WEBVTT - Fighting Cancer with CRISPR 0:00:15.356 --> 0:00:23.876 Pushkin. One of the most important technological breakthroughs so far 0:00:23.996 --> 0:00:30.476 this century is CRISPER aka Clustered regularly spaced palindromic repeats 0:00:30.876 --> 0:00:35.396 aka the extraordinary gene editing tool that is right now 0:00:35.516 --> 0:00:40.556 making its way to actual human patience. The FDA approved 0:00:40.596 --> 0:00:44.996 the first CRISPER produced drug last December, and now scientists 0:00:45.076 --> 0:00:48.276 are trying to improve on the original Crisper to bring 0:00:48.476 --> 0:00:56.876 more treatments to market. I'm Jacob Goldstein and this is 0:00:56.876 --> 0:00:59.076 What's Your Problem, the show where I talk to people 0:00:59.076 --> 0:01:02.676 who are trying to make technological progress. My guest today 0:01:02.756 --> 0:01:07.276 is Rachel Horowitz, the co founder and CEO of Caribou Biosciences. 0:01:07.876 --> 0:01:11.716 Rachel's problem is this, how can you make CRISPER work better? 0:01:12.236 --> 0:01:15.516 And how can you use it to engineer human immune 0:01:15.516 --> 0:01:19.476 cells to fight cancer. We started off talking about Rachel's 0:01:19.516 --> 0:01:23.556 graduate work at UC Berkeley. She studied with Jennifer DOWDNA, 0:01:23.676 --> 0:01:26.036 who would go on to win the Nobel Prize for 0:01:26.076 --> 0:01:29.316 her work on crisper. At the time, Rachel's work was 0:01:29.316 --> 0:01:35.916 focused on a protein called CAST six. Is it right 0:01:35.996 --> 0:01:38.716 that you spent five years studying one protein? 0:01:39.916 --> 0:01:44.556 I spent five years studying one small protein composed of 0:01:44.596 --> 0:01:48.356 only one hundred and eighty seven amino acids, So I 0:01:48.436 --> 0:01:49.636 was pretty far down the road hole. 0:01:50.476 --> 0:01:53.396 I mean, are you the world expert in that protein? 0:01:53.476 --> 0:01:55.556 Is there? Do you know more about that than anyone 0:01:55.556 --> 0:01:56.396 who has ever lived? 0:01:57.476 --> 0:01:59.436 There are probably three of us who know more than 0:01:59.476 --> 0:02:00.956 we ever wanted two about that protein. 0:02:01.356 --> 0:02:03.196 Just give me a little hit of that protein? Well, like, 0:02:03.356 --> 0:02:05.916 what is it? Why'd you spend five years studying it? 0:02:05.916 --> 0:02:10.396 It was my entry point to Crisper. I joined Jennifer 0:02:10.436 --> 0:02:14.516 dowdna's lab as a brand new baby PhD student in 0:02:14.596 --> 0:02:18.676 two thousand and seven. This was the dark ages of Crisper. 0:02:18.716 --> 0:02:22.716 There were three peer reviewed manuscripts that had been published 0:02:22.716 --> 0:02:25.076 at the time, so it took me about forty five 0:02:25.116 --> 0:02:26.756 minutes to get up to speed on the field. It 0:02:26.796 --> 0:02:31.716 was great, and I was joining a project headed up 0:02:31.756 --> 0:02:34.716 by a post doctoral fellow in the lab, and he 0:02:34.756 --> 0:02:40.116 had identified these Crisper associated or CAST proteins and he 0:02:40.156 --> 0:02:42.876 was trying to study all of them. Now he was 0:02:42.916 --> 0:02:46.636 able to make and study all but one. One was 0:02:46.796 --> 0:02:49.756 proving difficult in the lab, so he gave that one 0:02:49.756 --> 0:02:52.196 to me to see if I could sorted out. We 0:02:52.316 --> 0:02:55.116 did eventually sort it out, and in the end it 0:02:55.156 --> 0:02:58.596 turned out to be a very important little protein. It's 0:02:58.676 --> 0:03:03.596 actually responsible for making these small Crisper RNAs that are 0:03:03.636 --> 0:03:06.876 at the heart of Crisper biology. And so I had 0:03:06.916 --> 0:03:10.036 a lot of fun for many years really understand how 0:03:10.076 --> 0:03:14.556 that particular protein functioned, what it did, how it did 0:03:14.596 --> 0:03:18.396 it on a molecular level, and then ultimately zooming far 0:03:18.476 --> 0:03:20.996 far out how it fits into the broader use of 0:03:21.036 --> 0:03:21.876 Crisper systems. 0:03:22.156 --> 0:03:23.996 Yeah. I mean, if you're going to spend five years 0:03:24.036 --> 0:03:27.516 studying one protein, studying a protein that's essential to crisper, 0:03:27.876 --> 0:03:31.916 and doing it in like twenty ten, is as good 0:03:32.356 --> 0:03:33.036 as good as. 0:03:32.876 --> 0:03:35.356 It gets right right place, right time. 0:03:36.156 --> 0:03:39.316 And just to be clear briefly, just so we have it, 0:03:39.596 --> 0:03:40.516 what is crisper. 0:03:41.116 --> 0:03:47.076 Crisper is a technology for editing the genome. Crisper allows 0:03:47.156 --> 0:03:51.476 us to do a few different things to change genomes. 0:03:52.476 --> 0:03:54.916 We can hit the delete key. We can get rid 0:03:54.956 --> 0:03:57.836 of a gene that we don't want to express anymore. 0:03:58.676 --> 0:04:02.076 We can make a small change, maybe even as simple 0:04:02.156 --> 0:04:07.236 as a single nucleotide of DNA, and we can insert 0:04:07.276 --> 0:04:10.356 one or multiple new genes to actually give a cell 0:04:10.436 --> 0:04:12.276 new capabilities it didn't have. Before. 0:04:13.116 --> 0:04:16.716 So just in the last months, right order of magnitude months, 0:04:16.956 --> 0:04:20.556 there have been I guess the first drug approvals sort 0:04:20.596 --> 0:04:22.876 of based on Crisper, right, tell me about those. 0:04:23.676 --> 0:04:26.516 It's incredibly exciting. At the end of last year, the 0:04:26.556 --> 0:04:30.596 first ever Crisper edited therapy was approved by the FDA. 0:04:30.716 --> 0:04:35.036 It's now but approved by other regulatory agencies outside the 0:04:35.116 --> 0:04:38.596 US too. So this is a cellular therapy for the 0:04:38.636 --> 0:04:42.916 treatment of sickle cell and beta thalacemia. So this is 0:04:42.956 --> 0:04:46.556 the use case where you take cells, you use Crisper 0:04:46.676 --> 0:04:49.876 to change them, and then you deliver the cells as 0:04:49.916 --> 0:04:53.196 the therapy back to these patients and the vision is 0:04:54.036 --> 0:04:56.156 to try to actually cure sickle cell disease. 0:04:56.236 --> 0:05:00.756 It's quite remarkable and really fast from when you were 0:05:00.796 --> 0:05:03.756 in grad school and this kind of wasn't quite the 0:05:03.796 --> 0:05:06.996 original work, but this early work was happening. Right. It's 0:05:07.116 --> 0:05:12.116 twelve years, which for go from a lab and kind 0:05:12.156 --> 0:05:14.596 of just basic proof of concept to a thing in 0:05:14.636 --> 0:05:16.796 the world seems wildly fast. 0:05:17.756 --> 0:05:21.516 It's lightning speed. I'm not aware of any other life 0:05:21.556 --> 0:05:27.036 science technology that went from really important publication in science 0:05:27.116 --> 0:05:32.196 magazine to approved therapy anywhere near that fast. There are 0:05:32.196 --> 0:05:35.756 probably a few things to thank for That. One is 0:05:36.396 --> 0:05:41.916 Crisper's actually not the first genomediting technology. Genomediting has been 0:05:41.956 --> 0:05:45.396 around for a while, but the other approaches are much 0:05:45.516 --> 0:05:50.836 harder to use, and so this really unlocked a much faster, 0:05:51.116 --> 0:05:53.876 broader scale of genomediting. So there was a lot of 0:05:54.436 --> 0:05:59.396 resident expertise and capability that could be turbocharged by the 0:05:59.396 --> 0:06:01.076 introduction of chris per Gino mediting. 0:06:01.116 --> 0:06:02.796 It's like there were people who sort of knew how 0:06:02.796 --> 0:06:05.236 to do it already and then this incredible tool kind 0:06:05.276 --> 0:06:06.876 of fell out of the sky and was like, Oh, 0:06:06.916 --> 0:06:08.916 we can just do the thing. We're doing way better 0:06:09.476 --> 0:06:13.196 exactly we're saying there were a couple of reasons. Was 0:06:13.196 --> 0:06:15.076 that one reason was there another reason. 0:06:15.276 --> 0:06:18.676 That's one, and I think another is that there were 0:06:18.796 --> 0:06:24.116 things developed for other fields or biology well understood that 0:06:24.236 --> 0:06:27.876 could quickly be taken advantage of. So, for example, the 0:06:27.996 --> 0:06:32.036 genetic cause of sickle cell disease has been known for decades, 0:06:32.596 --> 0:06:36.156 and yet there hasn't been the right tool to do 0:06:36.356 --> 0:06:39.316 much of anything about it. And so this was sort 0:06:39.356 --> 0:06:44.596 of the perfect marriage of this incredible enabling technology and 0:06:44.676 --> 0:06:47.836 its ability to solve a biology problem that's been well 0:06:47.916 --> 0:06:49.276 understood for a very long time. 0:06:50.116 --> 0:06:53.276 Can you give me a sense of the landscape of 0:06:54.756 --> 0:06:59.396 how crisper is being used in drug therapies Now, broadly. 0:07:00.596 --> 0:07:04.196 Crisper is being used in two very fundamental ways for 0:07:04.276 --> 0:07:08.076 drug development. The first is basic research and the second 0:07:08.276 --> 0:07:14.036 is actually designing and doing new therapies, and that falls 0:07:14.276 --> 0:07:17.996 largely into two categories. One is the kind of work 0:07:17.996 --> 0:07:20.596 that we are doing here at Caribou, where we use 0:07:20.756 --> 0:07:26.556 crisper to actually modify or engineer cells, and the cells 0:07:26.916 --> 0:07:30.436 are the therapy. So by the time we deliver, for example, 0:07:30.956 --> 0:07:34.196 our Carte cell therapy CEB tend to patients, there's no 0:07:34.316 --> 0:07:37.636 Crisper inside of those cells anymore. Crisper is gone. It 0:07:37.676 --> 0:07:41.196 has modified the genome in multiple ways, and the cell 0:07:41.796 --> 0:07:46.196 is the therapeutic. The other strategy that some companies are 0:07:46.316 --> 0:07:51.316 using is to actually deliver Crisper inside the human body, 0:07:51.796 --> 0:07:55.116 and the idea is to try to correct a gene 0:07:55.476 --> 0:07:59.116 that causes a rare genetic disorder, and so in that case, 0:07:59.276 --> 0:08:01.316 crisper itself is the therapy. 0:08:02.356 --> 0:08:05.356 So in that latter case, I mean that is gene 0:08:05.436 --> 0:08:11.356 therapy essentially what people have therapy, and what's what seems 0:08:11.396 --> 0:08:14.156 to be next in line what's farthest along anyways in 0:08:14.236 --> 0:08:17.196 terms of other crisper derived therapies. 0:08:18.436 --> 0:08:20.516 Yeah, there's some very exciting work coming out of a 0:08:20.556 --> 0:08:25.716 company called Intellia Therapeutics where they're actually using crisper as 0:08:25.756 --> 0:08:30.116 the drug. So they are delivering it packaged inside these 0:08:30.156 --> 0:08:34.076 little fat particles to go directly to a patient's liver 0:08:34.316 --> 0:08:37.956 to correct a gene that causes a disease. And they 0:08:37.996 --> 0:08:41.996 are running what's called a phase three trial for one 0:08:41.996 --> 0:08:43.196 of those medicines right now. 0:08:44.316 --> 0:08:46.876 So I feel like this is a dumb question, But 0:08:46.956 --> 0:08:49.436 as I imagine that, like, does that mean that the 0:08:49.436 --> 0:08:52.956 therapy has to get to like every cell in the liver? 0:08:53.276 --> 0:08:55.676 Like is it going to change the genome of every 0:08:55.716 --> 0:08:57.796 cell in your liver? Is that the way that works? 0:08:58.756 --> 0:09:01.356 Thank goodness, No, that's not requite. 0:09:01.356 --> 0:09:04.356 It couldn't be that, right, It couldn't be that most 0:09:04.436 --> 0:09:07.356 of them like what like what? But it's sell by cell. 0:09:07.436 --> 0:09:11.076 It's like that the particle hits one liver cell and 0:09:11.156 --> 0:09:13.156 changes the genome, and then another one hits another one 0:09:13.196 --> 0:09:15.636 and then is there some kipping point? Like how does 0:09:15.636 --> 0:09:16.076 it work? 0:09:17.636 --> 0:09:19.516 It's a wonderful question, and I think there are a 0:09:19.556 --> 0:09:22.076 lot of people who sit in a lot of conference 0:09:22.116 --> 0:09:26.236 rooms staring at whiteboards trying to understand what is that 0:09:26.316 --> 0:09:30.996 tipping point? Because I think it's biologically unrealistic to think 0:09:31.036 --> 0:09:33.916 you can edit one hundred percent of cells in the liver, 0:09:34.036 --> 0:09:36.556 and if that's what's needed for a therapy, you're probably 0:09:36.596 --> 0:09:40.996 out of luck, and instead focusing on diseases where there's 0:09:41.036 --> 0:09:46.116 some model or suggestion that you know, maybe editing ten 0:09:46.196 --> 0:09:49.036 percent of the cells or fifteen or twenty percent of 0:09:49.076 --> 0:09:52.476 the cells would be enough, and there's confidence that the 0:09:52.516 --> 0:09:54.196 technology might be able to accomplish that. 0:09:54.396 --> 0:09:57.116 Well, what you mentioned that there's a therapy and did 0:09:57.156 --> 0:10:00.876 you say phase three in the final stage of clinical trials? 0:10:00.876 --> 0:10:02.596 What disease is that targeting? 0:10:03.236 --> 0:10:08.356 So Intellia is working on a disease called transthyretin amyloidosis 0:10:08.636 --> 0:10:13.076 or a TTR. For sure. It's a disease caused by 0:10:13.236 --> 0:10:19.556 misfolded proteins and it leads to neurodegeneration and cardiomyopathies. 0:10:20.116 --> 0:10:21.156 That's the one in the liver. 0:10:21.956 --> 0:10:26.876 They are editing liver cells because the liver produces the 0:10:26.916 --> 0:10:31.156 misfolded protein that causes problems elsewhere in the body. 0:10:31.836 --> 0:10:37.116 So, okay, clearly Crisper is this wildly useful breakthrough, but 0:10:37.316 --> 0:10:41.356 it's not perfect. And your company was founded in a 0:10:41.396 --> 0:10:46.996 way to address this key weakness of Crisper as originally developed. 0:10:47.036 --> 0:10:51.276 So what is the weakness in particular that your company 0:10:51.316 --> 0:10:51.996 is focusing on? 0:10:53.276 --> 0:10:58.356 Specificity? When I say specificity, I mean editing the one 0:10:58.556 --> 0:11:01.556 site in the genome that we intend to and not 0:11:01.956 --> 0:11:06.076 accidentally making changes anywhere else. Right in Microsoft Word, you 0:11:06.116 --> 0:11:08.836 put the cursor exactly where you want to write new text, 0:11:09.396 --> 0:11:11.756 not a mystery where the new text is going to land. 0:11:12.596 --> 0:11:16.916 Using a biological tool like Crisper, more often than not, 0:11:17.156 --> 0:11:20.676 you edit the site that you intend to. But biology 0:11:21.156 --> 0:11:24.916 is noisy, and sometimes the system lands in places you 0:11:24.956 --> 0:11:28.916 didn't expect and can make changes in places you didn't want. 0:11:29.116 --> 0:11:31.436 That could be a problem for what you're trying to do. 0:11:31.796 --> 0:11:34.876 And so our team for years has been focused on 0:11:35.156 --> 0:11:40.316 the challenge of specificity and ultimately developing new technologies to 0:11:40.396 --> 0:11:41.276 address this head on. 0:11:42.276 --> 0:11:44.276 What percent of the time does Crisper get it wrong? 0:11:44.316 --> 0:11:45.756 It's the question I want to ask, and I'm sure 0:11:45.756 --> 0:11:48.516 that's too broad a question, But how do you think 0:11:48.516 --> 0:11:49.796 about that? How should I think about that? 0:11:50.436 --> 0:11:56.036 It varies dramatically so the way Crisper actually works, it's 0:11:56.156 --> 0:11:59.516 usually a specific protein called CAST nine that cuts the 0:11:59.596 --> 0:12:02.596 genome at the site that you're trying to edit. But 0:12:02.676 --> 0:12:05.956 CAST nine on its own can't do anything. It's inert. 0:12:06.036 --> 0:12:09.676 If you will, it needs an RNA, a piece of 0:12:09.796 --> 0:12:14.596 RNA that's actually specifically designed to match the sequence of 0:12:14.636 --> 0:12:17.316 the genome that you're trying to modify. It partners with 0:12:17.396 --> 0:12:19.996 this RNA and the RNA takes it to the right place. 0:12:20.596 --> 0:12:24.636 So depending on which RNA you've designed, the edits could 0:12:24.676 --> 0:12:28.276 be more or less specific. There are plenty of examples 0:12:28.476 --> 0:12:32.396 of first generation Crisper cast nine where you could get 0:12:32.476 --> 0:12:36.476 really efficient editing at the site you want, and really 0:12:36.476 --> 0:12:39.676 efficient editing at several other sites as well that you 0:12:39.716 --> 0:12:42.436 did not want. And then there are many of us, 0:12:42.876 --> 0:12:48.676 my company Caribou bios Sciences included, who have invented, developed 0:12:48.796 --> 0:12:52.596 access to new technologies that can overcome some of these 0:12:52.636 --> 0:12:53.876 specificity challenges. 0:12:54.396 --> 0:12:56.436 I mean, it seems like in your case that particular 0:12:56.556 --> 0:13:00.476 technology is sort of the core proposition that the company 0:13:00.556 --> 0:13:02.676 is founded on. Right, Can we take crisper and make 0:13:02.716 --> 0:13:05.036 it work more reliably? 0:13:05.436 --> 0:13:06.156 Absolutely? 0:13:06.716 --> 0:13:08.396 So, what do you do to make it work better? 0:13:09.716 --> 0:13:12.116 So? At the heart of our company is what we 0:13:12.236 --> 0:13:18.116 call the Shardona technology. Now, Shardona is an acronym. Cchr 0:13:18.316 --> 0:13:23.836 DNA stands for a mouthful crisper hybrid RNA DNA technology. 0:13:23.996 --> 0:13:25.796 You now see why we use an acronym. 0:13:25.876 --> 0:13:27.676 But each of those words, I mean, it's like a 0:13:27.796 --> 0:13:32.796 relatively sort of you know, comprehensible acronym, right, like crisper 0:13:32.876 --> 0:13:36.836 hybrid RNA DNA. It's like, that's not wildly complicated. 0:13:37.596 --> 0:13:41.116 Fair, I appreciate that, And to be fair, it does 0:13:41.156 --> 0:13:44.476 actually describe what the technology is. So I just told 0:13:44.516 --> 0:13:48.676 you usually CAST nine or other crisper proteins need an 0:13:48.916 --> 0:13:51.876 RNA partner to get to the right side in the genome. 0:13:52.396 --> 0:13:56.916 What some of my colleagues did is actually develop hybrid guides, 0:13:57.196 --> 0:14:01.196 guides that are part RNA and part DNA. And it 0:14:01.276 --> 0:14:06.476 turns out the inclusion of DNA improves the specificity dramatically. 0:14:07.116 --> 0:14:10.516 We can measure this in a very quantitative way and 0:14:10.596 --> 0:14:14.076 see that it improves the specificity of editing by many 0:14:14.236 --> 0:14:15.236 orders of magnitude. 0:14:16.196 --> 0:14:18.956 A huh, So it's not like ten percent better, it's 0:14:18.996 --> 0:14:20.996 like one hundred times better. 0:14:21.076 --> 0:14:23.636 A thousand times better, even more. In some cases. 0:14:24.596 --> 0:14:26.796 Is there a sort of layperson's answer to why. 0:14:27.876 --> 0:14:32.276 Absolutely. It all has to do with what we would 0:14:32.356 --> 0:14:39.436 call it biochemistry affinity, meaning what is the binding tightness 0:14:39.996 --> 0:14:44.556 of the crisper system for the target genome? And it 0:14:44.636 --> 0:14:50.316 might intuitively feel like higher binding, higher affinity is better, 0:14:50.836 --> 0:14:54.476 but it actually turns out the opposite is true, huh, 0:14:55.116 --> 0:14:59.596 And that by including DNA we actually decrease the affinity 0:15:00.116 --> 0:15:03.756 of the complex for the target. And the reason you 0:15:03.796 --> 0:15:07.396 want to decrease the affinity is that really the entire 0:15:07.556 --> 0:15:11.996 human genome resents a laundry list of potential off target 0:15:12.036 --> 0:15:15.196 sites we don't want to edit. So you want low 0:15:15.316 --> 0:15:18.076 enough affinity that you're not accidentally grabbing all these other 0:15:18.116 --> 0:15:21.916 pieces of the genome and instead grabbing the one site 0:15:21.956 --> 0:15:23.396 that you actually want to modify. 0:15:24.236 --> 0:15:27.036 So is the challenge then to see how low you 0:15:27.076 --> 0:15:29.516 can get the affinity and have it still work. I mean, 0:15:29.836 --> 0:15:32.196 I get that you don't want it to not bind 0:15:32.236 --> 0:15:34.076 things that it's not supposed to bind to, or not 0:15:34.156 --> 0:15:35.996 cut things that it's not supposed to cut, but you 0:15:36.036 --> 0:15:37.876 do want it to bind to or cut the thing 0:15:37.916 --> 0:15:40.076 that it is supposed to cut. So presumably there's some 0:15:41.276 --> 0:15:44.076 optimal spot or maybe what's optimal depends on the use case. 0:15:44.116 --> 0:15:46.476 But how do you strike that balance. 0:15:47.116 --> 0:15:50.316 It's a very careful balancing act. You're absolutely right. Our 0:15:50.356 --> 0:15:53.676 research team has spent a huge amount of time working 0:15:53.756 --> 0:15:57.836 on this and has found ways to really develop the 0:15:57.956 --> 0:16:02.996 appropriate way to balance these two needs for each time. 0:16:03.076 --> 0:16:03.916 We need to make an. 0:16:03.876 --> 0:16:10.116 Edit still to come on the show. How Rachel and 0:16:10.196 --> 0:16:13.276 her colleagues are using this new kind of Crisper technology 0:16:13.676 --> 0:16:27.316 to create new treatments for cancer. There's this promising new 0:16:27.396 --> 0:16:30.916 kind of cancer treatment called car T cell therapy. T 0:16:31.116 --> 0:16:33.556 cells are a key part of the immune system, and 0:16:33.596 --> 0:16:36.876 the basic idea here is to engineer T cells to 0:16:36.956 --> 0:16:40.996 attack cancer cells. As you'll hear, a few car T 0:16:41.156 --> 0:16:45.276 cell therapies have been approved, but they're complicated and expensive. 0:16:45.956 --> 0:16:48.916 So Rachel and her colleagues are using Crisper to try 0:16:48.916 --> 0:16:50.756 to come up with a new kind of car T 0:16:50.916 --> 0:16:56.516 cell therapy that is both simpler and cheaper. So let's 0:16:56.516 --> 0:16:59.316 talk about some of the some of the projects you're 0:16:59.316 --> 0:17:02.076 working on with the technology. We'll start with what's farthest 0:17:02.076 --> 0:17:03.316 along clinically. 0:17:03.036 --> 0:17:07.676 Furthest along is a cell therapy that we call CB ten, 0:17:08.236 --> 0:17:12.396 and we are developing this to treat relapsed or refractory 0:17:12.556 --> 0:17:15.756 B cell non Hodgkin lymphoma. So that's a kind of 0:17:15.756 --> 0:17:19.436 blood cancer, and it's when B cells, part of the 0:17:19.436 --> 0:17:24.196 immune system, become diseased. And so we are using our 0:17:24.316 --> 0:17:29.556 Crisper genomeediting, our Chardonnay technology to actually take healthy T 0:17:29.756 --> 0:17:34.596 cells from healthy donors and then modify them through Crisper 0:17:35.196 --> 0:17:39.156 to teach them how to find and kill these kinds 0:17:39.196 --> 0:17:44.316 of diseased B cell cancers. These therapies are called car 0:17:44.396 --> 0:17:47.276 T cell therapies. We're not the first to work on them. 0:17:47.276 --> 0:17:50.916 There are many who are advancing these kinds of therapies. 0:17:51.676 --> 0:17:55.676 And CAR again is an acronym. It stands for chimeric 0:17:55.956 --> 0:18:00.556 antigen receptor, and it describes a special protein that we 0:18:00.716 --> 0:18:05.036 can encourage the T cells to express that gives them 0:18:05.076 --> 0:18:09.916 the ability to specifically recognize and kill these B cells. 0:18:10.556 --> 0:18:15.036 As I understand it, other companies have developed car T 0:18:15.236 --> 0:18:20.956 cell therapies that take an individual patient's own immune cells 0:18:21.556 --> 0:18:25.276 and develop them in the lab essentially, and then put 0:18:25.276 --> 0:18:28.316 them back into the patient to target cancer. Right. That 0:18:28.836 --> 0:18:32.956 is unsurprisingly, very very very expensive, right, because it's sort 0:18:32.956 --> 0:18:36.236 of like you're developing a custom drug for each patient, 0:18:36.396 --> 0:18:40.076 which is great in a way, but also it's like 0:18:40.116 --> 0:18:45.036 this bespoke, sort of individually tailored drug that it just 0:18:45.116 --> 0:18:47.316 costs a lot to make and it costs a lot 0:18:47.356 --> 0:18:50.116 to buy. And so my understanding is that you're trying 0:18:50.156 --> 0:18:52.876 to develop a version that is more like a traditional 0:18:52.916 --> 0:18:56.596 drug that doesn't have to be customized to every patient. 0:18:56.716 --> 0:19:00.516 Is that right, That's exactly correct. So there are today 0:19:00.556 --> 0:19:04.956 in the United States six approved car te cell therapies, 0:19:05.516 --> 0:19:09.956 and each one of them is what's called anatologous cell therapy, 0:19:10.356 --> 0:19:14.396 which is scientific fancy word for patient specific. 0:19:14.716 --> 0:19:17.236 And so those drugs, just to be clear, those are approved, 0:19:17.276 --> 0:19:20.236 they're in use, they exist in the world. 0:19:19.756 --> 0:19:22.076 Those are approved commercial products today. 0:19:21.876 --> 0:19:24.516 And they cost like hundreds of thousands of dollars per patient. 0:19:24.996 --> 0:19:29.596 Correct. Yeah, So they are proof positive that the immune system, 0:19:29.796 --> 0:19:35.076 specifically T cells, can be incredibly powerful anti cancer agents. 0:19:35.876 --> 0:19:40.356 They also demonstrate how challenging it is to develop one 0:19:40.556 --> 0:19:44.836 batch of therapy for each and every patient. That is 0:19:44.916 --> 0:19:48.036 not scalable. That is not going to be something that 0:19:48.156 --> 0:19:52.596 delivers this kind of therapy to broader and broader patient populations, 0:19:53.236 --> 0:19:57.516 and it's also restricted to cancer patients who have sufficiently 0:19:57.596 --> 0:20:00.636 good T cells to make the product in the first place. 0:20:00.796 --> 0:20:04.116 Oh, that's interesting, Like if you're a patient in your 0:20:04.116 --> 0:20:07.396 immune system is just totally beat down by having cancer 0:20:07.476 --> 0:20:09.596 or being treated for cancer, then you don't have the 0:20:09.636 --> 0:20:11.916 T cells to generate this therapy. 0:20:12.356 --> 0:20:18.076 That's exactly correct. There's also quite a lot of complexity 0:20:18.396 --> 0:20:22.876 and almost handholding, if you will, necessary to make these 0:20:23.316 --> 0:20:29.396 patient specific therapies, and so cancer centers like MD Anderson 0:20:29.916 --> 0:20:34.676 or the University of Pennsylvania, they have tremendous expertise and 0:20:34.716 --> 0:20:37.916 they have the staff to really work with patients to 0:20:38.156 --> 0:20:41.756 shepherd them through this process to ensure that they can 0:20:41.796 --> 0:20:45.276 actually support them provide any additional therapies they need while 0:20:45.276 --> 0:20:48.676 they're waiting for their therapy to be manufactured, to give 0:20:48.716 --> 0:20:51.756 them access to this kind of therapy. But that's not 0:20:51.796 --> 0:20:54.596 where the majority of patients are treated. The majority of 0:20:54.636 --> 0:20:59.196 patients are treated in community hospitals and community clinics that 0:20:59.316 --> 0:21:03.076 don't have the resources to shepherd patients through this kind 0:21:03.156 --> 0:21:05.916 of very complex stuff. 0:21:07.036 --> 0:21:11.436 So, so what do you have to do to make 0:21:11.716 --> 0:21:13.956 a one size fits most version of this, right you 0:21:13.996 --> 0:21:15.956 want to? It would be good for the world if 0:21:15.956 --> 0:21:19.916 we could move away from having to design this drug 0:21:20.436 --> 0:21:23.236 literally for each patient and have a drug that'll work 0:21:23.276 --> 0:21:25.396 for almost everybody. That's what you're trying to do. How 0:21:25.436 --> 0:21:25.996 do you do it? 0:21:26.636 --> 0:21:29.676 Yeah, the vision is to develop what the field would 0:21:29.716 --> 0:21:34.396 call allogeneic or off the shelf car T cell therapies. 0:21:34.236 --> 0:21:37.316 Which is what most drugs are, right, Like just a 0:21:37.396 --> 0:21:40.236 drug and the doctor gives you the drug and hopefully 0:21:40.276 --> 0:21:41.036 it makes you better. 0:21:41.116 --> 0:21:44.516 Right right, So step one is we need to use 0:21:44.796 --> 0:21:48.316 healthy T cells from healthy donors instead of T cells 0:21:48.356 --> 0:21:49.396 from cancer patients. 0:21:49.436 --> 0:21:49.756 Okay. 0:21:50.556 --> 0:21:54.356 Step two is you have to make this safe. Right, Typically, 0:21:54.396 --> 0:21:56.836 if you take a T cell from one person and 0:21:56.876 --> 0:22:00.036 put it in another person, you are probably going to 0:22:00.116 --> 0:22:03.556 cause what is called graft versus host disease, which is 0:22:03.596 --> 0:22:07.236 where the other person's T cells attack parts of your. 0:22:07.156 --> 0:22:11.316 Body, analogous to what is that transplant patients have. Basically, 0:22:11.676 --> 0:22:13.596 it's like yeah. 0:22:13.236 --> 0:22:16.396 Correct, correct, So right off the bat, we have to 0:22:16.436 --> 0:22:19.236 prevent that, and we do that through genome editing by 0:22:19.236 --> 0:22:22.356 getting rid of something called the T cell receptor. It's 0:22:22.396 --> 0:22:24.396 the thing on the surface of the T cell that 0:22:24.396 --> 0:22:27.596 would usually empower it to cause graph versus host disease. 0:22:27.676 --> 0:22:30.356 So that's hitting the delete key once to get rid 0:22:30.396 --> 0:22:30.556 of that. 0:22:30.836 --> 0:22:31.196 Okay. 0:22:32.516 --> 0:22:34.756 The second step is you have to give the T 0:22:34.956 --> 0:22:38.516 cells the CAR so it knows what it's looking for 0:22:38.916 --> 0:22:42.036 on the surface of cancer cells to appropriately identify and 0:22:42.156 --> 0:22:46.356 kill them. And many of our peers stop there. Those 0:22:46.396 --> 0:22:49.396 two combined would be what they envision as a product, 0:22:50.316 --> 0:22:53.196 but our team looked at that and said, that will 0:22:53.196 --> 0:22:53.996 never be enough. 0:22:54.396 --> 0:22:56.436 And so just to be clear, when you see people stop, 0:22:56.436 --> 0:22:59.356 there are people trying that, like, is that version of 0:23:00.196 --> 0:23:02.116 this drug in trials? Now? 0:23:02.396 --> 0:23:05.436 Yes, multiple human clinical trials are being run with something 0:23:05.436 --> 0:23:06.076 that looks like. 0:23:06.036 --> 0:23:08.636 That, and so if that works, that would be a 0:23:09.236 --> 0:23:13.076 off the shelf, one sized, fistmost normal drug kind of drug. 0:23:13.196 --> 0:23:14.916 You're skeptical that it's going to work. 0:23:15.436 --> 0:23:17.316 Correct, We think you have to take it a step 0:23:17.356 --> 0:23:21.636 farther and I'll tell you why. Okay, Yeah, these off 0:23:21.676 --> 0:23:25.116 the shelf T cells, they are foreign to the patient's 0:23:25.116 --> 0:23:28.156 immune system, and the patient's immune system is going to 0:23:28.196 --> 0:23:32.196 figure that out fairly quickly and actually kill off the 0:23:32.236 --> 0:23:35.676 CAR T cells. And that's very different from when you've 0:23:35.676 --> 0:23:38.036 had a product made from your very own T cells. 0:23:38.116 --> 0:23:41.036 They can last for a very long time, and so 0:23:41.076 --> 0:23:44.356 we look at that differential in time and say that's 0:23:44.356 --> 0:23:45.636 a problem we have to solve. 0:23:45.916 --> 0:23:48.516 Why doesn't everybody agree with you? 0:23:49.916 --> 0:23:52.196 I would say more and more people agree with us 0:23:52.196 --> 0:23:54.916 if you look at what's happening in the field. In fact, 0:23:55.036 --> 0:23:58.116 many of the first off the shelf car T cells 0:23:58.156 --> 0:24:00.996 that have been tried in human clinical trials have been 0:24:00.996 --> 0:24:03.996 retired because they didn't work as well as people had hoped. 0:24:04.356 --> 0:24:06.196 And I think many are now going back to the 0:24:06.276 --> 0:24:09.636 drawing board to think about what are other things we 0:24:09.716 --> 0:24:13.396 can do to empower or enhance these T cells to 0:24:13.436 --> 0:24:14.556