initiatives and expand our adoption with these customers. On the right side of the page, we have a wholly owned proprietary pipeline of eight disclosed assets, three of which are in phase I oncology programs, and Margaret will give an update on one of those later in the presentation. In the middle of the page is really how we bring the business together. It's deploying our platform at scale with our highly talented scientists, and we partner with pharmaceutical companies to jointly develop molecules together. This takes the form of upfront payments, equity ownership, milestones, and royalties.
In terms of our recent highlights, Q1 was $59.6 million of revenue, of which $48.8 million was in our software business. That grew 46% year- on- year. The remainder of the revenue, $10.7 million, was drug discovery revenue, and we finished the quarter with $512 million in cash, inclusive of the $150 million we received from Novartis in a deal that we announced late last year. Our guidance for the year is unchanged, 10%-15% revenue growth, $45 million-$50 million of drug discovery revenue, less than 5% operating expense growth, and our Q2 revenue estimate is $38 million-$42 million. In terms of our priorities for the year, as I mentioned, we continue to increase the adoption of our technology with customers and close some of the adoption gaps that we see between our largest and medium-sized customers.
We are working on enhancements to the platform, most notably our predictive tox initiative, which allows us to dial out liabilities in early stages of drug discovery to reduce costs over the timeframe of development and improve the probability of success. We expect to read out data from our three clinical programs this year and then focus on advancing the remainder of our proprietary programs and executing on our collaboration projects. 1505 is the first asset that we are going to read out. The abstract was published a few weeks ago, and we have a webcast scheduled next week to give additional information on that program. Margaret, our CMO, will give an overview of that abstract.
Thank you. The phase I study is a first in human study that was conducted with our MALT1 inhibitor 1505 in heavily pretreated patients with relapsed refractory B-cell malignancies. What we have demonstrated in our abstract and then in the poster that will follow is that 1505 is safe and well tolerated. There are no dose-limiting toxicities that have been observed, nor treatment-related serious adverse events, nor AE-related deaths. We have asymptomatic indirect bilirubin lab abnormalities which were common and predominantly grade one and two. We have dose-dependent increases in exposure that have been observed. We are encouraging preliminary monotherapy activity. Out of the 33 patients that were enrolled, we have 23 evaluable patients that were reported in the abstract. As you can see on the waterfall plot, we have categorized them by either CLL or SLL versus Waldenström's, and then the last category is the remaining patients that had been enrolled.
You can see from the waterfall plot, the majority of these patients have had some tumor shrinkage, and this is translated into one PR, two PRs in CLL, two MRs in Waldenström's, and 12 stabilization of disease. The PRs were observed in CLL and Waldenström's, and we were looking forward to presenting the data at EHA and ICML. Thank you.
Can we ask questions on that? Is there another slide? Yeah, I mean, that would be a great segue. At EHA, because this is the abstract, what additional data would we expect from the 23 patients? Will there be more patients, more follow-up? What is coming at EHA?
Right. The data cut off from the abstract versus the poster, we have three more months of follow-up as well as three more months of enrollment.
Okay. There'll be more patients.
Correct.
More follow-up. Okay. Based on this, what is the takeaway? We looked at this and the market looked at this, and the market says, "Looks like there's evidence of activity. Hard to interpret because it's early." What is the takeaway?
I think continuing with what we've been able to do, we've further built upon these conclusions. We will have more patients on the study and more level of activity that we'll be able to present. I think the conclusions here are that we are seeing preliminary activity as a single agent, although the patient numbers are small, not enough to make definitive conclusions in overall response rates. We're safe and tolerable, so we are an agent for a MALT1 inhibitor in terms of delivering it as a single agent and potential combination approaches.
Okay. Karen, you look like you're going to say something.
Yeah. I mean, I think we've obviously been talking about MALT1 for a while with you, Mike. One of the most important things that we wanted to see from this study was whether MALT1 as a mechanism itself could be safely administered. We all know that the prior disclosures around this target, there were evidence of dose-limiting tox, cardiorenal issues, which we believed, and I think many felt, would prevent or prohibit the combination with BTK inhibitors. We are very pleased to be able to provide this update, but also a further update around the safety. The safety that we think is key. We think this positions MALT1 as a potential partner to BTK, BCL2 that we've previously demonstrated in preclinical studies, and that it could be part of an all-oral regimen in the emerging landscape of fixed duration therapies, moving towards MRD.
Obviously, this is early data, as you said, coming out of a dose escalation trial. The conclusion here is I think we are very close to having a package that allows us to go to the FDA and align with them on a recommended phase II dose. We are pretty excited about that.
When you report this data, I guess next week is what you're saying, and then it's mostly similar data at ICML, which is actually two medical conferences you have. I think Wall Street would look at this and say, "Active, some evidence is of," quote, "partial response based on research criteria," but that the landscape is tricky because in CLL, there are existing agents. Now, most of those is dominated obviously by BTK. There's not a whole lot of stuff in second line. In DLBCL, there's definitely a lot of different things going on there. This is not clear that it's a monotherapy type of evidence of a single agent, got to get that as monotherapy.
It looks like it's adding things, but not necessarily how do you get that approved because either the overall response rates are numerically not high enough or the CR rates or just it's competitive. What is the message that we want to definitely take this into the second stage, which is added onto stuff because you need to show that stuff is safe in combination before we can go run pivotal studies? What would be the next step?
Yeah, I mean, Margaret should share her thoughts on study design and what we might be doing as a next step, but I would say that certainly you're right on. We wanted to see monotherapy activity from this mechanism to show that it's contributing something to the combination. One other point that I think Margaret touched on, but is also written up in the abstract, is a lot of these folks had failed BTK or BCL2 inhibitors. We think that provides an opportunity for MALT1 in combination with BTK, BCL2 as part of a new regimen in combination. A combination study is something we've been focused on for a while. We think we now have the package to allow us to move to that next step.
Are you implying because currently in CLL, they get a next generation BTK as first line, that's BeiGene and others. In second line, there's more limited, I don't think that they get another BTK, right?
No. Right.
There are limited options. Would you think that, hey, the optimal design here is in combination with a BTK versus a BTK alone and that that's going to have added PFS because the response rates on BTK are super high?
They are.
Yeah. How do you prove that this is going to be clearly evident as a drug because it needs to be combined, which means combined needs to have better efficacy than the single agent? How do we show that?
Yeah. First of all, I think that there is a commercial path that one might take, which I think you're alluding to, is how do you get the drug registered? Our immediate focus is on showing the signal for combination. To your point, the higher the response rate that you see in that indication, the more difficult it is to show that. That plays into the question of where we will be seeking that combination signal. Ultimately, how does that play into the commercial opportunity? Margaret, do you want to add anything here?
Right. I think what Karen is saying supports what you were also saying, that in the combination approach, the agents that are being used in relapsed disease are still also giving high response rates and durable response rates. We're going to look for those indications where we can combine it and, as you suggested, extend the duration of response, maybe make deeper responses, turn some of these into complete responses, or a better PFS. That's what we're starting to examine.
What is the common second line agent in CLL that you'd try to beat or would you add on?
There are so many agents for CLL, we probably have to go further down the line.
Okay.
Right. Yeah. You've got BCL2 inhibitors.
BCL2s. Okay.
Right. BTK, BTK degraders, BTK inhibitors.
Good. Okay. Okay. The next step is present this data, and then you're having a webcast or whatnot, so you would guide to the next steps. Is this something that would be going into a phase II in combination studies, safety phase I/IIs in combinations for 2026, and then let's guide the development from there? That would be the plan?
Yes. We believe we have a very robust package. The next step in this kind of phase one development would be to approach the FDA and discuss what that recommended phase two dose is and to discuss combination approaches.
Okay. Maybe following along that, since we have the two R&D folks here, this is one of the three programs that are in the clinic. The second one, maybe you can tease us with it or whatnot, but where would that be? Which one is it going to have data? When would that data be? Tell us why that would be better. I'm not sure if it's the Wee1 or the CDC7, but.
Next up is CDC7. That was the second one into the clinic. The dose escalation study has been ongoing. We're collecting data there. We do expect to provide an update of that phase I study this year. We were guiding to second half of the year on that particular program. The third program into the clinic was the Wee1/Myt1 co-inhibitor. That's obviously a lot earlier. While we're saying second half of the year, the question is, you know, what kind of venue would that be? That's to be determined. Yes, an update on the progress of those two phase I groups.
If we have CDC7 data later this year, what would we be looking for there? Because the history of CDC7 is a little bit mixed. I'm going to have to dig out some old posters. This is a solid tumor situation. What would we be looking for? What's good data?
Oh, right. Margaret, you should.
Right. For this agent, we went into AML where the preclinical data supported that that would be the better place to start with the drug. We are in a phase I in relapsed refractory AML. We have been looking for a good therapeutic index to demonstrate some responders, PR, CR, and a good safety profile.
Okay. So this phase one AML monotherapy, looking for evidence. Now, in phase one, it's a little tricky too because you can get responses, but then it's got to be durable. This is about safety first. Is there something specific in phase one that you would look for that says, "Aha, this is particularly better than the other CDC7s"? Like with this, what was important is that J&J had a lot of tox. You've clearly shown that you have evidence of activity and a therapeutic window that you can push forward. With CDC7, what was the issue there and what can you show in phase I that says this is better?
For CDC7, the standard toxicology would be cytopenias as well as GI tox. We would be looking for those. We're looking for CR and PRs as evidence of activity.
Did the prior one have tox or just low efficacy? What did you solve for to make your product better?
Yeah. The prior CDC7 inhibitors were either not very selective or they were unable to optimize the dose and regimen. Off-target tox, obviously the heme tox is part of cell cycle inhibition, but essentially people staying on drug was one of the biggest challenges in order to be able to derive efficacy. We believe in this phase one study, we'll be looking to see people staying on drug, people actually tolerating the drug well. At the same time, in the case of AML, we're looking for blast count reduction. Are we doing well in terms of controlling the disease? Ultimately, we'd be looking at durability. Of course, this year, I'm not sure.
First generation ones were not super potent. Were not as specific and selective. Obviously, like in many AML drugs, we're looking for blast count reduction, safety, efficacy. It's early. You don't know everything in phase I for AML versus say solid tumor. We're going to look for that. Okay. Let me maybe just tie those together because I think part of investors looking at Schrödinger are trying to understand the power of the platform. Now, on one side, it's as there's an angle that perhaps, again, I think relevant in today's market that the FDA and the world are coming to appreciate AI and how that could be in drug development. Jefferies had a nice 60-page report on this.
Also, the FDA recently came out and said that for preclinical antibodies, that sponsors could use AI for antibodies and kind of skip over non-human primate or other things. I think it's a little bit unclear, but that's something they've publicly come out and said. Now, you have your predictive tox software. Can you tell us about that and where is that? And can that generate revenue soon? And how will that be used for people in this AI environment?
Yeah, I'll cover that. We've been working on predictive tox for several years now. We have published several papers on this, most notably around hERG and the ion channel in the heart. This has been an internal project that we've now received some external funding from the Gates Foundation as well as a partnership with NVIDIA. We continue to build out this technology. It's a multiple-year build. We're at the stage of being able to beta test this opportunity with some of our pharma partners. We've had some great conversations with them. I think what we do is bring a structure-based approach to identifying off-target liabilities versus more of a yes/no binary outcome that a lot of them see on their own. We haven't gone to the point, Mike, of estimating revenue opportunity here.
I think we're still in the stages of testing the technology out with our partners and getting feedback from them. Once we have a sense for the value that we're creating, I think we'll then get to pricing. For this year, we have not included significant expectations into the revenue, but it is something that we would look to include for future years.
It's currently in beta though.
It's currently in beta. Yeah. And just one clarification on the FDA announcement, it kind of included antibodies and other approaches, but certainly small molecules are in scope for their announcements.
In other words, we're just waiting for them to sort of make it more clear or publish that they are going to because they come for the antibody when they put out a press release or something on this thing.
Yeah. I mean, I think there's actually been a roadmap for the 3Rs initiative to replace, reduce the use of animals, both in the use of the testing of biologics, but also for the testing of small molecules. The fact that we have these highly accurate digital assays, let's call them, we think has broad applicability both to biologics and to small molecules. Our ability to essentially test all species at once, I think, is very challenging to do empirically in the lab, but something that we believe will be an obvious fit for some of the initiatives, the objectives of the initiative.
Maybe just one other point, Mike, which is the way we have started to think about sizing this opportunity is today, you are optimizing a molecule to hit one target. This opportunity is increasing that by a couple of orders of magnitude to model out hundreds of off-targets. We do see a significant increase in the amount of computation and throughput that our customers would need to use this technology.
Maybe tie that together with this idea that this is an additional application, additional opportunity beyond your standard software platform. Talk a little bit about how big pharma, big biotech are embracing the platform because one of the things that we've been getting some questions on is, hey, look, the drug discovery stuff, we get it. If you have a wholly owned drug, you've come off your platform, it's showing clear efficacy, billion-dollar opportunity. Biotech analysts are experts at valuing that with the software, steady growth. We would like to see either greater adoption or more clear evidence of what's going on there. Do you have any comments about either revenue contract size, other things that have been going on?
I'd like to say that the Novartis deal that you signed in Q4 is like an evidence that a big pharma company is embracing it more completely across the platform. Maybe just talk to examples or metrics that you're looking at because there is steady growth, but it was not like, to be fair, that the company was blowing out quarters on software. Wall Street's been struggling with that a little bit.
Yeah. Maybe we'll tag team it. I think from a metrics point of view, we look at ACV as a metric. We have eight customers greater than $5 million annual ACV, 31 customers greater than $1 million of ACV. Obviously, that implies that there are many large pharmaceutical companies that are not adopting the technology at scale the way that the leaders are. There are also many biotechs that have a fraction of the budget using the technology at a greater scale than large pharmaceutical companies. That is a big focus of ours, converting those customers, current customers, into using our tools at full scale, full throughput, and also using some of our visualization tools, namely LiveDesign.
Mike, the predictive tox initiative is another way to engage with these customers and show them the capabilities that we have and introduce them to our broader suite of discovery tools.
Talk about the guidance then. The guidance is 10%-15% this year. It's been steady, 10%-15%. Is there either an obvious opportunity for that to accelerate? I go back to, yeah, Wall Street's been seeing steady growth, but the company has been quite bullish on this broader adoption. I'm not saying that you're going to see it in one quarter, but there's metrics that have been seen that it's more revenue per customer that's been going up because the number of customers that you have is, you know, you've got thousands of customers already, but it's more about the big guys going from $1 million to $5 million or more people going over $1 million. How has that been? You talked to Rami,
he would say, well, it takes time because you sit there in front of Merck. A nd Merck's got to take time to adopt it across the whole platform. Take a look at like Novartis. Novartis signed a big deal. So they clearly are implementing that across a lot of the portfolio. What would stop Merck or other people from just doing it more broadly, which would drive bigger revenues?
Yeah. I mean, I think it's hard to speak for other companies.
Generally, when you sit there and look at some of these big pharma companies.
Yeah. I think adoption remains the challenge. I think for us and many other players, just changing the way pharmaceutical companies do drug discovery is a challenge. I think particular to our business as well, we have some contracts that are annual, some contracts that are multiple year. Typically, these conversations around changing the way they think about drug discovery will happen upon a renewal. Mike, that's one of the factors that we look into when we set revenue for the year, is what opportunities do we see in front of us with our customers, but then what are the timing and cadence of renewals? That's kind of one of the factors we think about with setting expectations for the year versus what can occur over the next couple of years.
Right. Right. That's why the fourth quarter is such a big part of that wildcard swing is because that comes up with the most renewals because the most contracts are in that number. Actually, to be fair, the fourth quarter has been a beat for the last few years. Maybe just if I could also pull together this idea that looking at the next year's P&L this year, but also next year, you have 15% revenue growth. Your OpEx is going to be particularly focused around how much money you're spending on 1505 and driving these other things. I mean, these cost tens and twenties and thirties of millions of dollars to run studies. That has not been in the OpEx a year or two ago because they were preclinical. What does the P&L structure look like?
Certainly, there's no stated commitment to necessarily be profitable in any sort of quarter coming up. How should we look at that? Because as a loss-making company, technically, we're looking at cash burn, but you've got programs that are valuable, but also now the R&D is picking up. How should we think about your financials? Are we trying to get to profitability?
Yeah. I mean, profitability is always something that we look at. I think what you've seen we've done in the last few weeks, we've done an expense reduction that was really focused on making sure we're focused on our top priorities. For us, that's investing in our platform, investing in capabilities that will be relevant to our software customers, and investing in our proprietary assets. Just by way of context, we've grown considerably since the IPO in 2020, and the OpEx has increased along that period. I think we're now at scale as it relates to the business, but we continue to have flexibility to invest where we see opportunities, where we'll capitalized with our cash position and, again, continue to, we think we're at scale on OpEx, but having the ability to invest where we see opportunities.
When you say we're at scale, I feel like we're at that level. Yet, I feel like just to be clear, and certainly we're modeling that R&D is going to pick up meaningfully because you're running more clinical studies that cost a bunch of money. Am I thinking about that wrong? I actually think that you're actually taking a hard look at OpEx or that it's not growing that fast despite going to the clinic. You're getting operating leverage or how do I think about it? Scale, I'm not familiar with that term.
I mean, I think you're kind of addressing both parts of our business. I think on the therapeutic side, we're going to continue investing in our assets. You don't get operating leverage there per se. We're investing in outcomes and catalysts. On the software side of the business, I think while we don't measure profitability, we measure it at gross profit, but not below that. We do see operating leverage opportunities where the revenue is growing faster than the investments we're making in the platform.
In the software.
Correct.
Have you ever said the gross margins on software and operating if that software business was to be carved out or as a separate P&L? I get this question a lot, and it's an important one.
Yeah. No, it's a great question. I think our guide for the year is 74%-75% on gross margin. We've said in the past that if you look at our R&D, roughly half of that is affiliated with the software business, roughly half with the therapeutics business. So you can get a sense for it externally, but it's an important metric. We definitely are focused on it.
If I could just add another thought on the R&D cost though, I think over the last five years, we've had a steady stream of business development deals, and that is an important part of our strategy, not necessarily waiting until the clinic or advancing things on our own in the clinic. Last year, a huge part of the Novartis deal was a program that unfortunately we didn't talk about with you that was super exciting and that we ended up transacting with Novartis prior to disclosing it. That was a preclinical program that brought in a very significant amount of cash to the company. We see that opportunity, obviously, with all of our assets at every single stage of their discovery or development. Of course, we believe the more mature the asset, the more valuable they are.
This is part of our strategy is to bring in cash to the company and mitigate spending by doing partnerships.
To be fair, have not raised money since the IPO in public offerings. Very good. Thank you guys very much. I appreciate the time and we look forward to next week.
Great. Thank you.