1 00:00:02,840 --> 00:00:05,920 Speaker 1: Vos Narasimon is the CEO of Novartist, a major Swiss 2 00:00:05,960 --> 00:00:09,080 Speaker 1: based pharmaceutical company. Born in the United States the Indian 3 00:00:09,119 --> 00:00:11,960 Speaker 1: immigrant parents, he was educated at Harvard Medical School, but 4 00:00:12,080 --> 00:00:14,840 Speaker 1: chose not to practice medicine. Instead, he chose to go 5 00:00:14,880 --> 00:00:18,000 Speaker 1: into the pharmaceutical industry and is now leading the transformation 6 00:00:18,040 --> 00:00:21,160 Speaker 1: of Novartists to one of the most important pharmaceutical companies 7 00:00:21,160 --> 00:00:23,040 Speaker 1: in the world. Had a chance to sit down with 8 00:00:23,160 --> 00:00:25,960 Speaker 1: Vos in New York recently to talk about this transformation. 9 00:00:26,520 --> 00:00:29,120 Speaker 1: So many people know the names of the drugs that 10 00:00:29,160 --> 00:00:31,600 Speaker 1: they use, but they don't know the names of the 11 00:00:31,680 --> 00:00:35,400 Speaker 1: drug companies or pharmaceutical companies that produce them. So for 12 00:00:35,479 --> 00:00:38,159 Speaker 1: people who may not know much about Nevardists, tell us 13 00:00:38,200 --> 00:00:41,760 Speaker 1: what drugs or pharmaceutical products as are produced that people 14 00:00:41,800 --> 00:00:42,360 Speaker 1: would have heard of. 15 00:00:42,800 --> 00:00:44,720 Speaker 2: There's a couple of major drugs we have right now, 16 00:00:44,760 --> 00:00:48,000 Speaker 2: and Trusto is a medicine for heart failure. Another drug 17 00:00:48,080 --> 00:00:51,600 Speaker 2: Couthentics for a whole range of immunology indications. We have 18 00:00:51,600 --> 00:00:54,440 Speaker 2: a drug called Kiskali for breast cancer. As you know, 19 00:00:54,560 --> 00:00:57,160 Speaker 2: these names are not always tying to what the drugs 20 00:00:57,200 --> 00:01:00,520 Speaker 2: actually do. But yeah, we have a pretty broad portfolio 21 00:01:00,560 --> 00:01:03,640 Speaker 2: of medicines over fifteen medicines, over a billion dollars of sales. 22 00:01:03,720 --> 00:01:06,160 Speaker 1: By the way, speaking of their brand names, who comes 23 00:01:06,240 --> 00:01:08,440 Speaker 1: up with these brand names? Because they there are names 24 00:01:08,440 --> 00:01:10,640 Speaker 1: that I can't pronounce. Sometimes you don't know what they mean. 25 00:01:10,800 --> 00:01:11,920 Speaker 1: Do you have a team of people. 26 00:01:11,680 --> 00:01:12,160 Speaker 3: That came up. 27 00:01:12,200 --> 00:01:13,200 Speaker 4: It's a whole industry. 28 00:01:13,319 --> 00:01:15,800 Speaker 2: Maybe private equity even interested to get into it, but 29 00:01:15,840 --> 00:01:19,600 Speaker 2: there's a whole industry of people who basically try to 30 00:01:19,640 --> 00:01:24,520 Speaker 2: find word permutations that might tie to the drug, and 31 00:01:24,560 --> 00:01:26,520 Speaker 2: then you have to send it to the regulators and 32 00:01:26,560 --> 00:01:28,520 Speaker 2: they have to be sure that this word will not 33 00:01:28,600 --> 00:01:31,920 Speaker 2: be confused in any number of different languages for some 34 00:01:32,080 --> 00:01:33,440 Speaker 2: other medicine or something else. 35 00:01:33,560 --> 00:01:37,440 Speaker 1: People who don't follow this industry carefully may not recognize it. 36 00:01:37,480 --> 00:01:39,679 Speaker 1: But the way the industry works, as I understand it 37 00:01:39,720 --> 00:01:44,480 Speaker 1: is that large pharmaceutical companies either develop internally or through 38 00:01:44,600 --> 00:01:49,000 Speaker 1: an acquisition a drug or pharmaceutical product that they can sell, 39 00:01:49,320 --> 00:01:52,960 Speaker 1: and it's patented, and the patents last for seventeen years, 40 00:01:53,000 --> 00:01:56,840 Speaker 1: seventeen years, seventeen years, and after seventeen years it becomes 41 00:01:56,920 --> 00:01:59,720 Speaker 1: what's known as a generic, which means that it's not patent. 42 00:02:00,040 --> 00:02:03,040 Speaker 1: Can get it for presumably a lower price. So is 43 00:02:03,080 --> 00:02:05,360 Speaker 1: that a good way to make a business? You have 44 00:02:05,440 --> 00:02:08,880 Speaker 1: you build products in seventeen years they're kind of gone. 45 00:02:08,960 --> 00:02:10,960 Speaker 2: It's a tough way to make a business, for sure. 46 00:02:11,200 --> 00:02:13,120 Speaker 2: It means you're on a constant treadmill and you have 47 00:02:13,200 --> 00:02:16,600 Speaker 2: to constantly have the innovation capacity to have what we 48 00:02:16,639 --> 00:02:19,480 Speaker 2: call replacement power. You have to replace your sales with 49 00:02:19,560 --> 00:02:22,600 Speaker 2: the next medicines, the next innovation. So the only winners 50 00:02:22,639 --> 00:02:25,160 Speaker 2: in the long run are companies that have the R 51 00:02:25,200 --> 00:02:28,480 Speaker 2: and D firepower, R and D capacity to keep inventing 52 00:02:28,520 --> 00:02:32,359 Speaker 2: medicines to rejuvenate almost their entire portfolio. So you think 53 00:02:32,400 --> 00:02:34,480 Speaker 2: of a company like US forty five billion dollars in 54 00:02:34,560 --> 00:02:37,880 Speaker 2: sales every year. We can have anywhere from two to 55 00:02:37,960 --> 00:02:40,840 Speaker 2: eight billion dollars plus going off patent, and we have 56 00:02:40,880 --> 00:02:45,080 Speaker 2: to generate enough sales to replace that and grow on top. 57 00:02:45,520 --> 00:02:47,600 Speaker 2: And that's why you have a relatively limited number of 58 00:02:47,760 --> 00:02:49,359 Speaker 2: very large by pharma companies. 59 00:02:49,400 --> 00:02:52,560 Speaker 1: When somebody develops a drug or pharmaceutical product in a 60 00:02:52,600 --> 00:02:54,320 Speaker 1: company like you, do you have a big lab. I 61 00:02:54,320 --> 00:02:56,160 Speaker 1: assume is it all over the world or you have 62 00:02:56,200 --> 00:02:56,920 Speaker 1: it in Switzerland. 63 00:02:57,240 --> 00:02:59,600 Speaker 2: We invest about nine and a half billion dollars a 64 00:02:59,720 --> 00:03:03,800 Speaker 2: year in our and DA research headquarters are in Cambridge, Massachusetts, 65 00:03:03,800 --> 00:03:04,680 Speaker 2: and bossles it so on. 66 00:03:05,080 --> 00:03:07,400 Speaker 3: So when you get the product and what do you do? 67 00:03:07,440 --> 00:03:10,160 Speaker 1: You test it first on animals, and then you test 68 00:03:10,200 --> 00:03:12,639 Speaker 1: it on small subset of humans and then a large 69 00:03:12,680 --> 00:03:13,480 Speaker 1: subset of humans. 70 00:03:13,520 --> 00:03:14,200 Speaker 3: Is that how it works? 71 00:03:14,400 --> 00:03:16,359 Speaker 2: Roughly, that's how it works, and it's a long journey. 72 00:03:16,440 --> 00:03:18,080 Speaker 2: First thing we have to do is we have to 73 00:03:18,120 --> 00:03:20,600 Speaker 2: discover or find what we call a target in the 74 00:03:20,680 --> 00:03:23,000 Speaker 2: human body that we want a drug. We think this 75 00:03:23,160 --> 00:03:25,840 Speaker 2: target has some ability to impact human health and. 76 00:03:25,760 --> 00:03:27,000 Speaker 4: A disease we're interested in. 77 00:03:27,320 --> 00:03:30,040 Speaker 2: Then we have to design a drug to either inhibit 78 00:03:30,600 --> 00:03:34,000 Speaker 2: or promote that target, and that takes some time. AI 79 00:03:34,120 --> 00:03:36,480 Speaker 2: might help us do that faster, we'll see. And then 80 00:03:36,480 --> 00:03:39,560 Speaker 2: once we have that target drug optimized, we take it 81 00:03:39,560 --> 00:03:43,080 Speaker 2: into animals, make sure it doesn't cause any preclinical safety signals, 82 00:03:43,320 --> 00:03:46,080 Speaker 2: and then we finally move into humans. And from the 83 00:03:46,160 --> 00:03:48,080 Speaker 2: time we move into humans to when we get it 84 00:03:48,200 --> 00:03:50,680 Speaker 2: to people, it's usually around nine years. 85 00:03:51,080 --> 00:03:54,280 Speaker 1: Last year twenty twenty three, we saw an enormous increase 86 00:03:54,400 --> 00:03:57,280 Speaker 1: in drugs being taken that reduce your weight, and they 87 00:03:57,280 --> 00:03:59,400 Speaker 1: seem to work quite well. There are two drug companies 88 00:04:00,040 --> 00:04:02,760 Speaker 1: United States and one in Europe that seem to dominate 89 00:04:02,800 --> 00:04:03,360 Speaker 1: that business. 90 00:04:03,720 --> 00:04:05,680 Speaker 3: Are you going to get into that business? And why not? 91 00:04:05,760 --> 00:04:07,440 Speaker 3: It seems to be extremely profitable. 92 00:04:07,760 --> 00:04:09,160 Speaker 4: It is a business we're interested in. 93 00:04:09,240 --> 00:04:11,760 Speaker 2: We're working on really the next wave of medicines because 94 00:04:11,760 --> 00:04:14,760 Speaker 2: I think these GLP one medicines that you're talking about 95 00:04:14,960 --> 00:04:17,719 Speaker 2: are very well serviced by the current companies. It's a 96 00:04:17,720 --> 00:04:21,799 Speaker 2: fascinating story goes back actually to the early nineteen nineties. 97 00:04:21,800 --> 00:04:23,960 Speaker 2: It took us almost twenty five years to realize the 98 00:04:24,000 --> 00:04:27,280 Speaker 2: potent effect that these types of drugs would have on obesity. 99 00:04:27,480 --> 00:04:30,200 Speaker 2: But we think there's opportunity to improve on them, and 100 00:04:30,240 --> 00:04:33,040 Speaker 2: we hope it'll be It's very early stage within nov Artists, 101 00:04:33,040 --> 00:04:35,360 Speaker 2: but can we come up with drugs that better preserve muscle, 102 00:04:35,760 --> 00:04:39,000 Speaker 2: are maybe easier to take and more infrequently taken. One 103 00:04:39,040 --> 00:04:42,200 Speaker 2: area of where Novartis is one of the leaders is 104 00:04:42,279 --> 00:04:45,000 Speaker 2: in what are called small interfering RNA therapies. 105 00:04:45,080 --> 00:04:46,840 Speaker 4: It sounds like a fancy. 106 00:04:46,480 --> 00:04:48,719 Speaker 2: Word, but really what it allows you to do is 107 00:04:48,839 --> 00:04:51,440 Speaker 2: take drugs that you normally would take every single day 108 00:04:51,760 --> 00:04:53,559 Speaker 2: and make them drugs you only have to take twice 109 00:04:53,600 --> 00:04:56,239 Speaker 2: a year. So in cholesterol lowering, we have a medicine 110 00:04:56,240 --> 00:04:57,880 Speaker 2: that you only have to take twice a year to 111 00:04:58,160 --> 00:05:02,479 Speaker 2: lower cholesterol sixty percent. We're working on similar medicines for hypertensions, 112 00:05:02,520 --> 00:05:06,520 Speaker 2: high blood pressure, other risk factors for cardiovascular disease. And 113 00:05:06,560 --> 00:05:09,279 Speaker 2: the idea is can you get to very infrequently dosed 114 00:05:09,320 --> 00:05:12,200 Speaker 2: medicines because most people don't stay on the drugs. 115 00:05:12,080 --> 00:05:14,520 Speaker 1: As I get older, the drug that I'm most interested 116 00:05:14,839 --> 00:05:18,240 Speaker 1: in is one that deals with Alzheimer's or dementia, because 117 00:05:18,240 --> 00:05:21,440 Speaker 1: I'm always wondering am I going to be getting this disease? 118 00:05:21,920 --> 00:05:23,480 Speaker 3: What are you doing in that area? 119 00:05:23,600 --> 00:05:26,240 Speaker 2: So we're active and I think what we're really interested 120 00:05:26,279 --> 00:05:28,760 Speaker 2: in is again the next wave of what might be 121 00:05:28,839 --> 00:05:32,560 Speaker 2: effective therapies for Alzheimer's disease. Today there are two one 122 00:05:32,640 --> 00:05:35,760 Speaker 2: drug license, another drug coming targeting the plaques in the 123 00:05:35,760 --> 00:05:38,119 Speaker 2: brain anti amyloid that drugs as they are called. 124 00:05:38,279 --> 00:05:40,159 Speaker 4: But we think the next generation. 125 00:05:39,839 --> 00:05:42,400 Speaker 2: Opportunities are going to be to target other elements that 126 00:05:42,480 --> 00:05:45,440 Speaker 2: accumulate in the brain. One is called TAO. There are 127 00:05:45,480 --> 00:05:48,200 Speaker 2: other targets as well. But I would say Alzheimer's is 128 00:05:48,240 --> 00:05:49,840 Speaker 2: a really tough space. I mean, one of the things 129 00:05:49,880 --> 00:05:52,599 Speaker 2: that's very hard is you need to intervene very early 130 00:05:52,960 --> 00:05:57,600 Speaker 2: because it's a very slowly progressing disease, and identifying which 131 00:05:57,600 --> 00:06:00,159 Speaker 2: patients to intervene on and then figuring out what to 132 00:06:00,200 --> 00:06:03,120 Speaker 2: treat them the patients with is really really difficult. 133 00:06:03,279 --> 00:06:06,159 Speaker 1: On cancer related drugs, there are some cancer related drugs, 134 00:06:06,160 --> 00:06:08,000 Speaker 1: and I guess you have some as well, but. 135 00:06:08,000 --> 00:06:09,760 Speaker 3: They tend to deal with cancer. 136 00:06:09,800 --> 00:06:12,960 Speaker 1: Once you have cancer, they try to ameliorate the side 137 00:06:12,960 --> 00:06:15,000 Speaker 1: effects of it or the effects of it. What about 138 00:06:15,040 --> 00:06:18,000 Speaker 1: something that prevents cancer? Is that realistic in my lifetime? 139 00:06:18,240 --> 00:06:20,719 Speaker 2: That is something that's a heavy interest of the field, 140 00:06:20,800 --> 00:06:23,279 Speaker 2: and also at our company, we actually just got great 141 00:06:23,320 --> 00:06:25,839 Speaker 2: data on a breast cancer drug which can be given 142 00:06:25,880 --> 00:06:28,600 Speaker 2: to women who have had their breast cancer but resected, 143 00:06:28,600 --> 00:06:31,320 Speaker 2: but then to prevent it recurring. Now where there's a 144 00:06:31,320 --> 00:06:34,280 Speaker 2: lot of interest right now is can you identify things 145 00:06:34,279 --> 00:06:37,080 Speaker 2: in the blood and things are circulating so circulating tumor 146 00:06:37,160 --> 00:06:40,000 Speaker 2: DNA that would show that the cancer is starting to 147 00:06:40,400 --> 00:06:42,440 Speaker 2: happen in the body, but well before it would be 148 00:06:42,480 --> 00:06:45,520 Speaker 2: detectable in any kind of scan. If we can get 149 00:06:45,520 --> 00:06:48,200 Speaker 2: those tests up to an adequate level of precision and 150 00:06:48,240 --> 00:06:51,279 Speaker 2: start to treat patients well before the cancer shows up, 151 00:06:51,560 --> 00:06:53,839 Speaker 2: that would be the big opportunity, but that's still some 152 00:06:53,920 --> 00:06:54,440 Speaker 2: time away. 153 00:06:54,520 --> 00:06:57,720 Speaker 1: So you produce medicines that presumably help people with their 154 00:06:57,760 --> 00:07:00,279 Speaker 1: lives the better and live longer and so forth. Why 155 00:07:00,279 --> 00:07:03,119 Speaker 1: aren't you a more popular industry? You know, the private 156 00:07:03,120 --> 00:07:05,880 Speaker 1: equ industry has its attractors, have no doubt, but the 157 00:07:05,880 --> 00:07:08,760 Speaker 1: pharmaceutical industry is not right too far behind us. 158 00:07:08,880 --> 00:07:11,400 Speaker 3: Why do people not love you for the drugs you're producing. 159 00:07:11,680 --> 00:07:14,520 Speaker 2: Yeah, it's a long story in terms of the history 160 00:07:14,560 --> 00:07:16,040 Speaker 2: of this industry. Even if you go back to the 161 00:07:16,040 --> 00:07:18,960 Speaker 2: seventies or eighties, we were a much more popular sector. 162 00:07:19,040 --> 00:07:20,600 Speaker 2: I think one of the things that happened is as 163 00:07:20,600 --> 00:07:23,560 Speaker 2: we brought more and more medicines forward and patients got 164 00:07:23,600 --> 00:07:26,160 Speaker 2: on more and more therapies. The one thing we weren't 165 00:07:26,160 --> 00:07:29,640 Speaker 2: watching carefully enough as an industry was what was happening 166 00:07:29,640 --> 00:07:32,360 Speaker 2: at the pharmacy counter. There's a lot of focus in 167 00:07:32,440 --> 00:07:35,640 Speaker 2: congressional hearings and other places on list prices, but list 168 00:07:35,640 --> 00:07:38,240 Speaker 2: prices mean very little in the sector because you have 169 00:07:38,280 --> 00:07:41,720 Speaker 2: pharmacy benefit managers, you have retail pharmacies, you have wholesalers. 170 00:07:42,000 --> 00:07:44,160 Speaker 2: But what really matters is at the end of the day, 171 00:07:44,160 --> 00:07:46,520 Speaker 2: when somebody comes to the pharmacy counter. Can they afford 172 00:07:46,600 --> 00:07:49,520 Speaker 2: their medicines? And we're starting to address that. Some recent 173 00:07:49,600 --> 00:07:52,440 Speaker 2: legislation addresses that. We're thinking a lot about it. But 174 00:07:52,480 --> 00:07:54,200 Speaker 2: that's what we've got to figure out how to solve. 175 00:07:54,280 --> 00:07:57,720 Speaker 1: Let's talk about your background. So your parents came from where. 176 00:07:57,480 --> 00:07:59,920 Speaker 2: They came from Tumbil Nadu in southern India. 177 00:08:00,240 --> 00:08:01,880 Speaker 3: And when did they come to the United States. 178 00:08:02,000 --> 00:08:04,640 Speaker 4: They came in the late sixties and early seventies. 179 00:08:04,920 --> 00:08:06,120 Speaker 3: And were they educated? 180 00:08:07,040 --> 00:08:10,400 Speaker 2: They were they actually, you know, my father was alongside 181 00:08:10,400 --> 00:08:12,160 Speaker 2: his brothers were some of the first people in our 182 00:08:12,200 --> 00:08:15,240 Speaker 2: family to go to college in India. Father did his 183 00:08:15,280 --> 00:08:18,240 Speaker 2: PhD in India. I was able to work his way 184 00:08:18,280 --> 00:08:19,679 Speaker 2: up and then it was one of the first people 185 00:08:19,680 --> 00:08:20,880 Speaker 2: to come to the United States. 186 00:08:21,200 --> 00:08:23,480 Speaker 4: My mother came to Carnegie Mellon. She did a. 187 00:08:23,440 --> 00:08:28,520 Speaker 2: Degree in nuclear and becoming a nuclear engineer. And yeah, 188 00:08:28,560 --> 00:08:30,520 Speaker 2: it was I think a pretty extraordinary story and that 189 00:08:30,600 --> 00:08:33,440 Speaker 2: they were able to come from relatively modest beginnings, so 190 00:08:33,559 --> 00:08:37,199 Speaker 2: beginning with my grandparents in relatively small places in India 191 00:08:37,280 --> 00:08:39,679 Speaker 2: and ultimately find a way to the United States. 192 00:08:39,800 --> 00:08:41,439 Speaker 3: So you grew up in the Pittsburgh area. 193 00:08:41,559 --> 00:08:43,120 Speaker 4: I grew up a Pittsburgh Steelers fan. 194 00:08:43,160 --> 00:08:45,280 Speaker 3: Indeed, And I assume you did well in high. 195 00:08:45,160 --> 00:08:46,880 Speaker 4: School, did well, did well? 196 00:08:47,000 --> 00:08:49,560 Speaker 3: So you went to univer Chicago, went to the University 197 00:08:49,600 --> 00:08:51,720 Speaker 3: of chicag And why did you go there as opposed 198 00:08:51,720 --> 00:08:52,600 Speaker 3: to other good schools. 199 00:08:52,920 --> 00:08:54,000 Speaker 4: Well, it's an interesting story. 200 00:08:54,040 --> 00:08:56,880 Speaker 2: I actually applied to all of the ivs and applied 201 00:08:56,920 --> 00:08:59,240 Speaker 2: to a number of schools, and I didn't get in anywhere. Actually, 202 00:08:59,280 --> 00:09:01,920 Speaker 2: the one school that I did admit me was a 203 00:09:02,160 --> 00:09:04,600 Speaker 2: University of Chicago, and it ended up being such an 204 00:09:04,640 --> 00:09:07,320 Speaker 2: incredible gift in the end, because the University of Chicago, 205 00:09:07,360 --> 00:09:10,800 Speaker 2: I would still credit, perhaps more than any other educational experience, 206 00:09:10,840 --> 00:09:13,280 Speaker 2: taught me how to think, how to synthesize, how to 207 00:09:13,280 --> 00:09:14,560 Speaker 2: be relentlessly curious. 208 00:09:14,679 --> 00:09:15,600 Speaker 4: It was really positive. 209 00:09:15,640 --> 00:09:18,680 Speaker 1: Okay, So Harvard recognized and gets a mistake from before, 210 00:09:18,760 --> 00:09:21,319 Speaker 1: admitted view to the medical school, right, they did. And 211 00:09:21,480 --> 00:09:23,480 Speaker 1: so you went to Harvard Medical School. I assume your 212 00:09:23,520 --> 00:09:25,559 Speaker 1: immigrant parents were saying, great, my son is going to 213 00:09:25,559 --> 00:09:28,160 Speaker 1: be a doctor. Yes, So when you told them you 214 00:09:28,200 --> 00:09:30,400 Speaker 1: weren't going to be a practicing doctor, what did they say? 215 00:09:30,520 --> 00:09:33,079 Speaker 2: They were very confused. They were very very confused. I 216 00:09:33,400 --> 00:09:35,040 Speaker 2: you know, I had this idea in my mind, I 217 00:09:35,120 --> 00:09:36,640 Speaker 2: did a lot of work in public health. I had 218 00:09:36,720 --> 00:09:39,839 Speaker 2: some great mentors at Harvard, and I really wanted to 219 00:09:39,920 --> 00:09:42,720 Speaker 2: see how could I have a bigger impact beyond an 220 00:09:42,880 --> 00:09:46,040 Speaker 2: individual patient care, and so I wanted to I first 221 00:09:46,080 --> 00:09:48,679 Speaker 2: went to the World Health Organization, then I went to McKinsey. 222 00:09:48,960 --> 00:09:51,079 Speaker 2: But all of this time, I certainly think my parents 223 00:09:51,160 --> 00:09:52,959 Speaker 2: were assuming I was going to go back and do 224 00:09:53,080 --> 00:09:56,560 Speaker 2: a residency and become a cardiologist and kind of finish 225 00:09:56,640 --> 00:09:59,320 Speaker 2: the journey, and it never actually worked out that well. 226 00:09:59,440 --> 00:10:02,120 Speaker 1: For a while, you were, I guess, a protege of 227 00:10:02,280 --> 00:10:06,120 Speaker 1: Paul Farmer, the famous doctor who was at Harvard for 228 00:10:06,160 --> 00:10:10,000 Speaker 1: a while, among other places. And you then did other 229 00:10:10,080 --> 00:10:12,800 Speaker 1: things to help people in India. You went back working 230 00:10:12,840 --> 00:10:14,040 Speaker 1: with street children in India. 231 00:10:14,280 --> 00:10:14,679 Speaker 4: That's right. 232 00:10:15,120 --> 00:10:17,720 Speaker 1: So did your parents say, you have a Harvard Medical 233 00:10:17,760 --> 00:10:21,040 Speaker 1: School degree and you're making no money in India is 234 00:10:21,080 --> 00:10:23,480 Speaker 1: a great country, but why don't you go practice medicine? 235 00:10:23,880 --> 00:10:26,680 Speaker 2: Say that my father would ask, I worked so hard 236 00:10:26,720 --> 00:10:28,920 Speaker 2: to get out of these places, why are you working 237 00:10:29,000 --> 00:10:30,800 Speaker 2: so hard to go back to them? Was certainly a 238 00:10:31,160 --> 00:10:34,480 Speaker 2: confusion he had in his mind. But overall my parents 239 00:10:34,559 --> 00:10:37,000 Speaker 2: were very supportive of this public health goal. 240 00:10:37,040 --> 00:10:40,360 Speaker 1: I had okay, So you ultimately came to McKenzie after 241 00:10:40,480 --> 00:10:43,720 Speaker 1: some public health work and why did you not stay 242 00:10:43,720 --> 00:10:44,320 Speaker 1: at McKenzie. 243 00:10:44,760 --> 00:10:47,360 Speaker 2: Yeah, McKenzie was a great training ground for a physician 244 00:10:47,400 --> 00:10:49,360 Speaker 2: who didn't know anything about a P and L, a 245 00:10:49,480 --> 00:10:52,040 Speaker 2: balance sheet, knew nothing about M and A or evaluation. 246 00:10:52,200 --> 00:10:54,680 Speaker 2: I learned a lot very quickly, but I just felt 247 00:10:54,679 --> 00:10:57,360 Speaker 2: like it was a little bit detached from the real action. 248 00:10:57,720 --> 00:11:00,560 Speaker 2: And I had an opportunity presented to me to join 249 00:11:00,640 --> 00:11:03,400 Speaker 2: Novartists Pharmaceuticals to really try to look at our R 250 00:11:03,480 --> 00:11:06,400 Speaker 2: and D strategy at Novartists at the time, and it 251 00:11:06,520 --> 00:11:08,559 Speaker 2: was a little bit of a whim sort of a 252 00:11:08,679 --> 00:11:10,839 Speaker 2: gamble to try to see how that would work out. 253 00:11:10,960 --> 00:11:12,880 Speaker 4: I would have never imagined it would have unfolded the 254 00:11:12,920 --> 00:11:14,640 Speaker 4: way it did, but it was really great. 255 00:11:14,720 --> 00:11:16,280 Speaker 1: So you work your way up and then at the 256 00:11:16,360 --> 00:11:19,559 Speaker 1: age of forty, somebody at Nevarda says, we have a 257 00:11:19,640 --> 00:11:23,760 Speaker 1: forty year old who didn't go to business school, is 258 00:11:23,880 --> 00:11:27,160 Speaker 1: not from Switzerland, and he's a medical doctor who's never 259 00:11:27,240 --> 00:11:28,040 Speaker 1: practiced medicine. 260 00:11:28,200 --> 00:11:31,920 Speaker 3: Let's make him the CEO. It's right, So were you're surprised? 261 00:11:32,120 --> 00:11:32,920 Speaker 4: I was shocked. 262 00:11:32,960 --> 00:11:35,000 Speaker 2: I was shocked when they first asked me that to 263 00:11:35,080 --> 00:11:36,480 Speaker 2: even be part of it. I mean I had been 264 00:11:36,520 --> 00:11:38,800 Speaker 2: a head of drug development. I had the opportunity to 265 00:11:38,880 --> 00:11:42,880 Speaker 2: do so many different roles at Novartists in developing vaccines. 266 00:11:42,880 --> 00:11:44,320 Speaker 4: I worked in our vaccines. 267 00:11:43,960 --> 00:11:47,080 Speaker 2: Division, leading a little bit of our generics unit, working 268 00:11:47,160 --> 00:11:49,880 Speaker 2: in drug development for many, many years. And I think 269 00:11:50,600 --> 00:11:52,599 Speaker 2: part of the reason they were interested is because I 270 00:11:52,679 --> 00:11:55,760 Speaker 2: had gotten a background in R and D. But I 271 00:11:55,840 --> 00:11:58,640 Speaker 2: think it was also not only my age, but also 272 00:11:58,720 --> 00:12:01,280 Speaker 2: the fact that I think no other major pharmaceutical company 273 00:12:01,360 --> 00:12:04,920 Speaker 2: had an R and D head, our development head as 274 00:12:04,960 --> 00:12:05,439 Speaker 2: their CEO. 275 00:12:05,720 --> 00:12:08,600 Speaker 1: Your strategy has been different than the strategy you inherited, 276 00:12:08,640 --> 00:12:11,040 Speaker 1: and the artist was in many different areas. They had 277 00:12:11,080 --> 00:12:14,280 Speaker 1: a generic drug business and you sold that. Yes, so 278 00:12:14,400 --> 00:12:15,880 Speaker 1: why did you get out of that business? It seems 279 00:12:15,880 --> 00:12:17,280 Speaker 1: to be a recently profitable business. 280 00:12:17,480 --> 00:12:17,640 Speaker 4: Yeah. 281 00:12:18,520 --> 00:12:21,079 Speaker 2: As you know, when we have these conglomerates, you have 282 00:12:21,160 --> 00:12:24,040 Speaker 2: to ask is there value in the conglomerate? Is their 283 00:12:24,120 --> 00:12:27,080 Speaker 2: value in building all these different businesses together? And then 284 00:12:27,120 --> 00:12:29,120 Speaker 2: the question is what are we really great at? And 285 00:12:29,200 --> 00:12:30,840 Speaker 2: when I came into the role as CEO, I looked 286 00:12:30,880 --> 00:12:33,319 Speaker 2: we were in consumer health, we were in I care devices, 287 00:12:33,720 --> 00:12:37,199 Speaker 2: we were in generics. We had a broad range, broad portfolio, 288 00:12:37,679 --> 00:12:39,839 Speaker 2: and I think what our company's really great at is 289 00:12:39,960 --> 00:12:43,439 Speaker 2: discovering these novel breakthroughs and then getting access to over 290 00:12:43,480 --> 00:12:45,880 Speaker 2: two hundred and eighty million patients, which is our reach today, 291 00:12:46,280 --> 00:12:49,199 Speaker 2: largest we believe of any pharma company to all of 292 00:12:49,240 --> 00:12:52,080 Speaker 2: these patients. And so in order to do that well, 293 00:12:52,240 --> 00:12:55,320 Speaker 2: I didn't think we could allocate capital successfully across all 294 00:12:55,360 --> 00:12:58,640 Speaker 2: of these different businesses. So we spun al Con, the 295 00:12:58,720 --> 00:13:02,120 Speaker 2: largest public market spin in recent memory in Europe. We 296 00:13:02,240 --> 00:13:05,480 Speaker 2: spun out Sandos, We sold our consumer health business. It's 297 00:13:05,520 --> 00:13:08,000 Speaker 2: about one hundred and thirty billion dollars of transactions. Later, 298 00:13:08,480 --> 00:13:10,720 Speaker 2: we come out as a pure play medicines company, which 299 00:13:10,760 --> 00:13:12,640 Speaker 2: I think we're a best positioned for the long run. 300 00:13:12,720 --> 00:13:14,480 Speaker 1: Soh you're the CEO and you go to the board 301 00:13:14,520 --> 00:13:16,200 Speaker 1: and say, you know, we've been in the generics business, 302 00:13:16,200 --> 00:13:17,920 Speaker 1: we're in the consumer drug business, and we're going to 303 00:13:17,960 --> 00:13:19,240 Speaker 1: get out of all these except we're going to be 304 00:13:19,280 --> 00:13:20,960 Speaker 1: in the one business that we were now in. Did 305 00:13:21,040 --> 00:13:23,400 Speaker 1: they say, you know, you weren't qualified to make that 306 00:13:23,520 --> 00:13:24,559 Speaker 1: judgment or what did they say? 307 00:13:25,000 --> 00:13:25,160 Speaker 4: Well? 308 00:13:25,240 --> 00:13:28,000 Speaker 2: I think they went along, and I think they generally 309 00:13:28,080 --> 00:13:29,760 Speaker 2: were aligned. But I think it also was a step 310 00:13:29,800 --> 00:13:32,160 Speaker 2: wise journey. I mean, first we did consumer health and 311 00:13:32,200 --> 00:13:34,719 Speaker 2: we saw how that went, and then two years a 312 00:13:34,800 --> 00:13:37,320 Speaker 2: year later we did al Con, Then the pandemic came, 313 00:13:37,840 --> 00:13:40,000 Speaker 2: then we did did Santos. Because I think the fear 314 00:13:40,080 --> 00:13:42,520 Speaker 2: comes back from what we discussed earlier. When you have 315 00:13:42,679 --> 00:13:45,600 Speaker 2: a business in innovative medicines and you have these patent cliffs, 316 00:13:46,080 --> 00:13:48,800 Speaker 2: if you have these other businesses which are much more stable, 317 00:13:48,880 --> 00:13:51,559 Speaker 2: there's a feeling like you can offset your risk. You 318 00:13:51,679 --> 00:13:54,040 Speaker 2: have stable businesses and you have this one business where 319 00:13:54,040 --> 00:13:57,400 Speaker 2: you face these cliffs every fifteen to seventeen years. 320 00:13:58,120 --> 00:13:59,840 Speaker 4: I take the view that the only way you're going 321 00:13:59,920 --> 00:14:00,760 Speaker 4: to generate. 322 00:14:00,600 --> 00:14:03,360 Speaker 2: Enough medicines to keep growing as you focus your capital 323 00:14:03,400 --> 00:14:03,959 Speaker 2: on innovation. 324 00:14:04,240 --> 00:14:06,559 Speaker 1: So last week, as we're talking now, last week you 325 00:14:06,679 --> 00:14:09,520 Speaker 1: made another acquisition, I think for roughly five billion dollars. 326 00:14:09,840 --> 00:14:12,480 Speaker 1: You bought a company that is dealing with blood cancer. 327 00:14:12,640 --> 00:14:15,439 Speaker 1: So why was that a good acquisition? And how does 328 00:14:15,480 --> 00:14:17,000 Speaker 1: it as long does it take you to make an 329 00:14:17,040 --> 00:14:18,920 Speaker 1: assessment of whether an acquisition is good or not? And 330 00:14:19,000 --> 00:14:20,840 Speaker 1: do you come up with the ideas yourself, or does 331 00:14:20,880 --> 00:14:22,880 Speaker 1: some investment banker come along and tell you it's a 332 00:14:22,960 --> 00:14:23,400 Speaker 1: great idea. 333 00:14:23,480 --> 00:14:26,120 Speaker 4: We limit our use of investment bankers. In general. 334 00:14:26,480 --> 00:14:28,680 Speaker 2: What we try to look at is in the therapeutic 335 00:14:28,760 --> 00:14:30,800 Speaker 2: areas we're in. So we're in blood cancers. We've been 336 00:14:30,880 --> 00:14:32,960 Speaker 2: in blood cancers for over twenty years. Some of the 337 00:14:33,360 --> 00:14:35,600 Speaker 2: most pioneering drugs and blood cancers have come from our 338 00:14:35,680 --> 00:14:37,800 Speaker 2: research labs, and we say, if this is an area 339 00:14:38,000 --> 00:14:41,280 Speaker 2: we're in we have deep understanding, therefore this makes sense 340 00:14:41,360 --> 00:14:45,120 Speaker 2: to actually add another medicine to that portfolio, and so we. 341 00:14:45,280 --> 00:14:46,000 Speaker 4: Make that assessment. 342 00:14:46,040 --> 00:14:48,240 Speaker 2: If it's a good strategic fit, in this case a 343 00:14:48,320 --> 00:14:51,920 Speaker 2: good financial fit, we'll make the bet. One of the 344 00:14:51,960 --> 00:14:54,400 Speaker 2: things we've tried to be much more disciplined on is 345 00:14:54,480 --> 00:14:56,480 Speaker 2: to try to go at the lower end of the 346 00:14:56,600 --> 00:14:59,840 Speaker 2: range to under five billion dollars for acquisitions and really 347 00:15:00,120 --> 00:15:02,680 Speaker 2: ensure that they're in areas we have deep understanding. Generally, 348 00:15:02,720 --> 00:15:05,400 Speaker 2: when we've gone too far away from our core, the 349 00:15:05,520 --> 00:15:06,880 Speaker 2: value creation hasn't been there. 350 00:15:07,120 --> 00:15:10,760 Speaker 1: In twenty twenty three, AI burst onto the scene. Everybody 351 00:15:10,840 --> 00:15:14,320 Speaker 1: is now excited about AI. How is AI affecting your 352 00:15:14,400 --> 00:15:16,400 Speaker 1: company and do you think it's going to help your company? 353 00:15:17,080 --> 00:15:19,040 Speaker 2: I think a it's going to have a big impact, 354 00:15:19,080 --> 00:15:20,960 Speaker 2: but I think it's going to take more time than 355 00:15:21,000 --> 00:15:24,840 Speaker 2: most people expect. I think first in productivity areas, AI 356 00:15:25,000 --> 00:15:28,560 Speaker 2: has media applications, and I feel like in productivity we 357 00:15:28,640 --> 00:15:31,680 Speaker 2: can use AI for document management, document generations, not really 358 00:15:32,040 --> 00:15:35,600 Speaker 2: sexy areas, but things that really tractable in our sector. 359 00:15:35,760 --> 00:15:38,360 Speaker 2: Most uniquely, the big question is can you speed up 360 00:15:38,480 --> 00:15:40,920 Speaker 2: or increase the efficiency of drug R and D? And 361 00:15:41,000 --> 00:15:43,360 Speaker 2: there we're doing a couple of things, working on clinical 362 00:15:43,400 --> 00:15:46,160 Speaker 2: trials and optimizing our clinical trials. But the big bets 363 00:15:46,200 --> 00:15:51,320 Speaker 2: we've made are with Palenteer, Microsoft Research Labs, Google deep Mind, 364 00:15:52,000 --> 00:15:54,200 Speaker 2: and a few other partners to say, could you really 365 00:15:54,280 --> 00:15:58,600 Speaker 2: discover novel drugs that maybe weren't discoverable without AI? Can 366 00:15:58,680 --> 00:16:01,560 Speaker 2: you optimize drugs much more quickly? And this is all 367 00:16:01,600 --> 00:16:04,280 Speaker 2: building on the pioneering work that Google Deep Minded on 368 00:16:04,640 --> 00:16:08,040 Speaker 2: a technology called Alpha fold. There's a huge opportunity here, 369 00:16:08,240 --> 00:16:09,840 Speaker 2: But I think we also have to acknowledge that we 370 00:16:09,920 --> 00:16:12,200 Speaker 2: only understand about five to ten percent of what is 371 00:16:12,240 --> 00:16:14,800 Speaker 2: going on in the human body. So to expect AI 372 00:16:15,040 --> 00:16:17,480 Speaker 2: to use that five to ten percent to extrapolate and 373 00:16:17,560 --> 00:16:19,880 Speaker 2: come up with big discoveries is going to take time. 374 00:16:20,040 --> 00:16:23,120 Speaker 1: So other than AI, what medical technologies do you think 375 00:16:23,200 --> 00:16:25,840 Speaker 1: are coming along that in the next one, two or 376 00:16:25,880 --> 00:16:27,880 Speaker 1: three years are likely to change what you do or 377 00:16:28,000 --> 00:16:28,920 Speaker 1: change the medical world. 378 00:16:29,240 --> 00:16:30,160 Speaker 4: I think a couple of things. 379 00:16:30,320 --> 00:16:33,960 Speaker 2: One RNA therapeutics as I mentioned earlier in the broadcast, 380 00:16:34,120 --> 00:16:36,160 Speaker 2: or RNA therapeutics sRNAs. 381 00:16:36,360 --> 00:16:37,800 Speaker 4: These are really coming to life now. 382 00:16:37,880 --> 00:16:40,400 Speaker 2: What this allows you to do is treat diseases that 383 00:16:40,480 --> 00:16:43,760 Speaker 2: were not treatable or treat them with very infrequent drug dosing. 384 00:16:44,080 --> 00:16:45,680 Speaker 2: And if you could imagine if we could take on 385 00:16:45,840 --> 00:16:49,520 Speaker 2: blood pressure and cholesterol with once year dosing, hugely transformative. 386 00:16:49,800 --> 00:16:52,840 Speaker 4: Another one is sell therapy for immune diseases. 387 00:16:53,080 --> 00:16:56,080 Speaker 2: We've seen extraordinary results in early phase studies that if 388 00:16:56,120 --> 00:16:59,640 Speaker 2: you can reset somebody's immune system there are autoimmune disease 389 00:16:59,680 --> 00:17:03,200 Speaker 2: actually goes away, and we'll see if this is sustains. 390 00:17:03,320 --> 00:17:05,760 Speaker 2: But these are some of the most impressive results that 391 00:17:05,800 --> 00:17:09,199 Speaker 2: we've ever seen in early stage clinical studies. And then 392 00:17:09,240 --> 00:17:11,240 Speaker 2: the last is we're very big in an area of 393 00:17:11,320 --> 00:17:14,639 Speaker 2: cancer called radio ligend therapy. This is the idea that 394 00:17:14,720 --> 00:17:17,760 Speaker 2: can you bring nuclear particles right next to a cancer 395 00:17:17,880 --> 00:17:21,359 Speaker 2: in the body and deliver the radiation very locally, and 396 00:17:21,440 --> 00:17:23,600 Speaker 2: this has the opportunity to treat a whole range of 397 00:17:23,680 --> 00:17:25,720 Speaker 2: solid tumors in ways that we couldn't afford. 398 00:17:25,800 --> 00:17:27,639 Speaker 3: What do you do to kind of lower your global 399 00:17:27,720 --> 00:17:29,520 Speaker 3: footprint carbon footprint? What do you do? 400 00:17:29,920 --> 00:17:33,000 Speaker 2: Our big topic on sustainability is much more on access 401 00:17:33,000 --> 00:17:35,720 Speaker 2: to medicines, and so we have a big effort on 402 00:17:35,840 --> 00:17:38,639 Speaker 2: global access to medicines, trying to make sure our innovations 403 00:17:38,640 --> 00:17:41,400 Speaker 2: are accessible. The work we do in areas like malaria, 404 00:17:41,840 --> 00:17:46,040 Speaker 2: on leprosy, sickle cell disease to ensure populations around the 405 00:17:46,119 --> 00:17:47,960 Speaker 2: world can get access to these medicines. 406 00:17:48,240 --> 00:17:48,960 Speaker 3: How do you pay for that? 407 00:17:49,520 --> 00:17:51,800 Speaker 2: So it's all part of our sustainability efforts and we 408 00:17:51,920 --> 00:17:54,480 Speaker 2: view it as part of our core mission to deliver 409 00:17:54,560 --> 00:17:57,480 Speaker 2: these global health therapies to patients around the globe. So 410 00:17:57,600 --> 00:17:59,560 Speaker 2: we have a huge effort in global health R and 411 00:17:59,640 --> 00:18:02,680 Speaker 2: DST two hundred and fifty million dollars actually in trying 412 00:18:02,720 --> 00:18:05,199 Speaker 2: to discover the next wave of medicines to treat these 413 00:18:05,240 --> 00:18:06,240 Speaker 2: global health conditions. 414 00:18:06,320 --> 00:18:10,199 Speaker 3: What about DEID We're on a good track here. 415 00:18:10,240 --> 00:18:13,080 Speaker 2: We've actually about forty eight percent women in management media 416 00:18:13,119 --> 00:18:15,040 Speaker 2: and pay for women and of artists is higher than 417 00:18:15,320 --> 00:18:15,679 Speaker 2: for men. 418 00:18:16,359 --> 00:18:18,160 Speaker 4: So we have more work to do at the upper 419 00:18:18,240 --> 00:18:20,520 Speaker 4: levels of the company. But we're overall doing really well. 420 00:18:20,560 --> 00:18:23,359 Speaker 1: I think, what skill set do you think somebody should 421 00:18:23,840 --> 00:18:26,000 Speaker 1: develop in order to rise up to be a CEO? 422 00:18:26,320 --> 00:18:28,360 Speaker 2: I think the biggest thing I think about is curiosity, 423 00:18:28,520 --> 00:18:32,440 Speaker 2: just relentless, relentless curiosity. I think whatever position I was 424 00:18:32,480 --> 00:18:34,680 Speaker 2: put in at Novartis, it was usually a place where 425 00:18:34,720 --> 00:18:37,560 Speaker 2: I didn't know anything, had to learn teach myself, be 426 00:18:37,680 --> 00:18:41,280 Speaker 2: relentlessly curious and then apply it and having experiences in 427 00:18:41,359 --> 00:18:44,440 Speaker 2: a range of different parts of the business world is 428 00:18:44,480 --> 00:18:45,359 Speaker 2: going to be a huge success. 429 00:18:45,680 --> 00:18:47,640 Speaker 3: How many employees does Novardis have now? 430 00:18:48,040 --> 00:18:49,400 Speaker 4: Seventy six thousand. 431 00:18:49,280 --> 00:18:50,160 Speaker 3: Seventy six thousand. 432 00:18:50,200 --> 00:18:52,879 Speaker 1: It's a lot of employees, so you frequently get a 433 00:18:53,000 --> 00:18:56,080 Speaker 1: chance to meet them in some organizations somewhere or some meeting. 434 00:18:56,200 --> 00:18:57,640 Speaker 3: How do you deal with all those employees? 435 00:18:57,880 --> 00:19:00,280 Speaker 2: I think the most valuable thing I find in my 436 00:19:00,400 --> 00:19:02,000 Speaker 2: job is to go around the world and meet these 437 00:19:02,320 --> 00:19:05,960 Speaker 2: meet our people, be able to have town halls and interactions. 438 00:19:06,000 --> 00:19:07,679 Speaker 2: It used to be before we spun off all these 439 00:19:07,680 --> 00:19:10,400 Speaker 2: businesses one hundred and thirty five thousand people, so we've 440 00:19:10,440 --> 00:19:13,320 Speaker 2: definitely slimmed down. But I think there's nothing that can 441 00:19:13,400 --> 00:19:16,600 Speaker 2: replace showing up face to face and describing why. 442 00:19:16,560 --> 00:19:17,159 Speaker 4: We do what we do. 443 00:19:17,440 --> 00:19:19,880 Speaker 1: So, as the CEO of the artists, you tell your 444 00:19:19,960 --> 00:19:22,639 Speaker 1: subordinates these are the areas that I think we should 445 00:19:22,720 --> 00:19:24,440 Speaker 1: work on and see if you can come up with 446 00:19:24,560 --> 00:19:26,880 Speaker 1: a pharmaceutical product in that area. Or do they come 447 00:19:26,920 --> 00:19:29,200 Speaker 1: to you and say, we have a prospect here and 448 00:19:29,359 --> 00:19:30,800 Speaker 1: you bless this. How does that work? 449 00:19:31,119 --> 00:19:31,239 Speaker 4: Well? 450 00:19:31,359 --> 00:19:33,440 Speaker 2: In general, I have a philosophy that we call in 451 00:19:33,520 --> 00:19:36,720 Speaker 2: our culture unbost and we try to unboss our people. 452 00:19:36,800 --> 00:19:39,159 Speaker 2: We want our people to actually bring the ideas up 453 00:19:39,280 --> 00:19:41,119 Speaker 2: and then we of course have to challenge them, but 454 00:19:41,160 --> 00:19:43,399 Speaker 2: then we make the call. So I really believe that 455 00:19:43,560 --> 00:19:46,520 Speaker 2: in our sector where some of our scientists are world class, 456 00:19:46,800 --> 00:19:49,159 Speaker 2: many of our scientists are world class, they should be 457 00:19:49,240 --> 00:19:51,360 Speaker 2: bringing up the ideas and we have to curate them. 458 00:19:51,680 --> 00:19:54,720 Speaker 2: But certainly, I'm not sitting on some mountain here knowing 459 00:19:54,760 --> 00:19:55,760 Speaker 2: what the right thing to do is. 460 00:19:55,840 --> 00:19:56,680 Speaker 4: Certainly so, if. 461 00:19:56,600 --> 00:19:59,720 Speaker 1: Somebody is saying, I'm graduating from college or graduate school 462 00:20:00,080 --> 00:20:02,800 Speaker 1: the next year or so, and I want a nice career, 463 00:20:03,200 --> 00:20:05,600 Speaker 1: why should somebody want to be in the pharmaceutical industry. 464 00:20:05,600 --> 00:20:08,560 Speaker 1: Why not go into something sexy like private equity or 465 00:20:08,640 --> 00:20:10,560 Speaker 1: investment banking or something like that. 466 00:20:11,040 --> 00:20:14,639 Speaker 2: You know, despite some of the things people have, concepts 467 00:20:14,680 --> 00:20:16,800 Speaker 2: people have about our industry. In the end, what we 468 00:20:16,920 --> 00:20:19,240 Speaker 2: do is we create these miracles that fit in the 469 00:20:19,320 --> 00:20:22,320 Speaker 2: palm of your hand, these little medicines that can transform 470 00:20:22,720 --> 00:20:24,399 Speaker 2: a human beings life. And if you look at the 471 00:20:24,560 --> 00:20:27,200 Speaker 2: arc of history, in the last one hundred and thirty years, 472 00:20:27,280 --> 00:20:29,640 Speaker 2: we've been able to move through the power of medicine 473 00:20:29,680 --> 00:20:33,439 Speaker 2: life expectancy from thirty years to eighty years. We're now 474 00:20:33,560 --> 00:20:36,399 Speaker 2: able to cure diseases. We're able to give people, you know, 475 00:20:36,480 --> 00:20:38,600 Speaker 2: with debilitating disease their lives back. 476 00:20:39,040 --> 00:20:39,760 Speaker 4: So if you're part of. 477 00:20:39,760 --> 00:20:41,920 Speaker 2: That kind of enterprise, you can get up every day 478 00:20:42,040 --> 00:20:44,520 Speaker 2: knowing you're moving the needle for society, you're moving the 479 00:20:44,640 --> 00:20:48,080 Speaker 2: needle for mankind. I think we do reimagine medicine with 480 00:20:48,119 --> 00:20:50,119 Speaker 2: the medicines we create, and I think that's a pretty 481 00:20:50,119 --> 00:20:51,360 Speaker 2: inspiring way to spend your time. 482 00:20:51,600 --> 00:20:54,160 Speaker 1: So suppose a president came along to you and said, 483 00:20:54,640 --> 00:20:56,800 Speaker 1: I know you're living in Switzerland, but it'd be great 484 00:20:56,840 --> 00:20:59,680 Speaker 1: to be the Secretary of Health and Human Services or 485 00:20:59,720 --> 00:21:01,000 Speaker 1: head of FDA or something. 486 00:21:01,400 --> 00:21:02,080 Speaker 3: What would you say? 487 00:21:02,359 --> 00:21:03,520 Speaker 4: I would think hard about it. 488 00:21:03,920 --> 00:21:07,600 Speaker 2: At the moment, it would feel like a really daunting 489 00:21:07,720 --> 00:21:09,000 Speaker 2: task given the politics. 490 00:21:09,400 --> 00:21:11,960 Speaker 4: But on the flip side, I do think public. 491 00:21:11,760 --> 00:21:13,720 Speaker 2: Service, of course, has so much power, and I think 492 00:21:13,720 --> 00:21:15,560 Speaker 2: if you're in the right context, you could do a 493 00:21:15,600 --> 00:21:18,159 Speaker 2: lot of good for good for the world. But I 494 00:21:18,200 --> 00:21:20,959 Speaker 2: think it's very context dependent. As you know, it can 495 00:21:21,040 --> 00:21:23,880 Speaker 2: be a very short time in some of these roles 496 00:21:23,920 --> 00:21:26,119 Speaker 2: with some of the recent recent cabinet members. 497 00:21:26,240 --> 00:21:29,520 Speaker 1: Suppose I said, I'm a stock market picker and I 498 00:21:29,600 --> 00:21:31,600 Speaker 1: want to be buying good stocks and companies that are 499 00:21:31,640 --> 00:21:33,960 Speaker 1: going to grow and so forth. Why should I want 500 00:21:34,000 --> 00:21:35,960 Speaker 1: to invest in the pharmaceutical industry? Is it going to 501 00:21:36,000 --> 00:21:38,240 Speaker 1: continue to grow as it did last year? And what 502 00:21:38,359 --> 00:21:39,280 Speaker 1: about your own company? 503 00:21:39,320 --> 00:21:41,360 Speaker 3: Do you think it's going to have good growth prospects 504 00:21:41,359 --> 00:21:42,879 Speaker 3: over the next couple of years. We do. 505 00:21:43,119 --> 00:21:45,520 Speaker 2: We've signed up for a five percent plus growth, forty 506 00:21:45,560 --> 00:21:49,879 Speaker 2: percent plus margins, and very consistent growth over time. I 507 00:21:49,960 --> 00:21:52,080 Speaker 2: think the reason to invest in the sector is the science. 508 00:21:52,119 --> 00:21:53,760 Speaker 2: I mean, when you look again, if I go back 509 00:21:53,760 --> 00:21:56,440 Speaker 2: into the history, for most of the last century, we 510 00:21:56,520 --> 00:21:58,040 Speaker 2: were only giving people pills and. 511 00:21:58,080 --> 00:21:59,679 Speaker 4: Small, small molecule drugs. 512 00:22:00,080 --> 00:22:01,960 Speaker 2: Then we discovered that we had this whole world of 513 00:22:02,000 --> 00:22:06,000 Speaker 2: biologics and we could treat diseases with biologicals. More recently, 514 00:22:06,119 --> 00:22:09,239 Speaker 2: we've discovered that we can reprogram yourselves, we can edit 515 00:22:09,320 --> 00:22:12,320 Speaker 2: the genome, we can use these RNA therapeutics to completely 516 00:22:12,400 --> 00:22:15,880 Speaker 2: transform areas of medicine. Those technology areas are at their 517 00:22:16,040 --> 00:22:18,159 Speaker 2: very nascent stage, and what we're going to find is 518 00:22:18,160 --> 00:22:20,399 Speaker 2: they're going to open up whole new areas of growth 519 00:22:20,800 --> 00:22:24,040 Speaker 2: from our business standpoint and a human health impact standpoint. 520 00:22:24,359 --> 00:22:26,159 Speaker 2: And so to get in now, as that's happening, and 521 00:22:26,240 --> 00:22:28,680 Speaker 2: you've seen how the obesity companies have cleared five hundred 522 00:22:28,720 --> 00:22:32,040 Speaker 2: billion market cap, we hope that as we work in 523 00:22:32,119 --> 00:22:34,960 Speaker 2: our areas like cell therapy and RNA therapeutics, we will 524 00:22:35,000 --> 00:22:37,240 Speaker 2: also be able to climb to a whole other level 525 00:22:37,280 --> 00:22:38,400 Speaker 2: of market cap over time. 526 00:22:38,800 --> 00:22:40,440 Speaker 1: So as you look back on your career and are 527 00:22:40,440 --> 00:22:43,400 Speaker 1: still very early in the career relative to many other people, 528 00:22:43,480 --> 00:22:47,080 Speaker 1: I often talk to any regrets about going this route 529 00:22:47,200 --> 00:22:50,680 Speaker 1: or not becoming a medical doctor and working on patients, No, 530 00:22:50,920 --> 00:22:51,520 Speaker 1: I have to say. 531 00:22:51,600 --> 00:22:53,560 Speaker 2: I mean, when I look at the reach of our 532 00:22:54,119 --> 00:22:57,040 Speaker 2: medicines and the impact they have, I'll just go back 533 00:22:57,080 --> 00:22:58,879 Speaker 2: to my time with Paul Farmer just to say that 534 00:22:59,600 --> 00:23:02,760 Speaker 2: who unfortunately passed away, but it was an incredible mentor 535 00:23:02,840 --> 00:23:04,600 Speaker 2: and inspiring mentor. I always told him, I want to 536 00:23:04,640 --> 00:23:07,040 Speaker 2: have this big impact on public health. He of course 537 00:23:07,080 --> 00:23:08,920 Speaker 2: did it, working with patients and some of the poorest 538 00:23:08,960 --> 00:23:13,240 Speaker 2: communities in the world. Today, Novartis are malaria drug Coartem. 539 00:23:13,440 --> 00:23:17,160 Speaker 2: Coartem is almost ninety nine percent effective when it's given 540 00:23:17,200 --> 00:23:17,760 Speaker 2: on time to. 541 00:23:17,760 --> 00:23:18,840 Speaker 4: Treat a malaria patient. 542 00:23:19,119 --> 00:23:22,959 Speaker 2: Over four hundred million children treated with our malaria medicines 543 00:23:22,960 --> 00:23:25,720 Speaker 2: and the biggest malaria pipeline, so even from a public 544 00:23:25,800 --> 00:23:28,919 Speaker 2: health standpoint, the opportunity to have an impact at scale 545 00:23:28,960 --> 00:23:30,440 Speaker 2: has really been fulfilled. 546 00:23:30,040 --> 00:23:31,080 Speaker 4: With this role. 547 00:23:32,359 --> 00:23:34,800 Speaker 1: Thanks for listening to hear more of my interviews. You 548 00:23:34,920 --> 00:23:39,000 Speaker 1: can subscribe and download my podcast on Spotify, Apple, or 549 00:23:39,040 --> 00:23:39,879 Speaker 1: wherever you Lisien