Hello, everyone. My name is Sarah, and I will be your conference operator today. At this time, I would like to welcome everyone to Exscientia's Business Update Call for the third quarter of 2023. After the prepared remarks, there will be a question-and-answer session. If you would like to ask a question during this time, simply press star one. At this time, I would like to introduce Sara Sherman, Vice President of Investor Relations. Sara, you may begin. Thank you, operator. A press release and 6-K were issued this morning with our third quarter 2023 financial results and business update. These documents can be found on our website at investors.exscientia.ai, along with the presentation for today's webcast. Before we begin, I'd like to remind you that we may make forward-looking statements on our call. These may include statements about the initiation, timing, and progress of, and data collected during and reported from the company's clinical trials, expectations regarding the growth of the company's capabilities and the performance of its technology platform, and the company's projected cash runway. Actual results may differ materially from those indicated by these statements. Unless required by law, Exscientia does not undertake any obligation to update these statements regarding the future or to confirm these statements in relation to actual results. On today's call, I'm joined by Professor Andrew Hopkins, Chief Executive Officer, Dr. Dave Hallett, Chief Scientific Officer, and Ben Taylor, CFO and Chief Strategy Officer. Dr. Mike Krams, Chief Quantitative Medicine Officer, will also be available for the Q&A session. With that, I will now turn the call over to Andrew. Thank you, Sara. In the third quarter of 2023, we made great strides across our internal and partner programs. We are executing on a focused development pipeline and prioritizing our most differentiated, highest value oncology programs, including GTAEXS617, our CDK7 inhibitor in partnership with GT Apeiron, which is enrolling patients in a phase 1/2 clinical trial, and EXS74539, our LSD1 inhibitor, for which we anticipate submitting an IND in the first quarter of 2024. We also advanced partner programs, achieving the first milestone in our Sanofi collaboration, and inked a new partnership with Merck KGaA that bolstered our financial strength and expanded our reach. We continue to push forward with clinical validation of our precision medicine platform. EXCYTE-1 is a multicenter observational trial evaluating the predictive power of a functional precision medicine platform in ovarian cancer. We also have a similar program with Charité in hematological cancers. As a learning company, we're always looking for ways to advance and develop new tech. Exscientia's automation facility recently opened, and we have begun screening biological assays there. We plan to migrate all the primary assays we can from our CROs to our automated labs. We synthesized our first compound at our automation labs, and through 2024, plan to bring you more information on how we integrated AI to automate chemical synthesis at the facility. Productivity in the automated laboratory will ramp up through 2024. We're expecting a meaningful impact on the quantity of data we generate, as well as cycle times from the new labs. We are committed to the integration of AI and automation to improve the way drugs are designed. We also recently presented data on an automated de novo design tool that is able to deliver potent kinase hits from the AlphaFold structures. We developed this capability based on learnings from prior successful projects. The first exemplification of this design method was to show how novel, potent, and selective kinase inhibitors can be generated de novo from the AlphaFold kinome models. The method can potentially be applied across the proteome. This tool is a continuation of our philosophy of encoding and automating drug discovery wherever possible, and we look forward to applying this at scale across future projects. We believe we remain well-capitalized with $447.8 million in cash at the end of the quarter, providing us with a runway well into 2026 to advance our near-term programs, as well as grow our capabilities, driven by recent investments in automation, as well as other leading technological and scientific advancements, which allow us to reach key inflection points that will drive the value of our platform. We recently prioritized our pipeline to focus internally on the programs we believe will have the greatest clinical impact for patients and which have the highest probability of success. As previously mentioned, our partnership business continues to mature. This is highlighted by the new collaboration we announced in September with Merck KGaA, based in Darmstadt, Germany. Prior to signing the agreement, we identified three potential first-in-class or best-in-class targets in oncology and immunology. Under the terms of the agreement, we will receive an upfront cash payment of $20 million from Merck. If all milestones for all three initial programs are achieved, we'll be eligible for discovery, development, regulatory, and sales-based milestone payments of up to $674 million. We are excited to announce this partnership, as we believe our integrated technology platform will complement Merck's scientific prowess as we partner to address drug discovery challenges in cancer and immunology. We focus our internal pipeline on oncology targets, where our technology can help improve the probability of success through precision design and precision medicine. Two highly differentiated molecules that demonstrate this strategy are GTAEXS617 or 617, our CDK7 inhibitor, and EXS74539 or 539, our LSD1 inhibitor.... 617 has potential as a best-in-class reversible CDK7 inhibitor. It was designed for improved potency, selectivity, and pharmacokinetics compared to other molecules in development. Enrollment is ongoing in the Phase 1/2 ELUCIDATE adaptive clinical trial, with advanced solid tumors including head and neck cancer, pancreatic cancer, non-small cell lung cancer, hormone receptor-positive, HER2-negative breast cancer, colorectal cancer, and ovarian cancer. The model-driven adaptive trial is studying 617 as both a monotherapy and in combination with standard of care, where we expect our precision medicine platform to play a critical role in determining the optimal combinations. 539, our LSD1 inhibitor, also has best-in-class potential. 539 has a high level of differentiation due to its reversible mechanism of action, CNS penetration, preclinical safety profile, and anticipated flexibility of dosing that should help maximize therapeutic index. This unique set of properties provides both first-in-class and best-in-class potential for small cell lung cancer and acute myeloid leukemia. GLP tox studies for this compound are complete, and we expect to submit an IND in the first quarter of 2024. Just behind 539 is our MALT1 inhibitor, EXS73565, or 565 for short. We believe that 565 is highly differentiated due to reduced UGT1A1 inhibition, combined with potency and selectivity. 565 is progressing through IND and CT enabling studies, and we look forward to sharing more information on this with you in the first half of 2024. As for our partner programs, we currently have three in the clinic. EXS4318 or 4318, a PKC theta inhibitor designed by Exscientia and in-licensed by Bristol Myers Squibb, is in phase 1. Two programs designed by Exscientia for Sumitomo Pharma, DSP-0038, a bispecific 5-HT1A agonist and 5-HT2A antagonist, and DSP-2342, a dual 5-HT2A/5-HT7 antagonist, also are in phase 1 studies. We also achieved our first milestone for an immunology and inflammation target within our collaboration with Sanofi. As a reminder, the Sanofi collaboration is for up to 15 oncology and immunology targets, and potential milestone payments of up to $343 million per program. Beyond the programs highlighted, we believe we have a well-balanced blend of internal and partnered programs. This means that we're able to de-risk some programs with the help of our partners and fully maximize the value of the programs that we solely own. I'll now hand over to Dave Hallett, our Chief Scientific Officer, to walk us through an update of our LSD1 and MALT1 programs, including data presented last month at ESMO, the European Society for Medical Oncology. Dave? Thank you, Andrew. I'll start by spending some time on why we are so excited by our LSD1 inhibitor, including the recent data we presented at the ESMO Congress last month. As Andrew mentioned, we believe our LSD1 inhibitor, EXS74539, has best-in-class potential as its reversible mechanism of action, and its predicted human half-life is expected to translate to an improved therapeutic index through more flexible dosing options. We also believe it could be of benefit to patients with brain metastases due to its brain-penetrant design. We have completed GLP toxicity studies, and we intend to file an IND for EXS74539 in the first quarter of 2024. If the IND is cleared, this will enable us to go into a healthy volunteer study also in 2024. Understanding the impact of LSD1 inhibition on cells of myeloid lineage, such as platelets, is critical. This is likely to be highly variable in heavily pretreated oncology patients, hence why we believe starting with healthy volunteers is the best strategy. Like all things we do at Exscientia, we will incorporate this trial data into our simulations as part of our model-informed drug development approach. In turn, this will then allow us to establish a therapeutic dose and enable combination studies in Acute Myeloid Leukemia and Small Cell Lung Cancer at the outset. As combination therapy is the ultimate goal, we believe a pathway via healthy volunteers is the fastest route to achieve this. We are currently running translational studies, which will inform the combination strategies we prioritize when we start studies in patients. Though literature has shown the potential benefit of LSD1 inhibition in a variety of indications, including neuroendocrine, pancreatic, and prostate cancers, we believe that 539 has the highest potential benefit for patients with AML and small cell lung cancer. Highlighted here is the U.S. incidence for these two indications. In the U.S. alone, there are 45,000 patients each year impacted by these diseases. As a brain penetrant molecule, 539 should help address that population of small cell lung cancer patients that will develop brain metastases, which is roughly 50%. Through our precision medicine platform work, we will be aiming to identify those that are most likely to respond and factor this into our clinical development strategies. Our goal when designing 539 was to combine CNS penetration with an appropriate predicted human half-life and a reversible mechanism. Irreversibly deactivating this enzyme can contribute to poor control of platelet levels. We believe that having a reversible mechanism and combining this with a shorter half-life should result in a better therapeutic index. CNS penetration is important because it helps address brain metastases, which is prevalent in advanced disease. We believe that we have designed the first molecule that combines these three key criteria. LSD1 is an epigenetic modifier, but also forms a variety of complexes with transcription factors, promoters, activators, co-repressors, and non-coding RNAs. As a result, the key mechanisms of action are different in AML and small cell lung cancer, though LSD1 inhibition leaves tumor cells vulnerable to cytotoxic agents in both indications. In AML, LSD1 inhibition promotes cell differentiation by blocking the growth factor-independent repressor complex, leading to acetylation of key promoters. This results in the induction of leukemic blast cell differentiation, which slows or stops the expansion of tumor cells. LSD1's mechanism of action is different in small cell lung cancer. Here, inhibition of LSD1 suppresses neuroendocrine features through upregulation of NOTCH signaling, which in turn promotes differentiation into quiescent cancer cells. These quiescent cells are sensitized to combinations with cytotoxic agents or checkpoint inhibition. Here, we showcase the potential safety benefits of having a reversible mechanism coupled with a shorter half-life. This additional in vivo data highlights the activity of 539 compared to an irreversible LSD1 inhibitor currently in clinical development. In the left panel, you see the outcome of a 20-day study in a mouse model. 539 was dosed on a twice-per-day schedule at 6.6 mg/kg. 16 hours after the final dose on day 20, platelet levels were the same as control. This is in stark contrast to the irreversible inhibitor. Despite only administering this compound once per week at 0.4 mg/kg, mouse platelets remained substantially depleted on day 20. On the right panel, you see the outcome of a 15-day rat non-GLP study, where we looked at platelet levels as a function of both time and dose. Note the higher doses of 539 compared to the efficacy study and the dosing schedule studied here, three days on, four days off. While we initially saw a reduction in rat platelets followed by a rebound off drug, by day 15, platelets were back at control levels. 539 as a reversible LSD1 inhibitor, when coupled with intermittent dosing, is expected to reduce on-target toxicity. Irreversible inhibitors, regardless of dosing frequency, require resynthesis of the LSD1 protein before its normal functions resume and are predicted to have an inferior therapeutic index. Turning to efficacy, here we highlight dose-dependent oral efficacy observed with EXS74539 in a small cell lung cancer xenograft model. In this same study, we also evaluated a well-described blood-based neuroendocrine small cell lung cancer biomarker, progastrin-releasing peptide, or ProGRP for short. On the left, we can see dose-dependent monotherapy activity in a small cell lung cancer xenograft when dosed up to 3.3 mg/kg on a twice-a-day schedule. On the right, you can see the corresponding effect on plasma ProGRP levels. At 3.3 mg/kg, ProGRP levels are below the limit of detection in our assay, and this tracks beautifully with maximal effect on tumor volume. It is important to note that EXS74539 was well-tolerated throughout this 28-day mouse study. As a reminder, LSD1 inhibition is predicted to leave tumor cells vulnerable to combination approaches, and we demonstrate in vitro combination activity later in this presentation. Further in vivo combination studies are planned, and we expect to share the data with you in 2024. At ESMO, we presented new preclinical data demonstrating that EXS74539 induces AML cell differentiation marker expression when used on primary AML samples ex vivo, confirming EXS74539's general activity. As shown in the poster, healthy, non-transformed bone marrow blast differentiation was unaffected in our setup. Using CD86 as a biomarker for blast cell differentiation, we were able to compare EXS74539 to some irreversible LSD1 inhibitors currently in the clinic. The top graph shows that the level of differentiation on the Y-axis was comparable at different concentrations on the X-axis for different LSD1 inhibitors. This highlights that EXS74539, a reversible inhibitor, has comparable ex vivo activity to clinical stage irreversible inhibitors at the concentrations tested. In the bottom graph, we observe a high level of variability across patient samples in the differentiation response post LSD1 inhibition across EXS74539 and the two irreversible compounds. There are samples representing high, medium, and low levels of differentiation, and this level of heterogeneity supports further exploration of patient selection strategies in the clinic. Our precision medicine platform can also potentially help us identify the best combination therapies for a patient before entering the clinic. We also presented ex vivo data, where we quantified the activity of EXS74539 on AML cancer cells viability. The bar plot on the left highlights the variability of single agent response within our cohort, showing induced loss of cell viability in decreasing order. This produced a baseline to subsequently compare monotherapy response versus 539 plus standard of care combinations, as seen on the panel on the right. Each column on the panel to the right represents a standard of care treatment option. Each row is a patient sample corresponding to the list on the left. The grid displays whether synergistic effects were seen using the HSA method for 539 in combination with each standard of care option. This data demonstrates that 539 has general combination potential with common AML standard of care treatments. Even though samples with low single agent sensitivity to 539 could demonstrate a synergistic effect with a current standard of care treatment. We believe it may be beneficial to identify AML patients more likely to respond to 539 as a single agent in the clinic, as well as rational combinations. We are currently generating patient enrichment hypotheses, leveraging our single-cell omics capabilities to detail 539-induced gene expression on AML cell subpopulations. We look forward to sharing more data on this and testing our hypotheses retrospectively in AML patients. In addition to our ESMO poster, we have also generated additional preclinical data for LSD1 in small-cell lung cancer. The graph on the left shows the level of synergy in cell line models. This synergy, assessed using the Bliss Independence Model, is measured across the different small cell lung cancer subtypes on the Y-axis, and measured between 539 and various small cell lung cancer standard of care treatments and targeted therapies on the X-axis. As displayed by the color coding, synergistic effects were most frequently obtained in the two most prevalent molecular subtypes, A and P, which account for more than 80% of small cell lung cancer patients. The right-hand side highlights data that we have produced in cell lines known to be unresponsive to LSD1 inhibitors. As expected, 539 as a monotherapy has limited effect on proliferation in these cell lines. However, the interesting thing that we observe is that 539 has synergistic effects with suboptimal concentrations of the standard of care or targeted therapies. This further highlights the need for selecting the right combinations for the right patients. I'll now spend a few moments on our MALT1 inhibitor in IND-enabling studies. Alongside 539, we also presented data on 565, our MALT1 inhibitor, at ESMO. This highlights EXS73565's precision design characteristics and its potential for low drug-drug interactions. As we have shown previously, we believe we have designed a high-quality allosteric MALT1 inhibitor with a potential key safety differentiator. Once-daily administration of EXS73565 is supported by human pharmacokinetic predictions, with low predicted human clearance and high oral bioavailability. Importantly, even for the highest predicted human dose of EXS73565, the risk of inhibiting the UGT1A1 enzyme, as well as several transporters involved in bilirubin disposition, is low, resulting in a lower burden on the liver. This is something I will expand on later. Here, we highlight in vivo activity of EXS73565 in two xenograft models, one of which we newly published at ESMO, is a B-cell non-Hodgkin lymphoma model called OCI-Ly10, shown here on the left-hand side. In vitro, the OCI-Ly10 model is sensitive to both MALT1 inhibitors and BTK inhibitors, such as Ibrutinib. At ESMO, we highlighted data which showed that tumor growth regression was achievable with EXS73565 as a monotherapy at the highest dose evaluated, which was 60 mg/kg twice a day. This compares very favorably to data previously published from a clinical stage MALT1 compound. In the same model, this competitor compound did not show monotherapy regression. Monotherapy administration of either EXS73565 at 10 mg/kg twice a day, or Ibrutinib at 25 mg/kg once daily, while inhibiting tumor cell growth, did not meet the threshold to demonstrate tumor growth regression. However, where EXS73565 and Ibrutinib were given at the same dose as in combination, there was an apparent synergistic effect leading to tumor growth regression. EXS73565 was well tolerated during the dosing period, with no effects on body weight compared to the vehicle group. Data from a diffuse large B-cell lymphoma model, TMD8, is on the right-hand side. In vitro, this cell line is sensitive to both MALT1 and BTK inhibition. However, historically, this has been a really challenging model to show efficacy in vivo for either mechanism. This cell line is a model reflecting a more recalcitrant lymphoma that we are likely to also observe in the clinic, and which may benefit from a combination approach. As can be seen from the graph, EXS73565, in combination with ibrutinib, has synergistic effects displaying meaningful anti-tumor effects. We also presented data in primary human chronic lymphocytic leukemia, or CLL cells, for the first time at ESMO. These CLL samples were taken from patients that were either treatment naive or had been exposed to previous lines of therapies. Importantly, we observed limited impact to T-cell viability in the experimental setup. This data showed that EXS73565 selectively inhibited the proliferation of human primary CLL cells. This points to a broadening of target patients beyond just diffuse large B-cell lymphoma. You may have seen a recent disclosure from the first MALT1 inhibitor that went into patients, validating the potential of this mechanism by demonstrating clinical activity in lymphomas. As we've highlighted before, we believe there is a risk of hyperbilirubinemia linked to inhibition of UGT1A1 from some MALT1 inhibitors. Inhibiting UGT1A1 mediates bilirubin glucuronidation, which in turn can lead to jaundice or hyperbilirubinemia. As a result, selectivity over UGT1A1 was a key feature of our target product profile for EXS73565. In the published peer data, as shown on this slide, hyperbilirubinemia was observed in more than 40% of patients treated. We have shown preclinically that EXS73565 has a lower predicted risk of hyperbilirubinemia compared to this clinical compound. Notably, at predicted efficacious doses, the potential to also inhibit UGT1A1 has a margin approximately 14-fold greater for EXS73565 compared to a clinical stage compound. The predictions for this pharmacological asset are consistent with the published phase 1 results. Based on this data, we believe EXS73565 has a lower risk of drug-drug interactions, potentially allowing a wider range of combination use. This could also facilitate dose escalation in the clinic. Overall, 565 profile offers potential for further exploration of MALT1 inhibition as a monotherapy and/or in combination with other targeted agents in hematological malignancies, and we look forward to providing further updates on 565 in the first half of 2024. I'll now hand it over to Ben Taylor, our Chief Financial Officer, to walk us through the financials. Thank you, Dave. We announced last month that we are prioritizing development of a focused number of internal programs that are highly differentiated across oncology targets with clear market need. This will enhance the operational efficiency and allow us to maintain our cash runway well into 2026, while delivering on multiple important milestones in our key programs. We have also been applying the same discipline to our partnered discovery programs, and I am going to provide you with a brief update across the portfolio. We want all of our programs, whether internal or partnered, to have meaningful competitive differentiation and market potential. In our existing partnerships, we have ended our collaboration with EQRx, following their announced acquisition by Revolution Medicines, and we retain ownership to all intellectual property developed during that collaboration. With BMS, we have mutually decided to prioritize certain programs and not proceed with others. Some of the initial programs are still running, but we are also evaluating multiple ways to work together on newer targets or technologies. Our portfolio prioritization exercise has had no impact on our Sanofi or Merck KGaA collaborations. As Andrew mentioned, this quarter we also achieved our first Sanofi collaboration milestone for an immunology and inflammation target. We have also initiated the three programs with Merck KGaA. The combination of prioritizations in our internal and partnered pipeline maintains a broad portfolio of over 20 programs, but focuses our activities on those projects that we believe have the most potential for differentiation and patient impact. Looking forward, most macroeconomic forecasts now project a conservative environment into 2024. We have also seen large pharma go through dramatic strategic shifts and leadership changes that will also continue into 2024. This means that we need to be highly nimble as an organization to respond to the changes in the external environment quickly. We have, and will continue to do this through our operational efficiency initiatives, but we are also evaluating how we can evolve the partnership business to be more nimble in the future. Our existing partnerships with Sanofi, BMS, and Merck give us primary operational control, but require us to maintain substantial infrastructure to execute. This was initially necessary so that we could redefine the process of AI-based drug discovery. Over the last few years, we've demonstrated how that process can lead to better outcomes, and we have also learned in what ways we add the most value. In order to become more efficient and reduce unnecessary infrastructure, we are focusing our conversations with potential partners on the areas where we have the highest impact, primarily design and novel technologies. This should retain high-value downstream economics while increasing the profitability and flexibility of our partnerships. We also want to find structures that allow our partners to change their strategic focus without transferring that risk onto us. This will likely have an impact on timing of our ongoing discussions. While it is still possible we may sign a second partnership this year, our expectation is that it'll be in 2024. Given external uncertainties, we will maximize value creation over speed. I'll now take a minute to close with highlights from our financial results. Full results are detailed in our press release in Form 6-K. I'll review the results in U.S. dollar using the September 30, 2023, constant currency rate of 1.2214. We ended the quarter with $448 million in cash, cash equivalents, and bank deposits. Note that this excludes the upfront payment from Merck and the first milestone from Sanofi, which will be reflected as cash inflows in the fourth quarter of 2023 financials. We now expect to save over $55 million in 2023 versus our original budget, based on ongoing efficiency programs. Combining efficiency with our portfolio prioritization has put us in a strong financial position with a cash runway well into 2026. This will allow us to advance our differentiated clinical programs, deliver on our partnerships, and invest in new platform technologies. Our net operating cash burn has decreased every quarter of this year. For the first 9 months of the year, our net operating cash burn was $145 million, and we expect operating expenses for the fourth quarter to be largely offset by payments from Merck KGaA, Sanofi, and R&D tax credits. While we are not providing specific guidance for 2024, we expect cash outflows to be largely flat year-over-year, with increased inflows from the partnership business. With that, I will turn the call back to Andrew. Thank you, Ben. So as you heard today, at Exscientia, we are laser-focused on continuing to build an engine that designs and develops high-impact medicines that have the potential to transform patients' lives. We are continuing to build out a highly differentiated internal oncology pipeline, particularly our clinical and IND-enabling stage programs targeting CDK7 and LSD1. In addition, our partnerships are steadily progressing, including our recently announced first milestone with Sanofi and a new collaboration with Merck KGaA. These developments, paired with our technological advancements, solidify Exscientia's leadership in AI-enabled drug design and development. With that, we open up a call for questions and answers. Thank you. If you would like to ask a question, please press star one on your telephone keypad. To withdraw your question, simply press star one again. Your first question comes from the line of Alec Stranahan with Bank of America. Your line is open. Hey, guys. Congrats on the progress. This is John. I'm on for Alec. Just a quick question from me. On the 565 MALT1 inhibitor asset. So, you're guiding to an update in the first half of next year. So can you just give more color on what extent of data can we be expecting? You know, and what can we expect going to the second half of next year in terms of data read out? Thanks. Sure. Hi, Alec. Good to hear from you. So, we are certainly excited by the data we showed on MALT1 today. To give you more color on the preclinical and IND development program, I want to introduce Mike Krams, actually, to the party here. Yeah. Hi. Thanks for the question. So we're currently working through IND prep studies and are anticipating that we can provide you with an update early next year. But our thinking is that we will move into a clinical development strategy that will very efficiently demonstrate our ambition to have a better therapeutic index, building on what Dave discussed earlier around the differentiation on the liver tox issues. Thank you. Got it. Thanks for the color. Your next question comes from the line of Peter Lawson with Barclays. Your line is open. Great. Thanks for taking my question. Just the commentary you made around the changes within pharma, any way you can kind of add some color around how pharma is kind of thinking about AI, if they've become more interested, if it's something they continue to want to do through collaborations, or if it's something they want to, you know, build internally or, or own? Yeah. No, great question, Peter. So, we still see a lot of interest in large pharma. I'd say each one has a slightly different strategy. Almost all of them, I would say, are building significant AI capabilities. And what we see is really a variation, some of which are looking more for doing multiple partnerships externally. Some of them want to complement their own internal efforts. But what we have seen come across most clearly is they're really interested in our differentiated technologies. I think there will be many aspects of AI that just become standardized in the industry. So it's really where does our proprietary data, our combination of technologies, our ability to put the technologies together, make a difference? That's where large pharma really come to us and want to see how we can solve some of the problems that they can't traditionally do, or they can't do with their internal operations. Gotcha. Thank you. And then, as we think of that kind of large data sets for patients, I know there was news across the world this morning from another player in the AI space. Just, is that something you need to kind of secure yourself to get access to large patient data sets in oncology? I think they mentioned, like, 20 PB of data. Is that an important component to have? Well- Is that something you build? Really, really important thing to remember is we're a learning company more than a screening company. So, if we were focused on target identification, for example, there's a lot of screening involved in that. It's a big data problem. What we are most often doing is solving design problems and understanding specific patient enrichment strategies. And those aspects are really how do you learn your way into something where you don't have existing data? And so most of the data that we use actually on our design projects and for our precision medicine is actually proprietary, internally generated data. Because the data doesn't exist, either in the form or at all, that would be useful for doing a complex analysis of it. So, we don't believe that we need petabytes worth of data to be able to solve a problem. In fact, we look to find the most efficient way to learn from very specific data how we can solve that problem. Gotcha. Thank you. And then just look to go back on the MALT1 program. I didn't understand. Would it be preclinical data update, plus you'd kind of flush out a developmental plan in the first half? Yes. Precisely, that's the plan. Yep. Perfect. Thank you so much. Your next question comes from the line of Vikram Purohit with Morgan Stanley. Your line is open. Hi, this is Steve with Vikram. Thanks for taking our question. I want to get you any update on the biologics effort. Thank you. Yes, hi, Steve. Good to speak to you. Actually, Charlotte Deane will be presenting at PEGS next Wednesday on the results we've already generated on our proof of concept work. We're very excited actually by that data, which actually explores multiple different methodologies. So I recommend actually look out for Charlotte's presentation next week. Thank you. Once again, ladies and gentlemen, if you have a question, it is star one. Your next question comes from the line of Chris Shibutani with Goldman Sachs. Your line is open. Thank you very much. Good morning, good afternoon. You described looking at how the partnership business can be more nimble in the future. Perhaps it suggests that the arrangements that you have enable you to be less exposed to risk. Can you describe a little bit further about how the programs and the partnerships are evolving? Just a little bit more visibility into how that could shift would be helpful. Hi, Chris. Great to speak to you. Yes. So if you actually look at the history of Exscientia, it actually is a history of how we learn from every partnership and how those partnerships reflect the state-of-the-art of a technology platform at the time, as well, and what capabilities we can bring to our offering. Very much if you look at the Sanofi deal, which really is a full end-to-end program, identifying the drug targets, designing the molecules, also thinking about patient selection strategies. We then actually, with the new Merck program we set up, actually was not only more focused on drug design, but actually also, you know, Exscientia was bringing to the party the three projects that already have been initiated as part of the collaboration. So this actually is an example now of us moving away from, you know, initially, where maybe we were more reliant on our partners to bring projects to the table. On Exscientia now, actually, be much more in control of the initiation and the selection of the projects. And as Ben said in his, his, prepared remarks, the importance of this, Ben, is that so we can control risk a lot more, so we can really understand, we are investing in areas where we truly believe also we're creating differentiated molecules. One thing that's important, Chris, to think about Exscientia's partnership work is that we take as much care in understanding the target product profile and how we're going to differentiate commercially, as we do with our internal programs that you see, such as LSD1, CDK7, MALT1, and others, which will be announced in the near future. So this is an important element of it, actually. We really do want every project that we work on with someone to have that potential activity, to be, you know, the best differentiated molecule in its class. Then can I ask as well, I think a foundational aspect of your entire philosophy or approach, artificial intelligence, machine learning, is that it's iterative, and I would imagine through both successes and progress as well as setbacks, there is learning. Can you perhaps summarize what the decision to discontinue 546, the A2A candidate, what were the net learnings from that? I believe that there was some aspect of peer data, but, as you put that together, how did that decision, which was probably difficult but necessary, given how difficult drug development is, how did that inform what you're doing, with your core capabilities going forward? Yeah. Hey, Chris, this is Ben. I'll take that one. So I think when we look back, so A2A was originally started as a project at Exscientia about six years ago, when the company was just really doing chemistry design and partnered with Evotec for a lot of the other aspects. I think if you look at what we do now, we really run full biological and commercial analyses on all of our targets. We put a lot of analysis into that TPP, that target product profile, that Andrew was talking about. So I think to some extent, there was a lot of learnings coming out of A2A that formed those operations that we now have and led to a lot of the target selection that we've done on more recent programs, as well as our internal pipeline. Then I think there's also been aspects that have contributed to how do we analyze the programs as they go through. That being said, there was a number of commercial and competitive changes that have happened to the markets that A2A would look at over the last six years. Maybe some of those could have been predicted, but many weren't able to be predicted. They didn't have the appropriate data out. And so that's where I think being a learning company also comes in to being nimble. It's saying, "You know what? There's new data out. I need to reevaluate the fundamental decisions I made before, and rather than carry them through to completion because I'm on a path, I'm going to make the better decision as early as I can, based on the new data." So I'd say there's two aspects to it. One is our operational one, and the other is really the decision-making process. Chris, just to underline what Ben just said, the important thing is looking at new data, and then new data is also looking at it in the round, across our pipeline, across our portfolio. New data we see is also what you saw today, you know, from LSD1 and from MALT1, and the CDK7 work. Actually, when we then rank, you know, all of our programs together, that's when strategically we see actually that we have very defined questions to ask in the clinic, actually, with CDK7 and LSD1 and MALT1. With A2A, we found actually there was actually quite a number of multiple questions and risks, therefore, to be answered within our trial. And actually, where we want to really consider if we want to play to win in areas is if we want to increase our probability of success, is to really understand that of, you know, limiting the number of parameters and dimensions of risks that we sort of, and we need to study within our trials. That was an important element, not only looking with data within the A2A sort of, sphere, but also looking across the competing data we have, actually, how we prioritize across our whole pipeline. Got it. Thanks for the insights. There are no further questions at this time. I will turn the call over to Andrew Hopkins for closing remarks. Thank you, operator, and thank you to everyone on the call today for your continued support of Exscientia. As we seek to fundamentally change the way we design and develop drugs, we are laser-focused on designing and developing programs that address complex drug design challenges with clear impact on broad patient populations. The continued advancement of our pipeline is testament to the power of our platform and the strength of our business model, position us well as we work to deliver truly personalized medicines. With that, operator, you may now disconnect. Thank you. This concludes today's conference call. We thank you for joining. You may now disconnect your lines.