1 00:00:15,356 --> 00:00:22,916 Speaker 1: Pushkin. There's this problem that's been going on in the 2 00:00:22,956 --> 00:00:26,276 Speaker 1: background in the United States for a long time. The 3 00:00:26,316 --> 00:00:31,996 Speaker 1: problem is this, there are not enough drugs to go around. This, strangely, 4 00:00:32,436 --> 00:00:35,436 Speaker 1: is not about expensive new drugs that people can't afford. 5 00:00:35,876 --> 00:00:39,836 Speaker 1: This is about old, cheap generic drugs, drugs that just 6 00:00:39,916 --> 00:00:43,436 Speaker 1: are not available in sufficient quantities at any price. A 7 00:00:43,516 --> 00:00:47,756 Speaker 1: national pharmacist group recently reported shortages of three hundred and 8 00:00:47,956 --> 00:00:52,316 Speaker 1: nine of these generic drugs. There are multiple causes. It 9 00:00:52,356 --> 00:00:55,596 Speaker 1: could be the bankruptcy of some little known generic drug maker. 10 00:00:55,876 --> 00:00:58,956 Speaker 1: Could be a sudden surge in demand. Could be the 11 00:00:58,956 --> 00:01:01,916 Speaker 1: failure of some distant crop that is the source of 12 00:01:01,956 --> 00:01:06,276 Speaker 1: an essential drug ingredient. It's a complicated problem built out 13 00:01:06,316 --> 00:01:09,916 Speaker 1: of lots of little problems. But broadly speaking, the supply 14 00:01:10,076 --> 00:01:14,036 Speaker 1: chain for generic drugs is long and opaque and exists 15 00:01:14,156 --> 00:01:17,356 Speaker 1: largely outside of the United States, so it is very 16 00:01:17,396 --> 00:01:25,676 Speaker 1: difficult to see these drug shortages coming. I'm Jacob Goldstein 17 00:01:25,756 --> 00:01:27,716 Speaker 1: and this is What's Your Problem, the show where I 18 00:01:27,796 --> 00:01:30,836 Speaker 1: talk to people who are trying to make technological progress. 19 00:01:31,396 --> 00:01:34,756 Speaker 1: My guest today is Christina Smolky. She's a professor at 20 00:01:34,796 --> 00:01:37,956 Speaker 1: Stanford and the co founder and CEO of a company 21 00:01:37,956 --> 00:01:41,356 Speaker 1: called Anthea. It's a synthetic biology company. They're in the 22 00:01:41,396 --> 00:01:47,356 Speaker 1: business of genetically engineering microorganisms to produce commercial products. Christina's 23 00:01:47,396 --> 00:01:50,596 Speaker 1: problem is this, how do you turn ye cells into 24 00:01:50,676 --> 00:01:55,756 Speaker 1: tiny factories to create the active ingredients in drugs. If 25 00:01:55,836 --> 00:01:58,956 Speaker 1: Christina and her colleagues solve this problem, they won't solve 26 00:01:58,996 --> 00:02:02,156 Speaker 1: the drug shortage problem entirely, but they might help make 27 00:02:02,196 --> 00:02:02,676 Speaker 1: it better. 28 00:02:05,596 --> 00:02:08,516 Speaker 2: I actually started not in industry, not as a CEO 29 00:02:08,556 --> 00:02:10,716 Speaker 2: of a company, but I started as a professor. And 30 00:02:10,756 --> 00:02:13,236 Speaker 2: so there, you know, I was coming out the field 31 00:02:13,516 --> 00:02:16,076 Speaker 2: in a more academic way, looking at here's the state 32 00:02:16,076 --> 00:02:18,716 Speaker 2: of the technology, but think about how much more we 33 00:02:18,716 --> 00:02:21,436 Speaker 2: could do if we really open this up. And so, 34 00:02:21,636 --> 00:02:23,756 Speaker 2: you know, it was really let's focus on the hard problems. 35 00:02:23,836 --> 00:02:26,196 Speaker 2: Let's focus on the problems that people say right now 36 00:02:26,236 --> 00:02:28,676 Speaker 2: are impossible, that you will never get this to work, 37 00:02:28,876 --> 00:02:31,596 Speaker 2: the science just can't do it. And let's figure out 38 00:02:31,716 --> 00:02:36,316 Speaker 2: can we actually you know, make these impossible solutions possible 39 00:02:36,356 --> 00:02:38,556 Speaker 2: to really address these problems. And so that's where it started. 40 00:02:38,636 --> 00:02:40,796 Speaker 2: You know, for about fifteen years of my career was 41 00:02:40,876 --> 00:02:45,796 Speaker 2: really focusing on the you know, foundational scientific breakthroughs that 42 00:02:45,836 --> 00:02:48,476 Speaker 2: were needed to build a company like Anthea and really 43 00:02:48,796 --> 00:02:51,076 Speaker 2: bring those transformations into the industry. 44 00:02:51,476 --> 00:02:54,476 Speaker 1: So when you when you're starting out, you're thinking, Okay, 45 00:02:54,516 --> 00:02:58,036 Speaker 1: there is this nascent field synthetic biology, this basic idea, 46 00:02:58,796 --> 00:03:01,076 Speaker 1: I want to advance this field to the point where 47 00:03:01,076 --> 00:03:03,556 Speaker 1: we can make you know, drugs or the active ingredient 48 00:03:03,556 --> 00:03:05,916 Speaker 1: in drugs exactly what are the things people didn't know 49 00:03:05,956 --> 00:03:07,956 Speaker 1: how to do that you and your colleagues had to 50 00:03:07,956 --> 00:03:08,396 Speaker 1: figure out. 51 00:03:09,356 --> 00:03:12,236 Speaker 2: So there was a lot to figure out. And you know, 52 00:03:12,276 --> 00:03:14,236 Speaker 2: first and foremost when you looked at where the field 53 00:03:14,396 --> 00:03:17,676 Speaker 2: was when we when I started in this space, most 54 00:03:17,716 --> 00:03:20,436 Speaker 2: of where everybody focused and it's actually true still today 55 00:03:20,876 --> 00:03:25,516 Speaker 2: is on engineering cells to produce relatively simple compounds. So 56 00:03:25,596 --> 00:03:26,996 Speaker 2: let's just take a step back, and you know, we 57 00:03:27,116 --> 00:03:31,076 Speaker 2: use yeast, very similar organism that yeah, basically identical organism 58 00:03:31,116 --> 00:03:34,836 Speaker 2: that we've been using for centuries to brew beer, ferment wine, right, 59 00:03:35,076 --> 00:03:38,036 Speaker 2: so we have a long standing history of that. That's biomanufacturing. 60 00:03:38,436 --> 00:03:42,476 Speaker 2: But what the yeast of producing is ethanol, right, carbon dioxide, 61 00:03:42,596 --> 00:03:46,556 Speaker 2: very simple molecules that it does naturally. Now take a 62 00:03:46,556 --> 00:03:49,836 Speaker 2: step back, we want that yeast to produce a very 63 00:03:49,836 --> 00:03:55,076 Speaker 2: complex chemotherapeutic, right, or a very complex anti infective. How 64 00:03:55,116 --> 00:03:57,196 Speaker 2: do we teach it to do that? And when you 65 00:03:57,236 --> 00:03:59,396 Speaker 2: looked at where we started, you know, in this in 66 00:03:59,476 --> 00:04:02,356 Speaker 2: this field, what the field was capable of doing was 67 00:04:02,356 --> 00:04:06,036 Speaker 2: basically taking a organism like yeast and maybe moving you know, 68 00:04:06,196 --> 00:04:10,876 Speaker 2: three genes or three proteins into that organism. That basically 69 00:04:10,956 --> 00:04:14,436 Speaker 2: allowed the industry to produce very simple compounds. 70 00:04:13,916 --> 00:04:16,076 Speaker 1: Perfume, right. I feel like perfume was one of the 71 00:04:16,076 --> 00:04:17,596 Speaker 1: big ones, sense exactly. 72 00:04:17,636 --> 00:04:20,316 Speaker 2: Very close in structure to what the yeast could already make. Right, 73 00:04:20,956 --> 00:04:25,356 Speaker 2: in order to actually make these you know, drug ingredients, 74 00:04:25,596 --> 00:04:27,676 Speaker 2: we had to be able to transform the field from 75 00:04:27,676 --> 00:04:30,196 Speaker 2: thinking about and being able to sort of routinely move 76 00:04:30,236 --> 00:04:33,916 Speaker 2: maybe three to six genes or protein coding sequences into 77 00:04:33,916 --> 00:04:37,836 Speaker 2: the cell to be able to actually move twenty thirty 78 00:04:37,956 --> 00:04:41,396 Speaker 2: or more genes and protein sequences into a cell. And again, 79 00:04:41,516 --> 00:04:44,556 Speaker 2: these drug ingredients that we rely on are so you know, 80 00:04:44,556 --> 00:04:46,916 Speaker 2: they're so different, and they're so complicated from what yeast 81 00:04:46,916 --> 00:04:47,676 Speaker 2: would normally make. 82 00:04:47,916 --> 00:04:52,436 Speaker 1: Yes, it was not built to make chemotherapy drugs, right, 83 00:04:52,756 --> 00:04:56,396 Speaker 1: to spend a billion years evolving to make the drugs 84 00:04:56,436 --> 00:04:58,996 Speaker 1: we need to cure cancer exactly. So it is the 85 00:04:59,116 --> 00:05:01,116 Speaker 1: basic problem that like if you try and swap in 86 00:05:01,196 --> 00:05:04,276 Speaker 1: that many genes at once, the cell will just kind 87 00:05:04,316 --> 00:05:06,196 Speaker 1: of blow up and die. Be like, what are you 88 00:05:06,236 --> 00:05:08,716 Speaker 1: doing to me? I mean it's that the basic starting problem. 89 00:05:08,796 --> 00:05:10,676 Speaker 2: Yeah, you know that was certainly I would say the 90 00:05:11,156 --> 00:05:14,916 Speaker 2: general sort of I guess thinking at the time, right, 91 00:05:14,956 --> 00:05:17,236 Speaker 2: And you know, when we propose to do this, you know, 92 00:05:17,316 --> 00:05:19,956 Speaker 2: in my academic lab, we had a difficult time getting 93 00:05:19,956 --> 00:05:22,396 Speaker 2: funding for it, even at like a research level, because 94 00:05:22,436 --> 00:05:25,036 Speaker 2: the reviews would come back and say, this is you know, 95 00:05:25,196 --> 00:05:27,436 Speaker 2: this is impossible. There's no reason to even try to 96 00:05:27,476 --> 00:05:29,236 Speaker 2: do this because it will never work. 97 00:05:29,356 --> 00:05:32,316 Speaker 1: It's an engineering problem at a certain level at that point, right, 98 00:05:32,356 --> 00:05:34,876 Speaker 1: That is the sort of you have if you have 99 00:05:34,996 --> 00:05:38,276 Speaker 1: the genomic information, you know what genes you want, but 100 00:05:38,316 --> 00:05:39,836 Speaker 1: you got to figure out how to make them work 101 00:05:39,916 --> 00:05:44,116 Speaker 1: in a yeast, right, And I mean I want to 102 00:05:44,156 --> 00:05:46,116 Speaker 1: ask how do you do that? Although I know that's 103 00:05:46,156 --> 00:05:48,836 Speaker 1: like a ten year long answer, So maybe what I'll 104 00:05:48,836 --> 00:05:52,036 Speaker 1: ask instead is like, is there one piece of figuring 105 00:05:52,036 --> 00:05:55,876 Speaker 1: out how to do that that you can explain? You know, 106 00:05:56,036 --> 00:05:58,396 Speaker 1: is there one one thing you had to figure out 107 00:05:58,396 --> 00:06:00,356 Speaker 1: along the way where you came upon it and it 108 00:06:00,396 --> 00:06:03,276 Speaker 1: didn't work, and you figured out how to make it work. 109 00:06:04,116 --> 00:06:07,116 Speaker 2: Yeah, and you're right, this is an engineering problem. It's 110 00:06:07,116 --> 00:06:11,516 Speaker 2: a systems engineering problem. Right. So ultimately we're asking the 111 00:06:11,596 --> 00:06:15,316 Speaker 2: yeast to be this sort of mini nanofactory to produce 112 00:06:15,396 --> 00:06:19,156 Speaker 2: drug ingredients. Right, So not these sort of macro factories 113 00:06:19,196 --> 00:06:21,676 Speaker 2: we build out, you know, in our world, but really 114 00:06:21,716 --> 00:06:24,716 Speaker 2: kind of a cellular factory. So what's happening inside the cell. 115 00:06:25,036 --> 00:06:27,316 Speaker 2: One of the things that we brought to this field 116 00:06:27,436 --> 00:06:29,556 Speaker 2: is sort of a very unique strategy was to say, 117 00:06:30,316 --> 00:06:32,276 Speaker 2: you know, let's not the cell is not just a bag, 118 00:06:32,476 --> 00:06:34,956 Speaker 2: right where everything just sort of happens in this nebulous form. 119 00:06:35,036 --> 00:06:37,756 Speaker 2: Let's really think smartly about the cell as a system 120 00:06:38,076 --> 00:06:40,516 Speaker 2: and the biochemical environments that are in different locations of 121 00:06:40,516 --> 00:06:42,996 Speaker 2: the cell. And then when we change the sequence of 122 00:06:42,996 --> 00:06:45,996 Speaker 2: the proteins, we would very specifically give the yeast directions 123 00:06:46,036 --> 00:06:50,076 Speaker 2: of make this particular protein in this part of the 124 00:06:50,116 --> 00:06:53,156 Speaker 2: cell because there's a particular pH to do some environment, 125 00:06:53,196 --> 00:06:55,476 Speaker 2: you know. And then but this other part of you know, 126 00:06:55,476 --> 00:06:58,156 Speaker 2: the molecular machinery, the other steps of the proteins, we 127 00:06:58,196 --> 00:07:00,156 Speaker 2: want you to actually make it in this other area 128 00:07:00,156 --> 00:07:00,596 Speaker 2: of the cell. 129 00:07:00,956 --> 00:07:03,196 Speaker 1: So just to write to pick up on your factory metaphors. 130 00:07:03,236 --> 00:07:06,356 Speaker 1: So it's like the naive way to think about the 131 00:07:06,356 --> 00:07:08,916 Speaker 1: inside of the cell is just like a big empty room. 132 00:07:09,396 --> 00:07:11,756 Speaker 1: But you're thinking, like, no, it's not like that. I mean, 133 00:07:11,756 --> 00:07:13,476 Speaker 1: if the factory is the analogy, it's like, this part 134 00:07:13,476 --> 00:07:16,196 Speaker 1: over here is like where we should be whatever putting 135 00:07:16,236 --> 00:07:18,236 Speaker 1: the wheels on, and this part over here is clearly 136 00:07:18,236 --> 00:07:20,796 Speaker 1: where like the robot arms should be bolting the chassis together. 137 00:07:20,796 --> 00:07:24,676 Speaker 1: Because different parts of the inside of the cell are different, 138 00:07:24,756 --> 00:07:27,476 Speaker 1: are biochemically different, and some parts will work to do 139 00:07:27,876 --> 00:07:31,676 Speaker 1: some things and other parts will work to do other things, 140 00:07:31,676 --> 00:07:33,636 Speaker 1: and you can't do it in the wrong place or 141 00:07:33,676 --> 00:07:36,676 Speaker 1: it won't work exactly exactly. 142 00:07:36,676 --> 00:07:38,636 Speaker 2: I mean, that's an exact metaphor, right, and the exact 143 00:07:38,676 --> 00:07:39,756 Speaker 2: way to think about it, right. 144 00:07:40,116 --> 00:07:42,796 Speaker 1: And so let me ask just a few dumb questions 145 00:07:42,796 --> 00:07:44,796 Speaker 1: about that, because it's interesting. How do you tell the 146 00:07:44,836 --> 00:07:47,116 Speaker 1: cell where to do it? 147 00:07:47,116 --> 00:07:49,356 Speaker 2: It ultimately comes down to the directions you put in 148 00:07:49,356 --> 00:07:52,196 Speaker 2: the DNA, right, And it comes back to that gencoding 149 00:07:52,236 --> 00:07:55,356 Speaker 2: sequence where I mean, again it's biology does remarkable things, 150 00:07:55,436 --> 00:07:58,716 Speaker 2: but within you know, within that encoded sequence, you know 151 00:07:58,756 --> 00:08:02,316 Speaker 2: there are directions of you know, again exactly what amino acids. 152 00:08:02,356 --> 00:08:05,236 Speaker 2: You know, how you are basically making that protein amino 153 00:08:05,276 --> 00:08:08,316 Speaker 2: acid by amino acid. But there are also directions that 154 00:08:08,396 --> 00:08:12,116 Speaker 2: basically tell a cell and the cell's native machinery, no, 155 00:08:12,276 --> 00:08:14,076 Speaker 2: you're going to actually make the protein over in this 156 00:08:14,196 --> 00:08:16,596 Speaker 2: location right now. We want you to transport it over there. 157 00:08:16,636 --> 00:08:18,276 Speaker 2: We want you to move this over here, We want 158 00:08:18,276 --> 00:08:20,396 Speaker 2: you to insert it into this membrane. So you know, 159 00:08:20,396 --> 00:08:23,796 Speaker 2: I mean again, the cell is, it's so sophisticated, right, 160 00:08:24,476 --> 00:08:27,476 Speaker 2: we just you know, we just have to basically be 161 00:08:27,516 --> 00:08:31,116 Speaker 2: able to understand enough about the directions that the cell 162 00:08:31,236 --> 00:08:34,356 Speaker 2: uses and reads in its own native processes so that 163 00:08:34,396 --> 00:08:38,196 Speaker 2: we can begin to leverage you know, the strategies and 164 00:08:38,236 --> 00:08:40,836 Speaker 2: the routes that it has you know, developed, is a 165 00:08:40,836 --> 00:08:43,756 Speaker 2: way to move proteins to particular locations and cells. 166 00:08:44,036 --> 00:08:48,156 Speaker 1: So you figure that out over some period of time. 167 00:08:48,676 --> 00:08:52,516 Speaker 1: Is there a first drug ingredient that you get a 168 00:08:52,676 --> 00:08:55,516 Speaker 1: Y cell to make? Is there some like proof of 169 00:08:55,636 --> 00:08:56,556 Speaker 1: concept moment? 170 00:08:57,396 --> 00:09:00,876 Speaker 2: Yeah? There, yes, there was. So the drug ingredient that 171 00:09:00,916 --> 00:09:05,116 Speaker 2: we initially demonstrated with this is an ingredient called the 172 00:09:05,236 --> 00:09:09,036 Speaker 2: dane And this is actually an ingredient that is extracted 173 00:09:09,116 --> 00:09:11,556 Speaker 2: from medicinal plants, and it's an ingredient that's used to 174 00:09:11,556 --> 00:09:15,956 Speaker 2: produce about half a dozen different drug ingredients, from drugs 175 00:09:15,996 --> 00:09:19,316 Speaker 2: that are used to treat you very severe pain, to 176 00:09:19,476 --> 00:09:23,516 Speaker 2: drugs that are used as rescue mediations to treat addiction 177 00:09:24,476 --> 00:09:26,956 Speaker 2: and as well as overdose. 178 00:09:27,436 --> 00:09:29,636 Speaker 1: Like the drug that has the brand name Narcan. Is 179 00:09:29,636 --> 00:09:30,876 Speaker 1: it not lots like that? 180 00:09:30,956 --> 00:09:31,076 Speaker 2: Oh? 181 00:09:31,196 --> 00:09:31,596 Speaker 1: Interesting? 182 00:09:31,796 --> 00:09:35,996 Speaker 2: Is that drug Narcan and naloxone is a drug that 183 00:09:36,116 --> 00:09:39,476 Speaker 2: is used that is basically produced from the vein. We 184 00:09:39,556 --> 00:09:43,396 Speaker 2: published that demonstration, that proof of principal demonstration in twenty fifteen, 185 00:09:43,956 --> 00:09:46,036 Speaker 2: so that was and again that was done prior to 186 00:09:46,076 --> 00:09:49,276 Speaker 2: us starting anthea. It was done in our the academic 187 00:09:49,316 --> 00:09:54,436 Speaker 2: lab at Stanford, and again that particular demonstration, it took 188 00:09:54,436 --> 00:09:57,636 Speaker 2: over a decade, right to bring it all together. So 189 00:09:57,676 --> 00:09:59,476 Speaker 2: it was a very long term project in my lab 190 00:09:59,876 --> 00:10:01,876 Speaker 2: for the very reasons that we discussed for all of 191 00:10:01,876 --> 00:10:05,716 Speaker 2: these challenges, right, and it was one that because I 192 00:10:05,716 --> 00:10:08,036 Speaker 2: would say the field in general viewed it to be 193 00:10:08,076 --> 00:10:11,716 Speaker 2: impossible and thus not worth you know, spending research dollars on. 194 00:10:11,756 --> 00:10:12,956 Speaker 2: It was one that we spent a lot of time 195 00:10:12,956 --> 00:10:15,236 Speaker 2: bootstrapping in my lab because I really had a lot 196 00:10:15,236 --> 00:10:16,876 Speaker 2: of conviction that we could get this done. 197 00:10:16,996 --> 00:10:20,796 Speaker 1: So you publish this paper to show that you can 198 00:10:21,436 --> 00:10:26,716 Speaker 1: get yeased to produce this drug ingredient. What happens next? 199 00:10:26,956 --> 00:10:29,756 Speaker 2: The next questions are can it be done at an 200 00:10:29,756 --> 00:10:34,076 Speaker 2: efficiency and scale such that this can really offer you know, 201 00:10:34,156 --> 00:10:37,756 Speaker 2: solutions right to the industry, Because if you take what 202 00:10:37,796 --> 00:10:40,396 Speaker 2: we showed in twenty fifteen tried to scale it up, 203 00:10:40,676 --> 00:10:42,396 Speaker 2: I mean you would it would not be offering a 204 00:10:42,396 --> 00:10:46,436 Speaker 2: solution because it was so inefficient. Is still not efficiently 205 00:10:46,476 --> 00:10:50,836 Speaker 2: converting the sugar to that drug ingredient such that it 206 00:10:50,836 --> 00:10:53,276 Speaker 2: would just be too expensive because ultimately price is a 207 00:10:53,276 --> 00:10:56,036 Speaker 2: big consideration. So you know, there were and just to 208 00:10:56,076 --> 00:10:58,596 Speaker 2: give you like a sense of the degree what we're 209 00:10:58,596 --> 00:11:02,356 Speaker 2: discussing here, right again, when we look at what was 210 00:11:02,356 --> 00:11:04,996 Speaker 2: demonstrated in twenty fifteen, you know the yest we're producing 211 00:11:05,116 --> 00:11:08,676 Speaker 2: very low concentrations of that drug ingredient. We at Inthea 212 00:11:08,716 --> 00:11:11,956 Speaker 2: had to optimize that by over a millionfold, and not 213 00:11:12,036 --> 00:11:15,676 Speaker 2: just in scale but in efficiency of converting. That had 214 00:11:15,716 --> 00:11:19,956 Speaker 2: to be able to produce a million times higher concentration 215 00:11:20,636 --> 00:11:23,556 Speaker 2: of that drug ingredient than what we demonstrated. 216 00:11:23,076 --> 00:11:25,916 Speaker 1: A million times more drug per unit. 217 00:11:25,676 --> 00:11:28,796 Speaker 2: Sugar exactly right, or per unit use really right, So. 218 00:11:28,796 --> 00:11:31,556 Speaker 1: The yeast has to get way, way way better. Sure 219 00:11:31,556 --> 00:11:34,076 Speaker 1: it can make the drug. It's really bad at making 220 00:11:34,076 --> 00:11:38,636 Speaker 1: the drug. In two, it's terrible at making it exactly. 221 00:11:38,796 --> 00:11:41,236 Speaker 2: That's sort of independent of scale, you know, in terms 222 00:11:41,236 --> 00:11:43,716 Speaker 2: of like the volume that you're producing. It's saying, okay, 223 00:11:43,916 --> 00:11:45,716 Speaker 2: you know, whether you're we're growing you at a mill 224 00:11:45,756 --> 00:11:47,916 Speaker 2: or we're growing you at you know, one hundred thousand liters, 225 00:11:48,196 --> 00:11:50,396 Speaker 2: we need you to really steff up your game. 226 00:11:50,636 --> 00:11:52,476 Speaker 1: And yeah, right, you. 227 00:11:52,396 --> 00:11:54,756 Speaker 2: Know, converting that sugar into the drug product. And so 228 00:11:55,356 --> 00:11:59,036 Speaker 2: again that comes back to a lot it's an engineering problem. 229 00:11:59,076 --> 00:12:01,476 Speaker 1: So okay, this is the next problem you have what 230 00:12:01,636 --> 00:12:02,996 Speaker 1: you know, what what are some of the things you 231 00:12:03,036 --> 00:12:04,476 Speaker 1: do to increase efficiency. 232 00:12:04,716 --> 00:12:06,636 Speaker 2: So you know, again if we come back to this 233 00:12:06,756 --> 00:12:09,596 Speaker 2: idea of you know, you're assembling a car and a factory, 234 00:12:09,676 --> 00:12:11,796 Speaker 2: right and it's going through these different lines to sort 235 00:12:11,836 --> 00:12:14,156 Speaker 2: of build it in a modular way. That's you know, 236 00:12:14,316 --> 00:12:17,356 Speaker 2: the sort of manufacturing assembly line that you've developed is 237 00:12:17,356 --> 00:12:19,796 Speaker 2: sort of where you want your your drug ingredient to 238 00:12:19,836 --> 00:12:23,156 Speaker 2: stay on track, right, But it is operating within this 239 00:12:23,196 --> 00:12:26,196 Speaker 2: more broader complex system of the yeast. And so the 240 00:12:26,276 --> 00:12:29,916 Speaker 2: yeast will have just natural processes that it's developed, and 241 00:12:29,996 --> 00:12:32,396 Speaker 2: some of those will actually begin to interface with the 242 00:12:32,436 --> 00:12:34,876 Speaker 2: assembly line that you've put in, and so it. 243 00:12:34,796 --> 00:12:37,796 Speaker 1: Can start the yeast is busy being a yeast cell, right, 244 00:12:37,836 --> 00:12:41,556 Speaker 1: Like the yeast was not born to make this drug ingredient. 245 00:12:41,796 --> 00:12:43,636 Speaker 2: And it's you know, it's busy, as you say, being 246 00:12:43,636 --> 00:12:45,476 Speaker 2: in a e cell. It has its own objectives that 247 00:12:45,516 --> 00:12:48,836 Speaker 2: it wants to achieve, right in terms of you know, growing, 248 00:12:49,036 --> 00:12:52,996 Speaker 2: you know, doubling, and you know, producing its own products. Yeah, 249 00:12:53,156 --> 00:12:55,036 Speaker 2: it has its own dreams and you know, things that 250 00:12:55,076 --> 00:12:57,676 Speaker 2: it wants to accomplish. And so it's you know, the 251 00:12:57,756 --> 00:13:01,316 Speaker 2: natural system that you put it within is basically interfacing 252 00:13:01,436 --> 00:13:03,116 Speaker 2: with that assembly line that you've put it in. And 253 00:13:03,156 --> 00:13:07,876 Speaker 2: in many cases, right those natural systems can actually pull 254 00:13:07,916 --> 00:13:11,476 Speaker 2: away or divert your drug ingredient from the desired endpoint, 255 00:13:12,236 --> 00:13:14,276 Speaker 2: just you know, because of these interactions. 256 00:13:14,316 --> 00:13:16,876 Speaker 1: That's the weird thing, Like the yeast is making you crazy, 257 00:13:16,916 --> 00:13:19,796 Speaker 1: but like the yeast is also like the thing that's 258 00:13:19,796 --> 00:13:22,436 Speaker 1: making the thing you need exactly right, and so you have. 259 00:13:22,516 --> 00:13:25,556 Speaker 2: To really balance that very carefully because and so I mean, 260 00:13:25,596 --> 00:13:28,476 Speaker 2: you want the use to be multiplying, because every time 261 00:13:28,476 --> 00:13:31,156 Speaker 2: it multiplies, it's providing another cell factory that's going to 262 00:13:31,156 --> 00:13:34,236 Speaker 2: reduce drug ingredients. So you it's this balance between allowing 263 00:13:34,276 --> 00:13:36,596 Speaker 2: the EAST to obtain its objectives, which also feed into 264 00:13:36,596 --> 00:13:39,476 Speaker 2: your objectives, but then where it is, you know, being 265 00:13:39,516 --> 00:13:42,956 Speaker 2: disruptive to your process, trying to make surgical changes that 266 00:13:42,996 --> 00:13:45,676 Speaker 2: will still allow the yeast to be relatively happy, you know, 267 00:13:45,716 --> 00:13:47,516 Speaker 2: and feel like it is doing what it needs to do, 268 00:13:47,596 --> 00:13:49,916 Speaker 2: but still but then allowing more of your drug ingredient 269 00:13:49,956 --> 00:13:52,196 Speaker 2: to grow, to go towards the product that you ultimately 270 00:13:52,236 --> 00:13:52,796 Speaker 2: want to produce. 271 00:13:57,036 --> 00:13:59,116 Speaker 1: A few weeks ago and they announced that they had 272 00:13:59,156 --> 00:14:03,156 Speaker 1: completed their first manufacturing scale production of the bay and 273 00:14:03,236 --> 00:14:05,876 Speaker 1: they plan to start selling the ingredient to drug makers 274 00:14:06,036 --> 00:14:19,116 Speaker 1: next year. We'll be back in a minute. Now, back 275 00:14:19,156 --> 00:14:24,476 Speaker 1: to the show. So let's talk about drug shortages. To me, 276 00:14:24,676 --> 00:14:29,116 Speaker 1: still somewhat strange phenomenon in the United States, a country 277 00:14:29,156 --> 00:14:31,356 Speaker 1: where we're a rich country and we spend tons of 278 00:14:31,356 --> 00:14:33,356 Speaker 1: money on drugs, although no generic drugs are cheap, and 279 00:14:33,356 --> 00:14:34,796 Speaker 1: that's part of the thing. We can talk about that, 280 00:14:35,076 --> 00:14:41,756 Speaker 1: but it is remarkable how widespread and persistent drug shortages 281 00:14:41,796 --> 00:14:44,716 Speaker 1: are shortages in particular of generic drugs, and they seem 282 00:14:44,716 --> 00:14:48,676 Speaker 1: to be increasing over the last few years. What's going 283 00:14:48,716 --> 00:14:49,156 Speaker 1: on there? 284 00:14:49,716 --> 00:14:51,396 Speaker 2: I mean, I think one thing that has been noted 285 00:14:51,476 --> 00:14:53,916 Speaker 2: and that is notable is that in the US we 286 00:14:54,036 --> 00:14:58,596 Speaker 2: do not have manufacturing capacity to produce drug ingredients or 287 00:14:58,676 --> 00:15:01,476 Speaker 2: drug products really, right, It's very limited. Most of the 288 00:15:01,516 --> 00:15:04,076 Speaker 2: drugs that we consume are basically produced outside of the 289 00:15:04,196 --> 00:15:07,676 Speaker 2: US about ninety percent. What that ultimately plays into quite 290 00:15:07,676 --> 00:15:10,916 Speaker 2: a bit is lack of transparency and control over these 291 00:15:10,916 --> 00:15:14,676 Speaker 2: supply chains, right, because we don't have any domestic capacity. 292 00:15:14,996 --> 00:15:18,316 Speaker 2: Because the supply chains actually are quite complex in terms 293 00:15:18,356 --> 00:15:21,036 Speaker 2: of the different players involved, oftentimes we don't have a 294 00:15:21,036 --> 00:15:25,396 Speaker 2: lot of notice or yeah, really notice or transparency into 295 00:15:25,476 --> 00:15:27,236 Speaker 2: if we expect that there's going to be an issue 296 00:15:27,236 --> 00:15:30,436 Speaker 2: with the supply chain. Right, there's just again very limited transparency. 297 00:15:30,476 --> 00:15:33,196 Speaker 2: It's very difficult to track through all the supply chains. Now, 298 00:15:33,596 --> 00:15:37,476 Speaker 2: when you talk about just manufacturing technology for drugs and 299 00:15:37,516 --> 00:15:40,476 Speaker 2: the ways that they're being manufactured, there's essentially two different 300 00:15:40,516 --> 00:15:43,356 Speaker 2: ways that all of our drugs are being produced. Right. 301 00:15:43,636 --> 00:15:46,836 Speaker 2: We talked about agricultural sourcing, which a lot of that 302 00:15:46,916 --> 00:15:49,756 Speaker 2: is sort of where we focus. But again about forty 303 00:15:49,756 --> 00:15:52,796 Speaker 2: percent of our drugs are being produced through agricultural sourcing. 304 00:15:52,916 --> 00:15:57,436 Speaker 2: These are very complex basically drug ingredients. We cannot produce 305 00:15:57,436 --> 00:16:00,236 Speaker 2: them at scale with chemical synthesis, and so we still 306 00:16:00,276 --> 00:16:02,916 Speaker 2: basically rely on biological synthesis to produce them. 307 00:16:03,076 --> 00:16:05,556 Speaker 1: To be clear, you mean they come from plants. 308 00:16:05,476 --> 00:16:09,956 Speaker 2: Plants, sometimes other animals, right, So you know there are 309 00:16:10,436 --> 00:16:13,396 Speaker 2: in drug ingredients that are a extracted from animals or 310 00:16:13,436 --> 00:16:16,036 Speaker 2: even you know, sometimes it could be rare marine coral. 311 00:16:16,116 --> 00:16:17,716 Speaker 2: I mean, you know, but so you do really get 312 00:16:17,716 --> 00:16:19,156 Speaker 2: a spectrum. I think the bulk of it is going 313 00:16:19,196 --> 00:16:21,436 Speaker 2: to be plants, but it will meld into other areas. 314 00:16:22,036 --> 00:16:24,636 Speaker 2: But all of these you can imagine, these supply chains 315 00:16:24,636 --> 00:16:28,276 Speaker 2: are increasingly vulnerable. If you're farming in a small number 316 00:16:28,396 --> 00:16:30,476 Speaker 2: of areas across the globe and you have a fire 317 00:16:30,556 --> 00:16:32,876 Speaker 2: that goes through a region, or a flood, or you know, 318 00:16:32,996 --> 00:16:36,476 Speaker 2: any one of the sort of climate catastrophes we're sort 319 00:16:36,476 --> 00:16:38,636 Speaker 2: of seen and out of increasing frequency that can really 320 00:16:38,676 --> 00:16:42,916 Speaker 2: wipe out basically the crops and a large fraction of 321 00:16:43,116 --> 00:16:46,116 Speaker 2: the material that's being produced in any given year. And 322 00:16:46,196 --> 00:16:50,036 Speaker 2: so there can have these variabilities, right, also variabilities in 323 00:16:50,076 --> 00:16:52,916 Speaker 2: farming practices, variability and pest and disease that go through 324 00:16:52,916 --> 00:16:54,716 Speaker 2: an area. The point is that there's a lot of 325 00:16:54,796 --> 00:16:58,956 Speaker 2: vulnerability and variability that is becoming increasingly difficult to predict 326 00:16:58,996 --> 00:17:01,996 Speaker 2: and also just increasing in frequency. So what that means 327 00:17:02,076 --> 00:17:04,436 Speaker 2: is that supplies can vary right from year to year, 328 00:17:04,476 --> 00:17:06,436 Speaker 2: from growing season to growing season. And the other thing 329 00:17:06,516 --> 00:17:09,676 Speaker 2: is because the manufacturing cycles are so long, you know, 330 00:17:09,756 --> 00:17:11,756 Speaker 2: any one of these because of the time it takes 331 00:17:11,796 --> 00:17:15,076 Speaker 2: to grow the biomass or the organism right to complete 332 00:17:15,076 --> 00:17:17,876 Speaker 2: a manufacturing cycle. For most medicinal plants, it can be 333 00:17:17,996 --> 00:17:21,316 Speaker 2: two years to sometimes five years, right, just because of 334 00:17:21,356 --> 00:17:23,796 Speaker 2: how slow they might grow. So if you wipe out 335 00:17:24,396 --> 00:17:26,396 Speaker 2: a crop for any given growing season, you don't have 336 00:17:26,436 --> 00:17:30,116 Speaker 2: the ability to just grow more, right, you have to replant, 337 00:17:30,156 --> 00:17:32,996 Speaker 2: receive That can take years, So there's no ability to 338 00:17:32,996 --> 00:17:37,156 Speaker 2: sort of respond rapidly if demand changes or if you know, 339 00:17:37,276 --> 00:17:41,076 Speaker 2: part of your supply chain basically goes down with fermentation. 340 00:17:41,516 --> 00:17:45,516 Speaker 2: Right now, what you have is very sort of consistent infrastructure. 341 00:17:45,516 --> 00:17:49,756 Speaker 2: It's basically a fermentation vat whether you're producing a chemotherapeutic, 342 00:17:50,116 --> 00:17:54,596 Speaker 2: a sedative and anti infective right, or a pain medication. 343 00:17:55,156 --> 00:17:59,156 Speaker 2: Regardless of what ingredient you're producing, the infrastructure is the same. 344 00:17:59,276 --> 00:18:02,436 Speaker 2: You're basically swapping in different strains of yeast, and the 345 00:18:02,436 --> 00:18:05,476 Speaker 2: manufacturing cycle time is so fast, right, It's basically two 346 00:18:05,476 --> 00:18:08,796 Speaker 2: weeks a week to grow the yeast, get the drug produced, 347 00:18:08,796 --> 00:18:10,836 Speaker 2: and then an other several days to purify it to 348 00:18:10,916 --> 00:18:14,516 Speaker 2: really pure form. So because of the fast manufacturing cycle time, 349 00:18:14,956 --> 00:18:19,356 Speaker 2: and then because the infrastructure is very readily repurposable, right, 350 00:18:19,356 --> 00:18:22,996 Speaker 2: because ultimately it's the same, you can and you can 351 00:18:23,036 --> 00:18:26,756 Speaker 2: actually switch a facility from producing a chemotherapeutic to producing 352 00:18:26,796 --> 00:18:28,556 Speaker 2: a sedative in a matter of two days. 353 00:18:28,876 --> 00:18:31,396 Speaker 1: So the dream is to be the swing supply or 354 00:18:31,396 --> 00:18:34,036 Speaker 1: for whatever ingredient is in short supply in a way 355 00:18:34,076 --> 00:18:37,556 Speaker 1: that people who are using traditional technologies cannot be because 356 00:18:37,556 --> 00:18:39,116 Speaker 1: of the nature of the technology. 357 00:18:39,836 --> 00:18:41,316 Speaker 2: Yeah, I mean, I would let me just say, I 358 00:18:41,316 --> 00:18:44,316 Speaker 2: think I think for for me, the dream is actually 359 00:18:44,316 --> 00:18:46,836 Speaker 2: to disrupt the market, right, I mean, we shouldn't be 360 00:18:46,916 --> 00:18:51,476 Speaker 2: farming drug ingredients. It's very wasteful from a resource perspective 361 00:18:51,796 --> 00:18:54,156 Speaker 2: that land can be used to produce food, right, and 362 00:18:54,276 --> 00:18:58,236 Speaker 2: other products that you know we need for a growing population, right, 363 00:18:58,276 --> 00:19:00,556 Speaker 2: you waste a lot of biomass. You waste a lot 364 00:19:00,596 --> 00:19:02,596 Speaker 2: of water, I mean other things because most of that 365 00:19:02,636 --> 00:19:05,676 Speaker 2: plant material you're basically throwing away. It's just not a 366 00:19:05,676 --> 00:19:08,796 Speaker 2: good use of resources. So really the dream is this 367 00:19:08,796 --> 00:19:12,596 Speaker 2: techno should disrupt and transform the industry. It just makes 368 00:19:12,636 --> 00:19:16,716 Speaker 2: more sense, right. It can actually provide these ingredients at 369 00:19:16,716 --> 00:19:19,996 Speaker 2: a cheaper cost, It could provide them at a more consistent, 370 00:19:20,436 --> 00:19:23,396 Speaker 2: better quality, right, And it's it's just a more efficient 371 00:19:23,476 --> 00:19:26,156 Speaker 2: use of resources. So it really should be that transformation 372 00:19:26,196 --> 00:19:26,836 Speaker 2: in the industry. 373 00:19:30,516 --> 00:19:32,796 Speaker 1: We'll be back in a minute with the lightning round. 374 00:19:43,556 --> 00:19:45,516 Speaker 1: Back to the show. We just have to do a 375 00:19:45,556 --> 00:19:48,276 Speaker 1: lightning round, and then you can go. As a professor 376 00:19:48,276 --> 00:19:53,196 Speaker 1: of bioengineering, what do you understand about biology and or 377 00:19:53,276 --> 00:19:56,436 Speaker 1: engineering that most people don't understand? 378 00:19:56,876 --> 00:20:01,676 Speaker 2: I think you know. One thing is as engineers, we 379 00:20:01,796 --> 00:20:05,916 Speaker 2: provide solutions. We develop solutions with imperfect data, right, and 380 00:20:05,996 --> 00:20:08,276 Speaker 2: imperfect knowledge of the system. We have to have enough 381 00:20:08,316 --> 00:20:10,916 Speaker 2: knowledge and enough day to provide solutions that are going 382 00:20:10,956 --> 00:20:13,196 Speaker 2: to be meaningful, that are going to scale, right. But 383 00:20:13,396 --> 00:20:16,996 Speaker 2: and I think that can be at odds with a biologist, right, 384 00:20:17,076 --> 00:20:19,076 Speaker 2: or someone who's studying the pure science where we really 385 00:20:19,116 --> 00:20:22,036 Speaker 2: want to understand all the nuance, you know, understand everything 386 00:20:22,036 --> 00:20:24,156 Speaker 2: in sort of the beautiful detailed intricacy. 387 00:20:24,276 --> 00:20:25,796 Speaker 1: What's your favorite yeast? 388 00:20:26,516 --> 00:20:32,116 Speaker 2: Yeah, I really do like sacrimicos seravisier and you. 389 00:20:32,076 --> 00:20:33,916 Speaker 1: Know, tell me about sacrimisis. 390 00:20:34,156 --> 00:20:37,076 Speaker 2: Well, it's a it's a strain of use that we 391 00:20:37,156 --> 00:20:39,076 Speaker 2: use at anthea, but it's also the strain of right, 392 00:20:39,076 --> 00:20:41,916 Speaker 2: it's also use that are used again as brewers use 393 00:20:41,996 --> 00:20:42,796 Speaker 2: you know Baker's uast. 394 00:20:42,916 --> 00:20:45,396 Speaker 1: Right, if you weren't working on drug ingredients, what would 395 00:20:45,396 --> 00:20:45,956 Speaker 1: you be working on? 396 00:20:49,236 --> 00:20:51,996 Speaker 2: It's a good question. There's there's different ways to take that. 397 00:20:52,076 --> 00:20:54,436 Speaker 2: I mean, I think that there are a lot of 398 00:20:55,076 --> 00:20:58,396 Speaker 2: problems that are important in the context of synthetic biology. 399 00:20:59,476 --> 00:21:02,636 Speaker 2: You know, I could also I would love to also 400 00:21:02,996 --> 00:21:04,716 Speaker 2: there's another part of my life and sort of a 401 00:21:04,756 --> 00:21:06,276 Speaker 2: second life that I might live where I'm in a 402 00:21:06,356 --> 00:21:10,396 Speaker 2: very different industry. Right, So you know, but that that 403 00:21:10,436 --> 00:21:12,276 Speaker 2: did not that is not the road that we took. 404 00:21:12,796 --> 00:21:14,796 Speaker 1: What like, I feel like there's a very particular thing 405 00:21:14,836 --> 00:21:17,516 Speaker 1: in your mind as you say that, what is that? No? No, no, 406 00:21:17,556 --> 00:21:20,716 Speaker 1: I mean I you're thinking of something. What is the 407 00:21:20,716 --> 00:21:23,196 Speaker 1: thing I always. 408 00:21:22,916 --> 00:21:25,916 Speaker 2: I always joke with my friends and I would love 409 00:21:25,956 --> 00:21:28,436 Speaker 2: to just you know, my retirement plan on basically after 410 00:21:28,516 --> 00:21:31,196 Speaker 2: all of this is to go be like, I don't know, 411 00:21:31,356 --> 00:21:35,476 Speaker 2: an assistant to someone like Wes Anderson who makes these 412 00:21:35,476 --> 00:21:39,916 Speaker 2: incredible films that you know, I adore and I feel, 413 00:21:39,996 --> 00:21:42,596 Speaker 2: you know, and and really just create these very interesting worlds, 414 00:21:42,596 --> 00:21:44,556 Speaker 2: and I feel like I just would want to, you know, 415 00:21:44,596 --> 00:21:46,396 Speaker 2: maybe get his coffee or something. 416 00:21:46,516 --> 00:21:48,876 Speaker 1: Do you think of going into the movies when you 417 00:21:48,916 --> 00:21:50,636 Speaker 1: were whatever in college or something? 418 00:21:50,676 --> 00:21:52,876 Speaker 2: I mean in high school, I actually spent all my 419 00:21:52,916 --> 00:21:56,516 Speaker 2: time in drama, right, basically you know, doing school plays, 420 00:21:56,556 --> 00:21:58,996 Speaker 2: doing musicals, I mean, all that stuff. So and I 421 00:21:59,036 --> 00:22:00,996 Speaker 2: really thought up until the point of I was making 422 00:22:01,036 --> 00:22:04,676 Speaker 2: decisions to apply to college, you know, I thought that 423 00:22:04,676 --> 00:22:08,236 Speaker 2: I would go into basically theater and you know, do theater, 424 00:22:08,396 --> 00:22:11,036 Speaker 2: do movies, whatever. And then I just, you know, as 425 00:22:11,076 --> 00:22:15,916 Speaker 2: I was actually applying, kind of had a revelation of 426 00:22:16,156 --> 00:22:17,636 Speaker 2: do I really want to do that, you know, for 427 00:22:17,676 --> 00:22:20,596 Speaker 2: the rest of my life? It actually seemed difficult. Not 428 00:22:20,636 --> 00:22:22,436 Speaker 2: that what we're doing now isn't difficult, but it seemed 429 00:22:22,436 --> 00:22:25,316 Speaker 2: difficult in a way that maybe was difficult. You know, 430 00:22:25,396 --> 00:22:27,316 Speaker 2: even as much work as I could put in, right, 431 00:22:27,396 --> 00:22:30,316 Speaker 2: it's it's not necessarily you can't necessarily project the outcome, 432 00:22:30,676 --> 00:22:32,756 Speaker 2: and even at that time, you know, it was sort 433 00:22:32,796 --> 00:22:35,036 Speaker 2: of taking a step back and saying, you know, what 434 00:22:35,076 --> 00:22:36,476 Speaker 2: can I do? What do I want to do? Which 435 00:22:36,476 --> 00:22:39,316 Speaker 2: allows me to sort of build create, you know, and 436 00:22:39,756 --> 00:22:42,356 Speaker 2: make things and produce things, but something that could really 437 00:22:42,356 --> 00:22:45,556 Speaker 2: have a meaningful impact right on the world. And so 438 00:22:45,636 --> 00:22:48,676 Speaker 2: that kind of that then led me to engineering, you know, 439 00:22:48,836 --> 00:22:51,796 Speaker 2: engineering with biology and and and really that sort of 440 00:22:51,836 --> 00:22:53,676 Speaker 2: started that route as I went into college. 441 00:22:54,596 --> 00:22:57,316 Speaker 1: I've taken up enough of your time. Is there anything 442 00:22:57,356 --> 00:22:58,156 Speaker 1: else you want to say? 443 00:22:59,756 --> 00:23:02,036 Speaker 2: No, I think you've done a great job of directing 444 00:23:02,076 --> 00:23:05,676 Speaker 2: the conversation. So hopefully it's you know, then at a 445 00:23:05,676 --> 00:23:07,276 Speaker 2: good level for the Are. 446 00:23:07,156 --> 00:23:09,116 Speaker 1: They not at all worried? Sometimes at the end of inner, 447 00:23:09,436 --> 00:23:10,756 Speaker 1: I'm like, how am I going to make this work? Guy? 448 00:23:10,796 --> 00:23:12,356 Speaker 1: This is gonna be an easy one. This is great. 449 00:23:12,436 --> 00:23:14,756 Speaker 2: Thank you, absolutely, thank you. 450 00:23:20,876 --> 00:23:24,436 Speaker 1: Christina Smolke is the co founder and CEO of Anthea. 451 00:23:25,796 --> 00:23:29,956 Speaker 1: Today's show was edited by Karen Chakerjee, produced by Edith Russolo, 452 00:23:30,116 --> 00:23:31,676 Speaker 1: and engineered by Amanda K. 453 00:23:32,036 --> 00:23:32,316 Speaker 2: Wall. 454 00:23:33,596 --> 00:23:36,436 Speaker 1: You can email us at problem at pushkin dot fm. 455 00:23:36,476 --> 00:23:40,316 Speaker 1: We are always, always, always trying to find interesting new 456 00:23:40,356 --> 00:23:42,276 Speaker 1: guests for the show, So if there's somebody who think 457 00:23:42,276 --> 00:23:45,236 Speaker 1: we should book, please let us know. I'm Jacob Goldstein 458 00:23:45,276 --> 00:23:47,476 Speaker 1: and we'll be back next week with another episode of 459 00:23:47,516 --> 00:23:52,916 Speaker 1: What's Your Problem.