Good afternoon. My name is Gena Wang. I am SMID-cap biotech analyst at Barclays. Welcome to our second virtual Global Healthcare Conference. First, I wish everyone stay healthy, and I would like to thank all the participants, investors, and companies, and especially our event team and our corporate access team who made this virtual healthcare conference possible. With that, I would like to introduce our next presenter, John Evans from Beam. John, I hand over to you. Great. Thank you, Gena, and hello everybody. Great to be with you. Let me bring up some slides that I think will help us introduce the Beam story, and then we'll close that down and go into a Q&A, which I think will be hopefully quite illuminating. Beam is really a next generation of technology in gene editing. The goal here is really to improve our ability to make precise changes in genes that could be potentially curative, and do so without some of the things that have held back some of the earlier generations of gene therapy and gene editing technology, which I'll describe. We were founded by three of the leaders in the gene editing field, David Liu, Feng Zhang, and Keith Joung, and have been growing ever since 2017, with some very exciting technology. I will be making forward-looking statements today. As I said, Beam is really part of the vanguard of a set of companies that are really trying to transform medicine. We want to create what are going to be, we believe, lifelong cures for patients suffering from serious diseases. That means these are one-time curative therapies, which is, of course, a dream in medicine. Of course, we'll begin with rare genetic disorders, but really this can be applied to common diseases as well. Importantly, this is a platform, which means that if we can do this once successfully, we can do it potentially many times with relatively modest incremental investment, because these are ultimately programmable therapies, that based on a genetic sequence, you can quickly retarget, to create new versions. Beam is pioneering an approach to gene editing called base editing, which is really a fundamentally new way to do gene editing. Gene editing to date, as you may be familiar, has a few different versions. You have, of course, zinc fingers, you have TALENs, and then more recently, you have CRISPR. CRISPR, of course, was a big breakthrough in the field because of how easy it was to retarget. If you think about the challenge here, you're trying to discriminate a single address out of three billion bases in each cell so that you can land on the right spot. That is an incredible challenge, but each of these systems have solved that, and CRISPR has solved it in the most easy way. It's very flexible. You can rapidly retarget it by reloading the CRISPR with a different guide RNA, which tells it where to go. If you step back and say, okay, well, once you get there, what kind of edit are we making? All of these tools have made the same kind of edit to date, that is a cut or a double-stranded break. The analogy we use is that of having scissors for the genome. Once you get there, you make a cut. The cell will then put the pieces back together again, but will do so with damage. You'll have random insertions or deletions at the target site. You will disrupt that gene, but your ability to really reprogram it and to fix a gene is really quite limited. That was the backdrop for some great scientists in the lab of David Liu at Harvard to work on a next generation version of this system called base editing. The idea here is we want that same targeting ability that I mentioned before, but now once we get there, we want to make a much more precise change, down to the level of a single base, and we don't want to disrupt the sequence. We never want to lose control of that genetic code. The analogy we use is like having a pencil for the genome where we're going to erase certain letters, write them in a place, and we didn't change the sequence around it. That turns out to be exactly what we can do with this system. This is a base editor. We do use CRISPR. You can see that in gray. It is exactly the same targeting ability that you get with normal CRISPR applications. It's a guide RNA loaded into the CRISPR. That guide RNA encodes the sequence, which is the address within the genome where we're going to search and bind. Once it gets there, it sort of matches up with the DNA and actually opens it up. Now the differences begin. Instead of in normal CRISPR applications, once you've done that, the CRISPR will complete a double-stranded break of the entire genome at that site, the cell will put the pieces back together again. Here, we have changed the CRISPR protein so that it no longer makes the full double-stranded break. Instead, it just opens up the DNA. At that point, this second domain comes into play, and that is called a deaminase. Deaminases are chemical enzymes that are naturally occurring in all of your cells, and they catalyze very specific chemical reactions on certain kinds of DNA bases. The deaminase we use will only recognize single-stranded DNA as their substrate, so they will leave alone all of the double-stranded DNA in the cell. Specifically, there's a window of about four bases wide that is available to the deaminase for editing when we have this binding event. You can see that shown here. Our job is to position the binding such that our target base will be in that window, then very quickly, just through chemistry, it'll be modified by the deaminase. We have two different deaminases, a cytidine deaminase and an adenosine deaminase. That gives us a C base editor or an adenine base editor, respectively. The advantages to the system are quite numerous. First and foremost, this allows direct editing of single base pairs in disease-causing genes, without worrying about breaking the gene in the process through scrambling the sequence. That opens up applications like gene correction, of course. The most common gene mutation in disease is a point mutation. A single base change, we can potentially correct those back to normal using this system. That has not been possible with traditional cutting-based systems. That's, of course, a game changer. Things like sickle cell anemia, alpha-1 antitrypsin deficiency. Equally, for more general purpose genome modification, if you want to activate or silence genes or do multiplex editing at multiple sites in the genome, we can do all of that with single base changes. Now we're making those sets of large-scale genome modifications without needing to cut the DNA. Specificity is, of course, very good. We're very precise in the edit we make. We have a low to undetectable off-target profile, ultimately avoiding the double-stranded break gives us a gentler editing profile, which has advantages in many settings. Finally, none of this matters unless you can efficiently produce a therapeutic edit. We get very high levels of precise editing, really in any cell type, including dividing or non-dividing cells, primary cells, daughter cells. That's, again, not true in all CRISPR applications, but it's true for us, because ultimately all we're doing is chemistry. We don't care about the cell state. Once we're in the cell, we'll go to the nucleus, we'll search the genome, open up the DNA, and then just enzymology takes over, and we make the edit. Stepping back, ultimately, we do view this as a potentially best-in-class gene editing technology, very differentiated relative to the field, and we think it's going to be potentially applicable in a wide range of different disorders. Constructing a pipeline. Based on that belief in the potential value of this technology, we said from day one, we have an obligation to bring this forward for patients in every single therapeutic area where genetic medicine is possible. What we've been doing is we've been working across all of the different delivery modalities that are currently available in genetic medicine in parallel. That includes electroporation of cells outside of the body for ex vivo editing in hematology. Two programs in that portfolio to start in sickle cell disease. We have BEAM-101, where we're targeting the upregulation of fetal hemoglobin by targeting the regulatory region of the fetal hemoglobin genes. Here we can get higher levels of fetal hemoglobin expression than anyone else. We have about 60% upregulation, and just very high levels of editing, about 90%, 95%. With BEAM-102, we are doing now for the first time, the direct correction of the sickle cell disease mutation. This is a point mutation that we are able to repair back to normal, and now for the first time, we're creating cells that literally don't have the sickle cell disease mutation at all. This is a very differentiated approach, which is equally exciting for the treatment of sickle. We think these two programs are individually potentially best-in-class programs in the field, and of course, together give a very strong portfolio to potentially cure this disease. In oncology, very different approach. Now we're creating CAR T cells. This has, of course, been a breakthrough in cancer care recently, where we can retarget immune cells to target the cancer. Ultimately, what we want to do increasingly with those cells to make them even more effective is to knock out or edit surface proteins on those cells that will allow them to be allogeneic, avoid exhaustion, become more effective. Ultimately, that's what we can do here. Now, you can also use nucleases to knock out genes on the surface of cells like this. As you add more and more edits, if you're cutting, you're going to create many double-stranded breaks, and that is going to be genotoxic to the cell. The cell viability will gradually diminish, and also you will end up with mistakes as the cell puts the pieces back together again, which are called translocations, where you literally are rearranging chromosomes. With base editing, because we don't cut, we can make as many edits as we want. We don't have that risk. In this case, we're actually making four edits in the cells, the quad edited cell, BEAM-201. That is again, quite differentiated relative to the field. Not clear others are capable of doing that. We think that's a big advantage for base editing and cell therapy going forward. On the in vivo side, lipid nanoparticles, of course, famously, can go to the liver very efficiently. Here we have a couple of big targets, alpha-1 antitrypsin deficiency, huge unmet medical need. Patients with this mutation end up with toxicity in their liver from mutant protein buildup and a failure to secrete functional protein to the bloodstream to protect the lung from degradation. We are able to address both of those problems potentially by just editing the problem at its source, turning this one mutant letter back to normal in these cells. That will simultaneously prevent mutant protein buildup and restore secretion of functional alpha-1 antitrypsin protein to the blood. Equally, glycogen storage disease, a very severe disease in patients where they can't fast, and they could have fatal hypoglycemia. We can target for precise correction back to normal, the two most prevalent point mutations in that disorder, covering about 60% of this patient population, and we think a population that really does need new options. Very excited about that program as well. Finally, we can use viral vectors to deliver the editor, such as AAV. Initially, AAVs have already been shown to be successfully delivered to the retina. We're going to go there as well. Stargardt disease is a big unmet medical need, sort of a central loss of vision, macular degeneration. In this case, we can precisely correct back to normal the most prevalent point mutation in that disease, G1961E. Ultimately, a very broad portfolio. Each area establishing a potential franchise for us in different therapeutic areas. Of course, once we establish delivery to a given tissue, now we can do that again and again very efficiently. With relatively minimal changes, maybe you're changing the sequence of the guide RNA, or you're tweaking the editor sequence, you have an entirely new medicine that can now go to a different part of the genome and treat a different disorder within that same tissue. This early investment phase to get all of these capabilities set up is going to create the ability for a sustainable pipeline over the long term. Near term, obviously, the ex vivo programs go a little bit faster, primarily because there isn't a vectored engineer. That has been seen here. We have the ex vivo programs, BEAM-101, BEAM-102, and BEAM-201, are nearing that IND phase. The in vivo programs are moving along quite quickly as well and are being invested in parallel, and so we expect those to start to become development candidates as well over the next year or so. Specifically, if you can still see the screen, a couple of milestones to look out for over the rest of 2021. First, our first IND filing will be with BEAM-101. That's on track for the H2 of this year. Very excited to see that moving forward. The next two ex vivo programs, BEAM-102, which is the sickle cell direct correction, as well as BEAM-201, our CAR-T product for CD7 positive malignancies. The next milestones there will be to initiate IND-enabling studies for those products. We expect those to occur this year. As that happens, we'll be able to give a little more guidance on the IND timelines for those two products, but they're not too far behind BEAM-101. The fourth milestone to look out for from us in the near term would be lipid nanoparticles in primates in the liver. We want to show editing of test sites, with a potential clinical formulation. We expect to be able to share that data in the H1 of this year, and if we can do that sets us up to potentially by the end of the year, have our first development candidate out of the liver portfolio, and of course, that could set off the beginning of a wave of programs in that portfolio as well. We are continuing to progress the AAV program, doing primate studies as well with the Institute of Ophthalmology in Basel for this targeted correction within Stargardt. It's going to be a very exciting year. Stepping back just for a moment, beyond sort of the near-term pipeline. If you think about what we're really trying to build at Beam, ultimately we're, of course, very well known for next-generation gene editing, things like base editing. We have other technologies as well. We have nuclease technology. Cas12b is a wholly owned nuclease system. We can do RNA editing. We have access to prime editing technology, and there are other things we're working on. Very deep toolkit in terms of next-generation editing technologies. At the same time, again, as I said, nothing matters unless you can deliver it and make it with high quality. Delivery technologies is another huge area of investment for us. At this point, given the pipeline I've just shown you, we have the capability of doing autologous cell therapy, allogeneic cell therapy. All of our INDs and programs are going to be using mRNA technology to deliver the editor. Of course, non-viral vectors like LNP and then viral vectors like AAV. Finally, of course, manufacturing. We announced last year we'll be building a facility to do GMP manufacturing. This will be the largest facility in the gene editing space, 100,000 sq ft in North Carolina. That'll open up in a phased manner beginning in 2023. Really the vision for Beam is to create the integrated engine where we have all of these different technologies under one roof, and we can, of course, assemble them all for our own use, for high-value programs, as well as potentially be a one-stop shop for partnering for others who want to get into some of these spaces in genetic medicine. Finally, let me say that, of course, we've been innovating from day one on the payload side. Delivery initially with our pipeline has been focused on areas of low risk where we know we can get there. It's clinically validated, things like LNP to the liver, AAV to the eye. Ultimately, having built these capabilities, we do want to start to push the envelope there and innovate and start to push where delivery technologies can take us and make delivery as innovative at Beam as our payloads in gene editing. Ultimately, we believe that will be possible. One specific area we've been quite focused on for a while now has been, where can LNPs go beyond the liver, right? LNPs are great platforms for editing. They're scalable, they're synthetic, they have low cost of goods. You can redose them. They don't have packaging capacity limitations. Of course, they're transient, which is fine for us because we want the editor to express transiently, and then we make a permanent edit to the cell. That belief and insight really led to a very exciting transaction that we announced recently, to acquire Guide Therapeutics. Guide is a startup company based in Atlanta, coming out of Georgia Tech. They have a really cool technology where they can basically do high throughput screening of lipid nanoparticles, of different formulations, different lipids, different mixes of those components, then dose hundreds of these different options of these different LNPs into animals all at once, then use a DNA barcoding technology to identify which of those LNP recipes went to which tissues. That basically simultaneously gives you a screening platform to look at all possible tissues around the animal and find these LNP formulas that may be able to unlock those new tissues. We're very excited about it. Lots of opportunities, beyond the liver to think about LNP delivery, things like HSCs, if you think about sickle cell disease, T cells, if you think about in vivo CAR T, CNS, liver. I'm sorry, not liver, lung, muscle, et cetera. A huge opportunity here to expand what LNP can do, and we're very excited to work with that team. Finally, just to say, I think, we are also quite creative in deal-making. We've done a lot of different strategic collaborations. Sometimes we do them with innovators. Thinking about our partnership with Verve, where that's a really exciting company, where they are editing the liver to knock down cholesterol pathways to prevent heart attack. They have access to base editing technology through a deal we've done with them, as well as nuclease technology. Their first program is going to be a base editor. It's an A base editor. In return, Beam has an opt-in right at the end of phase I for a co-co 50/50 split in the U.S. for that program. Magenta, a very exciting collaboration for us, where they're working on next-generation conditioning, which would be potentially less toxic than current options in the transplant field, and we think would partner very well with our base editors. Thank you, John. Additional steps you need to do in order to file on time? Yeah. So far all looks like it's on track. We're finalizing the IND-enabling studies now. Once those are complete, it's really reviewing the data, writing up all the contents, and then making the submission. All of that goes forward. Finishing out the manufacturing as well is ongoing. We have been to the FDA with that package, and we got very clear feedback from them, so we feel good about where we stand and see a clear path. Okay. We did see a few clinical hold or harsher clinical hold in the past when they went to initial IND filing. Are you totally taking the feedback and then try to be as comprehensive as possible so that we'll not have any delay in terms of a clinical development? Correct. That is certainly the goal. These are all novel medicines, right? I think you have to be humble as a field, and so certainly cannot guarantee in either direction what might happen. I do feel that the guidance in the FDA has gotten very mature. They've seen packages like this before, so we feel good about that. In the case of specific clinical holds in the past that we've seen, we have a pretty good idea of why they happened, and certainly we've taken steps to address those sorts of liabilities in these sorts of packages. You can never say never, but we do feel good about the chance for a clean filing, yes. Okay. Can you share a little bit, your thoughts on the phase I trial design, also very high level, your approach, right? The hemoglobin promoter area versus, I know we've seen quite a few other different approaches, including BCL11A. What is the pros and cons, what is your initial trial design? Yeah. The trial design will be fairly standard in this field. That's part of where the FDA has gotten very comfortable. It will be sentinel dosing, just taking it slow to make sure that everything is on track. You've got to follow the patients, make sure engraftment happens and things like that. Wouldn't expect anything out of the ordinary there. In terms of the strategy we've taken, to your second question, yes, I think there are lots of different ways to potentially think about raising fetal hemoglobin. Of course, the reality is most companies are going after BCL11A because the only thing that they were capable of doing was cutting. If you're cutting or knocking something out, you can't knock out fetal hemoglobin, so you have to go to this indirect approach where you knock out the repressor, which holds down fetal hemoglobin. It clearly does work, which is great. From our perspective, the data that's been shared recently validates this as a clinical strategy and shows that this is potentially safe and effective for patients. We have to show that for ourselves. What we've been able to do is go after that strategy more directly, right? With the base editors that don't cut and can make these very precise changes, where would you like to go? Well, you go to the on/off switch of the fetal hemoglobin gene, which is the regulatory region for those genes. We have literally dialed into the exact base within those regulatory regions that gives us the highest dynamic response for turning on fetal hemoglobin with a very high level of editing. We're taking this sort of clinically validated strategy, and we think we're executing it better, type of thing. We get higher levels of editing. We're in the 90%-95% range within editing, which will leave a very small number of unedited cells left, which we think is attractive in sickle. In those edited cells, because of the consistency and precision of the edit we're making, we're getting this big dynamic response. We get over 60% F. The result of that is when you turn on F that strongly, you're also switching away from the adult globin. We actually see the adult globin falling to less than 40% of the total in the pool. That is lower levels of S protein, the sickle protein, than you see in the clinical data with a bluebird or a CRISPR approach. Ultimately, it is the S protein that's causing the disease. We think that that has a real chance to be potentially superior approach to achieving this upregulation strategy, and that's BEAM-101. Okay. Even given, I think both CRISPR and the bluebird study, relatively high bar, they show. Yes The fetal globin total is about 30%, 40%, actually over 40%. You're thinking you can beat that bar. It'll be next level. We do. Okay, good. When should we start to see the data? I know we are asking two steps down the road. I think it's too soon to say. I think we have to file the IND first. We have to see when that happens. As you know, the setup is both getting the sites open. Also, patients have to really be screened carefully and then consented and then prepared for this. I think once we have a sense of when that first patient dose is, then I think we can project more for seeing the data. I think it'll be some period of time after the IND filing for sure, before we could think we'd have data. Again, we're going to want to follow that data to make sure it's robust. We're not going to want a super early time point. We really need to see engraftment and persistence of the edited cells to know where we stand. Okay. End of 2022, would that be a possibility, maybe starting to show the data? I think it's a possibility, but I think a lot depends on exactly how those intermediate steps come. We'll give pretty clear guidance one way or the other at some point on what's possible as a range. Okay. Good. I wanted to ask your in vivo approach, and I think it's very important and interesting. The lipid nanoparticle, you mentioned that one is the primate data this year. Can you give a little bit more color on that? I certainly wanted to, for the partner, Guide Therapeutics, when should we start to see the data from that collaboration? Yes. Let me take them into reverse order. Guide, really exciting technology. It brings in people, it brings in lipids. We have now wholly own a library of lipid chemistry from them that joins our own. That's exciting. These sort of screening technology and early formulations. They're really sort of lead stage formulations, I would say too early to say when we would see data out of that or when they could affect the portfolio, but we'll be certainly investing aggressively. On the lead liver programs, where we've licensed a lipid from a third party, and we've been doing our own formulation. Those are very much moving forward well. What we would like to show is editing with a Beam formulation, and it's a proprietary formulation, at what will be hopefully on track towards a clinical dose. Something that's ready for the clinic, where we will be editing, initially, a kind of a target, a test site, where we can get a pharmacodynamic readout in the primate model. Ultimately, we would be pairing that vector, once that's sort of been engineered, with our editor payload. The editor payload, of course, will be editing a specific mutation, either in alpha-1 or GSD1a. Ultimately, that becomes the development candidate to move forward. The H1 this year, the lipid nanoparticle primate data, that will not be from either alpha-1 antitrypsin or GSD1. It will be another reporter gene. Yeah. Ultimately, there are no primate models for either of those diseases. We don't expect to create any. I think at the end of the day, you need to show editing in a normal primate, so you need a reporter gene for that. We've used mouse models successfully to show therapeutic effect of editing on a target site that we've engineered into the mouse. Then we think that data package should be sufficient to move forward. Okay. Can you give a color, like what is the half-life of that lipid nanoparticle in monkeys? Yeah. They're pretty brief. These are sort of all next generation biodegradable lipids. We're not talking about 30, 45 days here. I think it's on the order of days. Of course, the payload as well, right? mRNA, you get a sort of few days of expression. The editors are then around for 24 hours or 48 hours after they've been expressed. You get a sort of a nice curve of expression of the editor, and then it'll all wash out. I think that is very much the goal. We think that'll both help with the therapeutic index of LNPs, which is important to keep in mind, and yet give us a real opportunity for efficient and effective editing. Great. Thank you very much, John. That has been a great discussion, and we look forward to a great 2021. Very good. Thank you, Gena. Pleasure to be here. Yes. Bye-bye. Bye-bye.