1 00:00:04,760 --> 00:00:08,080 Speaker 1: Millions of Americans take prescription drugs, but how many of 2 00:00:08,160 --> 00:00:11,039 Speaker 1: us really know how they were developed or how they 3 00:00:11,039 --> 00:00:15,280 Speaker 1: even work. For most of us, drugs are just there 4 00:00:15,800 --> 00:00:18,479 Speaker 1: when you pick up your prescription from the pharmacy. You 5 00:00:18,520 --> 00:00:20,599 Speaker 1: don't think about the billions of dollars that went into 6 00:00:20,640 --> 00:00:25,160 Speaker 1: the research or the scientific breakthroughs that paved the way. 7 00:00:26,840 --> 00:00:31,120 Speaker 1: Welcome to Prognosis, a podcast about health, medical technology, and 8 00:00:31,160 --> 00:00:34,640 Speaker 1: the mind blowing innovation that's underway across the globe. I'm 9 00:00:34,640 --> 00:00:38,760 Speaker 1: your host, Michelle fay Cortez. This week, we're hearing the 10 00:00:38,800 --> 00:00:41,839 Speaker 1: story of the strange, circuitous path of one drug from 11 00:00:41,840 --> 00:00:45,280 Speaker 1: the Eureka moment to the market. It's a story about 12 00:00:45,320 --> 00:00:49,440 Speaker 1: a Nobel Prize winner, cutting edge genetic research, billions of 13 00:00:49,440 --> 00:01:00,520 Speaker 1: pharmaceutical dollars, and of all things, a worm. In August, 14 00:01:00,560 --> 00:01:05,000 Speaker 1: all Nylum, a seven billion dollar biotechnology company, one approval 15 00:01:05,040 --> 00:01:07,800 Speaker 1: to market its first drug. The company hopes it will 16 00:01:07,800 --> 00:01:10,759 Speaker 1: save the lives of roughly fifty patients who suffer from 17 00:01:10,760 --> 00:01:16,840 Speaker 1: a rare and ultimately fatal disorder. But the price sounds outrageous. 18 00:01:19,160 --> 00:01:22,960 Speaker 1: Beach patient, or rather the federal government and their insurance companies, 19 00:01:23,240 --> 00:01:26,040 Speaker 1: will have to pay about three forty five thousand dollars 20 00:01:26,080 --> 00:01:30,640 Speaker 1: every year. Here's Rebecca's Balding, Bloomberg's Boston Biotech Reporter on 21 00:01:30,680 --> 00:01:45,200 Speaker 1: the sixteen year journey of a single drug. I'm here 22 00:01:45,240 --> 00:01:48,840 Speaker 1: in Cambridge, Massachusetts, the global capital of the drug industry. 23 00:01:49,520 --> 00:01:52,640 Speaker 1: As a pharmaceutical executive told me recently, what New York 24 00:01:52,720 --> 00:01:55,920 Speaker 1: is to finance and Paris is to culture, Cambridge is 25 00:01:55,960 --> 00:01:59,600 Speaker 1: to science. Its heart is a place called Kendall Square, 26 00:01:59,680 --> 00:02:02,480 Speaker 1: next at M. I. T. Kendall Square used to be 27 00:02:02,560 --> 00:02:06,640 Speaker 1: a rundown neighborhood full of empty candy factories. Now the 28 00:02:06,640 --> 00:02:09,600 Speaker 1: neighborhood is full of gleaming buildings and companies with names 29 00:02:09,600 --> 00:02:16,200 Speaker 1: that suggest scientific expertise and mystery genzyme biogen voyager. Their 30 00:02:16,200 --> 00:02:19,760 Speaker 1: market values are usually counted by the billions. When you're 31 00:02:19,760 --> 00:02:22,000 Speaker 1: walking around the streets, you get the feeling that people 32 00:02:22,080 --> 00:02:25,200 Speaker 1: hidden behind glass walls are making decisions about the future, 33 00:02:25,960 --> 00:02:30,000 Speaker 1: possibly your future. Al Nylum is one of those companies. 34 00:02:31,639 --> 00:02:34,680 Speaker 1: All Nylum is named after the center star in Orion's belt, 35 00:02:34,800 --> 00:02:38,880 Speaker 1: the brightest in the constellation. It's a fitting metaphor. Al 36 00:02:38,960 --> 00:02:44,240 Speaker 1: Nylum is the platonic ideal of a biotech company. Sixteen 37 00:02:44,320 --> 00:02:46,840 Speaker 1: years ago, a group of scientists here wanted to take 38 00:02:46,880 --> 00:02:50,120 Speaker 1: an obscure insight about genetics and turn it into a drug. 39 00:02:50,960 --> 00:02:53,919 Speaker 1: This is the story about that drug, but it's also 40 00:02:53,960 --> 00:02:57,079 Speaker 1: a story about the biotech industry itself and what happens 41 00:02:57,120 --> 00:03:00,399 Speaker 1: behind those glass walls and it all be I'm back 42 00:03:00,400 --> 00:03:02,920 Speaker 1: in the late seventies when a story in the Washington 43 00:03:03,000 --> 00:03:05,560 Speaker 1: Post piqued the interest of a high school student named 44 00:03:05,600 --> 00:03:10,400 Speaker 1: Craig Mellow. Today, Craig is fifty eight years old. I 45 00:03:10,440 --> 00:03:12,840 Speaker 1: spoke to him on the campus of the Massachusetts Medical 46 00:03:12,880 --> 00:03:16,360 Speaker 1: Center in Worcester, where he runs a genetics lab. I 47 00:03:16,440 --> 00:03:19,400 Speaker 1: don't really know what to call Craig. My producers tell 48 00:03:19,440 --> 00:03:22,320 Speaker 1: me first names worked better for podcasts, But the reality 49 00:03:22,400 --> 00:03:25,920 Speaker 1: is Craig has a Nobel Prize. But Dr Mellow doesn't 50 00:03:25,960 --> 00:03:29,600 Speaker 1: sound right either. Craig is tall and athletic, with long 51 00:03:29,639 --> 00:03:32,320 Speaker 1: gray hair. I would pay him more as an enlightened 52 00:03:32,320 --> 00:03:37,040 Speaker 1: surfer pondering the universe than a celebrated molecular biologist. Here's 53 00:03:37,040 --> 00:03:41,400 Speaker 1: what started his interest in genetics. I got really fascinated 54 00:03:41,480 --> 00:03:45,480 Speaker 1: by genetics when I learned that the human insulin gene 55 00:03:45,920 --> 00:03:50,440 Speaker 1: could be expressed in bacteria that you could actually take 56 00:03:50,480 --> 00:03:53,520 Speaker 1: the human gene for insulin, put it into bacteria, and 57 00:03:53,520 --> 00:03:56,520 Speaker 1: the bacteria could make the human insulin protein. And I 58 00:03:56,560 --> 00:03:59,600 Speaker 1: read that in the Washington Post and I said, you know, 59 00:03:59,640 --> 00:04:04,160 Speaker 1: that's been to myself. That's incredibly powerful. Most people didn't 60 00:04:04,200 --> 00:04:07,480 Speaker 1: know it yet, but that discovery was the biotechnology industry's 61 00:04:07,600 --> 00:04:14,480 Speaker 1: big bang, the moment that would change medicine forever. Researchers 62 00:04:14,520 --> 00:04:17,839 Speaker 1: had shown that could make insulin a human hormone in 63 00:04:17,920 --> 00:04:21,880 Speaker 1: a lab. Here's why that's such a big deal. Most 64 00:04:21,920 --> 00:04:25,719 Speaker 1: medicines before then had been simple chemicals. Truth be told, 65 00:04:25,760 --> 00:04:29,239 Speaker 1: many of them didn't even work that well. Synthetic insulin 66 00:04:29,320 --> 00:04:31,960 Speaker 1: was one of the first medicines made from human cells, 67 00:04:32,520 --> 00:04:36,200 Speaker 1: and it worked beautifully. Diabetics who had previously relied on 68 00:04:36,279 --> 00:04:39,640 Speaker 1: insulin made from pigs and cattle finally had the real thing. 69 00:04:40,720 --> 00:04:42,919 Speaker 1: It was also an innovation that made Craig want to 70 00:04:42,920 --> 00:04:46,800 Speaker 1: go into medical research. Yeah. I always was interested in 71 00:04:46,880 --> 00:04:50,680 Speaker 1: the history of life and fossils, but the genetic information 72 00:04:50,760 --> 00:04:55,520 Speaker 1: inside of every cell in our bodies is a living fossil, 73 00:04:55,839 --> 00:04:59,880 Speaker 1: I'd say. I was so intrigued by the fundamental quest 74 00:05:00,000 --> 00:05:03,640 Speaker 1: gens of origins, even if it weren't applicable to anything. 75 00:05:04,080 --> 00:05:06,680 Speaker 1: I think it would be really fascinating and important to 76 00:05:06,720 --> 00:05:09,760 Speaker 1: try to understand this. But of course it turns out 77 00:05:09,839 --> 00:05:14,599 Speaker 1: that by understanding fundamental mechanisms of of biology, we can 78 00:05:14,640 --> 00:05:19,000 Speaker 1: make really important medicines like insulin. Craig decided to study 79 00:05:19,120 --> 00:05:22,040 Speaker 1: DNA specifically how he might be able to tinker with it. 80 00:05:22,600 --> 00:05:25,839 Speaker 1: Put simply, DNA as our body's blueprint, the master code 81 00:05:25,839 --> 00:05:28,880 Speaker 1: that lays out all of its processes. But it's just 82 00:05:29,160 --> 00:05:32,400 Speaker 1: the blueprint. To actually create life, you need a builder 83 00:05:32,440 --> 00:05:36,800 Speaker 1: and raw materials too. That's where a molecule called ribonucleic 84 00:05:36,880 --> 00:05:40,880 Speaker 1: acid or RNA comes in. If you're wondering what any 85 00:05:40,960 --> 00:05:43,640 Speaker 1: of this has to do with developing a drug, specifically 86 00:05:43,680 --> 00:05:47,520 Speaker 1: al Nylums drug, stick with me. But first let's go 87 00:05:47,560 --> 00:05:51,680 Speaker 1: over some basic molecular biology. It's really simple, I promise. 88 00:05:52,640 --> 00:05:56,120 Speaker 1: If DNA is the blueprint, RNA is the contractor that 89 00:05:56,160 --> 00:05:59,480 Speaker 1: gets hired to actually build the building. It reads the 90 00:05:59,600 --> 00:06:03,480 Speaker 1: architect plans and carries them out. In this scenario, Proteins 91 00:06:03,480 --> 00:06:06,440 Speaker 1: are the equivalence of brick or drywall. Proteins are what 92 00:06:06,480 --> 00:06:08,600 Speaker 1: the body is actually made up of. They make up 93 00:06:08,640 --> 00:06:12,760 Speaker 1: your hair, your eyes, your heart, every cell. RNA is 94 00:06:12,800 --> 00:06:15,640 Speaker 1: what creates them by reading the DNA's code and turning 95 00:06:15,640 --> 00:06:19,320 Speaker 1: that code into proteins. Most of the time this goes well, 96 00:06:19,640 --> 00:06:22,800 Speaker 1: except when there's an air in the blueprint. Defective DNA 97 00:06:23,080 --> 00:06:27,560 Speaker 1: turns into defective proteins, which in turn caused disease. And 98 00:06:27,560 --> 00:06:30,680 Speaker 1: in all of these cases, even though DNA has an error, 99 00:06:30,760 --> 00:06:35,680 Speaker 1: the RNA still repeats it. An error in one protein 100 00:06:35,800 --> 00:06:39,320 Speaker 1: may sound benign, but it's not. It's what causes disease. 101 00:06:39,800 --> 00:06:43,080 Speaker 1: That's why tinkering with DNA was so allerting for researchers. 102 00:06:43,520 --> 00:06:46,320 Speaker 1: If scientists like Craig could figure out how to change 103 00:06:46,360 --> 00:06:49,880 Speaker 1: the blueprint, they could prevent disease. That's key for later 104 00:06:49,920 --> 00:06:51,960 Speaker 1: on in the episode when we'll hear about how this 105 00:06:52,040 --> 00:06:55,560 Speaker 1: drug was actually developed. But back when Craig was first tinkering, 106 00:06:56,000 --> 00:06:58,279 Speaker 1: he was about as far as you could be from 107 00:06:58,279 --> 00:07:02,679 Speaker 1: developing a drug for human beings. For his experiments, Craig 108 00:07:02,720 --> 00:07:10,080 Speaker 1: worked on worms, yes, worms, specifically a species known as C. Elegants. 109 00:07:10,120 --> 00:07:13,480 Speaker 1: It's a favorite creature among genetic researchers because it's so simple. 110 00:07:14,040 --> 00:07:16,840 Speaker 1: It only has about a thousand cells humans have thirty 111 00:07:16,880 --> 00:07:21,480 Speaker 1: seven trillion. It's tiny only about one millimeter long and transparent. 112 00:07:21,920 --> 00:07:25,080 Speaker 1: You can see through all those cells under microscope. Despite 113 00:07:25,080 --> 00:07:28,400 Speaker 1: its small size, it has a nervous system. That's key. 114 00:07:28,600 --> 00:07:31,080 Speaker 1: The hope is that discoveries made on these animals might 115 00:07:31,160 --> 00:07:34,480 Speaker 1: also work in people. Craig had always been interested in 116 00:07:34,560 --> 00:07:38,200 Speaker 1: changes in DNA, but when he started his scientific career 117 00:07:38,240 --> 00:07:43,120 Speaker 1: after grad school, something surprising happened. Other researchers around the 118 00:07:43,120 --> 00:07:47,840 Speaker 1: country were experimenting not on DNA but on RNA. They 119 00:07:47,840 --> 00:07:52,440 Speaker 1: were getting strange, even inexplicable results. Craig decided to try 120 00:07:52,480 --> 00:07:58,320 Speaker 1: it for himself. I discovered some really weird things were happening, 121 00:07:58,680 --> 00:08:03,240 Speaker 1: really really awful, but weird. When Craig injected his worms 122 00:08:03,240 --> 00:08:05,760 Speaker 1: with DNA, he would have to inject them into the 123 00:08:05,800 --> 00:08:09,560 Speaker 1: worm's reproductive organs. Genetic changes would then appear in the 124 00:08:09,560 --> 00:08:13,280 Speaker 1: next generation and its children. But if he missed and 125 00:08:13,360 --> 00:08:17,520 Speaker 1: accidentally injected the DNA into a worm's gut, nothing would happen. 126 00:08:18,160 --> 00:08:20,600 Speaker 1: There wouldn't be any changes in that worm where his children. 127 00:08:21,080 --> 00:08:25,480 Speaker 1: The DNA would just degrade disappear. But with r n A, 128 00:08:25,560 --> 00:08:28,640 Speaker 1: Craig could inject the worm anywhere, even in the gut, 129 00:08:29,160 --> 00:08:31,960 Speaker 1: and it would still have an effect. What was even 130 00:08:32,040 --> 00:08:35,320 Speaker 1: stranger was that these effects were so strong and only 131 00:08:35,320 --> 00:08:37,760 Speaker 1: would it last through that animal's life, but it would 132 00:08:37,800 --> 00:08:41,720 Speaker 1: pass on to the next generation. Craig didn't know why 133 00:08:41,760 --> 00:08:45,280 Speaker 1: that would be. All he knew is that that shouldn't 134 00:08:45,280 --> 00:08:49,000 Speaker 1: be happening. He decided to call his longtime collaborator, Dr. 135 00:08:49,080 --> 00:08:54,240 Speaker 1: Andrew Fire. It was very surprising, and I, of course 136 00:08:54,520 --> 00:08:58,120 Speaker 1: I was very very interested in, you know, how that 137 00:08:58,200 --> 00:09:01,960 Speaker 1: could be happening and it. I called up Handy and 138 00:09:02,000 --> 00:09:06,400 Speaker 1: we spent hours talking about experiments. We talked about how 139 00:09:06,480 --> 00:09:12,720 Speaker 1: this might what this might be. Slowly they realized what 140 00:09:12,760 --> 00:09:16,840 Speaker 1: they had discovered. By tinkering with RNA instead of DNA, 141 00:09:17,559 --> 00:09:20,480 Speaker 1: they could eliminate a wrong message sent by a bad 142 00:09:20,720 --> 00:09:24,600 Speaker 1: DNA blueprint. It was as if the contractor never showed 143 00:09:24,640 --> 00:09:29,320 Speaker 1: up for work. The faulty building never got built. Craig 144 00:09:29,440 --> 00:09:33,240 Speaker 1: and doctor Fire continued to experiment and began publishing their results. 145 00:09:33,880 --> 00:09:35,960 Speaker 1: In two thousand and six, they would win the Nobel 146 00:09:36,040 --> 00:09:40,439 Speaker 1: Prize for discovering the phenomenon now known as RNA interference. 147 00:09:41,160 --> 00:09:43,960 Speaker 1: People hoped it could usher an as dramatic a medical 148 00:09:44,040 --> 00:09:47,520 Speaker 1: revolution as the insulin discovery Craig had read about in 149 00:09:47,559 --> 00:09:52,400 Speaker 1: the Washington Post eight years earlier. Their work delighted scientists 150 00:09:52,880 --> 00:09:57,000 Speaker 1: could researchers finally be able to treat genetic disease, but 151 00:09:57,080 --> 00:10:00,720 Speaker 1: it also fired up entrepreneurs. Was their need to be made? 152 00:10:01,400 --> 00:10:11,720 Speaker 1: The race was on. A research scientist named Rachel Myers 153 00:10:11,800 --> 00:10:15,920 Speaker 1: answered the call back in Cambridge, Massachusetts. Rachel signed on 154 00:10:15,960 --> 00:10:19,600 Speaker 1: as one of al nylum's first employees. Rachel has a 155 00:10:19,640 --> 00:10:23,640 Speaker 1: near perfect scientific resume. She earned her PhD from m 156 00:10:23,679 --> 00:10:26,480 Speaker 1: I T and completed a post doc at Harvard Medical School. 157 00:10:27,200 --> 00:10:30,040 Speaker 1: She was working at another hot biotechnology company in town 158 00:10:30,080 --> 00:10:31,800 Speaker 1: when she got the call to join a nylum in 159 00:10:31,840 --> 00:10:36,360 Speaker 1: two thousand three. She stayed for fourteen years. Most of 160 00:10:36,400 --> 00:10:40,280 Speaker 1: that time I spent working on one central problem, one 161 00:10:40,320 --> 00:10:43,560 Speaker 1: that's pretty common in the biotech industry. How do you 162 00:10:43,640 --> 00:10:49,360 Speaker 1: turn breakthrough research into something patients can actually use? Very quickly, 163 00:10:49,360 --> 00:10:53,200 Speaker 1: it became clear that there was one enormous challenge, and 164 00:10:53,240 --> 00:10:57,440 Speaker 1: that challenge is what we call the delivery challenge. In 165 00:10:57,559 --> 00:10:59,920 Speaker 1: order to make a drug that works by this mechan 166 00:11:00,080 --> 00:11:02,120 Speaker 1: is and you have to make a piece of RNA 167 00:11:02,520 --> 00:11:04,800 Speaker 1: and you have to introduce it into the cells. And 168 00:11:05,200 --> 00:11:07,240 Speaker 1: that sounds easy when I say it, but it turns 169 00:11:07,240 --> 00:11:10,960 Speaker 1: out that's extremely difficult, and it's difficult because an RNA 170 00:11:11,120 --> 00:11:15,920 Speaker 1: drug has two properties that make it very much not 171 00:11:16,520 --> 00:11:21,040 Speaker 1: a good kind of medicine. And the simple properties are 172 00:11:21,160 --> 00:11:26,439 Speaker 1: it's um got very high charge and it's big, very 173 00:11:26,520 --> 00:11:33,200 Speaker 1: very big. So it's probably, let's see, thirty times larger 174 00:11:33,240 --> 00:11:35,680 Speaker 1: than a normal drug like an aspirin that you would take, 175 00:11:36,600 --> 00:11:39,839 Speaker 1: and that makes it very difficult to think about how 176 00:11:39,880 --> 00:11:42,600 Speaker 1: you deliver it, get it to the places it needs 177 00:11:42,640 --> 00:11:45,480 Speaker 1: to go. At what point did you realize that that 178 00:11:45,600 --> 00:11:48,480 Speaker 1: was going to be the major challenge in the very beginning, 179 00:11:48,480 --> 00:11:52,240 Speaker 1: and in fact, people all over the world talked about 180 00:11:52,320 --> 00:11:56,080 Speaker 1: that as the challenge with developing drugs and RNA interference 181 00:11:56,160 --> 00:11:58,800 Speaker 1: the delivery challenge. So you joined on nyleum knowing that 182 00:11:58,800 --> 00:12:01,600 Speaker 1: that was going to be the major little If you 183 00:12:01,679 --> 00:12:04,480 Speaker 1: miss some of that, like RNA having a high charge 184 00:12:04,520 --> 00:12:08,079 Speaker 1: and being large, don't worry. You're not alone. You don't 185 00:12:08,080 --> 00:12:10,840 Speaker 1: have to understand the details. But here's why it matters. 186 00:12:11,320 --> 00:12:13,960 Speaker 1: What made r N a I so interesting in worms 187 00:12:14,000 --> 00:12:16,080 Speaker 1: was that you can inject it anywhere and it worked. 188 00:12:16,920 --> 00:12:21,240 Speaker 1: But that was worms. This was humans, and taking a 189 00:12:21,320 --> 00:12:25,400 Speaker 1: drug from worms to humans is almost impossible. In fact, 190 00:12:25,440 --> 00:12:27,560 Speaker 1: as a reporter, I'm surprised to learn that's how really 191 00:12:27,600 --> 00:12:29,840 Speaker 1: the science was in two thousand two when they started. 192 00:12:30,640 --> 00:12:33,520 Speaker 1: If someone pitched me today with a scientific studies saying 193 00:12:33,559 --> 00:12:37,200 Speaker 1: they cured disease and worms, I would honestly think they 194 00:12:37,200 --> 00:12:40,520 Speaker 1: were Charlottean trying to get one over on unsuspecting reporters 195 00:12:40,679 --> 00:12:49,720 Speaker 1: or investors. Worms are easy, humans are hard. Throughout this time, 196 00:12:49,840 --> 00:12:52,840 Speaker 1: Rachel and her colleagues were also thinking about another challenge, 197 00:12:53,480 --> 00:12:57,680 Speaker 1: what disease should they even focus on. Drug companies must 198 00:12:57,760 --> 00:13:01,360 Speaker 1: choose which diseases they attack, and maybe the most important 199 00:13:01,400 --> 00:13:04,760 Speaker 1: decision they make. These decisions aren't made in a vacuum. 200 00:13:04,840 --> 00:13:07,920 Speaker 1: Drugs don't work in every illness, but in this case, 201 00:13:08,400 --> 00:13:12,280 Speaker 1: in theory, at least, discovery could cure perhaps an unlimited 202 00:13:12,440 --> 00:13:18,640 Speaker 1: array of diseases very quickly. However, that field narrowed, so 203 00:13:18,679 --> 00:13:23,040 Speaker 1: as we continue to develop the technology, we learned something 204 00:13:23,160 --> 00:13:28,040 Speaker 1: really important. The delivery challenge and the solution to the 205 00:13:28,040 --> 00:13:32,160 Speaker 1: delivery problem lead us to a particular tissue, a particular 206 00:13:32,200 --> 00:13:34,120 Speaker 1: part of the body, and that part of the body 207 00:13:34,200 --> 00:13:37,640 Speaker 1: is the liver. And that was an enormous and important 208 00:13:38,280 --> 00:13:42,200 Speaker 1: finding that the best candidates we had for making drugs 209 00:13:42,480 --> 00:13:45,160 Speaker 1: worked by going to the liver. And so once I 210 00:13:45,240 --> 00:13:47,360 Speaker 1: tell you that, then you say, okay. So now if 211 00:13:47,400 --> 00:13:52,000 Speaker 1: we think about diseases, we have to think in a 212 00:13:52,160 --> 00:13:55,120 Speaker 1: somewhat refined way, right, and we have to think about 213 00:13:55,160 --> 00:13:59,920 Speaker 1: diseases for which a drug going to the liver is important. 214 00:14:00,280 --> 00:14:04,440 Speaker 1: So we started a very elaborate exercise to ask the question, 215 00:14:04,760 --> 00:14:09,280 Speaker 1: if we look out across medicine, what are the important 216 00:14:09,800 --> 00:14:13,440 Speaker 1: diseases with unmet needs where a drug going to the 217 00:14:13,480 --> 00:14:17,439 Speaker 1: liver will have an impact on that disease? That exercise 218 00:14:17,480 --> 00:14:20,520 Speaker 1: would eventually lead researchers to a disease whose name is 219 00:14:20,520 --> 00:14:25,160 Speaker 1: a mouthful. It's a type of hereditary amyloidosis. It's a 220 00:14:25,200 --> 00:14:28,080 Speaker 1: disease so rare that it often appears as a mystery 221 00:14:28,080 --> 00:14:31,840 Speaker 1: illness on shows like E. Rn House, where doctors aren't 222 00:14:31,840 --> 00:14:36,520 Speaker 1: a race against time to figure out a diagnosis. Doctor, 223 00:14:37,160 --> 00:14:47,120 Speaker 1: you have amyloidosis. Why should I believe him? Now? Television aside, 224 00:14:47,200 --> 00:14:51,000 Speaker 1: the illness is incredibly rare and incredibly tragic. My middle 225 00:14:51,040 --> 00:14:54,280 Speaker 1: age patients developed something called neuropathy, a kind of tingling 226 00:14:54,280 --> 00:14:57,360 Speaker 1: that begins in their toes and fingers but progressively spreads 227 00:14:58,120 --> 00:15:03,040 Speaker 1: sufferers eventually can't walk, their heart deteriorates, their stomachs can't 228 00:15:03,040 --> 00:15:08,080 Speaker 1: process food, and they ultimately waste away and die. The 229 00:15:08,160 --> 00:15:11,440 Speaker 1: disease is genetic, meaning that it runs in families. Some 230 00:15:11,520 --> 00:15:14,520 Speaker 1: people get it and some people don't, but it comes 231 00:15:14,520 --> 00:15:18,080 Speaker 1: on slowly. For some people can start in their twenties. 232 00:15:18,320 --> 00:15:21,720 Speaker 1: For others it starts in middle age. If it ran 233 00:15:21,760 --> 00:15:24,840 Speaker 1: in my family, there was no treatment for it. I'm 234 00:15:24,880 --> 00:15:26,360 Speaker 1: not sure if I would want to know if I 235 00:15:26,400 --> 00:15:32,000 Speaker 1: had it or not. Back when all Nylum started researching 236 00:15:32,040 --> 00:15:35,280 Speaker 1: the disease, there was no approved drug that treated the 237 00:15:35,360 --> 00:15:38,760 Speaker 1: underlying condition. But all Nyleum, with its approach of altering 238 00:15:38,800 --> 00:15:41,200 Speaker 1: illness at the genetic level, stood a good chance at 239 00:15:41,240 --> 00:15:44,720 Speaker 1: being able to address it. But they needed money. John 240 00:15:44,760 --> 00:15:47,960 Speaker 1: Marganorri is the CEO of all Nylum. He's the only 241 00:15:48,000 --> 00:15:50,920 Speaker 1: CEO of the company has ever had. He's a scientist 242 00:15:50,960 --> 00:15:53,200 Speaker 1: by training. He got a PhD from the University of 243 00:15:53,240 --> 00:15:56,520 Speaker 1: Chicago and is the son of Greek immigrants. In a 244 00:15:56,560 --> 00:15:58,520 Speaker 1: profile I read about him, I found out he liked 245 00:15:58,520 --> 00:16:01,120 Speaker 1: to play pool and smokes the accase general cigar, which 246 00:16:01,160 --> 00:16:03,680 Speaker 1: I can totally see. I can tell you John is 247 00:16:03,760 --> 00:16:07,320 Speaker 1: ubiquitous around Cambridge. He's one of the first CEOs I've 248 00:16:07,360 --> 00:16:10,440 Speaker 1: met here, and I don't think that's a coincidence. He 249 00:16:10,480 --> 00:16:13,320 Speaker 1: seems to pop up everywhere. Part of that is because 250 00:16:13,360 --> 00:16:15,760 Speaker 1: as the CEO of al Nylum, John has seen it 251 00:16:15,800 --> 00:16:19,040 Speaker 1: all Back when he joined the company, it needed money, 252 00:16:19,160 --> 00:16:21,840 Speaker 1: and lots of it. When I joined, we had raised 253 00:16:21,880 --> 00:16:24,320 Speaker 1: seventeen and a half million dollars. I mean, I knew 254 00:16:24,320 --> 00:16:27,360 Speaker 1: when I started that we would need to take probably 255 00:16:27,400 --> 00:16:30,240 Speaker 1: a decade or more before we had our first drug 256 00:16:30,640 --> 00:16:32,840 Speaker 1: that would come out of the science, and I knew 257 00:16:32,880 --> 00:16:35,160 Speaker 1: that it would take billions of dollars to ultimately do it. 258 00:16:35,440 --> 00:16:37,640 Speaker 1: Luckily for the company, the science was starting to get 259 00:16:37,680 --> 00:16:40,280 Speaker 1: a buzz. I mean, there was a lot of early 260 00:16:40,320 --> 00:16:42,880 Speaker 1: excitement around our interference. You know, it was written up 261 00:16:42,880 --> 00:16:45,120 Speaker 1: in as the as the as the molecule of the 262 00:16:45,240 --> 00:16:48,840 Speaker 1: Year by Science in two thousand two. You know, Forbes 263 00:16:48,920 --> 00:16:51,760 Speaker 1: wrote an article about it being the next billion dollar 264 00:16:52,360 --> 00:16:56,320 Speaker 1: breakthrough in biotechnology. Al Nylum started doing deals with big 265 00:16:56,360 --> 00:17:02,480 Speaker 1: companies Merk, Novartis, roche To Cada. Ultimately we raised over 266 00:17:02,520 --> 00:17:06,280 Speaker 1: a billion dollars from pharmaceutical partnerships that we formed. Soon 267 00:17:06,600 --> 00:17:08,600 Speaker 1: urn Ai as it became known was one of the 268 00:17:08,600 --> 00:17:13,879 Speaker 1: hottest areas of biotech. Everybody wanted a piece. But then 269 00:17:14,080 --> 00:17:18,080 Speaker 1: something alarming started to happen. Trials that used urn Ai 270 00:17:18,320 --> 00:17:22,280 Speaker 1: started to fail. Companies began to leave the field, splashy 271 00:17:22,280 --> 00:17:26,520 Speaker 1: acquisitions were written off, pharmaceutical partnerships ended. It started to 272 00:17:26,520 --> 00:17:29,240 Speaker 1: seem like all Nyleum might also be headed for extinction. 273 00:17:29,800 --> 00:17:33,119 Speaker 1: We had many, many near death moments as a company. 274 00:17:33,240 --> 00:17:37,639 Speaker 1: We had one in where basically the entirety of the 275 00:17:37,640 --> 00:17:41,240 Speaker 1: pharmaceutical industry, who we're working with us earlier to help 276 00:17:41,280 --> 00:17:43,880 Speaker 1: fund the company and help advance some of the science, 277 00:17:44,119 --> 00:17:46,879 Speaker 1: they basically gave up hope and they left the field. 278 00:17:46,880 --> 00:17:50,280 Speaker 1: And so there was a very strong vote of no confidence, 279 00:17:50,320 --> 00:17:52,720 Speaker 1: if you will, in what we were doing as a 280 00:17:52,760 --> 00:17:55,480 Speaker 1: public company. We were trading under our cash. We had 281 00:17:55,520 --> 00:17:57,960 Speaker 1: more cash on our balance sheet than we had stock 282 00:17:58,040 --> 00:18:01,720 Speaker 1: value as a stock. So that it's a pretty dire moment. 283 00:18:02,200 --> 00:18:06,879 Speaker 1: I can't emphasize this enough. Biotech companies fail all the time. 284 00:18:07,280 --> 00:18:10,600 Speaker 1: Clinical trial results will be disappointing, investors will figure the 285 00:18:10,600 --> 00:18:15,199 Speaker 1: science doesn't work, people pick up and move on. What 286 00:18:15,359 --> 00:18:18,960 Speaker 1: happens much more rarely in biotechnology is what happened next. 287 00:18:19,600 --> 00:18:23,120 Speaker 1: The company stuck with it, and thanks to John's fundraising 288 00:18:23,240 --> 00:18:25,960 Speaker 1: through the good times, they had the cash to actually 289 00:18:26,000 --> 00:18:29,679 Speaker 1: see the science through. After sixteen years of research, On 290 00:18:29,720 --> 00:18:32,960 Speaker 1: August ten of this year, on Nylum won approval for 291 00:18:33,040 --> 00:18:37,200 Speaker 1: on Patro, it's first drug and the first drug ever 292 00:18:37,280 --> 00:18:42,440 Speaker 1: approved to use RNA interference. John recounts the moment, Oh, 293 00:18:42,440 --> 00:18:45,679 Speaker 1: that's a funny story. I was actually on a stage 294 00:18:46,080 --> 00:18:49,680 Speaker 1: talking to our field force. My long standing partner and 295 00:18:50,280 --> 00:18:53,520 Speaker 1: our president, Barry green Um was looking at it at 296 00:18:53,520 --> 00:18:57,160 Speaker 1: his emails as he often does, and he screams out, John, 297 00:18:57,240 --> 00:19:01,400 Speaker 1: we just got approved. And sure enough, you know we did. Uh. 298 00:19:01,440 --> 00:19:03,359 Speaker 1: And I was there and got a round of applause 299 00:19:03,400 --> 00:19:06,080 Speaker 1: from everybody. Um, Barry came up, I gave him a 300 00:19:06,080 --> 00:19:08,520 Speaker 1: big hug, and you know, off we went. So it 301 00:19:08,560 --> 00:19:11,240 Speaker 1: was literally couldn't have been more. It could have been 302 00:19:11,240 --> 00:19:14,639 Speaker 1: better planned. It was a watershed moment, not just for 303 00:19:14,680 --> 00:19:18,320 Speaker 1: the company, but for the industry. At least a dozen 304 00:19:18,359 --> 00:19:21,680 Speaker 1: biotech companies are working on therapies, which, like all Nylum, 305 00:19:21,760 --> 00:19:25,159 Speaker 1: seek to treat disease at the genetic level. If All 306 00:19:25,240 --> 00:19:27,520 Speaker 1: Nylum could do it, the hope is that they can too. 307 00:19:28,640 --> 00:19:31,679 Speaker 1: In many ways. The drug represents the best aspects of 308 00:19:31,720 --> 00:19:37,160 Speaker 1: the industry, but it also represents its insane economics. An 309 00:19:37,160 --> 00:19:40,000 Speaker 1: Alum's drug will cost four hundred and fifty thousand dollars 310 00:19:40,000 --> 00:19:43,080 Speaker 1: a year four hundred and fifty thousand dollars a year 311 00:19:43,760 --> 00:19:48,080 Speaker 1: before any discounts. Only three thousand patients with this disease 312 00:19:48,080 --> 00:19:51,840 Speaker 1: have ever been diagnosed. Even at that high price, was 313 00:19:51,960 --> 00:19:55,359 Speaker 1: so few patients, it's unlikely that this drug will be 314 00:19:55,400 --> 00:19:59,200 Speaker 1: profitable anytime soon. It is a long time between now 315 00:19:59,240 --> 00:20:01,520 Speaker 1: and being profitable as a company. We can't do it 316 00:20:01,560 --> 00:20:04,280 Speaker 1: on patrol alone. We obviously have other products in our 317 00:20:04,320 --> 00:20:07,440 Speaker 1: pipeline to bring forward to ultimately um, you know, get 318 00:20:07,480 --> 00:20:09,280 Speaker 1: to a point as a company where we could be 319 00:20:09,320 --> 00:20:14,280 Speaker 1: a sustainable business. In its first three months on the market, 320 00:20:14,480 --> 00:20:17,400 Speaker 1: the drug generated only a half a million in sales, 321 00:20:18,080 --> 00:20:23,080 Speaker 1: a pittance in biotech. Investors are worried. Shares declined by 322 00:20:23,119 --> 00:20:27,000 Speaker 1: more than this year, but the market still sees promise. 323 00:20:27,560 --> 00:20:29,960 Speaker 1: The company has a market value of more than seven 324 00:20:29,960 --> 00:20:33,200 Speaker 1: billion dollars. To give you a sense, that's about the 325 00:20:33,240 --> 00:20:37,119 Speaker 1: size of Dunkin Donuts or Jet Blue, companies that are profitable. 326 00:20:38,040 --> 00:20:41,480 Speaker 1: Unlike all Nylum, which has generated hundreds of millions in losses. 327 00:20:42,640 --> 00:20:45,680 Speaker 1: But all Nylum isn't selling coffee or cheap flights to Florida. 328 00:20:46,600 --> 00:20:49,320 Speaker 1: What they do can mean the difference between life and death. 329 00:20:49,880 --> 00:20:54,760 Speaker 1: It's an awesome responsibility. But what keeps me going is 330 00:20:54,760 --> 00:20:57,120 Speaker 1: the fact that we know we have an important approach 331 00:20:57,400 --> 00:21:00,239 Speaker 1: for new medicines, and we have an ability to make 332 00:21:00,280 --> 00:21:03,240 Speaker 1: a big difference in patients lives. And you know, every 333 00:21:03,240 --> 00:21:05,200 Speaker 1: morning I wake up, I'm excited to go to work, 334 00:21:05,840 --> 00:21:11,320 Speaker 1: even to this day. Here's the scary truth about drug development. 335 00:21:11,960 --> 00:21:16,280 Speaker 1: It can be arbitrary. Scientific breakthroughs can send billions of 336 00:21:16,280 --> 00:21:20,240 Speaker 1: pharmaceutical dollars into any given field, but one high profile 337 00:21:20,400 --> 00:21:24,400 Speaker 1: failure can just as easily make that money disappear. Some 338 00:21:24,440 --> 00:21:29,600 Speaker 1: companies survive, but many don't. Firms get sold, research teams disperse, 339 00:21:30,320 --> 00:21:34,760 Speaker 1: patients die. Most drugs never go anywhere. They sit on shelves. 340 00:21:35,280 --> 00:21:38,760 Speaker 1: Small percentage going to clinical trials, and many of those fail. 341 00:21:39,600 --> 00:21:43,320 Speaker 1: But every so often one makes it through. And that's 342 00:21:43,359 --> 00:21:56,520 Speaker 1: only the beginning. And that's it for this week's prognosis. 343 00:21:56,720 --> 00:21:59,479 Speaker 1: Thanks for listening. Do you have a story about healthcare 344 00:21:59,480 --> 00:22:01,720 Speaker 1: in the US or around the world. We want to 345 00:22:01,760 --> 00:22:04,959 Speaker 1: hear from you. You can email me m Cortes at 346 00:22:05,000 --> 00:22:08,520 Speaker 1: Bloomberg dot net or find me on Twitter at big Cortes. 347 00:22:08,880 --> 00:22:11,040 Speaker 1: If you are a fan of this episode, please take 348 00:22:11,080 --> 00:22:13,480 Speaker 1: a moment to rate and review us. It helps new 349 00:22:13,520 --> 00:22:17,119 Speaker 1: listeners find the show. This episode was produced by Liz Smith. 350 00:22:17,480 --> 00:22:20,840 Speaker 1: Our story editor was John Heckinger. Thanks also to Drew Armstrong, 351 00:22:21,119 --> 00:22:24,520 Speaker 1: Francesco Levi's head of Bloomberg Podcasts. We'll see you next week.