1 00:00:03,560 --> 00:00:06,560 Speaker 1: From Bloomberg News and I Heart Radio. It's the big take. 2 00:00:06,920 --> 00:00:11,000 Speaker 1: I'm West Cassova today how researchers around the world are 3 00:00:11,119 --> 00:00:14,920 Speaker 1: using the big breakthrough behind the COVID vaccine to find 4 00:00:14,960 --> 00:00:26,119 Speaker 1: treatments for diseases of all kinds. Thanks to COVID, we're 5 00:00:26,239 --> 00:00:31,280 Speaker 1: all experts now in viruses and vaccines. M RNA, and 6 00:00:31,360 --> 00:00:34,880 Speaker 1: that last one, messenger RNA, is what we're talking about today. 7 00:00:35,000 --> 00:00:38,559 Speaker 1: It's the technology that made it possible to quickly develop 8 00:00:38,600 --> 00:00:41,879 Speaker 1: the COVID vaccine, and now researchers and drug makers are 9 00:00:42,080 --> 00:00:45,559 Speaker 1: racing to use the same technique for other illnesses, including 10 00:00:45,600 --> 00:00:49,800 Speaker 1: the big one to treat cancers. Before we dive into that, 11 00:00:49,880 --> 00:00:52,360 Speaker 1: maybe we should take a second to freshen up on 12 00:00:52,479 --> 00:00:55,360 Speaker 1: just what m RNA is and why it's such a 13 00:00:55,360 --> 00:00:59,520 Speaker 1: big deal. Most traditional vaccines, like for flu or for 14 00:00:59,600 --> 00:01:03,840 Speaker 1: measle months work by injecting a weekend or dead strain 15 00:01:04,040 --> 00:01:06,720 Speaker 1: of those viruses or a piece of them into your arm. 16 00:01:06,800 --> 00:01:09,640 Speaker 1: Your body's immune system to text the intruder and a 17 00:01:09,800 --> 00:01:13,240 Speaker 1: tax it and makes antibodies to fight off the disease 18 00:01:13,280 --> 00:01:16,280 Speaker 1: if you're ever exposed to it for real. Now, m 19 00:01:16,400 --> 00:01:21,840 Speaker 1: RNA vaccines are different mRNA is really the middleman, and 20 00:01:21,880 --> 00:01:26,560 Speaker 1: it brings the code for each gene to a machine 21 00:01:26,880 --> 00:01:32,039 Speaker 1: in our cell that reads the RNA and produces a 22 00:01:32,200 --> 00:01:36,840 Speaker 1: protein from that code. That's Dr Drew Wiseman, a vaccine 23 00:01:36,880 --> 00:01:40,080 Speaker 1: researcher at the University of Pennsylvania. He and his colleague 24 00:01:40,120 --> 00:01:44,280 Speaker 1: doctor Catalan Caroco develop the mr ANDA technology used in 25 00:01:44,319 --> 00:01:47,360 Speaker 1: the COVID shots. I'll talk more with Dr Wiseman in 26 00:01:47,360 --> 00:01:50,480 Speaker 1: a moment. M RNA, that middleman, he called it, is 27 00:01:50,600 --> 00:01:54,440 Speaker 1: part of your body's genetic structure. Its job is to 28 00:01:54,560 --> 00:01:57,840 Speaker 1: deliver instructions to yoursels. It tells them to make certain 29 00:01:57,840 --> 00:02:02,280 Speaker 1: proteins you need to live. An mRNA vaccine works by 30 00:02:02,360 --> 00:02:05,920 Speaker 1: injecting m RNA into your body that's been programmed to 31 00:02:06,000 --> 00:02:10,160 Speaker 1: tell yourselves to make proteins that match the proteins found 32 00:02:10,200 --> 00:02:13,360 Speaker 1: in the real virus, like the spike proteins sticking up 33 00:02:13,360 --> 00:02:15,320 Speaker 1: out of the coronavirus that makes those photos of it 34 00:02:15,360 --> 00:02:19,360 Speaker 1: looks so scary. Your body's immune system sees this foreign 35 00:02:19,440 --> 00:02:22,960 Speaker 1: material and makes anti bodies that can protect you later 36 00:02:23,120 --> 00:02:26,440 Speaker 1: if you're exposed to real COVID. M RNA research has 37 00:02:26,440 --> 00:02:29,120 Speaker 1: been happening for decades and a lot of scientists made 38 00:02:29,200 --> 00:02:32,800 Speaker 1: important contributions, but one nagging problem kept getting in the 39 00:02:32,800 --> 00:02:36,800 Speaker 1: way of an m RNA vaccine. The body was attacking 40 00:02:37,200 --> 00:02:41,359 Speaker 1: the m RNA itself before it could deliver its message. 41 00:02:42,000 --> 00:02:45,160 Speaker 1: This is where doctors Wiseman and Carrico come in. Their 42 00:02:45,200 --> 00:02:48,840 Speaker 1: breakthrough was to modify the RNA so your immune system 43 00:02:48,880 --> 00:02:51,600 Speaker 1: sees it as harmless and lets it do its job. 44 00:02:52,639 --> 00:02:56,239 Speaker 1: That opened the door to the COVID vaccine and using 45 00:02:56,720 --> 00:02:59,760 Speaker 1: mRNA for all kinds of other potential treatments and cures. 46 00:03:00,520 --> 00:03:03,359 Speaker 1: Their work won them a three million dollar Science Award, 47 00:03:03,480 --> 00:03:06,440 Speaker 1: and they're mentioned as possible contenders for a Nobel Prize. 48 00:03:09,120 --> 00:03:11,680 Speaker 1: None of this may have happened if it weren't for 49 00:03:11,720 --> 00:03:15,480 Speaker 1: a chance encounter. Wiseman and Kariko had at the photo 50 00:03:15,480 --> 00:03:22,399 Speaker 1: copy machine back in the nine es. She had been 51 00:03:22,400 --> 00:03:27,400 Speaker 1: working on it for around ten years and nobody was interested. 52 00:03:28,160 --> 00:03:32,640 Speaker 1: And we met and we started working together, and people 53 00:03:32,720 --> 00:03:37,200 Speaker 1: still weren't interested. But we were able to develop a 54 00:03:37,280 --> 00:03:42,640 Speaker 1: new way of working on RNA, and that led to 55 00:03:42,720 --> 00:03:48,720 Speaker 1: the development of nucleus side modified mRNA that people finally 56 00:03:48,760 --> 00:03:52,480 Speaker 1: became interested in. As Dr Wiseman and I got talking, 57 00:03:52,720 --> 00:03:56,360 Speaker 1: I asked him why mRNA research was such a hard sell. 58 00:03:57,040 --> 00:04:02,600 Speaker 1: RNA had been studied, it had been put into clinical trials, 59 00:04:02,720 --> 00:04:06,360 Speaker 1: and it had failed. So when Katie and I started 60 00:04:06,360 --> 00:04:11,360 Speaker 1: working on it, we developed new ways of making RNA 61 00:04:11,560 --> 00:04:15,440 Speaker 1: therapy work better. So is it an overstatement to say 62 00:04:15,560 --> 00:04:18,880 Speaker 1: that if you had not had a fateful encounter at 63 00:04:18,880 --> 00:04:21,800 Speaker 1: the copying machine, we might not have had the coronavirus 64 00:04:21,920 --> 00:04:24,880 Speaker 1: vaccine as quickly as we did. Um, Yeah, I think 65 00:04:24,960 --> 00:04:28,760 Speaker 1: that's true. That is pretty fascinating. Do you ever just 66 00:04:28,800 --> 00:04:31,400 Speaker 1: sort of look back on that moment and think, my goodness, 67 00:04:31,480 --> 00:04:35,400 Speaker 1: what if? Yeah, my wife and kids point that out 68 00:04:35,480 --> 00:04:38,640 Speaker 1: to us all of the time. And then when the 69 00:04:38,800 --> 00:04:43,960 Speaker 1: coronavirus first emerged in Wuhan, China, I believe you were 70 00:04:44,000 --> 00:04:47,640 Speaker 1: working on a flu vaccine and then you sort of 71 00:04:47,680 --> 00:04:51,560 Speaker 1: switched right because you saw a great promise in this. Exactly, 72 00:04:51,839 --> 00:04:55,840 Speaker 1: we were working on flu and other vaccines, and when 73 00:04:56,279 --> 00:05:01,280 Speaker 1: the COVID nineteen virus came out, we saw that as 74 00:05:01,360 --> 00:05:06,279 Speaker 1: a potential difficulty for the world, and we switched to 75 00:05:06,360 --> 00:05:10,760 Speaker 1: working on COVID nineteen. So you actually saw this and said, 76 00:05:11,040 --> 00:05:13,160 Speaker 1: wait a minute, this is going to be a very 77 00:05:13,200 --> 00:05:16,839 Speaker 1: big problem for the world, kind of like and went overstated, 78 00:05:16,880 --> 00:05:20,279 Speaker 1: but the world needs me, I guess so. I mean, 79 00:05:20,320 --> 00:05:23,440 Speaker 1: I'm kind of too humble to say something like that. 80 00:05:24,400 --> 00:05:29,320 Speaker 1: But when I saw the death and the disease come 81 00:05:29,360 --> 00:05:33,640 Speaker 1: out of Wuhan, China, my labs started working on it 82 00:05:33,920 --> 00:05:36,839 Speaker 1: with the idea of that this could be a really 83 00:05:36,880 --> 00:05:40,000 Speaker 1: bad thing and we needed to do something. And how 84 00:05:40,080 --> 00:05:43,480 Speaker 1: quickly did you realize that the work that you had 85 00:05:43,480 --> 00:05:47,560 Speaker 1: been doing for years was really very well suited for 86 00:05:47,800 --> 00:05:53,520 Speaker 1: this particular virus. So it was really immediate because we 87 00:05:53,600 --> 00:05:58,680 Speaker 1: saw this as a brand new, unknown virus that was 88 00:05:58,800 --> 00:06:05,719 Speaker 1: having worldwide potential damage and we needed to do something, 89 00:06:06,160 --> 00:06:10,120 Speaker 1: and the RNA that Katie and I had developed appeared 90 00:06:10,240 --> 00:06:14,040 Speaker 1: like a great potential way to address it. Now, the 91 00:06:14,120 --> 00:06:17,120 Speaker 1: UK has approved defineser Beyonce vaccine for use. That makes 92 00:06:17,120 --> 00:06:20,239 Speaker 1: Britain the first Western country to license a coronavirus vacts. 93 00:06:20,320 --> 00:06:22,760 Speaker 1: The fate of FISS COVID vaccine aur livees in the 94 00:06:22,800 --> 00:06:26,520 Speaker 1: hands of regulators who will be scrutinizing safety and efficacy. 95 00:06:26,560 --> 00:06:29,440 Speaker 1: Dating Certainly, everything that's been talked about from the FISER 96 00:06:29,520 --> 00:06:32,479 Speaker 1: and the Maderna vaccine as well up to date has 97 00:06:32,839 --> 00:06:36,479 Speaker 1: been very positive and leaves me optimistic about this vaccine 98 00:06:36,520 --> 00:06:40,479 Speaker 1: coming down the pipeline. So it was the goal now 99 00:06:40,560 --> 00:06:44,640 Speaker 1: to try to come up with a vaccine against coronavirus 100 00:06:44,920 --> 00:06:49,280 Speaker 1: that is the one that will attack them all exactly. 101 00:06:49,880 --> 00:06:54,880 Speaker 1: So we and others have been working on vaccines that 102 00:06:54,960 --> 00:06:59,920 Speaker 1: work against any virus that suddenly appears in the world. 103 00:07:00,320 --> 00:07:02,200 Speaker 1: Let me ask you about the business side of this. 104 00:07:02,600 --> 00:07:05,560 Speaker 1: So you paint a picture of a platform that could 105 00:07:05,720 --> 00:07:09,560 Speaker 1: quickly address a new disease, But the way the pharmaceutical 106 00:07:09,600 --> 00:07:11,680 Speaker 1: industry has worked is that they wanted to keep a 107 00:07:11,680 --> 00:07:16,040 Speaker 1: pretty close hold and newly developed therapies because they spend 108 00:07:16,080 --> 00:07:18,520 Speaker 1: a lot making them and they want to profit from them. 109 00:07:18,880 --> 00:07:21,840 Speaker 1: Do you see this as the sort of thing where 110 00:07:21,840 --> 00:07:26,960 Speaker 1: scientists and drug companies would actually share, or that there 111 00:07:27,000 --> 00:07:30,600 Speaker 1: would be proprietary versions of each of these platforms that 112 00:07:30,640 --> 00:07:35,000 Speaker 1: different manufacturers keep close to the best. So that brings 113 00:07:35,240 --> 00:07:43,239 Speaker 1: up a so see a economic worldview order that scientists 114 00:07:43,280 --> 00:07:46,800 Speaker 1: like me, we have a view that that we need 115 00:07:46,840 --> 00:07:51,880 Speaker 1: to develop something that can be rapidly used to treat 116 00:07:51,920 --> 00:07:54,600 Speaker 1: the world. How the world deals with that is a 117 00:07:54,640 --> 00:07:58,320 Speaker 1: whole separate and difficult thing. Is that something that you 118 00:07:58,600 --> 00:08:03,080 Speaker 1: discuss with your colleagues. We talked about it all the time, 119 00:08:03,880 --> 00:08:08,360 Speaker 1: sometimes not so kindly, about how the world sometimes deals 120 00:08:08,360 --> 00:08:12,560 Speaker 1: with it. Something that that has been central to my 121 00:08:13,120 --> 00:08:18,160 Speaker 1: really life since I was a tiny child is to 122 00:08:18,280 --> 00:08:24,040 Speaker 1: be able to develop therapies that can be used quickly 123 00:08:24,440 --> 00:08:29,920 Speaker 1: across the world and by the entire world to treat 124 00:08:30,320 --> 00:08:37,200 Speaker 1: and address any disease, any new change in life, change 125 00:08:37,200 --> 00:08:41,439 Speaker 1: in the world that happens. It's important that it's available 126 00:08:42,080 --> 00:08:47,280 Speaker 1: to the entire world to apply to the world's population, 127 00:08:48,320 --> 00:08:54,559 Speaker 1: not just a US or Europe based approach that can 128 00:08:54,559 --> 00:09:01,040 Speaker 1: be applied by wealthy nations and pharmaceutical companies. So I've 129 00:09:01,080 --> 00:09:06,040 Speaker 1: spent my life making therapies available to the world and 130 00:09:06,160 --> 00:09:09,480 Speaker 1: helping the world to develop it and apply it to 131 00:09:09,679 --> 00:09:15,160 Speaker 1: their particular diseases. But when you look at the distribution, 132 00:09:15,240 --> 00:09:18,880 Speaker 1: say of the coronavirus vaccine, it has been very uneven 133 00:09:18,920 --> 00:09:21,600 Speaker 1: around the world, and it's along predictable lines where rich 134 00:09:21,640 --> 00:09:24,960 Speaker 1: countries get it in less rich countries off and don't yees. 135 00:09:25,080 --> 00:09:28,920 Speaker 1: So that's what we've worked on. The minute the vaccine hit, 136 00:09:29,520 --> 00:09:32,959 Speaker 1: I had already been working in Thailand and they came 137 00:09:33,000 --> 00:09:36,439 Speaker 1: to me and said, we're worried that any vaccine that's 138 00:09:36,480 --> 00:09:40,640 Speaker 1: developed won't make it to us very quickly. So I 139 00:09:40,720 --> 00:09:44,480 Speaker 1: work with them to make their own vaccine and their 140 00:09:44,559 --> 00:09:49,880 Speaker 1: own company centers to be able to produce vaccine to 141 00:09:50,040 --> 00:09:55,040 Speaker 1: give to their population and surrounding populations. And we've done 142 00:09:55,080 --> 00:09:58,240 Speaker 1: the same thing in Africa, and we're doing the same 143 00:09:58,280 --> 00:10:02,880 Speaker 1: thing and all disadvantaged reasons of the world. Thank you 144 00:10:02,960 --> 00:10:05,080 Speaker 1: so much for taking the time to talk to me. 145 00:10:05,160 --> 00:10:08,199 Speaker 1: This was just fascinating. Thank you very much. I've enjoyed 146 00:10:08,240 --> 00:10:11,560 Speaker 1: talking with you. When the Big take is back, I 147 00:10:11,679 --> 00:10:15,920 Speaker 1: talked with Bloomberg Healthcare reporter Riley Griffin. She explains how 148 00:10:15,960 --> 00:10:19,480 Speaker 1: we got from Dr wise Men's research to big farmer 149 00:10:19,559 --> 00:10:23,520 Speaker 1: producing billions of doses of COVID vaccine in record time. 150 00:10:30,559 --> 00:10:34,880 Speaker 1: I'm happy to be here with Bloomberg reporter Riley Griffin. Riley, 151 00:10:35,240 --> 00:10:38,720 Speaker 1: there are a lot of companies that see a big 152 00:10:38,760 --> 00:10:41,839 Speaker 1: future in m R and A treatments, and you have 153 00:10:41,920 --> 00:10:45,040 Speaker 1: written a fascinating story about one of the big ones. Visor. 154 00:10:45,280 --> 00:10:48,079 Speaker 1: We're all familiar with Viser now because of the vaccine, 155 00:10:48,720 --> 00:10:53,720 Speaker 1: and it's an interesting story because before the pandemic, Fiser 156 00:10:54,080 --> 00:10:58,200 Speaker 1: had become something of sort of a staid company. They're huge, 157 00:10:58,600 --> 00:11:01,240 Speaker 1: they have a ton of money, and they used that 158 00:11:01,360 --> 00:11:04,720 Speaker 1: money to buy other drug companies instead of making their own. 159 00:11:04,760 --> 00:11:09,560 Speaker 1: But COVID changed that. COVID changed that absolutely. I would 160 00:11:09,559 --> 00:11:12,400 Speaker 1: say there was a shift right before COVID. Let me 161 00:11:12,480 --> 00:11:17,559 Speaker 1: take you back to Albert Borla takes the helm of 162 00:11:17,720 --> 00:11:21,599 Speaker 1: viser Um. He is the new CEO, and he ultimately 163 00:11:21,640 --> 00:11:24,160 Speaker 1: had a new vision for viser So this company that 164 00:11:24,280 --> 00:11:28,400 Speaker 1: had become quite a conglomerate with many of these big 165 00:11:28,520 --> 00:11:34,479 Speaker 1: blockbuster drugs that had gone off patent, think Viagra, think lipatore. 166 00:11:34,920 --> 00:11:37,439 Speaker 1: It hadn't had innovation in quite some time, and it 167 00:11:37,480 --> 00:11:40,959 Speaker 1: was looking to be more like the nimble biotechs that 168 00:11:41,000 --> 00:11:44,320 Speaker 1: were spurring a lot of investor interest, real growth stories. 169 00:11:44,720 --> 00:11:48,040 Speaker 1: And so Albert Borla had hived off the off patent 170 00:11:48,320 --> 00:11:53,640 Speaker 1: generic drug unit and sold it into another company. And ultimately, 171 00:11:54,240 --> 00:11:56,920 Speaker 1: you know, they were looking for science and that was 172 00:11:56,920 --> 00:12:00,800 Speaker 1: early hits. Albert bolas at a helm and they have 173 00:12:00,840 --> 00:12:03,720 Speaker 1: to decide what to do next. And they had already 174 00:12:03,920 --> 00:12:08,400 Speaker 1: been looking at these mRNA vaccines, but they weren't looking 175 00:12:08,440 --> 00:12:11,160 Speaker 1: at it for COVID. They've already been working on it precisely. 176 00:12:11,280 --> 00:12:15,960 Speaker 1: Wes so back in Visor clinches this deal with a 177 00:12:16,080 --> 00:12:19,840 Speaker 1: German company called bion Tech, and bion Tech was a 178 00:12:19,880 --> 00:12:23,800 Speaker 1: player in m RNA messenger RNA and Fiser had turned 179 00:12:23,800 --> 00:12:26,400 Speaker 1: to buy on Tech to work on an mRNA vaccine 180 00:12:26,440 --> 00:12:30,199 Speaker 1: for flu. Why did they think that it would transfer 181 00:12:30,480 --> 00:12:35,320 Speaker 1: naturally from flu to the coronavirus, which is a different 182 00:12:35,360 --> 00:12:38,959 Speaker 1: kind of virus. So there are a couple of benefits 183 00:12:38,960 --> 00:12:42,360 Speaker 1: to messenger RNA when it comes to vaccination, especially for 184 00:12:42,480 --> 00:12:48,840 Speaker 1: infectious disease UM. One is that messenger RNA ultimately allows 185 00:12:49,120 --> 00:12:53,440 Speaker 1: the body to be its own vaccine factory and create 186 00:12:53,480 --> 00:12:57,760 Speaker 1: those antibodies to thwart whatever the threat may be, in 187 00:12:57,760 --> 00:13:01,640 Speaker 1: this case COVID and so in the sense it compresses 188 00:13:01,640 --> 00:13:06,280 Speaker 1: the timeline. But also even more critically, the time to 189 00:13:06,400 --> 00:13:12,880 Speaker 1: manufacture mRNA is much shorter. So other vaccines require you too, 190 00:13:13,320 --> 00:13:19,319 Speaker 1: especially for flu. For example, you grow flu vaccines in eggs. 191 00:13:20,120 --> 00:13:22,840 Speaker 1: Um you can grow them in cells. There's there's a 192 00:13:22,840 --> 00:13:25,560 Speaker 1: cultivation process, and that takes a lot of time and 193 00:13:25,559 --> 00:13:28,520 Speaker 1: it takes a lot of resources. You don't have that here. 194 00:13:28,640 --> 00:13:31,760 Speaker 1: You create the messenger RNA and nothing needs to grow. 195 00:13:31,880 --> 00:13:34,560 Speaker 1: It goes straight into the body and so UM you 196 00:13:34,559 --> 00:13:38,640 Speaker 1: can also adapt messenger RNA quite quickly one time, Albert 197 00:13:38,640 --> 00:13:41,800 Speaker 1: Borla described it to me kind of like a VCR player. 198 00:13:42,200 --> 00:13:46,880 Speaker 1: You put the cassette in the tape. I'm dating myself there. 199 00:13:47,280 --> 00:13:49,800 Speaker 1: You put the tape in and you can take it 200 00:13:49,800 --> 00:13:53,640 Speaker 1: out and plug something else. The point being, Messenger RNA 201 00:13:53,800 --> 00:13:56,679 Speaker 1: is a really great tool if you want to compress 202 00:13:56,760 --> 00:13:59,520 Speaker 1: the production timeline, and that's what we needed in January 203 00:13:59,559 --> 00:14:04,439 Speaker 1: of money. So now, Fiser, you know how the story went. 204 00:14:04,600 --> 00:14:08,520 Speaker 1: They created this vaccine that was used millions millions people 205 00:14:08,520 --> 00:14:12,320 Speaker 1: around the world, and then when the different variants came out, 206 00:14:12,440 --> 00:14:15,520 Speaker 1: they tried to to match it using, as you describe, 207 00:14:15,559 --> 00:14:18,760 Speaker 1: the technology that allows them to kind of quickly readjust 208 00:14:18,840 --> 00:14:22,240 Speaker 1: it with you know, some kind of degree of efficacy. 209 00:14:22,520 --> 00:14:26,120 Speaker 1: Many folks know that this was a massive success. Billions 210 00:14:26,160 --> 00:14:29,320 Speaker 1: of doses shipped around the world to more than a 211 00:14:29,440 --> 00:14:33,000 Speaker 1: hundred and eighty countries, but few people know that this 212 00:14:33,120 --> 00:14:37,080 Speaker 1: vaccine doubled their revenue in a single year. That was 213 00:14:38,800 --> 00:14:42,280 Speaker 1: This year, Viser is expected to make more than a 214 00:14:42,360 --> 00:14:46,680 Speaker 1: hundred billion in revenue off of the vaccine. More than 215 00:14:46,720 --> 00:14:49,760 Speaker 1: half of that will come from the vaccine coupled with 216 00:14:49,880 --> 00:14:52,680 Speaker 1: the anti viral treatment that they've made for COVID paxilovid. 217 00:14:52,800 --> 00:14:56,200 Speaker 1: So the COVID business is more than half their business now. 218 00:14:56,720 --> 00:15:00,280 Speaker 1: But and this is an interesting thing in your story. 219 00:15:00,600 --> 00:15:04,840 Speaker 1: This creates a big problem because they are so geared 220 00:15:04,880 --> 00:15:08,800 Speaker 1: now towards coronavirus, and you know, let's all hope a 221 00:15:08,880 --> 00:15:11,160 Speaker 1: year from now we're not going to be talking about 222 00:15:11,200 --> 00:15:13,640 Speaker 1: this as often as we are now. They need to 223 00:15:13,640 --> 00:15:18,040 Speaker 1: do something else, and so they've sort of decided this 224 00:15:18,200 --> 00:15:24,160 Speaker 1: is their future for all kinds of other diseases. Absolutely, 225 00:15:24,200 --> 00:15:27,000 Speaker 1: and they're under pressure Wall Street. I mean this year, 226 00:15:27,040 --> 00:15:29,240 Speaker 1: I think this is going to be their most successful 227 00:15:29,320 --> 00:15:32,680 Speaker 1: year on record. Their stock is down and that's because 228 00:15:32,720 --> 00:15:35,240 Speaker 1: the fears that they just can't you do it again, 229 00:15:35,320 --> 00:15:37,720 Speaker 1: like it was one trick ponies sort of things. They're 230 00:15:37,920 --> 00:15:41,400 Speaker 1: victim of their own success and investors want to see 231 00:15:41,760 --> 00:15:46,400 Speaker 1: visibility into the future of their earnings potential. So what 232 00:15:46,440 --> 00:15:48,960 Speaker 1: are they going to do? So Fiser would say their 233 00:15:49,200 --> 00:15:52,040 Speaker 1: messenger are in a strategy is a big part of 234 00:15:52,080 --> 00:15:55,360 Speaker 1: their future. They are continuing to work with BioNTech on 235 00:15:55,440 --> 00:15:57,880 Speaker 1: flu that could come to market as soon as next year, 236 00:15:58,000 --> 00:16:01,320 Speaker 1: perhaps the year after if successful. Is it only that 237 00:16:01,400 --> 00:16:04,960 Speaker 1: the mrn A flu shot would be quicker to produce 238 00:16:05,000 --> 00:16:07,640 Speaker 1: so you get like a better assessment of which flu 239 00:16:07,800 --> 00:16:10,000 Speaker 1: is coming for us that year, or is it that 240 00:16:10,080 --> 00:16:13,440 Speaker 1: it's also more effective as of accin The latter is 241 00:16:13,480 --> 00:16:17,800 Speaker 1: the biggest question. So we're pretty certain that condensing that 242 00:16:17,840 --> 00:16:21,400 Speaker 1: production time is gonna position us better. That is a 243 00:16:21,440 --> 00:16:24,000 Speaker 1: bet that Fightser is making. It's also about that Maderna 244 00:16:24,040 --> 00:16:27,320 Speaker 1: is making I bet that Maderna has made prior to fight. Maderna, 245 00:16:27,360 --> 00:16:31,560 Speaker 1: of course, is the other very big manufacturer of the coronavirus. 246 00:16:31,640 --> 00:16:33,720 Speaker 1: You might have heard its name. Yeah, that is really 247 00:16:33,760 --> 00:16:36,440 Speaker 1: the first up to bat. That is the first real 248 00:16:36,600 --> 00:16:41,200 Speaker 1: trial of messenger RNA as a platform after the COVID vaccine, 249 00:16:41,240 --> 00:16:44,800 Speaker 1: so highly anticipated. Your question as to whether it will 250 00:16:44,840 --> 00:16:47,840 Speaker 1: be more effective, I can't tell you. Only the data will, 251 00:16:47,960 --> 00:16:52,760 Speaker 1: and we are watching for that data. One of the 252 00:16:52,840 --> 00:16:55,160 Speaker 1: questions that always comes up around drug companies is that 253 00:16:55,240 --> 00:16:58,680 Speaker 1: they spend a ton of money to develop these treatments 254 00:16:58,800 --> 00:17:01,840 Speaker 1: that are great benefit of the war old, and you know, 255 00:17:02,000 --> 00:17:03,880 Speaker 1: rich countries and rich people tend to get them in 256 00:17:03,920 --> 00:17:07,560 Speaker 1: less rich countries and people tend to not. The conditions 257 00:17:07,560 --> 00:17:11,240 Speaker 1: in which we've seen the COVID nineteen vaccines distributed are 258 00:17:11,680 --> 00:17:17,880 Speaker 1: unique to date governments have been the large purchasers Fiser 259 00:17:18,359 --> 00:17:22,399 Speaker 1: Moderna to they've priced the products differently for low, middle 260 00:17:22,640 --> 00:17:25,680 Speaker 1: and high income countries. I think there's a real question 261 00:17:25,720 --> 00:17:29,959 Speaker 1: of what happens after we switch to a commercial market, 262 00:17:30,160 --> 00:17:32,800 Speaker 1: and that is the plan next year. The plan next 263 00:17:32,840 --> 00:17:35,920 Speaker 1: year is that the US government will no longer pay 264 00:17:35,960 --> 00:17:39,760 Speaker 1: for COVID nineteen vaccines, let alone other COVID treatments, and 265 00:17:39,800 --> 00:17:45,360 Speaker 1: that this will shift to ensures and the more traditional 266 00:17:45,359 --> 00:17:48,760 Speaker 1: healthcare system in which we all get our drugs. Once 267 00:17:48,760 --> 00:17:51,359 Speaker 1: you shift to that commercial market, I think there's a 268 00:17:51,400 --> 00:17:54,200 Speaker 1: real question as to how these companies will price the products, 269 00:17:54,800 --> 00:17:57,800 Speaker 1: what that will mean in terms of access, what that 270 00:17:57,840 --> 00:18:01,119 Speaker 1: will mean in terms of global distribution, and where the 271 00:18:01,160 --> 00:18:04,560 Speaker 1: innovation really ultimately goes. Riley, thanks so much. This is 272 00:18:04,600 --> 00:18:08,560 Speaker 1: really terrific. Of course, thanks for having me. Coming up next, 273 00:18:08,600 --> 00:18:11,800 Speaker 1: the m RNA treatments we could see in the future 274 00:18:12,000 --> 00:18:24,040 Speaker 1: with Bloomberg's chief medical writer, Robert Langreth. We talked to 275 00:18:24,119 --> 00:18:27,600 Speaker 1: Dr Drew Wiseman about the future of m RNA technology 276 00:18:27,720 --> 00:18:30,880 Speaker 1: and Riley Griffin about what big companies like Fightser are 277 00:18:30,880 --> 00:18:33,359 Speaker 1: doing to try to develop it. So next I wanted 278 00:18:33,400 --> 00:18:37,640 Speaker 1: to check in with Bloomberg's chief medical writer Robert Langreth, 279 00:18:37,920 --> 00:18:41,480 Speaker 1: and asked him what new cures can we expect to 280 00:18:41,560 --> 00:18:44,600 Speaker 1: see coming soon? So the way you have to look 281 00:18:44,600 --> 00:18:47,359 Speaker 1: at this is, you know, at the beginning of a 282 00:18:47,400 --> 00:18:49,880 Speaker 1: new therapeutic area, you know, it sort of looks like, 283 00:18:50,119 --> 00:18:52,840 Speaker 1: you know, endless possibilities, and then it takes years and 284 00:18:52,920 --> 00:18:54,879 Speaker 1: years of research to figure out, you know, which are 285 00:18:54,880 --> 00:18:58,760 Speaker 1: those possibilities, Which is our therapeutic possibilities are you know, 286 00:18:58,880 --> 00:19:01,639 Speaker 1: really going to pan out with practical therapies that have 287 00:19:01,680 --> 00:19:05,439 Speaker 1: advantages over previous generations of therapies. So we're kind of 288 00:19:05,440 --> 00:19:09,040 Speaker 1: for m RNA, we're kind of at the endless possibility stage, 289 00:19:09,160 --> 00:19:11,960 Speaker 1: and we're still like doing the research to filter down 290 00:19:12,040 --> 00:19:14,199 Speaker 1: to figure out, like, which of those things are you know, 291 00:19:14,240 --> 00:19:17,400 Speaker 1: are really gonna work out in terms of a big 292 00:19:17,440 --> 00:19:20,840 Speaker 1: deal in terms of practical therapeutics. That's a really interesting 293 00:19:21,040 --> 00:19:23,120 Speaker 1: point because one of the things that we were hearing 294 00:19:23,160 --> 00:19:26,960 Speaker 1: when we were having our conversations was that mrn A 295 00:19:26,960 --> 00:19:31,080 Speaker 1: allowed the COVID vaccine to be developed much more quickly 296 00:19:31,240 --> 00:19:34,080 Speaker 1: than other vaccines, and it was able to sort of 297 00:19:34,280 --> 00:19:38,800 Speaker 1: short circuit the usual very lengthy process. Um. So you 298 00:19:38,880 --> 00:19:41,800 Speaker 1: seem to be saying that that won't necessarily be true 299 00:19:42,359 --> 00:19:48,240 Speaker 1: when they try to apply that same process to other diseases. Well, 300 00:19:48,359 --> 00:19:50,479 Speaker 1: so here's what I would say. I would say that, 301 00:19:50,520 --> 00:19:53,520 Speaker 1: you know, one of the clear and chief advantages of 302 00:19:53,640 --> 00:19:58,520 Speaker 1: m RNA over other types of therapeutic anti vaccine approach 303 00:19:58,640 --> 00:20:01,280 Speaker 1: is one of the clear advantages is in sort of 304 00:20:01,320 --> 00:20:06,200 Speaker 1: the speed of manufacturing and how quickly you can adjust that. Now, obviously, 305 00:20:06,359 --> 00:20:10,679 Speaker 1: you know, the pandemic highlighted one of m RNA's chief advantages, 306 00:20:10,720 --> 00:20:13,760 Speaker 1: which is just manufacturing something fast and kind of adjusting 307 00:20:13,800 --> 00:20:16,840 Speaker 1: on the fly. And it's not so clear yet how 308 00:20:16,880 --> 00:20:19,320 Speaker 1: important that advantage will be in you know, other non 309 00:20:19,359 --> 00:20:23,560 Speaker 1: emergency situations that the pandemic proved. One area that m 310 00:20:23,640 --> 00:20:26,679 Speaker 1: RNA will definitely work for is vaccines, and so that 311 00:20:26,760 --> 00:20:29,840 Speaker 1: sort of d risk to some extent other similar infectious 312 00:20:29,840 --> 00:20:32,639 Speaker 1: disease vaccine areas has suggests that, you know, there's nothing 313 00:20:32,720 --> 00:20:36,000 Speaker 1: stopping this from working in infectious disease anti viral vaccines, 314 00:20:36,359 --> 00:20:39,920 Speaker 1: and so that d risk other antiviral vaccines in terms 315 00:20:39,920 --> 00:20:42,560 Speaker 1: of m RNA. When you say d risk, what do 316 00:20:42,600 --> 00:20:44,960 Speaker 1: you mean? What is the risk? Here's what I mean 317 00:20:45,000 --> 00:20:48,080 Speaker 1: by D risk. Basically, it took some of the risk 318 00:20:48,119 --> 00:20:52,360 Speaker 1: out of developing other m RNA vaccines. For infectious disease vaccines, 319 00:20:52,640 --> 00:20:56,159 Speaker 1: it showed m RNA can definitively work, can succeed and 320 00:20:56,200 --> 00:21:01,360 Speaker 1: be effective foreign infectious viral disease. When you say risk, 321 00:21:01,560 --> 00:21:03,879 Speaker 1: do you mean that the risk that you spend a 322 00:21:03,880 --> 00:21:05,439 Speaker 1: lot of years and a ton of money and you 323 00:21:05,560 --> 00:21:09,440 Speaker 1: come up without a treatment. Yes, it just might not work. 324 00:21:09,480 --> 00:21:12,440 Speaker 1: There are other efficacy barriers that are just different from 325 00:21:12,720 --> 00:21:16,280 Speaker 1: infectious diseases. For COVID, we kind of we knew kind 326 00:21:16,280 --> 00:21:18,680 Speaker 1: of what the best thing to attack was pretty much 327 00:21:19,080 --> 00:21:21,400 Speaker 1: right off the bat, despite protein that stuck up from 328 00:21:21,400 --> 00:21:23,959 Speaker 1: the service, that was a thing we wanted to generate 329 00:21:24,040 --> 00:21:27,720 Speaker 1: an immune response against. Now, for cancer vaccines, and you're 330 00:21:27,720 --> 00:21:31,920 Speaker 1: trying to stimulate the body into generating an immune response 331 00:21:31,960 --> 00:21:34,440 Speaker 1: that targets cancer cells and kills them. That's what you're 332 00:21:34,440 --> 00:21:36,440 Speaker 1: trying to do, and that's why it's called cancer vaccines. 333 00:21:36,480 --> 00:21:40,520 Speaker 1: And it's been this really promising area that's never quite 334 00:21:40,560 --> 00:21:42,240 Speaker 1: worked out in a big way and you know, turned 335 00:21:42,280 --> 00:21:44,600 Speaker 1: out to be very very hard. So one of the 336 00:21:44,720 --> 00:21:47,040 Speaker 1: things about cancer, of course, is people think about we're 337 00:21:47,040 --> 00:21:49,399 Speaker 1: going to have a moonshot to cure cancer. But cancer 338 00:21:49,440 --> 00:21:52,840 Speaker 1: isn't one disease, it's many diseases. Does m r and 339 00:21:52,920 --> 00:21:57,719 Speaker 1: A hold any advantage in trying to treat many different 340 00:21:57,800 --> 00:22:01,600 Speaker 1: kinds of cancers in a way that exist instinc treatments do. Yeah. 341 00:22:01,720 --> 00:22:05,120 Speaker 1: So one of the most interesting areas that is being 342 00:22:05,160 --> 00:22:10,400 Speaker 1: tested with m RNA and cancer is personalized cancer vaccines. 343 00:22:11,040 --> 00:22:13,320 Speaker 1: And this is an area that play that's still in 344 00:22:13,359 --> 00:22:16,719 Speaker 1: a relatively early stages of testing and both Maderna and 345 00:22:16,800 --> 00:22:19,200 Speaker 1: bion Techno working on it, but this is an area 346 00:22:19,400 --> 00:22:22,080 Speaker 1: that kind of plays into the strengths of m RNA 347 00:22:22,200 --> 00:22:26,280 Speaker 1: and the ability to manufacture things quickly. So for personalized 348 00:22:26,320 --> 00:22:29,760 Speaker 1: cancer vaccines, you're actually taking samples of patients own tumors 349 00:22:30,160 --> 00:22:34,200 Speaker 1: and developing vaccines that would stimulate, uh, the immune system 350 00:22:34,240 --> 00:22:37,240 Speaker 1: attack characteristics of patients own tumors. This is like the 351 00:22:37,320 --> 00:22:40,040 Speaker 1: personalized vaccines, and the manufacturing has to go fast, and 352 00:22:40,119 --> 00:22:43,000 Speaker 1: that's something that can be done with m RNA because 353 00:22:43,200 --> 00:22:47,680 Speaker 1: m RNA the technology just allows kind of quick manufacturing 354 00:22:47,760 --> 00:22:51,520 Speaker 1: of individualized mRNA constructs of the pieces of m RNA 355 00:22:51,600 --> 00:22:53,480 Speaker 1: that are using the vaccines, and that's just something that 356 00:22:53,560 --> 00:22:57,840 Speaker 1: technology enables and it's one of the problems in developing 357 00:22:57,920 --> 00:23:01,600 Speaker 1: personalized cancer vaccines that the main facturing is very bespoke 358 00:23:02,359 --> 00:23:05,160 Speaker 1: uh and individualized, and that's hard to do with previous 359 00:23:05,240 --> 00:23:08,199 Speaker 1: technologies that were the production process is a bit slower. 360 00:23:08,440 --> 00:23:11,520 Speaker 1: So is that something that is showing promise in the 361 00:23:11,640 --> 00:23:15,720 Speaker 1: laboratory and that actually could go into production sooner? Is 362 00:23:15,800 --> 00:23:19,240 Speaker 1: that still in the early testing phases? That is in 363 00:23:19,359 --> 00:23:23,280 Speaker 1: the clinical trials right now? Both BioNTech and my Maderna 364 00:23:23,640 --> 00:23:26,080 Speaker 1: bi on Tech, for example, as a partnership with roche 365 00:23:26,440 --> 00:23:29,720 Speaker 1: as working on personalized cancer vaccines and melanoma and colorectal 366 00:23:29,800 --> 00:23:32,560 Speaker 1: cancer and that's in the second stage of human trials. 367 00:23:33,160 --> 00:23:37,320 Speaker 1: And Maderna is also working on personalized cancer vaccines. Right 368 00:23:37,359 --> 00:23:40,359 Speaker 1: So we talked about cancer, which is showing promise. What 369 00:23:40,520 --> 00:23:46,080 Speaker 1: other diseases are Pharmaceutical companies looking to urna to possibly 370 00:23:46,200 --> 00:23:50,440 Speaker 1: treat cancer, infectus disease and like vaccines, those are like 371 00:23:50,560 --> 00:23:54,280 Speaker 1: the furthest along and the most prominent merk. In August, 372 00:23:54,640 --> 00:23:56,440 Speaker 1: they said they would spend as much as three point 373 00:23:56,480 --> 00:23:59,320 Speaker 1: seven five billion to work on vaccines and cancer therapies 374 00:23:59,400 --> 00:24:01,840 Speaker 1: with a company called Orna Therapeutics, and they're developing this 375 00:24:02,000 --> 00:24:05,480 Speaker 1: like next generation technology called circular RNA, So there's a 376 00:24:05,560 --> 00:24:08,879 Speaker 1: couple of companies trying that. Like rare rare genetic diseases 377 00:24:08,960 --> 00:24:11,280 Speaker 1: is another big area. There's are diseases you probably like, 378 00:24:11,400 --> 00:24:13,119 Speaker 1: you know, names you haven't heard of, that you know, 379 00:24:13,160 --> 00:24:16,040 Speaker 1: affect a small number of people, but you know often 380 00:24:16,119 --> 00:24:18,240 Speaker 1: don't have good therapies, and if you can get something 381 00:24:18,320 --> 00:24:20,879 Speaker 1: to work, uh, you know, you could charge a very 382 00:24:20,960 --> 00:24:23,639 Speaker 1: high price, and patients are in desperate for treatments, and 383 00:24:23,640 --> 00:24:25,239 Speaker 1: there's a lot of these rare diseases. I would say 384 00:24:25,320 --> 00:24:28,600 Speaker 1: rare diseases is probably the third area that ARENA is 385 00:24:28,640 --> 00:24:31,200 Speaker 1: looking very promising. And but I can't say, you know, 386 00:24:31,280 --> 00:24:33,560 Speaker 1: there's a single disease that sticks out there. Test people 387 00:24:33,560 --> 00:24:35,960 Speaker 1: are testing trying a lot of different rare diseases right now. 388 00:24:37,800 --> 00:24:39,879 Speaker 1: So when you look down the road five years from now, 389 00:24:40,000 --> 00:24:42,840 Speaker 1: ten years from now, to the extent that you can do, 390 00:24:42,960 --> 00:24:47,520 Speaker 1: you think that RNA treatments are going to be transformative, 391 00:24:47,840 --> 00:24:50,600 Speaker 1: that they're going to really change the way drugs are 392 00:24:50,800 --> 00:24:55,080 Speaker 1: made and diseases are treated. Yeah, so here's the situation 393 00:24:55,240 --> 00:24:57,840 Speaker 1: kind of right now as I see it. There's definitely 394 00:24:57,880 --> 00:25:01,640 Speaker 1: going to be a number of vaccine results from other 395 00:25:01,760 --> 00:25:04,560 Speaker 1: types of RNA, m r and A vaccines coming out 396 00:25:05,000 --> 00:25:07,720 Speaker 1: in the next few years, and flu being the first one. 397 00:25:08,240 --> 00:25:11,720 Speaker 1: Will definitely get a better sense of like how effective 398 00:25:11,880 --> 00:25:14,879 Speaker 1: is this and what are the advantages disadvantages versus other 399 00:25:15,000 --> 00:25:19,040 Speaker 1: vaccine technologies and more mature vaccine areas such as influence 400 00:25:19,200 --> 00:25:22,080 Speaker 1: and such as uh there's another respiratory disease called r 401 00:25:22,280 --> 00:25:24,920 Speaker 1: s V. So vaccines will have a clear sense of 402 00:25:25,400 --> 00:25:27,680 Speaker 1: cancer within five years, will have a better sense of 403 00:25:27,880 --> 00:25:31,600 Speaker 1: are these personalized cancer vaccines? Are they working well? We'll 404 00:25:31,640 --> 00:25:33,159 Speaker 1: definitely have a bunch of results, will kind of have 405 00:25:33,160 --> 00:25:35,600 Speaker 1: a much better sense of that the rare diseases in 406 00:25:35,800 --> 00:25:39,000 Speaker 1: m RNA, the rare you know, genetic diseases, that's still 407 00:25:39,080 --> 00:25:41,000 Speaker 1: kind of wild card. It's really hard to know how 408 00:25:41,080 --> 00:25:42,800 Speaker 1: long that's going to take the play out. But what 409 00:25:42,920 --> 00:25:46,840 Speaker 1: I would say is that infectious disease viral vaccines, that's 410 00:25:46,880 --> 00:25:49,200 Speaker 1: the one thing that has proof of principle right now, 411 00:25:49,840 --> 00:25:51,760 Speaker 1: and the other areas they still need to prove it. 412 00:25:52,440 --> 00:25:55,760 Speaker 1: Many things to doctor Drew Weissman, as well as Bloomberg's 413 00:25:55,760 --> 00:25:59,200 Speaker 1: own Riley Griffin and Robert Langrith. You can find Riley's 414 00:25:59,240 --> 00:26:03,080 Speaker 1: full piece of out Fiser's next act over at Bloomberg 415 00:26:03,119 --> 00:26:06,879 Speaker 1: dot com. Thanks for listening to us here at The 416 00:26:06,920 --> 00:26:10,920 Speaker 1: Big Take, the daily podcast from Bloomberg and I Heart Radio. 417 00:26:11,440 --> 00:26:14,240 Speaker 1: For more shows from my Heart Radio, visit the i 418 00:26:14,400 --> 00:26:19,000 Speaker 1: Heart Radio app, Apple Podcasts, or wherever you listen. Read 419 00:26:19,040 --> 00:26:22,920 Speaker 1: Today's story and subscribe to our daily newsletter at Bloomberg 420 00:26:23,000 --> 00:26:26,600 Speaker 1: dot com slash Big Take, and we'd love to hear 421 00:26:26,640 --> 00:26:30,400 Speaker 1: from you. Email us with questions or comments to Big 422 00:26:30,480 --> 00:26:35,000 Speaker 1: Take at Bloomberg dot net. The supervising producer of The 423 00:26:35,040 --> 00:26:39,240 Speaker 1: Big Take is Vicky Burgalina. Our senior producer is Katherine Fink. 424 00:26:39,720 --> 00:26:43,440 Speaker 1: Our producers are Moe Barrow and Michael Falerro Hill de 425 00:26:43,520 --> 00:26:48,720 Speaker 1: Garcia is our engineer. Original music by Leo Sidrin. I'm 426 00:26:48,800 --> 00:26:52,400 Speaker 1: west Kosova. We'll be back tomorrow with another Big Take.