Solid Biosciences Inc. (SLDB) Earnings Call Transcript & Summary

Good morning. My name is Bert Powell, and I'm the Global Director of Research here at BMO Capital Markets. So it's my pleasure to welcome you to today's Biopharma Spotlight Series on novel technologies for the delivery of genetic medicines. It's an important new class of medicines that are the emerging technology in life sciences today. BMO Capital Markets biotech research analyst Kostas Biliouris will moderate all 4 of today's panel discussions. Each panel will take a deep dive with the companies who are leading the research and the development genetic medicines through adeno-associated viruses, where in a naturally occurring virus is converted into a delivery mechanism for genetic medicines, lipid nanoparticles were nanoparticles comprised of lipids and were used in COVID vaccines and other delivery platforms that can potentially address some of the limitations in adeno-associated viruses and lipid nanoparticles. Our last panel today will focus on the drug delivery in the CNS space, and we look forward to hearing about the latest advancements in this area given the challenges, underlying effective delivery of genetic medicines in CNS. Each of the panels are joined by companies tackling targeted areas with their own unique technologies. We're grateful that you have joined us to learn more about their journey and innovative approaches. If after today's session, you'd like more, please visit our conference [Indiscernible] or reach out directly to cast us with questions. These advancements in health care and human kind are the reasons why we at BMO put such great value and our depth of expertise in the health care sector. We're extremely proud of our extensive investment banking and product knowledge and our incredible research analysts [ Evan Sekaran], [Indiscernible] and, of course, Kostas Biliouris. Before I turn it over to Kostas, I want to remind everybody that in May, we'll have our next Biopharma Spotlight Series on radiopharma that will be hosted by [Indiscernible]. And with that, thank you for joining us today and hope to see you again in May.

Good morning, everyone. My name is Kostas Biliouris. I'm one of the senior biotech analysts here at BMO. Thank you for attending our event today. This is a biopharma series event with a focus on delivery of genetic medicines. I have the pleasure to have with me the panelists of the first panel, which is focused on AAVs and we have here with us Bo from Solid Biosciences, Bo is the President and CEO; Adrian, who is the co-founder of Dyno Therapeutics; David, who is the of 4D Molecular Therapeutics; and Ram, who is the EVP of Commercial Operations and Strategy of REGENXBIO. This panel is very interesting. We have a diverse type of companies here. Some of which develop AAVs towards out-licensing them to other companies. Other companies here in the panel develop AAVs for their own pipeline, whereas other companies develop AAVs, which are used both internally for their pipeline as well as for out-licensing. With that, we can start with the panelists. Thanks, everyone, for being here with us today. It's a pleasure to have you. I'll maybe ask you to give a brief introduction about the company and the founding team and how the technology was discovered in your company, you can keep it high level and then we can go into the details. And I will start with David, given that David will need to leave a little earlier today. So we can start with David and then go to Adrian, Bo and Ram.

Thank you, Kostas. So thanks for having us here today. I'm Dave Kirn, Co-Founder and CEO of 4D Molecular Therapeutics. I'm a physician, scientist and entrepreneur innovator. I've been in the industry for about 30 years. So good to meet you all. 4D Molecular Therapeutics is a platform and product company developing next-generation AAV gene therapeutics and genetic medicines. Our underlying platform technology is directed evolution. This is a Nobel Prize-winning technology. It allows us to create an event customized vectors for any therapeutic area that we want to address. We currently have 5 products in the clinic, and we believe we have clinical validation of 3 different vectors that we've invented at 4D using 3 different modes of administration and ophthalmology, lung and cardiology. That's our background. Thank you.

Thank you, Dave. Adrian?

Thank you. So Dyno start-up. So we've been -- we're right about 5 years old, coming up this year. Our focus has been entirely on AAV engineering. So initially, this was a technology that was developed in the Church lab at [Indiscernible] Medical School. And the premise there for Dyno is focusing on AAV engineering, marrying a [Indiscernible] and technologies. The first one of those is that next-generation sequencing-based readout to read out large pools of nucleotide molecules. Machine learning as a leveraging tool to design AAVs and then generating the data through pool screens and using next-generation DNA synthesis, that enables us to do experiments where we have pools with hundreds of thousands of AAVs that are designed using our own internal data and importantly, designed towards this goal of multi-property optimization. So to us, what we've been able to achieve at Dyno is AAV is targeting a number of disparate issues. A number of different rights of administrations, [Indiscernible] in DI and the brain, where we have more than 100x improved performance and on-target efficiency while keeping at least as good production capacity for that AAVs and then being able to simultaneously de-target key tissues like deliver. The reason we're able to do this is our experimental pipeline builds data that we're then able to explore computationally with this design and then validating our vectors. The last final bid that I want to say is our focus initially has really been on developing these AAVs and getting the success, and now we're shifting into the mode of trying to solve the problem of what -- how do you choose between 10 different AAVs in a particular target tissue. What are the experiments that enable you to do that [Indiscernible] since it's such a foundational decision at the start of a gene therapy product.

And maybe just one comment here. You are using the technology. You are out licensing the technology to partners and not having a pipeline internally right?

Yes. So Dyno has essentially a unique business model that we're the only -- or one of the very rare companies doing this. Our focus is entirely on developing these vectors and sharing them with our partners. We're able to license broadly across indications and therapeutic areas. This also means we're partner centric. So we're fully aligned with the success of our partners. We only succeed if the developers of the therapeutic products succeed. This also means we're not in a situation where, for instance, we might be competing in a therapeutic area or even competing for a limited patient pool, and we're kind of eager to earn our spot as this taxed partner of choice. And we developed this new business model in the field, which is essentially unique to gene therapy because of the separation between the delivery properties of the AAV and the therapeutic properties of the payload itself.

Thank you, Adrian. Bo?

Yes. Thank you, Kostas, and thank you for BMO Capital Markets for the opportunity to speak today. Bo Cumbo, I'm the President and CEO of Solid Biosciences. Solid is really on a transformation in 2023. For many of you who know Solid in the past. They were solely focused on Duchenne muscular dystrophy. In March -- I mean, December of 2022, they bought a company called AavantiBio. I was the President and CEO of AavantiBio, where we were focused on [Indiscernible] evolution as well for delivery for our pipeline programs as well as some nondilutive financing. And we were focused mainly on cardiomyopathies. So the combined company of Solid Biosciences with [Indiscernible] Aavanti this year. We're focused on next-generation Duchenne muscular dystrophy disease state as well as cardiomyopathies. And we have 2 different capsid platform we've been building for mainly our own internal pipeline as well as some nondilutive financing down the road. One focused on directed evolution. Another is a very intentional rational design approach from adding peptides and point mutations. And with that, I'll turn it back over to you, Kostas.

Thank you, Bo. And Ram?

Thanks, Kostas. This is Ram Palanki. I'm Senior Executive Vice President for Commercial Strategy and Operations at REGENXBIO. I think this is a great panel here and to be participating in along with other esteemed colleagues. With REGENXBIO, I think it's really important to remember that we were at the core and the foundations of the discovery of gene therapy itself. We go back to founding the company in 2009. And Ken Mills, who's our President, CEO and Founder of the company, really went on a quest to find AAVs that were effective because back then, there were a lot of safe AAVs, there weren't any effective AAVs. And that quest really led to aggregating and licensing the technology out of University of Pennsylvania of 100 different AAV serotypes that had different levels of tropism and propensity to effectively transduce different tissue types. And that became really the beginnings of REGENXBIO, where the company started as enabling gene therapy in the beginnings of the foundation of the company where that led to a very broad footprint for the NAV technology itself that's proprietary to us across large caps, mid caps and new companies being formed. And as we look back from 2009 to now where we are today, our technology is being used in multiple clinical trials and partner programs through -- in many ways, approved marketed product from Novartis for Zolgensma for spinal muscular atrophy. And it's been used in thousands of patients today. And I think it's a -- it's a technology that has gone through a process of validation, both on efficacy, durability and safety given the magnitude and the footprint and the diversity of the programs and the extent to which the technology has gone through in the drug development process. Today, coming into last year, we have announced our 5x25 strategy. And the idea there is to, by 2025, that we have at least 5 products from our own internal pipeline as well as through our partner programs, of programs being in late-stage development and being commercialized. So that's really the next 3 years for us going into 2025. And we're very excited about our internal pipeline spanning between common diseases and rare diseases, and we are probably the only company in the gene therapy space, targeting public health priorities like wet macular degeneration and diabetic renopathy. Together with pivotal programs in the subretinal space today.

Thank you, Ram. Very interesting. I think next, we can discuss the technologies that each one of your company is using towards AAV improvement, I would say. Maybe you can talk a little bit about the technology and some of the key characteristics that the AAV that you are developing have, and you can patch on tropes, immunogenicity, packaging size, transaction levels and anything else that you think is helpful for people to understand how your technology is potentially differentiated from other technologies. And we can start with David and go to Bo, Adrian and Ram again.

Thanks, Kostas. So when we started or the approximately 10 years ago, we started with the premise that while AAV has shown great potential already at that point, there was still a huge unmet need in the space for better vectors and that to move beyond the low-hanging fruits such as hemophilia, we really needed better vectors. And we thought that the key hurdles were certainly delivery transduction efficiency for specific tissues, evasion of pre-existing antibodies in the populations in the case of IV delivery. And then better safety and less immunogenicity, which again comes along with reducing the dose and having a more efficient vector. So that's what we're looking to solve. We're using directed evolution. We start with approximately 1 billion synthetic AAV capsids that are not present in nature or they're derived from the capsids in nature. And we're continually improving our libraries and diversifying them further. So that's step 1. Step 2 is for any vector that we want to develop for a novel therapeutic area. We start with what we call a target vector profile. And this is basically what cells do we want to target? What distribution in the target organ do we want to target? Do we want to target multiple organs? What route of administration do we want to use? What dose range do we want to be in? So we have a reasonable cost of goods and likely excellent safety profile and then do we want to build in resistance for existing antibodies. So we call that the target vector profile. That's literally at the whiteboard for any disease or set of diseases in a therapeutic area. And then the final step, which is obviously critical, is to do competitive selections in an iterative fashion in nonhuman primates. So this is evolution. We need to do it in the species that is close to the humans as possible. So all of our selections are done in nonhuman primates. And what we do is we administer the entire library, which is a physical library of protein capsids, each bar coded with its own DNA, so we can track it in the body. And then we infuse by the relevant route of administration, the relevant dose range and then we harvest the cells that we want to specifically target and we bring that back to lab, break open the cells, isolate those genomes that made it to the target tissue. We then repeat that this time at more stringent conditions, so lower concentrations of the virus or higher antibody concentrations. And we do that iterative loop anywhere from 2 to 4x over the course of several months, and we can identify in that pool of 1 billion of vectors the optimal vector that most closely fits that target vector profile that we designed. So that's what we've been doing since our inception. Again, we have 5 products using 3 different vectors we invented by that approach. One for intravitreal injection for retina targeting, a second aerosol delivery to lung and the third for IV delivery to heart. We continue to improve the platform, so now we're working on multi-tissue targeting and other features of the capsid.

And maybe one follow-up question here since you have already advanced your programs to the clinical states. Can you talk a little bit about the translation from nonhuman primates to humans since you have data from both. How well are the data from nonhuman primates translated to humans in terms of tropes, more dose selection or anything else that can be helpful here?

Yes, it's a great question. So once we discover vector, we characterized it in dose-ranging studies in primates and then we also tested on human tissue to make sure that vector also translates into the best available human organic tissue and is still superior to the conventional vectors. So far, everything we discover in primates has translated to that human tissue. And then now as you say, we have human clinical data, intravitreal, aerosol, IV. And in each case, we're thrilled with the degree to which performance in primates and human cell and disease models has translated into clinical results. So far, we've seen a great correlation that these vectors are doing exactly what they were designed to do in the clinic, which, of course, is the ultimate test. So far, we've seen great tracking from primate discovery, primary characterization, human cell disease model characterization and the clinical trial results.

Perfect. Thank you so much. Adrian, maybe you can talk a little bit about the technology. I guess you already provided some color, but maybe you can go into details and how can this 3-step process that you mentioned can lead to differentiated products.

Absolutely. So I want to comment on 2 aspects of the Dyno technology pipeline. One is this approach of how we design vectors using machine guided design. And then separately, is this approach of the technologies that we're deploying to characterize the vectors that we're creating. So first of all, about vector design, I think it's important to help frame how we think about vector design. So an AAV is really 1 set of 700 letters in a row from an alphabet of the amino acids. And we know that there are some -- several solutions from nature that exist that can differ in as many of 300 of those 700 letters. The goal is how do we explore this. And this really becomes an amazing machine learning problem as everyone I'm sure is well familiar with the sort of progress in our ability to engineer more and more sophisticated machine learning problem and machine learning algorithms and deploy them to more interesting tasks. In many key -- essentially all cases, the gating success is not the quality of your machine learning algorithm, that matters. But it's actually the training data that you have to deploy the machine learning model again. So at Dyno, we're solving both of those things. So one differentiating aspect is the quality and talent of our machine learning team and their sort of demonstrated ability in engineering these vectors that are highly divergent from anything seen either in nature or in other engineering efforts. So one aspect of this is if you think about the [Indiscernible] structure of AAV, most variants that are designed typically target loops on the outer pace of the caps than better relatively straightforward to engineer and exploit. For us, we'll target those loops, where we can couple those with mutations across the rest of the capsid, which are much harder to do, but enable us to explore the property space much more efficiently. On an experimental level, this comes down to these pool experiments where we synthesize a library of 100,000 variant. That are all designed with machine learning. And then it's interesting to think about the sequence of events that happens to that library. Initially, this is a set of plasmids, they go into vector production. We then take a small fraction of that library and measure the efficiency of all of those factors in production. Then we take that library and inject it either, for example, in an intravitreal injection when we're developing an eye product capsid or systemic injection if we're developing brain or muscle trophic vectors and then inject duties injections all in NHPs, of course, to maximize for the translatability into humans and then take this animal are able to isolate all the relevant tissues and then measure both how many vector genomes, vector copies have arrived in a specific tissue and also how well they're expressing. So getting both biodistribution, which is central for questions of toxicity and then on top -- on target transduction efficiency. All of these properties that I just mentioned, production, biodistribution, transduction matter, and we also think about this idea of a capsid profile. That some balance of these different properties that we ask our machine learning team to optimize drive transduction but never sacrifice production. If you're able to identify opportunities to lower transduction or biodistribution to relevant off-target issues, for example, deliver please [Indiscernible]. And this is exactly the type of vectors that we're generating. So for example, to brain delivery, we have things that outperform conventional vectors by more than 100-fold on brain, blood-brain [ barrier ] crossing transduction, while, at the same time, detargeting deliver and producing better than [indiscernible] The other big question for us is how do you actually compare vectors? I think that era of having an old vector, like a legacy vector and a new vector and you're just trying to compare is this new one better than the old one is changing. If you think about the landscape that -- the question that a gene therapy developer is facing next year is how do you choose between 10 different vectors that target -- that are all much improved relative to baseline. And you need to choose the best one because that decision is central to the gene therapy product. For us, these are experiments like single cell sequencing, where we can take a set of a large group of vectors and measures are on-target transduction across all the cell types of the retina, understanding precisely where our entire family of eye-targeted capsids are able to cross and are they specific group [indiscernible] receptors? Are they specific for our B cells or retinal ganglion cells, for instance. And our hope is this family of vectors will enable us to drive a whole class of different therapeutic applications that are targeting these different [indiscernible]

Thank Adrian, very helpful. And maybe a couple of follow-ups here. Given that the focus is on AAV and you are not developing a pipeline of products internally. I guess your goal is to optimize as much as possible, right? So where do you stop with this optimization? Where do you say, okay, we reach the maximum optimization or a global maximum, let's say, in terms of optimization. And if a company waits a little longer, can they get a more optimal vector or not necessarily? So I'm just trying to understand how the optimization process works here.

That's a -- those are 2 great questions. So let me address the first one. First off, what's the goal? I think there's 2 relevant scales to think about. Again, until now, the focus in our pipelines has been comparing -- developing improvement over existing wild-type vectors, for instance. I think that's actually the wrong benchmark. If we think about the brain, the goal isn't blank ex better over some other vector, it's what percent of total neurons are being transduced by your vector and how you measure that. So that takes, for instance, an approach to actually doing this measurement at a scale that's better than typically, for example, the types of measurements that are single -- a couple of pathologists tempting sections and coming up with an estimate comes up. That too is a place where machine learning that able to process tens of thousands of neurons from many different images across the brain is central, and this is the type of technology that we have. But the other thing I want to highlight is the focus is on the percent of neuronal transduction driving that as high as possible, and we've seen tremendous progress there. That doesn't end though, right? Like once you're able to transduce a therapeutically viable number of neurons. The question becomes at what dose? So now the goal is -- and that's why the sort of process of vector optimization is a long-term quest for us because we think that the likelihood that we're able to reliably lower the dose over time is going to be foundational. That's going to be really important for 2 reasons: first of all, toxicity that's going to scale with dose and kind of widening that therapeutic window. But second of all, is also the ability to use the less vector, make it more cheaply. Both in sort of derisking the actual therapeutic development pipeline but also ultimately reaching more patients and kind of maximizing the impact of gene therapy as a whole. In terms of your second question, I think you're onto something. Of course, we're in a period where -- this is a time when if you wait, vectors next year will be better than vectors today in a way that's never been true before. I think to us, it's an important question in terms of this is in part why we've developed strategic partnerships that are guiding us in thinking about what vector properties are more important. It's also the reason why us at Dyno, we want to work with therapy developers early and because we can understand best how to tailor to specific needs and also develop this relationship that enables the product developer to think about Dyno capsids, understand what we have today, but also understand what's coming down our pipeline and be able to make decisions in that context. So I think this issue is one that's central to how we think about positioning ourselves in the field.

Great. And maybe just out of curiosity, one more question. Do the companies that in-license your capsid report the results back to you from their either clinical studies or preclinical studies or they don't have to reach up to them to share the data with you when you out-license your technology to them?

I say this is an area where it depends on the partner. I think it's a place where our goal is to be the most effective partner for someone who's licensing Dyno capsid. That means we look for alignment. If we're able to share the data that makes obvious sense and we're obviously curious if there's -- if it leads to a better partnership to know that you can control all that data and keep it, have control over how it's shared and all that information, that's -- we understand that. And our goal is to drive that partnership to success. And we have the flexibility to make those decisions. So for partners who are interested in that direction, that's something we can definitely explore. And also the thing I want to highlight in terms of partnerships is it's a place where we can work across the key areas. So in [indiscernible] and in eye we have vectors that are very attractive that we are excited to share and we're excited to develop additional partnerships around.

Perfect. Bo, maybe you can talk a little bit about your technology and how you developed a new AAV for your clinical trial?

Yes. So similar to the others, I mean, we're looking for very much the same thing, whether it's increased clearance, speed transfection, immunization, et cetera. We're hyper focused on cardiomyopathies as well as, obviously, with DMD next-generation Duchenne and we do not do any work similar to Adrian and [indiscernible], CNS or brain region, we are hyper focused on cardiac and skeletal muscle. And we have 2 different approaches to try to tackle the issues that we're all based with here. We have, as I mentioned before, for our cardiac side of the business, we're really focused on direct evolution. And similar to what David mentioned, we have libraries -- millions of flagged assets that go through 3 rounds of animal species, 3 rounds of 3 different types of animal species. We're focused on [Indiscernible] nonhuman primates and pigs, so we can look at pig heart for cardiomyocytes. And we already through our first round. We have more work to continue to do. But in this area, we're focused specifically on increased clearance as well as tropism to the heart and obviously, liver detargeting. And so we're continuing to work on that. We look at NGS analysis after multiple rounds of animals work. And then hopefully, the readout will be at late this year to early next year. On the skeletal muscle side, we take a very different approach. We're actually manipulating immunoacid, bioamunoacid looking at and adding in peptides as well as point mutations. And this is hyper-focused on increasing tropism to skeletal muscle and as well as cardiac liberty targeting, but speed of transduction as well. We're thinking about how we can get to next-generation technologies where -- and use next-generation technologies for repeat dosing or antibody-positive patients and how we can knock down the antibodies or evade the immune system and also transduce in a very, very quick window of time. And so we have 2 different paths for 2 different purposes and different challenges. We're excited about the work we're doing. But I think similar to what David and Adrian was saying, we're all looking for the same thing. How do we increase transduction, how do we -- in distribution? How do we decrease the dose for safety? And then we also look for other things as well, similar to what the other panelists said about -- we have to make sure we can manufacture it. So it's important to -- that you might have the best caps in the world, but a very, very low yield. So it's important to take a look at that. And then some of the therapeutics that we are in similar to like FA, it's one of our programs. How can you transduce in a very linear fashion, transduce dose and transduce them in a linear fashion because you do not want some toxicities. And some of these capsid have a large S curve that we've noticed from transduction to dose. And so we want to make sure that as we increase the dose that we can get into narrow therapeutic windows. So these are all the challenges we're faced with. I think all of us have to take a look at the disease states we're in because they all do matter and then pick the best capsid that we have. I think our first capsid that came out of our libraries called SLB101 and we're using it for our next generation Duchenne program. We see basically 3 to 4x capsid -- I mean muscle tropism. We also see about 2x liberty targeting and we're very excited to see what it does in the clinic, we'll be in the clinic second half of this year. We've already through nonhuman primates. [Indiscernible] will be dosing patients at the end of this year and early next year, and hopefully, we'll see the results at that time.

Thank you, Bo, very useful. And I think it's very interesting that you also look at the speed of transduction, and you have -- with the new vector, much faster transduction than the previous one. One follow-up question. Would you consider also in-licensing vectors from other companies or you would be developing any vector you need internally?

Yes. I mean, ultimately, my goal is to get the best therapeutic to the people that need it. And if I don't have a big enough ego to say I find a capsid that Adrian or David are making and is going to help patients, then absolutely we'll bring it in and try to apply it to the drugs, the therapeutics they want. We want to control our own destiny, of course. But I'm here to help serve patients. So if we find something that works, it works better and safer and can solve the issues that we're talking about today. And absolutely, we'll bring it in. And we do look at other capsids, we're getting multiple capsids right now, we have partnerships with a couple of different collaborators on different ideas. And hopefully, that floats all boats, I'm here to help patients and get a drug to the market.

Perfect. Makes sense. Thank you so much. Ram?

Yes, Kostas, I think what you're hearing here from the entire panel is people are trying to solve for the general principles of gene therapy, right? We're trying to find vectors that could have broad and novel tissue selectivity, higher gene expression, longer-term gene expression and lower immune response and vectors that lend themselves to improve manufacturability. I think that was the genesis of REGENXBIO, when Ken went out there and tried to find vectors that could do that. And the discovery there was really -- he ended up finding the research that was being done at the University of Pennsylvania, which where they had discovered about 100 different naturally occurring vectors that had the capacity to do the things that we're all talking about on this panel today. And that really became the beginnings of the company. And I think as you look at our platform, the most important thing is the validation that has happened over the years, both in terms of our ability to license it to many of the large caps and the number of clinical programs that are ongoing on a partner basis in the clinic to a commercially approved product like Zolgensma, I think you probably have all seen the latest update from Novartis. They're now seeing kids hitting normal milestones up to 7 years with the data that they recently brought forward in. It's been administered in over 3,000 patients, right, between a commercially approved product that's been administered in a very large proportion of patients and our own programs that are running in the clinic today between wet AMD, diabetic retinopathy, MPS I, BS II and the programs that we have announced in DMD, we're actively including into the program as we speak. But there have been thousands of patients that have been treated and it continues to show that the principles and the foundations of the company that it was formed on the technology seems to perform, and we are very excited about coming into this year that we are getting closer to our 5x25 strategy, where again, the idea there is to bring forward about 5 products into late-stage development and commercial products coming out of our own internal pipeline and partnerships. So that's really the basics of the company. I think everybody that's on this call is trying to solve for the same issues that we really form the company as a basis for back in the day.

Very interesting. And one question I have is about manufacturing. You are having a large pipeline internally and you have out-licensed your technology actually to many partners, including commercial state companies. How do you manage to manufacture all these amount of AAVs? And are you continuously expanding your manufacturing capabilities? How do you handle all these demand on the manufacturing side?

Yes, Kostas. We have spoken about this publicly. We have installed our own capacity on a commercial manufacturing basis here in Rockville, and today, we're even proud to say that the commercial manufacturer products are being incorporated into our Phase III programs in wet AMD, and we'll be installing the commercially manufactured products here into the rest of the pipeline that we are exploring in late-stage development today and early stage development. The idea there is we started as an enabler of gene therapy. Now we have built end-to-end capabilities over the last decade or so with R&D capabilities through manufacturing, through clinical development across -- they are the key areas we operate in, right, eye, the brain as well as the muscle, and those are the 3 areas of our core late-stage programs today. And with DMD coming into play, muscle has become a very important component of our capability. So -- the idea here is we've built capabilities on a manufacturing basis where we can support all of these programs coming into the commercial stage on a global basis, where we control our own destiny and we have the ability and also the process of the product that we call NAV express, where we can manufacture a lot of these products on the basis of high purities, high yields, which gives us a lot of advantages when it comes to commercializing the products on the other side of clinical development.

Great. The next question, I would say -- I would like to touch on the next topic. Maybe it's twofold, can you talk a little bit about partnerships that you have, especially for the companies that are partner or out-license their technology to others? And the second is maybe you can help investors understand what is the next big milestone for your company, either a data readout or some new version of the technology coming up? Or what is, in general, the catalyst that investors should be watching for this year or next year whenever it is. We can start with David again.

Thank you, Kostas. So in terms of business development, we have a diversified business model where we look to raise equity financing and invest in our own programs with the goal to get to the market eventually and retain U.S. rights and build a commercial sales force in the U.S. So we want to be a fully integrated biopharmaceutical company. We believe that drives the most value for investors. At the same time, this platform is so broad. We can't do everything, so it's critical that we form value-generating partnerships in areas where we can't go as deep ourselves. Certainly, our lead program, 4D-150 for wet AMD and DME is one where we want to retain those U.S. rights, but we certainly will look at ex U.S. partnerships to help to co-fund and run the large Phase IIIs are required to get that to the market. So we believe in that diversified business model. In terms of upcoming catalysts this year, we have a number of them, so for 4D-150 our wet AMD and DME product. We have data readouts coming out at ARVO, the retina meeting, April 27 in the morning. That's a big readout for us, where we'll share data on all 3 dose cohorts in the Phase I portion of that trial, 15 total patients, 6 months to 16 months follow-up on safety, [Indiscernible] central subfield thickness and rescue injections. That's a big readout for us. We've also announced that we're currently enrolling a randomized Phase II, looking at 2 dose levels of 4D-150 versus aflibercept that 50-patient study we've given guidance that we should complete enrollment there by Q4. So enrollment is brisk. We're also starting a diabetic macular edema or DME study that IND is open, and we're looking to treat the first patient on that study in Q3. So that program is moving along nicely. And then our 4D-710 aerosol delivered product for cystic fibrosis lung disease. There, we expect to release our second data set from the Phase I portion of that Phase I/II trial. We expect to release that at a medical meeting in late Q2 of this year, and that will be additional follow-up, including FEV1 and quality of life from the first patient cohort at the low dose and then we'll also give additional data on biomarkers at the second dose level, second and highest dose level from that study. And again, the biomarker data from the first cohort that we reported late last year showed on the order of 40% of cells in the lung were transduced and expressed in the CFTR transgene after a single aerosol administration. So a really remarkable level of transduction, also with excellent safety, no adverse events following treatment. So we'll follow up that data as well. So I think most people are focused on those as our 2 lead programs, and we're driving those programs as quickly and as efficiently as we can.

Okay. Thank you so much, David. And I know you need to leave soon. So feel free any time. Thank you so much for participating in the panel, and it was a pleasure having you.

Thank you, Kostas, thanks for having me.

Thank you, Adrian. Maybe you can go next talk about the different partnerships you have and potential key milestones for the company.

Absolutely. I think it's helpful to flag kind of where Dyno is in our trajectory. So we're a Series A company in our last, which we raised in 2021, we've been based in Boston, Massachusetts, so we're probably -- approximately a scale of 100 people all focused on capsid engineering. Early into the company's history, we've always sought to develop key partnerships and we've been very blessed in having quite a bit of traction in this regard. We've established key strategic partnerships with Novartis, Roche and Spark, Sarepta and Astellas, and these are across a range of indications in the ocular levers ENF and muscle space. These partnerships have brought a significant amount of noninvestor revenue for our company at our stage, which has been very helpful for us as we look to develop this new model for a company that exists in the field of gene therapy that is focused on solving this delivery problem and then sharing these solutions with the field rather than taking on the risk of specific product development. The other thing that these partnerships have given us is establish a relationship, establish a stage where we can iteratively look for product market fit. I think this is more of an issue in the tech space than necessarily in the bio space, but at Dyno as a company positioned really at the intersection of those 2 states this is key. What is product market fit? This is essentially understanding partner needs, understanding the structure of the market and understanding how we position our capsids within the context of this market in a way that enables us to grow towards a sustainable and exciting business for ourselves and our investors. These -- our partnerships have been going quite well, have been a source of a lot of learning and a lot of very active development in our capsid engineering. Our milestones are simpler, we don't -- because we don't run clinical trials, to us, the questions aren't the ones associated with the risks of -- in the challenges of a typical clinical trial but rather our -- the progress of our engineering efforts. Because of the way that our platform is structured and also the scale of Dyno, we run programs in parallel across these key areas. And really, the key milestones for us are data outputs that we share -- typically at conferences, we're also sharing in active discussions as we -- in active discussions focused on licensing. And really there, the focus is on sharing the development of our vectors. I think our milestone is how are we improving on top of the typical vectors used for specific indications. I've [Indiscernible] about numbers like 100x improvement over the existing serotypes also looking at iterative improvements in the percent of cells transduced. These are the metrics that we're sharing. We also share key platform developments. When we develop new ways of measuring capsid properties that we think are central to guiding the choice of which vector is going to lead to our most effective therapeutic product. Typically, I would say those milestones come down to conference. It's ASGCT is a big one where we'll be sharing some exciting new results across our portfolio of capsid products.

Great. And maybe a follow-up. I'm sorry if I missed that. If any of your partners advances your capsid, your technology to the clinic and start a clinical trial I'm not sure if they have done it already or not, but would you announce this from your side or not necessarily this may be confidential?

These depend on the partnerships. For the most part, the way these partnerships are structured as specific preclinical milestones. I should mention all of these are in preclinical stages where we're actively developing these capsids for our partners. We're hoping to be able to share progress along these milestones. More importantly, it's also these milestones are associated as kind of a traditional strategic partnerships with significant financial revenue coming back for Dyno that's going to enable and essentially entirely be invested in our AAV engineering platform.

Bo, maybe you can talk about partnerships and the next key catalysts to watch.

Yes. I'll quickly go so [indiscernible] speak and then we're running out of time. I think.

We have a little more time. This was maybe a little.

Okay. All right. This year, as I mentioned before, is really a transformation [Indiscernible] Solid into the combination of the 2. We have multiple programs that are moving forward. We have about 4 different cardiomyopathy programs that are moving in different stages of preclinical studies. Our first lead program for [ VAG 3 ] will be moving into nonhuman primate studies later this year. Hopefully, the readout will be early next year depending on when we can actually get to nonhuman primates and dose them. Our cardiac -- other cardiac programs will work with different universities. By the way, all -- we do not have any corporate partnerships. We partner mainly with universities that are focused on the different cardiomyopathies that we're working with as we can continue to move through different preclinical studies as we go forward. So we have our other cardiomyopathies that are moving forward in preclinical studies. And as I mentioned, our capsid libraries are going through multiple rounds of nonhuman primate pig and mouse studies with 2 different types of capsid evolution going on, both directed evolution as well as rational design, as I mentioned earlier. And then our lead programs with Duchenne and we have a Duchenne program similar to Ram. That's [indiscernible] next-generation capsid, as I mentioned before, for delivery and speed of transduction so we can think about how we can get to the kids already have antibodies, that are antibody positive or the older children that have decreased heart and lung capabilities. So that program will be IND opened in the second half of the year, dosing patients, hopefully, second half of the year or early next year and then continue to have a readout sometime in 2024.

Perfect. Thank you so much, Bo. And Ram -- and don't worry about the watch there, take your time, please share all the information you want. I know you have a long list of partners, but maybe you can share the ones that are the at most advanced stage. And the key catalyst from your pipeline this year, what investors should be watched for?

Thanks, Kostas. I won't focus on the partnerships too much. I think that was the basis of the company back in the day when it was formed in 2009. I think most of you know, we probably have the largest footprint in terms of the BD world and with AAVs and multiple clinical trials right now in partnerships. And obviously, we talked about Zolgensma a bit. Outside of that, in our focus over the past few years has been really to build our own product candidates and bring them to patients across common diseases and rare diseases. I'll probably start with our common diseases, both wet AMD and diabetic retinopathy, both are public health priorities. And we have 2 different set of programs with our lead product candidate 314, which encodes for a transgene that expresses [Indiscernible] in the eye based on all of the early data from Phase I/II now coming into last year. Late last year, we even showed data up to 4 years that patients that had a response, continue to have the same response on a consistent and durable basis up to 4 years. And where we installed that same dose range into our Phase III program, which is atmosphere and [ ascended ] 2 large clinical trials exploring the efficacy and safety of the subretinal approach in wet AMD. We also have started suprachoroidal programs, AAVIATE and ALTITUDE, which explore in-office approach to the suprachoroidal route both in wet AMD and diabetic retinopathy. Both of those programs coming into last year, we shared the data continue to show encouraging data, and we're dose escalating. And based on the data we spoke about last year, we have expanded into a dose level 3 with prophylactic steroids to mitigate some of the inflammation that we observed in a nonprophylatic setting, which was all, again, managed very effectively with steroids in the earlier cohorts. So the idea here is to mitigate any risk of inflammation and hopefully avoid most of it or ultimately all of it. And we continue to recruit into both of those trials for wet AMD and MDR in 2023, and we plan to finish recruitment into the expanded dose cohorts by the first half of 2023. And coming into second half of 2023, we plan to provide data updates on both of those studies. We continue to be on track for our recruitment in the Phase III program between ATMOSPHERE and ASCENT and plan to file a BLA in 2024. And coming to our rare disease programs, with DMD, we've announced AFFINITY DUCHENNE program being actively initiated and now recruiting. And we plan to provide an update on data from patients recruited in the first half -- in the second half of 2023 on the basis of the preliminary data that we hope to observe based on the novel construct we have that's been optimized for better muscle function, better immunogenicity and optimized manufacturing. We also recently provided an update on the RGX-121 program that is now in Phase III, and it's actively recruiting towards a potential BLA submission in 2024. So we stay on track for the BLA submission in 2024, and it's one of the contributors to the 5x25 strategy. We also announced our updates in the recent earnings around the Batten disease program in Brazil, where we have injected a patient on an investigator-sponsored trial basis as well as initiating the ocular complications of Batten disease in the U.K. post activation of the IND in United Kingdom. So it's -- these are all the different set of things that are coming through right now in terms of execution. I think in terms of data updates, the main ones to look forward in the second half of this year are the suprachoroidal data updates between wet AMD and MDR as well as AFFINITY DUCHENNE program that's actively recruiting as we speak.

Perfect. Thank you so much. This was the end of the panel. Thank you so much, everyone, for attending the panel. Thanks to all the panelists who participated. Great discussion, very helpful insight, and I look forward to the next panel, which is focusing on [ LNPs ]. Thanks, everyone.

Thanks, Kostas.

Thanks, Kostas.