VolitionRx Limited (VNRX) Earnings Call Transcript & Summary

Hello, I'm Soo Romanoff, and I have the pleasure of joining the Volition team here today to share some of their continued strides in developing a rapid sepsis test. We'll first share the team's prepared remarks, Volition's CMO, Andy Retter will provide an update on the science, clinical data and practical applications, and that will help us understand the unmet medical need. We'll also hear from Gael Forterre, Volition's Chief Commercial Officer, will follow up the prepared remarks with Q&A from both of our presenters and Louise Batchelor, Group Marketing and Communications Officer. [Operator Instructions]. Let's get started.

Hello, everyone, and thank you very much for joining us today, and thank you for the introduction. I'm going to take us through a summary of our evolving clinical data, which we're really encouraged by, and it's starting to show really promising results. One of the strengths of Volition, certainly on the sepsis front, we've always been pursuing 2 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 embedded 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 worked at an NHS Trust in London. And just to be clear, the views expressed here today on 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 Spiderman's webs. They are webs of DNA injected behind a neutrophil to entrap and capture invading microorganisms and in particular, bacteria and fungi, they're absolutely critical. The DNA that's injected from the neutrophil is decorated with proteins. We 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 that the fluorescent green is antibody picking up DNA and showing that we're rating 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 [ rud ] paper published in the Lancet in 2019, and it shows that around 50 million people a year have sepsis. There are around 11 million deaths a year of sepsis that would have been higher in the COVID pandemic. It's the #1 cause of death in the hospitals, so a leading cause of readmission to intensive care. And it comes with huge financial but also physical cost 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 attend to work and work at the same level of capacity of what they do before. We also know that sepsis occurs at every age group from the very young to the very old and everyone in between. It is no respect of ethnicity or social economic 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 too often. Sepsis really is an unmet need and the 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 diagnosis and Volition started just over 10 years ago and is always focused on nucleosome technology we really are experts in adapting and using nucleosome technology to facility 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, improving. We're testing what we say we are, and that technology is allocated 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 in a meeting in France in Chantilly. Professor Djillali Annane, our long-term collaborator was there chaired the sessions for us. and everyone was tremendously excited by the data that we are 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, and he's been researching sepsis for well over 20 years and absolutely recognize 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 work 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. The key is that we have now studied data from 3 distinct sepsis popularity in the Netherlands, patients in France and patients in Germany and we're showing consistent signals across those 3 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 3,500 patients now and performed over 14,000 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 Q1. What are the headlines from those meetings? Well, when elevated H3.1 represents activation of our innate immune system and reflects a dysregulated or excessive host immune response and elevated H3.1 level is associated with an increased risk of mortality, is associated with increased risk of septic shock, is associated with an increased risk of multiple organ failure, and it's associated with an increased risk of acute respiratory distress syndrome. 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 the 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 mainly to improve patient outcomes. So this is incredibly powerful as we have a potential diagnostic and theragnostic tool. These next few slides are going to 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 round in 15 minutes, it's is measured on K2 EDTA tube 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, so important to Volition that 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 3 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 83.1% level, really less than about 30 nanograms per mil. 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. Showing in the next slide is the inpatients for sepsis. We now know that well over 80% of the H3.1 that we can 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's coming from neutrophils. That's really critical Volition as it proves that we're testing what we're saying 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 that earliest. But really, every vascular bed is affected, if you look in enough resolution. The final bit on the slide in the bottom right-hand corner shows how there's a link between nucleosomes and activation of your adaptive immune system and high auto-immune system through toll-like receptor 2 and toll-like receptor 4. And that's showing how NETs and nucleosomes communicate with higher functioning of our innate immune system and again leads to this exaggerated immune response. Summary, what we're saying is H3.1 sits at 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 this picking up the damage to vascular beds all dis-regulated 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 see it with liver dysfunction, cardiac dysfunction and pancreatic dysfunction to multisystem organ impairments 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 and 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 in 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 around yellow signal is H3.1, that's what we are in are picking up. We are picking up nucleosomes from those neutrophil extracellular traps there. We've got a link between NETs and our calculation system, that's immunothrombosis taking place is 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. So it's temporarily, really controlled, so carry at the right time and geographically, it's really controlled. And when you lose that control, you're starting to get this dysregulated to host immune response. So picking out, we've got 2 beds there. We've got excessive immunothrombosis as a key part of key strand of excessive [ NET ] pathology. And we've got excessive nucleosomes these parts as soon as acting as damage associated molecular protein. 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 damaged 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' paper, which was our first paper published in the Journal of Thrombosis and Hemostasis 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. It's really critical graph of 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. Scale at the bottom is 50 microns. It shows you how long these NET details can actually be. A standard capillary is about 10 to 15 microns, so you can see how it can block up or they can block blood vessels and they can prevent blood flow down the capillary leading to end organ damage. What we've seen from our clinical data is H3.1 is not impacted by patient's height, age, weight or sex. That's really important because it means that we can apply clinically without having to change our cutoffs or change our thresholds. And we've seen from detailed kinetic studies that there's no evidence of circadian rhythm affecting 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 almost all the rest of the DNA is coming from monocytes and other 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 2 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 because 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 going to take you through the clinical data now. This is data taken from the studies in Yena, 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 the 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 a 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 [indiscernible]. 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 1,000 patients in the [ Yena ] 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 in an H3.1 level greater than 20,000 nanograms per ml died. Those patients were level greater than 10,000 nanograms per ml, 1 in 4 died. And you can see how it drops as you go down as H3.1 concentration force. 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 2 slides and the program we use to produce this Kaplan-Meier here as extremely useful because it gives great transparency to our data. 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 SERMiner, what this data shows is that we were able to identify a cut off of 1,143 nanograms per ml. We showed a clear 90-day mortality signal. I've not repeated the graph here, but we have a second graph or 28-day mortality, which again shows that 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 of the lines of the graph here showing increased mortality with those high 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 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 1,000 patients from the SISPCT study and in total, just under 900 were able to be analyzed, and we could see through that data set, about 1/4 ended up with severe acute kidney injury, AKI, Stage 3. We measured H3.1 levels day not, day 2 and day 7 and patients were followed up at 28 days and 90 days for mortality, length of stay in ITU, hospital mortality, a requirement for renal replacement therapy and independence for renal replacement therapy. These bar charts just show those patients who developed a more severe renal failure had higher H3.1 levels. And again, this is emphasized in a slight more granular tabular form in this slide here showing that patients who had AKI Stage III and required renal replacement therapy had an H3.1 level of just under 1,898 and you can see that depicted in the box and whisker plots to the side here. Again showing the signal with the increased H3.1 level, increase 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 lines and physiological models and biological models that actually H3.1 itself is injurious. A key question for us was, is H3.1 has sort of innocent by standard 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 has been moved to the next graph. What you can see here is this big step. The black line, you can see a significant increased risk of acute kidney injury in patients who have an H3.1 level greater than 3,000. 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 a 28-day mortality, a figure where we identified a cutoff of 2,600 particularly important to pathology. And you can see how we're starting to move towards developing cutoff that clinicians can use. The next thing we did was create a model explaining how you can use H3.1 in conjunction with other standards, 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 count to predict those patients that would require renal replacement therapy. This model has actually performed extremely well. You can see 3 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 1,000 patients who are sick, who admitted to intensive care 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 the significantly increased risk. There's 22 patients in that group, but all of them require 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 can really help with 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 marker of NETosis and it's 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 going to 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 could 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 situation 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 vibrant deposition. That's tremendously interesting as a potential treatment for ARDS. To be clear this is an ARDS model for lung transplantation, it is 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 Yena 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 the target has potential for us to manipulate to. So that's really powerful. We can improve the diagnosis of patients and we can potentially improve and modify their treatments, what's tremendously exiting is the volume of clinical data we've got and the consistent results across data sets. And I'm just going to try and take you through some of that signal now. This is raw data taken for the patients we studied in the Netherlands. The straight line here, particularly on day 2, straight line with mortality is again show consistent mortality signal, the higher the H3.1 level, the greater the risk of patient out 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 2 showing the higher H3.1 level, the greater the risk the patient had of acute kidney injury or 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 formal organ failure, you can see this clear separation from those patients with no organ failure. We know because their box and whisker plots don't cross here that the area under the curve will have to be greater than 75%, just mathematically, that will 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 of multiple organ failure, which is potentially extremely useful to clinicians. It's particularly strong on day 2, 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 846 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 7 days compared to 90 days for the other data sets. And so the signal does look a little different there because of those caveats, but we 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 for 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 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 of higher the H3.1 level, the greater the risk that a patient has to require of developing acute kidney injury and requiring renal replacement therapy. The advantage that gives us as research of 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, easy for us to measure and can 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, have 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 when 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 3 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 and no extra blood tubes are used. It's the most commonly 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 15 minutes. So laboratory 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? A 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 are 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 Gael, our Chief Commercial Officer.

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 as a high likelihood of getting a treatable threats a game changer in effect 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 Gael Forterre, Volition's Chief Commercial Officer; and I'm here to add a few words about our commercial strategies before giving it back to Soo for Q&A. So overall, Volition focuses on R&D. This is our strength, and we are working with commercial partners to effectively put our products to the market. So 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. So what are we looking in those key partners? What's really important for us to really have a broad reach, so we're looking for partners that are present in multiple geographies, sizable, have a large installed base, so they don't have to deploy a large amount of machines and a 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 affair 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 success in the coagulation market. But as you might know, this also has been expanded to oncology, but this is not where 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 10 plus years of work now we have a large package, technical data, clinical data that is exciting for 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. 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. Average length of stay is close to 10 days, if not longer, in some cases. So you're looking at a very large market potential. In our case, 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 Soo. Thank you very much.

Thank you, Volition team for that informative presentation and your continued efforts in such an important area. [Operator Instructions]. 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.

Yes, I'll definitely take that one. So broadly, the research I've done or we've done with Volition covers 2 themes. It covers the basic scientific data, which is what we worked on with our innovation laboratory in Carlsbad, California. We published 3 papers, so far from that work stream, and we've got another 3 or 4 coming, which we'll hopefully publish over the next 6 months -- 6 to 12 months, I'll say. And that data shows that in septic the H3.1 that we are measuring is coming from neutrophils. It's coming from activation of innate immune system. Now there's lots of really cool and really interesting science there. But basically, that scientific works 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 ourselves 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 to organ failure for these trials in particular, AKI and ARDS?

The definition of sepsis is ultimately subjective. We tried quite hard to try and make 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 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 -- there's a clear hazard signal if you've got a high H3.1 level. I think I mentioned in the presentation, if you got a level over 2,500, you've got very significantly increased risk of requiring those therapies. So it should help with decision-making and planning therapies. It's also really exciting as it looks like it's a therapeutic target or at least 3 publications now we suggest that if you remove H3.1 in patients with very elevated level, you get improved outcomes. Those are animal models of sepsis, but that's very exciting for us.

Gael, 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 U.K. and Europe?

So our strategy is actually in licensing. So the next step are those in licensing agreements. Now on oncology, we have another track where there's more direct. I would say we have a pilot program in Europe as well to bring it to market pre-approval from our large partners. But really next steps are licensing agreements, and that will fuel the step for them to get regulatory approval and distribute our test.

So here's another one. You have reported H3.1 levels above that 1,000 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 60s who ever so slightly overweight. And that has sort of representative populations that they involved. They are predominantly Caucasian too. I think if I tease that question a little bit more, they're not aligned with the FDA demographics criteria, but we've seen no difference between age 6, weight or height in the data we've analyzed so far. And theoretically, there's no obvious theoretical reason why there'll be any significant difference between any sex, races or gender. So we're very confident in 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 discrete data sets and it's really quite unusual in sepsis to have a consistent signal across 3 and completely isolated experiments essentially. And so that's very reassuring that we are really picking up a genuine. If anyone new biomarker and 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 going to start to pick -- well, we will use it to pick out people with this dysregulated with an 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 what about the benefits of using H3.1 as a biomarker for sepsis-related AKI versus other biomarkers such as [ prolactin ], Presepsin, interleukins in addition to traditional C-reactive protein levels?

Yes, 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 just -- and there are definitely reasons why it could 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-chest 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. And if you take serial measurements, you're not quite sure if you just got noise in your signal or just -- which is the patient is getting better or worse, so it's hard to apply Presepsin, I've never used Presepsin. It remains a research test at the moment. So it don't think it has a particular advantage over H3.1 in renal.

Okay. How about another one here. NETosis has been shown to chronologically be elevated above normal in patients suffering from long COVID PASC. Have you confirmed this with your assay?

Okay. So Long COVID and our understanding of Long COVID is continuing to evolve. We see low level action of urinate immune system in a number of conditions. And so we can see persistently elevated levels. So yes, we have seen it to 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 where is over 1,000 nanograms per ml, but we'll have some patients who have, say, rheumatoid arthritis or an immune conditions, we'll have a level between 100 and 150, and that's the sort of thing that we see with patients with Long COVID. So it is of some news there.

And we'll keep these coming. If anybody else has questions, please feel free to submit them on the right side of your panel. How all these upcoming readouts impact your plan for regulatory filing under 510(k) pathway in terms of expected time lines. What else will we need -- what else be completed before we're able to file?