WEBVTT 1 00:00:00.600 --> 00:00:04.200 Yeah, thank you so much, Axel, and UH great to 2 00:00:04.240 --> 00:00:09.400 be here this morning. As uh, as Axel said, my 3 00:00:09.480 --> 00:00:15.240 name is Gino Blumenthal, uh uh vice president of Global 4 00:00:15.240 --> 00:00:20.239 Clinical Development at merk SO. I lead teams that focus 5 00:00:20.280 --> 00:00:24.879 on development of novel a d c's targeting Trope two 6 00:00:24.920 --> 00:00:29.559 and HER three and small molecules k s G twelve 7 00:00:29.640 --> 00:00:34.000 C and previously I was at the UH at the 8 00:00:34.119 --> 00:00:39.560 f d A for over a decade. Unfortunately, because of circumstances, 9 00:00:39.560 --> 00:00:42.920 we couldn't have uh someone from the government uh on 10 00:00:43.000 --> 00:00:47.799 our panel. Uh unfortunately, but UH I'll try to fill 11 00:00:47.840 --> 00:00:50.359 in as best as I know, how you know, with 12 00:00:50.399 --> 00:00:53.560 my uh you know, prior prior experience and in current 13 00:00:53.920 --> 00:00:56.240 interactions with with Project Optimists. 14 00:00:57.280 --> 00:00:59.039 We also have a great. 15 00:00:58.799 --> 00:01:03.960 Panel in person and we have a hybrid format as 16 00:01:04.000 --> 00:01:11.000 well because Andrew Faris Unfortunately there were problems with air 17 00:01:11.040 --> 00:01:16.760 traffic airlines at Ronald Reagan Airport, so she's but we 18 00:01:16.760 --> 00:01:18.959 were able to quickly pivot and have her. 19 00:01:18.879 --> 00:01:20.439 Join us virtually. 20 00:01:20.519 --> 00:01:26.280 So why don't we start with our panelists and just 21 00:01:26.480 --> 00:01:29.480 if you could introduce yourself and maybe give kind of 22 00:01:29.519 --> 00:01:37.120 a teaser, what are your impressions of Project Optimists from 23 00:01:37.159 --> 00:01:39.640 the last couple of years since its implementation. 24 00:01:40.159 --> 00:01:40.920 Let's start with Greg. 25 00:01:41.840 --> 00:01:44.120 I Hello, every ready, thanks you down. So my name 26 00:01:44.159 --> 00:01:48.040 is Greg Goldmacher. I am a diagnostic radiologist by training. 27 00:01:49.040 --> 00:01:53.000 I've been at MERK for about ten years, almost ten years, 28 00:01:53.959 --> 00:01:57.640 and I lead the Clinical Imaging and Pathology function. 29 00:01:57.799 --> 00:02:00.439 So this is the group that oversees the U use. 30 00:02:00.239 --> 00:02:04.840 Of imaging and pathology assessments UH to evaluate end points 31 00:02:05.280 --> 00:02:08.960 in human trials, so from phase one all the way 32 00:02:09.039 --> 00:02:13.080 all the way through, and in addition to you know, 33 00:02:13.159 --> 00:02:15.439 so in addition to kind of the routine things that 34 00:02:15.479 --> 00:02:20.520 we do with imaging for response rates and progression free survival, 35 00:02:20.639 --> 00:02:22.360 you know, the kind of things that are typically done 36 00:02:22.360 --> 00:02:25.719 in late phase development, we're doing a lot of active 37 00:02:25.759 --> 00:02:32.479 exploratory work internally for using more advanced imaging and analysis 38 00:02:32.520 --> 00:02:35.520 methods to try to get closer to the biology of 39 00:02:35.599 --> 00:02:41.360 the tumors. And well, so our team functions across therapeutic areas, 40 00:02:41.360 --> 00:02:43.520 but about eighty five percent of the work we do 41 00:02:43.599 --> 00:02:47.680 is in oncology, of course, and so we were doing 42 00:02:47.680 --> 00:02:49.080 a lot of work to try to get closer to 43 00:02:49.120 --> 00:02:53.599 the biology using various advanced analytic methods, which we'll discuss 44 00:02:53.639 --> 00:02:57.800 more more here and you know, as a teaser, and 45 00:02:57.840 --> 00:03:00.759 I guess the you know, the big idea I think 46 00:03:00.960 --> 00:03:03.800 is that you know, this traditional method of you know, 47 00:03:03.840 --> 00:03:06.599 you basically dial up the dose until the patient kills over, 48 00:03:06.639 --> 00:03:08.319 and then you back up a couple of steps and 49 00:03:08.439 --> 00:03:13.120 use that the maximum tolered does that doesn't really not 50 00:03:13.159 --> 00:03:16.039 only does that not necessarily that does that not balance 51 00:03:16.319 --> 00:03:20.599 benefit and risk optimally, but that may not even optimize 52 00:03:20.599 --> 00:03:23.800 the benefit side of it. And so there's we're going 53 00:03:23.840 --> 00:03:26.039 through a lot of efforts to try to get closer 54 00:03:26.439 --> 00:03:31.560 to true analyzes of benefit, with the challenge of course 55 00:03:31.599 --> 00:03:33.840 being that in early stage development you're working with such 56 00:03:33.840 --> 00:03:37.000 small numbers and that that's what we have to do better. 57 00:03:39.400 --> 00:03:43.120 So I'm Ryan Sullivan. I'm a medicaloncologist at mass General Hospital. 58 00:03:43.919 --> 00:03:48.919 I specialize in skin cancers, predominantly melanoma. And then I'm 59 00:03:48.960 --> 00:03:53.000 also a faculty member and our Tremier Center for Targeted Therapies, 60 00:03:53.039 --> 00:03:55.960 which isn't just MO likely targeted therapies but also includes 61 00:03:56.000 --> 00:03:59.280 immuna therapies. And I've been a Phase one investigator for 62 00:03:59.360 --> 00:04:03.919 about fifteen plus years in my life. So Project optimists 63 00:04:04.719 --> 00:04:08.439 fun fact, I kind of like it, and the reason 64 00:04:08.479 --> 00:04:10.599 I like it is for many of the reasons that 65 00:04:10.639 --> 00:04:12.960 Greg just said is that it allows us to be 66 00:04:13.000 --> 00:04:17.920 more thoughtful about choosing doses. But it has also requires 67 00:04:18.040 --> 00:04:20.800 us to probably spend a little bit more money and 68 00:04:20.920 --> 00:04:25.399 time as we're designing the trial to end up carrying 69 00:04:25.399 --> 00:04:25.680 it out. 70 00:04:27.639 --> 00:04:29.600 So thank you for the invitation to be here. So 71 00:04:29.920 --> 00:04:32.920 my name is Wim Voss. I'm the CEO Radiomics dot bio, 72 00:04:33.480 --> 00:04:37.439 a Belgian company that does advanced image analysis on radiology images. 73 00:04:37.879 --> 00:04:40.759 I'm an aerospace engineer by training, so I have nothing 74 00:04:40.800 --> 00:04:43.759 with the biology of cancer. But for the past twenty 75 00:04:43.839 --> 00:04:47.839 years I've been working on extracting more information from radiology 76 00:04:47.879 --> 00:04:51.360 images to enhance decision making clinical trials, first in the 77 00:04:51.399 --> 00:04:54.360 respiratory space and now for the past years in the 78 00:04:54.399 --> 00:04:58.079 oncology space. And I think what we specialize on is 79 00:04:58.079 --> 00:05:02.360 really finding those early signals of what's going on very detailed, 80 00:05:02.959 --> 00:05:06.399 not missing an individual tumor using all the information that 81 00:05:06.480 --> 00:05:09.439 is there to up sample small data sets. And I 82 00:05:09.480 --> 00:05:12.920 think very much like Ryan, I like Project Optimism. It's 83 00:05:12.920 --> 00:05:15.680 a step in the right direction. I think it really 84 00:05:15.680 --> 00:05:20.000 opens the door for personalized combination therapies, which will probably 85 00:05:20.480 --> 00:05:23.800 be the path way to cure for many patients. I 86 00:05:23.800 --> 00:05:27.199 think the problem today is that we face this transition period. 87 00:05:27.839 --> 00:05:32.319 We're actually we're treating patients even in the early clinical 88 00:05:32.360 --> 00:05:36.079 work to the best way possible for the patient as 89 00:05:36.079 --> 00:05:38.480 well as these patients are not volunteers, but typically it 90 00:05:38.920 --> 00:05:42.399 is their therapy the clinical trial, which makes it hard 91 00:05:42.600 --> 00:05:45.879 to go with lower dosages because you might not be 92 00:05:45.959 --> 00:05:48.639 optimal for the individual patient. But I think it is 93 00:05:48.680 --> 00:05:51.040 the way to go. I think we need to really 94 00:05:51.160 --> 00:05:55.600 understand what's the optimal dose for a given compound to 95 00:05:55.720 --> 00:06:01.920 get optimal tumor killing capabilities. Once we know that and 96 00:06:01.959 --> 00:06:04.319 we know in which tumors it is doing it, we 97 00:06:04.360 --> 00:06:08.879 can also understand the biology of those tumors, true combinations 98 00:06:08.879 --> 00:06:12.199 of different biomarkers in the end to find the right 99 00:06:12.199 --> 00:06:15.240 combination therapies. And I think in the coming five to 100 00:06:15.360 --> 00:06:18.879 ten years we will probably see project optimists evolve, but 101 00:06:18.920 --> 00:06:22.079 we might also see evolutions in the later stages of development, 102 00:06:22.120 --> 00:06:24.680 because how do you get a drug to market that 103 00:06:24.800 --> 00:06:28.759 might have an optimal efficacy in tumor killing characteristics but 104 00:06:28.879 --> 00:06:33.120 might not have optimal characteristics on a patient survival point 105 00:06:33.120 --> 00:06:34.720 of view? And I think that that's going to be 106 00:06:34.759 --> 00:06:37.680 a big challenge for the follow up of Project Optimists 107 00:06:37.680 --> 00:06:39.439 into the later stages of drug development. 108 00:06:40.680 --> 00:06:43.839 Thank you, and Andrea, Hi, good morning. 109 00:06:44.000 --> 00:06:46.160 Sorry I couldn't be there in person, but I'm glad 110 00:06:46.199 --> 00:06:48.920 I could be here virtually. I'm Andrea Ferris. I'm the 111 00:06:48.920 --> 00:06:52.959 president and CEO of Longevity Foundation. We are an organization 112 00:06:53.120 --> 00:06:58.079 that is focusing on transforming lung cancer. So with respect 113 00:06:58.120 --> 00:07:00.680 to Optimists, I think a lot of the speakers have 114 00:07:00.759 --> 00:07:04.560 touched on it in lung cancer specifically because there are 115 00:07:05.079 --> 00:07:07.720 so many treatment options available now, still not enough, but 116 00:07:07.759 --> 00:07:09.720 there are many more than there were a number of 117 00:07:09.800 --> 00:07:14.040 years ago. Overtreatment and toxicity is are a real issue, 118 00:07:14.079 --> 00:07:17.839 and cumulative toxicity is are a real issue. And the 119 00:07:17.959 --> 00:07:20.680 last speak Girl also touched on it just a little bit, 120 00:07:20.720 --> 00:07:23.120 but I think under treatment is also a big concern. 121 00:07:24.160 --> 00:07:27.680 So conceptually, I like the idea of finding. 122 00:07:27.360 --> 00:07:28.079 The right dose. 123 00:07:28.600 --> 00:07:32.439 My question is really more the methodology of doing it 124 00:07:32.480 --> 00:07:36.399 and whether randomized trials are really the best approach to 125 00:07:36.639 --> 00:07:40.519 finding it and how much additional cost, how many additional patients, 126 00:07:40.800 --> 00:07:45.319 how much additional time is that going to introduce into 127 00:07:45.959 --> 00:07:48.879 this new paradigm. So conceptually, I love the fact that 128 00:07:48.920 --> 00:07:53.120 we're looking at not overtreating, especially as I mentioned, many 129 00:07:53.160 --> 00:07:56.839 people are going on multiple therapies, so the cumulative toxicity 130 00:07:56.879 --> 00:07:59.680 is a real issue. But it's just I question the 131 00:07:59.759 --> 00:08:02.680 how and whether this really is the right approach and 132 00:08:02.800 --> 00:08:05.240 what's going to happen when we get into combination therapies. 133 00:08:07.199 --> 00:08:10.720 Great, thanks for the introductions and for the teasers. I 134 00:08:10.720 --> 00:08:15.279 think this will be a very robust discussion. So we 135 00:08:15.399 --> 00:08:19.439 have a bunch of different stakeholders true to the IO 136 00:08:19.439 --> 00:08:24.040 three sixty concepts, who are all you know with the 137 00:08:24.120 --> 00:08:27.839 vision of you know, developing you know, better, safer, more 138 00:08:27.879 --> 00:08:34.600 effective treatments for patients. We did hear that, you know, 139 00:08:34.759 --> 00:08:38.639 cancer therapeutics has evolved so much over the past few decades. 140 00:08:39.279 --> 00:08:42.759 We were not developing conventional chemotherapy anymore. 141 00:08:44.080 --> 00:08:48.000 We don't have to take drugs to the maximally tolerated dose. 142 00:08:49.440 --> 00:08:53.679 We're developing immunotherapies that harness the immune system, the t cells, 143 00:08:53.720 --> 00:08:57.919 et cetera to attack the cancer. Targeted therapies which you know, 144 00:08:58.039 --> 00:09:01.080 switch off a certain gene or protein that the tumor 145 00:09:01.159 --> 00:09:06.039 may be addicted to, and we're treating patients. For many, 146 00:09:06.080 --> 00:09:09.159 many years, a lot of cancers have been turned into 147 00:09:09.240 --> 00:09:12.879 chronic diseases, so we have to think about long term 148 00:09:13.039 --> 00:09:18.480 cumulative toxicities. We're trying to move agents into earlier treatment settings, 149 00:09:18.519 --> 00:09:22.759 more curative settings. So I think these are things that 150 00:09:22.799 --> 00:09:28.720 the entire community is is struggling with. 151 00:09:29.960 --> 00:09:30.639 I'm wondering. 152 00:09:31.919 --> 00:09:33.840 You know, we heard a little bit from each of 153 00:09:33.879 --> 00:09:38.519 you about sort of efficiency and in drug development. You know, 154 00:09:38.559 --> 00:09:42.759 it's intensely competitive. Patients can't wait. You know, we need 155 00:09:42.799 --> 00:09:47.200 to get good enough therapies, not necessarily perfect therapies, out 156 00:09:47.240 --> 00:09:50.200 to the clinics as quickly as possible. So how do 157 00:09:50.240 --> 00:09:54.039 you guys think about sort of trade offs in trying 158 00:09:54.080 --> 00:09:59.240 to develop you know, early data sets that can be 159 00:09:59.279 --> 00:10:08.360 acceptable to regulators, to clinicians versus you know, versus speed 160 00:10:08.639 --> 00:10:10.279 to get things into phase three? 161 00:10:11.480 --> 00:10:14.879 Maybe right, yeah, maybe I'll start since I do clinical trial, 162 00:10:16.799 --> 00:10:21.679 so I think it really as the I n D 163 00:10:21.960 --> 00:10:25.159 submissions are going in and you're actually even before and 164 00:10:25.200 --> 00:10:31.399 you're designing your strategy, I think keeping in mind project 165 00:10:31.399 --> 00:10:34.879 optimists is not even ideal, it's a necessity. And you 166 00:10:34.919 --> 00:10:38.480 have to begin to think about what's the strategy for 167 00:10:38.559 --> 00:10:42.480 dose escalation and dose finding, and then how can we 168 00:10:42.840 --> 00:10:49.399 begin to expand patients cohorts at various doses throughout that 169 00:10:49.519 --> 00:10:53.559 trial that aren't needlessly treating patients at a dose that's 170 00:10:53.600 --> 00:10:58.559 thought to be ineffective, but exposing patients to doses that 171 00:10:58.600 --> 00:11:02.559 are thought to have potentially some benefit while we're still 172 00:11:02.840 --> 00:11:06.840 escalating upwards. And I think the strategy that's been used 173 00:11:06.879 --> 00:11:09.279 in a lot of phase one clinical trials is the backfill, 174 00:11:10.279 --> 00:11:14.960 so as you're escalating upwards and you're clearing safety doses, 175 00:11:15.399 --> 00:11:17.600 that there's some metric of success. And I think we'll 176 00:11:17.639 --> 00:11:21.120 hear about some of those potential novel metrics of success. 177 00:11:21.679 --> 00:11:27.919 And once there's either a clear clinical response or a 178 00:11:27.919 --> 00:11:30.519 reduction in a biomarker that's thought to be associated with 179 00:11:30.519 --> 00:11:34.519 that disease, then I think you can begin to say 180 00:11:34.559 --> 00:11:39.039 that level is potentially therapeutic and you can expand enrollment 181 00:11:39.080 --> 00:11:41.639 at that while you continue to escalate upwards. 182 00:11:41.360 --> 00:11:42.000 On your dose. 183 00:11:43.639 --> 00:11:47.080 I think it's hard not to build in dose limiting 184 00:11:47.120 --> 00:11:52.960 toxicities and some statement about we will identify if it's 185 00:11:53.240 --> 00:11:56.960 possible to maximum tolerated dose, but ultimately we're going to 186 00:11:56.960 --> 00:12:01.600 move forward to an optimal dose that's been informed either 187 00:12:01.639 --> 00:12:06.039 by these expanded cohorts at dose levels that seem to 188 00:12:06.039 --> 00:12:10.879 be potentially effective, and then also based on the pharmacokinetics, 189 00:12:10.960 --> 00:12:15.679 the pharmacode dynamics, and really trying to choose a dose 190 00:12:16.000 --> 00:12:19.600 that hits the sweet spot and that maybe you know 191 00:12:19.759 --> 00:12:22.720 some I've seen some drugs that have a very linear PK, 192 00:12:23.039 --> 00:12:25.720 but the PD sort of begins. 193 00:12:25.360 --> 00:12:26.039 To level off. 194 00:12:26.039 --> 00:12:28.720 Well, that's that's already telling you something that you probably 195 00:12:28.720 --> 00:12:33.080 shouldn't keep pushing the dose if your pharmacodynamic effect is plateauing. 196 00:12:34.120 --> 00:12:37.879 And so I think that's one strategy, and then certainly 197 00:12:38.240 --> 00:12:40.960 other strategies would be let's find three or four doses 198 00:12:41.000 --> 00:12:43.559 that we think are possible to move forward with and 199 00:12:43.600 --> 00:12:46.840 then you start randomizing in your dose expansion or face two. 200 00:12:47.120 --> 00:12:48.919 But that's just an initial thought. 201 00:12:49.840 --> 00:12:52.440 Yeah, and we talked about PD. 202 00:12:52.840 --> 00:12:58.120 So pharmaco dynamic markers, Greg and whim, what are your 203 00:12:58.159 --> 00:13:01.639 thoughts on, you know, how do you assess what are 204 00:13:01.679 --> 00:13:06.519 the pharmacodynamic markets from an imaging standpoint you would look 205 00:13:06.559 --> 00:13:10.799 at to help help select the dose, and then what's 206 00:13:10.840 --> 00:13:14.559 the future behold start off again. 207 00:13:15.519 --> 00:13:19.080 So where we see it is really focusing in on 208 00:13:20.639 --> 00:13:24.279 the concept of using each tumor as its own data point. 209 00:13:24.600 --> 00:13:27.559 Of course, with the right statistics behind it. What we 210 00:13:27.600 --> 00:13:30.399 typically see is that when a tumor shows some kind 211 00:13:30.399 --> 00:13:34.559 of response to therapy, it tends to continued with that response. 212 00:13:35.000 --> 00:13:37.320 I would say the majority of tumors either grow or shrink. 213 00:13:38.480 --> 00:13:41.240 If you look at individual tumors, there's very little that 214 00:13:41.399 --> 00:13:44.120 actually change their course. Of course, if you look at 215 00:13:44.159 --> 00:13:46.440 a patient level and you look true resist or total 216 00:13:46.519 --> 00:13:50.480 tumor burden, you see these hockey stick effects. One of 217 00:13:50.519 --> 00:13:52.919 the questions I have there for myself and for the 218 00:13:52.919 --> 00:13:56.320 space is if a tumor is decaying at a certain dose, 219 00:13:57.039 --> 00:13:59.279 does it stop decaying or can we, even with a 220 00:13:59.320 --> 00:14:02.279 low dose, get that tumor to zero, because it really 221 00:14:02.879 --> 00:14:05.600 changes the whole paradigm of how we deal with things. 222 00:14:06.639 --> 00:14:11.759 Another concept for pharmacodynamics, when when we talk about trial design, 223 00:14:12.639 --> 00:14:14.799 might be to use many more patients as their own 224 00:14:14.799 --> 00:14:18.240 control using the concept of tumor growth or decay. And 225 00:14:18.360 --> 00:14:21.799 I think Greg will allude to that later, where you 226 00:14:21.799 --> 00:14:24.960 actually use the temporal change and not just a volume change, 227 00:14:24.960 --> 00:14:29.919 but the temporal tendency, which makes it possible to if 228 00:14:29.919 --> 00:14:32.480 you look at similar time intervals, even when a tumor 229 00:14:32.960 --> 00:14:36.200 is at a different initial volume, to compare the change 230 00:14:36.279 --> 00:14:40.559 rate over time, which I would say gives more power 231 00:14:40.559 --> 00:14:43.200 to the clinical trials because the patient is its own control. 232 00:14:43.799 --> 00:14:46.720 On the statistical side, it would really uplift that. Plus 233 00:14:46.720 --> 00:14:50.000 it would also prevent, I think to the point that 234 00:14:50.159 --> 00:14:54.799 was made before, it would prevent the undertreatment of patients 235 00:14:54.879 --> 00:14:57.279 because you can step them up to higher dosages. 236 00:14:59.159 --> 00:15:01.559 All right, So to follow up on this, thanks when 237 00:15:03.759 --> 00:15:06.080 the distinction that I'm thinking about here is that looking 238 00:15:06.080 --> 00:15:09.360 at pharmacodynamics and looking at efficacy markers. 239 00:15:09.600 --> 00:15:12.200 So they're related, but they're not quite the same thing. 240 00:15:12.799 --> 00:15:16.559 So pharmacodynamics, you know, seeing whether the treatment is having 241 00:15:16.600 --> 00:15:20.240 some biological effect, and looking at some combination of So 242 00:15:20.320 --> 00:15:22.159 in the case of radiomics, of course you know this 243 00:15:22.559 --> 00:15:26.600 idea that that biological changes are reflected in histology, and 244 00:15:26.639 --> 00:15:31.480 that histology is reflected in pixel level changes that may 245 00:15:31.519 --> 00:15:33.399 be actually not visible to the human eye. 246 00:15:33.519 --> 00:15:34.440 So this is something that. 247 00:15:34.399 --> 00:15:37.240 You know, you need AI models to extract from images, 248 00:15:38.440 --> 00:15:41.559 but that you can see the biological effects of treatment, 249 00:15:41.679 --> 00:15:44.000 and so you can establish some kind of a dose 250 00:15:44.039 --> 00:15:49.000 response curve by looking at you know, just biological change. 251 00:15:50.240 --> 00:15:53.960 The next level, though, the really challenging bit is translating 252 00:15:53.960 --> 00:15:57.120 that into long term efficacy and you know, as everybody 253 00:15:57.159 --> 00:16:00.399 who's done oncology DIRUGT development for a length of time knows, 254 00:16:00.840 --> 00:16:03.720 what happens is that early on you're looking at response, right, 255 00:16:03.840 --> 00:16:06.679 radiographic response, What does that mean? That means tumor shrinkage. 256 00:16:07.240 --> 00:16:09.600 But it's not hard to find things that shrink tumors. 257 00:16:10.399 --> 00:16:13.799 And unfortunately the history of cancer drug development is littered 258 00:16:13.799 --> 00:16:17.279 with examples of drugs that looked good based on shrinking 259 00:16:17.320 --> 00:16:20.639 tumors in small numbers of patients early on, but then 260 00:16:20.759 --> 00:16:22.799 you take it to phase three and it doesn't improve 261 00:16:22.879 --> 00:16:26.360 survival and that's, you know, not a great outcome for 262 00:16:26.440 --> 00:16:27.519 a variety of reasons. 263 00:16:27.919 --> 00:16:28.879 So what we need are. 264 00:16:28.840 --> 00:16:33.879 Things that really correlate well to survival ultimately. And if 265 00:16:33.919 --> 00:16:37.240 you can get to the point where you have dose 266 00:16:37.279 --> 00:16:39.240 expand you know, so as Ryan said, you know, you. 267 00:16:39.200 --> 00:16:41.200 Pick a few doses, two or three doses that you. 268 00:16:41.159 --> 00:16:44.279 Think might be the best dose, the right dose, and 269 00:16:44.360 --> 00:16:48.720 if you could truly compare those, you know, thirty forty 270 00:16:48.759 --> 00:16:52.679 patient dose expansion cohorts on os impact, that would sort 271 00:16:52.679 --> 00:16:56.000 of be the the you know, to really establish an 272 00:16:56.000 --> 00:16:59.519 optimal dose. And there are approaches around that based on 273 00:17:00.039 --> 00:17:04.400 tumor kinetic modeling where you incorporate a time component much 274 00:17:04.440 --> 00:17:07.839 more robustly than just looking at you know, time to 275 00:17:07.960 --> 00:17:11.279 progression or things like that, where you know, you decompose 276 00:17:11.400 --> 00:17:14.680 growth into an exponential decay in an exponential growth component, 277 00:17:14.920 --> 00:17:18.279 and you you know, based on either total tumor burden 278 00:17:18.559 --> 00:17:22.720 or per lesion back out of the of the curve 279 00:17:22.799 --> 00:17:26.680 fit the growth kinetic parameter that that you know, in 280 00:17:26.799 --> 00:17:28.839 a bunch of academic work has been shown to be. 281 00:17:28.920 --> 00:17:30.440 Robustly correlated with survival. 282 00:17:30.440 --> 00:17:34.000 And that's seems like a very promising method for once 283 00:17:34.039 --> 00:17:37.880 you've got your two or three dope potential doses, getting 284 00:17:37.920 --> 00:17:40.599 to what should you really take forward? Because you know 285 00:17:40.640 --> 00:17:43.599 what what you know really gives you the best os impact, 286 00:17:43.839 --> 00:17:46.319 so those so that distinction so you can have the 287 00:17:46.519 --> 00:17:49.200 kind of the the more radiomics you know, and and 288 00:17:49.240 --> 00:17:50.720 by the way, it doesn't have to be just radiomex 289 00:17:50.839 --> 00:17:52.880 it can be other changes. 290 00:17:52.960 --> 00:17:55.799 That look at that get to biology you. 291 00:17:55.720 --> 00:17:58.720 Know in aggregate like ct DNA or other you know, 292 00:17:58.759 --> 00:18:02.640 blood biomarkers or imaging markers on one hand, on the 293 00:18:02.920 --> 00:18:06.319 on the pharmacodynamics and then the getting as close as 294 00:18:06.359 --> 00:18:08.839 you can to the biology that makes tumors lethal which 295 00:18:08.920 --> 00:18:11.359 is growth. Right, what kills you is the growing tumor, 296 00:18:12.319 --> 00:18:18.519 So that combination could let us optimally estimate benefit. 297 00:18:20.240 --> 00:18:20.480 Great. 298 00:18:20.839 --> 00:18:25.440 Yeah, thanks, So Andrea, a question for you, you know, 299 00:18:25.559 --> 00:18:26.039 you deal? 300 00:18:26.599 --> 00:18:28.240 Can I comment on the last one first of the. 301 00:18:28.359 --> 00:18:30.359 Yeah, yeah, please go ahead. 302 00:18:30.599 --> 00:18:33.559 I'm just wondering, like listening to the conversations, you know, 303 00:18:33.799 --> 00:18:36.119 I think that it's I like the last speaker in 304 00:18:36.200 --> 00:18:38.319 terms of the modeling aspect of it. But I worry 305 00:18:38.960 --> 00:18:42.519 with the first speaker, especially is you know, don't we 306 00:18:42.559 --> 00:18:44.279 can't let perfect be the enemy of the good, And 307 00:18:44.359 --> 00:18:46.640 like how many patients do we want to put on 308 00:18:46.720 --> 00:18:50.880 all these various doses and taking forward and so forth? 309 00:18:51.000 --> 00:18:54.440 And is it really necessary that the other thing? I 310 00:18:54.519 --> 00:18:56.720 just would question or caution and I would love to 311 00:18:56.759 --> 00:18:59.839 hear the perspective of, especially as we are moving into 312 00:18:59.839 --> 00:19:04.200 earlier stage disease and earlier on is LS really the 313 00:19:04.279 --> 00:19:06.799 endpoint we want to be looking at there, especially for 314 00:19:06.880 --> 00:19:08.920 these types of dose escalation studies? 315 00:19:10.720 --> 00:19:13.160 Yeah, so I think to clarify. 316 00:19:14.359 --> 00:19:17.839 That, you know, I think Greg and Wim are trying 317 00:19:17.880 --> 00:19:23.359 to develop imaging endpoints that can help predict. 318 00:19:23.160 --> 00:19:24.799 Overall survival perfect. 319 00:19:25.359 --> 00:19:29.200 Yeah, not necessarily obviously, you know, you wouldn't have the 320 00:19:29.240 --> 00:19:34.000 statistical power, or the randomization, or the numbers to follow, 321 00:19:34.160 --> 00:19:37.319 or the time to follow patients on phase one dose 322 00:19:37.440 --> 00:19:38.799 escalation out to survival. 323 00:19:39.359 --> 00:19:42.559 Thank you to answer the the the how many patients 324 00:19:42.559 --> 00:19:42.920 do you need? 325 00:19:42.920 --> 00:19:43.799 I mean, just to refer to. 326 00:19:43.920 --> 00:19:47.160 There's one interesting publication from I think it was twenty 327 00:19:47.200 --> 00:19:51.920 twenty the Maitland paper, where this was an effort of 328 00:19:51.960 --> 00:19:58.240 the foundation of the NH analyzing data from a colorectal 329 00:19:58.359 --> 00:20:01.759 cancer trial. I think I think it was a I 330 00:20:01.839 --> 00:20:05.559 think it was a TKI and so interestingly so in 331 00:20:05.599 --> 00:20:09.039 this trial, the hazard ratio on OS was zero point 332 00:20:09.119 --> 00:20:11.799 eight two, so, you know, not a huge impact, right, 333 00:20:12.039 --> 00:20:12.880 you know, a. 334 00:20:12.759 --> 00:20:14.240 Modest survival effect. 335 00:20:14.839 --> 00:20:16.160 And what they did is they did kind of a 336 00:20:16.200 --> 00:20:21.079 resampling method where they would draw you know, n patients whatever, 337 00:20:21.119 --> 00:20:24.079 five hundred or one thousand times with replacement and see 338 00:20:24.359 --> 00:20:26.880 on the basis of that sample, if they used these 339 00:20:26.920 --> 00:20:31.599 various kind of kinetic parameter assessments, how how easily could 340 00:20:31.599 --> 00:20:35.640 they detect the OS impact. And what they found is 341 00:20:35.680 --> 00:20:40.000 that they had if they used tumor diameters, they were 342 00:20:40.039 --> 00:20:44.000 able to detect the OS impact with eighty percent power 343 00:20:44.279 --> 00:20:47.720 with like forty five patients, and if they used whole 344 00:20:47.799 --> 00:20:51.119 tumor volume it was something like twenty five patients. So 345 00:20:51.519 --> 00:20:55.720 we're talking about dose expansion cohorts of you know, thirty 346 00:20:55.799 --> 00:20:59.480 or forty patients. If this is done appropriately, should be 347 00:20:59.480 --> 00:21:03.240 able to differences. I mean, again, that's a modest different 348 00:21:03.279 --> 00:21:08.319 os difference that was predictable with a relatively small sample. So, Andrew, 349 00:21:08.559 --> 00:21:10.960 to answer your question of how many and how long, 350 00:21:11.680 --> 00:21:13.799 those are roughly the numbers I think that we're talking 351 00:21:13.799 --> 00:21:14.319 about here. 352 00:21:16.279 --> 00:21:18.799 Yeah, there's one thing I want to add to that, 353 00:21:19.480 --> 00:21:22.799 because it's in the end for the patient's survival is 354 00:21:22.799 --> 00:21:26.480 the most important thing. However, if we're developing a drug 355 00:21:26.720 --> 00:21:29.480 that would kill in all patients, like let's say half 356 00:21:29.480 --> 00:21:33.680 of the tumors very well, very rapid, but it might 357 00:21:33.720 --> 00:21:36.319 not have a survival benefit because the other tumors will 358 00:21:36.359 --> 00:21:40.079 continue growing and we kill that drug, we might throw 359 00:21:40.119 --> 00:21:43.640 away a valuable asset that, in the reality of combination 360 00:21:43.759 --> 00:21:46.000 therapies could add to the therapies. 361 00:21:46.000 --> 00:21:47.400 And I think there is a true. 362 00:21:47.319 --> 00:21:49.880 Danger there that if we don't have the right approach, 363 00:21:50.200 --> 00:21:52.559 that we're killing a lot of assets, or we're putting 364 00:21:52.599 --> 00:21:55.240 a lot of assets on the bench that could really 365 00:21:55.279 --> 00:21:58.480 add a benefit for the patients, and I think Project 366 00:21:58.519 --> 00:22:00.319 Altmost is a good step in that direction. That we're 367 00:22:00.359 --> 00:22:02.400 in this phase where we have to put the concepts 368 00:22:02.400 --> 00:22:05.359 together because on one hand, the FDA wants and the 369 00:22:05.359 --> 00:22:08.799 patient need additional survival, but on the other hand, we 370 00:22:08.839 --> 00:22:12.200 also need to focus in and zoom in onto what 371 00:22:12.319 --> 00:22:15.240 are the assets that have the potential to add to 372 00:22:15.279 --> 00:22:19.880 combinations that could really dramatically up the level of survival. 373 00:22:19.920 --> 00:22:23.759 I think, as as Excel showing earlier today, the next 374 00:22:23.799 --> 00:22:27.079 generation that will bring the survival up another twenty to 375 00:22:27.160 --> 00:22:27.799 thirty percent. 376 00:22:28.720 --> 00:22:30.079 Yeah, great point. 377 00:22:30.960 --> 00:22:33.640 So so back to you, Andrew and bringing us back 378 00:22:33.680 --> 00:22:36.599 to the here and now. You know, we've had some 379 00:22:36.759 --> 00:22:42.920 very future oriented thoughts which are really promising and exciting. 380 00:22:42.960 --> 00:22:47.000 But you deal a lot with the FDA, you deal 381 00:22:47.000 --> 00:22:47.559 a lot with. 382 00:22:47.680 --> 00:22:54.119 Investigators, and so what are you hearing about, you know, 383 00:22:54.200 --> 00:22:57.319 from a drug development standpoint, what are some of the 384 00:22:57.400 --> 00:23:01.200 current pain points around Project Optimist is it's sort of 385 00:23:01.240 --> 00:23:07.400 the inconsistency that you're of advice and kind of randomization 386 00:23:08.519 --> 00:23:12.400 of small cohorts for randomization's sake, just to check a box, 387 00:23:12.960 --> 00:23:16.839 or lack of clarity. I mean, what are you hearing 388 00:23:16.920 --> 00:23:19.319 and what are you trying to convey to the regulators. 389 00:23:20.079 --> 00:23:23.400 Yes to all of the above, especially from the investigators, 390 00:23:23.960 --> 00:23:27.000 many of them that I've spoken with, you know, they 391 00:23:27.160 --> 00:23:29.400 they keep coming back to that medicine is more of 392 00:23:29.440 --> 00:23:32.759 an art than a science, and obviously we need to 393 00:23:32.799 --> 00:23:36.200 have the science to approve drugs and to demonstrate efficacy 394 00:23:36.240 --> 00:23:39.319 and so forth. But almost all of them have said, 395 00:23:39.400 --> 00:23:42.039 you know, the irrespective of what the label says, they're 396 00:23:42.079 --> 00:23:45.400 going to be playing around with it anyway. And with 397 00:23:45.920 --> 00:23:49.640 to do a randomized trial with such small number of people, 398 00:23:49.759 --> 00:23:51.880 what are we really learning and gaining from it? Is 399 00:23:51.880 --> 00:23:54.799 sort of the perspective that I've heard from, and they're 400 00:23:54.799 --> 00:23:58.920 mostly academic researchers, you know, at the at the NCI 401 00:24:00.000 --> 00:24:03.480