Okay, so let's get started. My name is Yanan Zhu. I'm one of the biotech analysts here at Wells Fargo. It is my great pleasure to introduce our next company for this fireside chat session, Sana Biotechnology. We're fortunate to have CEO of Sana, Steve Harr with us here. So thank you, Steve, for joining us. To kick us off, could you give us an overview of the company's platform and programs? Sure. Yanan, thank you, first of all, for having us. And, you know, thank you, everybody, for joining us in the audience here and in the webcast. And I'm sure you know we'll be making some forward-looking statements, and so, please take a look at our 10-Q. We spent a lot of time on that, on the risk factors. So, the company was really founded with the idea of trying to, you know, create one of the really important companies in the cell and gene therapy era. And obviously, one of the great things about this space is that we get the privilege of really starting out almost every endeavor with curative intent, right? And I think that's something that's really fun about cell and gene therapy. One of the challenges of it, though, has been, you know, both the capital intensity of it very early, as well as, you know, really accessibility. So we kind of really go after those challenges from the get-go. And within the gene therapy space, we don't spend much time on that. We have a platform around delivery. I think, you know, many of you probably recognize that you can do more or less anything you want to with a genome in a petri dish. The real challenge has been in vivo delivery. And so what we really set out to do is to be able to deliver any payload, RNA, DNA, protein, to any cell in a, you know, specific and repeatable way. And the great thing is, every time you accomplish one of those, you really create a whole new category of medicine. And we've made a lot of progress on cell-specific delivery, and we can deliver, you know, pretty much any of those payloads. You know, we slowed down one of those programs a year ago. We didn't have the capital and bandwidth to push a fifth IND in the clinic in 2023. But you expect to see more from us around that in vivo delivery capability. And the other, and what you've all of the clinical programs relate to is something that we call the hypoimmune or cloaking technology. I think if you take a step back and within cell therapy, our goal is to be able to deliver, you know, a cell that engrafts, functions, and persists. And to make a cell really, to do that, you have to do all four to be important, right? The biggest challenge, generally, in the cell therapy or transplant space, has been persistence. You know, particularly, you put, you know, my cells into you, they will be killed, right? The way the field has accomplished that is either profound immunosuppression that turns off the immune system, or through autologous cells. Unfortunately, both of those really limit the number of diseases and patients you're able to help. The real foundational capability we went after in this portion was the ability to hide cells from allogeneic or immune recognition and rejection. I think we've made a bunch of progress in that. The immunology here, very simplistically, two arms of the immune system. There's the adaptive immune system of B and T cells, and there's innate immune system of NK cells and macrophages. And it's actually relatively straightforward in the era that we live in to deal with the adaptive immune system. You knock out MHC Class I and Class II, and really, you don't have an immune response, adaptive immune response. The challenge has been the innate. Once you do that, you turn on the innate immune system. Cancers and viruses figured out that long ago, right? And so we evolved things like natural killer cells that will get rid of those cells. So the key insight of this platform or technology is that overexpressing CD47, in conjunction with knocking out expression of Class I and Class II MHC, really, hides these cells from the immune system. And, you know, we've shown this now in published papers, in Nature, Cell, Science journals, I mean, we have many, many papers. And we've really... I think we've kind of, you could argue, proven that we can overcome allogeneic rejection in non-human primates. We've proven we can overcome this in mice and humanized mice, and the real key is how well this translates into people, right? We now have four separate programs ongoing in seven different indications in human testing. We've shown a little bit of human data early last year, and it was in an allogeneic CAR T-cell in patients with lymphoma and chronic leukemia. Four patients, you saw what you hoped you would see. It's early data. You know, two of them had a complete response, another had a partial response, and well-tolerated, and the cells were generally not recognized by the immune system, right? And so, that's really what we were hoping to see early. It doesn't tell you we've got a great drug yet. We've got more work to do. But that reads across into what we're doing in other areas. And I'm sure we'll get into it, but. And we have three areas, really, where we're making drugs clinically. One is Type 1 diabetes. I think most people would recognize that Type 1 diabetes happens because the immune system kills all the patient's pancreatic beta cells. So a patient can no longer make insulin to deal with glucose spikes. And a hundred years ago, that was deadly. Today, it's a chronic but difficult-to-treat disease. And the goal here is, from a single treatment, to be able to put cells into a patient and make them euglycemic or normal blood glucose with no insulin and no immunosuppression for life. And I think we'll know if that's possible here very soon. The second platform is in B-cell-mediated immune diseases. That's diseases like lupus, multiple sclerosis, myasthenia gravis. You know, there's been some really exciting data in autologous CAR T-cells to date. Our goal is to do this in a more predictable, scalable way with allogeneic CAR T-cells. I can get into why you should probably believe this will at least work somewhat. We'll know better this year how well it's working, our first clinical data. The third is in blood cancers, lymphoma, leukemia. We have two different drugs there, a CD19 allogeneic CAR T-cell, and another one targeting CD22. Hopefully, we'll get you some data that help you to begin to understand where those are as well in the not-too-distant future. So with that, I'll pause on the overview and turn the microphone back to you. Great. Great. Thank you for that, very helpful overview. I wanted to talk about the diabetes program. Yes. But I think important nugget might come from the oncology program, so let me ask that question first. Okay. In your oncology, because you have longer follow-up for your oncology study, do you see your engineered cell in these oncology patients, for example, twelve months out? Because some of the autologous T-cells, as you know very well, autologous CAR T can be around, still sticking around after one year. Wanted to see if you have seen that kind of observation in oncology? We haven't discussed any of the CAR T persistence data yet. We've shown some clinical responses, some safety from four patients very early in the study, and a little bit about the immune response to the cells, so stay tuned. Got it. But you're right, there's a nice read-through from that. I mean, I think one of the reasons, though, that so many people are focused on our Type 1 diabetes dataset is it is a cleaner, and it's a hot test. It's a higher bar, right? There's in oncology, you lymphodeplete people, right? So they lose some of their immune cells. We target B-cells with CD19, so they, who make antibodies, is compromised. In the Type 1 diabetes space, we actually are gonna be putting cells in that have a preexisting immune response to our cells, right, to beta cells. So it's kind of an exciting and interesting test to see, and there's absolutely no immunosuppression. So it will be, you know, really kind of, hopefully, transparent and indicative and predictive about the broad applicability of the platform. Got it. Got it. Can you, I think you have some data before year-end. You wanted to show some data from the investigator-sponsored human cadaveric islet cell study. So let's talk about, you know, the manufacturing of the cells, you know, there, 'cause, obviously this is the important readout and proof of concept, even though this is not the construct or the cell type you're going into, maybe the construct, but not the cell type you will eventually deliver, develop. But this is an important readout for proof of mechanism. So I was wondering, could these human cadaveric cells be amenable to all those manufacturing and engineering processes you're doing- Sure so that we know the cell that goes into the patients are ready to do the job, and if you happen to have a negative result, it shouldn't be due to a lack of engineering and Sure - cell manufacturing. So let me take a step back for the group. So I think, so about for the last twenty years or so, people have been doing transplants of cadaveric islets into people with Type 1 diabetes, and they've shown in many cases that patients become insulin-free and have normal blood glucoses. The biggest challenge with this is that that's neither a scalable nor is it a replicable manufacturing source, right? The second challenge is there aren't that many patients for whom lifelong immunosuppression is better than lifelong insulin, right? And so, others in the field have shown that you can make a stem cell-derived product, right, into a beta cell, and that you can transplant that, you know, very successfully. And again, though, you have the challenge of the immunosuppression. So our goal of this study is to see, can you transplant these cells and see survival without any immunosuppression? Because if you can, in some regards, it looks like a cure for Type 1 diabetes becomes inevitable, right? It may not be us that actually puts all the pieces together successfully, or if we do, we may not scale it well enough, but it is inevitable. Like, there should be real hope in the Type 1 diabetes community. The challenge that you're getting at is, when we set out to do this is, if you think back, and so let's just say this works, and it's an N of one, right, to start. I've never met anybody who could tell me how you had a false positive, meaning it worked, but it isn't truly true that you're able to hide your cells. But there are many reasons you could have a negative, right? Some would be true negatives. There's an immune response to our cells. Some would be a false negative, which is in, like, a third of these cadaveric-derived cells with no genetic manipulation. They just don't engraft, and so that's really just, you just do it again, right? And then your question, I think, is really important, which is, could you have a false negative? Which is, it looks negative, it looks like there's an immune response, but the reason is because you didn't have adequate engineering of your cells, right? And I think- Right. That is like something that I hate to think could happen. So we think it will take us time to tease that out, right? We think we've eliminated most of the risk of that occurring, right? Because you can always test the immune response against these engineered cells and against the cells, the product, to understand how well they really were engineered, right? But it doesn't guarantee we'll be able to tease that out. So there's some small risk of a false negative. I think we have to be very cognizant of that and work very hard to minimize the risk of that. There is no such thing as a false positive, which is why this works. You know, I think we can all be optimistic about the future for Type 1 diabetics. Again, I think this will take us time. There's a lot of risk in our being able to scale it and things like that, but someone will figure this out. Got it. Got it. Then could you give us the setup for this particular study, as you referred to as potentially an N of one study, in terms of how it is being done, and how should we interpret the results and your progress of- Yeah ... the enrollment, dosing, and all that? So what's done here? This is an investigator-sponsored trial. Okay. Our goal is not to make gene-modified cadaveric islet cells. Our goal is to make gene-modified stem cell-derived islets. But this really, really accelerates the speed of our learning. What's being done here is we have a group of potential donors, people with Type 1 diabetes, who have agreed that they would love to try this or like to try it. When someone will die, their pancreas, we will donate their pancreas, right? That's cadaveric-derived, and then that. It's no different than an organ transplant. Instead of transplanting the whole organ, the cells are isolated. That's a standard protocol that's done hundreds and hundreds of times a year, right? Probably a thousand times a year across the world. Instead of transplant at that point, what we will do is gene modify the cells, right? First, by knocking out two different genes, and then by knocking in another gene, right? And then by doing that, we hope to hide these cells from immune recognition. We then will select, hopefully, for cells that are mostly gene-modified, and then they all sit there in a single cell. When you recluster them, right, into small little pseudo-islets, they're called, right? And then they are transplanted into the arm of the patient. So theoretically, the patient could then, it's just a little incision, cells spread in, stitches made, patient could go home. They won't in this case, it's a phase I first human experience, they'll be watched in an inpatient center for some short period of time. So our goal is to see, because remember, there's no immunosuppression, there's nothing. If you transplant an organ or cells into any of us, we will reject them within a few days, right? So our goal is to see those cells survive and hopefully function. And the easiest way to see this will be radiographically, right? And so just do an MRI, it's their arm, and we can see the cells. That they survive, if we're there, let's just say a month. As you probably know, within a few weeks, but let's just say a month. You can feel pretty good that things are good, right? You'll feel better if you knew they were beta cells, right? So how do you know that these are beta cells? When we make insulin, we make proinsulin, actually, right? And then as it's secreted, it's cleaved into C-peptide and insulin. So if you have measurable C-peptide, you now have evidence that the patient's making their own insulin. So all of these patients haven't had C-peptide for years, long-term diabetes. And so that's an entry criteria. And so if you see C-peptide is stable over time, you can be confident that we have functioning beta cells that have evaded the immune system. So that is what we're really looking to see. You know, there's some chance that they survive, we don't quite have enough because you have to have the, you know. The third thing you could see is you can see the patient's blood glucoses get better, right? And so, you know, they just don't need insulin anymore. They need a lot less to control their blood glucoses. But it's a first-in-human study. The probability that's the dose we end up with is pretty low. I like to tell people if that's their investment thesis, they should just hold off to invest. You know, we'll be doing cartwheels if it happens, just because I think the patient will be doing so much better. I would argue with you because we're not trying to figure out whether cadaveric-derived islet cells work. We're trying to figure out, can these cells evade the immune system? So if they have C-peptide or they're euglycemic, the value of the company is exactly the same. Valuation may be different because I think of the excitement around controlling it, but the value is the same. We're trying to then say, "Okay, great." Our movement in stem cell-derived islets with these, you know, these gene modifications is very low risk biologically, right? There's other risks, but it's low risk biologically. We can get into that program in a minute, but that would be kind of. That's your goal. You want to see. If you see that these cells in a person has evaded the immune system, and they have no allogeneic rejection, they have no autoimmune recognition, that is almost a generalizable result, and we should feel really, you know, optimistic about, you know, where we can take this going forward. Got it. And that data, you haven't given a readout. Is that soon, or? I use the word soon. Soon? I'll let you interpret the word soon. You can interpret it, but yeah, I like the word soon. So the last update we gave was at the beginning of August. We said we had patients on the wait list, and that we hadn't treated a patient at that time. No more updates. We'll tell you when we have the data. ... Got it. And when you record the data, roughly, how long is the follow-up? I think you mentioned the word one month. Yeah, I go, you know, but, you know, I'm gonna leave it somewhat to the scientific team to say it's very clear, right? Clearly, this didn't work. Clearly, this did work, right? Mm-hmm. If they feel really good about it, I think that's when we discuss it, 'cause I think it would be quite material for the company in either direction. You know, a good rule of thumb might be that if you see cells in a month, you should feel like that's pretty clear, right? You may feel better about earlier than that. If there kind of looks like C-peptide's falling, you may wanna let it sit around a little bit longer, that kind of thing. But let's assume it looks pretty good at a month. That's a good time. Again, if they're rejected in four days, it doesn't take a month to figure that out. Mm-hmm. So- Right. We'll see what it takes. And in terms of patient number, I think, you know, perhaps you- What's that? In terms of patient number, I think you mentioned- I think if you, if you see it clearly in either direction, at one, you should. It's pretty definitive. If you don't know, it'll take more patients, right? They're great. They just do a graft and do more. They do another one. But if it's like, if there's autoimmune recognition, we have to deal with something. If there's allogeneic rejection, we have to deal with something. If the cells live, it's gonna be generalizable. Any of those results are pretty generalizable. Could there be a non-binary outcome, right? Yeah, that's what I'm talking about. Cells in a graft. Let's just say, we don't engineer the cells well enough. But otherwise, it's gonna be very clear. It's pretty binary. Got it. Got it. Great. And you do feel confident about the CD47 expression level? 'Cause you-- This is not dose ranging, but in terms of your transduction and expression level, you do feel confident that that's high enough to inhibit NK cell killing? It's an important question. So one of the real challenges here is you have to get the level of expression every one of our cells expresses CD47, every one of them. It's the recognition of self, right? And if you put, you know. And in fact, so if you look at, like, what's special about a red blood cell, it has no MHC Class I, it has no MHC Class II, and it markedly overexpresses CD47, right? Right. You can transplant red blood cells as long as your blood count, as long as your blood type is the same across any of us. And with any of us, what leads to turnover of red blood cells is CD47 is modified over time, right? And so that level is important, and it's cell type specific, how much you need to have, right? And so we think we understand this pretty well. We think we've got a good manufacturing system, but this isn't like a phase, you know, a commercial drug. This is an investigator-sponsored process. So we do test CD47 levels. I mean, I think, is there some risk that they modify in vivo or something like that? Those are things that we would look at to understand, hey, what happened here, right? But it's part of the release criteria is adequate CD47 expression. Got it. Great. So maybe let's just touch upon the SC451- Yeah. which is your, you know, internal program you want to move forward for Type 1 diabetes. Yeah. Where is that program? And once this gating factor is cleared, how does that program proceed? Yeah. So SC451 is a gene-modified stem cell that is differentiated into pancreatic islets, right? Pseudo-islets. And then they would be transplanted into a patient, and the goal would be a simple intramuscular injection, and the patients would be euglycemic or normal blood glucose with no insulin and no immunosuppression, hopefully for life, or at least for many years. So we kind of look at there are four big scientific questions we have to answer to really make this into a really important product. 'Cause you already know that most of the things can happen, but the first thing we need to do, that we have to deal with, is make a gene-modified, pluripotent stem cell master cell bank, where we're comfortable with the genomic stability over time. If you think about that, every time our cells divide, you make kind of one or two mistakes. No big deal, right? But in our body, we have almost every single gene mutation. And the challenge here is that you're making trillions of cells over time, trillions and trillions, right? And you are doing that in the context of media that enriches for cells that grow quickly. So you want to avoid clonality or creation of tumor cells, right? So that, you know, that proved to be a bit more challenging than we thought it would be or than we... You know, early on. We think we've nailed it. I wouldn't, you know, guarantee that yet, but we think we've really nailed that. And so, you know, stay tuned. But that has been what's taking us longer than we expected. The second scientific thing you have to grapple with is making the cells at adequate purity, potency, and yield to run a phase one study, right? I think we got that, right? I think we've got that one. The third thing you need to do is make the genetic modifications to overcome allogeneic and autoimmune rejection. We'll learn that soon, right? So the fourth thing we need to do is make drug product in adequate purity, potency, and yield to be commercially important. We got a long ways to go there, and, you know, I like to be very clear, we're underinvested in that today. You know, and that's something that, with hopefully good data, we'll be able to put more resources towards to really, you know, build that scale. And the scale here is not build more factories. The scale here is not buy more machines. The scale here is a scientific problem and challenge. So it's gonna take apply a real scientific insight to really push this into another level of what we can do. And I should add, or else to say, when I say yield, it's yield at cost of a reasonable cost of goods, too. I mean, I think, you know, you can always just build out, right? But you wanna we need to build out first. In that case, that number four leg of the whole construct whole program, it sounds like that is that going to gate the IND-enabling studies? That does not gate anything in the first human. It. There's some gate around that for, you know, probably registration studies, right? You have times when you can make changes to your manufacturing process. Ideally, you make substantive changes, you know, before you go into a registration study. There will be the other times to do that post-commercialization, but you have to really understand your product to do that. Right. Okay, so you could maybe- There's nothing related to the IND that's gated. Right. Okay. It's time. Like, I stopped trying to predict when it was gonna be because I've been wrong enough on this one. We've kind of committed to, if we think within six months, we'll tell you. So I can tell you we're not within six months in our mind, and that's kind of. We'll kind of leave it at that, and then we'll figure it out over time. Got it. Got it. Let's touch upon the autoimmune side of the story. Yeah. I think just a few bigger picture questions. There are several modalities just within the last year, autologous CAR T, allogeneic CAR T, which is what you're developing, and now bispecific antibodies. You probably add in NK cells, you know, some other things in there, too. Of course. You keep going, right? Yeah. Right. Yeah. How do we think about all these modalities, and what might be the winner solutions? I would start by saying, just generally in the autoimmune space, it's unlikely that there's a winner, right? You know, I think with all of these, what we've seen is that different patients have different biology, and that there's the need for, let alone the space for, more than one modality, right? And that relates to both their biology and patient preference, right? I mean, the simplest example, some people may not want lymphodepleting chemotherapy, right? Other people, you know, may not want long-term infusions, right? And so we're gonna have to... The people will have their choices. The second, I think you have to figure also what's your goal of therapy, right? So some goal of therapy will be to hold disease at bay, right? Other goals of therapy will be, well, I think of it as the control-alt-delete of your immune system or your B-cell repertoire, right? And so that goal is to have a disease for... Sorry, drug-free, complete remission of your disease, right? There, I actually think that the biology is very straightforward. You're gonna have to create some short period of B-cell aplasia, right? Knock out your B-cells, and then they'll grow back, and hopefully, you know, the pathogenic ones will be gone or held at bay. You can probably get complete responses without doing all that, right? It's a math game. You got to get rid of the pathologic B-cells. So the more of them you get rid of, the more likely it is you get rid of the bad ones. You could get lucky and do it with really, you know... So, and we'll get at how frequently do you have a complete response. I would bet you, you know, I could be wrong, that the modality most likely to get you, you know, consistent B-cell short-term B-cell aplasia is a CAR T-cell. It has a couple of things that go for it, right? One is volume and distribution. The beautiful thing about T-cells and the risk of T-cells is they go everywhere in your body, right? Antibodies, other cells don't go everywhere. They're kind of designed to stay in your bloodstream. And they can get in the bloodstream, lymph node, bone marrow, spleen. That's really kind of it. And so many of the pathologic cells reside in tissue-resident germinal centers. All right? That's where plasmablasts are. So that volume and distribution is really, really important. The second is you have to have enough drug on board to make it happen, right? There are three times, it's called three times ten to the eleventh, plus or minus, B-cells in your body. That's three hundred billion, right? And so if you want to deplete them all, you have to figure out, how am I gonna get enough drug on board to make that happen? The beautiful thing about T-cells is when they're activated, they divide, they kill, right? So you get logarithmic expansion of your CAR T-cell, which allows you, for a relatively digestible dose, to be able to target all those cells. So some of these modalities, I'm sure, will work in some patients. Some of them will be maybe not... You know, will have factors that work better in some patients than what CAR T-cells do. But my bet would be that CAR T-cells are the best. Now, what's the difference between autologous and allogeneic, right? We scaled. Their advantage, they work, right? So we need to show that we work as well as they do or close to as well as they do, because we have the scale nailed, right? And so I think it's most likely here that one of the things that we learned in oncology is these cells have to stick around for a while to have time to survey the whole body and get rid of all the tumor cells. Now, to get rid of, you're gonna get rid of most likely all B cells and tumor cells to do that, all right, CD19. It's probably true that you have to stick around a lot less long to get rid of all B cells, right? So the persistence that you need is probably less, which, you know, may mean that more allogeneic players can compete with us, right, than could in oncology. I mean, I think that's just something we'll have to think through. You know, so that, that would be my answer. You know, there's kind of I love what we're doing here. I think the probability this works is quite high. You know, there's some reasonable chance that we end up in a dogfight for a whole bunch of these with different modalities, different types of drugs. There's some reasonable chance we have the category killer because we've scaled it, we're making it work, and if it really, really works and has a high durable drug-free remission rate, it's gonna be hard to grapple with. Got it. Super helpful. And you, you are running a phase one? What's that? You are running a phase one study. We're running a phase one study, yeah. Right. Three autoimmune indications. Yep. Anything you can tell us about enrollment and what kind of data you could have this year? Yeah. How many patients? So enrollment, the only thing I can tell you is we. You can see on ClinicalTrials.gov, we kind of dosed our first patient in the May-ish timeframe, right? So that's in public. You know, we're in phase one dose escalation, which means the fastest you can enroll a patient is every four weeks. That never happens, right? You screen, then you went for the apheresis, then you give the CAR T, and then you start over again. So it's every six weeks or seven weeks or something like that. So it's not gonna be like. You can't expect. Once you're on a dose escalation, you can, you know, move more quickly, but that's once you clear a dose, you can dose expand within that dose, or you can go to the next dose, right? Or you can do both, so in parallel. So that gives you a sense of numbers. I kind of think of it very simply. There are two important questions that you have to answer, right? You already know from the oncology data we've shown you that we can deplete these cells, right? So the question is, can you do that in the autoimmune setting safely, and does that translate into clinical benefit? So that's reasonable to answer this year, right? Second question: How does this all compare to these other modalities? Where do you fit? That's gonna take us some time to answer, both because we need more data, and we don't understand what the other things do yet either, right? And so, that's gonna take us more time. So if you want to know, a reasonable expectation would be, "Hey, does this stuff work or not?" You can probably tell, right? So that would be a reasonable way to think about it. Got it. Very helpful. Yeah. In the remainder of the time, I'm just curious your thoughts on the B-cell malignancy side, the oncology side. The question I'm really curious is, what is your go/no-go criteria for allogeneic CD19 CAR T- Yeah in B-cell malignancy? I think I'll go through. Like, I'll just say each of these. What's beautiful about the Type 1 diabetes space is, if it works, it's gonna be spectacular, right? The hard part is you don't know if it works or not, right? You know, B-cell-mediated immune diseases, it almost certainly works, and if it does, you know, it's probably gonna be in a reasonable competitive position, but you know, you don't really know where it fits. The hard part about oncology, kind of already know it works for four patients, but it's a very competitive space with a high bar to move forward, and we may or may not hit that bar, right? And there are a couple reasons why we may or may not hit that bar. We may not get there, and the second, we may get there, and we may not have it, it may not be the best use of our capital to keep going forward, right? So the bar here, from our mind today, is you got to show comparable, complete, durable responses to what's seen in the autologous setting. And that will be an important drug. It will still be a dogfight, though, right? Because they have, you know, now many, many years of survival data, right? That will take us time to get. And so we have to really make a decision around, is this an important enough drug that we should go for it? If you really spend time in the marketplace talking to physicians and things, if it hits that bar, it will probably be a very important drug, right? You know, we'll have to figure out if that's the best, if we have the capital things to do that at that time, but so we have both of those hurdles we'll have to clear to go forward. The nice thing is, you can kind of guess already that you have a couple of complete responses out of the first few patients at pretty low doses, right, so it probably does something at least, right? Got it. Which in oncology is always a nice thing to see, right? You've helped some patients. Got it. Got it, got it. And the next data update, would we see it at ASH or? We hope to have some data this year, you know, wouldn't hide it up. I do think one of the key questions is that we just set reasonable expectations, right? And if the question is durable, complete responses, it will take us some time to get there, right? Unfortunately, there's no, like, mechanism for accelerating time. And when we gave data in January, there were four patients in it. So mathematically means that you can't have more than four patients in a year, even at the end of the year, right? Can't happen. So, that is kind of where we are. So I think that if you really kind of think through that one, it may be that the best, you know, time to learn is in the future, right? It's gonna take us some time to define that. Got it. Got it. I think speaking of time, we're out of time. We're out. out. We got the red light. Thank you so much, Steve. Thank you. This was a very interesting- Yeah -meeting. Thank you, everybody in the audience. Appreciate your time and attention. Thanks, everyone.