Chordoma Research Workshop and Clinical Trials

So important, this is the team of the iceberg, so I encourage anyone to ask any questions that the angle myself is to talk about. Um, but I think that was a great TF, uh, along with the Question of what is it actually to bring the therapy context into the mind? And I think we talked about how there's kind of, uh, gaps that occurs between this collab addition patterns perfectly different from every single government. So the challenge is that companies are not, uh, you know, I'm sure financial incentive. I don't know exactly where the trials happen. A lot of things that the way the trials come. So our next speaker today is gonna talk about, uh, where we come on those trials and better importantly, also. Things that we're doing in the meeting, trying to standardize three line concepts. It's a lot easier about labor lots more cost effective to get contents out of labor. A lot laboring on performance. So up in Massville, uh, uh, across the street, and I was there for, uh, I guess fourteen years now since 2012. And when I started my career, I was seeing patients with Josh earlier French and finally the location. And, you know, I think it'd be very rare to meet the new condition in the field and actually pretty shot control over those patients. Uh, but there is sunset where the subset where case was coming back to showing areas and general So, um, one of the mix of doing the metal oncology side is race or the idea is to help drugs, and because, you know, you're kind of And so we, you know, using tools in addition for genetic testing tools that are, you know, not referred, but the time, you know, pretty good. And we had a couple experiments. Look at sort of the, uh, uh, genetic basis for, chrome, it's, you know, like I said very early days, uh, it's, uh, technology, but, uh, the timing we got interesting that you can't say part of the chromosome is often here in chrome, but that's actually really important target out of the time. So anyway, so we hear another trial, uh, patients, which is fantastic, support how we have to fail these content generation sequence, but a lot of the same mutations, uh, and kind of not the question will create us when we should know how we directly target. So we kind of fall back on how we approach, uh, uh, developing drugs. This is where investigator comes up with an idea trying to source that drug, source funding, and they go that trial, and that's the revenue, and that's the main sort of pushes games for the last, ten plus years. And so there was a small code for new products and we're finding new drugs. So We are now one of the computers got together a couple years ago. Realize that we can't get all the same process for culture, we can't find a single institution basis in a long time. We gotta be faster. We've got to be able to make a single decision. And so, uh, certain rates are going to get how we switch on this process. Fasters, more efficient. There's the next generation coming to sort of, and that we get across the finish line there. So we're gonna talk a little bit about that process later. Alright, so I'm gonna take a few seconds talking to challenges. Uh, business about this culture cases. So, uh, you're talking four hundred cases per year, maybe six hundred a year, and four in Asia. If you think about this comparison to more common cases, the crust cancer, low cancer we have thousands of patients, it's really hard for us to get those, um, marks that we can do these across them eventually. So part of what we analyze that the child increases studies and carrying care, it's hard for us to get resources from, uh, residents, and then from the far side of So puts a lot of pressure on us because, uh, so that's very flexible. Uh, so the challenge we have is a very hair So, uh, came out earlier where some tumors run very slowly and they run those over time and some run very fast and very dangerous. And it's not hard to imagine that if you run a clinical trial, maybe the patients for one fit and the slower going too personally self-selecting on those trials that are fed, and they overinterpret the activity in your drug, but that's And it's so play with last time. We talked regularly, FDA, uh, we produce these organizations. These are real drugs, they want to work, uh, their benefits we have so much, and, uh, These are hard targets. You know, we, like I said about ten years ago, possibly service never be found in products that we can use on our campuses will be personally. It's a lot harder to find that we can anticipate. Okay, so he talking strategically, uh, set the stage for the terms of these clinical trials. We're gonna talk about the basis of medical trials to help you check the response ready, uh, progression things about the terms of the medical trial scheme is so we already understand about this platform. Um, so I showed the slide off. This is sort of the journey of the drug is it goes from the lab is. So we start during the discovery phase, and then we enter something called phase one person. The first time is actually everything in person. Uh, very general studies, once the ring notes, you can stay with the schedule, the side effects, all these things. So the very easy students came over They're all in addition to live classes, uh, one EPGs, it could be large classes, all these things, the really important parts of the study to try to figure out how to, for instance, to see why we use the trap, uh, typically all different kinds of answers, uh, uh, modern area all the same, you know, some mutation, uh. Uh, as phase two, I was unsure on phase two. Now we finally know the main thing as trying to try to treat the more OG basition population. So patients at all in residents all in the same position we're going after. And we're trying to make this decision to construct better what we have to do. We're trying to make this So we don't want to do is form the drugs in base three, which are these large rate of settings, um, and we can cost millions and millions of dollars, and we have waste resources for those resources on it, the majority will be in the track that we don't want to be. We want to stop processing. Um, so most of the road from living in this space base one, phase two. Maybe having a insight will see not the drug research parts of the so, uh, by, uh, something called a response rate, uh, it's a lot of record that's most commonly small. There's a response record and stalls, and, uh, this is a great old structure Very complicated, which is five five or six belonging single dimension. It's just a way for us to scare that across trial as well. Even though, you know, my lob shapes and shapes just belongs to the measures, even growth, and you have impression with the shapes, uh, to a certain way to find the results. So this is a trial which was not known as a different circle, uh, years ago. And, uh, each round is called these are all the individual patients. The bar goes up, tumor drugs, the strengths goes down. And it was cut off in three percent. Uh, that's a small partial response. So once the overall response rate for trial, this one number six responses at twenty-nine patients. Um, now we know Exactly, but you respond certain all the complicated structures that comes up between certain best we have right now very sensitive inventory bodies for years, but uh, it's trying to find better, better influence right now. So, uh, all right, and the last thing I want to talk about here for single last thing was this, uh, countless professional So that's kind of, uh, how patients all off patients get on trouble with more main per months, more growth. And so each of these levels, each of those levels takes down, or I'm sorry, a hundred percent of patients drops down one and one patient growth, and the next, next time, you can come and estimate and say, okay, uh, in this example Set of ones complications have drugs. There's a way to compare between trials compared to different arm systems. And live schemes, these are just the complications of the trial. So the left example is a automatic on a study for a single RAID to see a dose of the drug and give it to CHAPTER SETION. Second example for randomized cloud patients are red massive are ripped off, as I'm saying it's on one arm. Uh, and once you get randomized, arm, you can see it air, international. And so it's less than called crossover, where you go to work on one arm. All right, so taking that. Consideration, uh, plus setting trial we've had from that last few years, and if adjustments that you've heard, you know, they're interested in, uh, setting the strike, uh, some of the other cancer is basically more so to see all the breaks. So the real pressure that's really large of their cancer They call a certain audio reported there and some patients. Uh, this is supported by institutional data where others published, uh, that issues may get outside of your off label, and also, uh, just really got no tracks in, you know, displaying working this is a small study for, uh Sorry, basically I have this idea using this draw as a long cancer using the type of political CSP very high dose and saying, you know, maybe the dose is high on the work. And just like mentioned before some patients responded as a lot of purchases I would want to see that say this one study for studies. Uh, also showing, you know, so that's important. Let's talk here. This is really hard to session up because it's really hard on this context, uh, uh, Driving better than patients that's like around three. We're all seeing all our studies, control hard sands better. Um, and you know, we look at sort of individual institution data, how patients go on a particular drug, but that thought proof of comparison is a lot high. So we, think these drugs are active, but we all patients on these studies all these. It's very hard for us to get to work with City Red Tries and say, okay, yes, it's definitely a person should for this. That's just not gonna happen with us. So we, we have this motivation to take these challenges, uh, and work with our, uh, our colleagues for the 20s to try to be ready for the next step, uh, on development trials. So, uh, a lot of stuff we have said, so we can't compare cigarettes or the, uh, just again, cigar side is very hard to turn. So we look at cool studies from, uh, fire studies. So in place of, uh, uh, the, the radio calling speech and knowing. We actually extracted data from twelve clinical trials. These are twelve study twelve patients. We took our individual data out of those trials and pull all together and say, okay, how have we gone through the last 12 months years? And with that, our response to research only four months percent. But, uh, putting them all together are progression as well. Actually, pretty good at this, uh, point eight months. So there's a few different ways we could do all you talk about the study. Um, we can say here, okay, well, there's really some patients for the house smell and run the study, you know, they don't get all anyway. But, you know, this is definitely better. So, uh, this is a really important starting point, and you know, taking all the studies together, or if we can go, at least in the US, we can go to ensure something used as a target to say not some people how we implement patiently. Uh, to serve as a control arm to compare control, and we hope that'll be explained as many wearing just we can't extract individual patient data. We need patient variables that are, uh, there are linear so it's just not going to be that. Uh, what this is an important statistical framework, important place for us to start our next truck. We want to, move this curve in the right way. And so we're using it's almost as high fixed as trucks, and then we can have our controller on the FDA, our controller are better than this, and these new products will be hopefully that will be. So putting this all together, we need an efficient trial. We need trial to access the patients again. We've got a whole single institution based three study on the opening school places at once. We can go quickly. We can make these global decisions very fast. Uh, unfortunately, I think we take something to compare to this issue, and we'll talk a little bit about that. Should open questions the audience on the And eventually want to build this construction for these next years and one of these towns through a little periodier inhibitory. So I'm over time, but I just want to take a few minutes to take it through this. Uh, this is high level, so you can like hear this bread that exactly like it would want to get you done. So Uh, we're trying to minimize visualization when nobody wants to be regularized, so I recommend that we're trying to be patient friendly, we're thinking you're in the think about this. And so we need a comparison. So we think about this is, um, in Europe, we can't get access to most places to the trucks that was mentioned, and the standard compared personalization. Um, it does work for people like resuming patients. So we, you mean that within patients in Europe, so not like we eligible for the trial, we can set them. We want to add that they wouldn't anyway. If we treat them just like problem, we'll try to get the same eligibility longer than that. At the same time, we must randomize a few patients on the queue to standard compared value as well. And we're hoping we can show us these two arms are exactly the same, and then as we can mix our cells, and then spend the money and draw this reinforcation and control armor bash center. Meanwhile, we're gonna pull that up with other regions. Just like I see the measure before we have A version C between three drugs and two personal. And if we see on the A, we'll have randomization where we're ten eighty percent patients or we'll go to randomized A, or B in two weeks. Now we're asking that so you can randomize the C. Well, you go on that doesn't work randomized in Europe processors. Uh, the time is we want to have these options and governments are gonna go, and this is our starting point where we're getting all somewhere around 12 patients. We see the measurement we want to go see for expanding that's all around 30. We don't see that all that arm is still point for a lot of patients that are. Eventually, our seal open. Interesting thing. Now the way it's just a little different from five to three, uh, and so on. And the idea here is fast, uh, on broad access, we can build this control or we'll be at some point with the software and build this infrastructure for these next generations of job. And, you know, we learn a lot of lessons from this workshop as I mentioned earlier. We are definitely gonna have normal meetings of the FDA giving their feedback on the design, and they may have some thoughts about whether we should keep expectation on or how long we'll be. Um, I think our main points to you are kind of maybe more lofty and like you want to look at the rest of that time, the 10 months that you saw, the eighteen months and twenty months, maybe it's a long too ambitious for the First round of drugs, we might want to find that, but we think this is a really exciting point for coming in that business is going to be engaging. I guess that talk about the final summer happening. No, that was all these drugs we are. Okay. It's pretty, pretty interesting. One of the large such air small thing we pull off together, but the endpoints were unburied very similar. And only one select. And, uh, so once this tells us, so that tells us apart some of these, some of this big theories are not as much, but it also called us that promise of incremental benefit of all these materials together. And so clearly that's how we approach this actually earlier in the week. It will travel Um, Dr. Cotine, I want to thank you for your work, but I really want to thank you for being available for the local oncologists to help guide that here work for the oncologists a lot. My question might be for Dan, it might be for you, but how important is it to get that full genome to tell? We get pushback for that. There are surgeon, terrific, um, says it's not he's justified 150 as we do in the lab in the, um, hospital, but not that full 20, whatever, 20,000 types of 10. Yeah, that's a great question. So, so, uh, for, genetic testing, there's different panels. If you're talking about, there's some like very focus panels that they have a handful of 200, 400 genes that are line for, uh, uh, geospology, there's larger all the genes that might turn on, uh, there's a couple geodes. Oh, you know, I mean, five out of keeping, you know, genome. That's almost too much data. Like, like it's gonna be really hard to turn into whole genome analysis, uh, to guide there. So I sort of think of the genetic testing as a way for me to help decide what I'm gonna do. So there's a target deal that covers the childhood Effective excellent. They give you a little more information. Uh, they have all that's coverage over certain games. So somebody's more raw, you may do something small, like So I like to give us a few all, and sometimes I will start looking in there and I'll see how they pay for a couple years. And English has much. Um, I think we have some sort of flooding issues. That's one of the fixing science labs that just on the downloads act and the FDA, um, you know, they think We've got the metal lots around the work. The, the core people that we can work with, they're interested in currency because they understand the problem. I think better than, uh, guess we'll find out that they're interested in problems, markets and solutions. But a lot, we have to do it, and these are effective drugs, and, uh, they have to work with that environment. So they're open to creative ideas, they understand. But there are other examples of drugs that are for rare diseases, not a rare diseases that you can hide, and there's no business for it. So I mean, it just depends on like what drugs you find. Find a drug that has an age responsibility or something five percent fifty. I think that's a good lot easier to bring into fifty percent, or maybe there's a ten months. It's all the hardest work. Oh, got a question for you, uh. To your knowledge of me and set knowledge of any drug accommodations are being considered for possible trials or ones that have been talking about that are repurpose or yeah, yeah, sure, that's still, uh, one that are not currently justed because I can see my wallet or so. We're very used to it, absolutely. So, um, the temperature comes back and so on is really exciting to, you know, I'm sure many of you have heard. So we, that is, that trial was an initial. Well, that trial ended up in our last one. I don't see the changes. Um, there is these trucks that block proteins, uh, that are involved in sort of vascular chromatic. Quite interesting accommodation between therapy and complication. So we're very key on China C, uh, drop China. Um, uh, and while it's a little different than this ERC complain with CF cancer CSMA, we, we realize we probably have CR complications to that. I think important to my question is not in this workshop also itself, which is a question for the peaks here very interesting.