Good day, everybody. Thank you for joining us for our chat with Perspective Therapeutics. We have with us here today, Thijs Spoor, the CEO, and Annie Cheng from IR. Thank you for joining us. I wanted to start by asking you a question about Perspective and what makes you different from other radiopharm companies? Thanks, Louise, and thanks for hosting us for this. We love telling our story, and we're really passionate about what we do and how we do it. I appreciate there's a lot of interest in radiopharms right now. What differentiates us is we actually have a really compelling choice as we think we've made for isotopes. I think every company you speak to says they're isotope agnostic, but they're gonna make choices on what they wanna do and why. In our case, we've really said we wanna optimize our molecules. We actually spend a lot of work at first principles, really thinking through everything that we want to do with design the molecule, how we choose, you know, targeting a peptide, how we choose a linker, how we choose a chelator, how we choose the isotope. But all these things swirl together to make sure we're making best choices for dealing with a specific tumor type. And so we can't make a broad statement, you know, this one isotope or linker is best for all cancers. Cancer is very specific. What we differentiate is peptides with composition of matter IP, that use lead-203 and lead-212 to both image, treat, and target disease. So treat what you see, see what you treat, and we sort of pull all these things together. We can do that with an integrated delivery chain that actually brings from isotope all the way to tumor and outside the patient to make best possible choices as we go through. So there's a lot in there, and I'm sure we can kind of pick those apart through our conversation. Okay, let me start digging in a little bit. What's the ideal profile for radiopharmaceutical in your mind? So the ideal profile is you wanna actually have something that's gonna come in, hit the tumor hard and fast, and then disappear after it's done its job, right? So you wanna try to really think through, how do you actually go in and do that in the best possible way? And so for a radiopharm, if you're dealing with solid tumors, and tumors that are clearly defined with surface-expressing proteins, the ideal radiopharm in our mind is that goes, hits it quickly, very rapid accumulation on tumor, very rapid elimination from the body of any non-targeted radiotherapy, and then delivering a hard, fast punch that knocks out the tumor. Hopefully creates a lot of neoantigens, lets the immune system kick in, lets the body kick in and help heal, and once that's done, completely evaporates so that the body can heal itself without sort of fighting against the radiopharm on its own. So as we really look at how we do that, if we can actually design that peptide to go in very, very quickly, the beauty of how we actually image is we can see in a patient real time what's happening in that patient. We can look to see the in vivo fate of every molecule. So we can actually prove this concept out diagnostically first, and then actually therapeutically. So if we look at these images here, for example, this sums up really what we like to see with the ideal radiopharm. One hour after injection, what's happened in this patient? All your radiation's being deposited into the tumor, or it's being dumped out of the body through bladder or, or wherever else it can leave the body, and ideally, through several half-lives, so in this case, two half-lives later, all you're seeing is activity on tumor, or it's being dumped out of the body through the bladder. So in our mind, this is ideal because, again, you hit it hard and fast, create this neoantigenic storm, and then disappear before any further damage happens to normal tissue. Okay, great. Can you talk about your theranostic approach to treatment and why that might be competitive relative to other types of treatment technologies? Yeah. So the theranostic approach, in its most simple version, is see what you treat, treat what you see. And a lot of times in radiopharm development, if you kind of go back in the history, the first initial theranostic was iodine. It was really interesting. Elemental iodine accumulated in the thyroid gland, and as a result, you could have a version that was just diagnostic and another version that was therapeutic. And so that was great for thyroid cancer, but as the only thing it could really be really sort of suited for. Taking that a step further, by having that theranostic approach, you can actually see a lot of, you know, radiation if there's gamma emissions. Without becoming particle physicists on this call, different decays have different emission energies. Some of them are particle only, some of them are particle plus energy, some of them are energy only in terms of imaging energy. What we've done is said, "All right, let's figure out how to match these." The nice thing is we actually have a series of elemental twins, so they're two different versions of the same element, and so two isotopes, right? Lead-203 is a gamma emitter. Lead-212 is a partial gamma, but primarily leads to an alpha emission on the tumor itself. A lot of work up until now has been done using surrogates. So if you look within this overall construct, if we kind of make it more abstract, whatever you put inside your chelator is going to ideally be carried around wherever the peptide or antibody goes, and so you're gonna drag along a metal with you. A lot of the early work has been using gallium-68. It's a very convenient isotope. It gives rise to a PET image. And so difference between PET and SPECT, you know, PET uses two coincident photons, so it gives a very, very high-resolution scan, whereas SPECT is a single photon and is a slightly lower, but can be seen by a lot more different kinds of cameras. So there's some subtleties there that aren't as relevant to the question: Is this patient suitable for therapy or not? It is more relevant for the question: How can I perfectly stage the disease? There's two different questions that we wanna think about these radioactive elements and particles for how we think about their use in a patient. Are we truly trying to discriminate and find every single, you know, sort of cell in the body that's metabolically active? How can we screen things through? Or really trying to get a yes, no question, is this patient suitable for therapy? Some pretty powerful, you know, questions jump out, depending on how you're thinking about, you know, that imaging and the choices you make. If you actually have a perfectly predictive biodistribution, that allows for predictive dosimetry. So this means you have better treatment planning for the tumor itself in the patient, but also a better way to treat and, and manage the patient, to manage their lifetime exposure to various radiation, especially in really radiation-sensitive organs such as the kidney, where the FDA has mandated certain limits. So you do want to have these perfectly predictive scans if you can. You want to look at dosimetry. You have to look at lifetime dosimetry, lifetime exposure to various organs. And things fall apart a little bit if you change around elements. So if you're using gallium-68, for example, inside here for your image, and then you switch to lutetium-177 for your therapy, they're not always gonna be perfectly aligned. They'll be really, really close, and it's, you know, a good way to get a general sense for it, but it's never gonna be perfectly predictive, and there's quite a bit published about differences of isotopes 'cause it changes the molecule to a different chemical. It'll be similar, but not perfectly precise. Can I ask you a question here that some of, we've gotten from investors of, how durable do you think alpha-emitting particles will be? I think people believe the efficacy will be good if you've shown something from that front, but is there any evidence to show that the treatment's durable? So durability response is an interesting question because, we know that the mechanism of action with an alpha is different than a beta. So the mechanism of action with an alpha, it's a massively destructive particle with a very, very tight zone of destruction, whereas betas have a broader zone of damage. And damage and destruction are very different terms, right? If you're actually destroying cells with alpha particles, one hit, that cell is dead. It's never gonna heal, it's never gonna come back to life, it's never gonna do anything else, and you're trying to think through what's the overall impact within the tumor being hit with all these destructive particles. Betas give a damaging zone, and within that zone, you can inhibit some of the cell's ability. It's really hard to actually get a true cell, you know, sort of death from that, and we've actually done some work head-to-head that really underscores this concept. So on the screen here, what we're looking at is the difference between, you know, sort of untreated on the top left, a beta emitter on the top right. But then really getting into top right and bottom right, the difference between a beta in the top right and an alpha in the bottom right. So in this example, it's lutetium- emitting betas into neuroendocrine tumor. You see that over that kind of 20-day window, the it effectively acts to be more tumor static, let's call it, right? So you're suppressing things. You see in the human experience with lutetium that you, you tend to get a two-year PFS kind of metric. Because, again, the tumor is sort of held in check. It's trying to repair itself from a lot of single-stranded DNA breaks. It's really kind of shut down for a period, but then it kind of comes back. Whereas if you look on the bottom right with alphas coming in, alphas will actually destroy, you know, the cells they hit. And if you can make sure all that activity is destroying tumor cells, you can destroy everything that's expressing that surface receptor. You've actually got an incredibly durable response. So in the animal setting, as like for like as we can get it, this slide actually shows a great example. SSTR2 targeting, in this case, with either a beta on the top right or an alpha in the bottom right, and that durability response is extraordinary. If there are cells that do not express SSTR2, they won't be hit, and therefore, you won't reasonably expect there to be sort of a durable effect in cells that don't take it up. But any cell that's gonna have an alpha particle bound to it and it's released, it's not just damaged, it's effectively destroyed. Okay, great. You already have a robust pipeline of assets, and how do you expect to continue to add new molecular entities onto your portfolio of assets? So it's a great question. If I can zoom out for a second, just say how we kind of walk things out. So if we think about this basic construct of, you know, sort of targeting peptide, we can tune the linker. That's not proprietary, but the length of it will be. The actual chelator we use, we've invested quite a bit of energy into knowing exactly what it looks like. We'll take a chelator that we have a net zero charge in it, so the choice that we've been using for all of our molecules, filed IP around this chelator as well, is something that gives a net zero charge. So that's our base when we start thinking about a platform for where we're going after right now. If we're using lead as the, as the isotope to image and treat, and so far, for all the tumors we're looking at, it looks like it's the best one that we've identified at this point. So starting with that chelator with a net- zero charge, we feel that's better than the other chelators with a minus two or plus two, because a charged protein will tend to increase kidney accumulation and retention, and we're trying to get as much dose away from the kidney as we can. And once we start to think about a construct here, we actually do some pretty interesting work to then iterate once we actually have a target in mind. And I'll show you some examples of how we do this, real-time. So if we look here at our designs, if we know we have a clear target, in this case, we did this work in-house with FAP. And looking at FAP as a target using phage display, we found, you know, 1.5 billion combinations that could have worked. But then we'll start iterating through. We can do what they call grind and bind studies. We can look at sort of tumor to kidney doses and see how that looks in an assay. That's very dry data. Tells part of the story, but not the whole story. And what's really important for us is to really iterate through, and here we're looking at images of a mouse with a sarcoma in its right shoulder. And if we look at that sarcoma there, we know it's consistently, that's gonna be a sarcoma. In this case, we know it should be expressing FAP- alpha, and so we're gonna start targeting that. And as we went in, sort of 30 compounds in, we started to, you know, hone in on things that started to look really compelling, with high tumor uptake and rapid kidney clearance. And you look at this and say, "Well, these look like they're about relatively similar intensity," and that's okay, but not great. So we have tumor, we have kidneys, we have bladder. Making a few iterations forward on there, we tuned a few things, we tried a few more things out, and we got a much brighter accumulation in the tumor and, and much less staying in the kidneys. It's gonna get cleared through the kidneys, but the faster it goes through the kidneys, the better it is for the animal's health, because these are radiation-containing particles. Then, several compound generations later, you look at this accumulation. These images are all around at the two-hour mark, so two hours after injection. What's happened with all that radioactive material? You see amazing accumulation here, only in the sarcoma. You don't see retention in the kidneys. It has to have had gone through the kidneys in order to eliminate the body, and the animal recently voided its urine. But you can see quite clearly there's a huge accumulation in that tumor and nowhere else, and this tells you, gosh, if all of these decays were alphas instead of the imaging gamma here, you know you'd be doing an awful lot of damage to the tumor and hopefully very little damage to the animal. So when we think through, we spend a lot of time really trying to get this, you know, perfect. We do work against competitive agents if we know they exist. As an example, some of the earlier work we did in animals to really look at the difference in the SSTR2 environment. For example, you can see all the generic SSTR2 constructs on the right. Most of them are DOTA or DOTAM. In that case, you get a tumor-kidney ratio of one to one. That's been adequate, and and we felt that in the animal model at least, we could really optimize that. So we actually went from a 1-to-1 to an 8-to-1 ratio, and that involved changing the peptide structure, also changing the linker, also changing the chelator. All these things really, you know, have to be done in conjunction with each other. It's not a really simple, "I'm only gonna go for X versus Y. I'm only gonna go for isotope A versus B, or only gonna tune the one thing." All these things swirl together to lead to the ultimate PK/PD assessment, and the lecture we have of elemental twins is that without sacrificing any animals, we can do head-to-head, within the same animal, evaluations of exactly what a drug's efficacy will look like, and that's really, really compelling. We initially designed our programs with the mindset that we want best and safest possible product for the pediatric environment, to really spare kidneys. And the derivative of that is that these compounds look like they're very safe in the adult environment as well. Okay, great. So I wanted to see if we can move on and talk about your NET and melanoma studies. When you reported your first quarter earnings, you had an update on timing of that data, and we did get some questions on it. People were curious why you moved it from third quarter to second half of the year. So any thoughts there? Yeah, so we wanted to. As we said, as we designed the study, we started enrolling. We dosed patients in both our melanoma and our NET programs, very similar designs. We started dosing patients at the end of last year. We moved through our first initial safety cohorts very, very quickly, and so now we're in the second cohort. And we're dosing patients, looking at safety and efficacy. Plotting through for when we expect the data to come out and when we wanted to meet with the FDA, we had a pretty clear sense for how that was landing in the third quarter. To best position our data with potential medical meetings, we wanted to just widen that window a little bit to see which meetings made sense. And so, we didn't wanna sort of, you know, inadvertently trip over something if something actually ended up being in, on, you know, October first versus September 30th, or in extreme, but really trying to be really clear for what's there. We also, not knowing what various people's abstract deadlines are and when the abstracts come out and how things trickle through, we didn't wanna mislead anyone to saying that, "Gosh, if there's a presentation in November and the abstract up September." You know, it's sort of managing around all those kinds of issues. Okay, great. Actually, I saw a press release this morning regarding the SNMMI conference, your presentation of 12 patients from an investigator-initiated research. I wanted to get from you, you know, what do you think you'll see on those patients, or what do you hope to see? Is there any read-through from that to your own studies? So in the SSTR2 program, you know, we have our current company-sponsored trial, and that's the one that's described here. This is the mTPI-2 design that we're working through and enrolling patients in and evaluating. But as we were getting ready to launch the study, we were approached by Dr. Ishita Sen from the Fortis Institute in India, and she had some compassionate-use patients that she wanted to assess. These are patients that were SSTR2 positive that did not have any access to isotope, you know, with an SSTR2 agent. She couldn't access lutetium or actinium, and she really wanted to assess a compassionate-use environment. We have actually showed the first patient that she ever dosed, and I can go back to that in a moment. But what she had shown back in September was that when she was looking at quite a few patients that she was studying. At that point in September last year, end of September, she had presented, you know, what she was initially seeing. So right out of the gate, these were 10 patients that she was evaluating, eight GEP-NETs, two medullary thyroid cancer patients, and there was actually four patients in there that had previously seen Lutathera. So this is an all-comer study, all-comers evaluation, more of a real-world practice, where she's seeing a combination of some first line and some second line, in that GEP-NET SSTR2 space, plus those additional medullary thyroid cancer patients. Since then, she's continued to dose, and what she's disclosed is that there were two more patients that were being evaluated as well, so a total of 10 GEP-NETs then, plus the two medullary thyroids. So we'll see what's happened with all these patients. Fast-forward the clock nine months later, when she initially presented in September, obviously, there were several patients that were all ongoing and had not received all their doses yet. We expect to see what's happened with those patients, roll forward the clock. So what's really encouraging, we feel, is that this gives the first glimpse into what could happen in the first line and second line settings, so really kind of all-comers environment. Patients that express SSTR2, irrespective of what their prior therapy has been, how does that feel like? And then trying to get a few reads in on patients that have or have not seen a prior agent in place. So we think they'll be very supportive, informative, really guide the direction. I know that the investigators that we're speaking to on our U.S. trial are really encouraged by Dr. Sen's experiences, because they do imply that there is clearly a signal here and that these patients can be monitored for fairly safe, what feels like a reasonably safe sort of product. Okay, great. And I wanted to ask you about melanoma, too. I think we've seen less data there, but what gives you confidence in a positive read on the second half of the year? So when we look at melanoma, it's a very, very different disease, and this is what's interesting for us. As in my mind, there's three absolutely distinct kinds of tumors that we- that you want to sort of think about. Your liquid tumors, and then on the other side, your two different kinds of solid, a very homogeneous and a very heterogeneous type. So a lot of our discussions on initial programs and focusing on the solid tumors, and with one very, very homogeneous type of tumor, the SSTR2, such as neuroendocrine. But melanoma is really on the other end of the spectrum, being very, very heterogeneous. In patients that have melanoma, the literature implies only 50% will actually have MC1R expression, the marker we're going after. And so our, our... A lot of our confidence comes from the early animal work, where we saw pretty clearly, very similar to what we showed before with the SSTR2, we could actually show tumor accumulation, and then we could show that in those mice, the tumors would actually get knocked out. There's some additional work in combination that I'm sure we'll get to in a little bit. But if we just think about the initial dosing, what makes us feel confident is in humans that express MC1R, we can see some extraordinarily positive scans. And these scans, side by side, show the difference between tumor metabolic activity on the left versus tumor surface expression on the right. And really, what this means is the drug on the left, FDG, your classic way of diagnosing patients and standardizing kind of what they look like, how bad the disease burden is, how are things being addressed in those patients, what are all those metabolically active sites? But the degree of correlation on the right with all these sites that actually do pick up MC1R and express it, you can see a tiny little tumor down here that you don't necessarily as strongly over on the MC1R scan. But what's amazing about MC1R imaging is you can actually pick up brain mets, which FDG cannot pick up because there's so much background activity. So based on all this together, we know that if the cells express MC1R, that... And we can pick that up with the lead-203 scan, it will also receive a dose of alpha particles if we switch it from lead-203 to lead-212. And because it's the same composition of matter, same chemical, everything's identical, and it will kind of get that dose. We, as we look at how we actually are evaluating patients and screening it through, we know that patients coming in the post-second line setting, if they screen positive, that's only because they have a positive MC1R expressing scan. And so therefore, we think it's heavily enriched to say, "Who should benefit the most from it?" If you go deep in the weeds and the academics, there's arguments about micrometastatic disease and where that goes. We're not addressing that with the study. We're really looking at patients where they have a gross expression of MC1R. Will those tumors be able to be addressed by being, you know, treated directly with an alpha-emitting peptide that binds the tumor and then starts to give the dose? We have a lot of preclinical data in combination as well, but the monotherapy activity looks like it's fairly solid. Okay, great. I wanted to move on to manufacturing and why manufacturing could be a buried entry for radiopharma companies. So manufacturing is a really interesting one to think through because as we've all learned in cell therapy and everything else, that it's not enough just to have a great, you know, technology. You need to be able to get it to a patient, otherwise, it's kind of a so what? And when I think about distribution, there's two different ways to think about this theme. And so the question is, are we really looking at what's best, centralized or distributed? And I think in any modern distribution supply chain, as we've seen, fundamentally, networks tend to be more robust than centralized points. And I think if you can afford them, if you can do distributed production, you're in a pretty good position. My understanding is that Novartis has said publicly they are increasing the number of sites that can make lutetium-labeled products because they do want to have this more, more of a network effect, take risk off. Yes, you have to then administer, alternate sites of manufacturing, but the trade-off there is that any one site doesn't shut down your product. So, you know, there is one school of thought that says centralized, and a lot of the radiopharm space is centralizing in Indianapolis. Indianapolis is where the dangerous goods hub is for certain commercial carriers, and so it gets very convenient to have to be located there. There's a nice ecosystem there, but that's going with the assumption that you can, you can and must then ship things by air only to get out to your sites. Well, we've taken the approach of saying we actually think a distributed manufacturing network is important to do. It makes logistics easier. But the interesting thing is that's actually what this industry is used to. And if we look at how these networks get built and various manufacturing sites, there's an awful lot of work done over the past 30 years to build out a network of GMP manufacturing sites on the diagnostic side. There is a different bar from a degree of rigor between a diagnostic GMP and a therapeutic GMP. I'm using those terms for what's kind of called Part 212 compliance or Part 211 compliance with what the FDA requires for manufacturing. This is a map from 20 years ago of all the GMP diagnostic PET pharmacies that were out there. And looking at the map from 10 years ago and then from this year, the commercial industry builds out infrastructure and likes a distributed network. Lantheus Medical has shown that they can manage a network of over 50 GMP sites that contract manufacture their product for them for that local regional delivery. The interesting thing about these distribution networks, a lot of it ties into what is your half-life of your isotope, and how far can you get it? There's some really cool isotopes in nuclear medicine, like oxygen-15, that, you know, only exist for 20 seconds, right? And those things can clearly only be done in a hospital. There are some isotopes with very long half-lives of 10,000 years that are toxins that you'd never wanna put into a patient. But in the middle, there's a reasonable sort of trade-off. And so for fluorine-18, which is used for FDG PET imaging in 2.5 million-3 million procedures, you've got a two-hour half-life. So you know, kind of for most of the day, you could deliver the product. It doesn't mean in two hours it disappears. It means half of it disappears in two hours, and so you have a... You know, you have six to eight hours to kinda distribute that product out there. Lead-212 has a 10-hour half-life, and so that really gives us all-day distribution. In all-day distribution, we can kind of plot how far—who can you cover, how far can you go, you know, in the course of a day to get products out by ground or by air? And we've identified what are some reasonable places to get to for manufacturing. When we look at manufacturing as well from a cost, it's really important for investors to disaggregate the difference between a facility that has a cyclotron or a Rhodotron or accelerator on site versus those that don't. We don't. Our distribution hubs, we receive the isotope we're looking for in a parent-and-daughter version. Once the daughter isotope is on your site, you need clean room, and you need lead shielding to adhere to GMP and to make products that comply with GMP manufacturing limits at that 211 level of compliance, and then you wanna distribute out to your population centers. In the radiopharm space, we're not trying to get to every general practitioner in the U.S. or even to everyone's home. We're trying to get to cancer centers, and so cancer centers are clustered around population areas, and so getting product out to cancer centers is really the opportunity and the challenge. We have the extraordinary benefit of having some amazingly talented people that used to run GE's short-lived isotope team that we brought in-house, and they are working to address this real time. Okay, great. How is your manufacturing network currently set up? How many sites do you have, and how scalable is that once you start getting commercial product to the market? So we've shown here a map of what you could use to cover a lot of the country with some mixture of a sort of mostly ground. The purple circles are where we have manufacturing presence. We have a manufacturing presence in Iowa right now, where we actually produce product currently for our clinical trials for both melanoma and for neuroendocrine. That circle in the top right is a facility we purchased in Somerset, New Jersey. We've took possession of that site a little bit ahead of schedule in February, and we're converting that to be able to supply product for our clinical trials. We are going to need additional sites capable of manufacturing, we think, to have a more ground-based and therefore less vulnerable to air disruption and storms and all those kinds of things. So we do wanna make sure we build out, in effect, a ground-equivalent presence, around the U.S. You can see where we're probably looking at either partnering with someone or purchasing a site or building one as we build out this network. Right now, we can supply all of our clinical trial products from, our site in the Midwest as the sites come board, and then our site on the East Coast will be up and running in the second half. And that should supply product for the northeastern part of the country as well. Okay, and do you think that you will have enough supply to meet demand? And so we do. When we think through how the products get made, they get made in batches. And so for someone trying to model it, there's a different cost curve to make one dose than to make 10 doses because they are made in batches. And so if we make a batch and there's only one patient dose, no problem, quite a bit of product will just get thrown out for that day, and that's factored into our cost curves. As more and more demand ramps up, then, you know, you may get two patients from a batch, three, four, or five, and scale up, and then we just change our inputs for how much isotope we start with, for each batch to make sure that then at the end, post-synthesis, we have enough material for all the patients that need to come from that batch. So we can scale up the isotope in, and then that determines, how much isotope we get out the other end on a per-day, per-batch basis. Okay, great. Do you think that radiopharma has the potential to replace radiotherapy? Why or why not? And how do you move up into earlier lines of treatment with your technology? Yeah. No, it's a great question, and I'll argue, I think the field will honestly converge, so we don't think about radiotherapy as being external or internal. I think one of the core pillars of dealing with cancer is using radiation. radiation. The question that's really where the technology iterations can improve patient outcomes is how that radiation gets into the patient, or more importantly, how does it get to the tumor? So external beam has been a grounds, you know, main staple of radiation therapy up until now because you could actually... The only way to get the radiation to the tumor was going through the patient, through their other organs, to get to the tumor. We all know that radiation hitting a tumor is helpful, but we're doing everything we can to spare healthy tissue along the way, and that's really tricky with some of the external beam modalities. It wouldn't it be great if you could actually only have the radiation coming out onto the tumor and nowhere else? And that sort of wouldn't that be great scenario is actually playing out now with alpha particles. If you can bring that alpha particle using the body's blood flow to the tumor directly and nowhere else, and then have it released just on the tumor, nowhere else, that seems like a dream scenario, right? Only target within the tumor from within the tumor, as we call it, treating cancer from the inside out. In terms of what this mean for solid tumors, if you just have a single, tumor that's locally accessible, such as like a, you know, something on your skin, that's stage one, obviously, you wanna deal with that directly surgically. But as soon as you start to get into the body and things start spreading out with the risk of metastatic sites, it almost feels intuitive that you'd want to get into something that's more systemically delivered or distributed, but locally delivered. And so the difference between, you know, local delivery or, and systemic delivery versus systemic distribution, we're trying to take advantage of both of those together. So just going back to that kind of ref... You know, as a refresher image, or even one of our, our FAP scans, if we know in a patient, for example, with an osteosarcoma, we know where the major lesion is, and it's in that patient's shoulder, if we can actually treat that patient from the inside out, we can deliver drug in so it only goes into that site. You have an amazing ability to sort of treat that tumor directly, without damaging other parts of the body. We have a Gallium scan, for example, in a lung adenocarcinoma, where all these tumors, you'd have a tough time treating them with just external beam. You'd do whole body radiation, and that, you know that's gonna cause a lot of damage to healthy tissue. Our goal is to concentrate the release of the radiation only on tumor site and not hit other parts of the body. So I think there's a ton of room still to go. You know, you have approved agents out there for prostate and neuroendocrine. There's so many other solid tumor types where we think, changing this paradigm of only putting radiation onto the tumor and tumor only is really exciting. Okay, great. What about comparing and contrasting your technology to ADCs? We get that often, and who do you think ultimately wins, and why? So I mean, the easy answer is the patients ultimately win, so that's great, you know, because the innovation happens. But, you know, taking that as a given, I think it's easier to think about these as really being the same approach. Because what we're trying to do is we're trying to deliver a payload to a cell. And so if we look at how do we deliver that payload to the cell, we're gonna bind it. And so you can bind with either antibodies or peptides. There's different clearance kinetics that you wanna be mindful of with the ADC space and with the Radiopharm space. You do worry about that payload hitting on target and off target. There's a couple extra steps of complexity in there with ADCs as they're currently being envisioned, right? We have to bind, internalize, release the payload, and hopefully release the payload only inside the cell, and then have the payload only target the cell. I think that as the fields kinda... I think the fields will converge because at the end of the day, we're trying to target a cell and release then either a chemical payload or a radiation payload, and it's the same concept. What about combination therapy with Radiopharm? What have you seen that suggests that this would be helpful, or there are synergies there? Combination, I think, is right, truly one of the most exciting parts of the field right now. I'm really glad you asked that question because we've done some amazing work of looking at combinations. Obviously, in cancer being such a diffuse disease with heterogeneous tumor expressions, combinations have always been tried, and really anything we can do to try and, you know, fight the war on cancer and win is terrific. In this case, we're really trying to say, "All right, how do we actually, you know, treat the tumor and have other parts of the human, sort of immune system kick in and help and, and give the assist?" The nice thing about alphas, which you don't get with as much with external beam, and you really don't get as much of with betas either, is the neoantigenic formation of a particle hitting a tumor cell. And so alphas hitting a tumor, create a really strong neoantigenic event that's actually going to really, have a, a phenomenal impact. If we look at some data we've seen in mouse melanoma, in immunodeficient model, you can see untreated is the black line. Zelboraf in this group actually clearly had a benefit. But look what happened if you had a single dose of an alpha- emitting, neoantigen creating, you know, a particle into the mix, you got a huge change to that patient's or the animal's, excuse me, experience. In immunocompetent model, if you look at what's effectively Ipi/Nivo with the lipid line compared to control, again, some benefit, not great. Monotherapy on its own, that we've, you know, we tend to talk about with the SSTR2 space, definite improvement. But a phenomenal transformation when you actually get into this, you know, idea of a dual, checkpoint inhibitor, plus this neoantigenic, mode, where, you know, 43% complete response rate in the animals, where 75% of them, they can't actually regrow a tumor if challenged. I think the IO field should be really reinvigorated by this idea that we can actually make these drugs much more potent altogether. It's not a 1 + 1 = 2, it's 1 + 1 = 8 or 10, and I think that's what's super exciting for cancer therapy. Okay, great. I know we only have a few minutes left, but I do wanna squeeze in one question here that we do get a lot. So curious how scalable radiopharm is, and, you know, it... Will it be limited in terms of treatment centers or be something that could be a lot bigger over time? And then what kind of economics do providers get from using products like yours? So right now, the reimbursement, we're, I feel very grateful we live in a reimbursement system that tends to reward value and tends to reward outcome. And so you do actually have some currently pre-rated pharmaceuticals that reimburse in the $50,000-$60,000 per dose range, and with sort of, you know, patient treatments varying from three to up to maybe six doses. The reimbursement system does exist, and it's rewarding value, which I think is terrific. You see a huge growth in patient treatment centers. I know of many that are happening in my neighborhood and across the country with either medical oncologists or radiation oncologists or nuclear medicine physicians building the infrastructure to allow patients to come in and be treated. You'd have an explosive growth in manufacturing sites. All these purple chevrons on this map are sites that we're aware of that are being built to have GMP production capabilities for theranostic isotopes. And, you know, the nice thing about this industry is that it tends to innovate and build out infrastructure. So we know we're going to have many more sites that can manufacture drug. We know we're getting many more sites that can administer drug to patient. We currently have a reimbursement environment that supports that, and now we have to think about how do we grow and what happens next. So there are some considerations to think through, is how do we treat all the medical waste that comes from all these procedures? We think that short-lived isotopes actually do have some benefits to the overall system if that happens. We see that with the growth of more and more tumors being targeted, that opens up a lot more opportunities to treat and distribute. It's really important to, to have access to as many patients as possible, so I think a single site that can only produce compounds with a few-minute half-life isn't really reasonable and helpful, and therefore, things with distribution, possible half-lives, really win out here as the patients get access to more and more technology. Okay, great. I think we're out of time here. Thank you to Thijs and Annie for your time today and hosting this wonderful discussion with us. Great. Well, Louise, thank you for hosting us, and we really appreciate the questions and the insight.