Good morning, and welcome to the BioVie conference call. At this time, all attendees are in a listen-only mode, and a question and answer session will follow the presentation and fireside chats. If you'd like to submit a question, you may do so by using the Q&A text box at the bottom of the webcast player. As a reminder, this call is being recorded, and a replay will be made available on the BioVie website following the conclusion of the event. I'd now like to turn the call over to Cuong Do, Chief Executive Officer of BioVie. Please go ahead, Cuong. Good morning, everyone. Thank you, Tara. This, we believe, is a great day for the Long COVID patient community with some of the results that we'll be discussing today. I'm very excited to be sharing this with you. I'm joined today by two experts, which will come on camera later on. Michael Peluso is one of our clinical investigators who's been part of many Long COVID trials, as well as Ezra Spier, who is a Long COVID patient advocate who's also been participating in many trials. Over the course of this presentation, we will be making certain forward-looking statements. I will let you read this at your leisure. This presentation could also be found at our website. We are here because of bezisterim. Bezisterim is a very novel first-in-class molecule that is orally bioavailable, and it crosses freely into the blood-brain barrier. It is believed to act to block ERK and NF-κB activation, and thus it blocks the production of TNF-α, which is considered to be the master regulator of inflammation. We are studying bezisterim in Long COVID because it's believed, if you look at the graphic on the right, it's believed that the spike protein, the envelope protein on the COVID virus, if you have the infection or if in Long COVID, those fragments of those proteins are believed to activate something called the Toll-like receptor two or the Toll-like receptor four, which essentially activates NF-κB and ERK to lead to TNF-α and the production of other inflammatory mediators. Of course, since bezisterim blocks the activation of NF-κB and ERK, it is believed that it can have all these downstream impact and thus hopefully help with Long COVID symptoms. So we conducted this Long COVID, this ADDRESS-LC phase II trial. It is designed as a phase II signal-finding proof of concept trial. As you know, drug development typically goes through three different phases. Phase I first establishes that a drug is safe. Phase II is a signal finding. So try to figure out, does the drug have a signal? Does it have a chance of working in some patient population, and how do you show that it works? Then once you get the information from phase II that shows that, well, if we use this endpoint with this group of patients, you then move on to phase III confirmatory trial, which basically says, "This is our endpoint, and we're trying to get a statistical significance." That's the purpose of phase III. It's confirmatory. Phase II is purely signal finding. What we're trying to do is to identify the efficacy signal. Namely, what endpoint can we use to show that the drug has a favorable treatment benefit? We're trying to measure patient populations that can benefit from that. We need all this information so that we can design and size the phase III trial. In this trial, since it's the first time that we're looking in Long COVID, we evaluated 22 different clinical outcomes to try to figure out which measure works best. We also collected blood samples to assess a series of biomarkers. We're conducting a proteomic study evaluating over 380 different proteins. It should be noted that this work was supported by a grant from the Department of War. Let me first jump to give you the key findings before we go through the details. The first thing to recognize is that Long COVID patients are not one homogenous group, and in fact, it is a very diverse and heterogeneous population. When we think of Long COVID, we tend to think of fatigue, malaise, and brain fog, and we often assume that a patient has all three of those, and in fact, they do not. Patients can have any combination of one, two, or three of those symptoms. The key finding from our trial is that we believe bezisterim is very effective for these different patients who have the severe symptoms when they start the trial. But the critical thing to recognize is that you need to have the symptom to begin with in order to improve. If you have high symptoms of fatigue, you improve statistically significantly versus placebo on five different fatigue endpoints, along with trending in sleep and post-exertional malaise. If you have high malaise levels, you improve on malaise as well as cognition. If you have high cognitive impairment at baseline or brain fog, you improve on your brain fog. Lastly, the safety and tolerability profile of bezisterim was very similar to placebo. This is a very critical finding, especially in this patient population, where virtually every patient is on multiple different medications. One thing to recognize is that Long COVID is not COVID. It is not the same, and it shares an unfortunate part of the name. COVID, as you know, is the active infection that comes from the virus. Long COVID is a description of the aftermath of the infection. These are symptoms that are quite diverse. It could be fatigue, it could be brain fog, it could be very heterogeneous, and it could last for months and years after the actual COVID infection itself. It's a very large population out there. 17 million- 20 million U.S. adults are believed to have Long COVID symptoms now, and 3.8 million have it so severely that they're essentially considered to be disabled. They can no longer work or keep up with the physical demands of their job, and there are no therapies out there. There is a huge, great medical need for a therapy to address Long COVID symptoms. The challenge of developing a drug for Long COVID is actually not only to show that it works, but it's actually finding how. Because one, you see it's a very heterogeneous population. There are no validated biomarkers. There is no biomarker that you can point to that says, Ah, this person has Long COVID. It is purely assessed symptomatically and has large background variability, and everybody's on multiple medications. It's actually very difficult to find out how it works, how a drug works, who can benefit from it, and that's exactly what we set out to do, and we believe we have achieved that. I mentioned we measured 22 different endpoints, so this gives you a list of what those endpoints are. And a sense of how to read the numbers. When we're looking at clinical trial results, we're looking at two different things. One is just how large is the effect. So how much of a benefit does treatment provide compared to placebo? Statistics gives us a tool to do that, something called the Cohen's d, which measures the magnitude of the impact, the difference between two groups. The larger the number, the better. The second, it gets to a question of how sure are we that this result is significant? Excuse me. We look at the P value. The smaller the P value, the better, and typically something is considered to be statistically significant if the P is less than 0.05. At baseline, we compared the bezisterim treatment group versus the placebo group, and we see that virtually everything is very well-balanced, with the one possible difference being slightly more women in the bezisterim treated group compared to those that are on placebo. But everything else is pretty much balanced across the board. The other thing we find at baseline is there is huge variability in the symptoms. The way to explain this chart is that if you look at the left blue circle, you see that there are 112 patients out of a total of 203 that have high levels of fatigue at the start of the trial. If you look at the green, there were 98 patients who have brain fog, high levels of brain fog, and at the red, there are 72 patients with high post-exertional malaise. Equally important, if you look at the yellow, there are 44 patients, or 22%, with low symptoms in all three. As you can see, there is huge mixtures. Right in the middle, there's only If you look around, there are about 35% of the patients who have some combination of two. Likewise, there are about 35% of patients who have just one symptom. This is really, really critical to understand, because this is where everything starts. If you look at the 112 patients who have high fatigue, that's about half of 55% of the trial. But that also means that there are 45% of the patients in this population that does not have fatigue symptoms. One thing that we have always known about bezisterim, and frankly, many, many other drugs, is that you need to have the symptom to begin with before you can improve on that symptom. If you don't have the symptom, you can't improve, or if you have low levels of that symptom, you cannot improve. So understanding what symptom you actually have, what symptom a patient subgroup actually belongs in fact, is critical to understanding the results. You will see that on the next page. Because if you throw all 203 patients together and look at the 22 different endpoints, you will see something that's very interesting pattern. You will see that on all except one, all of the patients, all the Cohen's d favor bezisterim treatment. It basically giving us a signal that the drug appears to be working for patients who are taking the drug. Yet, when you look at the p-value for any one of these endpoints, you see that they do not reach the 0.05 level for statistical significance. So if you were to just stop there, you would say, "Oh, the drug did not work because we did not have statistical significance." But drawing that conclusion would be a huge mistake because of the point I made here about the different subgroups. You have to have a symptom to improve upon that endpoint. This becomes very clear here. So one thing that we do in clinical trials is we look at a patient at baseline. We divide them up into different levels of severities. We divide up into quartiles and tertiles. You can very clearly see here that on baseline PROMIS Fatigue, so this is an endpoint that looks at a patient's fatigue level at baseline. You see that those that have higher fatigue levels are the ones that are improving the most. This is consistently what we see with bezisterim across the various trials that we have conducted. So all we really did is we said top half of patients. So patients who have greater than median fatigue are considered to have high fatigue. This is what you find. This is a summary chart. Let me just go into the next one to give some bit more detail. So this chart looks only at the patients who have high fatigue, so the 112 patients with high fatigue level. What you see at the top in blue are five different endpoints that reaches statistical significance, the top three of which are all fatigue. The next one are the patient's impression of how they're feeling and the clinician's impression on how the patient's doing. You notice that the Cohen's d is higher. It's double what you see before. Like I mentioned earlier, all five of these metrics reach statistical significance. So what this says to us is that if you look at patients that have fatigue symptoms, bezisterim treatment helps them improve statistically significantly on fatigue. In addition, we get trending statistics on three additional endpoints, being malaise, sleep, and the patients also just feel better. It's less severe for them. So this makes intuitive sense, right? Because all of these endpoints are fatigue related, right? If you are less fatigue, frankly, sleep goes along with it. If you're sleeping better chances are you're going to be less fatigue. Now let me move on to the next group, which is the malaise group, as measured by the endpoint DSQ-PEM. Again, you see that the Cohen's d dramatically gets better. The patient improves statistically significantly on malaise. I'm sorry I don't have a laser pointer that could point out here. But the fifth item down, you see that on PEM, patients statistically significantly improve on malaise, but they also improve on cognition or brain fog, which makes intuitive sense. I do not know about you, but sometimes when I wake up in the morning and groggy, did not have enough sleep, I just do not think as clearly, right? Unfortunately, this is a patient population that lives with that constantly. By being able to help these patients with high post-exertional malaise, bezisterim appears to be helping not only on malaise, but you are helping them with their brain fog, right? Four additional metrics gets to trending statistics. Lastly, let me show what happens to those with brain fog. Again, the Cohen's d gets dramatically higher, bezisterim treatment appears to help statistically significantly on four different brain cognition endpoints. The patient also feels better on fatigue as well. So very consistent findings that if you have the symptom at the start of the trial, bezisterim treatment appears to give you statistically significant advantages over those on placebo. It is helping you improve upon your symptoms. Safety tolerability, it is very comparable, bezisterim treatment versus placebo. That is actually very important when you look at what really goes on with these patients. You see that 96% of the patients are currently taking one or more medication, right? The medication classes that they are in, there are 13 different classes representing 873 different medications are here. The last thing you want is to introduce onto this polypharmacy situation, a drug that could have safety concerns or drug-drug interactions or safety concerns. That we did not see. As you can see from the safety information here, it was just very benign, very similar to placebo. We look at this, and our interpretation is that bezisterim appears to be helping Long COVID patients with high baseline symptomatic burden, right? Baseline fatigue, post-exertional malaise, and cognitive impairment really drives the patient's ability to improve on that endpoint. The key point is you have to have the symptom to improve, and if you are not affected by the symptom, there is little room for you to improve. The bezisterim safety and tolerability is good. It allows for potential use with the patient population that is already taking many other medications. This is a very compelling signal that warrants advancing it to confirmatory phase III trial. This is what we interpret, right? We also have in the field. We have had the opportunity to share this information a couple of days ago with our investigators and our advisors, whom those of those you can see their names are listed here. We asked, among other questions, we asked every one of them, What would you do? Would you advance this to confirmatory phase III trials? All 12 out of 12 of our investigators and advisors strongly suggest that we move this on to phase III because this is literally the first medication we believe that has been shown to show a benefit on these neurological symptoms of Long COVID in any patient population. Looking ahead, we still are waiting for biomarker data to come back. We are hoping to get those in the next couple of months, and we will marry in the various biomarkers data with these clinical endpoints. We still have to plan for two different end of phase II meetings with the FDA, of course, for our Parkinson's trial that we have reported out about a month ago, and now our Long COVID trial. We have to plan for phase III, potentially pivotal registrational trials. We have lots of data to continue to analyze and a number of partnering conversations that we need to do in due course, right? Just to give you a pipeline overview, bezisterim is being developed for Parkinson's or Long COVID. We also evaluating in Alzheimer's disease in due course as well. We also have another asset, BIV201, for ascites. All of which, any one of which of these indication are significant commercial opportunities as well. With that, I thank you for your time. What I would like to do is turn the floor over to Michael. Tara, can you please stop the slide share, and let's bring Michael on screen. Michael Peluso is a clinical investigator from the University of California, San Francisco. He has been involved in a number of Long COVID trials. Let me turn it over to Michael. Could you please introduce yourself real quickly and give us your take on the data as you've seen it here? Yeah. Hey, everybody. I'm really happy to be here. I think this is a really exciting day for Long COVID patient community and Long COVID researchers. I've been working in this field for six and a half years now, since the very beginning, and there's been a lot of disappointment. These results, when I saw them, are shocking to me in the best possible way. This is really the most promising data that I have seen in this field. I'm really excited to see where this goes. Thank you, Michael. Can we bring Ezra on camera as well? Ezra has been working in this field for quite some time. He's a leading advocate for Long COVID patients. Ezra, can you introduce yourself a little bit and give us your take on this? Sure. Thanks so much for having me. My name's Ezra Spier. I'm somebody living with Long COVID. I've been sick for just about four years, and there are so many millions of patients like me who've been really struggling to get the care and support that we really need to live our lives and contribute to society in the ways that we want to. I'm very involved in Long COVID clinical trials as both a participant in trials and also I'm an advisor to different trials. I think one of the things that's been very challenging is the heterogeneous population. We know in the community that many of us try very wide variety of repurposed medications that already exist and able to be used off-label, and not everything works for every person. When we look at the research that has come out, it's been very challenging. Even large trials have not shown consistent impact on patient populations. Even within subgroups, oftentimes there's just not much of a signal. I think what really stands out to me about the data that have been presented today is that it shows a very clear direction in the data. To me, that is almost more interesting than meeting a particular threshold. Because what I know as a patient based on the community is that we need to figure out for whom is this going to work best, and what dosage is going to work best, and all these questions that come up, but we need to have a signal first. I think this really gets me excited about the additional discoveries we'll hopefully be able to make. I think it gives the community some hope because we've been seeing trial fail after fail after fail. Seeing something that provides demonstrated impact, I think is really exciting. Thank you, Ezra. All right. Tara, can you please bring everybody on the panel on for, and let's move on to the Q&A. There are a number of questions I'm sure that's been posed. Great. Yes. Thank you, Cuong. As a reminder to our audience, if you would like to submit a question, please use the Q&A text box at the bottom of the webcast player. Please hold for a brief moment while we pull for questions. Our first question, was ADDRESS-LC statistically powered to detect significance in the full ITT population, or was it designed from the outset as an exploratory signal finding study without that expectation? Why was it designed without a single pre-specified primary endpoint, and what does that mean for how the FDA will interpret the results? Well, thank you for the question. The study was designed at the outset to be a phase II signal finding study. This was a significant size. This is quite large. It is larger than a normal phase II study, because frankly, we did not know what to look for, nor did we know what to find. That is the reason why we had 22 different endpoints. The beauty is that when you are in phase II exploratory, you do not have to declare a single endpoint. That is why we declared all 22 of these different endpoints as, frankly, we are on a fishing expedition to basically see which endpoint could show a difference for those that are on drug versus those that are on placebo. We did not know what to expect. The fact that we ended up finding a signal here that showed that it was effective for 78% of the patients in the study was astounding. This is a huge signal, and 78% is a much, much larger responder population than you would typically see in any kind of trial. I hope that answered your question. Great. Thanks, Cuong. The next one: Since this study is described as hypothesis generating, does it make more sense for management to conduct another phase II trial in patients with high symptom burden rather than moving directly to a phase III? The purpose of a phase II trial is to give us the information so that we can move forward to design and size a phase III trial. We think we have that information. Let me ask Michael and Ezra to comment. They've worked on more Long COVID trials than I have. Right, so Michael? Yeah. A couple of points I would make from this discussion. There have been, at this point, a few dozen Long COVID trials of other agents, and really none of those have had results that are as consistent and as compelling as what I'm seeing here. Often in these trials where you have lots of endpoints, you're kind of contorting yourselves to do all of these exploratory analyses, and maybe one thing sort of pops up as interesting or compelling. In this study, it's a very sort of logical, easy to understand partitioning, stratification of the participants. Those with the most severe symptoms and the most area to improve. The results are consistent across almost all of the outcomes. It's really a very kind of simple, in a good way, story to have results that just intuitively make sense. From my perspective, that gives this group a lot of direction on how to think about a phase III study. What I would say, from my perspective as a clinical trialist in this field, is that I think there's enough here to thoughtfully and carefully design a phase III study that could be really a definitive trial. Ezra, anything to add? Yeah, no, echoing what Michael just said. Definitely agree. I would be concerned in a situation where a phase II trial had less compelling results, to be honest. I think that this is compelling enough to warrant a probably larger population that we're looking at. It gives us some areas to focus in on. There's still potentially opportunities for deeper dives into certain aspects or subgroups of the population. We'll leave that design up to the experts, of course. I think the other thing that's really important to keep in mind here, and I'm not coming here as an investor, I'm coming here as a patient, is my community is really struggling. We really need assistance. I think one of the aspects of the results that really stick out to me is the particular symptoms that seem to be improved with the drug. Symptoms like post-exertional malaise, where a small amount of exertion can create a disproportionate amount of fatigue and other symptom exacerbation, really debilitating symptoms. To speak for folks in my community, we're really looking at moving towards a potential FDA registration for a drug if there's not a really important reason to do that additional work. I would, on behalf of my community, encourage expediency wherever possible. Thank you, Ezra. Great. Thank you for the responses. Our next question: Can you describe the biological characteristics of the pre-specified subgroup that demonstrated significant clinical benefit, and did treatment-related changes in inflammatory or neurodegenerative biomarkers correlate with the magnitude of clinical response in those patients? Actually, Tara, can you please bring back the slides? I think that this question is best answered by looking at the Venn diagram and the, what we call the forest chart. The baseline characteristics are all defined by three metrics that gets at the symptom. One is fatigue as measured by PROMIS Fatigue, as the endpoint, right? And here we just took the median. If you have higher than the median score of 65, you would consider it to be high fatigue. On malaise, post-exertional malaise, we used the only tool that's available, something called the DSQ-PEM, right? And if you were in the top third, you were considered to be high on post-exertional malaise. And on brain fog or cognitive impairment, we use something called the Cogstate Batteries to measure objective cognition. So we give a person an iPad and give them mental exercises. We give them exercises to do, and various things are measured to see how long it takes you to do things and so forth. It all gets at brain fog. Can you do it quickly, slowly, and so forth? So that objectively measures your cognitive ability. It's as simple as that. And here, again, we use the median as the cut. And those three endpoints were used, those are the three most representative endpoints to define the cutoffs, if you will. And then you can see on this chart, we call it the forest chart. This is a summary of what I showed you earlier. If you have high fatigue when you started the trial, you saw statistically significant improvements in five different endpoints, three of which are all fatigue, directly measuring fatigue, then two of which are just measuring how you feel and the clinician's sense of how you're doing. If you look at the high malaise group, you improve on malaise, statistically, DSQ-PEM, the fifth line item down. But you also improve on brain fog as well because you're just able to think more clearly because you're just not tired and malaise-ic. Right. And lastly, if you have high brain fog or cognitive impairment, you improve on four different endpoints looking at brain fog with statistical significance. Right. I hope that answered your question. Let's bring the panel back up, please, Tara. Great. Thanks, Cuong. The next question, what is the biggest piece of evidence from this trial that gives you confidence bezisterim can succeed in phase III? Actually, let me ask Michael to comment on that, and then Joe. Two things I would say. The first thing is that the effect sizes are pretty compelling. Often we're reporting out these sort of minuscule effects, and here across all of the domains that were mentioned, the people who responded seem to have this moderate high effect, which I think is really promising and suggesting there's a real tangible benefit that could be present here. The second thing I would say is, we're mostly focusing on the potential efficacy outcomes here, but the safety data are actually really important, right? I'm a physician. Safety always comes first. The safety profile in this study seems really excellent. This is a patient population that can be very challenging to provide treatment to because people are often very sensitive to the effects of drugs. As was mentioned, there are also concerns about interactions between different medications. There is just no signal of any of that in this study, which makes me think that should the efficacy be proven, this is a treatment that could actually be implemented and scaled and given to people. I really think there's a really promising path forward here for those two reasons. Thank you, Michael. Joe? Yeah, I think you need to look at safety, as Michael said. That's the most important thing, because without that, really, you don't have an intervention. Safety first, of course. I'm also looking at directionality. I'm also looking at confluence, and I'm also looking at the agreement between subjective, which is what the patient, the individual tells us, as well as what the computer tells us. In that case, the cognition. We see this really nice confluence of effects that link fatigue, that link cognition, that link malaise. They all go in the same direction. As Michael said earlier, it's not just one thing that sort of sneaks across the finish line. It's the overall projection. If we were to look at that initial graph, that initial graphic where everything moves in one direction, but we don't quite get a statistically significant endpoint among those 21 or 22, that's because we're being incredibly diligent here or being incredibly conservative. Because if you look overall at that pattern, that pattern doesn't occur by chance. It just doesn't. I like the fact that, again, you've got this mix of objective, subject, the patients feel better, the computer shows that they are thinking better, that they're reacting more quickly, memory improves, and then again, the drug is safe. I think it's quite compelling and I have to agree with everything that Michael said here. Great. The next question, given there are currently no FDA-approved treatments for Long COVID, does BioVie plan to pursue breakthrough therapy, fast-tracked, or other expedited designations for bezisterim in this indication? Right. Penny, would you like to take that? Yes, we would. We will pursue breakthrough therapy. We believe the results are very compelling. There is a coherent clinical signal here, and is clear in the most severe population. We did not believe, first of all, that the design of our trial, which required monthly visits, would enroll such severe patients. As we are blinded and watching the blinded data, we saw these severe patients move. Of course, we did not know if they were in placebo or the drug arm. If we look at fatigue alone, the top half with the worst fatigue burden, you are essentially three times more likely to have a dramatic improvement on your fatigue almost 1.5 standard deviations, than you are in the placebo arm. We think the whole signal is just so coherent. If you enrich for cognitive impairment, you see movement of statistically significant improvement in the objective cognitive domains. We think it is fantastic data, and we are very excited, and we will pursue breakthrough. Great. Thank you. The next question, will the phase III trial enroll only the high symptom burden subgroups identified here? If so, how does that affect the addressable patient population enrollment timeline and trial size? That is a hard question. I will give that to Joe. The answer is we will certainly bring in the more severe patients. That is clear. We will also bring in some of the patients who do not fit that because when we go to FDA is going to want to see that what we saw in phase II is replicated in phase III. Because FDA is clearly interested in the overall population. They want the broadest possible label for the greatest number of individuals. So they are going to ask us to look at this again. This is not unusual for a clinical trial to show effects in the most severe patients. We see that across neuroscience. We see this in other indications as well. In part, it has to do with how well you are to begin with and the body's natural ability to heal, as well as the basics of biostatistics. I think the hint may be in that initial visualization we show where everything begins to move to the right. That suggests the entire population is getting better, and that is just sort of the nature of biostatistics. My hope is the FDA will be consistent with what it has done in the past, that a signal that shows itself in the most affected patients is also shown to generalize in the full population, and everyone ends up benefiting. That is my hope and expectation. Great. Thank you. The ADDRESS-LC trial was fully funded by a U.S. Department of War grant. Will any portion of the phase III costs be covered by that award or other non-dilutive government funding, or will the company need to fund the trial independently? Penny, would you like to get us started on that? Yes, we're definitely going to pursue follow-up funding from the CDMRP. We will also look potentially to the NIH RECOVER for funding. We believe this is very exciting and in parallel, obviously, we will raise money to fund this trial. Ideally, this trial will have some element of decentralization where some cohort of patients, the most severe, can be treated in their own homes. Ideally, we'd also like to include an open label extension so that anybody in the placebo arm can roll over into and have an opportunity for treatment with bezisterim in the bezisterim arm. Not trivial. We will pursue. We think it's very exciting data and a huge unmet need. We think this is the first really strong signal in this patient population, and we will pursue all avenues. Great. Thank you, Penny. The last question here, what are the next concrete milestones from here for the phase III protocol, financing, or partnership? Well, we just unblinded the data, so please give us a little bit of time. In the coming weeks, we will be working with Michael and other experts we've been working with to design the phase III approach, right. We have, of course, started thinking about that, but this is where we have to be extraordinarily thoughtful and double-check, triple-check everything because the phase III is the trial where you say, "This is our endpoint, and the only objective here is to get to P equal 0.05 or less." We believe we can get there. But give us a little time to design that, and we will then go and have an end of phase II meeting with the FDA to completely agree on that endpoint. Then we will start. We've had some conversations with other pharma companies, and they've been waiting for the results. Now we can share the results, and we'll see where those conversations start. Eventually, we'll go raise some money, but we have no imminent plans right now. We have sufficient funds to last for a while. We're just going to really focus on, right now, on the patient community, on the research community, sharing our data, and getting the word out on what this thing could really mean for the patient community. We're really, really excited about this, if you haven't picked it up by now. I'm particularly excited because this, we believe, is the first therapy that has been able to show a benefit on any of these Long COVID symptoms. Not just one, not two, but all three of these Long COVID symptoms for a large portion of the population here. 78% of the patients have at least one severe symptom, and that is how large of a population we believe we can help. We are very excited with that next step. We are just going to keep our heads down and do the work that needs to be done. With that, let me thank everyone for joining. Let me thank, especially Michael and Ezra for joining us and sharing with us in the group your experience and your comments. Thank you very much. We wish you have a great day.