Circio Holding ASA (CRNA) Earnings Call Transcript & Summary

Good morning. Welcome to Circio. We are live from our facilities in Stockholm today. My name is Erik Digman Wiklund, I'm the CEO at Circio. And together with me today, I have our Head of Research, Dr. Thomas Hansen. Our plan is to go through with you an update on our R&D strategy as well as data we have generated to date and plans going forward. So the presenters will be myself and Thomas. And for those of you who don't know, we had a history together. We did our PhDs together back in -- the early 2000s in a lab in Denmark and during this period, we actually co-discovered Circular RNA and published early work in the Circular RNAs based. And it's great to be back together in Circio and continue to develop novel Circular RNA therapeutics. So Circular RNA is emerging as probably the most promising class of novel RNA therapeutics following on the success of the mRNAs. And the reason why there is so much buzz around circular RNA is that circular RNAs are more stable. They are more durable than mRNA and also they are less immunogenic. And this durability and immunogenicity issues have been what's held back mRNA development for a long time. The core problem of mRNA is that they get degraded by exonucleases. These are enzymes inside of the cell that eat up RNAs. And you can see it drawn here on the cartoon by these small Pac-Mans. They eat the RNA from the end. A circular RNA lacks a free end. So there's nothing for these exonuclease enzyme to latch on to and therefore, the circular RNA is resistant to the standard way of RNA degradation inside of the cell. And this means the durability is vastly enhanced. So you get this advantage of an improved durability. With that, you can get more durable protein expression. Also you can engineer circular RNAs to be more efficient than protein expression and mRNA. So you get not only more durable expression but higher expression. And this is expected to be a very significant advantage. And therefore, many people in the field believe that over time, Circular RNA will replace linear mRNA as the preferred format for long RNA therapeutics. At Circio, we're taking a different approach. When we started this work, Thomas and I sat down and discussed how we can best approach the field of Circular RNA. The other players in this space are all doing effectively the same as what the BioNTech and Moderna did with mRNA. They're making a synthetic RNA in the lab. They package these in what's called -- were called LNPs, lipid nanoparticles, and then they deliver the LNP packaged RNAs for vaccines or for delivery to the laboratory to express that protein. What we observed is that no one had really taken the approach of making a vector based expression on circular RNA. So what we are doing, when we're doing it this way is we're building DNA constructs that you can bring into the cell and then they carry the recipe for the cell to generate their own circular RNAs. So our product is the DNA-based system, can be a DNA or a virus that transports the DNA carrying the instructions for circular RNA biogenesis inside of the cell. So then, once this is delivered to the patient, you will get circular RNA production and then subsequent protein expression. These are several advantages, and I'll try to explain that on the schematic here. So on this slide now, we're looking at cell and then inside of the cell, there is a nucleus, in the nucleus is where the DNA is. When you use the synthetic RNA approach, either in circular RNA or mRNA, these are LNP packaged. So the LNP packaged RNAs, they enter the cell, that was called endocytosis and then through these endosomes, they get into the cell. However, this process is very inefficient. Probably less than 5%, I think the estimates now are 2% to 3% are actually releasing to the cell. More than 95% of the RNA that gets absorbed is where it gets degraded. So it's a really inefficient way of getting circular RNA into the cell and then these copies that are there will then make proteins. Now the advantage of taking our approach is that we come in with our -- what we call [ circVec, ] (04:28) which is our DNA technology, either in the form of the virus or DNA. This gets transported into the cell, then it makes it's way to the nucleus. And once it's in the nucleus, you then have a stable DNA presence, carrying the instructions for circular RNA biogenesis. And 1 copy will make many more copies of RNA. So from just having a single copy inside the cell, you will make a bunch of circular RNAs that then will emanate from the nucleus. They will be natural to the cell and they get exported into the cytoplasm where they can make protein. The big advantage is doing it this way, we have higher concentration inside of the cell. We will [ omit ] (05:04) this problem of a poor release of the circular RNA which you get with the LNP packaged circular RNAs. And also it's been shown that intracellularly generated circular RNAs are even more durable. So the exogenous circular RNAs with the -- on the left side, typically have a half-life that is 3x to 5x better than mRNA. With our intracellularly generated circular RNAs have half-life in our hands is about 15x better. And that's because it's produced inside of the cell. It gets certain chemical marks, and this improves the stability. So we think our system is probably going to be generating more stable and durable circular RNAs. This will translate into higher protein expression and more durable protein expression. Here, we've done a bioinformatic simulation based on our data to date, showing the comparison of vector expressing mRNA versus a vector expressing a circular RNA. The blue 1 is mRNA and the red line is circular RNA. So if you come in with a vector to the cell, you can see with the mRNA, it's produced relatively fast, but then it peaks early and then it will start dropping because the mRNAs are less durable. The circular RNA, it takes a little bit longer to generate. It's a more complicated process of biogenesis, but then once it keeps -- once it starts building up, it's more durable and you reach higher steady-state level. So it means you can get your higher levels, more durable levels. And this gives you what we say, larger area under the curve. The total amount of the protein you make is much higher. This is looking at the RNA level. On top of this, you can make circular RNAs better protein expression. We achieve up to 5x better protein expression from our circular RNA versus a mRNA and this need to add that on top of this, you have now a system that can give you 10x, maybe 15x better protein expression that's also is more durable versus mRNA. And this is potentially a massive advantage for any DNA-based or virus-based therapeutic in the future. The next question is so what type of vector do you use? Well, we take 2 approaches. We are looking at viral vectors and we're looking at synthetic DNA vectors. If we start with the virus approach. So viruses have evolved to be very efficient and delivering DNA into the nucleus of a cell. It's a natural way of getting your DNA into the cell. So it's maybe the simplest, lowest technical hurdle approach to get our circVec -- circular RNA instructions into the cell nucleus. We are focusing on 2 different virus types. AAV, this is a type of virus that is typically used for gene therapy. It has advantages in terms of being very with low -- have low immunogenicity and it's very durable. So it's good for expressing a protein over a long period of time. The other approach is adenovirus. This comes from our [ ONCOS-102 ] program for those who remember that product. Here, we can adapt our oncovirus to make circular RNA. And adenovirus has certain different features, it's much more immunogenic. So this is suitable for vaccines, and it can also be used in cancer. So these are the 2 viruses we are developing, carrying our circVec and so to make Circular RNA. The disadvantage of using viruses is that because they are immunogenic, the patient gets an immune response to the virus over time, and it makes repeat dosing difficult. So if you want to do gene therapy, most gene therapies to date that are AAV-based can only be dose once. So this is a drawback on gene therapy today. Synthetic DNA has the potential to solve this problem. If you can use a synthetic DNA, you can potentially avoid this immune response and you can read those. So going in this angle, you have something that is simpler, it's simple to manufacture, and it can be repeat dose, which would be a great advantage over Circular RNA, sorry -- over and over and finally deliver gene therapy. Now the drawback with synthetic DNA is that cells have defense mechanisms to prevent this from happening to sense for DNA and break it down. And therefore, you need the delivery tool to get your synthetic DNA into the nucleus of the cell and not just be integrated. And this is still a challenge in the field. So I think most people believe that in, say, the next 10 or 20 years, synthetic DNA will be the format that is preferred for gene therapy. Still, the chemistry and technology to get it effectively delivered in patients remains to be solved. And therefore, we believe it's wise to pursue both avenues. Virus technically more straightforward, well established, manufacturing is there. Second step, synthetic DNA, technically more challenging, high risk, but also high reward and most expected to be in the future. We announced yesterday a collaboration with a Korean company called Neoregen. This is precisely to enable us to do this delivery of synthetic DNA vectors. So we are working on 2 different formats of novel DNA vectors. We plan to deploy these for gene therapy and vaccines, but we need some chemistry to get them efficiently delivered into the cell, and this is what Neoregen offers. So this is a simple research arrangement to begin with. Neoregen will adapt their peptides that they are developing to match with our circVec synthetic DNA vectors. We will then combine the 2. And then in our labs, we're going to test whether this can be used to efficiently transfer DNA circVec into the cell nucleus. So this point is a mutual 50-50-type preclinical collaboration, and it gives us access to an important potential technology to deliver the synthetic DNA vectors in the future. How are we going to deploy this? Well, the current priorities we are looking at is rare disease and vaccines. So rare diseases are genetic disorders where you have a missing protein and you can use gene therapy to replace that protein. And we see this as a major long-term potential of our technology. The second avenue we're pursuing is vaccines. Circio using our adenovirus to begin with to generate what we believe can be a single-dose vaccine format. If this works, we will have a platform that is highly potent and has a big advantage in that it doesn't need repeat dosing. As you recall, we have also a cancer program, and this may be is what we've pursued most actively in the past. And we still have several ideas we are working on in the oncology space. But for now, this is being deprioritized and the lead project internally are in the rare disease and vaccine space. First step in rare disease gene therapy is to show that we can improve on existing AAV gene therapy. So I mentioned before, AAV is a vector. AAV is the standard vector for gene therapy today, almost all of the approved gene therapies are AAV-based. The disadvantage of AAV is that you need to get really high doses, and these high doses, they lead to toxicity for the patients, which is a major challenge. And also they really drive up cost, [indiscernible] some of these gene therapies come at the very high price tags, several million dollars in some cases. we anticipate that by switching from mRNA-based AAV expression to circRNA-based AAV expression, as I showed you before, we can drive a 10x to 15x improved protein expression, and it will be even more durable. If this actually works, it would mean that you can reduce the dosing of AAV-based therapy simply from switching to circRNA instead of mRNA-based expression cassettes. If this can be demonstrated, you could drive much improved safety. You can reduce the dosing and you can reduce the cost. This would be massive advantages in AAV gene therapy. And we think this is the quickest route to demonstrate the proof-of-concept and an advantage of our approach. And if you can show it works in this setting, I think it's likely that anyone doing any DNA-based therapeutic are going to want to switch to a Circular RNA-based expression system rather than mRNA in the future simply due to this superiority. Where can we deploy this? Well, we've done extensive in our screen looking for suitable genetic disorders where we think our technology fits. And we've had several input criteria for this filtering process such as, which tissues do the disease manifests itself. Is the protein suitable for expression with our technology, how many patients have the disease, what are the symptoms, et cetera, and how large is the gene that you need to deliver. And also the competitive situation. So after this analysis, we now arrived at a shortlist of 6 candidates that we are exploring in more detail and we picked the top candidates. The lead disease that we are planning to develop a circVec candidate for is called alpha-1 antitrypsin deficiency or AATD for short. In this disease, the AAT protein is missing. This is a protein that's expressed in the liver and secreted into the blood stream. And AAT is primarily active in the lung. If you lack functional AAT you get inflammation and lung symptoms. Over time, these can be very serious. You get emphysema, developing chronic bronchitis, permanent inflammation in the lung. In parallel, you get problems in the liver. The mutant form of the protein accumulates in the liver causes protein deposits to form over time, these are toxic and cause cirrhosis, eventually cancer. And you have the disease where both the liver and lung is affected, and we have a problem both with a missing functional protein as well as accumulation of the mutant form. And this is something we can uniquely solve with our approach, because our circVec approach allows us both to remove the toxic protein as well as replace the functional protein. And Thomas will come back to this in his part of the presentation. No one else is doing this or have successfully done that so far. So we can potentially develop the first product to do what we call remove and replace. Remove the mutant form, replace the functional form using our circVec constructs. Currently, there is nothing approved for dealing with the liver associated AATD and there are only really inefficient technologies for the lung problem. So this is an area of high unmet medical need where we think circVec can provide a massive advantage for patients. Vaccines is the second program. Here, we're building on our adeno experience. We're making a first generation of non-replicating adenoviral vectors that then have our circVec inserts to make circular RNA and these circular RNAs will drive expression of the antigen that you're vaccinating against as well as additional immune response boosters. And this is the first generation that's been the first in-vivo experiments, and we're already at the process of developing second-generation products. The aim for vaccine concept is to build a preclinical proof-of-concept and then out license to a partner before entering the clinic. Rare disease, we're probably planning to take forward ourselves towards the clinic. So you can see rare disease in-house, vaccines, preclinical proof-of-concept and to do a partnering deal, hopefully, we can achieve that next year. We have also formed a collaboration in the vaccine space. In this case, it's with an academic lab at Washington University. This is a lab that is 1 of the world leaders in adenovirus developments. It's led by Professor David Curiel. And what we're doing here is developing a novel adenovirus-based concept for flu vaccination. This work will largely be done in the plant in Washington University, and it's about to start right now. So this means we'll get an active flu program going in the near future, managed externally. So that also means we don't spend as much resources ourselves internally. So with that, I hand over to Thomas to take you through some of the data that we have generated so far.

Good morning, and thanks for watching and thank you, Erik. I will try to brief you on the R&D development here at Circio. I will skip to this slide. And of course, I've been (18:02) [ starting technically seeing ] Erik on circRNA biology, been putting -- on this topic for a decade now and have a -- so a great deal of expertise, at least when it comes to the naturally occurring circRNA. So I could talk about this at length, but I'll try to be somewhat brief. So as you can see, at the top here. This is Molecular Biology 101, you have the conventional gene expression. So this is basically a piece of DNA from the genome, this contains exons and introns and if you slice these exons together, this will produce circRNA. That's the conventional way of gene expression. Occasionally, we have certain processes in our genome. We have these naturally forming circular RNA by a process called backsplicing. So this has been the objective of most of my academic research. But what is very interesting, and these were subsidiaries of [indiscernible]. So these critical elements just flanking the exon, as shown here, that's required and sufficient for this backsplicing. So that we can utilize to build our circVec. So the first approach we basically did was to try to get a good overview of what's naturally occurring in our -- in the human cells. So taking advantage of a lot of deep sequencing data sets, you can profile certain expression in tissues and cell lines. And what you can get here in this slide, especially circRNA expression and the corresponding sort of host gene mRNA expression. And from that, you can sort of derive high-express circRNA, that seems to have a very high efficient biogenesis rate as well. So from that, we basically -- in addition to trying to identify these critical features in the flanking inverted repeats where we have high expression circRNA that comes along with these elements in the flanking ingredients that enables the backsplicing process we could basically take out natural regions of our genome, put it into our little expression cassette and see whether we get circRNA expression. So that you'll see here, we tested a small subset of highly expressed naturally occurring circRNA and how do they perform in a sort of a vector system. At least 1 of them performed or outperformed all the other ones consistently. This is the 1 we referred to as L1. So that's basically a naturally occurring sequence that we build our circVec insert upon. So you can see it's much better than all the other ones we tested. So we believe we have a starting point here based on the best performing, naturally occurring circRNA taken from the human genome. And on the next slide here, we then build upon that and then conducting extensive research on how to optimize this sequence to enable first better biogenesis, more effective biogenesis, this is what you see out here. We have done extensive rational design optimization development, and this L1 is the 1 from [indiscernible]. So this is a naturally occurring sequence, but by doing different approaches, you can get up to almost up to 10x improvement in terms of biogenesis. All the optimization features has not worked as well as you can see here, but at least we have a setup that consistently outcompetes or outperforms the natural sequence. So we can do slightly better in nature by doing some rational design optimization steps. And maybe what's even more critical in terms of designing your circRNA specifically for protein expression, we actually developed and realized at an early time point that how you design this protein coding, as said is critical for protein yield. So this is so much systematic screen we've done, where we did different design rules. And as you can see, there's a subset of designs here from D2 to D7 that works quite effectively with D4, is the most effective design where, in contrast, there's other design rules that are completely blank in terms of protein expression. So if you have intensity here, that correlates with protein levels. So I think that's what we filed some of our early idea on basically what -- how to design your circRNA to enable high-yield protein expression, and that seems to be extremely critical to achieve the protein yield that we are getting from our circVec system. So that was a very -- a hallmark, a key data point going forward. So this is sort of the design that goes into what we are calling to circVec 1.0 cassette. And as you can see, when we try to compare what is the protein yield then for this first generation cassette compared to a conventional better expressing an mRNA-based cassette. And then you can actually see we get higher protein yield with the 1.0 system here. So we are already -- and this was at an early time point, and maybe to me, is slightly surprising, but we already on par or outcompeting conventional mRNA-based vector designs. Then what Erik also mentioned, the intrinsic benefit of using circRNA is basically the longevity of the RNA molecule. It's extremely stable. We have -- actually, it's stable to the extent that we have had technical issues measuring the half-life, but we have come up with an approach that actually gives us the half-life estimates with in this case, comes up to around 130 hours for the circRNA, and that's in contrast to 9-hour half-life for mRNA. So I think that's that pretty much aligns with what's in the literature, and we see then a 15x improvement in terms of half-life. So that also goes into that simulation. We showed you previously. And that, of course, translates to not only longer expression, but also accumulation of RNA over time. So it will translate into higher protein yield. And the data that we have so far is actually if you do a relatively short but a time course experiment shown here. You have circRNA levels at the early time point 48 hours after you introduced the vector system into cells. Those circRNA expression compared to mRNA due to the fact that the biogenesis is slightly more complex, it's a little slower. So this is also being optimized as we speak. But then the critical point here is if we move forward to 96 hours, there aren't any molecule accumulates due to the strong half-life, the mRNA declines. So in a long-term process, a long-term window, circRNA will prevail. So this we see consistently. What's also interesting is, this area [indiscernible]the protein yield. So this is RNA we measure here protein being measured despite the fact that we have lower circRNA levels at 48 hours here, we actually see higher protein yields. So you can actually -- sorry, we can actually design the circRNA on the translational rate outcompete mRNA translation due to these items that we insert in the circRNA cassette. And that seems to also accumulate over time. The mRNA declines here, we have a coating stability in addition to RNA stability. So here, there'll be some delay before we see this level of delta between circRNA and mRNA. But at least this is a consistent expression profile over time that we observed from our circVec system. And it's another sort of time course experiment where we also look at the ratio between circRNA and mRNA and what time it is goes to 144 hours. So this is 6 days after we introduce the vectors. Again, at the very early time point here 1 day after we introduce the vectors, it's a very slow -- not a very slow, it's a slow process for circRNA biogenesis, so it's below mRNA, but already after 48 hours in this experiment, we see on par expression comparing mRNA and circRNA and then it goes to above twice the yield using the circVec design. So this is again just we'll emphasize that this circVec 1.0 first generation cassette. So this is actually fits nicely with the simulation and what we would expect because you would expect some of the logistic curve, which is roughly what we get. So this will probably go [indiscernible] between 2x or 3x compared to mRNA in the system. So as we mentioned, we are developing this. One thing is the vaccine track that we are working on. And for a proof-of-concept, we have developed a number indicating in that markets, vector expressing the spike antigen that we all know from the COVID pandemic. Again, we see from the RNA level, mRNA-based expression is very high at the early time point in drugs, circRNA expression [indiscernible] early time point, but increases dramatically. We see probably the same from the protein levels, low levels at the circRNA after 48 hours, but then it accumulates quite dramatically and outcompetes the mRNA at 96 hours. So this is, again, the first generation that involves vector system that we are using, and this will be introduced into an in-vivo model very, very soon. So we are very excited to see how that will translate in terms of immunogenicity, but I'll come back to that. Finally, as in research, you consistently optimize your system. We do the same. So this is, of course, a never-ending process, but luckily, it's going in the right direction. So we started off here with some early data that we call circVec 0.1 version, so that's one of the pre-generation circVec, it didn't perform very well. The second point, all that I'm ensuring is so far, this is on the data and so far it's based on this cassette design. So this is a level of expression you guess on relative to this, just put to 1 in this bar chart here. And we've done a series of incremental improvements on that vector system. So now we recently sort of established the next paradigm for our cassette, which we call circVec 2.0, which roughly has a 10x -- up to a 10x increase in yield compared to the vector system that we're working on so far. So there's -- already we've come a long way. We have this vector system that we are very excited about to test in-vivo as well. So I think that looks very promising. But going forward, we will, of course, likely optimize this even further getting a 3.0 at some point hopefully with a similar x improvement. But for the in-vivo data, we have been working hard to generate this data package. We have been -- maybe the data so far has been a little technically variables. So we have not been able to reach any sort of solid conclusions when we benchmark to an mRNA based cassette, but what we at least have been able to conclude is that based on this 1.0 cassette, we can get circRNA biogenesis. We can get protein expression in our mouse model. So that's established. We can also do into tumor injection of replicating adenoviral vector that expresses a circRNA and we can also detect a circRNA expression, protein expression from that circRNA in the tumor. And we have also done a preliminary circVec vaccine experiment where we also got positive immunogenicity confirmed. But this is, as mentioned, down here, further optimal immunization. So unfortunately, required. We learn a lot from these early experiments, of course, from a scientific and ethical point of view. We want to set up the best possible design going forward in-vivo. But there's a lot of planned experiments for the time being. So there will be a critical readouts towards the end of the year on whole 3 -- at least on the biogenesis and protein expression of the [indiscernible] genes and on the vaccine that will generate more in-vivo data. So that sort of concludes the section on these highlights in terms of the R&D package that we have specifically also for the rare disease or alpha-1 antitrypsin. I think we have a very, very unique opportunity here with our circVec platform, as Erik mentioned, we have a removal case option for AATD. It has these 2 manifestations due to the lack of AAT expression, we have a lung manifestation. And due to this toxic accumulation of the mutant form you have a liver toxicity. So what we can basically do what this platform allows us to do is to, first of all, obviously use a circRNA to get high and durable expression of the functional AT protein, which likely could solve, treat the lung manifestation. In addition, we can design our vector that will actually allow us to remove specifically the mutant variant of this AAT and that will then alleviate this liver toxicity. So that's why we call this remove and replace. We replaced with the functional protein, and we removed the abnormal protein. So we hit 2 birds with 1 stone basically and treating the lung and the liver manifestation at the same time with 1 drug product. So the data that we have in-vitro so far is basically getting AAT expression from circVec. And in this case, it's also the 1.0 generation. This will be repeated now with the 2.0. But what we see consistently high levels of AT from mRNA, but it's dropping quite dramatically early on. So you can see these with the time course again. So circRNA starts off a little lower when it accumulates over time. So that's basically the expression profile that we get consistently using different payloads. And I think that's a promising readout for a long-term expression of AAT going forward. Then in addition, we can remove specifically the mutant AAT whereas some proprietary designs that we have on our vectors where we just see and expand where we missed that in the level of mutant AAT, and then we try different design slots, and we have 1 that specifically for what we call the [indiscernible] allele, and that seems to also be the only 1 responding in this experiment. So this is a very exciting technology to us. We are going to develop this even further to improve the yield and the knockdown specificity and efficiency but we are looking -- we are setting up in-vivo data as well to measure what is the general profile of AAT production from our circRNA vector compared to mRNA vector. So that's AATD. The summary here, I think we've come a long way. We've basically been working on this for maybe a little more than 1.5 years setting this up from strike. So it's a very time-consuming process to develop good science and basically what we've achieved, as I shared with you the circRNA [indiscernible] we have 10x biogenesis rate compared to the best design in nature. We believe -- we have this 15x extended half life compared to mRNA. And we have confirmed that we can express the circular RNA in in-vivo. So that's established. For the vector functionalities, we have shown -- sorry, we have shown that it works from a conventional DNA format. It works from viral-based format. So we believe it's vector agnostic approach, so we can basically plug and play into the vector system of choice there. But we will probably move forward with, as Erik mentioned, the different synthetic space, DNA formats as well as AV at least on the rare disease program. We have now an optimized circVec 2.0 and outperforms the 1.0 clinical impression. And we can express circRNA at least up to a 5kpm, until 5,000 nucleotides circRNA. So this -- we haven't attempted -- we have not attempted yet to go beyond that, but that at least works in the lab. So of course, we -- next step is to test the circVec 2.0 in multiple vectors types with in-vitro and in vivo. Our protein expression from the circRNA we get 3x to 5x enhanced protein expression to molecule compared to mRNA. We have validated this for several different protein payloads, including AAT, alpha-1 antitrypsin. And we also confirmed that it works when introduced into mice and we will, of course, also continue on establishing an in-vivo package for protein expression, both the durability and expression level. And then we can add in -- on top of that, I didn't touch so much upon this today, but we can add in other regulatory functionalities in the same vector system. So we can have a multifunctional cassette basically, that will [indiscernible] in addition to other functionality. So this we're also developing and working on to get that as effective as possible. So some of the readout that we expect going forward, in the rest of the year here, we have these 3 different vector formats that we're working on AAV is high. Relative to this where we will be testing the first vectors very soon, where we compare the circRNA-based expression from the AAV compare that to an mRNA. And of course, if that looks encouraging, we'll go directly to in-vivo studies as well for an AAV-based circVec format. Then we have 2 very interesting DNA formats that we'll be testing also throughout the end of the year here. So that's basically the same setup. Of course, for these DNA system, we need to identify delivery into sort of delivery enabling technologies, and we will probably testing the new region approach as well. So this would be highly available to some of these vector systems. So that will also be tested in-vitro first, as always, and then we'll go to in-vivo data afterwards. Lastly, for the experiment [indiscernible] As mentioned, we are setting up the COVID spike vaccine program, where we will inject mice with adenoviral vectors expecting a circRNA including spike protein and compare that to a similar vector for the expression spike from an mRNA vector. And then we will expect to get the readout of that towards the end of the year. So it's somewhat a lengthy protocol 6 to 8 weeks to evaluate the full potential of the immunogenesis, so it takes a while to meet out to finalize that study. In addition, which is maybe is a little quicker, this will be more expression to ability. So expressing reported setups such as the[indiscernible] to mice, you can track the expression, both the bio distribution and the expression profile over time. And here, we can actually utilize just synthetic DNA, the circVec 2.0 design and then see how that performs over time. And now utilizing different routes of administration and different delivery technologies. And similarly, we'll test specifically AT expression that you can pick up in the bloodstream. It's a secreted protein that they have and also have the possibility to track the expression over time in mice that has been -- that have been treated with the circVec 2.0 vector encoding AT and comparing that to an mRNA equivalent. So that brings me to basically the last slide. So we believe that we have a very unique position, not only in the circRNA field because we are probably the only significant players in the DNA format space where all the other players are synthesizing the circRNA in-vitro, but we're probably also the only circRNA player in rare disease space to our knowledge. And I think that gives us a very unique approach. I think what we have shown is that we get enhanced durability, enhanced protein expression from the circRNA and I think that then translates as Erik also mentioned into that we can actually reduce the dose level and reduce as a consequence. And that may actually solve some of the most critical issues currently with gene therapy going forward. So we believe, of course, in our technology, we think that going forward, the vector-based circRNA approach is probably going to outcompete mRNA based vector across for all DNA-based therapeutics in the future. Just as we believe for the synthetic RNA space, circRNAs will probably outcompete mRNA. And so for the applicability of synthetic RNA approach, this will probably be circRNA going forward and the capability of the DNA based approach might be [indiscernible] going forward. So with that, I'll -- well, thank you for listening. This is the last slide, and we will proceed with the Q&A.

Thank you, Thomas, and we've received some questions and we can move to tackle these. Let's see. So first 1 is typically, there is always interest and enthusiasm around getting data in patients and -- there's a question here relating to this. There seemingly are several delays in the new development. Can you comment on this? Do you want to start?

Yes. I mean, we can, of course, discuss whether we have delays or whether this is just a natural process of research. Of course, we would always hope to advance quicker, and we are working very hard to advance as quickly as we can. I think some of the things that may have been suboptimal is that some of our early design that we use for our reported -- the reported team that we focused on works extremely well in-vitro, did a lot of work on that, turns out in-vivo, it was sort of a suboptimal choice of payload. So that is not -- so that was somewhat negative data both for mRNA and circRNA. So it wasn't specific for the circRNA, it's that [indiscernible] just suboptimal design. So that's where we constantly learn and going forward, so we can make further decisions. And I think we -- as mentioned, come a long way. We have a very good in-vivo program coming up where we learned from some of the suboptimal design from that we've had. And that's -- I think that's the process you always need to have in and [indiscernible] you do the data driven decisions and then that will guide you, I mean, in your next experiment. Anything to add?

I would argue that we have progressed very quickly in terms of what we've been able to build of constructs. We very rapidly were able to establish a vector format that outcompete with the mRNA-based vectors. And as we've shown today, we already brought this to a next generation where we have a 10x improvement, up to 10x better protein expression or second gen compared to our first gen, and this has been achieved. No one else has done this before. It's the first time it's been done. And we've done it in 1.5 years. We achieved something that potentially can outcompete mRNA-based DNA therapeutics in the future. And we think it's likely that this, over time, will become the preferred format. So in that context, I think we moved very quickly. Now of course, there are -- we're guiding on what we're doing, and we've been guiding on the in-vivo readouts, for example, and these are real experiments that have been ongoing. And as Thomas said, experiments are not always behaving the way you expect. So we have to do certain optimizations before we're able to make any definitive conclusions, but we're learning from what we're doing and we're optimizing experimental setups, and we're now looking to test our circVec 2.0. So drug development research often unpredictable. You do an experiment, you learn something, you get more questions than any of that. And I think what we've learned so far has put us in a context where we now have good setups, multiple functionalities. We've been able to identify what are suitable disorders to move forward with. And when we started this, [indiscernible] that AATD, an alpha-1 antitrypsin deficiency will be a good target disease for us, and that's something that has emerged through the research and development that we have done. And again, we understand that people are impatient, and we will keep you updated as we progress. It's also important that we maintain know-how internally. We don't release too much information also it's important for future partnerships, future IP that you kind of hold close what you're actually doing from both the patenting as well as the competitive side of things. So second, we have a question regarding the Neoregen Biotech deal. How will Circio will use the MICT technology from Neoregen Biotech in its preclinical development, will it be used for the entire platform or certain indications? So yes, I can comment on this one. As we said before, the Neoregen technology enables delivery of synthetic DNA. So this does not apply to the viral delivery only to the DNA. In that case, you can't just give the DNA to the cell and expect that it will be going. You need the chemistry and technology to make it enter the cell and make the immune system and then travel to the nucleus. And this is what we'll be testing. At this point, this is at the early resource state. So it's a relatively low-cost experiments. We will simply test the chemistry only in 1 region in our lab and see how efficiently we're able to get the nuclear transfer of our synthetic DNA formats. And then that is successful, we'll bring it forward into in vivo work. But from what we've seen so far, this is a highly promising approach that we believe can overcome some important challenges facing the DNA in therapy space. Then we have a question on our Scientific Advisory Board and whether an individual called Alex Wesselhoeft has joined the Scientific Advisory Board. So Alexander Wesselhoeft is the founder of Orna Therapeutics and the person who did the early research that led to the foundation of that company. So Alex recently has left Orna Therapeutics and gone back to R&D and we can confirm that we've decided [indiscernible] consultants for Circio. So he's now helping us with some of our experimental designs and analysis, and there's also an intention that he will join our Scientific Advisory Board. So that's correct. We're currently working on setting up a new Scientific Advisory Board. Our previous Scientific Advisory Board was more immuno-oncology, oncolytic virus, clinical development focus. So we need to find individuals now with relevant competencies in rare disease, vaccines, DNA delivery and Alex will be 1 of those people and we'll update the market once we have fully completed this new Scientific Advisory Board. Then we had a question for Thomas. What is the biggest surprise or most interesting data you have generated so far?

Yes, as I showed you, we had this design rules that we also filed IP on that basically dictates whether you get high protein expression or basically zero protein expression from the circRNA. So I think that was to all of us, a big surprise that we were so black and white the picture. And I think that has now enabled us to move forward with a very effective vector design, irrespective of what we want to express, I think this also puts us in a good position from an IP perspective because we have good protection for this design rules that has been filed as mentioned. So I think that was quite surprising that it -- we saw this night and day, and it was very consistent throughout all the different experiments we conducted. On top of that, as Erik mentioned, that we were equal already at the 1.0 generation to actually compete with a good old mRNA optimized approach. So of course, what you should understand is that the circRNA technology basically initiated 10 years ago, a little bit more, and Erik and I were sort of humble contributors of some of the early research within the circRNA space. So it's a very, very young technology. And when you see biotech now, it's been out within the last 3 or 4 years or more recent even, so it's a young technology, and I think it has an extreme potential in already at this stage, we can actually be competitive with the technology that's been developed for a long period of time. So I think that's maybe the second thing that we've already come to this stage in the circRNA space that we can actually be competitive with established technologies.

Yes. And I would like to reiterate this point, circRNA what the most surprising was that we found certain design features that appear to be completely critical for the protein expression. And we have no idea which 1 would work or not in at starting off which is quite different besides one, it's very effective, and 1 is completely ineffective. And this design is crucial at least in our hands, and we've created an IP around that. We think it will be challenging for anyone moving into this space to circum that, that IP. So from what we see, we may have discovered certain aspects in the design area that will be crucial. And as we expect, this will become the future preferred format for DNA-based therapeutics. I think we sit on some very important know-how and intellectual property. So the final question we've received is when can we expect the next value inflection point from Circio? I think we've achieved many important value inflection points so far in terms of value inflection points for investors. I think a very important readout will be to show that we can get prolonged, a higher and more durable expression of the circRNAs reported in mice model using our circVec 2.0. Probably the lowest having fruit we'll be doing that with a simple DNA system first and then the key experiment will be doing it from AAV. AAV as we said before, is standard approach for gene therapy. So if we in the mice model can show head-to-head classic AAV versus our circRNA AAV expression of a suitable reported in the mouse model. And that will be, I think, a crucial data points to attract partners as well as prospective specialists, investors can firmly validate our technology against benchmark system in gene therapy. We're already now -- we've done our first gen version 1.0 experiments. We've seen the extraction or based on what we learned, we're optimizing those experiments. We're testing it with the DNA format, 2.0. And then after that, we'll do AAV. So I think likely later this year, we'll have the first data at probably in Q1, we'll start seeing potentially some of these key experiments and not -- and of course, drug development takes time. Getting this forward into the clinic will take still several years. We're in the early development phase. So shorter term in terms of value inflection points, I think what to look for is that we're able to do business development deals based on our technology. And we think this is a suitable platform that can be partnered either for specific therapeutic areas or vector users. So once we establish this robustly shown some of these key data points, we aim to do multiple partnering transactions in the future. And hopefully, we can achieve that already next year. So I think with that, we've dealt with the questions that have come in. So thank you all for attending. We will also be posting this webcast onto our web page. And as always, don't hesitate to reach out to us if you have questions. Always happy to speak with our investors. So thank you again and bye from Circio.