1 00:00:02,440 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. 2 00:00:11,640 --> 00:00:15,440 Speaker 2: This is the Bloomberg Surveillance Podcast. I'm Jonathan Ferrow, along 3 00:00:15,480 --> 00:00:18,680 Speaker 2: with Lisa Bromwitz and Amrie Hordern. Join us each day 4 00:00:18,720 --> 00:00:22,280 Speaker 2: for insight from the best in markets, economics, and geopolitics 5 00:00:22,440 --> 00:00:24,920 Speaker 2: from our global headquarters in New York City. We are 6 00:00:24,920 --> 00:00:27,680 Speaker 2: live on Bloomberg Television weekday mornings from six to nine 7 00:00:27,720 --> 00:00:31,240 Speaker 2: am Eastern. Subscribe to the podcast on Apple, Spotify or 8 00:00:31,320 --> 00:00:33,960 Speaker 2: anywhere else you listen, and as always on the Bloomberg 9 00:00:34,040 --> 00:00:37,600 Speaker 2: Terminal and the Bloomberg Business app. Savera joins us now, SAVERA, 10 00:00:37,680 --> 00:00:40,800 Speaker 2: good morning to you. Which one is this? Stagflation? Hard landing, 11 00:00:40,840 --> 00:00:41,880 Speaker 2: no landing? Where are we going? 12 00:00:42,320 --> 00:00:45,720 Speaker 3: I think we're going to a soft landing with a 13 00:00:45,840 --> 00:00:48,880 Speaker 3: reasonable market environment, maybe better. 14 00:00:48,640 --> 00:00:52,000 Speaker 4: Growth ahead than what we're used to. Higher rates, a 15 00:00:52,040 --> 00:00:54,360 Speaker 4: little bit of higher inflation. But look where we are 16 00:00:54,360 --> 00:00:54,920 Speaker 4: on inflation. 17 00:00:55,120 --> 00:00:57,080 Speaker 3: These are the levels that we all used to write 18 00:00:57,080 --> 00:01:00,960 Speaker 3: about as the Goldilocks levels. Right, We're not at nine, 19 00:01:01,000 --> 00:01:03,040 Speaker 3: we're not at zero, We're around. 20 00:01:02,840 --> 00:01:05,320 Speaker 4: Three or four. Those are healthy levels for equities. 21 00:01:05,360 --> 00:01:07,840 Speaker 2: It doesn't sound late cycle when you speak where are 22 00:01:08,000 --> 00:01:08,760 Speaker 2: we in this cycle? 23 00:01:08,920 --> 00:01:09,480 Speaker 4: Who knows? 24 00:01:09,520 --> 00:01:13,119 Speaker 3: I mean I think this cycle is very asynchronous, if 25 00:01:13,160 --> 00:01:16,200 Speaker 3: you will. So it's you know, there's some areas that 26 00:01:16,240 --> 00:01:18,679 Speaker 3: are booming. We're still kind of coming off of COVID, 27 00:01:18,760 --> 00:01:22,360 Speaker 3: So we've got services demand maybe slowing or tapering off, 28 00:01:22,400 --> 00:01:24,280 Speaker 3: goods demand potentially picking up. 29 00:01:24,560 --> 00:01:25,959 Speaker 4: We've got still tight employment. 30 00:01:26,160 --> 00:01:28,640 Speaker 3: But then there's also a couple of structural factors that 31 00:01:28,720 --> 00:01:29,200 Speaker 3: I think. 32 00:01:29,000 --> 00:01:31,600 Speaker 4: Are skewing the cycle call. 33 00:01:31,920 --> 00:01:36,160 Speaker 3: So we have a very tight employment market, and one 34 00:01:36,200 --> 00:01:39,399 Speaker 3: of the reasons for that is demographics, which we're you know, 35 00:01:39,400 --> 00:01:42,360 Speaker 3: we're in an aging demographic scenario. And then on top 36 00:01:42,400 --> 00:01:45,000 Speaker 3: of that, we had a huge number of early retirees 37 00:01:45,080 --> 00:01:48,560 Speaker 3: during COVID. Unless we loose an immigration, I think that 38 00:01:48,600 --> 00:01:51,279 Speaker 3: we're going to remain in this very tight labor market. 39 00:01:51,360 --> 00:01:54,440 Speaker 3: So that's the other factor. And you know, we've talked 40 00:01:54,440 --> 00:01:56,440 Speaker 3: about this. I think the consumer is in a very 41 00:01:56,480 --> 00:01:59,760 Speaker 3: different balance sheet set up than in prior cycles, where 42 00:02:00,120 --> 00:02:03,480 Speaker 3: you know, long term fixed rate mortgages eighty five percent, 43 00:02:03,800 --> 00:02:07,320 Speaker 3: very different from prior cycles. You've got baby boomers sitting 44 00:02:07,320 --> 00:02:08,600 Speaker 3: on wads of cash. 45 00:02:08,639 --> 00:02:10,919 Speaker 4: So I just think that. 46 00:02:11,280 --> 00:02:15,920 Speaker 3: This cycle you can't just map on the typical you know, oh, 47 00:02:15,960 --> 00:02:18,320 Speaker 3: the FED is tightening, it's. 48 00:02:18,680 --> 00:02:20,919 Speaker 4: You know, or late cycle. Now the FED is stopped 49 00:02:20,960 --> 00:02:23,480 Speaker 4: and they're going to start cutting. We're early. It's a 50 00:02:23,560 --> 00:02:26,560 Speaker 4: different a different type of market. You use the G word. 51 00:02:26,960 --> 00:02:28,560 Speaker 5: Sorry, I apologize to fans. 52 00:02:28,560 --> 00:02:30,560 Speaker 1: It's been a long way goldilocks. And we hear this 53 00:02:30,639 --> 00:02:32,880 Speaker 1: from Max Kettner's too, and this really raises a question, 54 00:02:33,000 --> 00:02:35,600 Speaker 1: or can we have goldilocks with five percent FED funds rates? 55 00:02:35,840 --> 00:02:37,119 Speaker 4: Is this actually just a new rate? 56 00:02:37,440 --> 00:02:38,680 Speaker 5: Is it not actually restrictive? 57 00:02:38,760 --> 00:02:40,640 Speaker 1: And is it something that can actually even allow a 58 00:02:40,680 --> 00:02:43,919 Speaker 1: broadening out and a rally even without any rate cuts 59 00:02:43,919 --> 00:02:44,320 Speaker 1: this year? 60 00:02:44,480 --> 00:02:44,960 Speaker 4: I think so. 61 00:02:45,200 --> 00:02:47,160 Speaker 3: I mean, I think there's a very high probability that 62 00:02:47,200 --> 00:02:49,920 Speaker 3: the FED remains on hold. Our economists have talked about 63 00:02:49,960 --> 00:02:52,359 Speaker 3: this as well, So we expect to cut in December. 64 00:02:52,440 --> 00:02:53,320 Speaker 4: Maybe no cuts. 65 00:02:54,120 --> 00:02:58,080 Speaker 3: Look, I think five percent is a manageable number, especially 66 00:02:58,120 --> 00:03:01,800 Speaker 3: if you have corporations that have locked in fixed straight 67 00:03:02,200 --> 00:03:05,280 Speaker 3: you know, long term debt you've got And this is 68 00:03:05,320 --> 00:03:08,359 Speaker 3: the S and P, not necessarily small caps or other regions. 69 00:03:08,720 --> 00:03:11,200 Speaker 3: But I think that the SMP has actually prepared for 70 00:03:11,240 --> 00:03:14,520 Speaker 3: this moment. Now you've got big tech companies, the go 71 00:03:14,520 --> 00:03:18,720 Speaker 3: go growth stocks initiating dividends. Right, We've got an environment 72 00:03:18,720 --> 00:03:22,519 Speaker 3: where the market is adapting to higher interest rates, shortening 73 00:03:22,560 --> 00:03:25,639 Speaker 3: their duration, giving us more cash. I think this is 74 00:03:25,680 --> 00:03:28,640 Speaker 3: actually a kind of a reasonable setup for equities here. 75 00:03:28,800 --> 00:03:31,200 Speaker 1: I don't want to be cynical. There is this concern 76 00:03:31,480 --> 00:03:34,120 Speaker 1: with people focusing on large caps that can handle this. 77 00:03:34,600 --> 00:03:37,440 Speaker 1: The people shrug off the highest delinquency rates. Going back 78 00:03:37,600 --> 00:03:40,960 Speaker 1: many years, this idea that if a number of people 79 00:03:41,040 --> 00:03:44,400 Speaker 1: just get blown out, fine, it's okay, you know, we 80 00:03:44,440 --> 00:03:46,920 Speaker 1: can just go into luxury, we'll go into big tech, 81 00:03:46,960 --> 00:03:48,760 Speaker 1: we'll go into the areas that'll do fine, and we'll 82 00:03:48,800 --> 00:03:51,560 Speaker 1: be fine, even if other segments are getting kind of blown. 83 00:03:51,520 --> 00:03:54,280 Speaker 4: Right, right, How long can that go on? I think 84 00:03:54,360 --> 00:03:56,040 Speaker 4: that is a key risk. 85 00:03:56,120 --> 00:03:59,200 Speaker 3: And I mean we've seen that income gap widen for 86 00:03:59,280 --> 00:04:02,960 Speaker 3: decades now, right. I think what's happening now is actually 87 00:04:03,040 --> 00:04:07,360 Speaker 3: potentially better for the middle to lower income customer if 88 00:04:07,640 --> 00:04:11,120 Speaker 3: you're in certain sectors. So look at manufacturing in the US. 89 00:04:11,160 --> 00:04:14,360 Speaker 3: There's still a very tight labor force. Real wage growth 90 00:04:14,400 --> 00:04:17,400 Speaker 3: is positive. Where you're seeing a lot of the layoffs 91 00:04:17,480 --> 00:04:22,120 Speaker 3: is more in white collar, you know, not necessarily Middle America, 92 00:04:22,240 --> 00:04:25,200 Speaker 3: where you're seeing still very strong signs of this restoring 93 00:04:25,320 --> 00:04:29,200 Speaker 3: boom that has a long tail, right. I mean, you 94 00:04:29,240 --> 00:04:32,200 Speaker 3: can't build a factory in a year. It's going this 95 00:04:32,200 --> 00:04:35,479 Speaker 3: This restoring theme is a very long term theme that 96 00:04:35,560 --> 00:04:38,640 Speaker 3: I think has legs over the next several years. And 97 00:04:39,080 --> 00:04:41,960 Speaker 3: that's where the job tightness is, that's where the real 98 00:04:42,000 --> 00:04:43,680 Speaker 3: wage growth is really positive. 99 00:04:44,040 --> 00:04:46,160 Speaker 4: And I think those are areas. 100 00:04:45,800 --> 00:04:48,440 Speaker 3: That are, you know, different from where we've seen benefits 101 00:04:48,440 --> 00:04:51,040 Speaker 3: in the past. So that's one way to stave it off. 102 00:04:51,040 --> 00:04:53,080 Speaker 3: And then you know, I think higher oil prices are 103 00:04:53,080 --> 00:04:56,240 Speaker 3: also a concern if you think about geopolitical risks. But 104 00:04:56,920 --> 00:04:59,120 Speaker 3: where we are today is I think the US is 105 00:04:59,120 --> 00:05:02,239 Speaker 3: in a better position because we are now a net 106 00:05:02,360 --> 00:05:05,359 Speaker 3: exporter rather than an importer, so we've got a little 107 00:05:05,360 --> 00:05:08,039 Speaker 3: bit more wiggle rim around oil than we did in 108 00:05:08,120 --> 00:05:09,000 Speaker 3: prior cycles. 109 00:05:09,279 --> 00:05:10,719 Speaker 4: But you're right, it's a concern. 110 00:05:10,800 --> 00:05:12,599 Speaker 6: Well when it comes to these low age workers saying 111 00:05:12,600 --> 00:05:14,720 Speaker 6: people they're getting jobs in manufacturing. But I go back 112 00:05:14,760 --> 00:05:17,960 Speaker 6: to what Diane Swanks said yesterday to Jonathan, Lisa and Tom. 113 00:05:18,160 --> 00:05:20,680 Speaker 6: These individuals move from the shadows of the economy into 114 00:05:20,680 --> 00:05:23,520 Speaker 6: the sun. Maybe that's the labor market that's getting a 115 00:05:23,560 --> 00:05:25,599 Speaker 6: better job, but then they get hit by inflation. They 116 00:05:25,640 --> 00:05:28,400 Speaker 6: get burned by inflation. Right, So how does the FED 117 00:05:28,480 --> 00:05:30,800 Speaker 6: think of these individuals when it comes to higher inflation, 118 00:05:30,960 --> 00:05:32,960 Speaker 6: because we know they have no appetite. 119 00:05:32,400 --> 00:05:34,279 Speaker 4: For a hike, right, right, right, right. 120 00:05:34,360 --> 00:05:36,400 Speaker 3: So I think that where we are now is an 121 00:05:36,480 --> 00:05:38,960 Speaker 3: environment where we really do need to see some of 122 00:05:38,960 --> 00:05:43,440 Speaker 3: these inflationary forces subside, and we're I think there's a 123 00:05:43,520 --> 00:05:46,479 Speaker 3: couple of things going on that could actually continue to 124 00:05:47,360 --> 00:05:48,839 Speaker 3: create a ceiling on inflation. 125 00:05:49,279 --> 00:05:49,960 Speaker 4: So think about it. 126 00:05:50,000 --> 00:05:54,000 Speaker 3: There's still demographics and demographics, We've got aging population, less 127 00:05:54,040 --> 00:05:57,480 Speaker 3: demand for stuff. That's that's another that's sort of a 128 00:05:58,360 --> 00:06:04,520 Speaker 3: disinflationary pressure. You've also got disruption from AI tech automation, 129 00:06:04,920 --> 00:06:09,000 Speaker 3: so that's a continued disinflationary pressure. I don't see inflation 130 00:06:09,200 --> 00:06:13,359 Speaker 3: going to the seventies levels that's really untenable for your 131 00:06:13,680 --> 00:06:18,000 Speaker 3: average consumer. I think there's enough of a secular disinflationary 132 00:06:18,240 --> 00:06:20,919 Speaker 3: force at play that we've all been talking about, you know, 133 00:06:20,960 --> 00:06:24,239 Speaker 3: for the last twenty years that can can actually stave 134 00:06:24,320 --> 00:06:28,960 Speaker 3: off a really aggressive level of inflation. And then on 135 00:06:28,960 --> 00:06:31,039 Speaker 3: top of that, I think the energy independence of the 136 00:06:31,120 --> 00:06:34,440 Speaker 3: US is a really important factor because you know, that's 137 00:06:34,480 --> 00:06:37,520 Speaker 3: a benefit to the US that most other developed. 138 00:06:37,120 --> 00:06:40,040 Speaker 4: Economies don't have. And I think that's something we should 139 00:06:40,040 --> 00:06:40,520 Speaker 4: be happy about. 140 00:06:40,600 --> 00:06:42,360 Speaker 2: Let's finish on something you've been focused on for quite 141 00:06:42,360 --> 00:06:45,080 Speaker 2: a while allan to call Amy value, and it's industrial 142 00:06:45,120 --> 00:06:48,000 Speaker 2: staff to capital. I remember you outlining this, I think 143 00:06:48,000 --> 00:06:49,919 Speaker 2: maybe twelve months ago. Still a big thing for you 144 00:06:49,960 --> 00:06:50,400 Speaker 2: and a team. 145 00:06:50,560 --> 00:06:53,279 Speaker 3: Yes, and it's worked for maybe two months out of 146 00:06:53,320 --> 00:06:54,440 Speaker 3: the last twelve. 147 00:06:55,160 --> 00:06:57,560 Speaker 2: But you know, I think where we are now against 148 00:06:57,600 --> 00:06:59,800 Speaker 2: throwing much Just for the record, I was genuinely interested 149 00:06:59,839 --> 00:07:01,640 Speaker 2: in that faces well. 150 00:07:01,360 --> 00:07:04,000 Speaker 3: You know again, I think we're in an environment where 151 00:07:04,360 --> 00:07:07,839 Speaker 3: the broadening of the market is still a theme we 152 00:07:07,920 --> 00:07:10,480 Speaker 3: talk about, and it's started to happen in the last 153 00:07:10,480 --> 00:07:11,320 Speaker 3: couple of months. 154 00:07:12,680 --> 00:07:14,800 Speaker 4: Look who's going to benefit from all. 155 00:07:14,720 --> 00:07:18,200 Speaker 3: These chips and this AI and you know automation. It's 156 00:07:18,240 --> 00:07:21,440 Speaker 3: old economy companies that get more labor light. And I 157 00:07:21,480 --> 00:07:23,840 Speaker 3: think that's the benefit that we could see over the 158 00:07:23,880 --> 00:07:25,760 Speaker 3: next you know, twelve to twenty four to. 159 00:07:25,960 --> 00:07:26,840 Speaker 4: You a few years. 160 00:07:27,640 --> 00:07:30,480 Speaker 3: I think the areas are you know, industries like ours, 161 00:07:30,520 --> 00:07:33,840 Speaker 3: the banks, right, I mean banks are very labor intensive. 162 00:07:34,240 --> 00:07:35,880 Speaker 4: Now there is this tool that. 163 00:07:35,800 --> 00:07:40,120 Speaker 3: We can use to replace people with bots and processes. 164 00:07:39,480 --> 00:07:39,960 Speaker 4: Et cetera. 165 00:07:40,360 --> 00:07:44,320 Speaker 3: So I think, you know, it's it's a potential streamlining 166 00:07:44,400 --> 00:07:47,720 Speaker 3: or cost cutting story self help for a lot of 167 00:07:47,720 --> 00:07:51,320 Speaker 3: these old economy services sectors that haven't really addressed their 168 00:07:51,400 --> 00:07:53,480 Speaker 3: labor intensity for for quite a while. 169 00:07:54,120 --> 00:08:05,520 Speaker 6: This was it's going to s. 170 00:08:04,960 --> 00:08:08,480 Speaker 2: Andrew Honposo. City office is one. We maintain our base 171 00:08:08,520 --> 00:08:10,960 Speaker 2: case from one hundred basis points of counts in twenty four, 172 00:08:11,200 --> 00:08:14,600 Speaker 2: substantially more than priced by interest rate markets. Andrew's with 173 00:08:14,720 --> 00:08:17,520 Speaker 2: us around the table, Andrew Hallo, let's go straight to it. 174 00:08:17,560 --> 00:08:20,440 Speaker 2: Four cuts in twenty four. This is not consensus. Where 175 00:08:20,440 --> 00:08:21,200 Speaker 2: does it come from? 176 00:08:21,280 --> 00:08:22,680 Speaker 5: Well, the Fed's going to cut this year. 177 00:08:22,720 --> 00:08:25,800 Speaker 7: I think that was very clear from CHERA Powell yesterday 178 00:08:25,800 --> 00:08:28,040 Speaker 7: that at least the next move is a cut, and 179 00:08:28,080 --> 00:08:30,560 Speaker 7: the way that they get there is because the inflation 180 00:08:30,640 --> 00:08:31,080 Speaker 7: data is. 181 00:08:31,000 --> 00:08:33,080 Speaker 5: Going to give them the opportunity. I don't think it's. 182 00:08:32,960 --> 00:08:34,640 Speaker 7: Going to two percent, but it's going to be slow 183 00:08:34,760 --> 00:08:37,040 Speaker 7: enough that it lets them cut. And then the labor 184 00:08:37,040 --> 00:08:39,360 Speaker 7: market is going to weaken. And we heard that from 185 00:08:39,400 --> 00:08:42,520 Speaker 7: Chaerir Powell, this idea that we're seeing that the trend 186 00:08:42,600 --> 00:08:44,199 Speaker 7: is really towards a weaker labor market. 187 00:08:44,240 --> 00:08:46,360 Speaker 2: Here, I think this is your signature cool for this year. 188 00:08:46,520 --> 00:08:49,280 Speaker 2: It's the weakness that you're anticipating in the labor market. 189 00:08:49,360 --> 00:08:51,200 Speaker 2: Do you see it now? Where's it coming from? 190 00:08:51,480 --> 00:08:54,160 Speaker 7: This is really important because what we heard from Chair 191 00:08:54,240 --> 00:08:57,679 Speaker 7: Powell is with the two mandates, the dual mandates and 192 00:08:57,800 --> 00:09:00,920 Speaker 7: better balance than their words, has come down. It's not 193 00:09:00,960 --> 00:09:03,440 Speaker 7: a two percent, but it's come down. They're looking at 194 00:09:03,520 --> 00:09:06,840 Speaker 7: employment now. And when you look at employment, Chirpewell highlighted 195 00:09:06,880 --> 00:09:08,679 Speaker 7: some of these things. You look at the conference board, 196 00:09:09,000 --> 00:09:11,480 Speaker 7: do people see jobs plentiful or do people see jobs 197 00:09:11,480 --> 00:09:12,120 Speaker 7: hard to get? 198 00:09:12,400 --> 00:09:14,600 Speaker 5: They're seeing jobs as harder to get. You ask people, 199 00:09:14,640 --> 00:09:16,679 Speaker 5: are you more worried about keeping your job? They are 200 00:09:16,679 --> 00:09:17,120 Speaker 5: more worried. 201 00:09:17,160 --> 00:09:19,280 Speaker 7: We see that in the New York Fed survey, and 202 00:09:19,320 --> 00:09:21,679 Speaker 7: then you go to the NFIB Small Business Survey. It's 203 00:09:21,679 --> 00:09:23,120 Speaker 7: going to come out to day at one pm. Let's 204 00:09:23,120 --> 00:09:25,680 Speaker 7: see where it is. But you're seeing small businesses that 205 00:09:25,720 --> 00:09:27,720 Speaker 7: are saying they're not excited about hiring. 206 00:09:27,760 --> 00:09:30,360 Speaker 5: So all of these indicators are going in one direction. 207 00:09:30,720 --> 00:09:33,600 Speaker 1: At the same time, we've been seeing signs of cracks 208 00:09:33,679 --> 00:09:37,040 Speaker 1: for a really long time. People expected things to weaken. 209 00:09:36,840 --> 00:09:39,160 Speaker 5: Substantially earlier this year. They haven't. 210 00:09:39,360 --> 00:09:41,720 Speaker 1: Late last year they didn't. So at what point do 211 00:09:41,720 --> 00:09:43,600 Speaker 1: you have conviction. This time is different. 212 00:09:43,920 --> 00:09:46,319 Speaker 7: So I think a lot of those calls were maybe 213 00:09:46,440 --> 00:09:49,319 Speaker 7: not wrong, but just very premature. And the cycle has 214 00:09:49,400 --> 00:09:52,199 Speaker 7: just extended a lot longer than many people thought. And 215 00:09:52,280 --> 00:09:54,320 Speaker 7: what we were going through in the labor market was 216 00:09:54,360 --> 00:09:57,160 Speaker 7: a kind of normalization. We had job openings that were 217 00:09:57,160 --> 00:10:00,959 Speaker 7: extremely elevated, We had just incredible will need to hire 218 00:10:01,080 --> 00:10:03,960 Speaker 7: people and restaff and we've really worked through a lot 219 00:10:03,960 --> 00:10:04,200 Speaker 7: of that. 220 00:10:04,240 --> 00:10:06,600 Speaker 5: Now when we look at these trends, take the quit rate. 221 00:10:06,480 --> 00:10:10,839 Speaker 7: And yesterday's Jolts report, that's a decade low, and what 222 00:10:10,880 --> 00:10:14,720 Speaker 7: that's telling us is that this isn't just normalization. 223 00:10:14,120 --> 00:10:14,640 Speaker 5: At this point. 224 00:10:14,720 --> 00:10:17,280 Speaker 7: This is people that at least in the last ten years, 225 00:10:17,280 --> 00:10:20,080 Speaker 7: people have not been this worried about holding onto a job, 226 00:10:20,160 --> 00:10:20,760 Speaker 7: which really. 227 00:10:20,600 --> 00:10:23,559 Speaker 1: Raises an interesting question about tomorrow's non farm payrolls report. 228 00:10:23,679 --> 00:10:26,160 Speaker 1: We're talking about how how high numbers will be and 229 00:10:26,200 --> 00:10:28,520 Speaker 1: how high numbers have been, and it really is one 230 00:10:28,520 --> 00:10:30,720 Speaker 1: of the reasons why people say this is a robust 231 00:10:30,800 --> 00:10:34,600 Speaker 1: labor market. Are you saying that those numbers inaccurately represent 232 00:10:34,760 --> 00:10:38,000 Speaker 1: the true labor market and are distorted by immigration, by 233 00:10:38,040 --> 00:10:39,880 Speaker 1: other types of features that. 234 00:10:39,960 --> 00:10:42,520 Speaker 5: Really might mask a real level. 235 00:10:42,280 --> 00:10:44,920 Speaker 1: Of weakness that could catch us to as sooner than 236 00:10:45,000 --> 00:10:45,760 Speaker 1: many people think. 237 00:10:46,040 --> 00:10:46,679 Speaker 5: I think that's right. 238 00:10:46,720 --> 00:10:48,240 Speaker 7: And one of the great things about being a US 239 00:10:48,240 --> 00:10:51,080 Speaker 7: economist is we have an incredible range of data to 240 00:10:51,160 --> 00:10:54,040 Speaker 7: draw on, especially with something like the labor market. So 241 00:10:54,320 --> 00:10:58,400 Speaker 7: the biggest focus is usually right that establishment survey, non 242 00:10:58,440 --> 00:11:01,320 Speaker 7: farm payrolls, those have been strong. If you look at 243 00:11:01,360 --> 00:11:05,439 Speaker 7: almost any other labor market indicator, they range from slightly 244 00:11:05,480 --> 00:11:07,840 Speaker 7: weaker to that than that to a lot weaker than that. 245 00:11:08,120 --> 00:11:10,800 Speaker 7: Take the household survey. That's where the unemployment rate comes from. 246 00:11:10,840 --> 00:11:13,320 Speaker 7: The unemployment rate has been moving up because employment in 247 00:11:13,360 --> 00:11:17,240 Speaker 7: the household survey has been softer. Take the Business Employment 248 00:11:17,320 --> 00:11:19,640 Speaker 7: Dynamics survey. Now this is something most people don't watch. 249 00:11:19,679 --> 00:11:22,079 Speaker 7: It comes out very, very lagged. The numbers just came 250 00:11:22,120 --> 00:11:26,319 Speaker 7: out from Q three. Nine million firms that are accounted 251 00:11:26,320 --> 00:11:28,720 Speaker 7: for in this This is really the official data on 252 00:11:28,960 --> 00:11:30,360 Speaker 7: what firms we're doing in Q three. 253 00:11:30,480 --> 00:11:32,640 Speaker 5: If you look at that data, we lost jobs in 254 00:11:32,679 --> 00:11:35,319 Speaker 5: the third quarter. I'm not saying that actually happen. 255 00:11:35,120 --> 00:11:37,160 Speaker 7: But you look at all these different data points, you 256 00:11:37,240 --> 00:11:39,080 Speaker 7: kind of PLoP them all together and try to figure 257 00:11:39,080 --> 00:11:39,920 Speaker 7: out where the trend is. 258 00:11:40,080 --> 00:11:42,000 Speaker 5: That trend is towards a weaker job market. 259 00:11:42,080 --> 00:11:43,760 Speaker 2: Let's take a look at the heart landing versus solft 260 00:11:43,840 --> 00:11:45,560 Speaker 2: landing shop. We'll do that together. I'll do it in 261 00:11:45,559 --> 00:11:47,640 Speaker 2: the air for you. It's been a long night, okay, 262 00:11:48,080 --> 00:11:51,200 Speaker 2: So soft landing here, all right? Heart landing over here, 263 00:11:51,320 --> 00:11:54,800 Speaker 2: self landing and macular disinflation, big supply side recovery, et cetera, 264 00:11:54,840 --> 00:11:57,920 Speaker 2: et cetera. Sounds like you're somewhere over here. Is that fair? 265 00:11:58,040 --> 00:11:59,679 Speaker 2: You're looking for something close to a heart land in 266 00:11:59,679 --> 00:11:59,960 Speaker 2: this year? 267 00:12:00,240 --> 00:12:00,640 Speaker 5: That's fair? 268 00:12:00,679 --> 00:12:03,240 Speaker 7: And I think that markets have actually moved away from 269 00:12:03,320 --> 00:12:05,840 Speaker 7: this soft landing idea. It's pretty clear from the inflation 270 00:12:05,920 --> 00:12:09,880 Speaker 7: data that we're not getting the soft landing. If activity 271 00:12:09,920 --> 00:12:11,680 Speaker 7: holds up, then maybe we're going to have more of 272 00:12:11,720 --> 00:12:14,960 Speaker 7: an issue with inflation. The reason I think that the 273 00:12:14,960 --> 00:12:17,080 Speaker 7: Fed's going to see enough to cut is because that's right, 274 00:12:17,080 --> 00:12:19,360 Speaker 7: We're more towards that hard landing end of the spectrum. 275 00:12:19,440 --> 00:12:21,439 Speaker 2: So when you look at market pricing, and this has 276 00:12:21,480 --> 00:12:23,960 Speaker 2: echoes of a conversation we had with Gershen distant found 277 00:12:23,960 --> 00:12:26,120 Speaker 2: of a lince Burn steam in the last week. Do 278 00:12:26,160 --> 00:12:28,480 Speaker 2: you see the pricing of say one rate cut this 279 00:12:28,600 --> 00:12:30,840 Speaker 2: year as just a weighted average of a whole range 280 00:12:30,840 --> 00:12:33,199 Speaker 2: of possibilities and maybe not the most likely outcome. 281 00:12:33,480 --> 00:12:35,440 Speaker 7: That's right, markets are always going to average over all 282 00:12:35,440 --> 00:12:37,920 Speaker 7: the possibilities. And you heard Chair Powell, it was kind 283 00:12:37,920 --> 00:12:41,640 Speaker 7: of this multiverse of possible Fed outcomes. Yesterday they could 284 00:12:41,720 --> 00:12:44,480 Speaker 7: not cut at all. They could be cutting. I think 285 00:12:44,520 --> 00:12:48,160 Speaker 7: what's important is a symmetry of the Fed's reaction function. 286 00:12:48,520 --> 00:12:52,360 Speaker 7: You don't need both softer inflation and a weaker labor market. 287 00:12:52,480 --> 00:12:54,640 Speaker 7: You just need one or the other, and that's why 288 00:12:54,640 --> 00:12:55,240 Speaker 7: they're going to cut. 289 00:12:55,360 --> 00:12:57,120 Speaker 1: It's fascinating to me that you said we're not getting 290 00:12:57,160 --> 00:12:59,560 Speaker 1: a soft landing. You expect one hundred basis points of 291 00:12:59,600 --> 00:13:02,640 Speaker 1: federal cuts. Is that basically you saying that you think 292 00:13:02,679 --> 00:13:05,199 Speaker 1: the damage will be done enough that even one hundred 293 00:13:05,240 --> 00:13:07,440 Speaker 1: basis points of rate cuts won't be able to give 294 00:13:07,800 --> 00:13:10,880 Speaker 1: that sort of surge of stimulus into the economy soon 295 00:13:11,000 --> 00:13:13,040 Speaker 1: enough to stave off a real downturn. 296 00:13:13,320 --> 00:13:16,160 Speaker 7: This is what happens in almost every monetary policy cycle, 297 00:13:16,200 --> 00:13:18,120 Speaker 7: and I don't think that there's good reason to think 298 00:13:18,160 --> 00:13:20,679 Speaker 7: that this cycle is going to be different. We have 299 00:13:21,080 --> 00:13:25,160 Speaker 7: inflation that's run higher than expected, still higher than expected 300 00:13:25,200 --> 00:13:28,040 Speaker 7: even in the first quarter, that has kept policy rates 301 00:13:28,120 --> 00:13:28,880 Speaker 7: higher for longer. 302 00:13:28,920 --> 00:13:31,160 Speaker 5: We're in the higher for longer stage of the policy cycle. 303 00:13:31,360 --> 00:13:33,760 Speaker 7: The next stage of the policy cycle is a weakening 304 00:13:33,760 --> 00:13:36,800 Speaker 7: of the labor market. Once it starts gradually weakening, it 305 00:13:36,800 --> 00:13:39,320 Speaker 7: then weakens more sharply. I think that's exactly what's playing 306 00:13:39,360 --> 00:13:39,760 Speaker 7: out now. 307 00:13:39,800 --> 00:13:42,760 Speaker 2: Just quickly. How united is that commits see on the FMC. 308 00:13:43,480 --> 00:13:45,320 Speaker 7: I think there are a lot of different views around 309 00:13:45,360 --> 00:13:47,800 Speaker 7: the table right now, and I think Powell is probably 310 00:13:47,840 --> 00:13:50,680 Speaker 7: something of a master in terms of somehow bringing things 311 00:13:50,760 --> 00:13:52,800 Speaker 7: enough together to do that press conference. 312 00:13:52,440 --> 00:14:04,880 Speaker 2: Yesterday Andrew Houn host Stephan I'm wonderful to catch up 313 00:14:04,880 --> 00:14:07,200 Speaker 2: with you, sir. The stock is just about positive in 314 00:14:07,240 --> 00:14:08,959 Speaker 2: the pre market. Can you talk to me about how 315 00:14:09,000 --> 00:14:13,079 Speaker 2: you're balancing cost cutting with investing in innovation given what's 316 00:14:13,080 --> 00:14:13,800 Speaker 2: in the pipeline. 317 00:14:14,840 --> 00:14:17,280 Speaker 8: Sure, well, good morning, Thank you for having me so 318 00:14:17,520 --> 00:14:20,720 Speaker 8: very pleased with a quote. We basically try to focus 319 00:14:20,960 --> 00:14:23,440 Speaker 8: on how do we drive sales, how do we drive 320 00:14:23,600 --> 00:14:26,520 Speaker 8: R and D, how do we prioritize opportunities, which is why, 321 00:14:26,560 --> 00:14:29,640 Speaker 8: for example, we announced that we are stopping the partnership 322 00:14:29,720 --> 00:14:32,720 Speaker 8: with Metagenomy in research engine editing. 323 00:14:33,200 --> 00:14:33,760 Speaker 5: Same thing if you. 324 00:14:33,720 --> 00:14:37,120 Speaker 8: Look at the portfolio we're looking very carefully at all investments. 325 00:14:37,600 --> 00:14:41,600 Speaker 8: And a good thing about those vaccines like respiratory vaccines 326 00:14:41,720 --> 00:14:44,480 Speaker 8: is your only pay the fase free study. What So 327 00:14:44,480 --> 00:14:46,840 Speaker 8: if you think about COVID, we still have sales from COVID, 328 00:14:47,280 --> 00:14:49,480 Speaker 8: but the investment in the idea of COVID has come 329 00:14:49,560 --> 00:14:52,240 Speaker 8: down a lot. As you said ours, we we are 330 00:14:52,280 --> 00:14:55,560 Speaker 8: antipating a launch this spring, but we're not going to 331 00:14:55,600 --> 00:14:57,720 Speaker 8: do another phase three four URSV. So you can still 332 00:14:57,960 --> 00:15:00,200 Speaker 8: basically have a lot of new studies going on on 333 00:15:01,600 --> 00:15:04,000 Speaker 8: reusing the capital you used to put in the other 334 00:15:04,080 --> 00:15:06,920 Speaker 8: products before. And then if you look at oncology, as 335 00:15:06,920 --> 00:15:09,400 Speaker 8: you know, when a fifty to fifty profit shared with Merk, 336 00:15:09,880 --> 00:15:12,000 Speaker 8: so merk is paying half of a face free study. 337 00:15:12,040 --> 00:15:14,120 Speaker 8: So that's how we're managing. When we're seeing a lot 338 00:15:14,160 --> 00:15:17,720 Speaker 8: in technology. You might have seen last week an announcement 339 00:15:17,840 --> 00:15:20,360 Speaker 8: with open Ai. We have actually more than seven or 340 00:15:20,560 --> 00:15:23,120 Speaker 8: fifty gpt is going and that is helping us a 341 00:15:23,120 --> 00:15:26,520 Speaker 8: lot scale the company across not only science, but striving 342 00:15:26,560 --> 00:15:30,800 Speaker 8: a lot of productivity in manufacturing, in commercial illegal So 343 00:15:30,800 --> 00:15:31,920 Speaker 8: that's kind of how we're doing it. 344 00:15:32,160 --> 00:15:34,080 Speaker 2: So Stephan, let's talk about something that our colleagues here 345 00:15:34,080 --> 00:15:37,440 Speaker 2: at Bloomberg are extremely focused on and that's your RSV show, 346 00:15:37,880 --> 00:15:40,320 Speaker 2: which according to our colleagues, some data is showing that 347 00:15:40,360 --> 00:15:42,760 Speaker 2: maybe it doesn't last as long as others in the market. 348 00:15:42,960 --> 00:15:44,520 Speaker 2: What we all want to know here at Bloomberger is 349 00:15:44,520 --> 00:15:47,440 Speaker 2: whether that raises questions about the promise of your technology 350 00:15:47,440 --> 00:15:50,080 Speaker 2: in treating other diseases. How would you answer that? 351 00:15:51,400 --> 00:15:53,040 Speaker 8: So we first said that if you look at the 352 00:15:53,120 --> 00:15:56,440 Speaker 8: data the duration of the over vaccines, they are very similar. 353 00:15:56,720 --> 00:15:59,720 Speaker 8: So I don't think it is scientifically correct to say 354 00:15:59,720 --> 00:16:02,160 Speaker 8: that one of a vaccine doesn't last as long as 355 00:16:02,200 --> 00:16:05,600 Speaker 8: the ones of a tool that are improved. And our 356 00:16:05,960 --> 00:16:08,960 Speaker 8: look at the data. This will be debated at the 357 00:16:08,960 --> 00:16:13,040 Speaker 8: CDC meeting at the end of drewn that for recommendations. 358 00:16:13,760 --> 00:16:16,160 Speaker 8: So this doesn't worry me. If you look at duration, 359 00:16:16,840 --> 00:16:20,920 Speaker 8: the duration of vaccination is induced by T cell. If 360 00:16:20,920 --> 00:16:24,160 Speaker 8: you look at cancer product, the only reason it works 361 00:16:24,640 --> 00:16:27,960 Speaker 8: is T cells, not antibodies. Antibodies don't have a rowing cancer. 362 00:16:28,000 --> 00:16:31,880 Speaker 8: It's about T cells going and attacking your cancer. If 363 00:16:31,960 --> 00:16:35,240 Speaker 8: a vaccine technology don't have good T cell response, the 364 00:16:35,320 --> 00:16:37,280 Speaker 8: cancer product will not look as good as it is. 365 00:16:37,600 --> 00:16:39,760 Speaker 8: So I'm not worried at all about duration. 366 00:16:40,480 --> 00:16:43,120 Speaker 1: Pretty much every time we speak Stepan, I ask you basically, 367 00:16:43,160 --> 00:16:44,840 Speaker 1: have we couraged cancer yet? So I'm glad that you 368 00:16:44,880 --> 00:16:46,600 Speaker 1: went there because that's been sort of one of the 369 00:16:46,640 --> 00:16:48,280 Speaker 1: big questions and I hope for a lot of the 370 00:16:49,480 --> 00:16:53,480 Speaker 1: mRNA vaccines. You have this melanoma vaccine in the works. 371 00:16:53,800 --> 00:16:54,960 Speaker 5: What more do you have to do. 372 00:16:54,920 --> 00:16:57,480 Speaker 1: To get it sort of set up for the approval 373 00:16:57,480 --> 00:17:00,400 Speaker 1: process to apply for that? And are you using artificial 374 00:17:00,440 --> 00:17:02,040 Speaker 1: intelligence to extracite. 375 00:17:01,560 --> 00:17:03,560 Speaker 5: That great question? 376 00:17:03,840 --> 00:17:07,920 Speaker 8: So if you look at cancer treatment in melanoma, we've 377 00:17:07,960 --> 00:17:11,320 Speaker 8: said that we need to achieve three things to be 378 00:17:11,359 --> 00:17:15,600 Speaker 8: able to talk to regulator about accelerated approval. So the 379 00:17:15,640 --> 00:17:17,960 Speaker 8: face to day ties data we shared on the show 380 00:17:18,320 --> 00:17:22,480 Speaker 8: several times, we see duration. If you remember in December 381 00:17:22,480 --> 00:17:25,239 Speaker 8: we had a three year survival, it was better than 382 00:17:25,240 --> 00:17:27,960 Speaker 8: the two year survival. So the difference between people on 383 00:17:28,040 --> 00:17:31,760 Speaker 8: all treatment and people that are just getting cathedral is 384 00:17:31,800 --> 00:17:35,600 Speaker 8: getting wider. So there's a very strong evidence that the 385 00:17:35,680 --> 00:17:39,160 Speaker 8: drug is working. So that's number one. Number two is 386 00:17:39,320 --> 00:17:43,400 Speaker 8: we need a phase free study to be substantially enrolled, 387 00:17:43,680 --> 00:17:46,879 Speaker 8: and so we are working very actively. Face free study 388 00:17:46,960 --> 00:17:50,679 Speaker 8: started two months earlier than planned last summer and so 389 00:17:50,720 --> 00:17:54,040 Speaker 8: when we are substantially enrolled, we will meet that criteria 390 00:17:54,760 --> 00:17:56,920 Speaker 8: and it could be later this year. And the third 391 00:17:56,920 --> 00:17:59,399 Speaker 8: one is a plant, because of course we need to 392 00:17:59,480 --> 00:18:03,199 Speaker 8: file in the restrection does all the information about the 393 00:18:03,200 --> 00:18:07,679 Speaker 8: manufacturing process BFD, and the day you file is allowed 394 00:18:07,680 --> 00:18:10,480 Speaker 8: to go of course audit your plant. That plant is 395 00:18:10,520 --> 00:18:12,160 Speaker 8: being built. I had the chance to go there two 396 00:18:12,160 --> 00:18:15,520 Speaker 8: weeks ago. The team is working NonStop, scheduling literally by 397 00:18:15,560 --> 00:18:17,960 Speaker 8: the days, a bit like we did during COVID during 398 00:18:18,000 --> 00:18:22,840 Speaker 8: the pandemic, and so I ancipate that potentially sometime next year. 399 00:18:22,960 --> 00:18:26,080 Speaker 8: You know, the if a regulator was willing to look 400 00:18:26,119 --> 00:18:29,520 Speaker 8: at the acceleted approval file, we should have this product 401 00:18:29,520 --> 00:18:31,600 Speaker 8: available to help a lot of people, because one in 402 00:18:31,640 --> 00:18:35,439 Speaker 8: two people benefit with notices coming back or no deaths 403 00:18:35,880 --> 00:18:38,240 Speaker 8: compared to the best drug available today to them on 404 00:18:38,280 --> 00:18:38,720 Speaker 8: the market. 405 00:18:38,880 --> 00:18:40,720 Speaker 1: Stephan, can you just give us a sense of you 406 00:18:40,760 --> 00:18:44,120 Speaker 1: talk about artificial intelligence. Everyone's talking about artificial intelligence. 407 00:18:44,160 --> 00:18:44,879 Speaker 5: Could you just talk. 408 00:18:44,720 --> 00:18:47,879 Speaker 1: About how much that could expedite generally some of the 409 00:18:47,960 --> 00:18:50,520 Speaker 1: drug production that we're seeing. Just how much that could 410 00:18:50,560 --> 00:18:54,520 Speaker 1: really get us to achieve, you know, that cure for cancer, 411 00:18:54,840 --> 00:18:57,960 Speaker 1: that cure for als, cure for Alzheimer's. You know, it's 412 00:18:57,960 --> 00:18:59,840 Speaker 1: funny you're talking about sex and city. I sit around 413 00:18:59,840 --> 00:19:01,320 Speaker 1: and worry about these things. You know, what do we 414 00:19:01,320 --> 00:19:04,200 Speaker 1: secure these things? So I'm just wondering. You know, this 415 00:19:04,240 --> 00:19:05,800 Speaker 1: is going to be in our lifetime in the next 416 00:19:05,800 --> 00:19:09,160 Speaker 1: couple of years because of some of the machine learning. 417 00:19:10,560 --> 00:19:12,560 Speaker 8: Yes, So I think there's a few things to tear 418 00:19:12,640 --> 00:19:15,520 Speaker 8: part in your in your great question. First is I 419 00:19:15,520 --> 00:19:20,000 Speaker 8: think machine learning in academic labs, in research labs, in 420 00:19:20,000 --> 00:19:24,560 Speaker 8: industry is helping accelerate the understanding of a human body. 421 00:19:25,119 --> 00:19:26,720 Speaker 5: If you think about you know, this. 422 00:19:26,760 --> 00:19:29,760 Speaker 8: Is Alzheimer and others complicated disease that we do not 423 00:19:29,840 --> 00:19:33,960 Speaker 8: have solutions for yet as a society. It's because we 424 00:19:34,000 --> 00:19:37,280 Speaker 8: do not understand the biology. We do not understand how 425 00:19:37,280 --> 00:19:40,000 Speaker 8: the disease happened, how a disease evolved, and so we 426 00:19:40,040 --> 00:19:44,840 Speaker 8: are just trying things and some work, but very few work. 427 00:19:44,920 --> 00:19:47,280 Speaker 8: Most of them don't work because we're just trying and guessing. 428 00:19:47,800 --> 00:19:50,440 Speaker 8: If you look at biology, once we understand that something works, 429 00:19:50,800 --> 00:19:54,439 Speaker 8: then the industry can comes with very very good actions 430 00:19:54,760 --> 00:19:56,720 Speaker 8: to deal with those. So I think AI will accelerate 431 00:19:56,840 --> 00:19:59,680 Speaker 8: the understanding of biology, which would be fundamental to bring 432 00:19:59,720 --> 00:20:03,680 Speaker 8: new Then AI is already used to accelerate discovery in 433 00:20:03,760 --> 00:20:05,960 Speaker 8: terms of what tool do you go after a disease 434 00:20:06,000 --> 00:20:09,399 Speaker 8: once you understand it at modern already we have different 435 00:20:09,480 --> 00:20:12,960 Speaker 8: chemical matters that are generated by our AI system that 436 00:20:13,080 --> 00:20:16,000 Speaker 8: are helping us to accelerate the work that humans are doing. 437 00:20:16,000 --> 00:20:18,400 Speaker 8: So it's an accelerator to the teams. And then there's 438 00:20:18,400 --> 00:20:22,520 Speaker 8: a huge chapter on productivity. If you think about clinical 439 00:20:22,560 --> 00:20:26,400 Speaker 8: development phase one, two and three, it's basically doing experiment 440 00:20:26,440 --> 00:20:31,760 Speaker 8: in human getting the data, finding the doors, doing more experiment, 441 00:20:31,880 --> 00:20:34,479 Speaker 8: and when you have all studied on, you gather all 442 00:20:34,520 --> 00:20:37,360 Speaker 8: the data and you submit by realator. My point is 443 00:20:37,400 --> 00:20:40,399 Speaker 8: it's all about data. We are literally hundreds of business 444 00:20:40,480 --> 00:20:43,639 Speaker 8: processes that need to happen, and I think many of those, 445 00:20:43,720 --> 00:20:45,760 Speaker 8: if not most of those, you've got to be able 446 00:20:45,760 --> 00:20:49,440 Speaker 8: to apply AI to shrink time to go faster. An 447 00:20:49,440 --> 00:20:52,919 Speaker 8: example we shared in March in a Vaccine Day, the 448 00:20:52,960 --> 00:20:56,880 Speaker 8: team wrote a GPT to help us to do those selections. 449 00:20:56,920 --> 00:20:59,400 Speaker 8: When you do clinical study your phase one, you try 450 00:20:59,440 --> 00:21:01,720 Speaker 8: several those is and then based on the data you 451 00:21:01,760 --> 00:21:04,080 Speaker 8: get in the clinic, you decide which jows go into 452 00:21:04,080 --> 00:21:05,000 Speaker 8: your phase free. 453 00:21:05,400 --> 00:21:06,520 Speaker 5: Well, it used to. 454 00:21:06,520 --> 00:21:09,240 Speaker 8: Take around a monph to do that by having people 455 00:21:09,280 --> 00:21:11,879 Speaker 8: and meeting and experts looking at the data. Will we 456 00:21:11,920 --> 00:21:16,320 Speaker 8: develop a GPT that basically get all the data from 457 00:21:16,359 --> 00:21:19,439 Speaker 8: the clinical study and suggest to us a doose in 458 00:21:19,520 --> 00:21:22,480 Speaker 8: literally a minutes or two. That is already a tool 459 00:21:22,480 --> 00:21:25,680 Speaker 8: that has been developed that I've seen used at the company. 460 00:21:25,920 --> 00:21:27,760 Speaker 8: There's just one example. So here you go to shrink 461 00:21:27,800 --> 00:21:29,919 Speaker 8: them off. And if you do that on the hundreds 462 00:21:29,960 --> 00:21:32,680 Speaker 8: of business processes that have to happen in preparing the 463 00:21:32,760 --> 00:21:36,040 Speaker 8: drug for the clinic, the clinical testing, the analyzing of 464 00:21:36,080 --> 00:21:39,320 Speaker 8: the data, the communication with VFDA. I think you can 465 00:21:39,400 --> 00:21:41,679 Speaker 8: save a lot of time. I don't know yet, because 466 00:21:41,760 --> 00:21:44,000 Speaker 8: only history will show us in the next few years, 467 00:21:44,240 --> 00:21:46,960 Speaker 8: can you shave thirty percent, forty percent, fifty percent of 468 00:21:47,000 --> 00:21:49,440 Speaker 8: how many years it takes you to develop a drug? 469 00:21:49,520 --> 00:21:52,560 Speaker 2: I think it's going to be very significant. Stephan, We've 470 00:21:52,560 --> 00:21:54,320 Speaker 2: got to leave there. Is fantastic to catch up. This 471 00:21:54,800 --> 00:21:57,560 Speaker 2: amazing to listen to you talk about the efforts taking 472 00:21:57,560 --> 00:22:00,399 Speaker 2: place at Maderna. But then see have Stephan bands. This 473 00:22:00,600 --> 00:22:05,119 Speaker 2: is the Bloomberg Surveillance Podcast, bringing you the best in markets, economics, 474 00:22:05,160 --> 00:22:08,120 Speaker 2: and geopolitics. 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