1 00:00:15,356 --> 00:00:23,916 Speaker 1: Pushkin. Hello, Hello Revisionist History listeners, Happy New Year. Twenty 2 00:00:23,956 --> 00:00:25,596 Speaker 1: twenty five is going to be a great year for 3 00:00:25,636 --> 00:00:27,796 Speaker 1: this podcast, and I want to give you a little 4 00:00:27,876 --> 00:00:30,756 Speaker 1: preview of what to expect. The main event of the 5 00:00:30,836 --> 00:00:33,396 Speaker 1: year is going to be a multi part series from 6 00:00:33,436 --> 00:00:37,556 Speaker 1: Alabama true crime, but with a very revisionist history twist, 7 00:00:37,796 --> 00:00:40,636 Speaker 1: So keep that in mind. Then before we drop that, 8 00:00:40,836 --> 00:00:43,676 Speaker 1: we're going to do two other smaller things. If you 9 00:00:43,676 --> 00:00:46,116 Speaker 1: remember last season, we did a series of interviews with 10 00:00:46,116 --> 00:00:48,476 Speaker 1: screenwriters on their favorite ideas that never made it to 11 00:00:48,516 --> 00:00:51,236 Speaker 1: the screen. We're doing another round of interviews this year, 12 00:00:51,556 --> 00:00:53,876 Speaker 1: half a dozen or so. And then we're also going 13 00:00:53,916 --> 00:00:57,396 Speaker 1: to do a smaller batch of old school revisionist history episodes, 14 00:00:57,716 --> 00:01:01,116 Speaker 1: some weird, some funny, some that will break your heart. 15 00:01:01,636 --> 00:01:04,716 Speaker 1: Over here at Pushkin, we've been hard at work all 16 00:01:04,876 --> 00:01:06,596 Speaker 1: with the goal of bringing you a little bit of 17 00:01:06,636 --> 00:01:13,836 Speaker 1: audio happiness. Stay tuned, everyone, Welcome to Revisionist History. We 18 00:01:13,876 --> 00:01:16,316 Speaker 1: have a special treat today. I had a chance to 19 00:01:16,316 --> 00:01:19,156 Speaker 1: sit down with a guy named Diego Rao who worked 20 00:01:19,156 --> 00:01:21,596 Speaker 1: for years at Apple Way UPI and then left to 21 00:01:21,596 --> 00:01:26,396 Speaker 1: become the chief Information and Digital officer at Eli Lillian Company. 22 00:01:26,676 --> 00:01:29,796 Speaker 1: One of the biggest drug makers in the world. Diogo, 23 00:01:29,996 --> 00:01:33,596 Speaker 1: as you will learn, is irreverent and fascinating and sees 24 00:01:33,636 --> 00:01:35,276 Speaker 1: a good ten years ahead of the rest of us. 25 00:01:35,676 --> 00:01:37,956 Speaker 1: At the end of our conversation, Diego said to me, 26 00:01:38,436 --> 00:01:41,756 Speaker 1: you know, we never got to AI, which is true. 27 00:01:42,196 --> 00:01:45,796 Speaker 1: Can you imagine a conversation about technology so interesting that 28 00:01:45,876 --> 00:01:49,756 Speaker 1: you never get to the subject of artificial intelligence? That's 29 00:01:50,076 --> 00:01:54,076 Speaker 1: what you're about to hear. We're going to talk about 30 00:01:54,556 --> 00:01:58,036 Speaker 1: a whole number of things, but I wanted you to 31 00:01:58,156 --> 00:02:01,436 Speaker 1: start because you're a very unusual figure. You work it 32 00:02:01,476 --> 00:02:04,156 Speaker 1: for Eli Lily, but you are a very unusual figure 33 00:02:04,156 --> 00:02:06,356 Speaker 1: at Eli Lilly. Is that a fair statement. 34 00:02:07,396 --> 00:02:10,876 Speaker 2: I think I have that reputation of being unusual at 35 00:02:10,956 --> 00:02:13,196 Speaker 2: least I like to try to do things a little 36 00:02:13,196 --> 00:02:13,756 Speaker 2: bit differently. 37 00:02:13,836 --> 00:02:17,156 Speaker 1: You know, I was talking about your background. Yeah, you 38 00:02:16,796 --> 00:02:19,476 Speaker 1: you worked in the tech industry for how many years? 39 00:02:19,636 --> 00:02:21,996 Speaker 2: I worked in the tech industry Well, really my whole life, 40 00:02:22,316 --> 00:02:24,796 Speaker 2: But I the last ten years before I came to Lily, 41 00:02:24,836 --> 00:02:28,076 Speaker 2: I was at Apple, and before that I was doing 42 00:02:28,156 --> 00:02:31,596 Speaker 2: technical other kinds of technology work and McKenzie and before 43 00:02:31,676 --> 00:02:33,636 Speaker 2: that I was in the startup world. So I've really 44 00:02:33,636 --> 00:02:35,596 Speaker 2: spent my whole life in technology. 45 00:02:35,796 --> 00:02:38,716 Speaker 1: How many people do you think have moved from Apple 46 00:02:38,876 --> 00:02:40,196 Speaker 1: to a life sciences company? 47 00:02:40,556 --> 00:02:42,676 Speaker 2: About five? I think I know them all. 48 00:02:42,756 --> 00:02:46,236 Speaker 1: Do you guys get together reading most of them? And 49 00:02:46,356 --> 00:02:48,796 Speaker 1: how did So this is a kind of I want 50 00:02:48,836 --> 00:02:52,196 Speaker 1: to start this little on this little tangent, but how 51 00:02:52,236 --> 00:02:54,996 Speaker 1: did that work? Exactly? So somebody comes to you and says, 52 00:02:55,476 --> 00:02:58,676 Speaker 1: have you ever thought to work for a pharma company? Well? 53 00:02:58,756 --> 00:03:00,676 Speaker 2: Yeah, And that's the way a lot of these things start. 54 00:03:00,756 --> 00:03:02,796 Speaker 2: It's you know, there was a recruiter that I worked 55 00:03:02,836 --> 00:03:05,276 Speaker 2: with who who gave me a call and said, hey, 56 00:03:05,356 --> 00:03:08,476 Speaker 2: I've got this this opportunity. It's in life sciences, and 57 00:03:08,596 --> 00:03:11,236 Speaker 2: I was like, I've never done anything in life sciences before. 58 00:03:11,236 --> 00:03:12,036 Speaker 1: It's like, that's okay. 59 00:03:12,316 --> 00:03:14,276 Speaker 2: So I look at the spec and the spec is, 60 00:03:14,476 --> 00:03:16,436 Speaker 2: you know, it's pretty interesting. So I'm like, okay, it's 61 00:03:16,436 --> 00:03:20,036 Speaker 2: worth a phone call. And then I meet our CEO 62 00:03:20,276 --> 00:03:22,516 Speaker 2: and our head of HR and like, these people are 63 00:03:22,556 --> 00:03:24,396 Speaker 2: really nice. And so that's like the second thing that 64 00:03:24,436 --> 00:03:26,916 Speaker 2: I noticed is that they're really, really, really nice. And 65 00:03:26,956 --> 00:03:29,196 Speaker 2: that's that's a big difference, by the way, coming from 66 00:03:29,316 --> 00:03:31,436 Speaker 2: versus the tech world. I have to say a little 67 00:03:31,476 --> 00:03:35,116 Speaker 2: more about that. And then I start talking to our 68 00:03:35,196 --> 00:03:37,636 Speaker 2: head of research and development about some of the problems 69 00:03:37,676 --> 00:03:41,876 Speaker 2: that we're trying to solve in life sciences, and I realized, Wow, 70 00:03:41,916 --> 00:03:44,476 Speaker 2: this is like a fascinating space. I kind of thought 71 00:03:44,516 --> 00:03:47,436 Speaker 2: that like everything exciting in the world was happening in tech, 72 00:03:47,916 --> 00:03:50,116 Speaker 2: and then I then I came to realize, no, actually, 73 00:03:50,116 --> 00:03:53,036 Speaker 2: there's a lot of exciting stuff that's happening outside of 74 00:03:53,076 --> 00:03:53,836 Speaker 2: just the tech world. 75 00:03:54,076 --> 00:03:57,236 Speaker 1: Yeah, so let's start. So you make this when did 76 00:03:57,236 --> 00:03:58,996 Speaker 1: you start your job at. 77 00:03:58,836 --> 00:04:01,556 Speaker 2: Lily May seventeenth, twenty twenty one. 78 00:04:02,516 --> 00:04:06,596 Speaker 1: So go through, just off the top of your head, 79 00:04:07,116 --> 00:04:12,996 Speaker 1: the most surprising things you learned moving from Silicon Valley 80 00:04:13,036 --> 00:04:14,916 Speaker 1: to a life sciences company. 81 00:04:15,876 --> 00:04:19,196 Speaker 2: Well, the number one thing that I actually saw was 82 00:04:19,276 --> 00:04:21,556 Speaker 2: actually the nice people parts. But you know, the second 83 00:04:21,556 --> 00:04:24,396 Speaker 2: thing that I noticed was really long time scales, Like 84 00:04:24,476 --> 00:04:27,276 Speaker 2: the size in the duration of things is just it 85 00:04:27,396 --> 00:04:31,036 Speaker 2: is just beyond belief. My first executive committee meeting in 86 00:04:31,076 --> 00:04:34,116 Speaker 2: twenty twenty one, we were talking about a revenue forecast 87 00:04:34,236 --> 00:04:36,876 Speaker 2: that was for two thousand and thirty and that was 88 00:04:36,996 --> 00:04:40,876 Speaker 2: nine years out, like in tech, like, looking like eighteen 89 00:04:40,876 --> 00:04:42,516 Speaker 2: months out of revenue is ridiculous. 90 00:04:43,556 --> 00:04:45,876 Speaker 1: Well wait, wait, so when you see that, what's your 91 00:04:46,076 --> 00:04:46,796 Speaker 1: what's your reaction? 92 00:04:46,876 --> 00:04:50,076 Speaker 2: Oh? Yes, there's no way we can predict our revenues 93 00:04:50,116 --> 00:04:51,996 Speaker 2: for you know, for nine years from now. And of course, 94 00:04:52,036 --> 00:04:54,676 Speaker 2: now I realize that I'm in here, that there are 95 00:04:54,716 --> 00:04:56,476 Speaker 2: a lot of things that you can predict and it 96 00:04:56,556 --> 00:04:59,676 Speaker 2: is actually very predictable. It's a big bed. If it works, 97 00:04:59,716 --> 00:05:03,356 Speaker 2: you'll know you'll you'll hit it. But it's much less volatile. 98 00:05:03,836 --> 00:05:07,116 Speaker 2: It's these time scales are crazy though, because like at 99 00:05:07,156 --> 00:05:09,596 Speaker 2: our last Executive Committee meeting right before the break, we 100 00:05:09,596 --> 00:05:12,316 Speaker 2: were talking about a product launch. I'll ask you a question, 101 00:05:12,556 --> 00:05:15,156 Speaker 2: when guess when our product launch is that we were 102 00:05:15,196 --> 00:05:16,916 Speaker 2: talking about in December. 103 00:05:17,916 --> 00:05:21,116 Speaker 1: Well, now that you've prime Prime three, it's going to 104 00:05:21,116 --> 00:05:22,676 Speaker 1: be five, six, seven years. 105 00:05:22,436 --> 00:05:25,796 Speaker 2: No, twenty and thirty six, Oh my god. And so 106 00:05:26,116 --> 00:05:27,916 Speaker 2: there is I can guarantee you that there are zero 107 00:05:28,036 --> 00:05:30,316 Speaker 2: tech companies right now talking about what they're going to 108 00:05:30,396 --> 00:05:31,836 Speaker 2: launch in twenty and thirty six. 109 00:05:32,116 --> 00:05:36,756 Speaker 1: Yeah. Yeah, and wait there not only so there is 110 00:05:36,836 --> 00:05:40,676 Speaker 1: certainty that this this product will be approved, but just 111 00:05:41,516 --> 00:05:45,796 Speaker 1: the the you can be you can be ten years 112 00:05:45,836 --> 00:05:48,476 Speaker 1: away and be certain will be approved, but know that 113 00:05:48,556 --> 00:05:50,196 Speaker 1: you still have ten years worth of work to do. 114 00:05:50,476 --> 00:05:52,996 Speaker 2: Yes, you can't be certain, of course, that anything is 115 00:05:53,036 --> 00:05:55,716 Speaker 2: going to be approved, and so we apply a probability 116 00:05:55,756 --> 00:05:58,476 Speaker 2: of technical success. This phrase I'd never heard of before 117 00:05:58,476 --> 00:06:00,156 Speaker 2: I got here, But every step ale of the way 118 00:06:00,276 --> 00:06:03,436 Speaker 2: has probability of technical success, and so you factor it 119 00:06:03,436 --> 00:06:05,916 Speaker 2: in and you you know, you take all that into account. 120 00:06:06,196 --> 00:06:08,236 Speaker 2: But you know, when you have a good medicine and 121 00:06:08,276 --> 00:06:10,196 Speaker 2: you know what it's going to take. But it just 122 00:06:10,276 --> 00:06:13,916 Speaker 2: takes ten years to bring a medicine to life, and 123 00:06:13,956 --> 00:06:15,676 Speaker 2: it's and I don't think that was one of the 124 00:06:15,676 --> 00:06:17,556 Speaker 2: things that I realized before I came into this, just 125 00:06:17,676 --> 00:06:19,596 Speaker 2: how long it takes and how much money it takes. 126 00:06:19,996 --> 00:06:22,236 Speaker 1: So it is possible that you will work on things 127 00:06:22,796 --> 00:06:25,076 Speaker 1: that you will never see come to fruish. 128 00:06:25,116 --> 00:06:28,316 Speaker 2: In fact, most of our scientists that work here will 129 00:06:28,356 --> 00:06:31,236 Speaker 2: never see their medicines that they're working on come to life, 130 00:06:31,756 --> 00:06:33,916 Speaker 2: which is kind of crazy to think of. 131 00:06:34,676 --> 00:06:36,676 Speaker 1: And it's affect the culture of organization. 132 00:06:37,036 --> 00:06:40,316 Speaker 2: It gives it a really long term perspective, like crazy 133 00:06:40,356 --> 00:06:43,556 Speaker 2: long term perspective when we when we're talking about things 134 00:06:43,636 --> 00:06:46,396 Speaker 2: making decisions, we're really not thinking, you know, like at 135 00:06:46,396 --> 00:06:48,556 Speaker 2: an executive committee level, there are some things that we're 136 00:06:48,556 --> 00:06:50,516 Speaker 2: doing on a you know, on a this year basis. 137 00:06:50,516 --> 00:06:51,716 Speaker 2: But there are a lot of things that we're doing 138 00:06:51,716 --> 00:06:54,236 Speaker 2: that we're really talking about, like the twenty thirties, like 139 00:06:54,356 --> 00:06:58,316 Speaker 2: just just a much different timescale from from anything else. 140 00:06:58,356 --> 00:07:00,476 Speaker 2: And so we're not going to do anything stupid. I 141 00:07:00,516 --> 00:07:01,756 Speaker 2: think it's one of the one of the good things. 142 00:07:01,796 --> 00:07:02,956 Speaker 2: We're not going to trade off some of the long 143 00:07:03,036 --> 00:07:04,316 Speaker 2: term to get a little bit of a benefit in 144 00:07:04,356 --> 00:07:06,636 Speaker 2: the short term. So I think it makes us much 145 00:07:06,636 --> 00:07:10,676 Speaker 2: more rational all that way. I guess I would say 146 00:07:10,676 --> 00:07:11,596 Speaker 2: we play the long game. 147 00:07:12,476 --> 00:07:14,156 Speaker 1: But I want to go back to so you come 148 00:07:14,196 --> 00:07:17,916 Speaker 1: to Lily and I'm curious, so what did they want 149 00:07:17,956 --> 00:07:18,476 Speaker 1: from you? 150 00:07:20,716 --> 00:07:26,116 Speaker 2: My boss, our CEO, gave me a mandate to really change, 151 00:07:26,156 --> 00:07:29,836 Speaker 2: to bring in technology into everything that we that we did, 152 00:07:30,516 --> 00:07:33,196 Speaker 2: So it was not a caretaker role, sort of a mandate. 153 00:07:33,276 --> 00:07:35,196 Speaker 2: You know, we want you to just keep running the things. 154 00:07:35,356 --> 00:07:37,116 Speaker 2: We want you to really figure out, like what can 155 00:07:37,156 --> 00:07:40,036 Speaker 2: you do to shake things up? And so that was 156 00:07:40,076 --> 00:07:43,516 Speaker 2: really that was really the goal. And I think a 157 00:07:43,556 --> 00:07:47,476 Speaker 2: big part of it was bringing a consumer orientation as well. 158 00:07:47,516 --> 00:07:50,596 Speaker 2: And I think this is an industry that has largely 159 00:07:50,636 --> 00:07:53,236 Speaker 2: worked the same since the nineteen fifties, I mean, if 160 00:07:53,276 --> 00:07:55,796 Speaker 2: you look at it, the way you get medicines today 161 00:07:56,076 --> 00:07:59,116 Speaker 2: as a patient is basically unchanged. You go to your doctor, 162 00:07:59,116 --> 00:08:02,636 Speaker 2: they write a form. Maybe now they submit your prescription electronically. 163 00:08:03,436 --> 00:08:05,116 Speaker 2: You still have to make sure you can pay for 164 00:08:05,236 --> 00:08:07,116 Speaker 2: You still have to go to a retail pharmacy in 165 00:08:07,156 --> 00:08:10,476 Speaker 2: most cases. None of that's really changed since the nineteen fifties, 166 00:08:10,476 --> 00:08:12,356 Speaker 2: even though we have so much more. So a big 167 00:08:12,396 --> 00:08:15,156 Speaker 2: part of what we're trying to do is actually a 168 00:08:15,196 --> 00:08:17,276 Speaker 2: big part of my mandate is to really bring this 169 00:08:17,356 --> 00:08:19,916 Speaker 2: into the twenty first century, or at least the late 170 00:08:19,956 --> 00:08:20,956 Speaker 2: twentieth century. 171 00:08:21,516 --> 00:08:25,636 Speaker 1: But is there within the portfolio of things that Lily does, 172 00:08:26,516 --> 00:08:29,676 Speaker 1: do you touch on everything or just are you? Are 173 00:08:29,716 --> 00:08:33,516 Speaker 1: you focused on the consumer side of the business. I mean, 174 00:08:33,516 --> 00:08:35,276 Speaker 1: what's the kind of not to remit? 175 00:08:35,676 --> 00:08:37,316 Speaker 2: The great thing is that I get to focus on 176 00:08:37,356 --> 00:08:40,436 Speaker 2: all of that stuff, So everything that's technology related. I 177 00:08:42,236 --> 00:08:45,196 Speaker 2: do cover everything from the discovery side through the consumer side, 178 00:08:45,196 --> 00:08:47,556 Speaker 2: and actually those are probably some of my favorite parts. 179 00:08:47,556 --> 00:08:49,436 Speaker 2: And I'm going to because of course I shouldn't be 180 00:08:49,436 --> 00:08:51,596 Speaker 2: say favorites, but you know, I love the discovery side 181 00:08:51,596 --> 00:08:54,116 Speaker 2: and discovering new molecules and what we can do there 182 00:08:54,836 --> 00:08:57,036 Speaker 2: a lot of cool stuff, especially with AI, we could 183 00:08:57,076 --> 00:09:00,276 Speaker 2: talk for hours about. And the consumer side is also 184 00:09:00,316 --> 00:09:02,236 Speaker 2: the place where I see where I have a passion 185 00:09:02,276 --> 00:09:04,756 Speaker 2: coming from my prior life at Apple and just seeing 186 00:09:04,796 --> 00:09:06,996 Speaker 2: the potential we have to change everything there. I think 187 00:09:06,996 --> 00:09:09,516 Speaker 2: this whole industry hasn't really focused on, like how do 188 00:09:09,556 --> 00:09:12,516 Speaker 2: we make it an amazing experience and work backwards. I 189 00:09:12,556 --> 00:09:15,356 Speaker 2: think the kinds of things that you see at Apple 190 00:09:16,156 --> 00:09:18,876 Speaker 2: and a lot of other consumer rinan companies just haven't 191 00:09:19,476 --> 00:09:21,076 Speaker 2: haven't arrived here yet. 192 00:09:21,236 --> 00:09:24,836 Speaker 1: And how does putting the customer first in that chain 193 00:09:24,916 --> 00:09:28,156 Speaker 1: of the h in that chain of kind of interest 194 00:09:28,196 --> 00:09:31,436 Speaker 1: groups change the way you do business or change the 195 00:09:31,476 --> 00:09:33,316 Speaker 1: way you think about what you're doing. 196 00:09:33,396 --> 00:09:35,476 Speaker 2: That was the most fundamental thing that I learned from 197 00:09:35,516 --> 00:09:38,276 Speaker 2: my time at Apple. And I think most companies will say, oh, 198 00:09:38,276 --> 00:09:40,516 Speaker 2: we care about the customer. But you know, whenever you 199 00:09:40,556 --> 00:09:43,116 Speaker 2: start a project, people will have I don't know, they'll 200 00:09:43,116 --> 00:09:45,156 Speaker 2: have five pillars or five things they need to go after. Well, 201 00:09:45,276 --> 00:09:47,996 Speaker 2: maybe there's the business case, the product, the customer, the 202 00:09:48,476 --> 00:09:50,516 Speaker 2: you know, you know, you'll have like five or six 203 00:09:50,516 --> 00:09:52,956 Speaker 2: different things. And the way you'd always do things that 204 00:09:52,996 --> 00:09:56,516 Speaker 2: Apple was was different. You would always start by like 205 00:09:56,676 --> 00:10:00,476 Speaker 2: what's the customer the consumer experience that you want to create, 206 00:10:00,756 --> 00:10:03,036 Speaker 2: and then work backwards and then figure out business. You know, 207 00:10:03,076 --> 00:10:04,836 Speaker 2: can you make a can you make it a financial 208 00:10:04,876 --> 00:10:07,276 Speaker 2: case around it? Well maybe you can't, Okay, so we 209 00:10:07,276 --> 00:10:09,036 Speaker 2: need to maybe we can see how we can change 210 00:10:09,036 --> 00:10:11,316 Speaker 2: the back and forth. But it really was everything was 211 00:10:11,356 --> 00:10:13,716 Speaker 2: centered on the customer experience. It wasn't like a pillar 212 00:10:13,796 --> 00:10:16,556 Speaker 2: of one thing of five. It was like the thing 213 00:10:16,636 --> 00:10:19,956 Speaker 2: that was that was guiding everything. And I think that's 214 00:10:20,116 --> 00:10:22,316 Speaker 2: we're not there yet, but that's like that's the kind 215 00:10:22,356 --> 00:10:24,676 Speaker 2: of thing we need to do. Like every single time 216 00:10:25,196 --> 00:10:27,916 Speaker 2: we need to go, uh, we need to go back 217 00:10:27,916 --> 00:10:30,956 Speaker 2: and see what's what's the customer experience? Like we need 218 00:10:30,956 --> 00:10:33,476 Speaker 2: to actually focus on like making a customer experience better. 219 00:10:43,756 --> 00:10:47,636 Speaker 1: You have a whole table full of goodies over there. 220 00:10:47,916 --> 00:10:50,876 Speaker 1: We need to pick a goodie and let's let's use 221 00:10:51,236 --> 00:10:54,916 Speaker 1: uh uh this as a specific walk me through the 222 00:10:54,996 --> 00:11:00,236 Speaker 1: kind of thinking behind the product, uh, the kind of challenge, 223 00:11:00,276 --> 00:11:03,796 Speaker 1: the specific challenges, how it represents this process that you've 224 00:11:03,836 --> 00:11:07,996 Speaker 1: been talking about. You pick great not just so people 225 00:11:08,036 --> 00:11:11,996 Speaker 1: know this about but a couple of feet from from 226 00:11:12,076 --> 00:11:16,676 Speaker 1: diego is there, there's about looks like eight to ten. Uh, 227 00:11:16,836 --> 00:11:20,156 Speaker 1: mysterious boxes that are so. 228 00:11:20,156 --> 00:11:22,556 Speaker 2: I have to I have to have to share with 229 00:11:22,596 --> 00:11:24,916 Speaker 2: everybody that like. Uh, Malcolm and I had a little 230 00:11:24,956 --> 00:11:27,156 Speaker 2: prep call before, you know, a couple of weeks ago, 231 00:11:27,476 --> 00:11:29,836 Speaker 2: and it was only about ten minutes because he just said, okay, 232 00:11:29,916 --> 00:11:31,996 Speaker 2: you know, if you got any toys, any goodies, like, 233 00:11:32,236 --> 00:11:34,236 Speaker 2: bring them along, and so like, my team gave me 234 00:11:34,276 --> 00:11:36,116 Speaker 2: a box of goodies here which is all slayed out 235 00:11:36,116 --> 00:11:38,276 Speaker 2: on the table. And then uh, and then I think 236 00:11:38,316 --> 00:11:39,836 Speaker 2: you said, okay, and I want to talk too much more, 237 00:11:39,956 --> 00:11:40,836 Speaker 2: Let's not do any more prep. 238 00:11:41,756 --> 00:11:43,836 Speaker 1: Well, the thing is, if you have small children, as 239 00:11:43,836 --> 00:11:47,116 Speaker 1: I do, you think exclusively in terms of of shiny 240 00:11:47,156 --> 00:11:50,076 Speaker 1: little gifts, you'd be sprung. I almost said, can you 241 00:11:50,076 --> 00:11:53,956 Speaker 1: bring snacks? That would be only stop awesome? 242 00:11:54,076 --> 00:11:57,036 Speaker 2: All right, so let me grab a box. All right, 243 00:11:57,036 --> 00:11:58,996 Speaker 2: I'm going to show you something that's that is now. 244 00:11:59,156 --> 00:12:02,596 Speaker 2: Let me grab that one, yep, and I'm I'm going 245 00:12:02,636 --> 00:12:04,196 Speaker 2: to hide it here for just a second. Tell you 246 00:12:04,196 --> 00:12:06,756 Speaker 2: what the what the problem is that we're going after. 247 00:12:07,556 --> 00:12:09,676 Speaker 2: One of the big challenges in the world right now 248 00:12:10,476 --> 00:12:15,836 Speaker 2: is medicine and medicine safety. When I was at Apple, 249 00:12:16,316 --> 00:12:20,756 Speaker 2: I saw counterfeit iPhones, and I couldn't believe it. You 250 00:12:20,756 --> 00:12:23,276 Speaker 2: wouldn't know that they were counterfeit until you actually picked 251 00:12:23,276 --> 00:12:26,036 Speaker 2: them up and played with them for like half an hour. 252 00:12:26,316 --> 00:12:27,916 Speaker 2: And sometimes we would have to send them in and 253 00:12:27,956 --> 00:12:32,316 Speaker 2: have them get X rayed to know that they're they're fake. Well, 254 00:12:32,876 --> 00:12:35,276 Speaker 2: that was on those were on products, you know, that 255 00:12:35,356 --> 00:12:38,076 Speaker 2: was like a thousand dollars product that Electronics very hard 256 00:12:38,076 --> 00:12:41,436 Speaker 2: to make counterfeit, but the economics were there. Medicines are 257 00:12:41,436 --> 00:12:43,836 Speaker 2: a lot easier to fake or at least make them 258 00:12:43,876 --> 00:12:45,796 Speaker 2: look fake. All you need to do is copy the 259 00:12:45,916 --> 00:12:48,396 Speaker 2: box and you know, if it's in a vial, you know, 260 00:12:48,436 --> 00:12:51,476 Speaker 2: put a label on it something like that. And with 261 00:12:51,596 --> 00:12:53,196 Speaker 2: some of the medicines that are out there right now, 262 00:12:53,236 --> 00:12:55,876 Speaker 2: there's a huge financial incentive for people to have to 263 00:12:55,956 --> 00:12:59,716 Speaker 2: make to say that they're making medicines that they really 264 00:12:59,756 --> 00:13:01,036 Speaker 2: are not and they're faking them. 265 00:13:01,116 --> 00:13:04,516 Speaker 1: What would be just just just fascinating. What is there 266 00:13:04,516 --> 00:13:10,476 Speaker 1: a particular kind of medicine for which the counterfeiters motivation 267 00:13:10,596 --> 00:13:11,116 Speaker 1: is greatest? 268 00:13:11,316 --> 00:13:14,676 Speaker 2: Well right now, uh, in chronic weight management, we have 269 00:13:14,756 --> 00:13:18,196 Speaker 2: the g LP one medicines and so above for for 270 00:13:18,356 --> 00:13:22,756 Speaker 2: us and the other leading maker of g LP one medicines. 271 00:13:24,436 --> 00:13:28,156 Speaker 2: Counterfeiting is a real, real threat and back to formularities 272 00:13:28,196 --> 00:13:30,796 Speaker 2: and things like that. A lot of insurance plans do 273 00:13:30,876 --> 00:13:34,356 Speaker 2: not cover uh, chronic weight loss management. Uh. And so 274 00:13:34,436 --> 00:13:37,516 Speaker 2: there's a huge financial incentive on the black market to say, hey, 275 00:13:37,516 --> 00:13:38,756 Speaker 2: we're going to go and. 276 00:13:38,756 --> 00:13:40,956 Speaker 1: Some uncertainty about outcomes. So you would take you a 277 00:13:40,956 --> 00:13:43,716 Speaker 1: while to figure out you're taking a fake correct it. 278 00:13:43,956 --> 00:13:46,876 Speaker 2: And I mean it's not only I mean it's not 279 00:13:46,876 --> 00:13:49,276 Speaker 2: only fake, it's actually many of these cases are risky 280 00:13:49,316 --> 00:13:51,956 Speaker 2: because once you see, uh, once you see like the 281 00:13:51,996 --> 00:13:54,796 Speaker 2: sterile environments that these medicines go through to be made, 282 00:13:55,236 --> 00:13:59,356 Speaker 2: you know that it could in the best case, it's harmless, right, 283 00:13:59,396 --> 00:14:01,316 Speaker 2: I mean, the best case is you don't get any effect. 284 00:14:02,036 --> 00:14:04,236 Speaker 2: And so what I've got here as a product, I'm 285 00:14:04,276 --> 00:14:09,396 Speaker 2: gonna uh, this can be any product and uh it's 286 00:14:09,396 --> 00:14:12,076 Speaker 2: so don't pay attention to what product this actually is. 287 00:14:13,676 --> 00:14:15,876 Speaker 2: And I've got the product right here, and I can 288 00:14:15,916 --> 00:14:18,756 Speaker 2: tap my phone against it and I will get it 289 00:14:19,396 --> 00:14:23,516 Speaker 2: in an an NFC tag. And that n f C 290 00:14:23,676 --> 00:14:26,156 Speaker 2: tag is just like when you do a contact list 291 00:14:26,236 --> 00:14:28,956 Speaker 2: payment and it will bring up, it'll bring up a 292 00:14:28,996 --> 00:14:30,836 Speaker 2: page to show you that you could actually verify that 293 00:14:30,916 --> 00:14:35,716 Speaker 2: the packaging matches something that we've produced. Unlike a QR code, 294 00:14:35,716 --> 00:14:38,356 Speaker 2: it can't be copied. It's cryptographically secure. And this is 295 00:14:38,356 --> 00:14:41,276 Speaker 2: where the technology part gets interesting, because they can copy 296 00:14:41,316 --> 00:14:42,796 Speaker 2: the box, they could do all kinds of things like that, 297 00:14:42,836 --> 00:14:45,156 Speaker 2: but they can't copy that tag. There's one and only 298 00:14:45,196 --> 00:14:47,596 Speaker 2: one tag that you can that you can tap and 299 00:14:47,596 --> 00:14:48,516 Speaker 2: then we can verify it. 300 00:14:48,876 --> 00:14:51,836 Speaker 1: Yeah, so how how how long did it take to 301 00:14:51,876 --> 00:14:53,396 Speaker 1: develop that particular technology? 302 00:14:53,636 --> 00:14:56,356 Speaker 2: So it took uh, this is something we did within 303 00:14:56,436 --> 00:14:58,676 Speaker 2: my first few months that coming here. Uh, and we 304 00:14:58,716 --> 00:15:02,396 Speaker 2: haven't launched it yet, so they the designing it is 305 00:15:02,476 --> 00:15:04,316 Speaker 2: very easy, the developing it is very hard. 306 00:15:04,436 --> 00:15:06,196 Speaker 1: So you could you could do. What you're saying is 307 00:15:06,436 --> 00:15:08,676 Speaker 1: what you have is a technology that could be a 308 00:15:08,676 --> 00:15:14,356 Speaker 1: platform or for building an interaction between the consumer of 309 00:15:14,356 --> 00:15:17,396 Speaker 1: the bill, the patient correct and the manufacturer. 310 00:15:17,596 --> 00:15:20,276 Speaker 2: That's absolutely right. And you know, we actually don't even 311 00:15:20,316 --> 00:15:22,756 Speaker 2: care about it necessarily being just for us, Like this 312 00:15:22,876 --> 00:15:24,476 Speaker 2: is the kind of thing where we'd say, this is 313 00:15:24,516 --> 00:15:27,156 Speaker 2: a great thing. If adherence can improve for patients across 314 00:15:27,196 --> 00:15:30,236 Speaker 2: all medicines, all manufacturers, that would be fantastic. 315 00:15:30,356 --> 00:15:35,436 Speaker 1: Yeah, how but you've put that RFID tag on the box. Correct, 316 00:15:35,716 --> 00:15:38,236 Speaker 1: But now there's still a thing inside the box. 317 00:15:38,036 --> 00:15:40,716 Speaker 2: Still up staying inside the box. So this is version one, 318 00:15:40,756 --> 00:15:43,316 Speaker 2: which is on the box, and then version two, which 319 00:15:43,316 --> 00:15:46,276 Speaker 2: we'll come to later, will be on the individual medicine itself. 320 00:15:46,436 --> 00:15:50,796 Speaker 1: What about protecting against an unauthorized use of the medicine? 321 00:15:50,796 --> 00:15:52,796 Speaker 1: What if the wrong person taps to your phone? 322 00:15:52,796 --> 00:15:56,116 Speaker 2: Against absolutely then you could actually make sure that you're 323 00:15:56,156 --> 00:15:58,116 Speaker 2: taking the right medicine. I also think making sure that 324 00:15:58,156 --> 00:16:00,356 Speaker 2: you haven't taken your medicine more than once in a 325 00:16:00,436 --> 00:16:02,636 Speaker 2: day is also an important thing because, you know what, 326 00:16:02,796 --> 00:16:05,676 Speaker 2: it's actually very easy to do. And I also think 327 00:16:05,716 --> 00:16:08,476 Speaker 2: that in a hospital environment it also is you know, 328 00:16:08,516 --> 00:16:10,316 Speaker 2: you could tie it into systems and make sure that 329 00:16:10,356 --> 00:16:14,036 Speaker 2: you're actually administering the correct medicine. Uh, not something that 330 00:16:14,396 --> 00:16:17,836 Speaker 2: you can imagine a work flashing up on on the 331 00:16:18,156 --> 00:16:20,916 Speaker 2: health healthcare provider's device if it's the wrong medicine. 332 00:16:20,956 --> 00:16:23,516 Speaker 1: So this is beta with the box. Yeah, how long 333 00:16:23,676 --> 00:16:25,756 Speaker 1: how many years before you think you could be actually 334 00:16:25,796 --> 00:16:28,556 Speaker 1: in the pill itself? The pill itself. 335 00:16:28,596 --> 00:16:30,796 Speaker 2: I don't know if we'll ever get past the consumer 336 00:16:33,036 --> 00:16:36,436 Speaker 2: acceptance of r f I D like if like actually 337 00:16:36,436 --> 00:16:38,356 Speaker 2: being in the pillow soft. But if we could get there, 338 00:16:38,996 --> 00:16:41,636 Speaker 2: that's that's not super far out, that's probably you know, 339 00:16:42,276 --> 00:16:45,996 Speaker 2: probably five years out of Yeah. Yeah, but it's not 340 00:16:46,356 --> 00:16:47,036 Speaker 2: the technology. 341 00:16:47,276 --> 00:16:49,276 Speaker 1: Your better version is that you point your phone at 342 00:16:49,316 --> 00:16:53,356 Speaker 1: your gut and you find all the stuff that's in there. Goodness, 343 00:16:53,356 --> 00:16:55,516 Speaker 1: what do they have for dinner? 344 00:16:55,636 --> 00:16:57,596 Speaker 2: Yeah? Exactly, it might not be good to find that out. 345 00:16:59,556 --> 00:17:02,316 Speaker 1: Pick another wearable because now I'm interested. First of all, 346 00:17:03,276 --> 00:17:05,636 Speaker 1: has literally ever done a wearable before? 347 00:17:06,156 --> 00:17:09,516 Speaker 2: Uh? No, We've not produced a wearable of our our own, 348 00:17:10,156 --> 00:17:11,996 Speaker 2: and it ends up being a little bit challenging as 349 00:17:12,036 --> 00:17:14,516 Speaker 2: a manufacturer. Be a lot easier if we didn't make 350 00:17:14,596 --> 00:17:18,436 Speaker 2: drugs to actually launch a wearable. But because you make 351 00:17:18,516 --> 00:17:21,356 Speaker 2: drugs and then then and then the question is as well, 352 00:17:21,396 --> 00:17:24,156 Speaker 2: are you using this too? Does it have to be? 353 00:17:24,316 --> 00:17:26,996 Speaker 2: Is it required for somebody taking to medicine? So there's 354 00:17:26,996 --> 00:17:29,276 Speaker 2: a whole host of things that makes it really complicated 355 00:17:29,276 --> 00:17:31,436 Speaker 2: for us to do it. So the most, for the 356 00:17:31,436 --> 00:17:33,836 Speaker 2: most part, where we use these things are in clinical trials. 357 00:17:34,076 --> 00:17:38,276 Speaker 1: So how many wearables take me ten years into the future? Yeah, 358 00:17:38,916 --> 00:17:41,596 Speaker 1: how many wearables am I wearing? If I want to 359 00:17:41,636 --> 00:17:44,876 Speaker 1: be completely you know, if. 360 00:17:44,716 --> 00:17:47,916 Speaker 2: You're a nerd out on all of this. You know, 361 00:17:48,516 --> 00:17:52,116 Speaker 2: I think it's probably on the scale of two to three. 362 00:17:52,196 --> 00:17:54,796 Speaker 2: I think I think there are only so many places 363 00:17:54,996 --> 00:17:59,396 Speaker 2: that that you're willing to put a wearable, you know. 364 00:17:59,476 --> 00:18:02,356 Speaker 2: I you know, you can imagine there's your ring, there's 365 00:18:02,436 --> 00:18:05,116 Speaker 2: a watch, and you know that you might be able 366 00:18:05,156 --> 00:18:08,476 Speaker 2: to if you've ever had like a ziopatch or anything 367 00:18:08,516 --> 00:18:12,516 Speaker 2: like that, part catch. Those are not terribly uncomfortable insuls. 368 00:18:13,036 --> 00:18:15,636 Speaker 2: You know, you could, you could imagine, But after that, 369 00:18:16,476 --> 00:18:18,676 Speaker 2: you don't have that many more places I think that 370 00:18:18,716 --> 00:18:21,356 Speaker 2: you would you'd be willing to wear something. So I'll 371 00:18:21,396 --> 00:18:23,396 Speaker 2: go I'll go with those three tops. 372 00:18:23,516 --> 00:18:25,956 Speaker 1: I was gonna say eyes I was reading eyes. Yeah, 373 00:18:26,316 --> 00:18:29,356 Speaker 1: but really I was really a really fascinating study that 374 00:18:29,476 --> 00:18:31,596 Speaker 1: was looking trying to figure out what the difference is 375 00:18:31,636 --> 00:18:34,876 Speaker 1: between a novice police officer and an expert police officer. 376 00:18:35,356 --> 00:18:38,596 Speaker 1: And they use eye tracking and gave them scenarios and 377 00:18:38,916 --> 00:18:41,876 Speaker 1: figured out that they're looking at different things. So you 378 00:18:41,876 --> 00:18:45,036 Speaker 1: have a scenario of like that guy here and this 379 00:18:45,116 --> 00:18:47,516 Speaker 1: is happening here, and someone's throwing this here, and we 380 00:18:47,556 --> 00:18:50,116 Speaker 1: see the experts like looking do do do do do 381 00:18:50,116 --> 00:18:54,836 Speaker 1: do do doo, and the novice is looking right, Yeah, 382 00:18:54,916 --> 00:18:57,436 Speaker 1: one spot versus But I'm just curious about, like, you know, 383 00:18:58,836 --> 00:19:01,036 Speaker 1: my sense is this is kind of once you started 384 00:19:01,036 --> 00:19:03,916 Speaker 1: going down this road. Yeah, there's lots and lots and 385 00:19:03,956 --> 00:19:04,876 Speaker 1: lots and lots of things. 386 00:19:04,996 --> 00:19:06,316 Speaker 2: No, I thought you were going to go down a 387 00:19:06,316 --> 00:19:09,796 Speaker 2: different path, which is like the what you might like 388 00:19:09,916 --> 00:19:12,196 Speaker 2: enhancing your eyes or your hearing or things like that, 389 00:19:12,236 --> 00:19:16,636 Speaker 2: which is also like that's just another fascinating space of science. 390 00:19:16,676 --> 00:19:20,876 Speaker 1: And yeah, yeah, why one of the things you said 391 00:19:20,876 --> 00:19:23,636 Speaker 1: earlier big more interested when you said that if you're 392 00:19:23,676 --> 00:19:26,156 Speaker 1: making drugs, and the question, one of the questions that 393 00:19:26,236 --> 00:19:29,436 Speaker 1: comes up is are you using the something like this 394 00:19:30,676 --> 00:19:34,796 Speaker 1: a wearable to market the drug? But I'm wondering whether 395 00:19:34,836 --> 00:19:39,476 Speaker 1: that's there's another way to frame that is. Surely one 396 00:19:39,716 --> 00:19:43,356 Speaker 1: logical step here is that you start to you're not 397 00:19:43,476 --> 00:19:45,556 Speaker 1: just giving someone a drug or giving someone a drug 398 00:19:45,596 --> 00:19:48,916 Speaker 1: in combination with a set of wearables that allow us 399 00:19:48,956 --> 00:19:54,356 Speaker 1: to maximize the value of the therapeutic. Right, is that 400 00:19:54,396 --> 00:19:56,156 Speaker 1: what we're are we gonna be? Are we gonna be? 401 00:19:56,196 --> 00:19:58,716 Speaker 1: Are you gonna be getting from your pharmacist or your 402 00:19:58,716 --> 00:20:01,236 Speaker 1: doctor a package of things to take home along with 403 00:20:01,276 --> 00:20:01,836 Speaker 1: your medication? 404 00:20:01,956 --> 00:20:03,996 Speaker 2: We do that with some of our clinical trials, you'll 405 00:20:04,036 --> 00:20:06,316 Speaker 2: get like, here are the devices to take with you. 406 00:20:06,716 --> 00:20:09,516 Speaker 2: But if you look at weight loss medications, we've we're 407 00:20:09,556 --> 00:20:12,876 Speaker 2: already all doing that right now, like because we all 408 00:20:12,916 --> 00:20:15,756 Speaker 2: have scales in our house, right and so and so. 409 00:20:15,916 --> 00:20:18,356 Speaker 2: I think that is a great example of like, if 410 00:20:18,356 --> 00:20:21,996 Speaker 2: you give feedback to the person taking the medicine, they're 411 00:20:22,036 --> 00:20:24,196 Speaker 2: going to be more likely to stay on. At least 412 00:20:24,196 --> 00:20:26,036 Speaker 2: that's one of my hypotheses. I think that if you 413 00:20:26,036 --> 00:20:27,956 Speaker 2: took away if you took away scales and you took 414 00:20:27,956 --> 00:20:30,036 Speaker 2: away mirrors, I think a lot of people, a lot 415 00:20:30,076 --> 00:20:32,756 Speaker 2: more people would drop off the product weight management medicines 416 00:20:33,076 --> 00:20:35,716 Speaker 2: early on. But the fact is, when you get on 417 00:20:35,756 --> 00:20:37,396 Speaker 2: the scale and you can see, hey, I lost you know, 418 00:20:37,476 --> 00:20:39,596 Speaker 2: I lost some weight, you want to stay on it. 419 00:20:39,676 --> 00:20:42,276 Speaker 2: We don't have anything like that for staffins or anything else, right, 420 00:20:42,316 --> 00:20:44,756 Speaker 2: And that's again like why people people drop off. Just 421 00:20:44,796 --> 00:20:47,796 Speaker 2: imagine if you could just see, oh, hey, actually you know, 422 00:20:47,876 --> 00:20:50,316 Speaker 2: or I'm taking cholesterol medication and you know what, Hey 423 00:20:50,356 --> 00:20:53,956 Speaker 2: my cholesterol went down versus yesterday, not versus three months ago. 424 00:20:54,276 --> 00:20:58,996 Speaker 1: Yeah, who controls this data? So interesting? You began this 425 00:20:59,036 --> 00:21:04,516 Speaker 1: conversation in talking about the multitude of steps that exists 426 00:21:04,556 --> 00:21:08,516 Speaker 1: between the manufacture of some of these medicines and the user. 427 00:21:08,716 --> 00:21:12,556 Speaker 1: That's right. Now, you're talking about a system where presumably 428 00:21:12,956 --> 00:21:16,316 Speaker 1: the manufacturer can speak directly to the patient. Correct. Does 429 00:21:16,356 --> 00:21:18,076 Speaker 1: this mean that you cut out some of the middlemen? 430 00:21:18,476 --> 00:21:23,036 Speaker 2: That's my hope. But the data, ultimately the first part 431 00:21:23,076 --> 00:21:25,356 Speaker 2: of your question. The data really should be with the patient. 432 00:21:25,596 --> 00:21:28,716 Speaker 2: And I think there's a tendency to say, even still 433 00:21:28,756 --> 00:21:30,716 Speaker 2: today in this industry, that the data is really for 434 00:21:30,796 --> 00:21:34,436 Speaker 2: the healthcare provider, and I think that's I think that's 435 00:21:34,436 --> 00:21:36,716 Speaker 2: a mistake. I think ultimately the data is for the patient, 436 00:21:37,196 --> 00:21:39,796 Speaker 2: and the patient can choose to share what the healthcare provider, 437 00:21:39,836 --> 00:21:41,116 Speaker 2: and the healthcare provider. 438 00:21:40,756 --> 00:21:41,676 Speaker 1: Can look at it. 439 00:21:41,716 --> 00:21:43,316 Speaker 2: But it really is it's really what the abot. 440 00:21:43,396 --> 00:21:48,116 Speaker 1: So my mom is an interesting home has archives, yeah, 441 00:21:48,516 --> 00:21:52,236 Speaker 1: which acts up on and so she moves around a lot. 442 00:21:52,276 --> 00:21:57,236 Speaker 1: This is a perfect tool for her. So somebody is 443 00:21:57,276 --> 00:22:01,116 Speaker 1: so does she is the model here that she checks 444 00:22:01,116 --> 00:22:03,356 Speaker 1: her movements scores and that's a way of and she 445 00:22:03,436 --> 00:22:06,556 Speaker 1: can choose, she can see, oh this is time to 446 00:22:06,596 --> 00:22:09,796 Speaker 1: share that my data with a practitioner. Isn't it more 447 00:22:09,836 --> 00:22:13,036 Speaker 1: efficient for her to have someone who is or same 448 00:22:13,476 --> 00:22:16,236 Speaker 1: AI or something that's continuously monitoring her. 449 00:22:16,916 --> 00:22:20,396 Speaker 2: I think the continuous measurement part is you're you're absolutely 450 00:22:20,396 --> 00:22:22,156 Speaker 2: correct about it, but I think it needs to be 451 00:22:22,276 --> 00:22:23,876 Speaker 2: I think she always needs to be able to see 452 00:22:23,916 --> 00:22:24,836 Speaker 2: the data herself. 453 00:22:24,996 --> 00:22:26,076 Speaker 1: Yes, and see that. 454 00:22:26,156 --> 00:22:28,316 Speaker 2: And by the way, that's not an that sounds That's 455 00:22:28,356 --> 00:22:30,396 Speaker 2: one of the things that sounds obvious if you're coming 456 00:22:30,436 --> 00:22:32,956 Speaker 2: from outside the industry to inside. But inside the industry 457 00:22:33,156 --> 00:22:35,756 Speaker 2: is you know, it's like, wait, why would you share 458 00:22:35,756 --> 00:22:38,236 Speaker 2: the data with the patients themselves? You want to you know, 459 00:22:38,316 --> 00:22:40,516 Speaker 2: that's something that the healthcare provider should see first. I mean, 460 00:22:40,916 --> 00:22:43,996 Speaker 2: what happens if your mom misinterprets the data without the 461 00:22:44,036 --> 00:22:45,236 Speaker 2: advice of a healthcare provider. 462 00:22:45,276 --> 00:22:46,436 Speaker 1: That's kind of the big. 463 00:22:46,276 --> 00:22:50,196 Speaker 2: Caution that would keep keep the industry from from saying 464 00:22:50,236 --> 00:22:51,956 Speaker 2: your mom should be able to see that data yourself. 465 00:22:52,036 --> 00:22:53,836 Speaker 2: But I take a very different view on that. 466 00:22:54,316 --> 00:22:56,636 Speaker 1: But we're moving. What's interesting, you know a lot of 467 00:22:56,676 --> 00:22:58,876 Speaker 1: these things. The implication a lot of what you're talking 468 00:22:58,916 --> 00:23:04,556 Speaker 1: about is we are moving the uh, the primary point 469 00:23:04,596 --> 00:23:08,516 Speaker 1: of contact from the hospital of the doctor's office to 470 00:23:08,516 --> 00:23:08,836 Speaker 1: the home. 471 00:23:09,916 --> 00:23:13,516 Speaker 2: Right that's if you don't moment going on a tangent 472 00:23:13,516 --> 00:23:14,916 Speaker 2: on that too. That's one of the reasons why I'm 473 00:23:15,036 --> 00:23:18,516 Speaker 2: really really excited about like how we can change things too, 474 00:23:18,596 --> 00:23:21,076 Speaker 2: because if you look at it today, it's there are 475 00:23:21,116 --> 00:23:24,396 Speaker 2: so many barriers to getting medicine, you know, Like first 476 00:23:24,396 --> 00:23:26,236 Speaker 2: you have to get a doctor's appointment, which we've all 477 00:23:26,276 --> 00:23:30,036 Speaker 2: suffered through, like it can take months to get one. 478 00:23:30,796 --> 00:23:33,436 Speaker 2: Then even after you have one, then you also have 479 00:23:33,476 --> 00:23:35,836 Speaker 2: to be able to get it actually get access to 480 00:23:35,876 --> 00:23:39,556 Speaker 2: the medicine, which is a big problem because I don't 481 00:23:39,556 --> 00:23:42,396 Speaker 2: know if you've heard these stats before, about forty five 482 00:23:42,396 --> 00:23:46,476 Speaker 2: million Americans live in pharmacy deserts. Forty six percent of 483 00:23:46,476 --> 00:23:49,476 Speaker 2: the counties in the country are in pharmacy deserts, where 484 00:23:49,476 --> 00:23:54,236 Speaker 2: there's no pharmacy within fifteen minutes of your house. And 485 00:23:54,316 --> 00:23:57,636 Speaker 2: so I think and so if you add all that together, 486 00:23:57,676 --> 00:23:59,596 Speaker 2: it can take months from like the moment you say, 487 00:23:59,636 --> 00:24:02,236 Speaker 2: you know what, I'm not feeling well or there's something 488 00:24:02,276 --> 00:24:03,596 Speaker 2: I want to change in my life to like the 489 00:24:03,676 --> 00:24:05,916 Speaker 2: day that you get the medicine. I want to bring 490 00:24:05,956 --> 00:24:08,356 Speaker 2: that like down to like the same day. You should 491 00:24:08,356 --> 00:24:11,036 Speaker 2: be able to say, you know what, today's the day 492 00:24:11,076 --> 00:24:13,036 Speaker 2: that I want to do something, and you should be 493 00:24:13,036 --> 00:24:15,676 Speaker 2: able to go in, you know, get get a telehealth 494 00:24:15,676 --> 00:24:19,996 Speaker 2: appointment and if a medicine is appropriate, get it shipped, 495 00:24:20,316 --> 00:24:22,836 Speaker 2: and get it a ride delivered. You know this the 496 00:24:23,236 --> 00:24:24,036 Speaker 2: exact same day. 497 00:24:24,156 --> 00:24:28,676 Speaker 1: Well, one last question for you, define what success looks 498 00:24:28,716 --> 00:24:30,476 Speaker 1: like for you. So you're how old are you? 499 00:24:31,276 --> 00:24:33,196 Speaker 2: I just turned fifty. 500 00:24:33,236 --> 00:24:33,996 Speaker 1: You're a young man. 501 00:24:34,996 --> 00:24:36,156 Speaker 2: I can't take care of that very often. 502 00:24:36,236 --> 00:24:39,996 Speaker 1: So you let's assume you retire from Lily at sixty five, okay, 503 00:24:40,356 --> 00:24:42,796 Speaker 1: and I so take me fifteen years into the future 504 00:24:43,116 --> 00:24:46,116 Speaker 1: and tell me what would have to happen for you 505 00:24:46,156 --> 00:24:49,716 Speaker 1: to feel like your time at Lily has been a success. 506 00:24:52,236 --> 00:24:55,316 Speaker 2: The biggest thing for me are going to is going 507 00:24:55,396 --> 00:24:58,996 Speaker 2: to be the consumer side and actually making really cracking 508 00:24:59,036 --> 00:25:00,836 Speaker 2: this and being able to like get that vision of 509 00:25:00,956 --> 00:25:04,356 Speaker 2: people saying I want to take a medicine and I'm 510 00:25:04,396 --> 00:25:06,836 Speaker 2: going to get it the same day, and then I've 511 00:25:06,836 --> 00:25:10,516 Speaker 2: got the tools to stay engaged with forever. Like that 512 00:25:10,556 --> 00:25:14,196 Speaker 2: would be. That's millions and millions of lives touched by 513 00:25:14,236 --> 00:25:17,116 Speaker 2: just getting medicine and staying on this. And that's one side. 514 00:25:17,556 --> 00:25:21,036 Speaker 2: The other side where I uh, where I would love 515 00:25:21,156 --> 00:25:25,716 Speaker 2: to make a mark is on the discovery side and 516 00:25:25,836 --> 00:25:30,036 Speaker 2: discovering new medicines with particular with AI. Can talk for 517 00:25:30,156 --> 00:25:33,436 Speaker 2: hours on that, but I think we're going to see 518 00:25:33,556 --> 00:25:36,996 Speaker 2: medicines no human could have ever imagined coming out over 519 00:25:37,036 --> 00:25:39,836 Speaker 2: the next decade. Because it takes ten years or more 520 00:25:39,916 --> 00:25:43,956 Speaker 2: to develop a medicine, it would take about fifteen years 521 00:25:44,156 --> 00:25:44,556 Speaker 2: for that. 522 00:25:44,476 --> 00:25:46,636 Speaker 1: To come to life. Yeah, I was thinking, you know 523 00:25:46,676 --> 00:25:48,676 Speaker 1: when you were talking in this is maybe a little 524 00:25:48,716 --> 00:25:52,556 Speaker 1: bit far fetched, but in the world of deterrence. So 525 00:25:52,596 --> 00:25:56,876 Speaker 1: the question is, if I have a law that punishes 526 00:25:56,916 --> 00:25:59,756 Speaker 1: you for a certain crime, you're The deterrent value of 527 00:25:59,756 --> 00:26:02,516 Speaker 1: that law is a function of three things, the certainty 528 00:26:02,516 --> 00:26:06,756 Speaker 1: of punishment, the swiftness of punishment, and the severity of 529 00:26:06,796 --> 00:26:10,556 Speaker 1: punish And of the three, we spend the most time 530 00:26:10,596 --> 00:26:16,916 Speaker 1: thinking about severity, secondly thinking about certainty, and the one 531 00:26:16,916 --> 00:26:19,516 Speaker 1: that we neglect is swiftness. Right, it takes years in 532 00:26:19,596 --> 00:26:21,956 Speaker 1: using us. And the argument that many people make is 533 00:26:21,996 --> 00:26:25,636 Speaker 1: that swiftness is actually the most potent of the three. 534 00:26:25,676 --> 00:26:28,236 Speaker 1: If you know you're getting punished the next day, then 535 00:26:28,276 --> 00:26:30,716 Speaker 1: you're now. It's funny because if you map that onto 536 00:26:30,716 --> 00:26:33,076 Speaker 1: what you're talking about. You were talking about the idea 537 00:26:33,076 --> 00:26:35,956 Speaker 1: of getting medicine the same day. What you're saying is 538 00:26:35,956 --> 00:26:39,716 Speaker 1: the swiftness variable is the neglected one here. And what 539 00:26:39,836 --> 00:26:43,076 Speaker 1: if if we improve swiftness, do you think we would 540 00:26:43,116 --> 00:26:47,076 Speaker 1: change the psychological circumstances around which people use drugs? In 541 00:26:47,116 --> 00:26:51,076 Speaker 1: other words, would the adherence problem be solved if we 542 00:26:51,116 --> 00:26:52,756 Speaker 1: address the swiftness problem? 543 00:26:53,756 --> 00:26:54,636 Speaker 2: I think so. 544 00:26:54,996 --> 00:26:55,396 Speaker 1: Actually. 545 00:26:55,476 --> 00:26:57,356 Speaker 2: I think if we got swiftness and you could actually 546 00:26:57,396 --> 00:27:00,236 Speaker 2: see an effect and know that something was happening, that 547 00:27:00,316 --> 00:27:03,836 Speaker 2: would change things. You know. And and by the way, 548 00:27:03,836 --> 00:27:05,756 Speaker 2: I love that model that you that you just mentioned. 549 00:27:06,436 --> 00:27:08,956 Speaker 2: In the technology world, we have things break all the 550 00:27:08,996 --> 00:27:11,516 Speaker 2: day time, and what everybody focuses on is like what's 551 00:27:11,556 --> 00:27:13,796 Speaker 2: the root cause, and like what's the severity and how 552 00:27:14,036 --> 00:27:16,316 Speaker 2: you know, how wifely is it? The thing that nobody 553 00:27:16,316 --> 00:27:18,396 Speaker 2: ever focuses on, which is where I try to get 554 00:27:18,396 --> 00:27:21,996 Speaker 2: teams to focused on, is swiftness the mitigation time to mitigate. 555 00:27:22,036 --> 00:27:23,876 Speaker 2: How long did it take you to mitigate that human 556 00:27:23,956 --> 00:27:26,236 Speaker 2: process of like how quickly did you take the feedback 557 00:27:26,236 --> 00:27:29,276 Speaker 2: and adapt? That's really you can. You can have all 558 00:27:29,356 --> 00:27:31,996 Speaker 2: kinds of risks as long as you've got as long 559 00:27:32,036 --> 00:27:34,996 Speaker 2: as it's reversible and you can switch. Uh, that's great. 560 00:27:35,156 --> 00:27:37,556 Speaker 2: So when it comes to medicines. If you can try 561 00:27:37,556 --> 00:27:39,836 Speaker 2: it and get feedback that it's not working or not 562 00:27:39,876 --> 00:27:42,556 Speaker 2: training in the right direction and change it, that would 563 00:27:42,596 --> 00:27:46,196 Speaker 2: be that that would be amazing, and I think you 564 00:27:46,236 --> 00:27:48,876 Speaker 2: would find that people would people would say, Hey, now 565 00:27:48,956 --> 00:27:51,196 Speaker 2: I know that you know this medicine I tried wasn't working. 566 00:27:51,196 --> 00:27:53,116 Speaker 2: I'm going trying a new one today. I can see progress. 567 00:27:53,156 --> 00:27:54,916 Speaker 2: I'm gonna I'm going to stay on it because i 568 00:27:54,916 --> 00:27:56,276 Speaker 2: know it's doing something well. 569 00:27:56,276 --> 00:27:59,676 Speaker 1: This has been really fascinating. Best of luck with all 570 00:27:59,716 --> 00:28:02,356 Speaker 1: the work you're doing. I hope next time I see you, 571 00:28:02,396 --> 00:28:05,916 Speaker 1: I will be have at least three wearables all. 572 00:28:06,396 --> 00:28:06,996 Speaker 2: Thank you, Malchael. 573 00:28:07,076 --> 00:28:12,436 Speaker 1: Yeah. Religionous History is produced by Lucy Sullivan with Nina 574 00:28:12,476 --> 00:28:15,916 Speaker 1: Bird Lawrence and ben Adaph Haffrey. Our editor is Karen 575 00:28:15,956 --> 00:28:20,636 Speaker 1: Schakerji mastering by Jake Korsky. Our executive producer is Jacob Smith. 576 00:28:20,956 --> 00:28:25,636 Speaker 1: Special thanks to Mount Romano, Eric Sandler and Kira Posey. 577 00:28:26,116 --> 00:28:27,756 Speaker 1: I'm Malcolm Gladwell.