Good morning, everyone. My name is Gena Wang. I'm SNIC Biotech analyst at Barclays. Welcome to Barclays Global Healthcare Conference. It is my great pleasure to introduce our next presenting company, Beam Therapeutics. With us, we have Giuseppe Ciaramella, our Chief Scientific Officer and the President. Pino, do you want to give a brief overview before we dive into specific questions? Yes, of course. Thank you very much for the opportunity to come and share some of our updates. Yeah. Beam Therapeutics is a next generation gene editing company that uses primarily this technology known as base editing. It is still a Cas9-based technology, but we use Cas9 as the landing pad and the targeting domain. We have changed it in a very important way, so it no longer makes the double-strand break, which we believe leads to some unwanted outcomes in editing. Instead, fused to that protein is an additional protein, which is a human enzyme called a deaminase, which is capable of catalyzing the direct conversion on the gene of a nucleobase to another. Depending on which deaminase we use, we can convert a C to a T or an A to a G. Obviously, as you know, an A or a C are present in any base pair in the genome. This gives us the opportunity to generate a very versatile editing technology that can not only correct point mutation, which is has proven to be very challenging for the first generation of editors based on nucleases. Also gives us the opportunity by doing that to do all sorts of different edits. In fact, we have products where we can knock out proteins, particularly in our BEAM-201 oncology cell-based therapies. We can actually activate genes by making changes in promoter regions of genes. This is the case for our BEAM-101 sickle cell disease program. As well as doing this in a multiplex fashion without running into the consequence of because of double-strand breaks or chromosomal rearrangements, which obviously can lead to some unwanted effect. That's it's proven a very robust, versatile technology that works well both in replicating and non-replicating cells because it's based on a direct enzymatic conversion of one nucleobase to another. Thank you, Pino. Maybe I wanted to ask you your technology, you know, in terms of... because you do based on the CRISPR, not really Cas, but you use the deaminase. Mm-hmm. You did have already IND clear, Correct. That's the ex vivo part. For the in vivo, you know, systemic delivery, do you think you know the, say, the IND package or safety package, what will be additional anything differences if we think about the IND package submission compared to, say, classic CRISPR-Cas9 technology? Yeah. For the in vivo submission for classic CRISPR-Cas9 versus base editing, I don't see any difference between the two. The only sort of minor thing is that there is a one off-target biology assay that is more relevant to base editor that it's not. It's essentially a version of the same assay that is used in the context of nucleases. In that context, it's called GUIDE-seq. Yeah. We have one seq, and essentially what it is an in vitro assay that is capable of generating, essentially, to recognize wherever in the genome a base editor has been introduced. This is thanks to the fact that a C is usually converted to a U, a uracil, that's read as a T. The adenosine is converted to an I, inosine, which is read as a G. Both U and I in the context of DNA can be very specifically recognized by particular enzymes. Those, when they recognize they make a cut, and then at that point it becomes like GUIDE-seq. You essentially introduce probes wherever that cut has actually occurred. That's the only assay that's different, but the package for the rest is essentially the same. I see. The question about is the package the same between ex vivo and in vivo? There is really one additional considerations that certainly regulators and our interactions with the FDA in pre IND discussion for BEAM-301 has certainly confirmed that. That is all to do about the potential for transferring the edit to progeny. Obviously in ex vivo setting, that's not a concern, but in vivo that could be a concern. Part of your package needs to ensure that both through a biodistribution analysis, but also maybe through progeny studies, you demonstrate that essentially you are not targeting reproductive cells. That's really the main difference. The rest is fundamentally actually pretty similar to in vivo LNP packages that I've seen in the past in my previous life at Moderna, and also have been seeing here now. There is no real unexpected concerns. Okay, very good. I have several questions. Regarding, I think at the first step you were saying the one seq- you are using. How do you tell the, you know, like, A to I, A to G, C to U from the polymorphs? These are really clever. They're essentially because in DNA you don't see U or I continuously. Oh, I see. They can actually scan the DNA and wherever there is a U they actually make a cut or wherever there is an I, they make a cut. If you remember when we talked last time, essentially the strategy for off target biology in general is essentially a funnel way. What you do at the very beginning, you create the worst case scenario. Typically you do this by a series of in silico and in vitro assays, where essentially you expose naked DNA, which is the worst possible case, to saturating doses of your editor. You generate basically the possibility wherever it might happen, of creating essentially a base edit in this case or off target. That allows you to generate essentially PCR probe at all of those places, where when you do the edit in the context of your cells of choice, let's say CD34 or primary hepatocyte, you then use the PCR to very specifically determine whether the theoretical off target has actually occurred or not. On top of that, you can actually determine the% to which it occurs. if it does occur. It's really a very, I would say very sensitive actually funnel, that characterizes that off target biology in a very meaningful way. sorry, Pino. like you still have like, that, you know, bring back like biased versus unbiased... Mm-hmm. Whole-genome sequencing. This is for a guide. This. biased because you have, your certain sequence in mind. The original assays will be what you would call biased because they are based on a degenerate sort of library. Okay. Yes. Yes. It's very extensive. You can couple that to an unbiased assay, which is called the Whole-genome sequencing. Basically the two together will give you essentially the broadest possible opportunity to interrogate off-target biology. I see. With this combination, FDA is totally fine with. Yeah. We've spoken about this now five times or so with the FDA, and it's absolutely acceptable to them. Okay, good. Very helpful. The other question is the ex vivo versus in vivo, you know, say progeny cells distribution in tissue. Maybe, you know, the any learning you can have from, say, Intellia's IND clearance or your partner Verve, hold, you know, anything you can learn from your 301 on these aspects. Yes. We obviously have had extensive discussion with the pre IND with the 301. Of course I don't have access to the, you know, the submission from Intellia. We know a little bit about Verve, but the really the pre IND conversation we had with the FDA was very clear in terms of the guidance that they provided. It was also clear to us that, you know, the fact that Intellia is actually clear the IND is not surprising to us. In the pre-IND feedback that we've received, It's obviously a very significant data package, but there was nothing that would prevent us almost like a systemically, ever, you know, sort of, creating this impossibility for an IND to be done. We didn't see that. It just it's a very, you know, heavy data package, but nothing more than that. With Verve, our perspective is maybe they didn't quite meet all of the data that they wanted to see, but it wasn't anything that was of concern of, you know, base editing versus nuclease. There's no biological rationale for that to be the case. Okay. Then, you know, you are you on track to submit by the end of this year in quarter-? Yeah, we still- 2024? We remain on, yeah. For 301, we guided that will be either the end of this year or early next year, and we're on track for that. We've also accelerated 302. This is the alpha-1 antitrypsin program, to the extent that we can, we are continuing to guide to be on track for, in this case, it's probably likely to be a CTA submission early in 2024. The reason why we are going for a CTA submission rather than IND at least in the first place, is because in many parts of Europe, the protein replacement therapy for alpha-1 has not been licensed. Therefore it gives us the opportunity to generate much clearer readout so that we don't have to worry about teasing apart the upregulation by the edit versus the protein replacement that's there. That's why we like it. Eventually we will of course, generate data in U.S. as well. Okay. Very helpful. Going back to BEAM-301, you know. -the IND package, like now we still have maybe, less than a year. Mm-hmm. Like, what are the steps you need to-. Yeah. -prepare and what data package to submit? Yeah. It's basically there is a sort of IND tox studies, which is, you know, similar. Typically, it's rodent and non-human primates. The really the sort of the one thing that makes the, you know, this guidance to some extent a little bit movable at the moment is also the formal biodistribution study needs to be done with the final drug product. The final mRNA for the editor, the final and the final LNP. The biodistribution, although we have data already that we've done in non-GLP conditions, there may be the odd cell that might be different between the two. We don't know until that data package has been generated, how many off target biology cell packages we need to do. One of the additional things that FDA's want to see in the in vivo setting is that the off-target excuse me, the off-target biology should be done not only in the target cells, but also in all of the cell types where the, but the drug product distributes to. That's not just at the tissue level. For instance, if it goes to the spleen, they want to see also which cell types within the spleen does the RNA actually go to. Then they want to see the same off-target package for that cell as well, regardless of whether you see editing or not. It may swing, if you will, the amount of data that we need to generate at that point. Other than that, the assets are the same. It's just a matter of, you know, generating the information. Okay. That's super helpful. Tox study, rodent, non-human primates, usually how long they will need? Yeah. They usually. There is a period on target. Basically, there's gonna be, we're gonna follow them for a month. We also have a recovery period that will be longer than that. Overall, the study will take between 4 and 6 months. Okay. The, I think if I got you correct, the NHP, the biodistribution, and then you're not sure if the GLP biodistribution will be required by FDA, right? We want to do the biodistribution with the formal. Mm. -drug products. This is- Okay. really the material that essentially is gonna go pretty much into the clinic. I see. Okay. That's really. We reserve a little bit of flex in that, but we're not expecting huge deviations from what we're seeing already. Okay. Good. Very helpful. Actually biodistribution, would they have some kind of requirement how much excess of doses, if you try to translate that to, you know, say, therapeutic window in human, will FDA have certain requirement of what dose you need to? No. Depending on the dose, maybe the biodistribution will be slightly different. Yeah, they don't. Typically what we do, you do to the highest dose that you can actually go. I see. in the biodistribution. You just, again, you create the worst case scenario so that it. I see. -the risks when. Basically animal like a maximum tolerated dose. Yeah. It will be, thereabout. You don't wanna go to. Yeah. Yeah, it will be the maximum tolerated dose. You don't wanna push it where it signs of intolerability exist because then that could change the biodistribution as well. I see. Okay. Yeah. Very helpful. Then CTA and IND package, any differences there? Yeah, there is some. Typically the FDA is a little bit more conservative in the package that they want. For instance, a progeny study, it's unlikely to be fully required by regulators, although they certainly prefer to see that data prior to dosing of some cohorts. They may be the requirement of the different cell types for off-target biology is less stringent in other. We don't yet have formal regulatory interactions, frankly, with other agencies to be able to completely guide you on that. That's from prior experience and also what we know from other sectors. Since you are going back to U.S. anyway in the future. Mm-hmm. Like, will you just collect all the same level of the details as if you prepare for the. Yeah. the 301? With the BEAM-301, we're still considering both U.S. and ex-U.S. Mm-hmm. In part that's driven also, by where the patient population actually is. Yes. We are, definitely, aim to prepare a package that is consistent with U.S. Yeah. Obviously some of that package can be redeployed in other settings as well. We will be doing the same for BEAM-302. As I said, we plan to have IND filed for the two programs anyway. We're just gonna, you know, plan ahead for doing that. Okay. That's good. very helpful. I do learn a lot with this. That's okay. Thank you. Going back to your clinical program, sickle cell, the BEACON study. First patient already enrolled in November. 2022. Right. Have you dosed that patient? Any status regarding the patient enrollment? Yeah. No, we have not dosed it yet. We have guided it. Typically, remember it's a very complex process that they need to. We expect on average that to take about 6 months, and we're on track for that kind of timeframe. Remember, these patients need to first of all go on to transfusion to count the bone marrow. They then need to go through mobilizations. Typically, it's 2 to 3 cycles of mobilization. That's to essentially generate as many CD34 cells as we possibly can. Those cells are sent to the manufacturing sites, where they're electroporated and the editor is introduced. They will be freeze-frozen and undergo a source of tests for release. Back to the clinic where there will be essentially conditioning of patients initially in this case for with busulfan, but hopefully in the future with our improved conditioning regimens. Finally dose. So, you know, you can understand why technically it takes, you know, the 6 months. But we're on track. In fact, very recently we announced a protocol amendment that actually is accelerating the way in which the Sentinel cohort can actually be enrolled into the study so that there is much more compression between the first patient and patient number 2 and 3. Such that we have guided now that we believe that we will complete the Sentinel dosing, we will initiate enrollment of the expansion cohort by the end of this year. That expansion cohort is really what is on the critical path to the BLA. The design of the study is intending to be pivotal and, in a, in a design which is very similar to what you've seen for CRISPR/Vertex. The quicker we start the expansion, the quicker obviously we can go to the end finish. That's our aim. Part of the acceleration of one oh one is to reduce the time between Vertex launching and us coming to the market. Okay. Very helpful. When do you think it will be realistically showing initial data? We announced that we're gonna be waiting until 2024 really to share some more meaningful clinical data. We have chosen not to do what has been done in other setting where a single patient data was really... We just don't think that it's really clinically meaningful to do. Having said that, we will probably make some... We haven't decided yet, but it's likely that we could let obviously community know that we will have formally initiated the enrollment of the expansion cohort. Mm-hmm. Infer from that we must have had a successful engraftment for the first patients. The first sentinel. Otherwise, we wouldn't be able to get there. There is an element of being able to be reassured that the progress of the study is on track whilst not disclosing clinical data that may not necessarily be meaningful to interpret following just a single patient, for instance. Without your data, would that be a little bit difficult to enroll patients to let them know? No, we're actually seeing an incredible, you know, desire actually to come onto our trial. In fact, there are several sites that are waiting for the sentinel to progress in order to patients have already been identified for that. There is a real desire actually for coming onto the trial that we are set up regardless of the data. I think that, frankly, our preclinical data with models that are very translatable, on what we've seen is certainly the best that I'm aware of that has been published. If that's were to be reproduced in the clinic, there is a lot of interest to be that patient. Maybe going to the competitive landscape. We saw quite a few others all showing like around maybe 40% that range. Yeah. the fetal globin, you know. What will be like clinical profile do you think that will be competitive? Yeah. We would like to be able to see that reduction of hemoglobin S to about 40% or less. In preclinical data, that's where we're at. We see a 60/40 ratio between the F up-regulation that we make. The reason why that 60% is important, we feel, is because it's only when you get to this level that actually you start reducing the hemoglobin S, because as you know, there is a, it's called a locus control region. Basically, there's a finite amount of hemoglobin protein that any given cell can make, and you need to push the system to making a lot of F to reduce the amount of S that it's making. Vertex and CRISPR at the moment, they still have about 55% hemoglobin S last time I've seen it. That's certainly something that we'll look at that. We expect that resolving VOCs will be similar to what Vertex and Bluebird have seen. It's difficult to really compete above 90+%. We expect our product to have to do the exactly the same thing. What we will be looking for is if even deeper biomarkers of resolution of all of that inflammatory milieu that sickle cell disease makes over and above VOCs that actually contribute to the disease. That's where we think our profile is very competitive. It is still intriguing to me that the moment from the Vertex, we've only seen the VOC data. To my knowledge, I haven't seen any additional biomarkers like resolution of hemolysis, viscosity of the blood, half-life of cells that would provide a much more comprehensive clinical package of resolution of sickle cell disease. That's what we aspire to generate. That's very helpful. The you do have also wave two and wave three conditioning regimen. I think that some feedback from sickle cell community, you know, the conditioning regimen is one very major hurdle there. You know, the important consideration for patients are willing to take the new next generation of genomic medicine. Maybe a little update on the wave two and the wave three. Absolutely. Yeah. You know, clearly busulfan, as you mentioned, is a major limitation, particularly due to the sterility that it causes. Having said that, though, I really wanted to stress the point that we do see that even in that setting, there is a very meaningful market. If you look at that, is every year, even with busulfan, there is about 1,000 patients that want this particular transplant with busulfan, and yet only 20% are eligible because of the donor issue. In this case, we don't have the donor issues because it's autologous. Even if you envisage 1,000 patients a year with a price point per treatment of $2 million-$3 million, that's a several billion dollars market already. I don't want investors to dis-discard that like that. Having said that, we think we can expand that significantly if you eliminate the busulfan. One of the approaches that we're making is what we call ESCAPE, which is we're benefiting from the precision and the ability of base editing not to do double-strand break, so that now we have a multiplex edit where not only do we have the edit that corrects sickle cell disease, but also now we add an edit that makes those edited cells basically stealthy to an antibody that can instead eliminate basically the non-edited resident cells. Through that approach, we feel that this would create a huge opportunity not only for sickle cell disease, 'cause obviously it would eliminate the toxicity associated with busulfan, but could potentially become a very transformational approach for transplants in general. That kind of approach will be able to be used in other transplant settings for oncology and other diseases. That's super helpful. I think that we only have 1 minute. Wanted to ask you about the, you know, the allogeneic CAR T program. Yeah. You know, the source there and the, you know, rationale for selecting. CD19. -CD19. Yeah. still on track for dosing our first patient midyear. This is initially for CD19 positive TALL patients, but also expanding to CD19 positive AML, which is, by the way, about 11%-15% of the patient population. The reason for basically picking CD19 is that CD19 is a well-characterized and expressed target in all of the T cells. In fact, one of the reasons for going after that is that originally these TALL were left a little bit behind because when you target CD19, essentially you are killing both your CAR T cells as well as the cancer cells. This is a phenomenon called Fratricide. You need to eliminate CD19 from the cells in order to prevent that. That then pushes you to do many, several edits. In fact, BEAM-201 is the first quadruple-edited CAR T cells that I'm aware of, and we were able to do that without chromosomal rearrangements. That's in part what we've done. For next generation of CAR Ts, we really believe that we need to get to an allogeneic series of edits that are much more persistent than what has been possible to do so far. We don't believe that B2M knockout alone is gonna be sufficient, and I think the clinical data is supporting that view. We're working very hard on making additional edits. Ultimately, we believe that you need 4 to 6 edits to be able to get there. That's why base editing is ideally placed to be able to do that. Okay. Well, thank you very much, Pino. Thank you, Gena. We look forward to lots of updates. All right. Thank you. Thank you.