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Q3 2023 Exscientia PLC Earnings Call

Participants

Andrew L. Hopkins; Founder, CEO & Executive Director; Exscientia plc

Ben R. Taylor; CFO, Chief Strategy Officer & Executive Director; Exscientia plc

David Hallett; Chief Scientific Officer; Exscientia plc

Michael Krams; Chief Quantitative Medicine Officer; Exscientia plc

Sara Sherman; VP of IR; Exscientia plc

Alec Warren Stranahan; Associate; BofA Securities, Research Division

Chris Shibutani; Research Analyst; Goldman Sachs Group, Inc., Research Division

Peter Richard Lawson; Research Analyst; Barclays Bank PLC, Research Division

Vikram Purohit; Equity Analyst; Morgan Stanley, Research Division

Presentation

Operator

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. (Operator Instructions). At this time, I would like to introduce Sara Sherman, Vice President of Investor Relations. Sarah, you may begin.

Sara Sherman

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; after 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. And with that, I will now turn the call over to Andrew.

Andrew L. Hopkins

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 prioritized our most differentiated highest-value oncology programs, including GTA, EXS-617, our CDK7 inhibitor in partnership with GTAparon, which has enrolled in patients in a Phase I/II clinical trial and EXS-74539, 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 in our precision medicine platform. Xigen is a multicenter observational trial evaluating of predictive power of a functional precision medicine platform in ovarian cancer. We also have a similar program with Charite in hematological cancers. As a learning company, we are always looking for ways to advance and develop new tech. Exscientia's automation facility recently opened, and we have begun screening biological assets. 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 integrate an AI to automate chemical synthesis at the facility.

Productivity in the automated laboratory will ramp up through 2024. We are 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 Dova design tool that is able to deliver potent kinase hits from the alpha fall structures. We developed this capability based on learnings from prior successful projects. The first exemplification of this design effort was to show how novel, potent and selective kinase inhibitors can be generated in de novo from the alpha fold kino models. The method can potentially be applied across the Protium. This tool is a continuation of our philosophy of encoding and automated 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 3 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 3 initial programs are achieved, we will 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 progress as we partner to address drug discovery challenges in cancer and immunology. We focus our internal pipeline of oncology targets, where our technology can help improve the probability of success through precision design and precision medicine. 2 highly differentiated molecules a demonstrator strategy at GTA-EXS-617 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 I/II 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 study in 607 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 is 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 meloid leukemia, GLP tox studies for a compound are complete, and we expect to submit an IND in the first quarter of 2024. Just behind 539 is our MALT1 inhibitor EXS-73565 or 565. We believe that 565 is highly differentiated due to reduced UGT1A1 inhibition, combined reportance and selltivity. 565 is progressing through IND and CTA enabler 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 free in the clinic, EXS4318 or 4318, a PKC FTA inhibitor designed by Exscientia and in-licensed by Bristol-Myers Squibb is in Phase I. And 2 programs designed by Exentiafor Sumitomo Pharma, DSP 038, a bispecific 5-HT1A agonist and 5HT2A antagonist and DSP2342, a dual 5HT2a/5HT7 antagonist also are in Phase I 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 immological targets and potential milestone payments of up to GBP 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 derisk some programs with the help of our partners and fully maximize the value of our 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 MALT-1 programs, including data presented last month at ESMO, the European Society for Medical Oncology. Dave?

David Hallett

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 539 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 a 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 539 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 modeling formed 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 2 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. It reversibly 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 a first molecule that combines these 3 key criteria. LSD1 is an epigenetic modifier, but also forms a variety of complexes with transcription factors, promoters, activators, corepressor and noncoding 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 Rhopressa 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 not signaling, which in turn promotes differentiation in quiescent cancer cells. These crescent cells are sensitized at combinations with cytotoxic agents or checkpoint inhibition. Here, we showcased 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 milligrams per kilogram. 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 milligrams per kilogram, mouse platelets remain substantially depleted on day 20. On the right panel, you see the outcome of a 15-day rate 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, 3 days on, 4 days off. Whilst we initially saw a reduction in wrap platelets followed by a rebound of 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 539 in a small cell lung cancer xenograft model. In the same study, we also evaluated a well-described blood-based neuroendocrine small cell lung cancer biomarker, progastrin releasing peptide or GRP 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 milligrams per kilogram on a twice a day schedule. On the right, you can see the corresponding effect on plasma pro GRP levels. At 3.3 milligrams per kilogram, pro GRP levels are below the limit of detection in our assay, and this tracks beautifully with maximum effect on tumor volume. It is important to note that 539 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 539 induces AML cell differentiation market expression when used on primary AML samples ex vivo, confirming 539 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 539 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 539, a reversible inhibitor has comparable ex vivo activity to clinical stage irreversible inhibitors at the concentrations tested.

In the bottom graph, we observed a high level of variability across patient samples in the differentiation response post LSD1 inhibition across 539 and the 2 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 539 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 where the 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 the 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 hypothesis, 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 respectively 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 2 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 observed 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 565 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 565 is supported by human pharmacokinetic predictions with low predicted human clearance and high oral bioavailability. Importantly, even for the highest predicted human dose of 565, 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 565 in 2 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 565 as a monotherapy at the highest dose evaluated which was 60 milligrams per kilogram twice a day. This compares very favorably to data previously published from a clinical stage Merck 1 compound. In the same model, this competitor compound did not show monotherapy regression, monocytic administration of IV 565 at 10 milligrams per kilogram twice a day or ibrutinib at 25 milligrams per kilogram once daily, whilst inhibiting tumor cell growth did not meet the threshold to demonstrate tumor growth regression.

However, where 565 and ibrutinib were given at the same doses in combination, there was an apparent synergistic effect leading to tumor growth regression. 565 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, TMD-8 is on the right-hand side. In vitro, this cell line is sensitive to both MALT-1 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're unlikely to also observe in the clinic and which may benefit from a combination approach. As can be seen from the graph, 565 in combination with ibrutinib has synergistic effects displaying meaningful antitumor 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 565 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 the 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 inhibition of UGT1A1 from some AT1 inhibitors. Inhibiting UGT1A1 mediates bilirubin glucaronidation, 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 565. 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 565 has a lower predicted risk of hyperbilirumanemia compared to this clinical compound. Notably, at predicted efficacious doses, the potential to also inhibit UGT1A1 has a margin approximately 4-fold greater for 565 compared to a clinical stage compound. The predictions for this pharmaclinical assets are consistent with the public's Phase I results. Based on this data, we believe 565 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 you over to Ben Taylor, our Chief Financial Officer, to walk us through the financials.

Ben R. Taylor

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 partner 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 retained 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 3 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 on to 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 will be in 2024. Given the 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 and 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.

Andrew L. Hopkins

Thank you, Ben. So as you've 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 targeted 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 Exentia's leadership in AI-enabled drug design and development. With that, we'll open up the call for questions and answers.

Question and Answer Session

Operator

(Operator Instructions). Your first question comes from the line of Alec Stranahan with Bank of America.

Alec Warren Stranahan

Congrats on the progress. This is John on for Alec. Just a quick question for me. On the 565 MALT1 inhibitor acid. 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? And what can we expect going to the second half of next year in terms of data readout.

Andrew L. Hopkins

Sure. Alec, good to hear from you. So we are certainly all excited by the data we showed on MALT1 to give you more color on the preclinical and interdevelopment program. I want to introduce Mike Krams actually to the party.

Michael Krams

Yes. Thanks for the question. So we are 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.

Operator

Your next question comes from the line of Peter Lawson with Barclays.

Peter Richard Lawson

Ben, just the commentary you made around the changes within pharma, any way you can kind of add color around how farmers kind of thinking about AI if they become more interested if it's something they continue to want to do through collaborations or if it's something they want to build internally or own?

Ben R. Taylor

Yes. 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.

Peter Richard Lawson

Got you. And then as we think about kind of large data sets for patients, I know there was news across the world this morning for another player in the AR 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 petabytes of data. Is that an important component to have something you build?

Ben R. Taylor

A 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.

Peter Richard Lawson

And then just would love to go back on the M1 program, I didn't understand. Would it be preclinical data update plus you kind of flush out a developmental plan in the first half?

Andrew L. Hopkins

Yes, precisely. That's the plan, yes.

Operator

Your next question comes from the line of Vikram Purohit with Morgan Stanley.

Vikram Purohit

This is Steve Vik. I will not give you any update on our largest efforts?

Ben R. Taylor

Yes. Steve, good to speak to you. Actually, Charlotte Dean will be presenting at PEG 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 presentation next week.

Operator

(Operator Instructions). Your next question comes from the line of Chris Shibutani with Goldman Sachs.

Chris Shibutani

You described looking at how the partnership business can be more nimble in the future. Perhaps it suggests that the arrangements that you have enabled 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.

Andrew L. Hopkins

Chris, great to speak to you. Yes. So if you actually look at history Exscientia, it actually is a history of how we learn in 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 designed in 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 Exscientia was bringing to the party of the 3 projects that already have been initiated as part of the collaboration. So this actually is an example now of us moving away initially, where maybe we're more reliant on our partners to bring projects to the table. And Exscientia now actually be in much more control of the initiation and the selection of the projects. And as Ben said in his prepared remarks, the importance of the spend is that so we can control risk a lot more, so we could really understand. We are investing in areas where we truly believe also we created differentiated molecules. One of the thing that's important, Chris, to think about Exscientia's partnership work is that we take as much care and 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 which is an important element of it actually. We really do on every project that we work on with someone to have that potential active to be the best differentiated molecule in its class.

Chris Shibutani

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 828 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?

Ben R. Taylor

Yes. Chris, this is Ben. I'll take that one. So I think when we look back, so HA was originally started at a project at Exscientia about 6 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 PPP, that target product profile that Andrew was talking about. And 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. And 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 6 years. And 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 2 aspects to it. One is our operational one and the other is really the decision-making process.

Andrew L. Hopkins

And 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 around across our pipeline across our portfolio. New data we see is also what you saw today from LSD1 and MALT1 and the CDK7 work. And actually, when we then rank 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. And 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 were to increase our pod success is to really understand that of limiting the number of parameters and dimensions of risks that we need to study within our trials. That was an important element, not only looking with data within the AA sort of sphere, but also look at across the competing data we have, actually, how we prioritize across our whole pipeline.

Operator

There are no further questions at this time. I will turn the call over to Andrew Hopkins for closing remarks.

Andrew L. Hopkins

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 a 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. And with that, operator, you may now disconnect.

Operator

Thank you. This concludes today's conference call. We thank you for joining. You may now disconnect your lines.