Team's prepared remarks, Volition CMO, Andrew Retter, will provide an update on the science, clinical data, and practical applications, and that'll help us understand the unmet medical need. We'll also hear from Gaëlle Forget, Volition's Chief Commercial Officer. We'll follow up the prepared remarks with Q&A from both of our presenters, and Louise Batchelor, Group Marketing and Communications Officer. If you have any questions during the presentation, please feel free to submit them through the Q&A tab at the right side of your panel. We'll try to do our best to address them all. For now, let's get started. Hello, everyone, and thank you very much for joining us today, and thank you for that introduction. I'm gonna take us through a summary of our evolving clinical data, which we're really encouraged by and starting to show really promising results. One of the strengths of Volition, and certainly on the sepsis front, we've always been pursuing two parallel streams. We have our clinical data, and we have our scientific data, and really, they work hand-in-hand together to prove the case for H3.1 and really help us understand how we will use it and how we will interpret the results when we move it to the bedside and embed it in clinical practice. So I really hope you enjoy today's presentation, and I hope you enjoy going through the data. I think many of you have seen me before. My name is Dr. Andrew Retter. I'm Volition's Chief Medical Officer. I also work at an NHS trust in London, and just to be clear, the views expressed here today are my own. I'm not representing my hospital trust in any way. And also, just to be clear with everybody, I am paid by Volition, and I have shares in Volition, too. What are NETs? NETs are neutrophil extracellular traps. They were discovered in 2004, so it's a relatively new discovery of our immune system or function of our immune system, and I always view them in my head as sort of Spider-Man's webs. They are webs of DNA ejected behind a neutrophil to entrap and capture invading microorganisms, and in particular, bacteria and fungi. They're absolutely critical. The DNA that's ejected from the neutrophil is decorated with proteins, which stimulate other cells of the immune system, essentially saying, "Come here and help," and they also can be directly toxic to viruses, and bacteria, and fungi, helping to degrade the invading organisms and stopping them spread. And they also physically act as a barrier to just entrap them as well. This slide here shows the fluorescent green is antibody picking up DNA and showing them erupting behind a neutrophil. Why are we so interested in sepsis? Well, we have good data, and we know that sepsis is one of the most common causes of death in the world. This data is taken from the Rudd paper, published in The Lancet in 2019, and it shows that around fifty million people a year have sepsis. There are around eleven million deaths a year of sepsis. That will have been higher in the COVID pandemic. It's the number one cause of death in the hospitals. It's a leading cause of readmission to intensive care, and it comes with huge financial, but also physical costs to patients and their families. It's estimated to cost over $60 billion a year in treatment in the U.S. alone, and over 40% of survivors suffer long-term consequences. Many are unable to return to work, or many are unable to return to work and work at the same level or capacity of what they did before. We also know that sepsis is, occurs at every age group, from the very young to the very old and everyone in between. It is no respecter of ethnicity or socioeconomic status either. Truly has a huge footprint and is a huge global health problem. My hospital has a particular interest in treating sepsis, and on a daily basis, we admit patients and see patients suffering from the most severe effects of sepsis. It's not unusual for patients to lose limbs related to severe infections and septic shock. Sadly, we see people die, of sepsis all too often. Sepsis really is an unmet need, and there is desperate need for new diagnostic and new therapeutic strategies to improve outcomes. Volition's purpose has always been to develop a low-cost, easy-to-use, routine test to help diagnose this. And Volition started just over ten years ago, and it's always focused on nucleosome technology. We really are experts in adapting and using nucleosome technology to facilitate diagnosis now, and we're really the main company focusing on this, and it gives us a unique advantage compared to our competitors. The major part of the research is focused on developing the antibodies and testing and proving we're testing what we say we are, and that technology is all sorted now. It's well-covered within our intellectual property portfolio. The application of the antibody, actually, that's very routine and very easy to adopt, and so there should be very few or minimal barriers to its implementation in hospital laboratories worldwide. We're very lucky to work with a number of key experts in the field of sepsis and key opinion leaders, and we recently presented and shared all our clinical data with them at a meeting in France, in Chantilly. Professor Djillali Annane, our long-term collaborator, was there and chaired the sessions for us, and everyone was tremendously excited by the data that we were presenting, both the scientific and the clinical data. We are very grateful for the support from our key opinion leaders, in particular, Professor Djillali Annane. He's been researching sepsis for well over twenty years and absolutely recognized as an expert in the field, and other members from the Sepsis Definition Group as well. On the back of the key opinion leader meeting, we worked together to present our data at the recent European Society of Intensive Care Medicine conference, and I'm showing you some of the data that we presented there. A key point is that we have now studied data from three distinct sepsis populations: in the Netherlands, patients in France, and patients in Germany, and we're showing consistent signals across those three distinct populations. That's unusual in sepsis. That's very reassuring that we're detecting a genuine and true biological signal, and we have a very large volume of data. We've tested almost three and a half thousand patients now and performed over 14 thousand measurements, which has given us a wealth of data. We're writing that data up and hope to have publications by the end of Q4 and early Q1. What are the headlines from those meetings? Well, an elevated H3.1 represents activation of our innate immune system and reflects a dysregulated or excessive host immune response. An elevated H3.1 level is associated with an increased risk of mortality, it's associated with an increased risk of septic shock, it's associated with an increased risk of multiple organ failure, and it's associated with an increased risk of acute respiratory distress syndrome. It's also associated, and we have increasingly strong data to show a strong link between a high H3.1 level and the risk of acute kidney injury, and the risk of acute kidney injury progressing to severe renal failure, requiring renal replacement therapy. The consistency of these findings and the fact that H3.1 rises very rapidly and early in a patient's admission, has led us to believe that H3.1 can be seen as a potential treatable trait in patients with sepsis. What we mean by that is that we hope to identify early, and we hope that manipulating its levels to reduce them may lead to improved patients' outcomes. So this is incredibly powerful, as we have a potential diagnostic and theranostic tool. These next few slides are gonna focus on the scientific rationale behind H3.1. This slide is basically identifying our antibody technology, showing that we are picking up the nucleosome and the histone tail on the nucleosome as well, and then the level is detected by standard chemiluminescence assay. There's been a tremendous amount of work behind the scenes from our laboratory teams in the U.S. and in Belgium to optimize the test so it's easy to use. We can now turn the test around in fifteen minutes. It's measured on K2 EDTA or a purple-top bottle, so on a standard blood-testing tube, indeed, the most commonly used blood-testing tube. So it's hugely applicable and really easy to use. And again, it's so important to Volition, as it should reduce barriers to adoption. This slide is a little complicated, but what it's trying to show is that we get nucleosomes into our bloodstream from three sources. The first is from necrosis, from the death of cells. Secondly, we get it from apoptosis, which is the natural death of cells, the senescence of cells, and the leakage of their DNA components. That's occurring in all of us, and the normal range we've identified is an H3.1 level, really less than about 30 nanograms per mL. We all have some cells that are turning over and being replaced, and that's why we see this sort of low level in our circulation. What I'll show you in the next slides is that in patients with sepsis, we now know that well over 80% of the H3.1 that we detect, and the circulating nucleosomes that we detect, come from neutrophils. So you're really seeing, in septic patients, this sort of significantly elevated H3.1 level, we've confirmed that that's coming from neutrophils. That's really critical for Volition, as it proves that we're testing what we say we're testing, and we really are measuring the immune response. When you have excessive levels of nucleosomes, they can activate platelets, which can lead to further activation of neutrophils, activation of complement, and this sort of feed-forward loop, which then becomes excessive and can damage distal organs. Circulating free nucleosomes and histones are particularly toxic to endothelial surfaces and can damage the endothelial bed of blood vessels, and really, you get a multi-organ effect here. The lungs and kidneys, in particular, have very large vascular beds, so it's not a surprise that we're picking up the signal there earliest, but really, every vascular bed is affected if you look in enough resolution. The final bit in this slide, in the bottom right-hand corner, shows how there's a link between nucleosomes and activation of your adaptive immune system and higher-order immune system through Toll-like receptor two and Toll-like receptor four, and that's just showing how NETs and nucleosomes communicate with higher functioning of our innate immune system, and again, leads to this exaggerated immune response. In summary, what we're saying is H3.1 sits at a triumvirate of innate immunity, inflammation, and coagulation. The majority of its extracellular pathology is due to the indiscriminate binding of the anionic components of nucleosomes to the circulation into the vasculature, and that, just going back to the last slide, is why we're seeing so many vascular beds damaged by nucleosomes. This picture is taken from Ella Silk's paper, published in Cell Death and Disease in 2017, and it's picking up the damage to vascular beds or dysregulated or disrupted endothelial function. I've highlighted the kidneys and lungs being affected here, but you can see that excessive histones, that key component of nucleosomes, are seen in brain injury. You can also see it with liver dysfunction, cardiac dysfunction, and pancreatic dysfunction, too. Multi-system organ impairment is occurring here. This is another complicated slide. What we're showing here is that you've got an invading microorganism breaking through an air sac in the lung, an alveolus in the lung. That microorganism comes into contact with platelets. It comes into contact with complement, leading to activation and generating immune response. Central to that immune response are neutrophils. Neutrophils become activated, and some of those neutrophils will release neutrophil extracellular traps. Those are the lines of DNA ejecting behind the neutrophil here. The round yellow signal is H3.1. That's what we are picking up. We are picking up nucleosomes from those neutrophil extracellular traps there. We've got a link between NETs and our coagulation system. That's immunothrombosis taking place. It's trying to capture bugs and stop them spreading and propagating. It's exquisitely localized. It's only occurring at the site where there is tissue invasion, and it's only occurring at the time when there's that invasion, and that's a really critical point to get across. It's temporally really controlled, it's occurring at the right time, and geographically, it's really controlled, and when you lose that control, you're starting to get this dysregulated host immune response. So picking out, we've got two bits there. We've got excessive immunothrombosis as a key, key part or key strand of excessive NET pathology, and we've got excessive nucleosomes, these parts of NETs, damage... acting as damage-associated molecular proteins. So when you have them in excessive levels, they too can cause distant, organ damage as well. So we're picking up sort of a double damage signal, so to speak, which we think is why it's so clinically relevant. The role of H3.1 in NETosis. This is us proving that we're measuring what we say we're measuring. This slide is taken from Kieran Zukas's paper, which was our first paper published in the Journal of Thrombosis and Haemostasis this summer, and really what we've got in the left-hand side of this graph is these blue bars of H3.1 increasing, where we see the DNA signal and the NET signal increasing, too. This really critical graph for Volition, as it shows we're measuring what we say we're measuring. The video file on the right-hand side is showing the sort of mushroom cloud of NETs erupting behind a neutrophil. The scale at the bottom is 50 microns. It shows you how long these NET tails can actually be. A standard capillary is about 10-15 microns, and so you can see how it can block up, or they can block blood vessels, and it can prevent blood flowing down a capillary, leading to end organ damage. What we've seen from our clinical data is H3.1 is not impacted by a patient's height, age, weight, or sex. That's really important, 'cause it means that we can apply it clinically without having to change our cut-offs or change our thresholds, and we've seen from detailed kinetic studies that there's no evidence of circadian rhythm affecting your H3.1 level. Again, that's important, because it means we can use the test any time of day. This graph here is looking at fragment lengths of DNA in patients with sepsis, and what you're seeing is particularly the green part, or the green tail of the graph here, is showing you're seeing this increased fragment length. This led us to go and study that, to try and identify that DNA. We're identifying cell-free DNA from patients with sepsis. We're able to identify that using methylation patterns and comparing those methylation patterns to DNA methylation libraries, that over 80% of that cell-free DNA is coming from neutrophils. Actually, the blue bar at the bottom of this graph is showing that the rest of... almost all the rest of the DNA is coming from monocytes, another key cell in our innate immune system. So we're really, really picking up activation of our innate immune system here. The line on the other side of the bar chart is picking up DNA from a cancer patient and just showing we've got the two here for comparison, just to show the difference. So in sepsis, we really are picking up DNA from neutrophils. We've repeated that in a larger number of patients. We will publish this data later this year, but we're showing a consistent signal across a larger number of patients with sepsis now. You're seeing this consistent increase in fragment length. We've identified those DNAs in nucleosomes, and we've identified that it's coming from neutrophils. That's really important, 'cause that's the basic science reinforcing and reaffirming that we're measuring what we say we're measuring, and that we're measuring DNA and nucleosomes from neutrophils. I'm gonna take you through the clinical data now. This is data taken from the studies in Jena, the studies in Amsterdam, and the studies in Paris. What do these first graphs show? Actually, they're not very impressive, these first graphs. What they show is there is little correlation between a patient's neutrophil count and their H3.1 level. That's actually really, really, really important for Volition, because it means that your H3.1 is telling you much more information than you get from just the white cell count or just the neutrophil count alone. So it's supporting and justifying the rationale for measuring H3.1 in addition to measuring a patient's full blood count. The next thing we looked for was to see, is there a signal between H3.1 and badness? And the simple answer to that question is, yes, there is. High H3.1 predicts mortality. This is a scatter plot taken from just under a thousand patients in the Jena data set, and what you can see is this spike at the beginning of the graph. The patients with a very high level died earlier. This is represented in tabular form in this slide, showing that every patient who had an H3.1 level greater than 20,000 nanograms per mL died. Those patients with a level greater than 10,000 nanograms per mL, one in four died, and you can see how that drops as you go down, as your H3.1 concentration falls. All of our data analysis has been done in the statistical program, R, and that's the program we used to analyze the data for the last two slides, and the program we used to produce this Kaplan-Meier graph here. R is extremely useful because it gives great transparency to our data, and it gives us great confidence in sharing our results and allowing others to independently validate them and verify them. We used a package here called Survminer. What this data shows is that we were able to identify a cutoff of 1,143 nanograms per mL, which showed a clear 90-day mortality signal. I've not repeated the graph here, but we have a second graph for 28-day mortality, which again shows that a cutoff of 2,600 nanograms per mL is a key mortality signal indicator. Those patients with levels above that had significantly increased mortality, and you can see the clear separation in the lines of the graph here, showing increased mortality with those higher levels of H3.1. That's important for doctors and nurses because it will help us triage patients and potentially escalate them earlier. It's also suggesting it's a trigger to start thinking about modifying therapy. Next, we looked to see the signal between H3.1 and organ failure, and the organ failures that we particularly looked for were acute kidney injury and the requirement for renal replacement therapy, and then for respiratory failure and, in particular, severe respiratory failure and acute respiratory distress syndrome. So the renal data, first of all. We looked at just over a thousand patients from the SISPCT study, and in total, just under nine hundred were able to be analyzed, and we could see through that data set, about a quarter ended up with severe acute kidney injury, AKI Stage 3. We measured H3.1 levels Day naught, Day two, and Day seven, and patients were followed up at twenty-eight days and ninety days for mortality, length of stay in ITU, hospital mortality, and requirement for renal replacement therapy, and independence from renal replacement therapy. These bar charts just show those patients who developed more severe renal failure had higher H3.1 levels. Again, this is emphasized in a slightly more granular tabular form in this slide here, showing that patients who had AKI Stage 3 and required renal replacement therapy had an H3.1 level of just under a thousand eight hundred and ninety-eight, and you can see that depicted in the box and whisker plots to the side here, again, showing the signal with an H3.1 increased H3.1 level, increased risk of organ failure, and specifically increased risk of acute kidney injury. One of the key questions we asked ourselves is: Are we just seeing something accumulate, or is it adding something extra to the pathology? We are confident, from our understanding of science and physiological models and biological models, that actually H3.1 itself is injurious. A key question for us was: Is H3.1 a sort of innocent bystander that you just see accumulate, or is it actually linked to the pathology and linked to the progressive organ failure? So we compared the kinetics of H3.1 to other standard biomarkers. What I'm picking up here is creatinine. Creatinine is released from the breakdown of our muscles and accumulates in people with kidney injury. It's inert. It's not damaging the kidneys itself, and you can see here, there's just progressive increase in creatinine levels across this Kaplan-Meier curve. This pattern is really quite different with H3.1 as we move to the next graph. What you can see here is this big step. The black line, you can see a significantly increased risk of acute kidney injury in patients who have an H3.1 level greater than three thousand. That's really quite different to the creatinine graph that went before it. That different kinetic pattern is suggesting that H3.1 is injurious to the kidney in some way, that we're breaching a threshold. That's consistent with the mortality data that went before, particularly the twenty-eight-day mortality figure, where we identified a cutoff of two thousand six hundred is particularly important to pathology, and you can see how we're starting to move towards developing cutoffs that clinicians can use. The next thing we did was create a model explaining how you can use H3.1 in conjunction with other standard clinical blood tests to help with decision-making. It's really critical. H3.1 is going to be used in addition to standard tests. In this model here, we used H3.1 in addition with a patient's urine output, in addition with a platelet's platelet count to predict those patients that would require renal replacement therapy. This model has actually performed extremely well. You can see three main signals from this. We were able to identify a large number of patients that didn't require and weren't ever going to require renal replacement therapy. This is a population of almost a thousand patients who are sick, who are admitted to intensive care and been diagnosed with sepsis, and that's really early reassuring data that we can use to predict and inform their clinical course and help clinical decision-making. The opposite is true with the black line at the bottom, where patients with a high H3.1 level, low platelet count, and low urine output, you can really see their significantly increased risk. There's 22 patients in that group, but all of them required renal replacement therapy by day 4. Perhaps for me, clinically, the most useful line is actually the brown line, the second line up from the bottom, where you can see the increased risk of requiring renal replacement therapy using this model, and that could really help with this clinical decision-making and with the triage of patients. And we're continuing to explore this, and we're really excited because we've seen that sort of consistent signal across the, in particular, across the data set from Amsterdam, but also the data set from Paris, too. So, in summary, H3.1 is a marker of netosis, and it's a promising biomarker in the context of, acute kidney injury and severity of acute kidney injury. Compared to creatinine, we have a different kinetic profile, and we think it's central to the pathology of acute kidney injury, and we're able to produce a clinically relevant model incorporating H3.1 into standard laboratory parameters. This opens up exciting possibilities for improving the management of sepsis-induced acute kidney injury. Next, respiratory failure. This paper has only just been published. It was published by Mittendorf in Transplantation in August of this year, and I'm just gonna take you through it, because I think it underpins the importance of H3.1 and why we're so excited about potentially manipulating it as a target. In this group, they developed a pig model of severe respiratory failure. They injected gastric acid into the lungs of pigs, and this slide just shows that they were very good at producing acute respiratory distress syndrome. You can see a significant oxygen requirement in the animals, and you can see a significant increase in the lung injury score in the animals. We're picking up a couple of things in this next slide. You can see an increase in levels of H3.1 in the animals with acute respiratory distress syndrome. You can see increased infiltration of immune cells and expression of another marker of NETosis, that's a citrullination of H3, and you can see increased fibrin deposition in the lungs of the animals with acute respiratory distress syndrome. The team used an extracorporeal column to absorb H3.1 and absorb NETs, and basically, this graph is just showing that they were successfully able to remove the levels. In the treated patients, you had significantly less infiltration of immune cells into the lungs and significantly less fibrin deposition. That's tremendously interesting as a potential treatment for ARDS. Now, to be clear, this, this is an ARDS model for lung transplantation. It's not a sepsis ARDS model, but the principle should absolutely hold true for sepsis and is tremendously exciting. What particularly excites me is that independently of their data, from the data from our colleagues in Vienna, shows a high H3.1 signal in acute respiratory distress syndrome. Those patients with septic shock and severe ARDS in our study group had the highest H3.1 levels. It really makes us think that this is a target for us to study, a target for us to understand better, and a target that has potential for us to manipulate, too. So that's really powerful. We can improve the diagnosis of patients, and we can potentially improve and modify their treatments. What's tremendously exciting is the volume of clinical data we've got and the consistent results across data sets, and I'm just gonna try and take you through some of that signal now. This is raw data taken from the patients we studied in the Netherlands. The straight line here, particularly on day two, straight line with mortality, is again showing a consistent mortality signal. The higher the H3.1 level, the greater the risk the patient had of dying. Again, this is data from the Netherlands, and again, it repeats the acute kidney injury and renal failure signal. The linearity here is particularly strong on admission and on day two, showing the higher the H3.1 level, the greater the risk a patient had of acute kidney injury and requiring renal replacement therapy. This data from Holland also shows the higher the H3.1 level, the greater the risk of multiple organ failure. The lines here are added, because when patients had four or more organ failure, you can see this clear separation from those patients with no organ failure. We know, because the box and whisker plots don't cross here, that the area under the curve will have to be greater than 75%. Just mathematically, that'll be true, and so you're really picking up the signal, and we're just showing it in another way, the signal between a high H3.1 level and multiple organ failure, which is potentially extremely useful to clinicians. It's particularly strong on day two, that signal. We're seeing a similar signal with H3.1 and mortality in the data collected from the patients in Paris. You can see this level of eight hundred and forty-six is a key threshold level here. The median is much higher. The Paris data set is slightly smaller at the moment, and actually, follow-up is only for seven days, compared to ninety days for the other data sets, and so the signal does look a little different there because of those caveats, but we're still remain encouraged, and it's still consistent. This is looking at septic shock in patients from Paris. Again, you're showing a consistent signal with a higher level of H3.1 in those patients with septic shock. This is a different graph presenting similar data, just in a slightly different way to what I've shown you before. What you're seeing here is a hazard ratio, so the higher your H3.1 level, the greater the risk of you requiring renal replacement therapy in the patients we've studied in France. It's just a different way of showing the similar data, but again, it reinforces the signal that the higher the H3.1 level, the greater the risk the patient has of developing acute kidney injury and requiring renal replacement therapy. The advantage that gives us as researchers studying is that AKI is very well defined. There's established diagnostic criteria internationally for that, so we're confident, and the results are consistent, and actually, when a patient goes on to renal replacement therapy, that's a very clear outcome measure. So it's really well defined, easier for us to measure, and just gives us applicable results that we can move to the bedside. This data from Paris also shows a repeat signal of those patients who acquired respiratory support and developed acute respiratory distress syndrome. Again, you are seeing the patients who acquired invasive mechanical ventilation, who had the worst respiratory failure, had these higher H3.1 levels... What we've just covered is the scientific rationale showing that the H3.1 test is actually measuring what we say it's measuring, and we're measuring this innate immune response. What we've shown you is a strong signal between H3.1 and mortality, between H3.1 and acute kidney injury, and risk of requiring renal replacement therapy, and a strong and consistent signal between H3.1 and severe respiratory failure and acute respiratory distress syndrome. We've looked at over 3,000 patients now. The test has been performed well over 14,000 times, and it's extremely exciting that we are seeing a consistent signal across three distinct and separate data sets. Most importantly, the test is easy to use. It can be done on a standard purple top K2 EDTA tube, so no extra blood sampling equipment, no extra blood tubes are used. It's the most commonly used tube in the laboratory, and with our work with our teams from Belgium and the U.S., we've been able to adapt the test so we can turn around and produce a consistent signal in fifteen minutes, so laboratories should be able to adopt this easily and should be able to turn around results to clinicians in real time almost, so it can impact and influence patient care. We are confident we are making really good progress to defining H3.1 as a treatable trait in sepsis. What's next for us? We need to actually publish those results. The publications have already been drafted and will absolutely be submitted by the end of Q4 for publication. We hope to have them available for you to read as soon as possible. We're moving forward with out-licensing, and on that note, I'd like to leave you with a few words from Professor Annane, who's been a great champion and mentor to this project, and after Djillali speaks, you'll be hearing from Gaelle, our Chief Commercial Officer. Thank you so much. First time I have seen so many data coming so fast and with consistent findings. So what we are likely to see now with H3.1, and more globally with NETs measurements, is a high likelihood of getting a treatable trait, a game-changer in effectively modifying patients' trajectory. So I think this is something that is very likely to be translated by most physicians like me in their routine practice in the next couple of years or so. Good morning, everyone, and thank you, Andy. I'm Gaelle Forget, Volition Chief Commercial Officer, and I'm here to add a few words about our commercial strategy before giving it back to Sue for Q&A. Overall, Volition focuses on R&D. This is our strength, and we are working with commercial partners to effectively put our product to the market. The way we monetize is, we are negotiating those contracts with them and then receiving upfront milestones, royalty, and payments, ongoing payments for the supply of key components. What are we looking in those key partners? Well, it's really important for us to really have a broad reach. We're looking for partners that are present in multiple geographies, sizable, have a large install base, so they don't have to deploy a large amount of machines and large amount of CapEx just to get to the market. We need partners that have an experience in tech transfer, because we are working with them to effectively transfer our technology on their platform, as well as regulatory and clinical affairs experience. And finally, really important for us as well, is really patient-focused. So now, with that in mind, we are having discussions with those large partners, with a focus on sepsis and the coagulation market. But as you might know, this also has been expanded to oncology, but this is not what we're focusing on here. We have a data room that is accessible, and we're starting to share effectively information with them. What is very exciting for Volition right now is that after ten plus years of work, now we have a large package, technical data, clinical data, that is exciting for, you know, those large potential commercial partners, and we're progressing in those discussions. So in terms of market opportunity, you heard from Dr. Djillali Annane at ESICM, and as well in the Q&A session. You know, when asked when he would be using it, he mentioned for every patient in intensive care every time. So if you look at what it means in terms of market potential, in Europe, we're talking about around 18 million potential patients. In the U.S., around 15 million. You know, an average length of stay is close to 10 days, if not longer in some cases. So you're looking at very large market potential. In our case, you know, we quantify it north of $7.5 billion. So Volition is really addressing a large unmet need, and we're very excited to progress our commercial discussions and announce something to you, hopefully very soon. So with that said, now I'll pass it on to Sue. Thank you very much. Thank you, Volition team, for that informative presentation and your continued efforts in such an important area. Just a reminder, if you have any questions, please submit them via your Q&A tab at the right side of your panel. I'll read them as they come across. We already have a few here. ... We understand the VolitionRx assay focuses specifically on the identification of circulating H3.1 nucleosomes as an indicator of sepsis and disease severity. Can you remind us on why H3.1 is a reliable proxy for measuring NETs? I think that might be for Andy. Hi. Yeah, I'll definitely take that one. So broadly, the research I've done or we've done with Volition covers two themes. It covers the basic scientific data, which is what we've worked on with our innovation laboratory in Carlsbad, California. We've published three papers so far from that work stream, and we've got another three or four coming, which we'll hopefully publish over the next six months, six to twelve months or so, and that data shows that in septic patients, the H3.1 that we are measuring is coming from neutrophils. It's coming from activation of your innate immune system. Now, there's lots of really cool and really interesting science there, but basically, that scientific work's proven that it's coming from... That the H3.1 we're detecting is coming from patients, coming from neutrophils in patients with sepsis, which is really key. All our cells have H3.1 in them, but we're picking up in septic patients particularly well. Thanks. So here's another one. The recently presented clinical data builds on the data collected previously on severe sepsis. What's the rationale for specifically focusing on sepsis-associated organ failure for these trials, in particular, AKI and ARDS? So, the definition of sepsis is ultimately subjective. We try quite hard to try and make it as robust as possible, but the definition is still subjective. Whereas organ failure, and the definitions around organ failure, and if someone goes on a ventilator or if someone goes on a dialysis machine or renal replacement therapy, those are really cold, hard, objective measures. And so we get a much clearer, much more robust, much more translatable, informative signal by specifically chasing and quantifying those organ failures. What we've shown with H3.1 is there's really a clear hazard signal if you've got a high H3.1 level. I think I mentioned in the presentation, if you've got a level over two and a half thousand, you've got, you know, very significantly increased risk of requiring, you know, those therapies. So it should help with decision-making and planning of therapies. It's also really exciting, as it looks like it's a therapeutic target. There are at least three publications now, which suggest that if you remove H3.1 in patients with very elevated level, you get improved outcomes. Now, those are animal models of sepsis, but that's very exciting for us. Yeah. Gaelle, maybe this one is for you. Excluding the out-licensing to large pharma, what further steps are required prior to availability of the tests for commercial launch in the UK and Europe? So our strategy is actually in licensing. So the next step are those in licensing agreement. Now, on oncology, we have another track where that is a more direct. I would say we have a pilot program in Europe as well to bring it to market, pre, you know, approval from our large partners. But really, next steps are licensing agreements, and that will fuel the next step for them to get regulatory approval and distribute our test. So here's another one. You have reported H3.1 levels above one thousand are associated with increased rate of mortality. For the patients admitted at these levels, were there any other commonalities in terms of demographics or health parameters? I'll take that question. Okay, so the studies were done in Europe, and so they represent a classic European sepsis population. So, generally speaking, that's middle-aged patients in their mid to late sixties, who are ever so slightly overweight. And that's the sort of representative populations that they're involved. They are predominantly Caucasian, too. I think if I tease that question out a little bit more, they're not aligned with the FDA demographics criteria, but we've seen no difference between age, sex, weight, or height in the data we've analyzed so far. And theoretically, there's no obvious theoretical reason why there'd be any significant difference between any sexes, races, or gender. So we're very confident the results are applicable. The final point I would add, what's so unusual and what's got the community so excited, is that this is... The data I presented to you is three distinct, discrete data sets, and it's really quite unusual in sepsis to have a consistent signal across three, you know, completely isolated experiments, essentially. And so that's very reassuring that we, we are really picking up a genuine, and a genuinely new biomarker, an exciting biomarker. So can the NETosis test differentiate between congestive heart failure and pneumonia? Okay, so we haven't got a lot of data on that specifically, but yes, I would expect it very much to be able to. Pneumonia, chest infection will have a greater, much greater inflammatory response than congestive cardiac failure would do. And so you could certainly see how it would be particularly useful there in its applicability. It's gonna start to pick... Well, we will use it to pick out people with this dysregulated, excessive immune response, and that's really helpful. So you wouldn't expect to see so much immune activation in congestive cardiac failure, so yes, I think it will help in the differentiation. ... So, So, so what about the benefits of using H3.1 as a biomarker for sepsis-related AKI versus other biomarkers, such as, procalcitonin, Presepsin, interleukins, in addition to traditional C-reactive protein levels? Yikes! That's quite a tricky question. There's years of research covered in that question. Okay, CRP is old. It's about 80, maybe even close to 100 years old now, and doesn't offer a lot of differentiation. It's just, and there are definitely reasons why it can be low and reasons why it's high, which don't relate to the underlying pathology, so it's not very discriminatory for us. Interleukins, if we went back 20 years, everyone would have been really excited about interleukins, but the problem with interleukins is that the inter- and intra-subject variability is just too high. The levels literally ping up and down all over the place, so bringing that to the bedside is really hard. It's really hard to understand what the normal ranges are. It's really hard to pick the patient at the right point. If you take serial measurements, you're not quite sure if you've just got noise in your signal or just the patient's getting better or worse. So it's hard to apply. Yeah. Preseptin, I've never used Preseptin. It remains a research test at the moment, so I don't think it has a particular advantage over H3.1 in renal failure. Okay, how about another one here? NETosis has been shown to be elevated above normal in patients suffering from long COVID PASC. Have you confirmed this with your assay? Okay. Long COVID and our understanding of long COVID is continuing to evolve. We see low-level activation of your innate immune system in a number of conditions, and so we can see persistently elevated levels. So yes, we have seen it to a degree, but we haven't specifically looked at long COVID. One of the things that's become an awful lot of work has been put into defining the normal range of H3.1 and defining the higher ranges. So we know that normal is less than 30 nanograms per ml. We can see clear pathology and mortality signal when it's over 1,000 nanograms per ml. But we'll have some patients who have, say, rheumatoid arthritis or an immune condition, please excuse my cold, will have a level between a hundred and a hundred and fifty, and that's the sort of thing that we see in patients with long COVID. So it is of some use there. Thank you. Yeah, we'll keep these coming. If anybody else has questions, please feel free to submit them on the right side of your panel. How will these upcoming readouts impact your plan for regulatory filing under the 510(k) pathway in terms of expected timelines? What else needs to be completed before we're able to file? I'll take that. I'll take that one. So the FDA gave us a clear path, and we had to compare to sort of predicate devices. The data we've got helps reinforce the strength of our argument. We've got really good scientific data, we've got good manufacturing data, and we've got great clinical data, too. So look, we, so we're really confident by that. All of those will go in to support any submissions to the FDA. One of the reasons I mentioned the European population beforehand is that that data is not submissible directly to the FDA, although they will consider it and consider the consistency of the signal. So Gaelle mentioned it in his talk about the importance of us working with licensing partners to work on taking that forward to bringing it to market. Yeah, maybe I can add to that. That's the goal of our licensing discussion, is to bring the data, the package to our licensing partners so they can move this test through their different regulatory bodies. Yeah, and we believe you're planning to introduce a next generation version of this test. Can you update us on that? Which is kind of a follow-up on the last one. Do you want me to do that one? So we're gonna have two versions of the test: a Nu.Q Rapid and a Nu.Q Sensitive. The Nu.Q Rapid we can turn around in 15 minutes, and certainly for the vast majority of indications in the clinical setting, we'll think that will be the one that people go for. And that enables the range to be from about 20 nanograms per ml with linearity all the way maintained all the way up to 20,000 nanograms per ml, so really broadly applicable. The Nu.Q Sensitive will have a range down to 3 nanograms per ml and up to 6,000. So when I mentioned earlier about some patients with inflammatory conditions and those levels of 100, you'll get slightly better resolution with the Nu.Q Sensitive, and so that might be clinically useful. And that's how we've split the product line as it is. And really, that's due to internal, the software operating the machine and some of the reagents we use. The actual test itself, the nuts and bolts of the test, the antibody, they don't change at all. Andy, we'll give you a little bit of a breather here. Gaelle, you've mentioned you recognize sales from both royalties and sale of key components as part of your commercial strategy. Can you explain what that means as the kind of additional returns you can generate from that? What can we expect to hear, when can we expect to hear about your licensing discussions with potential partners? Okay. So, maybe I'll start with the first one, the structure of the deals. So we're looking for, you know, two key components, if I may say, on those deals, you know, upfront and milestones, as well as ongoing payments, and those ongoings are for the supply of key components as well as royalties. So effectively, we're looking for supply and licensing agreements. So, that's the way we are looking to structure a transaction with those partners. And the way to do so is, you know, to offer value on both side. The idea of the second piece, the royalty and the supply, is first, we believe we're number one in nucleosome production, so we wanna. This is our core competency, and we wanna develop it and share it with our partners. Number two is we also are really interested in building the long-term value of our business through growing sales, so this is where supply of key components as well as royalty, you know, that grow over time, build that value, so that's for the question about the deal structure. As far as timeline, if we rewind a little bit, I think it's very exciting. For the first time in the company history, we have the technical data, the clinical data, to go out and talk to the large diagnostic companies, and we're engaged in a lot of discussions with them right now, lots of interest. We aim to close the first transaction in Q1, and we're for sure working really hard to get there. Obviously, the timing is not completely in our control, but that's the timeline we have internally. Maybe this is for both of you. I mean, the data looks really good. This is from Bruce Jackson from Benchmark. What else is needed in order to make the test the standard of care? Maybe, Andy, you start on the medical side, and maybe I can add a word on commercial. So we're at a really interesting point, and I think Gaelle just touched on it. We've got great scientific data, we've got great clinical data, and we've got a test which is easily applicable. We need to work with a licensing partner that's got much greater access and a much greater footprint in hospitals than we do to actually bring this test. So instead of me talking to you about it being used in, you know, three and a half thousand patients, fourteen and a half thousand tests, we're talking about it being used in tens of thousands, if not hundreds of thousands of patients, and that's why we need to work with... Well, one of the key reasons for us to work with licensing partners is to exploit that hospital base and get that footprint in there. When that's done, and when it's been used a huge amount, you know, large amount of times, that's when it can move to stopping standard of care. There's tremendous interest in the medical community about using this as a therapeutic target, about taking it away, and we very much hope that that will sort of be a sort of pioneering approach that helps embed and accelerate its use onto, onto wards. And that's where we're aiming to go. Not sure to add. It's really. We say it's a test that is bigger than us in terms of market potential and what we can do alone. So, that's why we're interested in those external parties to work with us to put it on the market. Yeah. I mean, Sue, if I can just jump in and just add one point- Yeah ... that I would say is that we are now deep in discussions with a whole range of companies. You know, and so in terms of answering very directly to Bruce's what do we need, we need to close some of our deals out, you know, and get the partners on board, because I think that that's gonna be what takes us forward, as Andy said. So yeah, but it's been fantastic, the level of interest that we've had so far. Yeah. I mean, it's really important that we're complete finishers. We've completed our research studies, we've completed our scientific, or we're in the process of completing our scientific work. Now we need to complete the deals, 'cause this is one of the most exciting things in sepsis for thirty, forty years, and actually, we have a duty to make sure it works and that it gets to help patients. Right. Right. And, Andy, you deal with sepsis patients all the time, so that resonates really well. Here's another one. You talked about manipulating H3.1 levels. Have you already... Has this already been done in studies in the form of therapy, and how does that manipulation work? So it's been done twice in two slightly different techniques, if you forgive me. One is there was a pig model of sepsis. Blood was taken out of the pigs with sepsis, the H3.1 was absorbed, and then the cleaned blood was returned to them, and those animals did better. There is a sheep model of sepsis run by a team in Belgium at one of the famous university hospitals, and they used a polyanion molecule to bind to H3.1, and again, they showed improved outcomes in those patients. So you've got diagnostic potential, and really interestingly, you've got this therapeutic target. It's why you heard Charlie talk in his speech about a treatable trait, and that's new. We've never had that before, and there are a number of interesting ways in which you could antagonize or try and act on H3.1. And actually, some of the key pioneering work we've been doing with our innovation laboratory, you heard me mention Kieran Zukas's paper, but Brandy Atterbury's paper and another paper from one of our colleagues, Justin, is just about to be published, too, and that's all working on those themes. And we now have ways of stimulating neutrophils, which we're starting to work with pharma to test new molecules as well, which is really exciting for us. Yeah, and Sue, if I, if I can just add one point from, I was recently at the ESICM Congress that Andy mentioned, and I do think one of the interesting things for, for me as a kind of, as you all know, non-scientific background, but there was a real consistency to a lot of the messaging in the different sessions. You know, it's an enormous congress. There's 10,000 doctors there, but there was a lot of consistency, and one of the things that I thought was really interesting was when you look at the world of oncology, and we're kind of used to personalizing the medicine now and precision medicine, and that's something that's still emerging really in the world of sepsis and sepsis management. I thought what was very interesting for me is that there was a real excitement and buzz around this possibility of this treatable trait, and indeed, about a number of the studies that we've got designed, and one of the studies that's still ongoing, the RHU RECORDS study, is seen as a really gold standard study. I think what's benefited us is just having got connections across a number of different countries, across some really good data sets with some of these key people. You know, we're very much part of the conversation, and I think this treatable trait and this potentially unlocking future, therapeutics or even actually testing or retesting some of the previously failed therapeutics, but actually, if they're tested in this smaller population, in this identified, phenotype, then maybe some of the existing treatments might also be useful. So I think there's quite a lot of interest around not only new therapies to remove H3.1, but all kinds of some of the older therapies, that maybe haven't done so well, could they also be utilized in this kind of sub-cohort of patients? So, it's certainly an interesting time, I think. Yeah, I think that's really helpful, Lou. I think that's all the time we have for questions today. If you have any other questions or if you'd like to speak to the management team, please reach out to the Volition investor team contact listed on the company press release. Also, we'll be hosting an oncology webinar next month, so please keep an eye out for the invite. Thank you all for joining us here today. Thanks very much. Thanks, Sue. Thank you, Volition team.