Morning, everyone, and thank you for joining us on our next session. I'm Michael Yee, a senior biotechnology analyst here at Jefferies, and I'm very pleased to have the opportunity to introduce Schrödinger. The CFO, Geoff Porges, as well as Chief Medical Drug Development Guru, Karen Akinsanya, is here to give us an overview of Schrödinger. Jeff's going to come up and do some slides, and then we'll have plenty of time for some great Q&A. Thanks, Mike. Good morning, everyone. I'm delighted to give you a quick overview of Schrödinger. I'll move through the slides very quickly, and then we'll have hopefully plenty of time for a discussion with Mike. So, a cautionary statement: please refer to our SEC filings for a discussion of all relevant risks, where they're clearly articulated. So Schrödinger really combines two core elements to our technology platform. The company is built on the use of physics-based first-principle methods for predicting attributes of chemicals, particularly small molecules. There are advantages to using physics-based methods. They're very accurate. They can explore vast chemical space. But the disadvantage is they're slow and they're very computationally intensive. We combine that with the use of machine learning, or AI, and AI is effective at interpolation between data. It's very fast. It can handle very large data sets, but it's not accurate, at least with the same accuracy as physics-based methods. So we combine the two. We use our physics-based methods to create training sets for specific targets to identify novel chemicals that we then advance into further discovery. So with this platform, we capture value in three different ways. The first is we have a thriving software business. In 2023, that business generated $153 million in revenue. It's growing nicely. Literally, every pharmaceutical company that researches novel small molecule compounds is a customer. There are about close to 1,800 customers globally spending over $1,000 a year on software. Very high retention, very sticky. We really like this business, and we think this can continue to grow. But we've supplemented it. We have collaborations with pharma companies where we deploy the technology effectively on their account, using our internal team that Karen will describe, to discover molecules of interest against specific targets, usually that they've identified, but in some cases that we've identified, and that we're then furthering in that collaboration. We've done 18 collaborations. I'll talk a little bit about the most recent one, which we announced two weeks ago with Novartis. And then lastly, we have a proprietary portfolio. We now have eight-plus active programs. This number goes up and down, depending upon whether they're partnered and where they are. But most of those are preclinical. But as you'll hear, we have three clinical programs in phase I. We're very excited to see readouts from those programs next year. Now, I mentioned the 18 collaborations. Some of those collaboration programs are now in fairly advanced clinical development. The earliest collaboration in Schrödinger's history was with Agios, and there are two products on the market that you're probably familiar with: the IDH1 and IDH2 inhibitors. There's the TYK2 program that was developed originally by Nimbus, now acquired by Takeda. That's in phase three. And then there are a number of programs in phase two and phase I. You can see the list of collaborators across the bottom. And we do expect this list of collaborators to continue to increase over time as we complete our obligations on certain collaborations and then identify and establish new ones. So two weeks ago, we announced, I think two weeks ago, ten days ago, we announced the collaboration with Novartis. This is a large multi-target research and licensing collaboration. It also includes a significant expansion in our software contract with Novartis. They'll be now using our software at what we've described as industry-leading scale. It's a significant step up in software use. It's a three-year agreement that gives them access to the software, and then Karen will talk more about the collaboration, but the collaboration did have a significant upfront payment and then downstream payments, milestones, and subsequently royalties, so a little bit more detail here. Novartis will see us advancing the discovery efforts, but once we discover a molecule of interest, they will then take the program on for further development and then ultimately commercialization. They will be entitled to global commercial rights. We will receive those milestones, but also royalties on global sales. There was $150 million paid upfront. And we haven't disclosed specifically the therapeutic areas or the number of programs, but suffice to say that this is a sort of manageable scale of collaboration, and it does take us into new therapeutic areas relative to those that we've been in in the past in our collaborations. Just in terms of revenue, just for level set, the $150 million is not recognized as revenue upfront. It's going to be spread over the four-year obligation period of the contract. So very modest revenue in 2024, but then ramping up in 2025 and 2026. The $2.3 billion is contingent upon us achieving discovery and development and then ultimately commercial milestones. And of course, royalties depend on products coming to market. The software agreement does trigger revenue in the fourth quarter. It's a mixture of what we call an on-prem or upfront license and a hosted or ratable revenue license. So we will see a bump in the revenue in the fourth quarter and then a contribution to revenue going forward. Naturally, we won't break that out separately, but it is consistent with the updated guidance we've provided. The other thing that we're very excited about, and we made an announcement yesterday about our predictive toxin initiative. The traditional use of our software has been to optimize the properties, particularly the binding of molecules against a target of interest. Pick, for example, I'm trying to think, VEGF or any target to achieve the highest binding affinity and the optimal chemical properties against that target. What we've now been increasingly asked to do is to ensure that the molecule does not bind to other targets, so-called off-targets. And we've done quite a bit of work to validate that we can do this. We've already characterized CYPs, and now we've also done hERG. And predicting that a molecule will avoid binding to these off-targets turns out to be almost as important as the binding to the primary target of interest. And so we now have funding from the Gates Foundation for a multi-year effort to characterize up to 100 off-target proteins. So we can then capture this in our software for our customers to not only optimize the binding to the target of interest, but also ensure that a molecule that they're advancing into development doesn't have any risk of binding to all of these off-targets. So we think this is both, it's going to be very helpful for our internal drug discovery efforts, and we're already deploying this against a handful of targets that you can see there. But over time, we expect to deploy this to our customers. This is our pipeline. We can talk a little bit about this, but we have three programs in clinical development. I'll just highlight those: our MALT1 inhibitor, CDC7 inhibitor, and our WEE1, MIT1 inhibitor. The first two are in heme malignancies. The MALT1 is in a global phase I dose-ranging study for B-cell malignancies. The CDC7 inhibitor is in a global dose-ranging phase I trial for AML and MDS, high-risk MDS. And then the WEE1 program has gone into a phase I study for solid tumors. We're really excited to see the data from them next year. Just quick financial highlights. We reported Q3, quickly Q3 results: $31.9 million in software was up 10%. Drug discovery revenue was down 75%. The reduction was because in the same period last year, we had a number of accelerated milestones. A number of programs came back to us from BMS when they restructured their portfolio. That triggered an increase in revenue. That's why there is that decline. And certainly, the drug discovery revenue, as we've indicated, is pretty volatile, depending upon the achievement of milestones in the collaborations. Our gross margin has come down a little bit because of the Gates collaboration. We think it'll stay around this range and then trend back up after we get through that collaboration. And then OpEx came in at $86 million, which is around 8% above where we were last year. We remain very well capitalized. We have $400 million in cash at the end of the third quarter. We expect to receive the $150 million from Novartis sometime around year-end. And then we also have ballpark $50 million of equity in Structure, which is a co-founded company that we have access to if we need additional capital. So we really have a very long runway. Quick financial guidance: we raised our software revenue guidance from 6% to 13% to 8%-13%. We brought down drug discovery revenue to 20%-30%. The main trigger for that change was the timing of expected milestones and the uncertainty about whether they come in the very end of the year or next year. Other aspects of our guidance are pretty much unchanged. So key priorities: we're really focused on driving increased customer adoption of the technology, advancing the science underlying the platform, expanding the portfolio of collaborations, achieving proof of concept for our proprietary programs, and bringing more programs into the clinic. And you can see there the timelines, first half of next year and second half of next year for the clinical data. So Mike, thanks. That was fantastic. Maybe we could take those a little bit piece by piece. You know, in my opinion, the last number of years since you've gone public, significant focus on the software business. In fact, I think all I spoke with were software and healthcare IT investors, and then obviously, you have definitely done a good job building out an internal pipeline. We're not talking about software. We're talking about wholly owned assets, cancer assets in the clinic, biotech stuff, and that's a significant source of opportunity as well. On the software side, I feel like the market has been, I guess, a little bit unclear as to what the underlying growth rate is and whether it's accelerating. Are people adopting more of it? Are people using more of it, more per person or more per company, et cetera? There's been various metrics you've given. Maybe the Novartis deal speaks to that, and then last year, the Lilly deal. What is the underlying growth rate of this company? Are there metrics that tell us it's accelerating, or is it just steady eddy, or what? To describe, what is the outlook for software? Yeah, you're right, Mike. The software growth rate has come down from the heady days of 2020 and 2021. Two things really drove much faster growth in that period. One was, of course, a lot of capital in biotech, and sort of every small biotech company was sort of putting money to work, and a lot of the work they were doing was virtual. We were all working virtually, so why not discover drugs virtually, and so that did contribute a lot of growth during that period that's come down. I think we're now operating with more of a sort of sustainable growth trajectory. At least for the last couple of years, as you point out, Mike, the growth has been driven by those very large accounts. And we're finding that there's just a probably growing appetite amongst those global companies to step up the use of our software, really as a way of improving the productivity of their drug discovery, reducing the cost of their drug discovery efforts, and hopefully in the long run, coming up with better molecules. And as we're seeing more and more turnover in R&D leadership, so the incoming kind of heads of R&D are much more sophisticated about the use of computation, and they're calling up and saying, "Okay, we want to be one of those global customers, leading industry leader sort of thing." So we see a lot of opportunity to continue that. We're not by no means penetrated across the whole industry in depth of use. Everybody uses it, but if you go into certain companies, there's very modest use. I mean, I don't want to lock into a specific growth rate, but we really think this is clearly a double-digit growth business. Are you seeing important evolution of change in the decision-making process, or what are the key hurdles for someone like (I'll remind again, because there was a big announcement last week) Novartis, $150 million upfront to collaborate on drugs, as well as up the use of the software. So that's a pretty big commitment. And then last year, Lilly. But you know, when you look at the software business, again, you say, "Well, gosh, Jeff, all these things are happening, but the software business is accelerating." So maybe just speak to, is it IT budgets or is it R&D budgets? Maybe that's what it is. What is the decision tree and what gets people to spend more? Yeah. Do you want to jump in and talk about the Novartis experience? Yeah, certainly. I mean, I think we're well aware that Novartis has actually been a very interesting computational and AI as a method of transforming drug discovery and other parts of their business for quite some time. They have been a customer for more than a decade, but as Jeff said, new head of R&D really trying to kind of implement this now across the whole discovery group, and so the Novartis deal, I think, is emblematic of what we're going to be seeing as large companies tap into the R&D intent, but also the budgets that they're allocating towards AI and computational transformation. And so in the case of Novartis, those two things came together, a desire to see R&D become more efficient, as Jeff said, but really to embrace a gold standard platform across all of their labs to essentially have computation be really the mainstay of how they're doing drug discovery. And so that big step up from the 10 years or more that they've been using the software now to our enterprise LiveDesign platform across all of their labs across the world, I think, is emblematic of what we're going to see. I mean, I'm looking for value creation. Investors are looking for shareholder returns. I would say software business growing nicely is great. In fact, since I'm a biotech analyst on software, I've always said there's way more upside in the proprietary drug discovery pipeline and the software business and the partnerships. If you're helping people find more drugs, that's great, but $2 million a year of extra software per customer, which would be a lot, is not so much value creation if you can come up with your own drugs, so that business continues, the software business continues to do well. The Novartis deal, the Lilly deal, and in many cases, they're coming back to you to ask for your help to develop targets and candidates against those targets to help them grow drugs, and if they become drugs, you get milestones and royalties. That's great. Let's then shift, if I may, to can you do it using your own software? And are you guys just as good or better drug developers than some of those guys all in these other rooms? And tell us about what progress you've made there and the molecules you have in the clinic. Yes, absolutely. So we have three molecules in the clinic, as Jeff said. First is in a phase I dose escalation trial in B-cell malignancies. That is a MALT1 inhibitor. And for those that don't know what that is, MALT1 is a target that's in a very well-characterized pathway. It's the BTK pathway. We know that patients relapse and are resistant to BTK inhibitors. We've demonstrated, as have others, that if you combine a MALT1 inhibitor with a BTK inhibitor, you can push those tumors back into regression and remission. We have now worked through a lot of our phase I trial. We're very excited to next year reveal the results of our first part of our dose escalation trial. So in the first half of next year, we expect to be releasing data on our molecule and also preliminary PK safety and activity in patients. Okay. So you said first half of the year. First half of the year. Yes. ASCO falls in the first half of the year. It does, but this is a heme-onc asset, and so we expect a hematology conference. But okay. Now, getting back to whenever the data may come, tell us why we should be excited about MALT1 other than strong preclinical data? Oh, sure. But to what degree has J&J, which you did, I think you mentioned, I'll just say, I'm the analyst, so J&J has put out data, but maybe summarize what they've seen and could you be better? Where's the opportunity? How active is the target? Right. So as you mentioned, it's a first-in-class target, but over the last couple of years, J&J, actually all the big guns in BTK are very interested in MALT1. So J&J, AbbVie, both have programs. The first data really that came out at ICML, I think it was last year or the year before, shows that MALT1 does have monotherapy activity. However, as I described, this is really a combination play. It was interesting to see them also release data in CLL, where they saw combination activity with a BTK inhibitor. And so we expect to see monotherapy activity for our drug. We do know that the leading assets have had some issues, and we're very pleased to say that in a healthy volunteer study that we did last year, the molecule behaves well. It's very safe so far in healthy volunteers, but we're also seeing the same thing in patients, very well tolerated, and so safety is important. We do know that some of the leading molecules had to be dropped and backups are coming forward, but we're very pleased with the profile of our drug so far. We know it's more potent in human B cells. If you take B cells out of people and you try and inhibit those with our compound, it has shown to be very, very potent against the target, so we expect to see good monotherapy activity and are excited to take it to combination. Okay. So what type of monotherapy activity is good? Throw me out some numbers that they've reported, appreciating they had safety issues. So it doesn't have to necessarily exactly be the same as them if you have a safe and well-tolerated drug. But obviously, there are many DLBCL and CLL, to a certain extent, but many DLBCL options. Yes. So if it is a combination play, then what? You want to show lots of good monotherapy activity so that you can add on to those and make it better? Yeah. What is good results and what would be the next steps? I mean, first of all, let's just put what's in the literature out there. J&J saw about 28%-25% ORR in ABC DLBCL. Heavily pretreated patients. Heavily pretreated. People failed R-CHOP and stuff more than that. Correct. So that was the ORR they saw, and a really nice bump into the 70s in combination with BTK inhibitor. However, I will also say that there is the potential for combination with BCL2 inhibitors. That data is not out in the world from the clinic yet, but we do know that there is really nice synergy with BCL2. So two standard of care agents, I would say, where there's opportunity for combination. Now, what we've heard from KOLs is that 20% ORR on its own as a baseline for monotherapy is a signal to go forward. Of course, we'd love to see more, but that is what they say they're looking for as a baseline because the combination is what's going to drive the remission and the regression. So we're looking forward to seeing how this shows out next year. So we're talking about the study you're running. Describe it again. Pretty much all DLBCL patients. It's what? So dose escalation is in all comers in B-cell malignancy, relapse refractory, many lines of therapy failure, as you've said. We are also now looking, obviously, at the sensitive population, which is ABC DLBCL. Now, that doesn't mean that's the commercialization opportunity because we think this has opportunity in mantle cell, CLL, and in ABC DLBCL. But it does appear that that's where the signals were coming from in the original trials that were published last year. So in our dose escalation, we have been enriching our trial in those non-GCB DLBCL patients. Okay, and the idea would be to take it forward in combination in DLBCL and/or CLL. Correct. Yes. With standard of care to show safety, but also added efficacy and longer durability in relapse-refractory. That's right. Yes. I mean, our decisions around our combination trial and phase two are not fully complete, but you're correct. We see opportunity in MCL, CLL, and ABC DLBCL. Okay, so we'll look forward to that data in the first half. That's important data, and sounds like you're going to be pushing it forward as long as it's active and well tolerated. Correct. Okay. There are other candidates you also have in the clinic, and personal opinion and analyst opinion is that there's been less focus on those. I would say WEE1, which is in the clinic, has been challenging for other players. Yes. So should we be excited about yours and when do you have data? The difference, of course, with WEE1 is that that is a target that has shown a lot of activity, 50% ORR in uterine serous carcinoma in the hands of original developers. You're correct to say that this has been a challenging target because of therapeutic index. What we've done is we've brought forward now a WEE1 PKMYT1 co-inhibitor. Why is that important? It's important because there is a synthetic lethal relationship between those two targets. And what that means is that you can actually bolster the activity that you're seeing in situations where you have CCNE background. And also in the WEE1 PKMYT1, you see synergy in terms of activity, which we believe is going to open up the therapeutic index. We've shown that actually you can get a much larger effect in terms of tumor regression, but not the heme tox that you can see with a frank WEE1 inhibitor, which has been challenging to manage in the clinic. So the primary tox for WEE1 was heme tox? Correct. Is that because I recall that Zentalis dropped their program and they had some deaths from sepsis? I'm not sure that they've dropped it, but. Clinical hold. The share price is on hold, but okay. But the point is they had issues. They did have some signals of efficacy, but they've had safety. And obviously, that program is on hold. You believe in your data, dose escalation, it is a MIT-1 WEE1 that you could show response rates in this type of serous ovarian carcinoma or what? There's no reason why we wouldn't be able to achieve the same type of ORRs that have been seen in gynecological cancers with the idea that you can take very long dosing holidays. That's the basis, excuse me, of our package. You can dose for a few days with our drug and get out of the system so that you have the heme tox. You're doing phase I dose escalation in serous carcinoma patients? Actually, we have a broader capture of patients, including gynecologists. When is that data coming out? We hope to have some data by the end of the year. We initiated the trial mid-year this year, and dose escalation is underway. So yeah, hopefully. End of 2025. Correct. Okay. Fantastic. Thank you very much for the update. We look forward to the progress. Yes. Thank you, guys.