WEBVTT - Getting Yeast to Make Medicine 0:00:15.356 --> 0:00:22.916 Pushkin. There's this problem that's been going on in the 0:00:22.956 --> 0:00:26.276 background in the United States for a long time. The 0:00:26.316 --> 0:00:31.996 problem is this, there are not enough drugs to go around. This, strangely, 0:00:32.436 --> 0:00:35.436 is not about expensive new drugs that people can't afford. 0:00:35.876 --> 0:00:39.836 This is about old, cheap generic drugs, drugs that just 0:00:39.916 --> 0:00:43.436 are not available in sufficient quantities at any price. A 0:00:43.516 --> 0:00:47.756 national pharmacist group recently reported shortages of three hundred and 0:00:47.956 --> 0:00:52.316 nine of these generic drugs. There are multiple causes. It 0:00:52.356 --> 0:00:55.596 could be the bankruptcy of some little known generic drug maker. 0:00:55.876 --> 0:00:58.956 Could be a sudden surge in demand. Could be the 0:00:58.956 --> 0:01:01.916 failure of some distant crop that is the source of 0:01:01.956 --> 0:01:06.276 an essential drug ingredient. It's a complicated problem built out 0:01:06.316 --> 0:01:09.916 of lots of little problems. But broadly speaking, the supply 0:01:10.076 --> 0:01:14.036 chain for generic drugs is long and opaque and exists 0:01:14.156 --> 0:01:17.356 largely outside of the United States, so it is very 0:01:17.396 --> 0:01:25.676 difficult to see these drug shortages coming. I'm Jacob Goldstein 0:01:25.756 --> 0:01:27.716 and this is What's Your Problem, the show where I 0:01:27.796 --> 0:01:30.836 talk to people who are trying to make technological progress. 0:01:31.396 --> 0:01:34.756 My guest today is Christina Smolky. She's a professor at 0:01:34.796 --> 0:01:37.956 Stanford and the co founder and CEO of a company 0:01:37.956 --> 0:01:41.356 called Anthea. It's a synthetic biology company. They're in the 0:01:41.396 --> 0:01:47.356 business of genetically engineering microorganisms to produce commercial products. Christina's 0:01:47.396 --> 0:01:50.596 problem is this, how do you turn ye cells into 0:01:50.676 --> 0:01:55.756 tiny factories to create the active ingredients in drugs. If 0:01:55.836 --> 0:01:58.956 Christina and her colleagues solve this problem, they won't solve 0:01:58.996 --> 0:02:02.156 the drug shortage problem entirely, but they might help make 0:02:02.196 --> 0:02:02.676 it better. 0:02:05.596 --> 0:02:08.516 I actually started not in industry, not as a CEO 0:02:08.556 --> 0:02:10.716 of a company, but I started as a professor. And 0:02:10.756 --> 0:02:13.236 so there, you know, I was coming out the field 0:02:13.516 --> 0:02:16.076 in a more academic way, looking at here's the state 0:02:16.076 --> 0:02:18.716 of the technology, but think about how much more we 0:02:18.716 --> 0:02:21.436 could do if we really open this up. And so, 0:02:21.636 --> 0:02:23.756 you know, it was really let's focus on the hard problems. 0:02:23.836 --> 0:02:26.196 Let's focus on the problems that people say right now 0:02:26.236 --> 0:02:28.676 are impossible, that you will never get this to work, 0:02:28.876 --> 0:02:31.596 the science just can't do it. And let's figure out 0:02:31.716 --> 0:02:36.316 can we actually you know, make these impossible solutions possible 0:02:36.356 --> 0:02:38.556 to really address these problems. And so that's where it started. 0:02:38.636 --> 0:02:40.796 You know, for about fifteen years of my career was 0:02:40.876 --> 0:02:45.796 really focusing on the you know, foundational scientific breakthroughs that 0:02:45.836 --> 0:02:48.476 were needed to build a company like Anthea and really 0:02:48.796 --> 0:02:51.076 bring those transformations into the industry. 0:02:51.476 --> 0:02:54.476 So when you when you're starting out, you're thinking, Okay, 0:02:54.516 --> 0:02:58.036 there is this nascent field synthetic biology, this basic idea, 0:02:58.796 --> 0:03:01.076 I want to advance this field to the point where 0:03:01.076 --> 0:03:03.556 we can make you know, drugs or the active ingredient 0:03:03.556 --> 0:03:05.916 in drugs exactly what are the things people didn't know 0:03:05.956 --> 0:03:07.956 how to do that you and your colleagues had to 0:03:07.956 --> 0:03:08.396 figure out. 0:03:09.356 --> 0:03:12.236 So there was a lot to figure out. And you know, 0:03:12.276 --> 0:03:14.236 first and foremost when you looked at where the field 0:03:14.396 --> 0:03:17.676 was when we when I started in this space, most 0:03:17.716 --> 0:03:20.436 of where everybody focused and it's actually true still today 0:03:20.876 --> 0:03:25.516 is on engineering cells to produce relatively simple compounds. So 0:03:25.596 --> 0:03:26.996 let's just take a step back, and you know, we 0:03:27.116 --> 0:03:31.076 use yeast, very similar organism that yeah, basically identical organism 0:03:31.116 --> 0:03:34.836 that we've been using for centuries to brew beer, ferment wine, right, 0:03:35.076 --> 0:03:38.036 so we have a long standing history of that. That's biomanufacturing. 0:03:38.436 --> 0:03:42.476 But what the yeast of producing is ethanol, right, carbon dioxide, 0:03:42.596 --> 0:03:46.556 very simple molecules that it does naturally. Now take a 0:03:46.556 --> 0:03:49.836 step back, we want that yeast to produce a very 0:03:49.836 --> 0:03:55.076 complex chemotherapeutic, right, or a very complex anti infective. How 0:03:55.116 --> 0:03:57.196 do we teach it to do that? And when you 0:03:57.236 --> 0:03:59.396 looked at where we started, you know, in this in 0:03:59.476 --> 0:04:02.356 this field, what the field was capable of doing was 0:04:02.356 --> 0:04:06.036 basically taking a organism like yeast and maybe moving you know, 0:04:06.196 --> 0:04:10.876 three genes or three proteins into that organism. That basically 0:04:10.956 --> 0:04:14.436 allowed the industry to produce very simple compounds. 0:04:13.916 --> 0:04:16.076 Perfume, right. I feel like perfume was one of the 0:04:16.076 --> 0:04:17.596 big ones, sense exactly. 0:04:17.636 --> 0:04:20.316 Very close in structure to what the yeast could already make. Right, 0:04:20.956 --> 0:04:25.356 in order to actually make these you know, drug ingredients, 0:04:25.596 --> 0:04:27.676 we had to be able to transform the field from 0:04:27.676 --> 0:04:30.196 thinking about and being able to sort of routinely move 0:04:30.236 --> 0:04:33.916 maybe three to six genes or protein coding sequences into 0:04:33.916 --> 0:04:37.836 the cell to be able to actually move twenty thirty 0:04:37.956 --> 0:04:41.396 or more genes and protein sequences into a cell. And again, 0:04:41.516 --> 0:04:44.556 these drug ingredients that we rely on are so you know, 0:04:44.556 --> 0:04:46.916 they're so different, and they're so complicated from what yeast 0:04:46.916 --> 0:04:47.676 would normally make. 0:04:47.916 --> 0:04:52.436 Yes, it was not built to make chemotherapy drugs, right, 0:04:52.756 --> 0:04:56.396 to spend a billion years evolving to make the drugs 0:04:56.436 --> 0:04:58.996 we need to cure cancer exactly. So it is the 0:04:59.116 --> 0:05:01.116 basic problem that like if you try and swap in 0:05:01.196 --> 0:05:04.276 that many genes at once, the cell will just kind 0:05:04.316 --> 0:05:06.196 of blow up and die. Be like, what are you 0:05:06.236 --> 0:05:08.716 doing to me? I mean it's that the basic starting problem. 0:05:08.796 --> 0:05:10.676 Yeah, you know that was certainly I would say the 0:05:11.156 --> 0:05:14.916 general sort of I guess thinking at the time, right, 0:05:14.956 --> 0:05:17.236 And you know, when we propose to do this, you know, 0:05:17.316 --> 0:05:19.956 in my academic lab, we had a difficult time getting 0:05:19.956 --> 0:05:22.396 funding for it, even at like a research level, because 0:05:22.436 --> 0:05:25.036 the reviews would come back and say, this is you know, 0:05:25.196 --> 0:05:27.436 this is impossible. There's no reason to even try to 0:05:27.476 --> 0:05:29.236 do this because it will never work. 0:05:29.356 --> 0:05:32.316 It's an engineering problem at a certain level at that point, right, 0:05:32.356 --> 0:05:34.876 That is the sort of you have if you have 0:05:34.996 --> 0:05:38.276 the genomic information, you know what genes you want, but 0:05:38.316 --> 0:05:39.836 you got to figure out how to make them work 0:05:39.916 --> 0:05:44.116 in a yeast, right, And I mean I want to 0:05:44.156 --> 0:05:46.116 ask how do you do that? Although I know that's 0:05:46.156 --> 0:05:48.836 like a ten year long answer, So maybe what I'll 0:05:48.836 --> 0:05:52.036 ask instead is like, is there one piece of figuring 0:05:52.036 --> 0:05:55.876 out how to do that that you can explain? You know, 0:05:56.036 --> 0:05:58.396 is there one one thing you had to figure out 0:05:58.396 --> 0:06:00.356 along the way where you came upon it and it 0:06:00.396 --> 0:06:03.276 didn't work, and you figured out how to make it work. 0:06:04.116 --> 0:06:07.116 Yeah, and you're right, this is an engineering problem. It's 0:06:07.116 --> 0:06:11.516 a systems engineering problem. Right. So ultimately we're asking the 0:06:11.596 --> 0:06:15.316 yeast to be this sort of mini nanofactory to produce 0:06:15.396 --> 0:06:19.156 drug ingredients. Right, So not these sort of macro factories 0:06:19.196 --> 0:06:21.676 we build out, you know, in our world, but really 0:06:21.716 --> 0:06:24.716 kind of a cellular factory. So what's happening inside the cell. 0:06:25.036 --> 0:06:27.316 One of the things that we brought to this field 0:06:27.436 --> 0:06:29.556 is sort of a very unique strategy was to say, 0:06:30.316 --> 0:06:32.276 you know, let's not the cell is not just a bag, 0:06:32.476 --> 0:06:34.956 right where everything just sort of happens in this nebulous form. 0:06:35.036 --> 0:06:37.756 Let's really think smartly about the cell as a system 0:06:38.076 --> 0:06:40.516 and the biochemical environments that are in different locations of 0:06:40.516 --> 0:06:42.996 the cell. And then when we change the sequence of 0:06:42.996 --> 0:06:45.996 the proteins, we would very specifically give the yeast directions 0:06:46.036 --> 0:06:50.076 of make this particular protein in this part of the 0:06:50.116 --> 0:06:53.156 cell because there's a particular pH to do some environment, 0:06:53.196 --> 0:06:55.476 you know. And then but this other part of you know, 0:06:55.476 --> 0:06:58.156 the molecular machinery, the other steps of the proteins, we 0:06:58.196 --> 0:07:00.156 want you to actually make it in this other area 0:07:00.156 --> 0:07:00.596 of the cell. 0:07:00.956 --> 0:07:03.196 So just to write to pick up on your factory metaphors. 0:07:03.236 --> 0:07:06.356 So it's like the naive way to think about the 0:07:06.356 --> 0:07:08.916 inside of the cell is just like a big empty room. 0:07:09.396 --> 0:07:11.756 But you're thinking, like, no, it's not like that. I mean, 0:07:11.756 --> 0:07:13.476 if the factory is the analogy, it's like, this part 0:07:13.476 --> 0:07:16.196 over here is like where we should be whatever putting 0:07:16.236 --> 0:07:18.236 the wheels on, and this part over here is clearly 0:07:18.236 --> 0:07:20.796 where like the robot arms should be bolting the chassis together. 0:07:20.796 --> 0:07:24.676 Because different parts of the inside of the cell are different, 0:07:24.756 --> 0:07:27.476 are biochemically different, and some parts will work to do 0:07:27.876 --> 0:07:31.676 some things and other parts will work to do other things, 0:07:31.676 --> 0:07:33.636 and you can't do it in the wrong place or 0:07:33.676 --> 0:07:36.676 it won't work exactly exactly. 0:07:36.676 --> 0:07:38.636 I mean, that's an exact metaphor, right, and the exact 0:07:38.676 --> 0:07:39.756 way to think about it, right. 0:07:40.116 --> 0:07:42.796 And so let me ask just a few dumb questions 0:07:42.796 --> 0:07:44.796 about that, because it's interesting. How do you tell the 0:07:44.836 --> 0:07:47.116 cell where to do it? 0:07:47.116 --> 0:07:49.356 It ultimately comes down to the directions you put in 0:07:49.356 --> 0:07:52.196 the DNA, right, And it comes back to that gencoding 0:07:52.236 --> 0:07:55.356 sequence where I mean, again it's biology does remarkable things, 0:07:55.436 --> 0:07:58.716 but within you know, within that encoded sequence, you know 0:07:58.756 --> 0:08:02.316 there are directions of you know, again exactly what amino acids. 0:08:02.356 --> 0:08:05.236 You know, how you are basically making that protein amino 0:08:05.276 --> 0:08:08.316 acid by amino acid. But there are also directions that 0:08:08.396 --> 0:08:12.116 basically tell a cell and the cell's native machinery, no, 0:08:12.276 --> 0:08:14.076 you're going to actually make the protein over in this 0:08:14.196 --> 0:08:16.596 location right now. We want you to transport it over there. 0:08:16.636 --> 0:08:18.276 We want you to move this over here, We want 0:08:18.276 --> 0:08:20.396 you to insert it into this membrane. So you know, 0:08:20.396 --> 0:08:23.796 I mean again, the cell is, it's so sophisticated, right, 0:08:24.476 --> 0:08:27.476 we just you know, we just have to basically be 0:08:27.516 --> 0:08:31.116 able to understand enough about the directions that the cell 0:08:31.236 --> 0:08:34.356 uses and reads in its own native processes so that 0:08:34.396 --> 0:08:38.196 we can begin to leverage you know, the strategies and 0:08:38.236 --> 0:08:40.836 the routes that it has you know, developed, is a 0:08:40.836 --> 0:08:43.756 way to move proteins to particular locations and cells. 0:08:44.036 --> 0:08:48.156 So you figure that out over some period of time. 0:08:48.676 --> 0:08:52.516 Is there a first drug ingredient that you get a 0:08:52.676 --> 0:08:55.516 Y cell to make? Is there some like proof of 0:08:55.636 --> 0:08:56.556 concept moment? 0:08:57.396 --> 0:09:00.876 Yeah? There, yes, there was. So the drug ingredient that 0:09:00.916 --> 0:09:05.116 we initially demonstrated with this is an ingredient called the 0:09:05.236 --> 0:09:09.036 dane And this is actually an ingredient that is extracted 0:09:09.116 --> 0:09:11.556 from medicinal plants, and it's an ingredient that's used to 0:09:11.556 --> 0:09:15.956 produce about half a dozen different drug ingredients, from drugs 0:09:15.996 --> 0:09:19.316 that are used to treat you very severe pain, to 0:09:19.476 --> 0:09:23.516 drugs that are used as rescue mediations to treat addiction 0:09:24.476 --> 0:09:26.956 and as well as overdose. 0:09:27.436 --> 0:09:29.636 Like the drug that has the brand name Narcan. Is 0:09:29.636 --> 0:09:30.876 it not lots like that? 0:09:30.956 --> 0:09:31.076 Oh? 0:09:31.196 --> 0:09:31.596 Interesting? 0:09:31.796 --> 0:09:35.996 Is that drug Narcan and naloxone is a drug that 0:09:36.116 --> 0:09:39.476 is used that is basically produced from the vein. We 0:09:39.556 --> 0:09:43.396 published that demonstration, that proof of principal demonstration in twenty fifteen, 0:09:43.956 --> 0:09:46.036 so that was and again that was done prior to 0:09:46.076 --> 0:09:49.276 us starting anthea. It was done in our the academic 0:09:49.316 --> 0:09:54.436 lab at Stanford, and again that particular demonstration, it took 0:09:54.436 --> 0:09:57.636 over a decade, right to bring it all together. So 0:09:57.676 --> 0:09:59.476 it was a very long term project in my lab 0:09:59.876 --> 0:10:01.876 for the very reasons that we discussed for all of 0:10:01.876 --> 0:10:05.716 these challenges, right, and it was one that because I 0:10:05.716 --> 0:10:08.036 would say the field in general viewed it to be 0:10:08.076 --> 0:10:11.716 impossible and thus not worth you know, spending research dollars on. 0:10:11.756 --> 0:10:12.956 It was one that we spent a lot of time 0:10:12.956 --> 0:10:15.236 bootstrapping in my lab because I really had a lot 0:10:15.236 --> 0:10:16.876 of conviction that we could get this done. 0:10:16.996 --> 0:10:20.796 So you publish this paper to show that you can 0:10:21.436 --> 0:10:26.716 get yeased to produce this drug ingredient. What happens next? 0:10:26.956 --> 0:10:29.756 The next questions are can it be done at an 0:10:29.756 --> 0:10:34.076 efficiency and scale such that this can really offer you know, 0:10:34.156 --> 0:10:37.756 solutions right to the industry, Because if you take what 0:10:37.796 --> 0:10:40.396 we showed in twenty fifteen tried to scale it up, 0:10:40.676 --> 0:10:42.396 I mean you would it would not be offering a 0:10:42.396 --> 0:10:46.436 solution because it was so inefficient. Is still not efficiently 0:10:46.476 --> 0:10:50.836 converting the sugar to that drug ingredient such that it 0:10:50.836 --> 0:10:53.276 would just be too expensive because ultimately price is a 0:10:53.276 --> 0:10:56.036 big consideration. So you know, there were and just to 0:10:56.076 --> 0:10:58.596 give you like a sense of the degree what we're 0:10:58.596 --> 0:11:02.356 discussing here, right again, when we look at what was 0:11:02.356 --> 0:11:04.996 demonstrated in twenty fifteen, you know the yest we're producing 0:11:05.116 --> 0:11:08.676 very low concentrations of that drug ingredient. We at Inthea 0:11:08.716 --> 0:11:11.956 had to optimize that by over a millionfold, and not 0:11:12.036 --> 0:11:15.676 just in scale but in efficiency of converting. That had 0:11:15.716 --> 0:11:19.956 to be able to produce a million times higher concentration 0:11:20.636 --> 0:11:23.556 of that drug ingredient than what we demonstrated. 0:11:23.076 --> 0:11:25.916 A million times more drug per unit. 0:11:25.676 --> 0:11:28.796 Sugar exactly right, or per unit use really right, So. 0:11:28.796 --> 0:11:31.556 The yeast has to get way, way way better. Sure 0:11:31.556 --> 0:11:34.076 it can make the drug. It's really bad at making 0:11:34.076 --> 0:11:38.636 the drug. In two, it's terrible at making it exactly. 0:11:38.796 --> 0:11:41.236 That's sort of independent of scale, you know, in terms 0:11:41.236 --> 0:11:43.716 of like the volume that you're producing. It's saying, okay, 0:11:43.916 --> 0:11:45.716 you know, whether you're we're growing you at a mill 0:11:45.756 --> 0:11:47.916 or we're growing you at you know, one hundred thousand liters, 0:11:48.196 --> 0:11:50.396 we need you to really steff up your game. 0:11:50.636 --> 0:11:52.476 And yeah, right, you. 0:11:52.396 --> 0:11:54.756 Know, converting that sugar into the drug product. And so 0:11:55.356 --> 0:11:59.036 again that comes back to a lot it's an engineering problem. 0:11:59.076 --> 0:12:01.476 So okay, this is the next problem you have what 0:12:01.636 --> 0:12:02.996 you know, what what are some of the things you 0:12:03.036 --> 0:12:04.476 do to increase efficiency. 0:12:04.716 --> 0:12:06.636 So you know, again if we come back to this 0:12:06.756 --> 0:12:09.596 idea of you know, you're assembling a car and a factory, 0:12:09.676 --> 0:12:11.796 right and it's going through these different lines to sort 0:12:11.836 --> 0:12:14.156 of build it in a modular way. That's you know, 0:12:14.316 --> 0:12:17.356 the sort of manufacturing assembly line that you've developed is 0:12:17.356 --> 0:12:19.796 sort of where you want your your drug ingredient to 0:12:19.836 --> 0:12:23.156 stay on track, right, But it is operating within this 0:12:23.196 --> 0:12:26.196 more broader complex system of the yeast. And so the 0:12:26.276 --> 0:12:29.916 yeast will have just natural processes that it's developed, and 0:12:29.996 --> 0:12:32.396 some of those will actually begin to interface with the 0:12:32.436 --> 0:12:34.876 assembly line that you've put in, and so it. 0:12:34.796 --> 0:12:37.796 Can start the yeast is busy being a yeast cell, right, 0:12:37.836 --> 0:12:41.556 Like the yeast was not born to make this drug ingredient. 0:12:41.796 --> 0:12:43.636 And it's you know, it's busy, as you say, being 0:12:43.636 --> 0:12:45.476 in a e cell. It has its own objectives that 0:12:45.516 --> 0:12:48.836 it wants to achieve, right in terms of you know, growing, 0:12:49.036 --> 0:12:52.996 you know, doubling, and you know, producing its own products. Yeah, 0:12:53.156 --> 0:12:55.036 it has its own dreams and you know, things that 0:12:55.076 --> 0:12:57.676 it wants to accomplish. And so it's you know, the 0:12:57.756 --> 0:13:01.316 natural system that you put it within is basically interfacing 0:13:01.436 --> 0:13:03.116 with that assembly line that you've put it in. And 0:13:03.156 --> 0:13:07.876 in many cases, right those natural systems can actually pull 0:13:07.916 --> 0:13:11.476 away or divert your drug ingredient from the desired endpoint, 0:13:12.236 --> 0:13:14.276 just you know, because of these interactions. 0:13:14.316 --> 0:13:16.876 That's the weird thing, Like the yeast is making you crazy, 0:13:16.916 --> 0:13:19.796 but like the yeast is also like the thing that's 0:13:19.796 --> 0:13:22.436 making the thing you need exactly right, and so you have. 0:13:22.516 --> 0:13:25.556 To really balance that very carefully because and so I mean, 0:13:25.596 --> 0:13:28.476 you want the use to be multiplying, because every time 0:13:28.476 --> 0:13:31.156 it multiplies, it's providing another cell factory that's going to 0:13:31.156 --> 0:13:34.236 reduce drug ingredients. So you it's this balance between allowing 0:13:34.276 --> 0:13:36.596 the EAST to obtain its objectives, which also feed into 0:13:36.596 --> 0:13:39.476 your objectives, but then where it is, you know, being 0:13:39.516 --> 0:13:42.956 disruptive to your process, trying to make surgical changes that 0:13:42.996 --> 0:13:45.676 will still allow the yeast to be relatively happy, you know, 0:13:45.716 --> 0:13:47.516 and feel like it is doing what it needs to do, 0:13:47.596 --> 0:13:49.916 but still but then allowing more of your drug ingredient 0:13:49.956 --> 0:13:52.196 to grow, to go towards the product that you ultimately 0:13:52.236 --> 0:13:52.796 want to produce. 0:13:57.036 --> 0:13:59.116 A few weeks ago and they announced that they had 0:13:59.156 --> 0:14:03.156 completed their first manufacturing scale production of the bay and 0:14:03.236 --> 0:14:05.876 they plan to start selling the ingredient to drug makers 0:14:06.036 --> 0:14:19.116 next year. We'll be back in a minute. Now, back 0:14:19.156 --> 0:14:24.476 to the show. So let's talk about drug shortages. To me, 0:14:24.676 --> 0:14:29.116 still somewhat strange phenomenon in the United States, a country 0:14:29.156 --> 0:14:31.356 where we're a rich country and we spend tons of 0:14:31.356 --> 0:14:33.356 money on drugs, although no generic drugs are cheap, and 0:14:33.356 --> 0:14:34.796 that's part of the thing. We can talk about that, 0:14:35.076 --> 0:14:41.756 but it is remarkable how widespread and persistent drug shortages 0:14:41.796 --> 0:14:44.716 are shortages in particular of generic drugs, and they seem 0:14:44.716 --> 0:14:48.676 to be increasing over the last few years. What's going 0:14:48.716 --> 0:14:49.156 on there? 0:14:49.716 --> 0:14:51.396 I mean, I think one thing that has been noted 0:14:51.476 --> 0:14:53.916 and that is notable is that in the US we 0:14:54.036 --> 0:14:58.596 do not have manufacturing capacity to produce drug ingredients or 0:14:58.676 --> 0:15:01.476 drug products really, right, It's very limited. Most of the 0:15:01.516 --> 0:15:04.076 drugs that we consume are basically produced outside of the 0:15:04.196 --> 0:15:07.676 US about ninety percent. What that ultimately plays into quite 0:15:07.676 --> 0:15:10.916 a bit is lack of transparency and control over these 0:15:10.916 --> 0:15:14.676 supply chains, right, because we don't have any domestic capacity. 0:15:14.996 --> 0:15:18.316 Because the supply chains actually are quite complex in terms 0:15:18.356 --> 0:15:21.036 of the different players involved, oftentimes we don't have a 0:15:21.036 --> 0:15:25.396 lot of notice or yeah, really notice or transparency into 0:15:25.476 --> 0:15:27.236 if we expect that there's going to be an issue 0:15:27.236 --> 0:15:30.436 with the supply chain. Right, there's just again very limited transparency. 0:15:30.476 --> 0:15:33.196 It's very difficult to track through all the supply chains. Now, 0:15:33.596 --> 0:15:37.476 when you talk about just manufacturing technology for drugs and 0:15:37.516 --> 0:15:40.476 the ways that they're being manufactured, there's essentially two different 0:15:40.516 --> 0:15:43.356 ways that all of our drugs are being produced. Right. 0:15:43.636 --> 0:15:46.836 We talked about agricultural sourcing, which a lot of that 0:15:46.916 --> 0:15:49.756 is sort of where we focus. But again about forty 0:15:49.756 --> 0:15:52.796 percent of our drugs are being produced through agricultural sourcing. 0:15:52.916 --> 0:15:57.436 These are very complex basically drug ingredients. We cannot produce 0:15:57.436 --> 0:16:00.236 them at scale with chemical synthesis, and so we still 0:16:00.276 --> 0:16:02.916 basically rely on biological synthesis to produce them. 0:16:03.076 --> 0:16:05.556 To be clear, you mean they come from plants. 0:16:05.476 --> 0:16:09.956 Plants, sometimes other animals, right, So you know there are 0:16:10.436 --> 0:16:13.396 in drug ingredients that are a extracted from animals or 0:16:13.436 --> 0:16:16.036 even you know, sometimes it could be rare marine coral. 0:16:16.116 --> 0:16:17.716 I mean, you know, but so you do really get 0:16:17.716 --> 0:16:19.156 a spectrum. I think the bulk of it is going 0:16:19.196 --> 0:16:21.436 to be plants, but it will meld into other areas. 0:16:22.036 --> 0:16:24.636 But all of these you can imagine, these supply chains 0:16:24.636 --> 0:16:28.276 are increasingly vulnerable. If you're farming in a small number 0:16:28.396 --> 0:16:30.476 of areas across the globe and you have a fire 0:16:30.556 --> 0:16:32.876 that goes through a region, or a flood, or you know, 0:16:32.996 --> 0:16:36.476 any one of the sort of climate catastrophes we're sort 0:16:36.476 --> 0:16:38.636 of seen and out of increasing frequency that can really 0:16:38.676 --> 0:16:42.916 wipe out basically the crops and a large fraction of 0:16:43.116 --> 0:16:46.116 the material that's being produced in any given year. And 0:16:46.196 --> 0:16:50.036 so there can have these variabilities, right, also variabilities in 0:16:50.076 --> 0:16:52.916 farming practices, variability and pest and disease that go through 0:16:52.916 --> 0:16:54.716 an area. The point is that there's a lot of 0:16:54.796 --> 0:16:58.956 vulnerability and variability that is becoming increasingly difficult to predict 0:16:58.996 --> 0:17:01.996 and also just increasing in frequency. So what that means 0:17:02.076 --> 0:17:04.436 is that supplies can vary right from year to year, 0:17:04.476 --> 0:17:06.436 from growing season to growing season. And the other thing 0:17:06.516 --> 0:17:09.676 is because the manufacturing cycles are so long, you know, 0:17:09.756 --> 0:17:11.756 any one of these because of the time it takes 0:17:11.796 --> 0:17:15.076 to grow the biomass or the organism right to complete 0:17:15.076 --> 0:17:17.876 a manufacturing cycle. For most medicinal plants, it can be 0:17:17.996 --> 0:17:21.316 two years to sometimes five years, right, just because of 0:17:21.356 --> 0:17:23.796 how slow they might grow. So if you wipe out 0:17:24.396 --> 0:17:26.396 a crop for any given growing season, you don't have 0:17:26.436 --> 0:17:30.116 the ability to just grow more, right, you have to replant, 0:17:30.156 --> 0:17:32.996 receive That can take years, So there's no ability to 0:17:32.996 --> 0:17:37.156 sort of respond rapidly if demand changes or if you know, 0:17:37.276 --> 0:17:41.076 part of your supply chain basically goes down with fermentation. 0:17:41.516 --> 0:17:45.516 Right now, what you have is very sort of consistent infrastructure. 0:17:45.516 --> 0:17:49.756 It's basically a fermentation vat whether you're producing a chemotherapeutic, 0:17:50.116 --> 0:17:54.596 a sedative and anti infective right, or a pain medication. 0:17:55.156 --> 0:17:59.156 Regardless of what ingredient you're producing, the infrastructure is the same. 0:17:59.276 --> 0:18:02.436 You're basically swapping in different strains of yeast, and the 0:18:02.436 --> 0:18:05.476 manufacturing cycle time is so fast, right, It's basically two 0:18:05.476 --> 0:18:08.796 weeks a week to grow the yeast, get the drug produced, 0:18:08.796 --> 0:18:10.836 and then an other several days to purify it to 0:18:10.916 --> 0:18:14.516 really pure form. So because of the fast manufacturing cycle time, 0:18:14.956 --> 0:18:19.356 and then because the infrastructure is very readily repurposable, right, 0:18:19.356 --> 0:18:22.996 because ultimately it's the same, you can and you can 0:18:23.036 --> 0:18:26.756 actually switch a facility from producing a chemotherapeutic to producing 0:18:26.796 --> 0:18:28.556 a sedative in a matter of two days. 0:18:28.876 --> 0:18:31.396 So the dream is to be the swing supply or 0:18:31.396 --> 0:18:34.036 for whatever ingredient is in short supply in a way 0:18:34.076 --> 0:18:37.556 that people who are using traditional technologies cannot be because 0:18:37.556 --> 0:18:39.116 of the nature of the technology. 0:18:39.836 --> 0:18:41.316 Yeah, I mean, I would let me just say, I 0:18:41.316 --> 0:18:44.316 think I think for for me, the dream is actually 0:18:44.316 --> 0:18:46.836 to disrupt the market, right, I mean, we shouldn't be 0:18:46.916 --> 0:18:51.476 farming drug ingredients. It's very wasteful from a resource perspective 0:18:51.796 --> 0:18:54.156 that land can be used to produce food, right, and 0:18:54.276 --> 0:18:58.236 other products that you know we need for a growing population, right, 0:18:58.276 --> 0:19:00.556 you waste a lot of biomass. You waste a lot 0:19:00.596 --> 0:19:02.596 of water, I mean other things because most of that 0:19:02.636 --> 0:19:05.676 plant material you're basically throwing away. It's just not a 0:19:05.676 --> 0:19:08.796 good use of resources. So really the dream is this 0:19:08.796 --> 0:19:12.596 techno should disrupt and transform the industry. It just makes 0:19:12.636 --> 0:19:16.716 more sense, right. It can actually provide these ingredients at 0:19:16.716 --> 0:19:19.996 a cheaper cost, It could provide them at a more consistent, 0:19:20.436 --> 0:19:23.396 better quality, right, And it's it's just a more efficient 0:19:23.476 --> 0:19:26.156 use of resources. So it really should be that transformation 0:19:26.196 --> 0:19:26.836 in the industry. 0:19:30.516 --> 0:19:32.796 We'll be back in a minute with the lightning round. 0:19:43.556 --> 0:19:45.516 Back to the show. We just have to do a 0:19:45.556 --> 0:19:48.276 lightning round, and then you can go. As a professor 0:19:48.276 --> 0:19:53.196 of bioengineering, what do you understand about biology and or 0:19:53.276 --> 0:19:56.436 engineering that most people don't understand? 0:19:56.876 --> 0:20:01.676 I think you know. One thing is as engineers, we 0:20:01.796 --> 0:20:05.916 provide solutions. We develop solutions with imperfect data, right, and 0:20:05.996 --> 0:20:08.276 imperfect knowledge of the system. We have to have enough 0:20:08.316 --> 0:20:10.916 knowledge and enough day to provide solutions that are going 0:20:10.956 --> 0:20:13.196 to be meaningful, that are going to scale, right. But 0:20:13.396 --> 0:20:16.996 and I think that can be at odds with a biologist, right, 0:20:17.076 --> 0:20:19.076 or someone who's studying the pure science where we really 0:20:19.116 --> 0:20:22.036 want to understand all the nuance, you know, understand everything 0:20:22.036 --> 0:20:24.156 in sort of the beautiful detailed intricacy. 0:20:24.276 --> 0:20:25.796 What's your favorite yeast? 0:20:26.516 --> 0:20:32.116 Yeah, I really do like sacrimicos seravisier and you. 0:20:32.076 --> 0:20:33.916 Know, tell me about sacrimisis. 0:20:34.156 --> 0:20:37.076 Well, it's a it's a strain of use that we 0:20:37.156 --> 0:20:39.076 use at anthea, but it's also the strain of right, 0:20:39.076 --> 0:20:41.916 it's also use that are used again as brewers use 0:20:41.996 --> 0:20:42.796 you know Baker's uast. 0:20:42.916 --> 0:20:45.396 Right, if you weren't working on drug ingredients, what would 0:20:45.396 --> 0:20:45.956 you be working on? 0:20:49.236 --> 0:20:51.996 It's a good question. There's there's different ways to take that. 0:20:52.076 --> 0:20:54.436 I mean, I think that there are a lot of 0:20:55.076 --> 0:20:58.396 problems that are important in the context of synthetic biology. 0:20:59.476 --> 0:21:02.636 You know, I could also I would love to also 0:21:02.996 --> 0:21:04.716 there's another part of my life and sort of a 0:21:04.756 --> 0:21:06.276