Good morning, good afternoon and good evening, everyone. My name is Jessica Hogan and I will serve as your moderator for today's event. Before we kick off today's agenda, I do have a few housekeeping items to review with you. At the bottom of your screen are application widgets. They are resizable and movable, so feel free to manipulate them to get the most out of your desktop space. For the best audio quality, please make sure your computer, speakers or headset are adjusting adjusted accordingly so you can hear the presenters clearly. If you have questions during the presentations, you can submit them using the Q&A widget on your screen. Please know that we do capture all questions. So that's all I must share with you on the technical side. And to that aim, we have a very exciting panel discussion in store for you today. At this time, I would please for a better experience enlarge in the media player for this panel discussion. And unfortunately, we did have one panelist who was not able to make it today, but we do have Natalie here from Siren who will be able to step in on behalf of Nicole. So to that aim, it is my pleasure to hand things over to Ratish, who will be our moderator for the panel discussion today. Thank you so much Jess for the warm introduction. Excited for day two of the symposium. My name is Ratish Krishnan, I'll be a moderator for today. I'm currently the Director and Head of Focus Modalities for Millipore Sigma. And you know, I listened in to day one, a lot of incredible insights and engaging discussions on the future of biotech innovation and then I was really energized. As you know, I'm ready to dive into today's program. As Jessica mentioned, we have a fantastic lineup in store. And also as a quick note, we'll be taking questions from the audience even, you know, in this panel discussion session. So feel free to type in your questions and we'll try to address them as we go based on, you know, the flow of the the event. And I do, you know, wanna reiterate that, you know, Nicole couldn't join us, but you know, we still have two outstanding leaders from the biotech industry, specifically in the AAV space, representing companies who are making significant strides in the world of gene therapy and and AAV. So Doctor Natalie Clement is VP of Vector Development at Siren Biotechnology and she has over 25 years of experience in gene therapy manufacturing. I have personally have had the privilege of listening to her in conference talks when I started my career in gene therapy back in 2016. And Michael Vizga is the CFO of Factory Therapeutics and he has a very impressive background in finance, particularly healthcare, investment banking and including a great deal of experience with mergers and acquisitions as well. So let's start by getting to know a bit more about each of them and their journeys that bought them here. So maybe we start with Natalie. Natalie, what sparked your interest in gene therapy and maybe AAB technology? And maybe there was a defining moment that you set you on the spot to start with you. Hi, good morning everyone. Good morning, Ratish. And, and first of all, let me thank you and your company for organizing this event and, and giving Saran Biotechnology the opportunity to talk a little bit about what we are doing. I was thinking about what really, was there a moment in my career or in my early years where I never wanted to, to work on gene therapy? There's none. I'm always wanted to work on gene therapy from really the beginning of my university years. But what I think through through my entire career, what has defined my I made the right choice moment is really of course, each time you meet a patient. But I remember a specific event that may be that was like so special to to dip in into my core was when Doctor Who from Taiwan presented his phase one data on the AADC clinical trial at ASGCT. And he was showing videos of of young kids six months old to 12 months old before and after receiving the AAV AADC drug product of which we had participating producing when I was at University of Florida. And you could see these kids who could stand, who could laugh, who could eat. That moment is the moment I said I made the right choice, I'm on the right track, and I'm going to stick to it for the rest of my life. Very timely information, if I may say, is that that drug product is now marketed. It's Abstasa, which was just approved yesterday in the US. It had been approved in Europe before, but it's now approving the US. So this is a moment that you don't forget. Yeah, a lot of impact, right. I remember the same thing when when we was working in process development for mostly, you know, maps and vaccines and then the the shift to gene therapy came in and everybody was wondering what this is. Is it is it is just like a hype, right. But then as soon with a lot of clinical data, right, you started seeing hope and there's never going back for me. So thank you so much for sharing that. Natalie and Mike, how about you? Your background, right? What have you learned of AAV in your time at Vectory? How has the journey been for you? Yeah, no, it's a, it's a great question. And again, thank you all for, for joining today. You know, from my side, you know, I started in healthcare investment banking. So I was there for about 12 years, you know, working with a broad spectrum of, of biotech and pharma companies ranging from, you know, small molecules to gene therapies. I actually went to a company after I left banking as ACFO. It was also in the CNS space where Vectory is focused on small molecules and that company is called the Mandy Therapeutics. And we were focused on Parkinson's. And you know, again, it was for, you know, disease modifying. And with our small molecule it became clear that there would be, you know, regular, you know, a process and procedures associated with this. And then as I started learning about trajectory and the optionality that provided in terms of a gene therapy, it became clear that, you know, being able to change somebody's life in an area where we're focused in ALS and CNS, where there's so much unmet need, you know, and being now have an impact for essentially a lifetime for this person is incredible. And knowing that a gene therapy approach for where we're trying to go and being able to kind of go through this one time procedure and being able to once again change somebody's life. And again, these people with AOS, they typically have a three or four year life once they're diagnosed. So it's incredibly short. So being able to essentially expand that in disease modified with an AV as our platform in terms of our delivery, it is really what excites me about where the gene therapy space can go over time. I think, you know, I think we can all look around and say that it's not perfect as of today, but I think we continue to refine it and I think over time it will become more of a standard of care as we focus on the potential growth opportunities for what gene therapy can provide. Absolutely right. Like I think even I think there was a talk yesterday from the Alliance of Regenerative Medicine, right. Like, I mean, it started as hype, then there was hope, now it's reality, right? Slowly but surely. So thanks to, you know, companies like you making great strides in that. So this is great. Thanks for both for sharing that bit of personal experience, right? And I'm sure the audience is excited to hear more insights from you. Just wanted to, you know, I was thinking, right, Halloween was just a couple of weeks ago. I have a four year old daughter. She's already taken her a Halloween costume for next year. She wants to be Elsa from Frozen. I just thought I'd throw in a slight question to maybe get audience to get to know you a little bit better, right? So what was your Halloween costume this year? Or if you didn't dress up, what would your go to costume have been? Maybe Natalie? So I do dress up for Halloween and and and I have I have had many Elsas costume for my daughter all over this one. So happy to hear it is still fashion because I haven't seen many. So I was originally going to be a very simple skeleton. I had bought myself this one one piece suit skeleton, but at the time of leaving the house, I was like, this is kind of simple and a little bit revealing. And I was like, Oh no, I'm not going to do that. So I, I went into I have a huge chest of like full of costumes that I have collected over the years and I dig into it and I found this really long under skirt Tutu kind of things and I became a ballerina skeleton, which is, you know, ballerina would have been my other career if I had not been a scientist. So that's what I was this year. Hey, how would you? And then I unfortunately did not dress up. We have two kids. I was in charge of handing out the candy this year. So my son is five, He was Rocky from Paw Patrol. My daughter was is 3 and similar to yours, dressed up as Elsa. My wife was Anna. If I was to dress up, My kids are also into Spidey or Spider Man, so they're kind of into that, that world of Marvel characters. So my son likes to think that because I'm so strong in his eyes that I could be the Hulk. So I would probably dress up as the Hulk. Unfortunately, as you probably look at me, I don't quite match the Hulk in terms of physique. But you know, that's the great thing about little kids. They can live in that world where you can be anything and it's great to be idolized in that regard. Yeah, infinite imagination, right? Yeah, exactly. And I was Pennywise the clown from IT. So I just like, slap in my mask and just wear whatever I'm wearing, something comfortable. It does get cold here in Saint Louis where I'm based out. So always go for like costumes with a lot of padding and cushioning. So thank you, very interesting answer. So thank you so much, you know, for sharing that. And let's zoom out a bit from your personal journeys, right? And maybe dive into a bigger picture that both of your companies are trying to solve, right? Like your vision, both Siren and Vector V, right, have unique approaches to gene therapy. Both have bold ambitions, right? As understandably. And Mike, I understand that like you know, your company's developing a distinctive or rather a unique platform, right, that combines monoclonal antibodies with AAV, I believe it's called the vectorized maps. And then actually on the other hand, Siren is focusing on combining AAV with the cytokine immunotherapy mechanism, right? And then I'm assuming you're like no novel approach to tackling cancer and so on. So, so maybe, Natalie, let's start with you, right? Could you share like a specific unmet need in the AAB space that Siren Biotechnologies is addressing and maybe also elaborate a little bit on why that is critical? Sure. So I think it's important that I, I give you a little bit, explain you what what Siren Biotechnology is all about. I wish Nicole was with us. She is an amazing storyteller and she would be the best to tell you how Siren came all about. But I'm going to try. In a nutshell, Sirens Biotechnology's mission is rather bold. We are trying to find a universal cure to cancer. So Nicole founded Siren upon realizing that the therapy that she had pioneered when she was at UCSF could achieve amazing success in her in the proof of concept studies that she had run. And I'm bringing that therapy available to the patient community was a no brainer. She, she just had to do it. And the success and innovation of our therapeutic paradigm at Siren really relies on leveraging 2 modalities and putting them together. On one side, you have immunotherapy, which has been, as you know, a trademark to cure cancer over the past many, many decade, decades. And they are combining that with gene therapy that is still to some extent an emerging biomodality that has rather been used for a systemic or genetic diseases, but very rarely, if ever for cancer. And so this is how Sarin creates an immunogene therapy approach to treat cancer and the board aspect of it and one that is really dear to Sarin and dear to me. It's the universality, hopefully the university that we can leverage from 1 drug. We are gonna be delivering a cytokine expressing AAV drug product that is not cancer specific. And so the hope and goal is that our first drug product could be reused and used into multiple type of cancer and an indication which is along the way gonna save time and resources at not having to redevelop a new drug product each time. So this is really the unique and an innovative approach of Sarin to to fight cancer and using AE vectors. Yeah. And then maybe to follow up, very interesting and like you said very bold, right. It's is this, I know gene therapies are historically marketed as one and done type therapies. Is that the angle you're looking at as well for cancer one shot treatment? Or maybe it's not quite defined yet or? I would say it's probably not defined yet. Of course we are going to have to demonstrate it. It is certainly going to be one time and done for the cancer that you are treating in the patient that you receive. Is it going to in initiate a memory in terms of you know metastasis coming from that same original cancer perhaps is it going to protect you against any new cancer coming up? Probably not because the AAV is going to be transient, right. We it is not an integrated vector. So we are delivering the drug product. The effect is going to be extremely strong and extremely time sensitive. It's going to be a lot at once, but the vector should be cleared once the the cancer cells are are removed from from the body. So but you know, we never know. We, we'll see, Ask me this question in five years and hopefully we'll have some good news to share. Absolutely and and then maybe you know, when you whenever you hear the word universal gene therapy, right, that's it's like you said, right, bold and ambitious. So is your company looking to approach the the serotropism, right? Is it, is it a single serotype or is it based on the cancer? I mean you'll have to use different serotypes of AAV. Or are you able to shed any light on sort of like that aspect? So what what I can share is that at at the current plan and strategy is to work with a serotype that has multitropism that has been shown to to to be usable in multiple organs throughout the body. There is certainly going to be effort and resources invested into finding a universal capsid at some point, but it is not the one. The one that we are going to be focusing on is pretty broad tropism already. Right, right. It's like I saw, I remember seeing from your website, right, like sounding the alarm on cancer. So it's seems like that's what the company is trying to do Very interesting. So thank you for sharing that. And then maybe, Mike, switching gears to Vectory for a moment here, right, Maybe you could tell us a little bit about your company's approach with the vectorized maps and how it stands out in the current landscape of AAV research? Sure. So yeah, Vectory is using vectorized antibodies and so we are developing a platform using intracellular antibodies. We are also engineering capsids and then we have kind of scalable AAD manufacturing process. But in terms of the antibodies themselves, they are designed to bind the specific toxic variant of the protein and not the normal variant. So the theory behind Vectory is that we need to go further upstream than many of our peers, so our lead assets in AOS and focus on the target TDP 43. Most CNS disorders are related to protein aggregation of some sort. What we've believe in our current theory is that instead of focusing on mopping up the protein outside the cell, what we need to do is go intercellular and restore the natural flow of TDP 43 between the nucleus and the cytoplasm. So our intercellular approach is able to target these intracellular toxic proteins and re restore the natural flow essentially of TDP 43 between the nucleus and cytoplasm. So getting rid of the aggregation and degradating that and then ideally the healthy TDP 43 will be able to restore in going between nucleus and cytoplasm that as it is supposed to do. So that's kind of the theory behind where we are. And our real point of differentiation once again is more the intracellular aspect instead of focusing on once again what's outside the cells. So that the hope is that there will be more disease modifying for these patients as we're going more to the source. Right. And then you mentioned a neurological right, Is this this technology primarily, you know ACNS type indication or do you think that there is potential for this technology in other areas? Yeah, It really can be used pretty broadly right now. You know, as an early stage biotech, we're focused on CNS disorders as that's where, you know, right now we feel like that's the let's say the lowest hanging fruit in here where we can certainly make the most impact. But over time, this certainly can be evolved to cardiomyopathies in other other areas as well. So it's certainly not ACNS specific company. It really comes down to how we want to grow the company over time. And I think once we continue to de risk our lead asset O2, it will give us more optionality to expand outside the world of CNS and to and to other disorders as well got. It got it. So thanks. Thanks for sharing that, Mike. And you know, I wanted to sort of quickly bring in another topic, right? Like which? Both companies are working towards right, commercialization of your pipeline, right. I myself have been pretty fortunate to work in the AV space in my previous roles and was involved in bringing one of the therapies for Hindi into the market. Although I was not there when the when, when we got the approval. And we all know that commercializing Aavs, right from a manufacturing standpoint is is class comes with a lot of challenges, right? It's still an infant space, Natalie, to your point, right, it's emerging. There is concerns around price tags as, as we probably, you know, deal with every day. So I just want to get your thoughts right from being, you know, a therapy developers on what keeps you optimistic about the future of AAV and gene therapy despite, you know, all the skepticism around, you know, these challenges. Maybe, Michael, let's start with you and maybe then we'll hear from Natalie. Yeah. I think that, you know, in terms of where we are in terms of our approach, you know, as I said before, I think the intracellular antibody approach, it is new and innovative. So I think that there's going to be continued evolution of the AV in the gene therapy space. Yeah. I think that kind of dovetails actually into, you know, how we're looking at the landscape and how it's continuing to pivot over time where there continues to be new capsids that we're monitoring as a internally as we create them in house as well as we monitor what other people are doing. And you continue to see, you know, the evolution in terms of, you know, for the CNS world, broader distribution in being able to have a slightly safer AEB platform as well. So I think over time we're continuing to see these evolutions in these small changes in technology that over the course of time become incredibly magnified. And the magnitude of these changes are huge in terms of again the safety profile, the distribution, etcetera to really make these gene therapies. I think as I said before, more of a prevalent aspect as companies that think will realize the benefit of this versus, you know, a small molecule where the Redux ability is constant. So I think it will continue to be evolution that regard. Natalie, your take. Sure, there are many, many things that keeps me excited and I'm going to try to make it to make it short, the 1st, I mean the first is just to to see that more and more patients are benefiting from it. As you said earlier, it's not a hope anymore. It is happening now. There is still a lot of work to be done. There is a lot of work to be done in making these therapies affordable, amenable to to whoever needs them. So that's going to be on the technical point of view, improving production, reducing cost of goods, etcetera, etcetera. To narrow down more on and bring it back the spotlight on what Sarin is really trying to accomplish. Is that really going beyond what the traditional gene therapy used to be thought to be doing for genetic disease, bringing gene therapy to treat cancer? But why not after cancer, there are many other diseases that need to be that can be treated with cytokine or any other vectorized immune system regulating a protein like infectious diseases. And, and, and why not toxic toxicity or, or war drugs that, that that can be affecting the population. So I think we have, we are just opening the Pandora box and still trying to find what we can get out of it. I'm I'm really, my hopes are pretty high, very high for serine to really pave the way toward expanding gene therapy beyond rare diseases and genetic diseases. Absolutely, cancer is an Achilles heel. And I remember during the pandemic there was also exploratory studies on AAV for COVID, right? So out of academia. So, so yeah, definitely it's, you know, the the niche is just broadening right from rare mono, you know, genetic disorders to. You know, broader. More common diseases. So. So yeah, I agree, right. And I think I'm confident. I like coming from a process development background myself. I remember map days where .1g per liter was considered a success. Now it's 10, right? And now you're talking intensification, so I'm sure, right, like these manufacturing costs and you know, the affordability of these gene therapies when you know cost of foods will continue to evolve. And and you know, in fact that two of my colleagues are presenting later today on the cost of goods for normal therapy. So if you're in the audience, stay tuned for that. But I'd be remiss if I didn't address a broader sort of team that's affecting the industry today, that is the economic challenges post COVID, right? Might given you a background right in finance and perspective on the current environment, I would like to understand like what strategies are you using to maintain momentum and optimism with data in your company? Yeah. I think really in challenging times, I think that the goal is always to be flexible and you know, from a high level approach in terms of how we look at things. So we were very lucky to be able to execute on 130,000,000 Series A or €130 million Series A in November. But a lot of it comes down to being very thoughtful about your approach and continue to refine things and continue to assess the prioritization of the pipeline and regularly reassess that even within our own company, we're constantly looking at things in terms of how do we fail quickly and coming to a faster conclusion before you go into, you know, these longer toxin, more expensive talk studies, and then you have your your failures there. So we're constantly reassessing the the company itself. But in terms of the AV space specifically, again, it comes down to to flexibility where we want to make sure that the AEB 5 that we're using today is the technology that supports our current assets, but also how do we continue to monitor other things out there to make sure that we're using it the best delivery mechanism. So I think overall, it comes down to again, flexibility. How are you looking at the prioritization of your assets, but also what else is there to make sure you're not so entrenched with you what you're doing that you're not willing to see the forest through the trees of what else could be out there that could be actually a better outcome for for your construct in your DC? It's refreshing to hear prioritization streamlining. It's not something that may be used here internally, but it's a usage generally across the industry. And and you know, it's sort of like the need of VR and sticking to that same team. Natalie, right? Talking about challenges, maybe are you able to share some of the biggest challenges that you and then that siren as overall right you're facing right now in terms of developing and commercializing, you know, your treatments in your pipeline? Sure. Well, I think it is really going back to your previous question in a nutshell, the biggest challenge we all face is, is funding. Why is it? It's because all these product manufacturing approaches to get to the clinic, you need to invest an immense amount of resources to produce the drug and to conduct Ind inhibit toxicology study to convince and to prove that it is safe to go into human and especially when it is the first first in human drug product. So funding is the big challenge because manufacturing in and conducting all of these studies take a lot of money to conduct. One of the IT it it's a, it's a double edged sword for us is the fact that we are, you know, trying to very to focus on. I think it is very important what Mike said. You really need to be bold to attract investors interest by having very bold set of, of data like Seren has that are black and white. It works. It works in mice, it works. You know, it has to be evaluated in human. We cannot miss that chance. But you also need to be focused on really prioritizing the resources, allocating the resources to go to your first phase. One, and this is coming from my CMC back background, this is something I always tell focus on CMC. It's going to be taking you more resources and more time that you ever think focus on that. But one of the kind of a second level challenge that we have is that we are, you know, investing for success in our first phase one, but we also want to build the foundation for the universality approach of of our drug products. So what if it's an immense success? We want to be ready to move to Phase 2-3 and and to commercial as quickly as possible. And this is only possible if you have put in place the foundation before your phase one, especially regarding manufacturing, right. So you want to be able to pivot very quickly, quickly to larger scale and and and to BLE enabling testing methods and and manufacturing methods. So this is the day-to-day challenges that we that we live at Sarin pretty much everyday. How do we allocate our resources wisely or in immediate return on investment but also sitting for the future? Exactly, exactly. And then you mentioned a good point there, right, like I think prioritization resources. So I also want to stay with you and come to recruitment, right, a new company, right, recently launched. How has your sort of recruitment strategy been? I mean, do you, I know overall the biotech landscape is, you know, struggling with layoffs and so on and so forth. So maybe maybe you can comment on how hard or easy was it for you to like find right talent and and maybe sharing a little bit of your experience so far. My team, yeah. Yeah. Yeah. Yeah. Well, one approach that Nicole has really followed very closely and that I totally support is stay lean. And we're lean. We are a very small company. I am the only person on CMC. We have a small group working on preclinical and a very tiny group working on clinical. So the company itself workforce is really lean, which means that you need to make it very, very wise choice in who you hire. It's not been a challenge to find talent. I have to say probably one of the reason is Nichols Network and being so recognized in the gene therapy field and also being located in San Francisco near UCSF and many other biotech companies. So recruiting talent was not a challenge, but we spent quite a lot of effort making sure we recruited the right talent so that we could we could stay lean. You know, one, one of the strategy that is usually quite difficult to decide for a start up in particular is how much are you going to develop in house and how much you're going to outsource. Outsourcing is expensive. We all know that CDM OS are expensive. Consultants are expensive also. But staying lean as a as as a company and and using the expertise from outsource company has been something that has worked pretty well for us at this time. Thank you. Thank you so much. And I just wanted to shift focus also for a moment here, right, about this topic where about partnerships, right? I think I'm really excited. I think every successful business requires, you know, strong partnerships. It's a critical pillar, right, for the success of any company, especially in the biotech space and emerging biotech companies like yours, right, Siren and Victory, they play a critical role in, you know, developing, you know, medical breakthroughs, right? In fact, I saw somewhere that about 80% of the total development pipeline is with smaller companies, right, like emerging biotech companies, SAC, which is a truly remarkable statistic. And one of the things that, you know, we as a company do is the advanced Biotech Grant program, which we run globally, rights designed to support companies, you know, such as the emerging biotech space, right? And we provide expertise and resources that they need to get to their path of commercialization. So I know both Siren earlier this year, excuse me, and Victory right back in 2021, Mike, have been recipients of this prestigious award and we are excuse me. Yeah, my my throat is acting up. But and we are, you know, honored to be part of your journey. So Mike, maybe I'll switch to you, right. Can you help our audience understand the importance of partnerships, especially with, you know, technology providers from from that lens, how has it sort of helped your journey in your, you know, commercialization, right, or AAB development and maybe some examples of how partnership between our companies has sort of made a tangible impact on your work? Yeah, it's a great question. So as you know, we received a grant from your company back in 2021. It was it was great for us in terms of being recognized and also to begin our our collaboration partnership. So we're able to to use that grant to get some critical reagents, consumables to help the company build out its manufacturing process for our lead asset at that time. Since then our relationship has evolved and the partnership has as well. So we have a insect cell line partnership which is a substrate that we use for our AAD product. But what's really impressed me most about our partnership is being able to leverage each other synergistically in the know how and expertise which we can leverage from your The technical team that you provide has been incredibly valuable and just tremendous for our relationship, as well as using you as a really jumping off point in terms of better understanding the products, how should be thinking about it and being able to use you as a sounding board as well. So from our side, it's been incredibly beneficial relationship outside of just, you know, the partnership around Insec. So and to be able to use your company really as a resource and I think that again and again and again, I think that partnership should be looked at outside of just, you know, what was the give and take of it in terms of the tangible. But moving beyond that too, how can you leverage each other in terms of sounding boards as well. And our relationship has really been able to benefit from that. Good to hear, Mike. And I know our team in Europe, I know you're based in Amsterdam, right? Most of your research work, they truly enjoy working with you, right. And thanks for sharing that. And then maybe Natalie, putting your process development hat on for a second, right? I'd like to get your perspective cuz you know, you're now plans to work with technology providers. So what do you think that like we can the role we can play in helping you overcome your challenges and maybe scaling your operation towards that journey that you're on? Yeah. So first of all, I would like to to, to say that I really agree with my my shared and and really having this partnership into leveraging both sides expertise, especially when it comes to AV manufacturing, the expertise that your company has and and many other technology providers have developed over the years. It's, it's an immense source of, of knowledge, the one that we as, as sponsors have developed and acquired over the years as well. And our needs may be different. So you, you know, everyone learns from one another because a lot of the, of time, each case is, is a little bit different. So what I can tell you is that receiving the award was one of the greatest highlights of for, for for Siren. It is just in itself getting an award being recognized has a a boost effect that makes makes us all even more excited to continue. But working with leaders in in the biotech world is is even more more important. We are just starting to work on on that on this partnership. But what I can see very well is that because Sarin is extremely, it's very important to Sarah and excuse me to make sure we can develop a platform that can produce our drug product, our AV vector drug product efficiently at low cost. That that is one of the long term goal in addition to of course, curing cancer. And there's only one way to do that is to work efficient processes. And so all the innovation that is conducted in, in research laboratories and in and in company like yours in, in trying to, in increase AV production yield, whatever platform you're using, whatever it could be changing the media, it could be changing a transfection reagent. There's, there's a lot of innovation in, in that aspect. Recently they are transfection enhancer or boosters and exploring all of these innovation to try to boost our titer, increase our recovery when you're thinking about downstream and also continue to maintain or further increase the quality of our product in terms of purity. And you know using all the the tools that you are focusing on developing to help us and us basically telling you what we need. I think it is a very successful approach to. To create new things that are going to change and impact not only sarin, but probably more, more startup and more company investing in gene therapy in the future. Absolutely. I think innovation should never stop, right? They should always, you know, I mean, I remember this terminology, right? Like fit for purpose and purpose built technologies, right. So when I first entered the gene therapy space, it was all we use this filter for maps. It worked for AAV, right? But I think, you know, we've seen that culture of innovation, right? Like, hey, we need to make products built for gene therapy and viral vectors. So that's coming up. And I agree, right? I agree with what you said. And then thanks for sharing that. Maybe just to follow up on that and maybe to both of you, maybe we'll stick to Natalie here, right? What are some of the qualities right from an ideal technology partner that that that that you're looking for? Maybe one? Or two, the quality of the of the drug product, right. So the quality attribute that that we are looking for, they are pretty standards, but we are extremely specific on on the purity level of course, but also the potency of the drug product making sure it is consistent and it is high a very low amount of residual impurities. We all know there are many, there are hostile protein, hostile DNA, residual DNA. And so investing in not only improving the upstream because for people who have heard me speak, I always say quality and quantity, but also quality starting upstream. So again, we've all the innovation that is that we've discussed earlier, you can really improve quality of your product early on in in your transfection or, or or whatever or or your Baculo infection based platform. If it's what you're using by increasing the percentage of full, by reducing the amount of plasmid or wholesale DNA or number of cells that you are using, yet still boosting your AV titers. So, so that, that is, that is very important. And then you are, you know, making sure that you're downstream of purification process is optimal at removing all these impurities. So those are the, the quality that we are looking for because they ensure they, they, they ensure efficient efficiency in the clinic. But first of all, they ensure safety. And, and let's not forget that it's the first thing we need to demonstrate in our first phase one. Absolutely. And then maybe Mike, switching gears a little bit to business and relationship aspects, right, like with with technology providers like what, what are some of those aspects that you look for in your relationships? Yeah, it's a good question. I think, you know, the the first thing is just, you know, know, how have they done this before precedent? I think, you know, one of the things that we've kind of are working on currently is really from the CDMO side, you know, making sure we're choosing the right person and the right team. Because ultimately from from our company's side, we largely do a lot of our batches in house. And we made that decision early on that we would, you know, as a COGS benefit, as was keeping the process in house and, you know, own the process because a huge benefit for us to have that degree of control as we start to pivot towards the clinic, we are, you know, moving towards a more active relationship with a CRO and CDMO. So, you know, from our side, it comes down to, you know, do we feel comfortable down? Do they have the process in place in the know how? But I think a lot of it comes down to being collaborative as well. We want to make sure it's a group that we can manage together because ultimately there is going to be a sense of control that we are going to be losing as we pivot from in house to working with the CDMO and making sure that again, it's a relationship that we can build that going forward. And also making sure that we're not losing timelines as well because ultimately from a shareholder perspective that the timelines are are critical importance here. So making sure that there's regular dialogue in a willingness to have that it is, has been hugely valuable for us as we go through the process of selecting. Got it. And then maybe just to pull some string there, right, like a forward-looking question. So if you could Fast forward, let's say five years, right, what would be for victory, right? The biggest milestone that you hope your company would have achieved? Yeah. From our side, I think clinical proof of concept would really validate first of all the broader platform, but the hugely valuable for O2. First of all, creating shareholder value, which is always important, but I think even more importantly is really having a meaningful benefit to patients. Ultimately, we're looking at our assets as disease modifying and be able to slow or potentially even stop and reverse the process that people are going through with AOS and other CNS related disorders is horrific to watch it and be a part of. So being able to have that meaningful benefit to such an area of unmet need would be incredibly uplifting. And I think for first of all the broader CNS space, but I think also for the gene therapy space as well, I think it could be an incredible tailwind for both parties as well As for patients, so. Thank you, Mike. And just looking at time, it's just flying by, right? Like when you have a good conversation. I do want to remind the audience to type in questions in the chat. Keep them coming. We did have some through another channel that came through. Right. I'm gonna just take a couple. Let's see. So yeah, this is a good one. So what trends in gene therapy are you most excited about and where do you see the field going the next 5 to 10 years? It wasn't address to anyone specific, but let me maybe put Mike you on the spotlight. Yeah, I think one of the the trends that we're we're seeing is the the reduce ability aspect. And you know from from our side, you know, we're, we're hopeful that our gene therapy and our AAV is a, a lifelong procedure for these patients. But I, we are starting to move towards the redose ability aspect, which is, is incredibly beneficial to patients. As you know, we're going to be going earlier and earlier with some of these patients that we can treat and looking at somebody with, you know, DMD or somebody's illnesses that hit very early in people's lives, being able to have that redose ability aspect is hugely valuable. So I think that's, you know, certainly one of the overall goals I think would be beneficial that we're starting to see a trend in. And I also am hoping that over the next 10 years, there's a better translatability between capsids and drugs from what we're seeing between mice and humans. Because right now we have a lot of capsids that are terrific at targeting brain tissue and and a mouse, but the translatability to humans isn't there. So you end up doing a phase one, phase two study and then really determining there that this drug may or may not work. So I think being able to get closer to translatability with a EVs and with broader gene therapy in general will be hugely beneficial as they allow companies to fail faster and then be able to reallocate their capital to try other strategies as well Got. It thanks Mike for sharing that. And maybe there's another one and maybe I'll just pass this to Natalie, right? So what advancements or new technologies do you think Natalie will be? Game changes for AAV therapy maybe from a technical side? So in the past, there's been, there's been few moments where where they've been game changer before looking at the future, just to to provide an example, one was to find affinity resins that could really boost the, the purification, the quality and the recovery. For many stereotypes, they're like universal resins. Now I come from a time where we had, we didn't have that for pretty much a big part of my career producing AAV. So that had a huge impact and I think the trend is going to keep on improving affinity binding and specificity of of this reason. The second big impact was to finally moving away from non scalable platform like adherent and and moving to suspension. It seems like a no brainer today if you just join the field, pretty much everyone is going to move to suspension at some point. That was not the case a while ago. So one one thing that I'm really hoping will will happen over the next 5 to 10 years will be improving manufacturing platform to a point where we may be able to start thinking of automation. I have this cell shuttle from Solaris that has been put in place for cell and therapy manufacturing. Nothing stops us from dreaming that this will happen to to AV at some point. We have all the tools for that. So automation will have a huge impact in making the the processes more reliable and reducing the cost of goods because at the end this is that's what we want to achieve, making this drug more affordable. Yeah. And I think to your earlier point about universe universal platform templating, right, I think that will play a key role in making these sort of bold ideas come to vision. So there's another one I want to read it out, right. What about non communicable diseases? I'm guessing this is around the pipeline, right? Do you think this will be an important issue to work on and is big pharma addressing these diseases? Natalie, do you want to take that one? Mike, I'm not sure what non communicable disease are. Are they one that that have a very low amount of patients, ultra rare disease or disease? Probably more common diseases, right? Or. So expanding, yeah, if it's in that, in that, in that way, I really believe that gene therapy is going to expand to not to beyond just genetic disease and rare diseases. Again, I think Sarah leading the way in, in cancer, which effects a very large number of people to metabolic diseases like diabetes or or other infectious diseases as well. I I really think the niche is there. It is an awakening side of the gene therapy field, but I really think it's going to grow and and pick more more steam over the next 5 to 10 years. All right. And I think you know the clarification is around cardiac diseases, diabetes like much you know beyond gene therapy. So, so I think you addressed it pretty well. Maybe, maybe Mike, another question, can you reflect on the potential of exosomes as vectors in gene therapy? You know, that might be a a, a better question for for one of my peers on the panel, OK. I I can answer just a briefly. I'm not an expert on exosome, but I just happened to be a, a scientific Advisory Board member of a, a startup Quay Health that is investing in exosome. And they've been able to convince me that the potentials is enormous for exosomes. And there is also a path to combine exosomes with AV gene therapy. So exosomes and, and, and modalities, therapeutic modalities using exosomes are, are booming right now and, and it's going to grow very, very seriously over the next few years. I'm very curious to know how and when exosomes and AAV can merge. I'm very curious about that. Thank you. Thank you so much. And I think, I think that you know, was was the perfect answer, right. And just looking at time we do, you know, seems like we are running out. So we'll we'll probably switch to closing remarks. But you know, just a note to the audience, keep the questions coming. We'll see what we can do, you know, after the session to, to get them answered. But, you know, thanks again for your, you know, good questions, right? It really keeps the panel going. Maybe, you know, it's like closing remarks, right, Natalie and Mike, I think, you know, I'm just looking at the, I mean, I think we've covered all these questions have touched on a lot of key topics. Maybe I'll start with Mike here. So Mike, when you look back on your journey, right, if you had the chance sort of to do it all over again, right, maybe from a strategy perspective, what, what is there a thing that would you know that you would change about your journey or wish you had done it sooner? Or maybe you can comment there on if you had. Like magic more and. Go back in time. It's a good question and you know, not, not to minimize the question, I like to think that each of the decisions I made was a building block towards something. So ultimately I probably wouldn't change much because as I said, each right decision, wrong decision was a building block to where I am. And ultimately, if I could go back in time and change some of those wrong decisions to make them right, I probably would have walked into that trap just later in life. So I always like to be able to look at my failures and be able to use those as an understanding of maybe how I could have done things differently. You know, I think the only thing looking back I would probably change is I was in investment banking for almost 15 years. I probably would have left the world of banking a bit earlier to go to an operational side. I just absolutely love the opportunity to build something and really have an ownership and a stake in the company and being a part of it as it grows. So that's probably the only thing I'd probably try to do earlier just so I could be a part of some of these terrific companies like Vectory just earlier in my career and really be a part of something special. Great. Great. Thanks, Mike. Natalie, maybe something for you, right, like we started with you, we'll end with you. As we wrap up, what would be your Moon shot goal for the future of gene therapy? I, I'm going to repeat several, several thoughts that both Mike and I have have already expressed during this discussion. But having AAV of the shelf in the future for rare disease, for genetic diseases, for cancer and beyond, I, I think this is, this is what I am hoping for and I, I believe I will see it. Perfect, perfect. Thank you so much, Mike and Natalie, this was fantastic, right? You guys shared a lot of insights and experiences with us, with the audience today, right? You've got immense value, so thank you again. It was truly inspiring to hear both of you and the work you've been doing, the space in gene therapy. And again, like I said, we're proud to partner with both of you on your path towards commercialization. I know the journey isn't easy, right? But we want to be there as trusted partners for you. And again, and a big thanks to our audience for joining us and engaging us with a lot of good questions. So this concludes our panel and I hope you know everybody enjoys the rest of the sessions. And over to you, Jess. I think Jess, you're on mute, but maybe I'll just jump in quick here after the panel discussion. I think we'll have a break. Just I don't think we can still hear you. Let's get into break for 10 minutes while we sought some IT issues. And again, thank you again for the panelists. And yeah, stay tuned for more engaging talks up next. Tess, this is Johannes. Can you hear me? I can hear you, Johannes. Yes. I have a lot of feedback and echoing to speak. Can everyone hear me? Yes, I can hear you. Do you also have echo? No, I do not have echo. Welcome back everyone and apologies for the technical difficulties earlier. We seem to be doing better now. So welcome back and moving on to our next presenter. Johannes is the founder and CEO of Bio Labs and Lab Central. Today, he will be giving a presentation on creating environments where founders thrive. Johannes, welcome to the symposium. Please feel free to begin your presentation. Thank you, Jessica. Good morning, good afternoon and good evening. I don't know what time zones you're all joining from. It's my pleasure to to join you for this discussion and to see a little bit of our world. So my name is Johannes Srihoff. I'm founder and CEO at an organization called Bio Labs and also Lab Central, which is one of our sister and spin out organizations where we build environments for founders of scientific companies. These are often scientists, engineers, medical doctors who have therapeutic ideas that need to be developed and most of them in biotech and they need environments where they can develop lab safely, their lab based innovations. And so that that's what we're going to talk about today and hopefully that at some point you will find an opportunity to visit one of our sites or consider building one of your ideas in in in one of our sites. Next slide. I I think I'm able to advance myself here. So one the slide that I'd like to share is why are we even excited about biotech translation? Well, it's a huge economic opportunity on the one hand. And on the other hand, it's also important that our societies, that each of our societies be well prepared. As you we have all seen during the COVID crisis, some countries were better able to respond and were able to mount a vaccine defense than others were. Biotech is also a driver of intellectual property and societal value as we create access for patients to new therapies. All of us know, have family members or have friends who are suffering from diseases that urgently need cures, and many of you I know are working on those and I'm grateful for that. And last not least, we work very closely with the Pharmaceutical industry who are in need of innovation at all times. Because as many of you may know, we now have a situation where over 70% of the newly approved drugs by the big pharma companies are not actually invented in house by them, but but source at some point through acquisition or through licensing into these companies. Here are some of the elements that we've identified from doing this now for over for over 10 years, 15 years maybe in many cities. We are currently in 14 markets and have 23 or 24 labs open, and there are some recurring themes that we always see essential for a successful environment in which startups can thrive. And it all, of course, starts with academic excellence. If you don't have a medical school and a couple of research institutions that produce top notch research, you will probably not have a successful startup startup ecosystem. But a great academic research alone is not sufficient for that either. You need a lot of other things to to also be present, For example, the presence of knowledgeable venture capital. And I I take note of the knowledgeable because just money isn't gonna fix it. Ideally, you will find investors who can contribute more than just the money and the Czech who will be on your serve on your board and give you guidance and make the right connections to strategic partners or to future employees at the right time. And who will have the experience of running many other companies that you might not have as a first time entrepreneur. Supportive tech transfer practices and licensing experience is another very important bottleneck in many cases that unfortunately hinders the successful creation of startups and that I recommend groups look into if you. If you are an administrator at a university, please do spend time and effort to staff your tech licensing office with experts and experienced players who will not be an obstacle but rather support your academic founders in their spin out ideas. We need supportive environmental and cultural and governmental environment that will allow will permit academics to pursue the idea of founding companies. If there's a mindset that a spin out is counter to the academic mission, then oftentimes that that creates real obstacles and we need access to talent at the right time. Developing drugs is a team sport is a relay race and a marathon and and it needs very different types of talents at different stages of development. So having access to a broad and and deep talent pipeline is certainly helpful for all of these startups. Lab space and lab functionality is what what we specifically provide and we have a few slides to talk about that in in more detail and industry support. We are grateful for the support that we have from industry, including from the sponsor of this event, whose complicated name legal entanglements I'm not going into today. This is our footprint today between Bio Labs and our partner organizations, Lab Central and NBC Bio Labs. We currently cover 14 major markets mostly in the United States and in Europe and a small footprint in Japan where we where we run two dozen labs right now for for startups. We have over 500 companies that use our labs today and about half of them turnover. Every year since we got started, we helped accelerate more than 1000 startups and created those startups, created over 8000 jobs in the process. These are my organizations. So when when you hear me talk, I I sometimes confound the organizations because for me this is all one thing. My mission is to help entrepreneurs and to help startups and I do that through multiple entities. I do that through lab entities and I do that through a venture capital firm that I also Co founded. It's called Mission Biocapital, an early stage seed, and Series A, a life science investment fund with about $500 million under management based in Boston and San Francisco. At Lab Central, it is our vision to provide the perfect and the best possible environment for founders to pursue their startups. And we do that through multiple activities. We do that through Well Located, Strong spaces that are fully equipped community and and industry support. Labcentral itself was founded as a public private partnership between Bio Labs Mission and with the Massachusetts government. They gave us an initial grant that allowed us to launch our first Labcentral site and then we were able to bring in many other industry players and and other startup contributors. The outcome of this is that we have now been able to accelerate hundreds of projects and hundreds of startups through through Lab Central and you see some of the impact on the right. Certainly I'm mostly interested in the clinical trials and the outcome for patients. We now know that there are more than 15,000 patients who have been dosed with drugs that were invented or called or developed in our labs. That makes me really happy and proud. Sorry, I keep getting called. Here. We started Lab Central in 2013 and our mission is to really support entrepreneurs as they spin off their companies. We do that with space and we do that with community. We also provide operational support such as environmental health and safety, procurement, a whole lot of programming and networking and mentoring opportunities for our companies. It's not like you can just show up and be admitted. It's actually fairly selective. Companies can apply at any time, but they have to go through a selection process that's fairly rigorous. We accept about one out of four applicants and we look for the criteria that would prescribe success in startups. Our mission is not to make startups easier for everybody. Our mission is to make good companies really strong and give the top 25% of founders the perfect environment and increase their chances of success because we believe that we will have the biggest societal benefit and impact by focusing on on the very talented and the very well placed startups and give them the perfect environment. And so the process is really that at any time you can apply through our websites. We will typically do a quick screening call with you and ultimately we'll present live in a selection committee meeting that we hold at every site for at every in during every month of the year. So we have dozens of these meetings every year, and we see hundreds of new companies applying every year. That allows us to have a very good overview of the scene of innovation that is going on in the US and now in in many other countries. So we see trends really early. We are able to compare and contrast the strength of the scientific solutions and the teams. We typically look for four things in in the presentation. So if you're ever applying, keep that in mind. One, we look for the quality of your science. Two, we look for the business plan. We want you to present a business plan. And, and if, if you don't really have a credible business plan, you should probably stay in academia a little bit longer. And it, our labs are not for basic science discovery, but for development. Three, we look for the team, who's on the team? What have they done before? Why should we believe that this team is best positioned to develop the business plan that they just presented to us? And then four, what type of funding have you raised? How much money have you raised? But also what quality of funding have you raised? It's a very different thing if you raise $1,000,000 from a qualified venture capital firm who is an expert in your area, or if you're able to convince a review committee at the NIH or the NCI to give you a highly competitive grant. Yeah, it's a different thing if you have a rich uncle who just likes you and gives you money because he can. And so that that makes a big difference. And it's part of our selection criteria as well. Once you admit it in the labs, you will benefit from our model, which is that you have access to fully built out and fully functional labs immediately. You can move in, get a bench, you will have everything at your disposal from pipette to a centrifuge to an oven, to APCR machine up to mass spectrometry and even in some cases vivarium capabilities. So that cuts your time from idea to the first experiment down by many months. In tip, in the typical traditional way, you would have to outfit your own lab, purchase your own lab equipment. We have fully outfitted labs with all the permits, all the procurement, all the operational support in place and now you don't have to own the expensive lab equipment. You can just use it. It's part of your rental model. And and so it is a really significantly lowers the bar for people to try out new ideas from, you know, many millions and and many months to get started to a couple 100,000 in running costs during your your first several years. We work very closely and successfully with many industry partners. You see a snapshot of our sponsor wall here and and these come in all different flavours. We have minipo Sigma here, we have Thermo Fisher here, we have Zeiss. They are suppliers of lab equipment and they help us have the best and most up to date complement of tools available for for you the scientists. We also work very closely with about 18 of the 20 largest farmer companies, not all of them shown here throughout our network who provide capital and support and presence and mentoring to our startups through a multitude of tools. And it's a real win win because as we said before, the farmer companies, of course they come because they need to know new ideas and they need to know what are the new trends. And maybe eventually they will want to acquire you if you make it to the right milestone. For the for the startup entrepreneurs and the scientists who are spinning out companies from academia, it's super valuable to be able to talk early to a multitude of different pharma partners to hear what is it they really look for. I've been through that same transition as a medical doctor and then a scientist. I didn't know much about what pharma is looking for in a drug development program. I thought they're super excited just about my science. Eventually we'll have to all learn that the realities of drug development demand different things. Maybe they are different models required. It's not so much about the high impact factor of publication any longer, but it's about choosing the right and validating model that will be acceptable to pharma and that will find green light with the FDA so that you can move your project forward. And so by enabling the proximity between pharma, the buy side and startups, the sell side, we are able to accelerate that discussion and make it much more efficient for both sides. We have built under the Lab Central brand. So, so far six different labs starting with the original location in Kendall Square at 700 Main St. You see that up top in the left corner called Lab Central 700 built in 2013. That's where we offer individual lab bench rental for small start-ups. We've then built graduation programs at Lab Central 610. This is for companies who have more than 10 or 15 employees and they want to grow with us to 2030, 40 employees at that location. And most recently, we've opened Lab Central 238 specifically for companies developing complex biologics. This is a facility where we have much more lab space available for you. And this is for typically somewhat more mature companies who are working on process development and scale up mostly for cell and gene therapy modalities. We also have other smaller labs. Two of them partnered with Harvard University, one on the campus of Howard Business School called the Palyuka Harvard Life Lab, and one on the campus of the Harvard Medical School in Longwood called the Botnick Howard Life Lab. And then finally, we run on behalf of buyer. We designed and we run and we staff the Bayer collab here in Kendall Square. Here's a a slide that shows the trends at Lab Central, the number of applicants that we're tracking. So in a typical year, we we would admit between 60 and 80 new companies. These these are the admissions numbers during the year of of COVID. It was crazy. It went through the roof. We had, we had so many more companies knocking on our doors. We now back to pre, pre pandemic levels. I have to say, I don't know how many of you are in fundraising mode. We are seeing now signs of spring after about 18 months of really hard fundraising environment for startups. We are seeing that companies are able to get C drones and Series A rounds underwritten again. Now we we think that situation has really improved especially since the summer of this year. We're not out of the woods yet, but certainly things are trending better right now. So hang in there if you're if you're part of that population. I wanted to share with you a few of the trends that we're seeing in terms of modalities and and disease areas and indications. These are the areas in which our companies have developed their own clinical trials. And you'll see that the vast majority of cases is in oncology and this is mostly because of the nature of our funding in oncology. It's an it's often an easier case for the venture community to invest in oncology startups because often it's permitted in this indication for you to do your first in man study in patients. So hopefully you will see some efficacy outcomes or clinically meaningful outcomes already very early on in your first in man study because you're able to go into patients. That's why this these oncology indications, hematology indications are typically more easier to underwrite for for venture capital investors. We also see a large number of neuro and neuro degeneration companies. It's very interesting because neuro was a field that had not much going for it about 10 years ago. I think it's mostly through the development of precision medicines and targeted interventions using for example, ASO modalities or others, also gene therapy modalities that we're making real progress here. And I have great hopes that the field of neurodegeneration and in general neurological treatment, also neuro psych, psychiatric treatments are developing much stronger in the years to come. This is sort of one of my final, this is my final slide here. We were just sharing with you our pride in having enabled many, many companies and many innovators, many new ideas and birth them into the world. This leads to very meaningful outcome, both economic outcome, large amounts of venture financing raised by our companies, good number of IP OS out of our cohort of startups that typically started with one or two people only and significant M&A outcome for many of them. Most importantly, again to repeat that for me is the outcome that we're having for patients. We know of more than 250 clinical trials that have been launched for compounds invented or developed in our labs and more than 15,000 patients have been dosed with that. And so while I cannot report to you yet that any drug has been approved that was invented in our labs, it is really a matter of time. And I'm quite confident that soon enough we'll be able to celebrate that. As you know, it takes a long time from ID to to drug approval. Well, this is my last slide and I want to thank you all for your attention and your time. And want to also invite you, if you ever find yourself in Kendall Square or near any of our labs in Philly, in New York and North Carolina or in, you know, European locations on the West Coast, please do stop by and say hi. Thank you. Thank you so much, Johannes, for sharing your insights with us today. That was a great presentation. And at this point, what I would like to do is I would like to let the audience know that if you have any final questions to please submit them now using the Q&A widget on your screen. So if you'd like to have a sip of water, we are now moving into Q&A session. So we'll we'll give the audience a couple seconds to see if we get any chats coming through. So far, no questions. But Johannes, if you have any, you know, I, I know you, you just gave your closing slide. But if there's anything else that has popped into your brain that you would like to leave the audience with, we do have another minute or two. If there's any last comments or things you'd like to say, I'll leave it to you unless, and if not, we can always move to our next presenter. But I'll leave to you if you have any last words. Yeah, I just want to encourage people to start thinking, even if you're an academic scientist, think about are you able to take this idea out? I want to encourage you. There's lots of help for you available and you can come to us or any other of these shared spaces and you will, you will get a lot of advice and a lot of support and help. And we're grateful to also to our industry partners for, for the support that you are all providing. Thank you very much. Wonderful, fabulous, and thank you so much again for your time today. We really, really loved having you here and appreciate everything. So thank you. Great. And we have a couple minutes now until our next presentation. So we'll maybe take a quick minute or two break and we'll come back here at 11:35 Eastern Time for our next presentation. Hi, everyone. So we're ready to move on to our next presenter. Oliver will be giving a presentation on mRNA process and cost modeling, a tool to optimize process development. So, Oliver, I am now ready to turn things over to you. OK. Thank you for that introduction. I appreciate it. Hello everyone. My name is Oliver Prince. I'm the senior modality expert for PDNA and mRNA in the Americas. And I'll be walking to you walking through this presentation on the mRNA cost modeling. This isn't my disclosure slide, so I'll move on to the next slide. And so I'll use this pointers. This is work. So I showed on the slide here is that mRNA technology is a modality with high potential largely due to its bioprocessing simplicity. We're all familiar with the central dogma of life, which is DNA makes, RNA makes protein, which mRNA takes full advantage of. On the left, which is shown here, I'll put my pointer here you'll see the typical biological processes that are so derived, right. The cell is particularly important here because it allows us to use produce monoclonal antibodies to treat things like and inflammation. And antibodies are very effective at not only tagging proteins, but also inhibiting and blocking them from eating a disease. This is why they're so popular and well distributed in terms of the pipeline. Similarly, another cell derived biological is viral vectors and viral vectors is significantly different is that we're Co opting the biological mechanisms of a virus to then insert a gene and then use the targeting principles of that viral vector then targets particular cells and to mediate an expression. So what are the challenges? And clearly the challenges will reside in the upstream. A lot of research and effort and process development would be an optimizing cell lines, media sourcing and things of that nature in addition to some of the biosafety considerations related to viral vectors. So how is mRNA different? Like I said, it's largely an enzymatic process. What you need primarily a sequence data, which is why it's so effective, it's so quick and it's mostly so free. And when I say mostly it's because generally speaking, because you're starting with the DNA template that's going to and in most cases start with plasmids being amplified in the bacterial system. However, there are other methods employed. However, there are challenges. It's not perfect, right? It's less well established. Now. I know we're standing on the shoulders of many decades of research as it released it relates to mRNA, but it is as the pandemic has shown us, the recent pandemic has shown us and even where we are now, the access to adequate suppliers and supply of critical reagents is not well distributed. So what am I presenting here? And so we developed this model to help increase access in particular for domestic vaccine production. I'm going to start here with a comparison of wow, how mRNA compares to the other three traditional modalities, which you may be familiar with. And this is an easy comparison because it's the ones that we're most familiar with. In particular, starting with the pathogen based, right? And something you'll notice very quickly, we start to move from the one bug 1 drug to A1 platform many targets. And that's what's typified here in the in the pathogen based system. It's well established technology, long development time, but clearly there are biosafety concerns, especially when you're dealing with BSL 2 and BSL 3 or even BSL 4 pathogens. However, it has the lowest cost of goods. So it's not going anywhere, going anywhere anytime soon. The two the next two, I'd like to point out viral vectors I've already mentioned and talked about because it's it's more of a it's more of a you're inserting your gene of interest into a vector. But virus like particles are a little bit different is that you're actually taking a protein or antigen of interest and displaying that in such a way. So it's a virus like particle. It's displayed the whole. So it's actually an express protein that's the plated displayed in a certain topology to get you that immune sprons that you're looking for. The difference is between the main differences here are the cost of goods. Now just for your, for your awareness medium cost of goods just means that it just costs more than the pathogen based. I'm not assigning the cost. I'm just saying it costs a little bit more because it's a little bit more sophisticated technology. And with regard to the mRNA technology, again, I'm going to reiterate this point. It's very rapid primarily because you only need the sequence information and easy to deploy. As a result of that, most of your energy are going to be in the sequence and most of your research energy is going to be derived in involved in doing the sequence information and then and then doing the bioprocessing and then packaging that up into the encapsulation of the lipid nanoparticle. However, as noted in Bullet 3, because of the rapid production, there is a global shortage of not just technical expertise because not a lot of people have a lot of experience developing this, but also in the in the sourcing of critical material materials. And as a result, in particular for a lot of the more materials, the cost of goods tend to be very high. And so we've developed this model to help enable decision making and where cost will be derived from. So what are some of the process assumptions that it went into this model? And I'll scroll through this just so you know that our starting point here at the far left is the plasmid DNA. And it's circularized here for good reason because we're including the three enzymatic steps to get your full length mRNA as part of this process. This process train is organizing to make Purify, Formulate and Final fill just to help facilitate this conversation to bring us all on the same page. In addition, we're also including the LNP formulation that's disappear as part of that cost consideration. However, we are excluding prior preservation, which is shown here. So in the next part, we're including UFDF and chromatography after each enzymatic step, which is noted here and the cartoon. And then next we're addition, we're including an additional UFDF before and after the LNP formulation, which is located in the formulation section here followed by a buffer exchange in concentration prior to final film. These are important things to consider that I'm pointing out is because they actually contribute to the costs deriving the process and a lot of the information that I'm going to be sharing with you today. So this is more of a / a high level overview. I would like to give some visibility to the step yields each one of the unit operation. This may be of interest to the audience. Step yields and recoveries are estimated based on literature. Ports and enzymatic and Chrome steps are the rate limiting steps in this process. This is worth capturing because if your DNA is not converted to mRNA, it doesn't matter. And I thought mRNA is not cap. That also doesn't matter. We're only looking at full length capped mRNA with the Poly A tail that's going to be encapsulated into the lipid nanoparticle. So how do we build the model? Right? And this is an example of the cost breakdown. There are 5 buckets here. I'm going to go from counterclockwise. Starting with capital. That just refers to the things related to your building. That includes your equipment cost and capital. Capital estimate includes installation, pipe work, HVAC validation. Materials is going to be important for us because that's actually where you're going to be. Your enzymes and your NTPS are going to be. That also includes cleaning chemicals and buffers, consumables. That's going to be part of your purify bucket that I mentioned previously. That's going to include your filters, membranes, chromatography, resins and single use components followed by the labor. These are the people in the staff that's going to be running the facility or the lab that you're in. And then other in costs, other costs including insurance, engineering, spare part and utilities. As you can see here in this little in this chart here, we're teasing something that's going to come up later on as it relates to which I'll show in a second, which will come apparent as we go through this presentation. So this slide here is just an extension of what I've showed previously just to show you that this is intentionally meant for you not to read and for you to squint. It's because they're, just to let you know that there's a lot that went into this, there's a lot of data behind a lot of these assumptions. And so it's necessary to boil these up to a high level so that we can have a discussion and make assumptions, right? And that's, that's generally the definition, essentially the definition of the model. So I just wanted to give some visibility to that. So this is the overall approach going from left to right input model outputs. The input includes the process flow, which I walked into, walked you through pricing, which I did not discuss, a number of assumptions, and the process parameters which I touched on lightly, which is here. The model includes mass, material balances, sizing for consumables, equipment, time, labor and even floor spacing. And finally, the outputs and which is going to be used to help answer 3 main questions, which I'll touch on shortly. So this is this slide here. Before we jump into that, this is essentially my disclosure of the slide to say that this model is directionally correct and but it's not perfect. There are three elements that are highlighted here. Cost models can't predict if the given given approach will work technically. So it may, it may fail, so it doesn't account, It may not account for your ability to do this work in your hands with minimal cost and cost models can't use the absolute cost with high accuracy. It's only directionally, it's only directional, right? And then finally, we can't, there are these things we just don't know right in tunes, including innovations in technology. This, this particular report was generated a few years ago and is in the process of being updated. So I just want to create some visibility here. But that said, that should not prevent you from or limit you from answer asking questions related to what I'm going to present to you. So what questions did we explore with our model? There are bucketed 3 here on the left. How much mRNA can you expect to make at a given scale? What is the distribution of cost at a given scale? And finally, for a given demand forecast, what should your facility look like? And I'll get and all that, what, what should your facility look like? Seems a little bit vague, but I'll dive into that and you'll see where we're going with that. So regarding the process assumptions, based on what I've shown you in that process train a few slides ago, it's 5.4g per liter as your IBT yield with a 36% downstream recovery for our production run and a .1 milligram per dose. These are the assumptions that we're going into. That's going to help elucidate the answering of these following three questions. So the first question, how much mRNA can you make per year per line at maximum capacity? Just to Orient you here, primary Y axis is in grams, secondary Y axis is in millions of doses. This X axis is your IBT volume in liter. So that's one 1050 and 200 liter scale. And this pink line at the top is going to be your doses per year. And then this purple box or your grams per or your grams per year. The key the, the, the simple take away of here is, is is it should jump out to you immediately is that you don't need a huge reactor to get a lot of mRNA out of your system. So for example, a one liter bend scale can give you about 2,000,000 doses, 2 million doses of mRNA based on what we're seeing here. And, and this is based on the capacity assumptions here, 2 batches per week, 40 manufacturing weeks per year with no losses due to testing. For those of you in the audience that are doing the math, theoretically you can do 10 one liter, 10 one liter scale reactors to increase the capacity of this. You could even do 510 liter reactors to increase the capacity. But the point is for what you put in, you get a lot out and 2,000,000 doses is quite a bit at the extreme end. 311 million doses is not the cover N cover all of the United States from a simple 200 liter reactor. But but because just because that's the simple answer, that does not mean that's the correct answer, right? And we're going to walk through that very shortly. So what are the, what are the distribution of costs at these various scales? Just to Orient you, this is the primary Y axis, U.S. dollars per dose, secondary Y axis installed capital of millions of dollars in U.S. dollars. And here we have the scales at 11050 and 200 liters, right? The assumptions are the same. And this is our legend. As I walk you through this, the first thing you'll notice is that I'll, which I'll highlight is the cost of goods decrease as the dose, the doses increase. And so that means as highlighted here from 1.5 million all the way to 311 million doses, you're seeing the cost to produce that begins to go down as you would expect. And the second element here, there's an increase and cap, there's an increase in costs from one liter to 10 liter, one liter bench to 10 liter floor mixer. And that's actually just highlighting the costs associated with moving, working with a bench scale, which some of you may be currently working on. But as you start to move into larger and larger scales, you have to now start to account for floor space and other things related to that. And so that's actually why this pink line jumps up to approximately 20 million, again, a model, it's directionally correct. Just expect that your costs will go up as you make that transition. And finally, what I'll highlight here, you'll notice this blue box which I mentioned was going to be a lot of your reagents, including the enzymes and DNTPS. That is actually constantly always part of your cost and start to dominate most of your cost as you move to the higher scales, particularly for the 200 liter scale. Something I'll note just in case you're wondering if I'm kept comparing the same amount of effort, it's each one of these have 80 batches. So I think this is something to keep in mind in terms of when you're looking at the distribution of cost, particularly in particular for your material cost for this type of system. How can we? And so the next two questions I'll address here, how can we meet different forecast demands and how many batches and what sizes should they be? And so this is a standard curve to help address these three demand. And I'm going to just jump this here. The three demand scenarios explored, OK, these, these the both the Y&X axis are, are in the log scale and the, and the primary Y axis here total IBT volume needed. And then the X axis forecasted demand in grams. And you can see there's three different demand scenarios explored at 1 to 2200 to 401 kilogram. And we're going to use this framework to help explore these questions a bit deeper and make some have some ask them simple answers, right. Anyway, OK, so in the first one here for low forecast demand, that's the lowest constant, lowest gram amount of mRNA consider batches one to 10 liters of scale. And so this is the chart that I showed on the previous slide. These are your pie graphs showing you the distribution of costs. A quick, quick, your quick, your eye will notice a quick change in the colors from the purple and that's the the install capital showing the increase in cost that I've shown that was shown previously. And so this particular table, the batch slide showing batch size showing one liter versus 10 liter, 6 batches versus one for a different kind of output, which makes sense. Something I want to call your attention here is the capacity utilization. It's basically it's your actual process output divided by your maximum capacity throughput. So you're what you actually got versus what you can get in an ideal situation. And shown here, it's about 6% for the one liter and .7% for 10 liters. So this should jump out to you as why this is, but I'll walk you out. I'll explain very quickly why that is. At 6% capacity utilization, there's a $28.17 cost per goods for 100 microgram dose. The reason why your cost go up is that there's no free on you. There's no free space in bioprocessing. So if you have facility or if you have equipment that you're under utilizing utilizing, you're still paying for it. So as a result, your cost of goods go up in this regard, and that's highlighted there. So for a medium forecast demand, we're saying to consider maximizing capacity utilization at smaller scales. And so this is the intermediate on this graph. There are 4 volumes that we're looking at. And a quick, a quick glance at this pie chart, you'll see a transition of two primary colors that which I like to highlight the green are the consumables. So that's going to be your single use, your bags, chromatography resins and things like that. And then also the change of your materials. And so if you go from left to right, as you're, as you start to produce more and more, you're actually maximizing the utilization of those materials in green. And so that takes less, less and less of your cost burden within this model. However, your material cost goes up because you still need to buy reagents, your buffers, your enzymes. You can't reuse enzymes obviously, and DNTPS and so. So taking a look at this chart, you can see that we're looking at all of the the batch sizes. You can see at the low smaller scales, you're running more batches to get a certain level of productivity. Comparing the one liter versus the 10 liter, you'll see the increase in capital cost. However, I want to highlight the capacity utilization. Like I said before, there's no free space. However, because you're producing a similar amount of output, you actually come up a little bit cheaper in your total cost of goods at per 100 gram dose. So basically it's actually cheaper to run 13 lines versus 65 lines for the same productivity output for a cheaper drug when you move to the 50 liter versus the 200 liters. I know that the output is vastly is a little bit different here in terms of grams. However, I want to point to the utilization differences, right? And see, you can see at the 200 liters you're, even though it's easy and convenient to do a 200 liter scale, However, it's not the best use of your efforts and investment. You're only using point 1% of that capacity to produce a drug that's going to cost you $7.46. And this is the most expensive on this chart. Remember, there's no free space or there's no free unused space. Everything costs and so and so, and I'm not trying to suggest the correct answer, but within this model, within this table, you would see that this 50 liter scale seems to be ideal in the sense that it's giving you about $20 million versus the 10 liters for $20 million. You're getting the best bang for your buck for for lack of a better term, you're getting 3% capacity utilization, probably the cheapest cost of goods for your 100 micrograms of drug and you're running fewer batches at a smaller scale. So now for a high forecast demand. And so this is a, this is a nice one as I like this one because you actually normalize the output in kilograms of mRNA and they're saying here, they're actually, we're being LED here, right, a 50 liter scale process to optimize flexibility and utilization. So we're at the tail end of our curve. These are the three scales that we're looking at 10:50 and 200 liters. 1 liters clearly is not practical for doing 1.5 kilograms of mRNA. At the smaller scale, you can see it, 10 liters, you're running 80 batches versus 4 batches at the 200 liters to get the same output. The install capital, the cost associated with this are not appreciatively different, I would say, even though the difference between 26,000,000 and 20 million is $6 million. So yes, that's a real difference. However, capacity utilization is the thing I want to draw your attention to, right? Because you can do it in one step. That may not be always the cost effective thing to do. And especially when you're working at smaller scales, which is not the purpose of this particular thing, you start to consider what's the impact and your bottom line in terms of what you invest and what you get out. As you move from the 10 liter scale for this higher output, your drugs cost about 5 point five, $5.56 for your cost of goods. It's because you're running 80 batches at the, at this scale, you're running 4 batches and the drug actually comes, actually comes out to be a little bit cheaper. However, however, I will say, however, your installed capital is much higher because again, you're not using all of the capacity or potential capacity of this particular system. So I know that may have been a little fast, but hopefully that was clear and you were able to follow along. Something I would like to leave you here is never too early to start considering the impact of your costs. There is a follow up study coming up with regard to smaller scales for this that is in development. So I look forward to getting the opportunity to present that. But it's never too early to determine your forecast demand for your mRNA, especially for the target market that you're looking to the that you're like you're looking to aim for. It may be different for vaccine and the pandemic situation, but clearly it'll be different for cancer and some of the other ones. Need to assess the impact of the number of lines, batch size and the number of batches, which has been alluded to here in this presentation. And I'll leave with this last point is that you need to plan your their facility for flexibility, but optimize for capacity at whatever scale that you're working on, whether it's lab, excuse me, bench top or an expanded situation. So hopefully that was clear. I see Jess's online, so I'm finished. This is my last slide. I think there's a thank you slide with my picture on it. But yeah, we can pause here. Thank you. Awesome. Thank you so much, Oliver for your insights on this very popular and important topic. So we have a couple minutes left before we have to go to our last presenter, but I do want to remind the audience that if they have any final questions for Oliver to please submit them now using the Q&A widget on your screen. So we do have a question, Oliver. And the first question is, does this model fit for non vaccine production in front of these other targets? Oh, so that's a, that's a, that's an interesting question. So I think that when it was published, I don't think that was the intention. So it was very focused on the very much so focused on coming out of the pandemic and what was available. Because it is a model, you theoretically can apply it to any therapeutic. And so I would call it agnostic. However, I would, I would say, I would hold, I would hold off on making too many assumptions here. So wait for, I would say wait, hold on, wait for an update. But if I were doing this, if I needed somewhere to start, I would. I would use it as a starting point, right? Hopefully that helped. Great, great. And another question, any ideas on how or if facility automation impact this model? Yeah. So I think the easy one was earlier in the slide I show you that the downstream recovery rate was at 36%, which is abysmal. So I would say automation would probably improve on the efficiencies in your recovery and improving recovery would be theoretically reduce the cost of goods in overall production. So now you can get more out of a smaller space. So yeah, that hopefully that helps. Great. And one final question for today before we move to our final presenter is does this model change for a multi modal facility? I would say no because I think you could use it. You could. I would say no in quotation marks because it can give you a scenario where you can plan your campaigns throughout the year. So you can start. You can run maybe a 50 liter reactor or you can run maybe 5-10 liter reactors. And so you can plan your facility as well. And so you can stop your campaign and pick up another one and then resume. So your costs are going to be fixed as it relates to your, your campaign and your process. So maybe it'll help you streamline and plan. So I think it can be applied, but that's not the attention. But yeah, I believe the kid could though. Great. Thank you so much, Oliver, again for your time today and for your presentation. Thank you. OK. All right. OK, bye bye. Great. Bye, bye. And now moving on to our final presenter. David Bohanek is Senior Expert for Viral Vectors Americas within our company. Today, David will present on modeling the effects of process improvements on AAV costs. David, welcome to the symposium. Please feel free to begin your presentation. Thanks so much, Jess. It's great to have the opportunity to speak with everyone today and I really appreciate it. You know, when I, when I think about the value of, of cost modeling for the production of new modalities, right, whether like mRNA, which which Oliver just just spoke about or, or in this case for AAV. One thing I kind of think about is, is that there's a little bit of a paradox, right? And and what I weigh is that on one hand. You typically don't know many of the details that you need to get accurate output until you're at a stage where your process and your manufacturing strategy are, are well defined. So it's a fairly late in, in clinical development. But, but on the other hand, you know the time when the insights from such a model could be the most impactful, right? The time when you can get the changes that lead to, to big reductions in costs and, and when you can really do things to your process to, to, to and make it, you know, more cost effective is at a much earlier stage. And so, you know, what I want to do today is, is show a few case studies looking at, at the types of, of insights that we can get from, from the cost of goods modeling for AV production. And show some things that might not be entirely obvious, but would be valuable to understand when you're still at that that early stage and able to define your process and really try to prioritize your, your development off efforts. So the intent is really to show that even with what I think Oliver referred to as like imperfect models, we can still get valuable and actionable insights from these types of models. And so if I can ask the audience here to think about gene therapies and the types of headlines you see, what's the biggest challenge that usually comes up? And it's, it's, it's typically the, the price, right? It seems like there's, there's constantly headlines about, you know, a new drug becoming a new gene therapy, becoming the world's most expensive drug, or how the cases are limiting patient access or, or, or the prices are so high that that the commercial viability is. And I realized that the price of these therapies is, is not the same thing as as manufacturing costs. And there are a number of reasons why the prices are so high. So I'm not trying to oversimplify things and imply that, that the cost of goods is the primary determinant for the prices, but I do, I do think it's, it's fair to emphasize that developers are very aware of this challenge and that a lot of attention is paid to it in that there is real pressure on the teams who are, are responsible for putting together the manufacturing processes to, to keep this in mind and to, to really drive the costs to, to, to, to, to lower to lower levels. And there are reasons why, you know, manufacturing AAP gene therapies is, is very expensive, right? And one of these reasons is, is, you know, intrinsic to, to how the types of therapies that are being pursued, which is that there aren't very many doses being manufactured or that need to be manufactured. So this this small number of doses means that you can't necessarily realize the economies of scale that you would otherwise. And so this is due to the fact that in many cases these therapies have have targeted rare or ultra rare indications. And it's also related to the fact that these are well, you know, I have a more curative nature like that, that these are not treatments that patients are going to receive month after month indefinitely, but that they have a, a, a much more durable effect that that the patients don't need to be re dosed, at least within, you know, the foreseeable future. The, the other factor is that the, these are, this is a someone newer modality and that many companies the, the, the processes are fairly inefficient, right? That many companies are starting out at the point where they don't have a template that they, they have already established that they're using technologies that in some cases haven't really been purpose built for AAV manufacturing. So they might be borrowing technologies from, from, you know, technologies that might be used for manufacturing monoclonal antibodies or other biologics. And then additionally, there there are really significant challenges that exist in trying to scale up these, these processes, particularly in the in the upstream space, where if if you take a process that might be at, at a scale of a few 100 liters and scale it up to a few 1000 liters, the the efficiency can can drop off pretty significantly that there's, there's challenges with with how the transfection steps, for example, or scaled up. And, and on top of all that, in many cases, there really isn't much time available for process development. You know, many of these therapies have expedited regulatory pathways, which means that many of the activities that would be typically done and occur sequentially in a very well established cadence could be happening all at once. So you have this kind of dual challenge of trying to do something that's new, right, to develop a new process for which there isn't a huge existing body of work out there to reference and you're trying to do it with less time. And so that's really part of how we frame this project, right, is to recognize that with the limited time and resources available that there's really this need to be able to, to determine what the impact is for, for improvements to, to the process, right? If, if you're trying to evaluate, you know, what happens if we use a different upstream platform, what happens if we adapt the different technology for, for, for the harvest step and so forth. You know, the, the benefits in some cases may be related to the, the product itself and in the likelihood of clinical success, the quality of the product and so forth. It may be related to fitting into a certain facility. But really for, for this, this presentation, I want to set it up with, with the framework that specifically does it in the context of, of trying to lower and, and reduce the cost of goods. And So what what I'll do is, is step through three different scenarios that that you can see described here. And they describe situations that might reduce the cost of goods compared to a baseline process. And the intent here is not to go into too technical detail in terms of what types of steps could be taken to realize these benefits, right? For the first scenario where we talk about increasing the tighter of AAV and the bioreactor, there's multiple ways that can be done, right? And I'm not going to go into the detail of whether this is some cell line engineering or this is due to the, the optimization of the transaction step or, or the, the cell culture media optimization of those types of things. Just to just recognize that all of those those activities are really done with this one goal in, in, in mind, right, with the intent of increasing the the tighter. And so the question is what impact could that potentially have on the cost of goods if if you're successful in that? So our process and cost modeling was done using Biosol software. This is a commercially available software. It's I think similar to the approach that Oliver described and we covered the process from the upstream, you know, where we have the, the C train as, as the starting point all the way through the production of, of bulk drug substance. So final filling and, and some of the QC tests were not within the scope of, of the model that we'll be discussing here. And the model was done with within the, the framework of, of considering a developer who wants to own their own manufacturing process. So a facility dedicated to this, this AAV product in the first scenario, which which I, I alluded to is, is to look at what happens if we cannot increase the extreme tighter, increase the tighter by like a factor of 2 or 5 or 10. And, and you know that, that could mean that you can make 2 or 5 or 10 times more of the, of the, of the virus and, and that many more doses. But, but the reality is just because you increase the tighter that that doesn't really change the, the patient demand, right? You're still trying to make the same number of doses regardless of, of what our, our titer is. And so the real, you know, benefit could be that because we have the higher titers that the upstream process that the, the, the bioreactor size could be smaller. And so that's, you know that that does lead to cost reductions because you would have smaller equipment, you would use less cell culture media and other upstream chemicals. And, and as you can see here, the, the bioreactor volume would decrease with, with the inverse of the titer, right? That seems very intuitive, I would say. But when we look at the at the manufacturing costs, right, on the other hand, which are shown in blue, they do not continue to, to decrease proportion proportionally. They kind of level off. And you can see that at a certain point in this example, you don't really get as much a return as as the tighter increases. And the reason for this is that while the upstream costs continue to decrease with with the increase in the tighter, the key downstream costs for each batch change very little, right. The the chromatography resins, for example, we assume that the binding capacities were largely independent of the titer and that a certain amount of AAV is bound to a certain volume of the resin. And so the volume and also the volume that you elute off of the capture column doesn't change just because you have a higher titer in the upstream process. So any of the steps downstream of that column will you know, be at essentially the same as as they were in, in, in the lower tighter cases. And another way you could look at it and and say, well, maybe instead of decreasing the bioreactor volume, what if we keep this the the volume constant and instead just manufacture fewer batches, right. So maybe if we had a facility that is is fully optimized, are not fully optimized, fully utilized, right, where we're have a a small volume and we're manufacturing or we in this case we have a smaller tighter and we need to manufacture 41 batches beer. What happens as we increase the tighter and and we need make fewer and fewer and fewer batches. And so since so many of the, the consumables are single use, right, that can have a, a more significant effect in terms of lowering the cost compared to, to the, the smaller, the smaller volume because, because you would use less of all those consumables, right? Not just for, you know, the upstream process, but, but for the downstream process as well. So the, the second scenario is to look at what happens if in the upstream process you can make fewer empty capsids, right? What is, what is the benefit of that? And I think sometimes we can see with, with some companies, there's, there's a little bit of a disconnect between the upstream and downstream PD teams where, you know, from the upstream point of view, the question might be why would we even want to bother, you know, dedicating resources to this, right? Because the downstream process is going to enrich the AV to, to enrich the level of full capsids anyways. And I think there's two potential issues with this line of thinking, right? One, you know, the first of which isn't really part of this analysis, but it's, it's that the, if the starting level of of empty capsids is too high, it may be impossible to reach as high level as enrichment is needed with with kind of the, the available chromatography steps. And then the second issue, which which I do want to show here is that the enrichment doesn't really happen until the near the end of the process. So this is at at what you can see shown here as the ion exchange, the IEX chromatography step so. So what happens is is both chromatography steps end up binding both empty and full AAD capsids and so they are sized accordingly. So if there are fewer empty capsids at the harvest than the cost of these chromatography chromatography steps can be reduced because you won't have to bind those empty capsids and you could have smaller columns and and use less rising. And so similar to what we saw, you know, in, in scenario one, there are, there are definitely benefits to, to making this improvement in terms of lowering the cost, but but they level off as you transition to conditions where most of the AAV you're binding is, is full of capsids. Is is full capsids, right. Once you get above about 50% full capsids the the the cost tended to flatten out. However, if, if your upstream process can produce AAV where maybe you're already at the therapeutic therapeutically appropriate level, then in principle you may be able to eliminate this step. And and so you realize the benefits of of simplifying the process and A and a greater cost reduction if if you can completely remove that, that anion exchange chromatography step. In the third scenario that I wanted to to focus on is, is to look at what happens if we can improve the recovery in the in the downstream process. So the way that the model is set up is again similar to what Oliver showed with, with the mRNA where each one of these steps, there is some yield loss of the, the product. It may be a 10% loss or 20% loss or what have you throughout, throughout the entire process. And so we ran the cost model in the process model, we gradually increased the recovery to these various steps and, and saw what, what was the impact. And by increasing the downstream recovery, you know, it's, it's important to realize that that you, you can really reduce the costs of a whole process, including the upstream, right? If, if you can not lose as much of the virus during purification, then you don't need to produce as much in, in the upstream process. However, you know, even in this scenario, we see a certain level of, of diminishing returns, right? Where even if you can increase the recovery by a factor of 5. And in this case, I'm showing, you know, if, if you're starting at A at a 20% recovery and you get all the way up to like a theoretically 100% recovery, right. Even if you can achieve that level of improvement, the cost per dose only decreased in this example by, by a factor of 2. And so for this example, this is is where we're looking at at a rare disease where there might only be I think it was like 440 doses per year that that's, that's, that are being manufactured. And the, the reason that we, we have this, this kind of limited return on, on that increase in, in the recovery is that, you know, for these conditions, a significant fraction of the costs are fixed, meaning that if they're either the capital costs associated with the equipment in the facility or the other, you know, non capital expenses that are are fixed but, and, and associated with the facility. So if we if we do this same exercise, but instead we look at what happens if we have a higher demand scenario where maybe instead of 400 doses we're looking at 4000 doses per year. Then all of a sudden the fixed costs become, you know, a much smaller fraction of of the overall costs. And then the benefits you can realize from making this same improvement of of 20% to 100% in the recovery, it becomes, you know, 4 fold increase, decrease in, in the cost as opposed to, to the the two fold decrease. So just depending on, on what you know, what the situation is in terms of the, you know, the demand for the, the therapy can have a significant impact on what, what benefits you might see from from these process improvements. And, and as we kind of went through these scenarios, as we, we looked separately at what might happen from upstream and downstream improvements and saw there's limitations to both approaches. And so there's, there's this kind of natural question is what if we do both, right? What if we do them both at the same time? And what you can see is that you can get a much more significant improvement in the in the cost, right? A reduction in the cost. If you can do, you know, more modest improvements in both the tighter and the recovery at the same time, then you would achieve, even if you can make very dramatic improvements in either one like that, that increasing the recovery by or the the harvest tighter. You know, to to either extreme of this graph is not going to give you the same kind of benefits that you can by going part way through, you know, by making a, you know, a increasingly, in this case, maybe the recovery to 30 or 40% in the tighter to to 1 E 11. So you know, as you're developing your process and, and you're trying to to decide, you know, which which platform to use and, and what your manufacturing strategy will focus your efforts. And it's really important to have some sort of of tool to be able to understand and, and predict what these things might mean to your, to your manufacturing costs and to have some kind of tool that, that you can identify what the biggest factors could be. And, and even if it is an imperfect model, and it definitely will be imperfect and, and maybe even, you know, highly imperfect, if, if that means anything, it's important to consider, you know, what your options are before things start getting locked in during the clinical phases, right? Because the alternative is to wait too long before you start thinking about it and ending up at a point where you can no longer make the changes that'll that'll really make a difference. So I wanna thank everybody for their time and attention. And I'd I'd be happy to take any any questions at this point. Thank you very much, David. That was a great presentation. And as David has just mentioned, it is now time for Q&A. So if any of you in the audience have any final questions for David, please submit them now using the Q&A widget on your screen. So one question for you, David. How can we model the costs at the start of the clinical trials when we don't know what the final dosage will be yet? Yeah, I mean, it's, it's, that's a fair question, right? Like if you don't know the dosage, how can you, how can you and how can you predict the costs? And I, I think it's, you know, another way to look at it is, you know, what uncertainty to does not knowing the dosage right at that early stage have on, on your ability to, to, to predict the cost, right? Because the, the cost will be certainly an important factor right in, in, in the vibe, the, the kind of the, you know, the viability from a, from a commercial standpoint. And so, so I, I think with what having a, a good model enables you to do is actually run it on the different scenarios that, that the, the dosing may end up at, right. If, if in your phase one trial you're looking at, at a certain range or you think it could be wider than, than a certain range, But you can, you can run the model fairly easily with all of these different dosages and, and, and see, you know what, what are the implications? Because it, it, it, you know, there's, if, if your dosing is, is five times higher, it's, it's, it's likely right that the costs are going to be higher, but maybe not five times higher because you might have a, a larger scale and, and, and benefits like that. Awesome, another question, what was the dosage used for these examples? Yeah. So, so I think everything I think it's on one of these slides earlier. So everything that we had shown was with the same dosage and that sometimes we kind of played around with with a number of doses that were that were needed. But yeah, so the dosing was was 3 * 10 to the 14th VGS. So that's per patient, that's not per per kilogram or anything like that. I think that's, that's an important point to, to consider, right? Because with AAV the, the dosing can vary pretty significantly, right? That, that I think for, for even the commercially approved therapies, there's like a 5000 or 10,000 full difference in terms of, of what the dosing levels are. And, and obviously that can have a a dramatic impact on on costs. Great. And I think we have time for one more question today. How did you select 95% for the target of percent full capsids? Yeah. I, I, I don't think that was meant to imply. Let me go to the right slide here. Yeah, I think they're talking about this one here, right? I, I don't think this was meant to imply that 95% is, is is is a target, right? I, I, I think it, I mean, obviously it has to be somewhere about 50%, but, but I, I don't wanna try to predict, you know, what, what, what is, is required or possible, right? I think I think both are fair questions from a regulatory standpoint that that there's not necessarily a magic number and, and you know, from a process standpoint, maybe reaching 95% is not not necessarily achievable all the time. But, but I think it was just more to show that, you know, the, the trends, right, that that further improvements in, in the upstream process are, are you're not getting a return unless you can really remove that step. So I think you'd like likewise see a similar benefit if it was, if it was 70% for example, and that was where the where you, you decided that you, you no longer needed the enrichment. Great. Well, thank you so much again, David. And that's just about all the time we have for questions today, everyone. And that's it for this year's symposium. We hope you've enjoyed this virtual event and we kindly ask that you share feedback with us today using the survey that will pop up on your screen shortly. So thank you everyone. Again, thank you to our experts and presenters for their amazing presentations and for all the engagement. Have a great remainder of your day. _1733395200076

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