1 00:00:15,356 --> 00:00:26,956 Speaker 1: Pushkin. I love vaccines, I really do. Vaccines train your 2 00:00:26,996 --> 00:00:32,316 Speaker 1: body to make these antibodies that protect you against deadly diseases. 3 00:00:33,196 --> 00:00:35,516 Speaker 1: It's a thing you get so you don't get sick 4 00:00:35,596 --> 00:00:38,396 Speaker 1: in the first place, and it's so clever and so 5 00:00:38,636 --> 00:00:42,996 Speaker 1: elegant and so obviously useful. I think it is honestly 6 00:00:43,036 --> 00:00:45,756 Speaker 1: fair to say that vaccines are truly one of the 7 00:00:45,916 --> 00:00:49,236 Speaker 1: greatest inventions of all time, on the very short list. 8 00:00:49,236 --> 00:00:52,356 Speaker 1: They've saved hundreds of millions of lives. Give me all 9 00:00:52,396 --> 00:00:57,156 Speaker 1: of them, Give me all of the vaccines. But I 10 00:00:57,196 --> 00:01:03,276 Speaker 1: gotta say the flu vaccine sucks. The flu vaccine sucks. 11 00:01:03,356 --> 00:01:08,196 Speaker 1: It really does, And for a somewhat simple reason. The 12 00:01:08,276 --> 00:01:12,476 Speaker 1: flu virus mutates so quickly that we can't come up 13 00:01:12,516 --> 00:01:15,596 Speaker 1: with vaccines fast enough to keep up with it. So 14 00:01:16,036 --> 00:01:19,596 Speaker 1: every year scientists develop a new vaccine, but even in 15 00:01:19,636 --> 00:01:23,236 Speaker 1: the time it takes to manufacture that vaccine, the virus 16 00:01:23,316 --> 00:01:26,436 Speaker 1: keeps mutating. As a result, even if you get a 17 00:01:26,436 --> 00:01:29,156 Speaker 1: flu shot every year, there's still a good chance that 18 00:01:29,196 --> 00:01:31,956 Speaker 1: you'll get a bad case of the flu. Last year's 19 00:01:31,996 --> 00:01:35,676 Speaker 1: flu shot, for example, was only about thirty five percent effective, 20 00:01:36,676 --> 00:01:39,876 Speaker 1: And so for decades now, scientists have asked a fairly 21 00:01:39,916 --> 00:01:43,076 Speaker 1: obvious question, is there some way to come up with 22 00:01:43,116 --> 00:01:45,836 Speaker 1: a flu vaccine that would work not just for the 23 00:01:45,876 --> 00:01:48,796 Speaker 1: strain of flu that is circulating right now, but for 24 00:01:48,916 --> 00:01:52,556 Speaker 1: almost all strains of flu, including strains that haven't even 25 00:01:52,676 --> 00:02:01,556 Speaker 1: evolved yet. I'm Jacob Goldstein and this is What's Your Problem, 26 00:02:01,596 --> 00:02:03,516 Speaker 1: the show where I talk to people who are trying 27 00:02:03,556 --> 00:02:07,916 Speaker 1: to make technological progress. My guest today is Jacob Glanville. 28 00:02:08,036 --> 00:02:11,956 Speaker 1: He's a bioengineer and an immunologist, and he's the founder 29 00:02:11,996 --> 00:02:15,396 Speaker 1: and CEO of Centivax, a company that's trying to make 30 00:02:15,596 --> 00:02:19,916 Speaker 1: a universal flu vaccine, a flu vaccine that will consistently 31 00:02:20,036 --> 00:02:23,076 Speaker 1: and reliably prevent people from getting the flu. 32 00:02:23,396 --> 00:02:26,916 Speaker 2: You imagine talking to a generation that didn't have flu anymore. 33 00:02:26,956 --> 00:02:27,996 Speaker 3: They would think we were nuts. 34 00:02:28,036 --> 00:02:29,676 Speaker 2: They were just like, oh, yeah, every year we have 35 00:02:29,716 --> 00:02:32,636 Speaker 2: a circulating pandemic and then six months later there's another one, 36 00:02:32,636 --> 00:02:34,596 Speaker 2: and yeah, you know, fifty thousand people die. 37 00:02:34,676 --> 00:02:37,396 Speaker 3: But what do you do? And like, that's nuts, But 38 00:02:37,916 --> 00:02:38,876 Speaker 3: we take it for granted. 39 00:02:40,076 --> 00:02:43,556 Speaker 1: The vaccine that Jacob's company, Centivax, is developing for flu, 40 00:02:43,876 --> 00:02:47,596 Speaker 1: is likely to go into human trials next year. The 41 00:02:47,596 --> 00:02:51,676 Speaker 1: company is also in earlier stages of developing universal vaccines 42 00:02:51,716 --> 00:02:56,996 Speaker 1: for HIV and COVID, among other diseases, and wildcard. They 43 00:02:56,996 --> 00:03:00,876 Speaker 1: have also worked on creating a broadly effective anti venom 44 00:03:01,116 --> 00:03:04,036 Speaker 1: for snake bites. We talk about snake bites later in 45 00:03:04,076 --> 00:03:08,076 Speaker 1: the conversation. To start, Jacob told me about the moment 46 00:03:08,116 --> 00:03:11,756 Speaker 1: he first got the ia for a universal vaccine. It 47 00:03:11,836 --> 00:03:14,836 Speaker 1: was around twenty twelve. He was working for the drug 48 00:03:14,836 --> 00:03:18,356 Speaker 1: company Feizer, and he wasn't working on vaccines, but he 49 00:03:18,516 --> 00:03:22,996 Speaker 1: was doing something related. His job was to identify antibodies 50 00:03:23,036 --> 00:03:25,796 Speaker 1: that could be used to treat disease, and at this 51 00:03:25,876 --> 00:03:29,156 Speaker 1: particular moment, he was studying antibodies that would bind to 52 00:03:29,236 --> 00:03:33,076 Speaker 1: a particular protein called PCSK nine. 53 00:03:33,516 --> 00:03:35,876 Speaker 2: And so I was riding back on my motorcycle one 54 00:03:35,916 --> 00:03:38,996 Speaker 2: evening and I was reflecting on this problem where there 55 00:03:39,036 --> 00:03:41,916 Speaker 2: was this target called PCSK nine. It kind of looks 56 00:03:41,956 --> 00:03:47,076 Speaker 2: like Mickey mouse's head, and they really wanted antibodies against 57 00:03:47,196 --> 00:03:49,556 Speaker 2: kind of where the neck is that if you get 58 00:03:49,556 --> 00:03:50,556 Speaker 2: an anybody there. 59 00:03:50,476 --> 00:03:53,596 Speaker 3: Then that can affect cholesterol and lower cholesterol. 60 00:03:54,156 --> 00:03:56,436 Speaker 2: The problem is that they're getting anybodies against the ears, 61 00:03:57,316 --> 00:03:58,756 Speaker 2: and they weren't getting anybodies. 62 00:03:58,396 --> 00:03:58,996 Speaker 3: Against the neck. 63 00:03:59,236 --> 00:04:00,516 Speaker 2: And so I was trying to figure out, is there 64 00:04:00,516 --> 00:04:03,196 Speaker 2: an engineering way to sort of focus the immune system 65 00:04:03,356 --> 00:04:06,436 Speaker 2: at arbitrary sites that would save me a bunch of time. 66 00:04:06,756 --> 00:04:09,636 Speaker 2: And I started imagining, what if I were to take 67 00:04:10,356 --> 00:04:13,556 Speaker 2: that target not just from humans, but from like a 68 00:04:13,596 --> 00:04:18,276 Speaker 2: donkey and an alligator and a chicken, and like just 69 00:04:18,716 --> 00:04:21,956 Speaker 2: take a swath of different versions of that. They were 70 00:04:21,956 --> 00:04:24,196 Speaker 2: different just about everywhere up in the ears, but they 71 00:04:24,196 --> 00:04:25,916 Speaker 2: were the same down where the neck was. 72 00:04:26,196 --> 00:04:26,436 Speaker 1: Huh. 73 00:04:26,796 --> 00:04:27,476 Speaker 3: And then if I. 74 00:04:27,516 --> 00:04:30,556 Speaker 2: Mixed those together and diluted each one so there wasn't 75 00:04:30,676 --> 00:04:33,436 Speaker 2: enough of any one of the species of PCSK nine, 76 00:04:33,636 --> 00:04:35,996 Speaker 2: then maybe only the neck would be the thing which 77 00:04:36,076 --> 00:04:37,956 Speaker 2: was shared across all of them, and the entire immune 78 00:04:37,956 --> 00:04:39,356 Speaker 2: system would focus on uh huh. 79 00:04:39,396 --> 00:04:41,756 Speaker 1: So like in total, the sort of sum total of 80 00:04:42,556 --> 00:04:44,316 Speaker 1: the mix, it would be like a lot of neck. 81 00:04:44,476 --> 00:04:46,956 Speaker 1: The neck is conserved. The neck is what is the same, 82 00:04:47,516 --> 00:04:51,556 Speaker 1: and there's only enough of that to induce the antibody response. 83 00:04:51,756 --> 00:04:54,356 Speaker 1: So that then if you whatever inject that into an 84 00:04:54,436 --> 00:04:56,916 Speaker 1: animal or a person, what the person's immune system is 85 00:04:56,956 --> 00:04:58,476 Speaker 1: going to see is a lot of neck. 86 00:04:58,676 --> 00:05:00,636 Speaker 2: Yeah, And so they finally focus on the neck instead 87 00:05:00,636 --> 00:05:02,956 Speaker 2: of getting distracted by the ears. That was the principle, 88 00:05:03,716 --> 00:05:05,436 Speaker 2: And so I got home, and then at a certain 89 00:05:05,436 --> 00:05:07,956 Speaker 2: point I realized I was being an idiot and what 90 00:05:08,316 --> 00:05:10,116 Speaker 2: this was was not a way to save a few 91 00:05:10,116 --> 00:05:13,876 Speaker 2: months on an Anybody discovery campaign, that this was a 92 00:05:13,876 --> 00:05:16,236 Speaker 2: potential window opening to the to the. 93 00:05:16,196 --> 00:05:17,596 Speaker 3: Holy grail of vaccine science. 94 00:05:17,836 --> 00:05:21,076 Speaker 2: The holy grail is that all of the major viruses 95 00:05:21,076 --> 00:05:26,836 Speaker 2: that we're confronted with flu, influenza, HIV, ebola, these viruses 96 00:05:26,916 --> 00:05:30,956 Speaker 2: mutate and change, but they always have some little spot 97 00:05:31,036 --> 00:05:34,316 Speaker 2: that they cannot mutate. And those spots are always super important. 98 00:05:34,316 --> 00:05:36,596 Speaker 2: That's why they can't mutate it because if you mutate it, 99 00:05:36,596 --> 00:05:37,276 Speaker 2: the virus. 100 00:05:37,036 --> 00:05:38,036 Speaker 3: Is no longer infectious. 101 00:05:38,116 --> 00:05:41,396 Speaker 2: Yeah, And normally they get away with it by having 102 00:05:41,596 --> 00:05:44,676 Speaker 2: distracting areas and most of the surface that can mutate. 103 00:05:44,796 --> 00:05:46,916 Speaker 2: And that's why we have to update our flu shots 104 00:05:46,916 --> 00:05:47,356 Speaker 2: every year. 105 00:05:47,716 --> 00:05:50,916 Speaker 1: Distracting meaning distracting to our immune systems, like our more 106 00:05:50,916 --> 00:05:53,836 Speaker 1: immune systems. Ooh, I like the ears. I like that 107 00:05:53,876 --> 00:05:57,036 Speaker 1: shiny part on top, and that's exactly Yeah. 108 00:05:57,076 --> 00:06:00,076 Speaker 2: Basically, the conserved Achilles heel is a small site and 109 00:06:00,116 --> 00:06:02,156 Speaker 2: most of the surface can vary, and it can't it 110 00:06:02,196 --> 00:06:04,756 Speaker 2: gets away with not changing the critical site by varying 111 00:06:04,796 --> 00:06:07,116 Speaker 2: lots of stuff around it and taking advantage of the 112 00:06:07,156 --> 00:06:09,476 Speaker 2: fact that the immune system doesn't know the difference, and 113 00:06:09,516 --> 00:06:12,756 Speaker 2: so to the ability to focus the immune system against 114 00:06:12,756 --> 00:06:16,476 Speaker 2: a conserve site would be the basis of a universal vaccine, 115 00:06:16,556 --> 00:06:19,876 Speaker 2: because instead of targeting one strain of flu or one 116 00:06:19,916 --> 00:06:23,476 Speaker 2: strain of coronavirus or one strain of HIV, you could 117 00:06:23,556 --> 00:06:25,916 Speaker 2: target the shared sites that the virus is never allowed 118 00:06:25,956 --> 00:06:28,076 Speaker 2: to mutate. And if you do that, then you're suddenly 119 00:06:28,156 --> 00:06:31,276 Speaker 2: hitting the entire class of influenza viruses, including future ones 120 00:06:31,276 --> 00:06:32,156 Speaker 2: that haven't evolved yet. 121 00:06:32,236 --> 00:06:32,356 Speaker 3: Right. 122 00:06:32,756 --> 00:06:34,876 Speaker 1: I mean that part of the idea is the part 123 00:06:34,916 --> 00:06:38,876 Speaker 1: everybody knew already, right, Like that is the relatively obvious idea. 124 00:06:38,876 --> 00:06:41,036 Speaker 1: It's like, don't go for the part that changes, go 125 00:06:41,196 --> 00:06:43,276 Speaker 1: for the part that's the same. Right. The hard thing 126 00:06:43,876 --> 00:06:47,876 Speaker 1: is how do you do that? So had when you 127 00:06:47,956 --> 00:06:50,636 Speaker 1: described the idea of like, oh, just take a bunch 128 00:06:50,636 --> 00:06:55,116 Speaker 1: of different ones, dilute them, mix them together. Nobody had 129 00:06:55,196 --> 00:06:56,076 Speaker 1: thought of that before. 130 00:06:56,796 --> 00:07:01,476 Speaker 2: Yeah, so surprisingly not to your point, people since the 131 00:07:01,556 --> 00:07:04,756 Speaker 2: nineties were aware of these conserve sites, and so they 132 00:07:04,836 --> 00:07:05,836 Speaker 2: knew where the sites were. 133 00:07:05,916 --> 00:07:08,156 Speaker 3: We had crystal structures it was just, how the hell 134 00:07:08,196 --> 00:07:10,036 Speaker 3: do you get the immune system focus on those sites? 135 00:07:10,116 --> 00:07:12,436 Speaker 3: Was the problem. Yeah, and people have tried a couple 136 00:07:12,436 --> 00:07:12,916 Speaker 3: different things. 137 00:07:12,956 --> 00:07:15,676 Speaker 2: They tried chopping out parts of the protein, but then 138 00:07:15,716 --> 00:07:18,036 Speaker 2: the site you're interested in falls apart. It's like trying 139 00:07:18,036 --> 00:07:21,476 Speaker 2: to grab a snowflake. It'll melt in your hands. They 140 00:07:21,516 --> 00:07:23,956 Speaker 2: tried a couple other techniques that didn't work out. 141 00:07:24,756 --> 00:07:26,956 Speaker 1: So okay, so you have this new idea for how 142 00:07:26,996 --> 00:07:30,396 Speaker 1: to make a universal vaccine that nobody's tried before, which 143 00:07:30,516 --> 00:07:33,156 Speaker 1: to use flu for an example, would mean you take 144 00:07:33,196 --> 00:07:36,076 Speaker 1: a bunch of different strains of flu, and in particular 145 00:07:36,116 --> 00:07:38,996 Speaker 1: the sort of spike protein of the flu that your 146 00:07:39,196 --> 00:07:42,796 Speaker 1: immune system sees. Then you dilute them and mix them 147 00:07:42,836 --> 00:07:46,036 Speaker 1: all together in a single vaccine. So what the patient's 148 00:07:46,036 --> 00:07:48,436 Speaker 1: immune system winds up seeing the most of is the 149 00:07:48,476 --> 00:07:52,196 Speaker 1: part that's the same in all those different strains, the 150 00:07:52,236 --> 00:07:55,396 Speaker 1: part that doesn't change. And then ideally the patient will 151 00:07:55,436 --> 00:07:59,716 Speaker 1: develop antibodies to that part, the part that doesn't change, 152 00:08:00,116 --> 00:08:02,716 Speaker 1: and therefore the patient will be immune to like almost 153 00:08:02,796 --> 00:08:03,676 Speaker 1: any strain of flu. 154 00:08:04,076 --> 00:08:06,196 Speaker 3: Yeah, and you recognize it might not work right. 155 00:08:06,276 --> 00:08:08,236 Speaker 2: You always are like, look, this is a pipe drain, 156 00:08:08,276 --> 00:08:09,916 Speaker 2: but like I could not go to sleep because I 157 00:08:09,956 --> 00:08:11,796 Speaker 2: was like, if this works, this is such a stunning 158 00:08:11,796 --> 00:08:14,756 Speaker 2: breakthrough that it's like it's hard to sleep when you're 159 00:08:14,796 --> 00:08:15,396 Speaker 2: thinking about that. 160 00:08:15,476 --> 00:08:16,916 Speaker 3: It sort of becomes all consuming. 161 00:08:17,756 --> 00:08:21,316 Speaker 1: So you get this idea, and you're working for Pfeiser, 162 00:08:22,316 --> 00:08:26,396 Speaker 1: a company that makes vaccines. By the way, what do 163 00:08:26,436 --> 00:08:26,756 Speaker 1: you do? 164 00:08:27,756 --> 00:08:27,956 Speaker 3: Yeah? 165 00:08:27,996 --> 00:08:31,436 Speaker 2: So again, I was not doing anything involving their vaccine group. 166 00:08:31,436 --> 00:08:33,556 Speaker 1: I was doing for intellectual property reason. 167 00:08:33,636 --> 00:08:36,476 Speaker 3: Ye. Yes, I was not working on vaccines at Pfizer. 168 00:08:38,876 --> 00:08:41,076 Speaker 3: I resigned. So I did two things. 169 00:08:41,116 --> 00:08:45,236 Speaker 2: I started my first company, Distributed Bio, and I also 170 00:08:45,276 --> 00:08:48,436 Speaker 2: applied for the PhD program in immunology at Stanford. 171 00:08:48,516 --> 00:08:50,516 Speaker 1: And you do this because of your idea? 172 00:08:51,076 --> 00:08:51,356 Speaker 3: Yeah? 173 00:08:51,516 --> 00:08:55,876 Speaker 2: Yeah, Because basically I applied to the PhD program because 174 00:08:55,876 --> 00:08:58,716 Speaker 2: I was like, if I'm wrong, I need to stop 175 00:08:58,716 --> 00:09:01,396 Speaker 2: thinking about this. I need to surround myself with brilliant 176 00:09:01,396 --> 00:09:03,996 Speaker 2: immunologists who can kick holes in this, and I need 177 00:09:04,036 --> 00:09:06,316 Speaker 2: to be able to make sure I'm not being myopic. 178 00:09:06,476 --> 00:09:09,956 Speaker 3: And then if I'm right, I need the world to 179 00:09:09,956 --> 00:09:10,276 Speaker 3: hear me. 180 00:09:10,396 --> 00:09:12,516 Speaker 2: And so I need to be a card carrying PhD 181 00:09:12,556 --> 00:09:15,236 Speaker 2: immunologists from Stanford so that people go, Okay, this guy 182 00:09:15,316 --> 00:09:19,716 Speaker 2: is into some Yahoo and then for the company side, 183 00:09:19,996 --> 00:09:21,956 Speaker 2: I just saw this opportunity to be able to go 184 00:09:22,036 --> 00:09:24,076 Speaker 2: test it because I originally I did go out and 185 00:09:24,116 --> 00:09:26,796 Speaker 2: I try to talk to some vcs in twenty twelve, 186 00:09:27,556 --> 00:09:29,556 Speaker 2: and I think there, you know, predictably, their answer is like, 187 00:09:29,556 --> 00:09:30,156 Speaker 2: what the hell is this? 188 00:09:30,236 --> 00:09:31,036 Speaker 3: And who the hell are you? 189 00:09:31,116 --> 00:09:34,396 Speaker 1: And you were a bachelor's degree, right, we'd worked at 190 00:09:34,636 --> 00:09:37,556 Speaker 1: Miser for a couple of years, like a million other people, 191 00:09:37,676 --> 00:09:38,476 Speaker 1: so not you. 192 00:09:38,476 --> 00:09:40,196 Speaker 3: Know, you can't blame him. I was like, I guess 193 00:09:40,236 --> 00:09:41,836 Speaker 3: I'm nobody right now. Let me go fix that. 194 00:09:41,996 --> 00:09:45,716 Speaker 2: Yeah, And so I decided that I was going to 195 00:09:45,796 --> 00:09:48,956 Speaker 2: go found a company because there was some work I 196 00:09:49,036 --> 00:09:51,996 Speaker 2: was doing at Pfeiser that i'd public created some publications 197 00:09:52,036 --> 00:09:54,076 Speaker 2: on using the deep genomic sequencers to look at the 198 00:09:54,076 --> 00:09:57,476 Speaker 2: immune system and then building better anybody libraries with what 199 00:09:57,476 --> 00:09:59,796 Speaker 2: we learned about that, and I realized there was a 200 00:09:59,796 --> 00:10:01,956 Speaker 2: business that could be built on that. And my intention 201 00:10:02,116 --> 00:10:04,276 Speaker 2: was to build that business and use it to subsidize 202 00:10:04,276 --> 00:10:07,676 Speaker 2: some of the early proof deep risking experiments. 203 00:10:07,156 --> 00:10:09,916 Speaker 3: On this universal vaccine concept. And so that's what I did. 204 00:10:09,956 --> 00:10:12,516 Speaker 2: So I just did both for five years and didn't 205 00:10:12,516 --> 00:10:15,716 Speaker 2: sleep that much until the PhD. Graduated from that, and 206 00:10:15,716 --> 00:10:17,956 Speaker 2: then later I sold the first company distributed by it. 207 00:10:18,076 --> 00:10:20,796 Speaker 1: So the company you start you're selling your clients are 208 00:10:20,876 --> 00:10:24,796 Speaker 1: drug companies essentially, right, But you're doing that that's sort 209 00:10:24,836 --> 00:10:28,556 Speaker 1: of your side hustle. That's sort of funding your vaccine dream. Right. 210 00:10:29,116 --> 00:10:34,556 Speaker 1: And while you're doing that, you start doing this research 211 00:10:34,956 --> 00:10:39,236 Speaker 1: on your vaccine in pigs in Guatemala, right, tell me 212 00:10:39,276 --> 00:10:39,756 Speaker 1: about that. 213 00:10:40,876 --> 00:10:43,596 Speaker 2: The background is I grew up in Guatemala. My parents 214 00:10:43,596 --> 00:10:46,876 Speaker 2: are Americans, but they met in Guatemala in the seventies 215 00:10:46,916 --> 00:10:49,516 Speaker 2: and they built this hotel and restaurant with my grandmother. 216 00:10:50,316 --> 00:10:51,276 Speaker 1: Hippie dream. 217 00:10:51,876 --> 00:10:53,676 Speaker 3: Yeah, the hippie dream, that's exactly what it is. 218 00:10:53,676 --> 00:10:57,156 Speaker 2: There's small hippie enclaves down there, and then there's most 219 00:10:57,156 --> 00:10:59,276 Speaker 2: of the village is the wheel may In and then 220 00:10:59,316 --> 00:11:01,796 Speaker 2: there's Katchi Kels and some other Mayan communities, and it's 221 00:11:01,876 --> 00:11:04,436 Speaker 2: very beautiful lake. So it makes sense that the hippies 222 00:11:04,436 --> 00:11:04,916 Speaker 2: would go there. 223 00:11:05,556 --> 00:11:07,036 Speaker 3: The Civil War largely. 224 00:11:06,796 --> 00:11:09,276 Speaker 2: Drove them away, but my family, when I was a 225 00:11:09,276 --> 00:11:11,076 Speaker 2: little boy, they went down there to try to fix 226 00:11:11,156 --> 00:11:13,196 Speaker 2: up and sell the property. And then one thing led 227 00:11:13,196 --> 00:11:15,556 Speaker 2: to another and we ended up becoming innkeepers. 228 00:11:14,996 --> 00:11:18,356 Speaker 3: And so I grew up in the village. 229 00:11:19,876 --> 00:11:21,716 Speaker 2: I think it probably had an effect on my interest 230 00:11:21,756 --> 00:11:24,316 Speaker 2: in immunology in the first place. And I had this 231 00:11:24,316 --> 00:11:27,196 Speaker 2: connection to Guatemala, and I ended up maintaining a connection 232 00:11:27,316 --> 00:11:29,996 Speaker 2: to USAK, which is the University of San Carlos, the 233 00:11:30,476 --> 00:11:34,636 Speaker 2: National University. And so fast forward in my career too, 234 00:11:34,676 --> 00:11:38,236 Speaker 2: when I was thinking about universal vaccines, like one of 235 00:11:38,236 --> 00:11:41,076 Speaker 2: my I say, one of my deep impressions left from 236 00:11:41,076 --> 00:11:43,556 Speaker 2: some work adviser was this. I was very impressed with 237 00:11:43,556 --> 00:11:46,676 Speaker 2: a group that was doing animal health work because I 238 00:11:46,716 --> 00:11:49,436 Speaker 2: felt like, instead of using mice, they would often ask 239 00:11:49,476 --> 00:11:52,396 Speaker 2: what's the most relevant and similar animal model to humans 240 00:11:52,436 --> 00:11:55,516 Speaker 2: for this indication? Mouse is not a person like no 241 00:11:55,636 --> 00:11:57,596 Speaker 2: animal as a person, but you can find something that's 242 00:11:57,636 --> 00:12:01,556 Speaker 2: a closer fit and waste less time on failed translation. 243 00:12:02,556 --> 00:12:04,916 Speaker 2: And so I liked I had this technology. I was 244 00:12:04,916 --> 00:12:06,956 Speaker 2: trying to figure out where to apply it. I actually 245 00:12:06,956 --> 00:12:08,556 Speaker 2: called one of the guys and I was like, what's 246 00:12:08,596 --> 00:12:13,196 Speaker 2: the venor market that has a rapidly mutating pathogen that's 247 00:12:13,196 --> 00:12:14,196 Speaker 2: also found in humans? 248 00:12:15,116 --> 00:12:17,396 Speaker 3: And he said, it's definitely flu in pigs. 249 00:12:17,476 --> 00:12:19,916 Speaker 2: They get the flu in fact they transmitted to humans, 250 00:12:20,316 --> 00:12:23,156 Speaker 2: and so pigs are definitely not as convenient as mice, 251 00:12:23,196 --> 00:12:24,756 Speaker 2: but I felt that the data would be much more 252 00:12:24,796 --> 00:12:26,676 Speaker 2: meaningful because they actually get the flu. 253 00:12:26,796 --> 00:12:27,036 Speaker 1: Yeah. 254 00:12:27,636 --> 00:12:30,436 Speaker 2: So I ended up doing it back in Guatemala with 255 00:12:30,956 --> 00:12:34,436 Speaker 2: Airwin Calagua, my collaborator at the University of San Carlos, 256 00:12:35,036 --> 00:12:36,996 Speaker 2: and some property that my father had. So I ended 257 00:12:37,036 --> 00:12:38,916 Speaker 2: up making some calls. I found out we could get 258 00:12:38,916 --> 00:12:41,156 Speaker 2: the pigs. There was a vet who was involved in 259 00:12:41,196 --> 00:12:44,156 Speaker 2: the H one in one two thousand and nine pandemic 260 00:12:44,156 --> 00:12:45,116 Speaker 2: shift monitoring. 261 00:12:45,436 --> 00:12:48,836 Speaker 1: You're doing it in Guatemala because it's cheaper. Basically you're offshoring. 262 00:12:48,916 --> 00:12:52,316 Speaker 2: You're yeah, it's way cheaper, radically cheaper and faster. I 263 00:12:52,316 --> 00:12:55,276 Speaker 2: think if the cycle time is astonishingly slow to do 264 00:12:55,396 --> 00:12:57,756 Speaker 2: animal studies and ask for grants like you're lucky to 265 00:12:57,796 --> 00:12:59,436 Speaker 2: get a study done like once every two and a 266 00:12:59,476 --> 00:13:03,076 Speaker 2: half years according to the US model, Whereas in Guatemala 267 00:13:03,236 --> 00:13:05,556 Speaker 2: the costs were radically cheaper. I could build a facility 268 00:13:05,596 --> 00:13:07,836 Speaker 2: to spec and I was, you know, I'm an engineer, 269 00:13:07,876 --> 00:13:09,916 Speaker 2: so I need to be able to do cycle yeah. Yeah, 270 00:13:09,956 --> 00:13:12,596 Speaker 2: and so this enabled me. I think we ran five studies. 271 00:13:12,276 --> 00:13:13,796 Speaker 3: There over a couple of year period. 272 00:13:13,836 --> 00:13:15,996 Speaker 2: We're able to go pretty quickly go in and do 273 00:13:16,196 --> 00:13:19,796 Speaker 2: rapidly de risk this universal vaccine technology in a way 274 00:13:19,796 --> 00:13:23,356 Speaker 2: that was economically feasible given the growing profits but still 275 00:13:23,396 --> 00:13:26,476 Speaker 2: finite profits that I had from the Anybody discovery and 276 00:13:26,556 --> 00:13:27,716 Speaker 2: software side of the business. 277 00:13:27,996 --> 00:13:30,276 Speaker 1: So when you're doing those pig studies, I mean just 278 00:13:30,316 --> 00:13:34,436 Speaker 1: to return to your initial idea of using essentially different 279 00:13:34,476 --> 00:13:38,276 Speaker 1: different strains. Let's say you got to figure out what's 280 00:13:38,316 --> 00:13:41,556 Speaker 1: the right concentration, because if you do too little, it's 281 00:13:41,836 --> 00:13:44,676 Speaker 1: you don't get any meaningful immune response, and if you 282 00:13:44,716 --> 00:13:46,756 Speaker 1: do too much, then you're getting immune response to the 283 00:13:46,756 --> 00:13:48,636 Speaker 1: parts that are not conserved, to the parts that you 284 00:13:48,676 --> 00:13:50,796 Speaker 1: don't want immune response to exactly. 285 00:13:50,836 --> 00:13:52,796 Speaker 2: I was just just proving the concept right because I 286 00:13:52,796 --> 00:13:54,636 Speaker 2: think there's definitely people who are like, this isn't going 287 00:13:54,716 --> 00:13:54,956 Speaker 2: to work. 288 00:13:54,996 --> 00:13:55,596 Speaker 3: There's no way. 289 00:13:56,516 --> 00:13:59,316 Speaker 2: And look, if I'm wrong, then if it doesn't matter 290 00:13:59,356 --> 00:14:01,516 Speaker 2: if I put fifteen things in, if each one's below 291 00:14:01,516 --> 00:14:04,316 Speaker 2: the dose and they're not interacting like I was hypothesizing, 292 00:14:04,436 --> 00:14:06,676 Speaker 2: then you should see no immune response. 293 00:14:06,756 --> 00:14:08,196 Speaker 3: Right, So I could have just been wrong. That's the 294 00:14:08,236 --> 00:14:10,596 Speaker 3: other thing I was testing, does the principle hold? And 295 00:14:10,796 --> 00:14:12,356 Speaker 3: the answer was definitively yes. 296 00:14:13,036 --> 00:14:14,996 Speaker 1: So okay, So you have this idea that it works 297 00:14:16,236 --> 00:14:18,996 Speaker 1: somewhere around here, you sell I don't know which one 298 00:14:18,996 --> 00:14:20,796 Speaker 1: is the side hustle and which one is the main hustle. 299 00:14:20,836 --> 00:14:24,276 Speaker 1: I guess vaccinating pigs in Guatemala sounds like a side hustle, 300 00:14:24,316 --> 00:14:26,396 Speaker 1: even though it's the thing you really care about. Right, 301 00:14:28,236 --> 00:14:32,396 Speaker 1: you sell distributed bio and you've spin out sent to 302 00:14:32,476 --> 00:14:37,956 Speaker 1: vax the vaccine company, right, and then what then where 303 00:14:37,996 --> 00:14:38,236 Speaker 1: are you? 304 00:14:38,796 --> 00:14:41,596 Speaker 3: Yeah? So it was a good time. 305 00:14:41,676 --> 00:14:46,196 Speaker 2: So we got the Gates Foundation awarded us this in 306 00:14:46,236 --> 00:14:49,196 Speaker 2: the Pandemic Threatgrand Challenge award to test the vaccine no 307 00:14:49,236 --> 00:14:52,636 Speaker 2: longer in Guatemala, but up in American facilities that had 308 00:14:52,756 --> 00:14:56,516 Speaker 2: biosafety containment, so that we could challenge the animals who've 309 00:14:56,556 --> 00:15:00,196 Speaker 2: been vaccinated with these strains that had evolved after the mixture. 310 00:15:00,276 --> 00:15:03,036 Speaker 2: So we deliberately pretended it was two thousand and seven 311 00:15:03,436 --> 00:15:05,516 Speaker 2: and only included strains up to two thousand and seven. 312 00:15:06,036 --> 00:15:08,156 Speaker 2: Then we challenged the animals with the two thousand and 313 00:15:08,196 --> 00:15:11,756 Speaker 2: nine pandemic shift virus, a twenty twelve a twenty seventeen virus. 314 00:15:12,036 --> 00:15:15,036 Speaker 1: That's a big question, right, It's like testing something that's 315 00:15:15,036 --> 00:15:18,276 Speaker 1: out of the model, right, Like it's saying, Okay, we 316 00:15:18,356 --> 00:15:21,276 Speaker 1: give somebody this vaccine and then there's a new kind 317 00:15:21,276 --> 00:15:24,796 Speaker 1: of flu. Does it work? Yeah? Yeah, And it. 318 00:15:24,836 --> 00:15:25,836 Speaker 3: Felt that that was essential. 319 00:15:26,076 --> 00:15:28,036 Speaker 2: By the way, those same pigs we pulled their serum 320 00:15:28,076 --> 00:15:30,036 Speaker 2: out of the freezer over the last couple of months 321 00:15:30,076 --> 00:15:32,396 Speaker 2: and they neutralized the H five and one that's currently 322 00:15:32,436 --> 00:15:34,916 Speaker 2: outbreaking in cows and chickens and some people. 323 00:15:34,956 --> 00:15:37,596 Speaker 1: Huh the bird flu. 324 00:15:36,236 --> 00:15:38,556 Speaker 3: The great super broad immune response. 325 00:15:39,596 --> 00:15:43,476 Speaker 2: So the timing was good. CR wanted to buy. I 326 00:15:43,516 --> 00:15:47,836 Speaker 2: was happy to do it, and my condition was I'm like, look, 327 00:15:47,876 --> 00:15:50,676 Speaker 2: I want to take this universal vaccine technology with me 328 00:15:50,756 --> 00:15:52,476 Speaker 2: to a new company, and they agreed to that. That 329 00:15:52,636 --> 00:15:56,116 Speaker 2: was December thirty first, twenty twenty is when when the 330 00:15:56,316 --> 00:15:59,636 Speaker 2: sale completed, and so basically January first. 331 00:15:59,636 --> 00:16:02,036 Speaker 1: That is a remarkable time to go all in on 332 00:16:02,076 --> 00:16:05,676 Speaker 1: a universal vaccine. December thirty first, twenty twenty. 333 00:16:06,036 --> 00:16:09,996 Speaker 2: We transitioned over January first, twenty twenty one. I'm now 334 00:16:10,036 --> 00:16:12,916 Speaker 2: the CEO and founder of Cinevacs, and I started calling 335 00:16:12,996 --> 00:16:15,036 Speaker 2: an army of geniuses of the best people that I've 336 00:16:15,076 --> 00:16:17,156 Speaker 2: worked with to gather together, and I was like, look, 337 00:16:17,196 --> 00:16:18,436 Speaker 2: this is going to be the big one. 338 00:16:18,316 --> 00:16:21,276 Speaker 1: Where like a like a heist movie, like, oh it's eleven. 339 00:16:22,276 --> 00:16:24,436 Speaker 3: Yeah, it was like the best people of my entire 340 00:16:24,476 --> 00:16:25,236 Speaker 3: career I worked with. 341 00:16:25,356 --> 00:16:26,996 Speaker 2: You don't need a lot, you just need every person 342 00:16:26,996 --> 00:16:29,196 Speaker 2: to be exceptional, and like, if we do our jobs right, 343 00:16:29,236 --> 00:16:30,516 Speaker 2: we touched the long arch of history. 344 00:16:30,676 --> 00:16:35,316 Speaker 1: Yeah, so what have you figured out? Like, what have 345 00:16:35,356 --> 00:16:38,156 Speaker 1: been the key things you've figured out? Since then? 346 00:16:38,436 --> 00:16:42,876 Speaker 2: We identified a couple extra people we brought in, including 347 00:16:42,996 --> 00:16:47,556 Speaker 2: Jerry's Sadoff. He's this guy who has more vaccines approved 348 00:16:47,596 --> 00:16:51,716 Speaker 2: than anyone alive. So things like guarda cel MMRV that 349 00:16:51,796 --> 00:16:55,316 Speaker 2: all children take. You have the coronavirus vaccine from J 350 00:16:55,476 --> 00:16:57,756 Speaker 2: and J the one shot, and you know, I think 351 00:16:57,756 --> 00:17:00,476 Speaker 2: fourteen vaccines have been approved under his watch. It wasn't 352 00:17:00,516 --> 00:17:03,236 Speaker 2: just that he had done a huge amount of like 353 00:17:03,276 --> 00:17:05,676 Speaker 2: the modern vaccines that define the modern health era. It's 354 00:17:05,716 --> 00:17:07,956 Speaker 2: that his hit rate was unusually high, Like it wasn't 355 00:17:07,956 --> 00:17:10,076 Speaker 2: like he worked on one hundred get to those fourteen 356 00:17:10,156 --> 00:17:12,636 Speaker 2: he had, Like his ratio of success. 357 00:17:12,276 --> 00:17:13,796 Speaker 3: Was unusually high. 358 00:17:13,956 --> 00:17:15,556 Speaker 2: And that told me I wanted to work with them, 359 00:17:15,596 --> 00:17:17,676 Speaker 2: And so I called them up and went out to 360 00:17:17,676 --> 00:17:19,356 Speaker 2: have dinner with them, and I was like, Jerry, you 361 00:17:19,396 --> 00:17:21,596 Speaker 2: told me this universal vaccine technology is the only thing 362 00:17:21,636 --> 00:17:23,676 Speaker 2: you thought was worth a damn like, come join me 363 00:17:23,716 --> 00:17:25,276 Speaker 2: and like, let's kick a hole in the universe. And 364 00:17:25,316 --> 00:17:28,076 Speaker 2: so he came. And the reason I'm telling you this 365 00:17:28,156 --> 00:17:30,636 Speaker 2: is that he didn't just come in with phenomenal clinical plans, 366 00:17:30,676 --> 00:17:33,756 Speaker 2: which he did. He also came in with some strategies 367 00:17:33,796 --> 00:17:35,196 Speaker 2: where he's like, one of the things I've noticed for 368 00:17:35,236 --> 00:17:38,636 Speaker 2: both the coronavirus vaccines and the RSV vaccines was that 369 00:17:39,116 --> 00:17:42,116 Speaker 2: the folks who added in little mutations to keep those 370 00:17:42,116 --> 00:17:45,596 Speaker 2: spikes stable, those vaccines were successful, and the folks who 371 00:17:45,596 --> 00:17:49,156 Speaker 2: didn't add in good stabilizing mutations their vaccines were unsuccessful. 372 00:17:49,236 --> 00:17:49,796 Speaker 1: Huh. 373 00:17:49,836 --> 00:17:51,756 Speaker 2: And he said, I think that that's just a critical thing. 374 00:17:51,796 --> 00:17:55,156 Speaker 2: You want to trap these spikes in their stable forms 375 00:17:55,156 --> 00:17:57,276 Speaker 2: so the immune system can target what the spike looks 376 00:17:57,316 --> 00:17:59,596 Speaker 2: like before it a tax a cellar before it falls 377 00:17:59,596 --> 00:18:01,156 Speaker 2: apart to confuse the immune staff. 378 00:18:01,276 --> 00:18:04,116 Speaker 1: So, just to be clear, like the spike proteins, it's 379 00:18:04,156 --> 00:18:07,916 Speaker 1: the hema glutenants that are in nature on the outside 380 00:18:07,956 --> 00:18:11,716 Speaker 1: of the of the of the flu virus. They have 381 00:18:11,756 --> 00:18:14,396 Speaker 1: a three dimensional shape, right, Yeah, they can change three 382 00:18:14,396 --> 00:18:17,356 Speaker 1: dimensional shape, and that actually turns out to be important 383 00:18:17,396 --> 00:18:20,316 Speaker 1: for sort of simple mechanical like a key fitting into 384 00:18:20,356 --> 00:18:23,476 Speaker 1: a lock. Reason right, and it's and they don't if 385 00:18:23,516 --> 00:18:26,116 Speaker 1: you rip them off the virus as you are when 386 00:18:26,156 --> 00:18:28,756 Speaker 1: you're presenting them in this vaccine necessarily stay in the 387 00:18:28,796 --> 00:18:30,676 Speaker 1: shape you want them to stay in. That's a o. 388 00:18:31,036 --> 00:18:33,276 Speaker 2: They're kind of like a little three prong grappling hook 389 00:18:33,316 --> 00:18:35,636 Speaker 2: and they change shape in order to like hook into 390 00:18:35,636 --> 00:18:38,236 Speaker 2: the cell membrane and then tear it open. And they're 391 00:18:38,276 --> 00:18:40,156 Speaker 2: designed kind of like with hinges because they need to 392 00:18:40,156 --> 00:18:42,036 Speaker 2: be able to be mobile and make changes. And so 393 00:18:42,076 --> 00:18:44,996 Speaker 2: this protein is not inherently stable, but what you want 394 00:18:45,156 --> 00:18:47,036 Speaker 2: is you want the thing very stable because you want 395 00:18:47,076 --> 00:18:50,356 Speaker 2: the immune system to train on defeating the trimer when 396 00:18:50,356 --> 00:18:53,356 Speaker 2: it's in it's sort of cocked and loaded, but prior 397 00:18:53,396 --> 00:18:58,196 Speaker 2: to shoot position. And we've seen with RSV and coronavirus 398 00:18:58,196 --> 00:19:00,756 Speaker 2: that that was absolutely essential for the successful vaccines. 399 00:19:01,076 --> 00:19:03,156 Speaker 3: And so anyway, Jerry came in was like, we should 400 00:19:03,196 --> 00:19:03,756 Speaker 3: do this with flu. 401 00:19:03,956 --> 00:19:06,836 Speaker 2: I had a bunch of experience stabilizing proteins from work 402 00:19:06,876 --> 00:19:10,996 Speaker 2: we did stabilizing antibodies Advisor and then also at my company, 403 00:19:11,356 --> 00:19:14,676 Speaker 2: a distributed bio and so we ran a quick campaign 404 00:19:14,716 --> 00:19:17,556 Speaker 2: and we identified these great stabilizing mutations and they had 405 00:19:17,556 --> 00:19:20,116 Speaker 2: like a pretty stunning effect on the quality of the 406 00:19:20,156 --> 00:19:20,956 Speaker 2: immune response. 407 00:19:21,476 --> 00:19:25,916 Speaker 1: So you're doing this basically atomic level engineering of the proteins, right, 408 00:19:25,996 --> 00:19:27,556 Speaker 1: yeah's the thing. Go on? What else? 409 00:19:27,956 --> 00:19:28,796 Speaker 3: And then the other thing. 410 00:19:28,836 --> 00:19:31,516 Speaker 2: The major thing we've done is we started the manufacturing, 411 00:19:31,636 --> 00:19:34,076 Speaker 2: we advanced the program not just for flu, but we're 412 00:19:34,116 --> 00:19:38,836 Speaker 2: also we have data validating the universal coronavirus vaccine, We're 413 00:19:38,876 --> 00:19:43,276 Speaker 2: testing on HIV, we're testing on a malaria and a 414 00:19:43,356 --> 00:19:44,956 Speaker 2: number of other pathogens right now to. 415 00:19:44,956 --> 00:19:47,156 Speaker 3: Be able to create a portfolio. So those have been 416 00:19:47,196 --> 00:19:49,316 Speaker 3: some of the major activities in the last couple of years. 417 00:19:50,196 --> 00:19:52,716 Speaker 1: When are you doing human clinical trials? 418 00:19:53,076 --> 00:19:55,756 Speaker 2: Yeah, so we've got about nine months left of manufacturing 419 00:19:56,316 --> 00:19:58,996 Speaker 2: or eight months of manufacturing, and then you spend a 420 00:19:59,036 --> 00:20:02,076 Speaker 2: month getting permission from the FDA to start your study 421 00:20:03,116 --> 00:20:04,476 Speaker 2: and then we'd start human trials. 422 00:20:04,676 --> 00:20:07,516 Speaker 1: So okay, so next year you're starting human trials. Next year. 423 00:20:07,836 --> 00:20:09,876 Speaker 1: So when you think about the future, the future of 424 00:20:09,876 --> 00:20:12,836 Speaker 1: the company, of your work, like, what are you worried about? 425 00:20:13,156 --> 00:20:16,396 Speaker 2: So I worry about less and less things, and then 426 00:20:16,436 --> 00:20:19,156 Speaker 2: the things I worry about evolve. So in terms of 427 00:20:19,316 --> 00:20:21,036 Speaker 2: is it going to be safe. I worry about that 428 00:20:21,196 --> 00:20:28,156 Speaker 2: extremely little. We have been vaccinated with influenza HA protein 429 00:20:28,236 --> 00:20:31,316 Speaker 2: since the nineteen forties. It's actually the best validated, diverse 430 00:20:31,356 --> 00:20:34,196 Speaker 2: class of versions of HA compared to any other vaccine 431 00:20:34,196 --> 00:20:34,916 Speaker 2: that's been tested. 432 00:20:34,956 --> 00:20:37,396 Speaker 3: And it's that's all. The history of safety has been 433 00:20:37,396 --> 00:20:39,636 Speaker 3: extremely good. We're using the. 434 00:20:41,076 --> 00:20:44,196 Speaker 2: Advisor Biointech mRNA chemistry, so you can get a non 435 00:20:44,196 --> 00:20:45,356 Speaker 2: exclusive license to it. 436 00:20:45,596 --> 00:20:47,956 Speaker 1: That's the same one they used for the COVID vaccine. 437 00:20:48,116 --> 00:20:50,436 Speaker 2: Yeah, it's been in billions of people, so we know 438 00:20:50,476 --> 00:20:53,836 Speaker 2: what the safety profile is. So safety I'm not concerned 439 00:20:53,876 --> 00:20:56,316 Speaker 2: about in terms of efficacy, like how well it works. 440 00:20:57,196 --> 00:20:59,996 Speaker 2: I basically don't believe in any one animal's immune system 441 00:21:00,036 --> 00:21:02,756 Speaker 2: because you could always overfit the immune system, could overfit 442 00:21:02,836 --> 00:21:06,116 Speaker 2: in a certain bizarre and unpredictable way. And so we've 443 00:21:06,156 --> 00:21:11,156 Speaker 2: tested this in pigs, but also ferrets, also rats, also mice, 444 00:21:11,716 --> 00:21:15,316 Speaker 2: also cows, and also human immune organoids, which is organ 445 00:21:15,356 --> 00:21:17,796 Speaker 2: donors offer their lymph nodes. They're smashed up and you 446 00:21:17,836 --> 00:21:19,916 Speaker 2: basically create a bunch of little mini lymph nodes from 447 00:21:19,916 --> 00:21:22,436 Speaker 2: a donor and you can vaccinate them under different conditions 448 00:21:22,476 --> 00:21:25,476 Speaker 2: to see how someone with a lifetime of immune memory, 449 00:21:25,476 --> 00:21:29,676 Speaker 2: including deflu and vaccines, would respond to our vaccine or 450 00:21:29,676 --> 00:21:32,796 Speaker 2: a control vaccine. And when we did that as well 451 00:21:32,836 --> 00:21:36,076 Speaker 2: as all the other animals, we consistently saw this universality effect. 452 00:21:36,796 --> 00:21:39,436 Speaker 2: And so going into the human trials, I think we're 453 00:21:39,476 --> 00:21:42,876 Speaker 2: pretty bullish that the effect is going to be dramatically 454 00:21:42,916 --> 00:21:46,556 Speaker 2: better than the current vaccine. So I think we're going 455 00:21:46,596 --> 00:21:50,076 Speaker 2: in assuming that the human trials probably will perform well. 456 00:21:50,076 --> 00:21:52,236 Speaker 3: But I honestly I won't sleep well at night until 457 00:21:52,276 --> 00:21:54,556 Speaker 3: I get that data and I'm like, Okay, yeah, we're 458 00:21:54,596 --> 00:21:55,396 Speaker 3: on solid footing. 459 00:21:55,716 --> 00:21:58,316 Speaker 2: We've done everything I can to de risk it with 460 00:21:58,396 --> 00:22:02,036 Speaker 2: these other organisms and even human immune organoids, and now 461 00:22:02,036 --> 00:22:03,476 Speaker 2: it's time to run it in humans. 462 00:22:05,156 --> 00:22:07,356 Speaker 3: Fundraising is always a headache where we've got. 463 00:22:07,196 --> 00:22:09,916 Speaker 2: Now at least multiple groups gathering around with sheet options 464 00:22:09,956 --> 00:22:12,796 Speaker 2: and we're looking at them. But it's it's been, just 465 00:22:12,796 --> 00:22:15,236 Speaker 2: to put it lightly, a difficult period for biotech fundraising, 466 00:22:15,276 --> 00:22:17,196 Speaker 2: and we've managed to survive where a number of other 467 00:22:17,236 --> 00:22:20,756 Speaker 2: companies have not. But you know, I've probably gained some 468 00:22:20,796 --> 00:22:23,276 Speaker 2: gray hair and probably you know, took away some of 469 00:22:23,276 --> 00:22:26,916 Speaker 2: my health span as a consequence of surviving this period. 470 00:22:27,796 --> 00:22:29,476 Speaker 1: I mean does that last thing mean you're afraid of 471 00:22:29,516 --> 00:22:31,516 Speaker 1: running out of money? That's what I mean. 472 00:22:31,516 --> 00:22:34,036 Speaker 3: Every company worries about that. That's the nature of adventure. 473 00:22:34,156 --> 00:22:36,236 Speaker 2: We've managed to pull it together and we just got 474 00:22:36,276 --> 00:22:39,996 Speaker 2: this grant which covers us. But the fear is that 475 00:22:40,036 --> 00:22:42,876 Speaker 2: we're stuck, that we need to go continue raising money 476 00:22:42,916 --> 00:22:44,316 Speaker 2: so that we can go pay for the rest of 477 00:22:44,356 --> 00:22:47,956 Speaker 2: manufacturing and pay for clinical and and armed for the 478 00:22:47,996 --> 00:22:50,636 Speaker 2: next parts. And to be blunt, this has been an 479 00:22:50,636 --> 00:22:53,676 Speaker 2: absolutely terrible period in biotech. So we got seventy five 480 00:22:53,676 --> 00:22:55,796 Speaker 2: percent off on all of our equipment for my entire 481 00:22:55,876 --> 00:22:57,916 Speaker 2: laboratory because we got it from auctions. A lot of 482 00:22:57,916 --> 00:23:00,836 Speaker 2: this stuff was in like new stuff in boxes where 483 00:23:00,836 --> 00:23:02,716 Speaker 2: a company just ran out of money and they're stuck. 484 00:23:02,796 --> 00:23:04,756 Speaker 3: And you know, I've benefited from it. 485 00:23:04,836 --> 00:23:07,996 Speaker 2: I've benefited from being able to hire remarkable people that 486 00:23:08,116 --> 00:23:11,156 Speaker 2: otherwise we're struck to find an opportunity because of it's 487 00:23:11,196 --> 00:23:13,596 Speaker 2: we've basically lived in this like a little bit of 488 00:23:13,596 --> 00:23:15,716 Speaker 2: a biotech hangover after I think there was too much 489 00:23:15,756 --> 00:23:18,596 Speaker 2: investment and sometimes in some pretty goofy stuff during the 490 00:23:18,636 --> 00:23:20,756 Speaker 2: pandemic for biotech, and I think we're in this like 491 00:23:20,756 --> 00:23:22,196 Speaker 2: a little bit of a headache, a little bit of 492 00:23:22,276 --> 00:23:26,236 Speaker 2: a macro economic global uncertainty area, and those things are 493 00:23:26,276 --> 00:23:28,556 Speaker 2: both slammed up against biotech in an unproductive way. 494 00:23:28,636 --> 00:23:35,316 Speaker 1: Yeah, it's okay. What's the happy version of the story. 495 00:23:36,316 --> 00:23:39,516 Speaker 2: The happy version is that our vaccine works the same 496 00:23:39,516 --> 00:23:42,036 Speaker 2: as it has in all those animals and organoids that 497 00:23:42,076 --> 00:23:46,316 Speaker 2: we've seen. We bring it forward universal vaccine just becomes 498 00:23:46,476 --> 00:23:49,676 Speaker 2: the vaccine because that's suddenly a vaccine that you take 499 00:23:49,716 --> 00:23:52,516 Speaker 2: and you don't get sick. The first thing it does 500 00:23:52,636 --> 00:23:55,876 Speaker 2: is it creates a massive improvement in global health. And 501 00:23:55,876 --> 00:24:00,156 Speaker 2: then the major impact of you know, flu kills people, right, It. 502 00:24:00,116 --> 00:24:01,996 Speaker 3: Gets a lot of people sick. People lose a lot. 503 00:24:01,836 --> 00:24:04,796 Speaker 2: Of time from school, pregnant women in their second trimester 504 00:24:04,996 --> 00:24:07,076 Speaker 2: to get flu, or seven times more likely to have 505 00:24:07,116 --> 00:24:09,956 Speaker 2: a child with schizophrenia and they're adult. 506 00:24:10,036 --> 00:24:13,516 Speaker 3: Like. There's a bunch of like squali and consequences. 507 00:24:13,476 --> 00:24:15,876 Speaker 2: But the biggest effect is that when this gets out there, 508 00:24:15,956 --> 00:24:17,636 Speaker 2: the pandemic era is over. 509 00:24:19,116 --> 00:24:21,436 Speaker 1: And when you say pandemic you mean flu pandemic. 510 00:24:21,716 --> 00:24:24,276 Speaker 3: Yeah, the flue pandemics are over, which is our most 511 00:24:24,316 --> 00:24:26,756 Speaker 3: common source of pandemics. We had five in the last 512 00:24:26,876 --> 00:24:30,756 Speaker 3: hundred years. We had two or three per century before then, 513 00:24:30,756 --> 00:24:33,236 Speaker 3: so they got faster. We have a lot more people. 514 00:24:33,636 --> 00:24:36,516 Speaker 2: We have these pig megafarms, like we need to fix this. 515 00:24:37,156 --> 00:24:39,756 Speaker 2: And with this vaccine, you no longer have a pandemic 516 00:24:39,836 --> 00:24:42,716 Speaker 2: era because you have a decent proportion of the population 517 00:24:42,796 --> 00:24:45,796 Speaker 2: that's already immune to the new virus strains before they hit. 518 00:24:46,276 --> 00:24:48,636 Speaker 2: And that's what the new world looks like. And so 519 00:24:48,716 --> 00:24:51,356 Speaker 2: that's the happy version for flu. But our intention is 520 00:24:51,396 --> 00:24:53,836 Speaker 2: to do that for every pandemic pathogen, to just one 521 00:24:53,876 --> 00:24:56,276 Speaker 2: by one go and in the pandemic era, to come 522 00:24:56,356 --> 00:24:59,836 Speaker 2: up with countermeasures that first protect the world from pandemics 523 00:24:59,876 --> 00:25:04,436 Speaker 2: the medical, personal, and economic costs. Second protect the world 524 00:25:04,436 --> 00:25:06,876 Speaker 2: from just major outbreaks. And then ultimately I want to 525 00:25:07,236 --> 00:25:09,756 Speaker 2: have these same tools can arm future decade to attempt 526 00:25:10,036 --> 00:25:12,276 Speaker 2: eradication campaigns that previously. 527 00:25:11,876 --> 00:25:14,876 Speaker 3: Were not possible. And that's the future we want to build. 528 00:25:17,836 --> 00:25:31,636 Speaker 1: We'll be back in just a minute. Let's talk about 529 00:25:31,636 --> 00:25:32,236 Speaker 1: snake bites. 530 00:25:32,996 --> 00:25:33,956 Speaker 3: All right, let's do it. 531 00:25:35,236 --> 00:25:37,036 Speaker 1: How'd you get into the snake bite business? 532 00:25:37,716 --> 00:25:43,716 Speaker 2: Yeah, so it was twenty seventeen, and I think it 533 00:25:43,796 --> 00:25:48,196 Speaker 2: was because the World Health Organization was announcing, you know, 534 00:25:48,236 --> 00:25:51,836 Speaker 2: the neglected tropical disease nature of snake bite, kind of 535 00:25:52,036 --> 00:25:53,996 Speaker 2: declaring it a neglected tropical. 536 00:25:53,636 --> 00:25:58,076 Speaker 1: Disease, basically saying, hundreds of thousands of people are killed 537 00:25:58,236 --> 00:26:01,036 Speaker 1: or very badly wounded every year by snake bites. It's 538 00:26:01,076 --> 00:26:04,276 Speaker 1: not just some weird thing, and not enough. 539 00:26:04,156 --> 00:26:07,356 Speaker 2: People are trying to develop countermeasures. 540 00:26:07,396 --> 00:26:09,076 Speaker 1: And I think what had happened because most of the 541 00:26:09,276 --> 00:26:11,636 Speaker 1: people who are who die or are severely injured are 542 00:26:11,636 --> 00:26:12,236 Speaker 1: super poor. 543 00:26:12,676 --> 00:26:14,676 Speaker 3: Yeah, yeah, that's. 544 00:26:16,276 --> 00:26:19,156 Speaker 2: It reminds me of a Mandy python where they have 545 00:26:19,196 --> 00:26:21,116 Speaker 2: the Roman Senate and someone goes. 546 00:26:21,076 --> 00:26:22,156 Speaker 1: What do we do about the poor? 547 00:26:22,236 --> 00:26:23,836 Speaker 3: And then all in unison they put up their hands. 548 00:26:23,876 --> 00:26:25,876 Speaker 3: They're like, fuck the poor, all right, next. 549 00:26:27,116 --> 00:26:29,796 Speaker 1: That's a neglected tropical disease story. 550 00:26:29,676 --> 00:26:32,556 Speaker 3: And the fundamental problem. Yeah. 551 00:26:32,676 --> 00:26:36,116 Speaker 2: I think also that I'm to be fair, I don't 552 00:26:36,116 --> 00:26:38,156 Speaker 2: know to be fair, but like the companies that make 553 00:26:38,196 --> 00:26:39,796 Speaker 2: anti venom, most of them are kind of doing it 554 00:26:39,836 --> 00:26:42,476 Speaker 2: as a public service, as a loss, because most of 555 00:26:42,516 --> 00:26:44,516 Speaker 2: the people who need anti venom, of the millions of 556 00:26:44,556 --> 00:26:48,276 Speaker 2: bytes per year, they're poor. They're subsistence agriculturists and their 557 00:26:48,316 --> 00:26:52,676 Speaker 2: children and people who live in rural environments. And if 558 00:26:52,716 --> 00:26:54,596 Speaker 2: you take that market, which is probably like five to 559 00:26:54,636 --> 00:26:57,596 Speaker 2: six hundred million total per year, but it's fractured across 560 00:26:57,636 --> 00:27:01,716 Speaker 2: thirty to forty products. Each of those things is pretty unattractive. 561 00:27:01,436 --> 00:27:04,156 Speaker 1: Just to be clear, because you need different anti venom 562 00:27:04,596 --> 00:27:07,076 Speaker 1: for different snakes different Yeah, there currently is. 563 00:27:07,036 --> 00:27:08,876 Speaker 3: No universal anti venom on the market. 564 00:27:09,156 --> 00:27:11,756 Speaker 2: So people had started ending programs to make certain types 565 00:27:11,796 --> 00:27:13,356 Speaker 2: of anti venoms, and I think that was happening in 566 00:27:13,356 --> 00:27:16,236 Speaker 2: twenty sixteen. So then in twenty seventeen the World Health 567 00:27:16,356 --> 00:27:20,036 Speaker 2: Organization brings some attention to this, and then I started. 568 00:27:19,716 --> 00:27:20,356 Speaker 3: Thinking about it. 569 00:27:20,436 --> 00:27:23,676 Speaker 2: I you know, in my village we had snake bites sometimes, 570 00:27:23,676 --> 00:27:26,516 Speaker 2: and I just like, I like topical diseases, particularly if 571 00:27:26,516 --> 00:27:30,356 Speaker 2: they interface with cool bioengineering. And I'd been working on 572 00:27:30,396 --> 00:27:33,316 Speaker 2: the universal vaccine work, and so I started wondering, I'm like, 573 00:27:33,356 --> 00:27:36,356 Speaker 2: you know what, I wonder if that same idea of 574 00:27:36,396 --> 00:27:40,316 Speaker 2: the conserved Achilles heel that's found across all flu or 575 00:27:40,356 --> 00:27:40,916 Speaker 2: all HIV. 576 00:27:41,116 --> 00:27:43,436 Speaker 3: I wonder if snake venom. 577 00:27:43,196 --> 00:27:46,436 Speaker 2: Toxins have that, Because if that's true, maybe you don't 578 00:27:46,476 --> 00:27:49,036 Speaker 2: need to make six hundred and fifty different anti venoms. 579 00:27:49,356 --> 00:27:52,476 Speaker 2: Maybe it's actually that you only make one cocktail of 580 00:27:52,476 --> 00:27:55,716 Speaker 2: broadly neutralizing antibodies and it could work against all snakes. 581 00:27:55,356 --> 00:27:58,876 Speaker 3: A universal anti venom. And so I did a little 582 00:27:58,916 --> 00:28:02,036 Speaker 3: you know, playing around on my computer, and sure enough, 583 00:28:02,076 --> 00:28:05,436 Speaker 3: there's basically like ten major toxins that all snakes use. 584 00:28:05,676 --> 00:28:06,516 Speaker 3: Nature's lazy. 585 00:28:07,276 --> 00:28:09,116 Speaker 2: And then when I pulled up a bunch of sequel 586 00:28:09,356 --> 00:28:11,516 Speaker 2: is from a bunch of different snakes and I compared 587 00:28:11,556 --> 00:28:14,716 Speaker 2: where they buried, where they mutated relative to each other 588 00:28:14,916 --> 00:28:18,036 Speaker 2: versus not again, I found a little conserved spot and 589 00:28:18,116 --> 00:28:21,076 Speaker 2: it's it's the business end, right, because these toxins can mutate, 590 00:28:21,076 --> 00:28:22,756 Speaker 2: except they can't mutate right where they need to go 591 00:28:22,796 --> 00:28:27,876 Speaker 2: bind your neurons, your nicotinic casido colon receptor to paralyze. 592 00:28:27,356 --> 00:28:28,156 Speaker 3: You and so forth. 593 00:28:29,036 --> 00:28:31,076 Speaker 2: And so at that point I got pretty stoked, where 594 00:28:31,076 --> 00:28:32,276 Speaker 2: I was like, I'm pretty sure this is and like 595 00:28:32,316 --> 00:28:34,556 Speaker 2: at the time, no one had been talking about broadly 596 00:28:34,596 --> 00:28:37,156 Speaker 2: neutralizing anybody's outside of viruses. 597 00:28:37,196 --> 00:28:38,476 Speaker 3: And I was like, this is so cool. 598 00:28:38,676 --> 00:28:39,916 Speaker 2: And so then I was like, all right, where do 599 00:28:39,956 --> 00:28:43,076 Speaker 2: I find a person who has been met a couple times? 600 00:28:43,156 --> 00:28:43,316 Speaker 3: Right? 601 00:28:43,316 --> 00:28:45,716 Speaker 2: And I was like looking for a clumsy snake researcher, 602 00:28:45,796 --> 00:28:49,236 Speaker 2: Like there's like a site in Costa Rica. There's a 603 00:28:49,236 --> 00:28:51,876 Speaker 2: place in Arizona. There's some places in India where I 604 00:28:51,916 --> 00:28:54,116 Speaker 2: was reaching out and like I was kind of coming 605 00:28:54,196 --> 00:28:56,596 Speaker 2: up empty, and then I don't know how, somehow, like 606 00:28:56,676 --> 00:29:00,476 Speaker 2: I desperately just started like Google searching, and I found 607 00:29:00,476 --> 00:29:03,636 Speaker 2: these insane articles about this guy named Tim Freedy who 608 00:29:03,676 --> 00:29:07,356 Speaker 2: had spent like at the time, over seventeen years self 609 00:29:07,396 --> 00:29:12,076 Speaker 2: immunizing hundreds of times with sixteen different species of snake. 610 00:29:12,516 --> 00:29:14,756 Speaker 2: What he did is he milked the snakes, he weighed 611 00:29:14,756 --> 00:29:17,996 Speaker 2: out microgram initial doses and administered it, and then he 612 00:29:18,676 --> 00:29:21,156 Speaker 2: escalated over a period of months up until the point 613 00:29:21,156 --> 00:29:23,116 Speaker 2: that he took milligrams. And it was only after he 614 00:29:23,156 --> 00:29:25,036 Speaker 2: built up that immunity. Then he would then have the 615 00:29:25,676 --> 00:29:26,716 Speaker 2: animals challenge. 616 00:29:26,516 --> 00:29:29,476 Speaker 3: Him because no one lives people. You can't live from 617 00:29:29,516 --> 00:29:31,156 Speaker 3: a mamba bid it. He'll kill you. Yet he is 618 00:29:31,236 --> 00:29:33,116 Speaker 3: able to take it. You see that video. 619 00:29:33,156 --> 00:29:34,996 Speaker 2: What you don't see is he spent about nine months 620 00:29:34,996 --> 00:29:38,716 Speaker 2: building up immunity against it by starting with microgram trace doses. 621 00:29:39,156 --> 00:29:43,956 Speaker 1: That's crazy. So you're like, that guy is walking universal 622 00:29:44,036 --> 00:29:44,636 Speaker 1: anti venom. 623 00:29:44,716 --> 00:29:45,836 Speaker 3: Yeah, if anybody has. 624 00:29:45,676 --> 00:29:48,396 Speaker 2: The secrets of universal anti venom, it's pumping through this 625 00:29:48,436 --> 00:29:49,956 Speaker 2: guy's veins right now and so I was like, I 626 00:29:49,996 --> 00:29:53,636 Speaker 2: have to meet him. I couldn't find his contact information 627 00:29:53,676 --> 00:29:56,596 Speaker 2: anywhere online, and so I contacted the reporters and one 628 00:29:56,596 --> 00:29:57,156 Speaker 2: of them put me. 629 00:29:57,076 --> 00:29:58,396 Speaker 3: In touch with them and had his number. 630 00:29:59,116 --> 00:30:00,516 Speaker 2: And so I had this call and I told I 631 00:30:00,556 --> 00:30:02,996 Speaker 2: remember it super clearly, and where I was just like, look, 632 00:30:03,396 --> 00:30:05,676 Speaker 2: I know this may be awkward, but I would love 633 00:30:05,716 --> 00:30:07,476 Speaker 2: to get my hands on some of your blood. 634 00:30:08,196 --> 00:30:10,756 Speaker 3: And his response was I've been waiting for this call 635 00:30:10,796 --> 00:30:11,516 Speaker 3: for a long time. 636 00:30:13,516 --> 00:30:16,116 Speaker 1: And and so what happened, and. 637 00:30:16,036 --> 00:30:18,476 Speaker 2: Then what I do is we just scheduled twenty eight 638 00:30:18,516 --> 00:30:20,676 Speaker 2: days apart two blood draws and each one was for 639 00:30:20,676 --> 00:30:22,876 Speaker 2: twenty mili liters, so that there was no risk as 640 00:30:22,916 --> 00:30:25,316 Speaker 2: to the blood dramaut This is like a couple of tubes. 641 00:30:26,916 --> 00:30:28,836 Speaker 2: And so then that that got sent over to my lab. 642 00:30:29,156 --> 00:30:32,876 Speaker 2: I then processed it in my and I separated out 643 00:30:32,876 --> 00:30:35,796 Speaker 2: the serum and the cells, and from the serum, I 644 00:30:35,796 --> 00:30:37,636 Speaker 2: wanted to check his work. I think, you know a story, 645 00:30:37,956 --> 00:30:40,036 Speaker 2: you know, seemed credible and stuff what I wanted to confirm. 646 00:30:40,076 --> 00:30:42,076 Speaker 2: And so I had ordered a series of snake venoms. 647 00:30:41,796 --> 00:30:44,756 Speaker 3: Which, by the way, it is suspiciously easy to order. 648 00:30:44,796 --> 00:30:48,916 Speaker 2: The bit of mistakes, I have learned during this project. 649 00:30:49,796 --> 00:30:51,636 Speaker 2: I was like, this should not be this easy anyway. 650 00:30:51,676 --> 00:30:53,756 Speaker 2: So I had a bunch of panel of snakes, some 651 00:30:53,876 --> 00:30:56,276 Speaker 2: that he said he'd immunized against, and I also picked 652 00:30:56,316 --> 00:30:57,196 Speaker 2: ones that he never had. 653 00:30:57,276 --> 00:30:59,956 Speaker 1: Oh interesting, this is testing the universality. 654 00:31:00,116 --> 00:31:01,916 Speaker 2: Yeah, yeah, And so I tested his sierra and I 655 00:31:01,916 --> 00:31:04,196 Speaker 2: also tested mine and a couple other control serra on 656 00:31:04,236 --> 00:31:07,516 Speaker 2: this on the venoms. Now, the control people like me 657 00:31:07,756 --> 00:31:10,316 Speaker 2: who have never been bit, we had no response to 658 00:31:10,316 --> 00:31:13,516 Speaker 2: this serum. He had blazingly high responses to all the venoms, 659 00:31:13,516 --> 00:31:15,836 Speaker 2: including the ones he had never been exposed to, including 660 00:31:15,836 --> 00:31:17,556 Speaker 2: new genera like very different snakes. 661 00:31:18,316 --> 00:31:20,356 Speaker 1: So, based on this, right, you come up with this 662 00:31:20,916 --> 00:31:25,596 Speaker 1: anti venom cocktail that seems like it could work against 663 00:31:25,956 --> 00:31:28,356 Speaker 1: not all venomous snakes, but a lot a lot of 664 00:31:28,396 --> 00:31:32,356 Speaker 1: different kinds of venomous snakes. You publish a paper about 665 00:31:32,356 --> 00:31:34,716 Speaker 1: this in the journal Cell. Where does it go from here? 666 00:31:34,756 --> 00:31:35,556 Speaker 1: What happens next? 667 00:31:36,116 --> 00:31:38,156 Speaker 2: We've reached out to the Welcome Trust and so some 668 00:31:38,196 --> 00:31:40,396 Speaker 2: other groups that might be interested in this. We've also 669 00:31:40,476 --> 00:31:43,156 Speaker 2: reached out to I guess I won't say their names, 670 00:31:43,156 --> 00:31:46,356 Speaker 2: but there are some pharmaceutical companies that develop anti venom 671 00:31:46,396 --> 00:31:47,876 Speaker 2: to try to see if this is something they'd be 672 00:31:47,916 --> 00:31:50,076 Speaker 2: interested in doing a partnership on to pick up. I 673 00:31:50,076 --> 00:31:53,276 Speaker 2: think my feeling is that I would ideally like to 674 00:31:53,276 --> 00:31:57,196 Speaker 2: have a pharmaceutical partner to go develop this with or 675 00:31:57,276 --> 00:32:01,396 Speaker 2: a massive support from some foundation, because otherwise it's you 676 00:32:01,436 --> 00:32:03,876 Speaker 2: can make it profitable, you can unfracture that market, and 677 00:32:03,916 --> 00:32:06,556 Speaker 2: you could be manufacturing this and serve maybe a five 678 00:32:06,636 --> 00:32:07,436 Speaker 2: hundred million. 679 00:32:07,196 --> 00:32:10,076 Speaker 3: Dollars per year market. 680 00:32:10,316 --> 00:32:13,356 Speaker 2: But to get there you have to go spend at 681 00:32:13,436 --> 00:32:15,716 Speaker 2: least ten and probably more like twenty million dollars on 682 00:32:15,956 --> 00:32:18,796 Speaker 2: GMP and some other early activities, and then twenty five 683 00:32:18,796 --> 00:32:21,316 Speaker 2: million for clinical and I think it's hard to imagine 684 00:32:21,316 --> 00:32:22,876 Speaker 2: who's going to put that money up front for what 685 00:32:22,956 --> 00:32:26,396 Speaker 2: is a relatively small profit, which is the whole frustrating 686 00:32:26,436 --> 00:32:28,756 Speaker 2: aspect of neglected tropical diseases, and. 687 00:32:28,676 --> 00:32:34,116 Speaker 1: That's why they're neglected. Yeah, we'll be back in a 688 00:32:34,116 --> 00:32:48,076 Speaker 1: minute with the lightning round. Okay, last thing is the 689 00:32:48,156 --> 00:32:54,556 Speaker 1: lightning round. So, as I understand that you dropped out 690 00:32:54,556 --> 00:32:58,356 Speaker 1: of school to run your family in hotel restaurant when 691 00:32:58,396 --> 00:33:00,276 Speaker 1: you were in high school, or you took a year 692 00:33:00,316 --> 00:33:05,236 Speaker 1: off high school, what's one thing you learned from that. Yeah. 693 00:33:05,436 --> 00:33:07,676 Speaker 2: I think one thing I learned is that people on 694 00:33:07,876 --> 00:33:12,596 Speaker 2: teams don't that people do not crave chaos. I think 695 00:33:12,636 --> 00:33:14,636 Speaker 2: people want to know what the people are calmed down 696 00:33:14,676 --> 00:33:16,676 Speaker 2: by knowing that they're rules, even if the rules don't 697 00:33:16,716 --> 00:33:20,156 Speaker 2: benefit them. And I dropped out to go run the restaurant, 698 00:33:20,196 --> 00:33:23,116 Speaker 2: and I was like fifteen year old kid, and you know, 699 00:33:23,116 --> 00:33:24,836 Speaker 2: initially people didn't really listen to me. 700 00:33:25,036 --> 00:33:26,516 Speaker 3: You know, it was just like a crazy time. 701 00:33:27,036 --> 00:33:29,156 Speaker 2: And that was crazy for the employees because the employees 702 00:33:29,156 --> 00:33:31,476 Speaker 2: are like, I don't know, like your son's here, but maybe, 703 00:33:32,556 --> 00:33:35,516 Speaker 2: you know, maybe David's going to die and my dad's 704 00:33:35,556 --> 00:33:35,996 Speaker 2: going to die. 705 00:33:36,036 --> 00:33:37,716 Speaker 3: And then my mom was like, let's just shut it down. 706 00:33:37,716 --> 00:33:38,876 Speaker 3: I can't deal with that. I'm like, Mom, we need 707 00:33:38,876 --> 00:33:40,196 Speaker 3: the money to be able to go pay for the bill, 708 00:33:40,316 --> 00:33:42,076 Speaker 3: the medical bills. You know. 709 00:33:42,156 --> 00:33:45,316 Speaker 2: So everyone was acting chaotic and it was like extremely 710 00:33:45,356 --> 00:33:47,556 Speaker 2: difficult to manage the team and try to keep people 711 00:33:47,636 --> 00:33:51,396 Speaker 2: focused to do their jobs. And you know, this thing 712 00:33:51,436 --> 00:33:56,196 Speaker 2: happened where one evening, one of our cooks was like 713 00:33:56,236 --> 00:33:58,516 Speaker 2: walking out and he had this big bag and I 714 00:33:58,596 --> 00:33:59,996 Speaker 2: went over and I was like, what the hell are 715 00:34:00,036 --> 00:34:01,356 Speaker 2: you doing? And I realized he was stealing a bunch 716 00:34:01,356 --> 00:34:03,156 Speaker 2: of steaks, like it was just stakes, but it was 717 00:34:03,196 --> 00:34:04,876 Speaker 2: with a bunch of the other chefs, and I was 718 00:34:04,916 --> 00:34:07,796 Speaker 2: just like, I didn't do it for a tactical reason. 719 00:34:07,836 --> 00:34:09,596 Speaker 2: I just did it because I was fed, and I'm like, 720 00:34:09,596 --> 00:34:11,396 Speaker 2: you're stealing from my dying father and I just the 721 00:34:11,436 --> 00:34:12,836 Speaker 2: last thing I need. So I was just like, give 722 00:34:12,836 --> 00:34:14,956 Speaker 2: it back, you're fired, go away, And they were shocked 723 00:34:14,996 --> 00:34:16,196 Speaker 2: and I was like, no, no, you're fired. You're not 724 00:34:16,236 --> 00:34:19,276 Speaker 2: allowed to come back in anymore. We'll send you your 725 00:34:19,716 --> 00:34:21,796 Speaker 2: severance basically in two weeks, get. 726 00:34:21,636 --> 00:34:22,276 Speaker 3: The hell out of here. 727 00:34:22,316 --> 00:34:25,316 Speaker 2: And like what I was not anticipating is the next 728 00:34:25,356 --> 00:34:27,356 Speaker 2: day everybody showed up for work and suddenly there was 729 00:34:27,356 --> 00:34:29,636 Speaker 2: actually everyone was calmer, And I think it was the 730 00:34:29,756 --> 00:34:32,876 Speaker 2: transition of perception of power that they were like, they want, 731 00:34:32,956 --> 00:34:34,996 Speaker 2: you know, I did something harsh, and yet suddenly everybody's 732 00:34:35,036 --> 00:34:37,236 Speaker 2: performance improved, partially because they're like, Okay, now I know, 733 00:34:37,476 --> 00:34:39,156 Speaker 2: like the hand that feeds, But it was also like 734 00:34:39,236 --> 00:34:41,676 Speaker 2: knowing that there was some rules and there was a plan. Yeah, 735 00:34:42,436 --> 00:34:44,676 Speaker 2: and I want to leave you with the thought that 736 00:34:44,716 --> 00:34:47,276 Speaker 2: wasn't like my lesson was like okay, be like the 737 00:34:47,276 --> 00:34:48,276 Speaker 2: Red Queen all the time. 738 00:34:48,316 --> 00:34:50,636 Speaker 3: That's not absolutely the way to go. That's not leadership. 739 00:34:50,756 --> 00:34:52,596 Speaker 2: But I think what I did learn is that when 740 00:34:52,596 --> 00:34:55,236 Speaker 2: times are difficult, people prefer to know that there's a 741 00:34:55,276 --> 00:34:58,356 Speaker 2: plan and it's organized and there's a solution, even if 742 00:34:58,436 --> 00:35:01,116 Speaker 2: it's rules that don't benefit them, rather than having opened 743 00:35:01,116 --> 00:35:03,436 Speaker 2: into chaos. And I think that was counterintuitive to me 744 00:35:03,636 --> 00:35:07,236 Speaker 2: because my personality is different actually thrive in chaos and 745 00:35:07,316 --> 00:35:11,556 Speaker 2: having those sorts of complicated choices and I resent confinement 746 00:35:12,036 --> 00:35:14,956 Speaker 2: of any form. But I think that that actually for 747 00:35:15,036 --> 00:35:18,556 Speaker 2: most organizations, that's empowering and important. And to articulate the 748 00:35:18,636 --> 00:35:20,796 Speaker 2: rules and people know there's a system that people are like, 749 00:35:20,796 --> 00:35:23,756 Speaker 2: I feel comfortable because now I understand and it can 750 00:35:24,476 --> 00:35:25,916 Speaker 2: work in a predictable environment. 751 00:35:25,916 --> 00:35:27,156 Speaker 3: And I think that part's important. 752 00:35:27,356 --> 00:35:29,796 Speaker 1: So that's something you learned running the restaurant that has 753 00:35:29,796 --> 00:35:32,396 Speaker 1: helped you as a CEO. I know you recently bought 754 00:35:32,436 --> 00:35:35,436 Speaker 1: the restaurant, so now you're a restaurant owner. Is there 755 00:35:35,436 --> 00:35:38,636 Speaker 1: something you've learned running a biotech company that now helps 756 00:35:38,636 --> 00:35:39,556 Speaker 1: you running a restaurant? 757 00:35:39,956 --> 00:35:42,876 Speaker 3: Oh so yeah, yeah. 758 00:35:42,276 --> 00:35:47,396 Speaker 2: Well externalizing responsibilities so I don't run the restaurant. I 759 00:35:47,476 --> 00:35:49,836 Speaker 2: bought the hotel and restore or the restaurant and some 760 00:35:49,876 --> 00:35:51,916 Speaker 2: of the properties, not the full hotel. Some other people 761 00:35:51,916 --> 00:35:55,596 Speaker 2: bought some of the bungalows. And then what I did 762 00:35:55,716 --> 00:35:59,556 Speaker 2: is I basically wanted to maintain the value of the 763 00:35:59,796 --> 00:36:01,916 Speaker 2: property and increase it and make sure that all the 764 00:36:01,956 --> 00:36:04,676 Speaker 2: people who some of us have worked for our family 765 00:36:04,716 --> 00:36:08,916 Speaker 2: since my childhood, that their jobs weren't compromised, which during 766 00:36:08,916 --> 00:36:09,876 Speaker 2: the pandemic. 767 00:36:09,636 --> 00:36:11,956 Speaker 3: Where tourism was like really bad, like there was a 768 00:36:12,036 --> 00:36:12,516 Speaker 3: risk of that. 769 00:36:12,636 --> 00:36:15,796 Speaker 2: And so I run it essentially as a it's a cooperative. 770 00:36:15,836 --> 00:36:18,116 Speaker 2: It's really like, I don't extract financing from it. I 771 00:36:18,596 --> 00:36:20,276 Speaker 2: have basically a guy we worked with for a long 772 00:36:20,316 --> 00:36:23,516 Speaker 2: time and another team member. I've just told them, like, look, 773 00:36:23,556 --> 00:36:25,756 Speaker 2: my objective is for you to maintain the reputation of 774 00:36:25,796 --> 00:36:27,596 Speaker 2: the place. Just keep running it well and make sure 775 00:36:27,596 --> 00:36:29,276 Speaker 2: I don't. And my one requirement is I need to 776 00:36:29,276 --> 00:36:30,196 Speaker 2: not think about it at all. 777 00:36:30,396 --> 00:36:30,716 Speaker 1: Huh. 778 00:36:31,476 --> 00:36:34,716 Speaker 2: And I'm working on the universal vaccine techt so maybe i'll, 779 00:36:35,516 --> 00:36:36,756 Speaker 2: you know, in the future, I'll want to go and 780 00:36:36,796 --> 00:36:38,876 Speaker 2: settle around and be a restaurant tour but like right now, 781 00:36:38,876 --> 00:36:40,196 Speaker 2: I just needed to not think about it. 782 00:36:42,596 --> 00:36:45,156 Speaker 1: Her to use the word hard ass a few times 783 00:36:45,156 --> 00:36:48,716 Speaker 1: in other interviews, are you a hard ass? 784 00:36:50,476 --> 00:36:56,636 Speaker 2: I think on myself and on an expectation of detailed 785 00:36:58,556 --> 00:37:00,356 Speaker 2: I think research needs to be done in a very 786 00:37:00,396 --> 00:37:02,716 Speaker 2: particular process. I don't think my team would say I'm 787 00:37:02,756 --> 00:37:03,196 Speaker 2: a hard ass. 788 00:37:03,236 --> 00:37:07,476 Speaker 3: I don't I think that, or maybe I've evolved over time. 789 00:37:07,516 --> 00:37:10,316 Speaker 2: I think I have exacting standards of expectation of how 790 00:37:10,316 --> 00:37:12,436 Speaker 2: to get things done. But it's not like it's more 791 00:37:12,516 --> 00:37:14,836 Speaker 2: like me driven of anxiety than me going in. 792 00:37:14,796 --> 00:37:18,076 Speaker 3: And like I don't bark at people or anything. I'm like, guys, we. 793 00:37:18,116 --> 00:37:19,596 Speaker 1: Have to have this anxious hard as. 794 00:37:20,316 --> 00:37:21,676 Speaker 2: Yeah, I have to be like, look, we have to 795 00:37:21,716 --> 00:37:25,476 Speaker 2: have a set of standard you know, controls, and then 796 00:37:25,476 --> 00:37:26,836 Speaker 2: we need to run this in a certain way and 797 00:37:26,836 --> 00:37:28,796 Speaker 2: we need to have things documented. Otherwise we're just walking 798 00:37:28,796 --> 00:37:31,356 Speaker 2: on quicksand and we'll just mess up every time. So 799 00:37:31,756 --> 00:37:33,276 Speaker 2: now I don't think I'm a hard ass. I think 800 00:37:33,316 --> 00:37:36,356 Speaker 2: there's certain things where I have exacting expectations. But I 801 00:37:36,396 --> 00:37:38,196 Speaker 2: also think that you have to have that if you 802 00:37:38,236 --> 00:37:40,716 Speaker 2: want to build a I've struggled to find an example 803 00:37:40,756 --> 00:37:43,516 Speaker 2: of a big company that was built on technology where 804 00:37:43,516 --> 00:37:45,396 Speaker 2: the CEO did not have that property. Because I think 805 00:37:45,396 --> 00:37:48,036 Speaker 2: there's a certain expectation of excellence that is required to 806 00:37:48,036 --> 00:37:51,396 Speaker 2: build something great. Maybe a little bit of a hard ass, 807 00:37:51,836 --> 00:37:53,996 Speaker 2: A little bit of hard ass, all right, occasional. 808 00:37:57,036 --> 00:38:01,276 Speaker 1: Jacob Glanville is the founder and CEO of Centovax. You 809 00:38:01,276 --> 00:38:05,076 Speaker 1: can email us at problem at pushkin dot fm, and 810 00:38:05,156 --> 00:38:08,036 Speaker 1: please do email us. I read all the emails. Today's 811 00:38:08,076 --> 00:38:12,196 Speaker 1: show was produced by Gabriel Hunter Chang, edited by Alexandra Garriton, 812 00:38:12,596 --> 00:38:15,956 Speaker 1: and engineered by Sarah Bruguer. I'm Jacob Goldstein, and we'll 813 00:38:15,956 --> 00:38:18,076 Speaker 1: be back next week with another episode of What's Your 814 00:38:18,076 --> 00:38:28,316 Speaker 1: Problem