Beam Therapeutics Inc. (BEAM) Earnings Call Transcript & Summary

Welcome to the afternoon session of Day 2 of the Bank of America Healthcare Conference. My name is Greg Harrison, and I'm one of the biotech analysts here at BofA. I also have Mary Kate Davis from the team here with me. And it's my pleasure today to introduce John Evans, Chief Executive Officer of Beam Therapeutics. John, would you like to start off with some opening remarks, and then we can jump into Q&A?

Sounds great, Greg. Thanks for having us. It's great to be here this week back in person. So I'm John Evans, CEO of Beam. I've been doing this from the beginning of the company, about 4.5 years now. Before Beam, I was at Agios for several years developing drugs in cancer and rare diseases. So Beam is a next-generation gene editing company. So we're in the CRISPR field, but we are a newer way of using CRISPR that fixes some of the deficiencies of the previous technology platforms. So I put us in the general category of onetime cures and this big push in the industry towards that vision. Of course, that begins with gene therapy where you're trying to add some extra gene into the cell. Then it's moved more into the interest in gene editing, where wouldn't it be better if you can actually just fix the genome itself in a more direct and durable way. And then gene editing tools themselves have gone through these waves of innovation, starting with Zinc Fingers and TALENs then moving to CRISPR, of course, but still all making double-stranded breaks as the means of editing, which is sort of cutting, which is where you come up with the analogy of calling it the scissors of the genome. And then base editing is sort of a 2.0 version of gene editing, where instead of cutting, we're going to more precisely change a single base within the gene sequence and do it without creating the break. So that gives us lots of advantages both in efficiency and specificity and potentially safety, which we're quite excited about. So we see this as a potentially best-in-class way of doing gene editing. Then in addition to that piece, we've sort of said, well, if this can be so broadly applicable and potentially a best-in-class technology, we need to get it to patients everywhere. And so the other thing that Beam has been really active doing is building out delivery technologies. So we made the important decision early days to go after all of the available ways to deliver genetic medicines. So this is ex vivo editing of blood cells in hematology. We have programs there in sickle cell disease and then more to come, ex vivo editing of T cells in CAR-T. So we have a program there for T cell leukemia and then again many more places to take our technology to create highly engineered cell therapies. And then in vivo editing, doing things like lipid nanoparticles and viral vectors to reach different tissues in the body and do direct editing there with some of our lead programs coming in the liver using lipid nanoparticle delivery and then again many more to follow. So it's a very broad portfolio, lots of different ways to help different kinds of patients and broad capabilities that we can apply to many different diseases over time. The last piece of the puzzle then is manufacturing. So in addition to the payload and the delivery, we're building manufacturing internally. It's not open yet, but by the end of next year, we should be up and running with a very large manufacturing facility in North Carolina that will be under our own control. So that starts to be really what we're trying to build with Beam, which is an integrated platform for precision genetic medicine -- the right edit, the right delivery, the right manufacturing for really any disease, and that will create a sustainable pipeline for us as well as be substrate for a lot of partnering opportunities as well.

Great. Maybe you could talk a little bit through how the base editing actually operates and what types of edits you can perform and what that gives you the opportunity to do.

Yes, great question. So what we do, we're using CRISPR. And we use CRISPR for that same flexible targeting ability that is why CRISPR is so famous and so popular. And it is indeed a breakthrough. What we've changed is the edit. So once the CRISPR gets there, normally, it just cleaves and it cuts the DNA at that target side. So we've turned that off. So we're not trying to fully break the DNA, but instead, we sort of open it with the CRISPR. And then the edit is made just by a second component, which is tethered to that, and it's called the deaminase. This is a chemical enzyme that actually occurs in all of your cells, and its job is to modify bases and turn them from one into another. And so we can use 1 of 2 different kinds of editors to make 2 different kinds of chemical modifications to the DNA. One that does an A to G edit and the other does a C to T edit. And if you think about it, every base pair in your body has either an A or a C in it. There's either A-T pairs or G-C pairs. And so that means that every base in the genome is potentially editable and we can then modulate its function. And so what do we do with that? We do a lot of things. So first, certainly, we do things like point mutation repair. So you're correcting a single letter misspelling in a gene and turning it back to normal. So this would be things like sickle cell disease where every patient has the same single-letter misspelling or alpha-1 antitrypsin deficiency, where again, every patient has one letter wrong. We can turn it back to normal. So that's a big part of what we do, but there's many other things as well. So we can also use single-based changes to silence genes, and that's a universal strategy. So really any gene is potentially silence-able with a single base change. And now we've done that without using the cutting that you get with some other tools. We can activate genes and turn them on, like going to the on-off switch and making a single base change there. We can modify their function, right, by changing a protein sequence, changing an amino acid in a surface of a protein. So there's really a vast set of ways we can use this, and we see it as a very versatile system. And our pipeline is, in some ways, designed to tease out all of those different applications and exploit them in parallel.

Great. Now given that you're developing both in vivo and ex vivo programs, could you walk us through the delivery mechanisms used in each and how that -- what are the advantages, disadvantages?

Yes. So for us, there's no perfect delivery technology, but delivery is incredibly critical to making our technology work to really make any genetic medicine platform viable. So ex vivo, what we're doing is we're taking cells out of the patient. We are then taking them to the lab, manufacturing them there. We generally use electroporation, which is a little electrical current that will send the editing machinery into the cell, then it will be expressed, move to the nucleus, edit the DNA. It's a fairly quick process. Then those cells are administered back to the patient. So in sickle cell disease, this is an autologous therapy. So you're literally taking the patient's own cells out of the body, fixing them and then putting them back in. And in the T-cell, the immunology portfolio, we're using allogeneic cells. So we take healthy cells from a donor, edit them so they can target tumors, and then dose many patients with those cells. And so that will be a more scalable and hopefully effective way of doing CAR-T style therapy versus the autologous approaches. In vivo, we're doing a few different things. The core main one that we're using is lipid nanoparticles, and this is exactly the same as the COVID vaccines that many people here may have gotten. So this is an mRNA payload that encodes for the editor. It has a guide RNA, which is the targeting element for CRISPR. And then it's encoded in the lipid nanoparticle. And so we use this in a few different ways. So one is we can do just an infusion in which it will go to the liver and efficiently edit hepatocytes there in the liver. But we actually have technology as well where we can do screening in animals and identify lipid nanoparticles that can go to other tissues as well. And we do this with DNA barcodes that are actually loaded into unique LNP formulations then dosed all at once into the body of these animals, and you see where they go. Then you can optimize different LNPs for different delivery formulations. So for instance, we've shown the ability now to take LNPs not just of the liver where our first-gen applications will be, but also to things like the blood, so editing the marrow directly after an infusion, editing immune cells in vivo. We're looking at CNS. We're looking at muscle. So we think LNPs could be a really broad and quite an interesting platform for in vivo editing and for a variety of different tissues. The other way we deliver in vivo is with viral vectors. So we've used a little bit of AAV, which is, of course, a famous well-known vector. We're using it initially in the eye. Of course, Luxturna has already been approved there. So that works. But I would say that long term, we are looking at other options in the viral space. We think AAV is good but could be improved, especially for editing. So we have some research area efforts on that front. And in the near term, probably putting more into expanding the LNP nonviral delivery for in vivo editing.

Great. Maybe just to talk a little bit more about the safety advantages that Beam's base editing could have. Maybe what are the benefits of avoiding double-stranded breaks? And how could the safety maybe compare to a more traditional CRISPR Cas approach?

Yes, it's a great question. So yes, why do we care about the double-stranded break? I think that for a lot of people, this was clearly the part of the editing system when the first version of these technologies came out that could be improved, but it's important to understand why. So a double-stranded break is a genotoxic event in the cell. So it is a sign of DNA damage. And the cell is definitely alarmed when it sees it. You get some DNA-damaged pathways that come up and then it rushes to sort of put the pieces back together again -- so it doesn't want to lose control of the chromosome. So it does that and then it basically does so with errors. So it makes random mistakes, both insertions and deletions that are called indels, okay? And that's, of course, why the cutting works as an editor because it actually scrambles the gene sequence at random at the cut site. You can't control the sequence you get. You actually end up with tens or even hundreds of different unique alleles cell to cell, but you're definitely going to scramble the sequence and it will no longer code in the right way. So that's where other sort of nuclease companies are using this to knock out genes, right? Scramble them pretty well. So all that said, sometimes it doesn't get the pieces back together again. So you can occasionally get chromosomal changes. You get larger-scale rearrangements of chromosomes, which are certainly concerning. They happen at a low frequency, but it's certainly not zero. They get particularly concerning if you add more than one edit at the same time. If you think about it, you're stacking breaks all at the same time. The cell doesn't always know how to put the pieces back together again. So that's sort of one category of advantage. And I think certainly, things about safety and genomic integrity are places where base editors look like they have an advantage there. Other advantages are actually just they're very efficient, right? So our editing is just chemistry, right? So it's all biochemistry. This is enzyme modification of the genome. So we aren't reliant on complicated repair pathways that may be active or not in the cell at any time. The cell maybe -- doesn't have to be dividing or not dividing in the right moment. Once we're in the cell, we'll go to the nucleus and we will edit. And so we generally get very high levels of editing efficiency, often more than a nucleus. So our lead sickle program, BEAM-101, has over 90% editing at the target site. Our CAR-T product has 4 different edits all at the same time, all about 95% editing efficiency. So we think that just the raw efficiency and precision of it is really, really strong. And then the last area of advantage is just the control of the gene sequence you get out the other end. So we know exactly what GNC sequence will result at the target site, and it is a much purer outcome than that sort of random scatter that you're getting from others. And so we can characterize that, we can sort of fully understand the safety and the therapeutic effect of that edit and then do, as a result, a lot more different kinds of things than I think you can do with earlier technologies.

Great.

Maybe we can turn to the BEAM-101 program, sickle cell and thalassemia. Maybe talk about your approach there and how you see the landscape in this somewhat crowded space and where you could set yourself apart.

Yes. So the space is crowded, although at this point, you've got really the CRISPR Vertex program that I think looks like it's on track for a filing towards the end of this year, which we're hopeful does happen. And then I think really, we're right in the mix to be kind of the next gen there, and I think we're quite differentiated on top of that. And there's still, of course, a huge unmet need in a massive population there. So we actually are quite excited about the opportunity to really bring something unique to patients in sickle cell. And we think that it is a meaningful market opportunity for the field as well as obviously for our programs. So as a result, we have 2 different programs that are coming forward there. So one is BEAM-101. So BEAM-101 is upregulating fetal hemoglobin, which is the same, now clinically validated approach that others have taken in the past. But we do it with a more precise and more effective at using the base editing. So what we do is we install point mutations in the on/off switch of the fetal hemoglobin genes. We can go directly to those genes now because we're not cutting. And we've identified literally the base that we think gives us the biggest dynamic response in the edit. So we get over 90% editing, which I think is higher than CTX001, for instance. And then we also get more dynamic response for that edit, so we're up around 60% to 65% F. And then concomitantly, what you're really trying to do is get rid of the S, the sickle protein, which is what's causing the disease, and we turn that down to about 40%, okay? So again, that is higher F and lower S than you're getting with other competitor programs. And furthermore, that profile of about 60-40 of the F versus the S is similar to what you see in patients who are normal sickle trait carriers, okay? They're about 60-40 adult globin to their sickle protein. So we think we are fully restoring patients with this down to that trait profile, which is the threshold of disease. So we think that's a superior product and we think it looks like a best-in-class editor for that approach. Then we also have BEAM-102, right? So BEAM-102 is the thing that really only Beam can do, and that's to directly correct the sickle mutation itself. You've taken the one letter that is misspelled, turning it back to normal. There, we're getting well over 80% of editing. And now you're taking a cell population that's all sickle. And by the end of that edit, you're down around 10% sickle protein, and everything else has been turned into normal adult globin. It's a variant of hemoglobin called the Makassar variant, but it's normal hemoglobin. So obviously, that's very exciting as well. So basically, with these 2 products, we see superiority on the editing style and the potential clinical outcomes here. And so we're going to bring both of them forward in sickle. We'll run 2 trials. BEAM-101 obviously will start first. BEAM-102 IND will get filed later this year. And then we'll most likely move just one of them forward to commercialization based on data. We'll just make a data-driven decision in sickle. BEAM-101 obviously also has application in beta thalassemia as well. But bottom line is we see a strong potential for these to be preferred products by the time we reach the market, and we think it is a meaningful market. and then by the way, then over the long term, we think we can even grow the market from there by doing additional life cycle changes in these programs where we go back and we fix conditioning to make the transplant less toxic. That will open this up to more patients. And then even the third generation would actually be an in vivo delivery of these editors using a lipid nanoparticle, and then you get rid of the transplant altogether. So we see a steady progression for these sort of core editors to get to a compelling regimen that's really friendly for patients and will grow the market over time.

So how do you anticipate that these factors that you've mentioned could translate into efficacy when the trial reads out? -- I mean it's -- if patients are already having 0 or close to 0 VOCs, how do you improve on that even if you are cutting in more efficiently?

Yes, there's no question. And from my perspective, it's amazing news for patients that such a high bar is getting set on VOCs and that's nothing but good. And so I certainly hope that CRISPR Vertex continues that way. It turns out that with a relatively modest amount of correction, you can get that VOC eradication and stabilize the patients on that front. It also looks like so far that VOC lowering will be an acceptable end point to the FDA. Of course, we have to see that play out. But that's really good, because what it means is it gives us a very well-validated path to filing in sickle. And so we are certainly studying what CRISPR and Vertex are doing. We study what Bluebird has done. Our trial is designed in a very similar way. So we have to go through a sentinel phase where we do one patient at a time just to confirm safety and engraftment. That's with the FDA's oversight. But then once that's done, you can really open up to continuous enrollment. We'll open up to about 45 patients in each trial. And then we do hope, if all of this plays out the way we might, that we could then file that trial. So I think that we are setting ourselves up to follow a similar path, and we would certainly need to be competitive on eliminating VOCs, for sure. Now to your question, people with sickle cell don't die of VOCs, okay? They die a lot of other things. And so there's definitely other damage that is going on in their bodies that may not be captured by that measure. And so that's the opportunity to show not just the editing differentiation but the clinical differentiation over time. So we will be looking at things like hemolysis, right? Do you -- how many cells have you left behind that are still unedited right? So that high editing efficiency may make a big difference because those cells are going to turn over and eventually can create risk of AML or MDS, Rheology: what's the quality of the blood? Organ damage, right? That's often what does kill you eventually. So can we measure changes in the inflammation state or the other sort of organ parameters? Pain, there may be a lot of subclinical pain or pain that is not all the way to getting you to the hospital for a VOC but may be unaddressed. And so we think across all of that, that's going to give us a lot of opportunity, I think, to look deeply at these patients and help understand what does cure look like, how close can we get and where are we going farther based on the precision and power of the edit versus previous therapies.

Great. Now when we look at the BEAM-102 program, what advantages could there be to that approach relative to 101 just in that you won't have these high levels of fetal hemoglobin, which we normally don't have? Is there any disadvantage to people living the rest of their lives with high levels of fetal hemoglobin?

Yes, I think that's one of the sort of open questions in the field on the F strategy, which I think is fair. That said, I'd like to point to -- there are patients -- and the reason we know fetal hemoglobin helps with these diseases, there are patients who are beta-0/beta-0 patients who literally have no normal hemoglobin and -- but they have F upregulated and they are protected from beta thalassemia. They seem relatively normal. I mean there's not an obvious deficit, and they have 100% F. So I think we don't really have good evidence that there is a problem. It's sort of an open question, I guess. So you're right. I mean I think that certainly, the attraction of 102 on one hand is that it is just normal hemoglobin and as opposed to F upregulation, but I think F is now clinically validated and works. And we really don't see a lot of evidence that it will have a drawback. So I think the other attraction of 102 obviously is you're eliminating the S from the cells, so you have certainly even lower levels of sickle globin. Does that make a difference? We will see.

Okay. Maybe we can talk a little bit about the 201 program. How did you settle on this particular indication? Is it a way to prove your concept of editing these T cells? And how are you looking at that?

Yes. So the interesting challenge in T cell editing for cell therapy is we really need things to be allogeneic, right? Autologous is very powerful but it is not scalable. It's not going to get to patients enough. And so we've said from the beginning we need to be allogeneic. The problem with allogeneic is we don't yet fully know how to make things allogeneic. So we have the ability to edit at very high levels. So the question is what are you going to do first. And so -- and to explain that, this is another place where the double-stranded breaks become relevant. So with making these more sophisticated cell therapies, you want to make lots of edits. But if you make lots of cuts using first-generation technology, you will create a lot of translocations and errors when those pieces are put back together again, and cell viability really starts to fall off. So if we want to make cells that have a lot of edits in them, you're really going to need to use base editing. And we see that as a clear trend in the field, and that's going to play to our advantage. So when we looked at for a first application, what we chose was this sort of T cell leukemia population because it needs a lot of edits, first, and it's very clear how it will work, okay? And so the B-cell leukemias are, of course, the targets for the CAR-Ts using CD19. That's Kymriah and Yescarta. And those work great. So the T cell leukemia has been left behind for specific reasons. So if you create a CAR-T against a T cell antigen like CD7, which is the one we're using, your CAR-T also has CD7 on it. And so the CAR-Ts will kill each other before they have a chance to kill the tumor. And that's called fratricide. And so people have sort of ignored it. So we can fix that, right? So in addition to knocking out TRAC -- and we knocked out PD-1 and CD52 to make it allogeneic, we also knock out CD7. And so the CAR Ts ignore each other until they can see the tumor and then they kill that. So it's a quad-edited cell. Every edit is made at 95% knockout, no cutting, and looks very, very potent. So that will be an IND this year -- later this year. And it's just a population that's been ignored. They're desperate for new options, and we're quite excited to bring that to them. Longer term, really, it's about identifying what are the edits that are needed to make things increasingly allogeneic that can then bring that kind of technology to many more patients, many more indications over time.

Great. And then looking at the BEAM-301 program, can you just walk us through that strategy of using lipid nanoparticles to deliver in vivo?

Yes. So here, we're going to now target the liver. We're going to go in vivo. So this is -- lipid nanoparticles are a really growing and exciting technology. Of course, begins with Alnylam with delivering RNAi and ONPATTRO. And then Moderna came along and started to figure out how do you deliver mRNA, which are much longer than RNAi and so you have a bigger payload challenge, but they did that, and they successfully did it. We and of course, our President and Chief Scientific Officer, Pino Ciaramella, came from Moderna. He did all of their vaccines work. So he had a lot of experience in mRNA and LNP delivery. So we have engineered now our own process to make LNPs work for the liver and do it potently and scalably and with good process control parameters and things like that. And so when we deliver a base editor to the liver, we're going to hepatocytes and we're trying to edit there. And as soon as it's in the cell, it will edit. So our first program there is BEAM-301. So this is again a point mutation correction. So we're going after the most common single base misspelling in a disease called glycogen storage disease Ia. It's a terrible disease where patients can't reprocess glycogen to glucose, which means they can't fast. And so literally, even overnight, if you don't eat every 2 to 3 hours, you can die of hypoglycemia. And so you're constantly needing to wake yourself up and feed and make sure you don't fall into that trap. So we can correct that and do that with this editor. In a mouse model that disease, with a single administration of our editor, we normalized mice. They live normally at normal metabolism, normal glucose control. Without the single treatment, they're dead within a couple of days. So beautiful illustration of the power of this potentially to be a onetime transformative therapy. So that was a development candidate nomination at the end of last year, and that will be in IND-enabling studies in the second half of this year, which is then set up for next year and IND filing. So very excited about that as a sort of important program for those patients and then also kind of opening the doors to a very large number of potential liver programs for us over time. And again, the beauty of this -- I mean all of these areas but especially in the LNP world, it's so scalable we could do as little as change the guide RNA, that's the targeting element, which is a short RNA sequence in CRISPR, and replace it with a new one. You have an entirely new medicine, right? And yet everything about that product, the acute toxicity, the manufacturing process, the regulatory package is going to be identical from one product to another. So once -- it obviously takes a while to get the first one to where it's ready and you still are working it out and finalizing it. And that's all the work we're doing right now. But gradually, once we get that flywheel going, then we can start to create many products very quickly over time because all you're doing is plugging in a new genetic code sequence for where you want to target and everything else is the same.

So do you think that could speed up regulatory time lines in the future? Have you discussed that with the FDA? Are they receptive to that just overall?

Yes. I do think that's possible. We know from other genetic platform companies that they have been able to start skipping steps after a while, right? I mean you don't need to do the fifth acute tox study if it's going to show you the exact same result every time. All you're doing is changing the sequence of the letters and the genetic sequence. Everything else is the same. They will let you start to skip those steps. So I think that does start to happen, and that's really important. And the other frankly more important thing is not just the time lines or the cost of avoided studies. It's the confidence, right? The thing that's the most important thing in biotech is probability of technical success, right? Is it going to work? If you all knew it was going to work, this job is easy. So the value is that once you've shown it works once, it should do the same thing again and again. And then you can really start to go fast. And so my favorite example of this is Alnylam on the RNAi side of things, where it took them a long time to get the first gen going. We hope to do a little faster than that, but once they did, it started to be very predictable. And more recently, now they've gone, I don't know what it was, 6 for 6 in Phase III trials or something like that, right? So that's unheard of in the small molecule world. So that's the promise. And again, we're getting there. We're not quite there yet, but as these become increasingly plug-and-play, those time cycles are shortening and the probability of success will be correlated in a positive way.

Now what's the status of the alpha-1 antitrypsin program? That seems to me at least like kind of an ideal disease for your approach.

We agree. So alpha-1 is a huge population, great unmet need, about 60,000 patients in the U.S. So every patient, again, has a single letter misspelling in a gene for this protein called alpha-1 antitrypsin. The mutant form of that is then building up in their liver and causing liver toxicity, which can lead to liver failure eventually. And it's not successfully being secreted where it's supposed to be in your bloodstream protecting your lungs from degradation, which can lead to emphysema, oxygen support and ultimately even double lung transplant. So it's a terrible disease. And it really doesn't have good therapies. It has not been a good target for gene therapy. It has -- some people are going after one or the other side, maybe just the liver or just the lung. But in terms of a transformative approach that can address both sides, there's really been not much. So our approach would do that. So with a single letter misspelling, we can change it back to normal, and every allele we fix is not producing mutant protein and is now producing the normal secreted protein again. And it's in a coding region of the gene, but because of the precision of the base editor, we can go in there and make those changes and we still have a functional gene at the other side of that. So very excited about the program. We actually just announced we'll have an updated data set at ASGCT coming up really soon, and we're showing increased potency of those editors. So we've been working on that target site and making sure that we're as potent as we can be. So I think we're around twice as potent as some of the earlier things we did and at lower doses, which will be effective in the clinic. So quite excited about that. We have said that we will get at least one additional liver development candidate this year. So alpha-1 would be a candidate for that as well as a second glycogen storage disorder program and then even some of our partnered programs with Pfizer and Apellis and others are candidates. So I think there's going to be a lot of potential in the liver both rest of this year and then into the following year to start to really go fast.

Okay. We're running low on time, but I wanted to touch on prime editing and maybe you could talk a little bit about how that's unique and what that would allow you to do beyond your traditional base editing.

Yes. Maybe I'll answer that in a slightly more general sense, which is we do a lot of different deals that I think are quite creative. We've done sell-side deals for Pfizer and for Apellis, that are quite famous. But equally, we're doing these sorts of innovator-innovator partnerships. So one was Verve, for instance, where they're using our base editors to do cardiology editing to prevent heart attack, very, very exciting. Prime, really exciting, newer technology, kind of like base editing where it doesn't cut but it makes other kinds of changes. So we did a deal with them to get access to that technology and sort of our field of use and then work with them on delivery technology and other things to sort of help them get going. So that's a really synergistic symbiotic relationship. And I think those sorts of things, we'll do more of them over time. It's a way we take advantage of the depth of our platform to get access to what others may have and deepen our technology stack so that we can always be on the leading edge of where technology is going.

Great. Well, with that, I'd like to thank you, John, for joining us, and thank everyone here in the room today as well. All right.

Thank you.