WEBVTT - Turning Cells into Tiny Factories

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<v Speaker 1>Pushkin. One of the strange things about making a podcast

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<v Speaker 1>is you make the show, it goes out in the world.

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<v Speaker 1>Your mom tells you she likes it, but you don't

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<v Speaker 1>really know much about what people think of the show,

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<v Speaker 1>and in particular, you don't know how to make your

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<v Speaker 1>show better. And I really really want to make this

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<v Speaker 1>show better. I want this to be a show that

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<v Speaker 1>you look forward to every week, the show that you

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<v Speaker 1>tell your friends about. And so to that end, please

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<v Speaker 1>please please tell me how to do that. Tell me

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<v Speaker 1>how to make what's your problem a better show, a

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<v Speaker 1>show you like more. If there's some person you want

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<v Speaker 1>me to talk to, or some subject you want me

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<v Speaker 1>to cover, or something you want me to do differently, anything,

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<v Speaker 1>really let me know. You can email me at problem

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<v Speaker 1>at pushkin dot fm. That's problem at pushkin dot fm.

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<v Speaker 1>Or you can talk to me on Twitter. I'm at

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<v Speaker 1>Jacob Goldstein, just my name. To be honest, we don't

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<v Speaker 1>get that many email messages yet, not that many people

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<v Speaker 1>talk to me on Twitter. So I can guarantee you

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<v Speaker 1>I will personally read every email and Twitter message you

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<v Speaker 1>send with gratitude. Thank you. Now here's the show. Here's

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<v Speaker 1>a big, wild idea what if scientists and engineers could

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<v Speaker 1>turn yeast in bacteria into tiny factories that would manufacture

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<v Speaker 1>everything from perfume to food to fuel. This idea has

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<v Speaker 1>a name synthetic biology. People have been working on it

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<v Speaker 1>for more than a decade now, and it's really hard.

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<v Speaker 1>First you have to engineer DNA and then you stick

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<v Speaker 1>it into yeast or bacteria in order to make the

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<v Speaker 1>thing you want, the fragrance or the fuel or the food.

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<v Speaker 1>And then you have to figure out how to do

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<v Speaker 1>it at scale, how to make a lot of it,

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<v Speaker 1>and also you have to make it cheaper or better

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<v Speaker 1>than what's already out there. Really, the dream of synthetic

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<v Speaker 1>biology is like a whole new industrial revolution, but using

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<v Speaker 1>cells instead of machines. I'm Jacob Goldstein and this is

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<v Speaker 1>What's Your Problem, the show where entrepreneurs and engineers talk

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<v Speaker 1>about the world they're going to build once they solve

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<v Speaker 1>a few problems. My guest today is Reshma Shetty. She's

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<v Speaker 1>the co founder and chief operations officer of Ginko Bioworks.

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<v Speaker 1>It's one of the biggest synthetic biology companies in the world.

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<v Speaker 1>One big obvious problem that Ginko faces the company has

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<v Speaker 1>lost billions of dollars trying to turn synthetic biology into

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<v Speaker 1>a viable business. So the problem for today's show is this,

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<v Speaker 1>how do you try and do this big, hard thing

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<v Speaker 1>way out there on the scientific frontier and also eventually

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<v Speaker 1>make enough money to create a financially sustainable business. We

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<v Speaker 1>started our conversation talking about the original idea for Ginko,

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<v Speaker 1>which came to Reshma and her co founder when they

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<v Speaker 1>were grad students at MIT dreaming about the big things

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<v Speaker 1>they wanted to do with synthetic biology. So you start

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<v Speaker 1>a company. We did. We did. We started a company

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<v Speaker 1>because we worked at a place MT, like most academic institutions,

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<v Speaker 1>really focuses on doing new things. Right. Can you invent

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<v Speaker 1>something new? Can you discover something new so that you

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<v Speaker 1>can publish on it, Right, And that's what academia is

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<v Speaker 1>built to do. And that's a really great thing because

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<v Speaker 1>we should be discovering new things and we should be

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<v Speaker 1>inventing new things. Yeah, but with biology, what we really

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<v Speaker 1>felt was holding us back was not just doing something

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<v Speaker 1>new or inventing something new. It was could you make

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<v Speaker 1>the process of engineering biology faster, cheaper, easier. Yeah. And

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<v Speaker 1>what was interesting is that we started working on that

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<v Speaker 1>problem during grad school, but it just wasn't very celebrated.

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<v Speaker 1>People were like, why do you want to make it

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<v Speaker 1>easier for other people to do this? That seems like

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<v Speaker 1>a dumb thing. Work on it, right, You're just building tools.

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<v Speaker 1>You're not actually doing anything with the tools exactly right.

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<v Speaker 1>And so there's a sort of skepticism even at a

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<v Speaker 1>place like MT around spending your time tool building. Okay,

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<v Speaker 1>And so we decided to start a company, candidly, not

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<v Speaker 1>because I wanted to be a founder. I actually didn't

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<v Speaker 1>want to be a founder. You know, I had never

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<v Speaker 1>dreamt about starting a company before. But we felt that

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<v Speaker 1>starting a company was the best way to work on

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<v Speaker 1>this problem of how do you make biology easier to engineer?

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<v Speaker 1>I read that some of your earliest customers were in

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<v Speaker 1>the in the fragrance industry, and I thought going through

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<v Speaker 1>that work you did might be a case study to understand,

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<v Speaker 1>you know, what the company does and what kind of

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<v Speaker 1>problems come up and how you solve those problems. Can

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<v Speaker 1>you talk me through that work? Yeah? So when we

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<v Speaker 1>first started the company, you know, we didn't have a

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<v Speaker 1>particular technology, we didn't have a business model, we didn't

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<v Speaker 1>have a way of making money, right, it was a

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<v Speaker 1>great way to start a company. I highly recommend. But

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<v Speaker 1>what we did have was that we were kind of

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<v Speaker 1>voracious learners. We kept coming up with wrong hypotheses. Where

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<v Speaker 1>we finally got some traction was actually looking at the

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<v Speaker 1>flavor and fragrance industry. So it turned out that this

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<v Speaker 1>is a huge industry. It's a multibillion dollar industry that

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<v Speaker 1>almost no one's heard of. I certainly hadn't heard of

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<v Speaker 1>it when we started the company. But they make all

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<v Speaker 1>of the flavors and fragrances that go into household goods. Right,

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<v Speaker 1>So if you go browse the DETERSI denial, you know,

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<v Speaker 1>and you can probably smell some of the detergents and

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<v Speaker 1>soaps and shampoos and whatnot that are in your local supermarket,

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<v Speaker 1>you know, those fragrances are all concocted by the flavor

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<v Speaker 1>and fragrance industry. So it turned out that there was

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<v Speaker 1>this pain point in the flavor and fragrance industry where

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<v Speaker 1>they wanted to use biology to manufacture their ingredients, but

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<v Speaker 1>it just you know, it wasn't feasible at scale, and

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<v Speaker 1>so they were really interested in using fermentation. This idea

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<v Speaker 1>that you could grow yeast in a vat to produce

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<v Speaker 1>flavors and fragrances, much like you might brew beer. And

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<v Speaker 1>so cracking that nut was our first sort of realization, Hey,

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<v Speaker 1>there's actually really a market or engineeredsels that could produce

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<v Speaker 1>flavor and fragrance ingredients. Are you allowed to say specifically

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<v Speaker 1>what you did or is it like that? So some

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<v Speaker 1>of our earliest contracts were around things like peach flavor,

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<v Speaker 1>coconut flavor, and so, so what specifically do you do?

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<v Speaker 1>I mean, do you take some jeans from a peach

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<v Speaker 1>and stick them in a yeast and the yeast makes

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<v Speaker 1>peach smell? Is it like that? Yeah, basically, except you're

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<v Speaker 1>not just limited to beach, because it turns out that,

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<v Speaker 1>you know, biology has a lot of reuse and a

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<v Speaker 1>lot of commonality, and so it might be the actually

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<v Speaker 1>the best genes for making a peach flavor might not

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<v Speaker 1>come from a peach. They might come from another species,

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<v Speaker 1>which is kind of fascinating, right, And so you keep

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<v Speaker 1>tweaking it and iterating on it until you're making a

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<v Speaker 1>lot of your ingredient of interest. And so, right now,

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<v Speaker 1>somewhere in the world, is there like a vat full

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<v Speaker 1>of yeast, cranking out peach smell that's going to go

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<v Speaker 1>into like soap or shampoo or something. There absolutely is, yes,

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<v Speaker 1>So where is the company now? What's sort of what

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<v Speaker 1>is the state of Ginko now? The span of what

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<v Speaker 1>we work on is huge, right, everything from food to health,

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<v Speaker 1>to act culture, to flavors and fragrances. So we started

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<v Speaker 1>a joint venture with Buyer, the largest ad company in

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<v Speaker 1>the world, working on essentially a biofertilizer, So being able

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<v Speaker 1>to reduce the amount of fertilizer that we need to

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<v Speaker 1>grow crops like corn by essentially engineering microbes to provide

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<v Speaker 1>the fertilizer to provide the fixed nitrogen rather than fertilizer.

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<v Speaker 1>And if you actually look at it, fertilizer is incredibly

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<v Speaker 1>bad for the environment. The process by which we make

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<v Speaker 1>fertilizer in this world, I don't know, It's like something

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<v Speaker 1>like fertilizer is like six or seven percent greenhouse gas emissions.

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<v Speaker 1>I mean, it's something completely interesting. So it's the production

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<v Speaker 1>of fertilizer emits a lot of carbon dioxide into the atmosphere.

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<v Speaker 1>So if you can if you can reduce the need

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<v Speaker 1>to make fertilizer then that helps exactly solve the problem. Yeah,

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<v Speaker 1>so can you sort of give me a comparison of

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<v Speaker 1>the state of the world as it was when you

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<v Speaker 1>were in grad school versus the state of the world

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<v Speaker 1>that you have created now? In grad school, it probably

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<v Speaker 1>take me nine months or so to basically design, build,

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<v Speaker 1>and test twenty designs at a time, like twenty different Yeah,

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<v Speaker 1>twenty different genes or to many different pathways. Maybe at

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<v Speaker 1>a time that was like state of the art. How

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<v Speaker 1>long would it take Ginko now to try twenty designs. Well,

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<v Speaker 1>we wouldn't ever bother to try twenty designs. We only

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<v Speaker 1>try thousands of designs at a time. Okay, It still

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<v Speaker 1>takes a lot longer than i'd like. It still probably

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<v Speaker 1>takes three months to kind of go through the whole cycle,

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<v Speaker 1>maybe two months if we're lucky. So, if before it

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<v Speaker 1>was you could try twenty designs in nine months, how

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<v Speaker 1>many designs could you try now in two or three months.

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<v Speaker 1>Now I'm trying thousands of designs in two or three months.

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<v Speaker 1>Thousands Okay, So it's thousands of times faster than it

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<v Speaker 1>was when you started. Yeah, and then I can learn

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<v Speaker 1>from which ones worked and which ones didn't and even

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<v Speaker 1>more intelligently do my next round of thousands of designs.

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<v Speaker 1>And so is what you have built sort of like

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<v Speaker 1>a factory for testing? Have you built like a factory lab? Yeah,

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<v Speaker 1>it's it's essentially a factory for cell programming. What's it

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<v Speaker 1>look like. It's a whole bunch of robots sort of

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<v Speaker 1>placed in rows across the lab with these essentially train

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<v Speaker 1>tracks that can move samples between the different robots, and

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<v Speaker 1>so it's pretty cool looking. So like the robots are

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<v Speaker 1>like robot arms, and what's going on the train tracks? Yeah,

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<v Speaker 1>these these big arms that can basically move plates from

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<v Speaker 1>one robot to another and train tracks to be able

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<v Speaker 1>to move samples between the robots. To do the processing

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<v Speaker 1>steps you need to either read the DNA or write

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<v Speaker 1>the DNA, or put the DNA into cells or test

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<v Speaker 1>how those cells are performing. So the robots are doing

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<v Speaker 1>all of those steps. Yes, that's a dream after the break,

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<v Speaker 1>a problem Ginko has not solved yet. How do you

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<v Speaker 1>build a company based on this wild, radically new technology

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<v Speaker 1>and also make a profit. That's the end of the ads.

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<v Speaker 1>Now we're going back to the show. Kinko went public

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<v Speaker 1>last year and the company is now worth billions of dollars,

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<v Speaker 1>but Reshma and our co founders still haven't made the

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<v Speaker 1>company work as a profitable business. They have revenue, but

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<v Speaker 1>it doesn't come close to covering their costs, and so

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<v Speaker 1>the problem of becoming a profitable company is what we

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<v Speaker 1>focused on in the second part of the interview. It's

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<v Speaker 1>impressive in a way that you know, it's continued to

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<v Speaker 1>get funded and you've grown so big, and you have

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<v Speaker 1>lost and continued to lose a lot of money. I

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<v Speaker 1>feel like in the long run, that's a problem that

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<v Speaker 1>you have to solve eventually, Like how do you solve

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<v Speaker 1>that problem? So in our business, the way our business

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<v Speaker 1>model works is when we collaborate with a customer on

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<v Speaker 1>a self program, we get two different kinds of value

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<v Speaker 1>out of the relationship. We get fees and milestone payments

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<v Speaker 1>from our customers to help offset our dcosts, and we

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<v Speaker 1>get what's called downstream value share. Downstream value share typically

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<v Speaker 1>comes in the form of either royalties on products made

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<v Speaker 1>using Ginko organisms or equity stakes in our customers. And

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<v Speaker 1>we've been expanding a lot in the number of cell

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<v Speaker 1>programs that we've taken on, but many of them are

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<v Speaker 1>still in the development stage, and so essentially the way

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<v Speaker 1>we ultimately become a sustainable business is as more and

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<v Speaker 1>more of our cell programs successfully complete and recognize that

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<v Speaker 1>downstream value share. That's where the rail like ultimate long

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<v Speaker 1>term value potential of Ginko is. So you're basically saying

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<v Speaker 1>when the investments you've already made payoff, that will do it.

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<v Speaker 1>I mean, I get the math of what you're saying

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<v Speaker 1>is that you've put a lot of money into things,

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<v Speaker 1>and if they make a lot of money in the future,

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<v Speaker 1>then you will be profitable. Is that right? Yeah? I

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<v Speaker 1>mean it's like, um, you know, think about it. If

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<v Speaker 1>your typical like pharma biotech company, they lose the hundreds

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<v Speaker 1>of millions of dollars, right, but if the drug works,

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<v Speaker 1>there's like a big, big enough path at the end

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<v Speaker 1>to justify that upfront risk. Basically, it's sort of all

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<v Speaker 1>long shots, right. The drug companies essentially make lots and

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<v Speaker 1>lots of long shot bets and most of them don't work,

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<v Speaker 1>and then once in a while they have a huge

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<v Speaker 1>winner that makes up for all the ones that don't. Exactly,

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<v Speaker 1>but in our case, we instead of a company that

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<v Speaker 1>is betting up like typically in pharma or in biopharma,

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<v Speaker 1>you know, the company might have one bet, right, one

0:12:47.996 --> 0:12:50.476
<v Speaker 1>long shot bet, or maybe a couple of long shot bets.

0:12:50.956 --> 0:12:53.996
<v Speaker 1>We're a platform company, so we actually have lots and

0:12:54.116 --> 0:12:57.116
<v Speaker 1>lots of long, long shot bets, and you know, and honestly,

0:12:57.436 --> 0:12:59.636
<v Speaker 1>some of them are not going to work, right. You know,

0:12:59.876 --> 0:13:02.716
<v Speaker 1>some cell programs won't work, or the cell program will work,

0:13:02.756 --> 0:13:04.916
<v Speaker 1>but it won't commercialize the way we think, or whatnot.

0:13:05.356 --> 0:13:08.116
<v Speaker 1>The question is will there be enough winners, and will

0:13:08.156 --> 0:13:10.636
<v Speaker 1>they be those winners be big enough to justify the

0:13:10.716 --> 0:13:14.076
<v Speaker 1>whole thing? And we're betting that they will. I recognize

0:13:14.116 --> 0:13:16.316
<v Speaker 1>that we're sort of at a time will tell ending

0:13:16.476 --> 0:13:20.476
<v Speaker 1>of the narrative, and it's valid. It's clearly true. Time

0:13:20.516 --> 0:13:25.236
<v Speaker 1>will indeed tell. I'm just trying to think of how

0:13:25.276 --> 0:13:27.036
<v Speaker 1>to parse it. I mean, I guess another way to

0:13:27.116 --> 0:13:30.556
<v Speaker 1>think about it is whether and to what extent these

0:13:30.716 --> 0:13:34.356
<v Speaker 1>various bets will pay off. Let me flip the question

0:13:34.436 --> 0:13:37.396
<v Speaker 1>on you, right, yeah, please please, Here's the way I

0:13:37.556 --> 0:13:39.756
<v Speaker 1>look at it. Right, the world has a lot of

0:13:39.836 --> 0:13:43.996
<v Speaker 1>serious things that it is facing, right, climate change, pandemics,

0:13:44.516 --> 0:13:49.556
<v Speaker 1>you know, supply chain issues, right, having enough food to

0:13:49.716 --> 0:13:52.836
<v Speaker 1>feed our planet having enough clean water to provide to

0:13:52.956 --> 0:13:56.476
<v Speaker 1>our planet. Right to me, the cost of not doing

0:13:56.596 --> 0:14:00.316
<v Speaker 1>something is unfathomable to me. So I would much rather

0:14:00.796 --> 0:14:04.676
<v Speaker 1>try and fail at this, which at least has gives

0:14:04.756 --> 0:14:08.556
<v Speaker 1>us a shot of solving some of these pressing world problems,

0:14:09.196 --> 0:14:13.796
<v Speaker 1>then not try at all. In a minute, the Lightning Round,

0:14:13.956 --> 0:14:17.396
<v Speaker 1>where we learned Rashma's favorite micro organism, her least favorite

0:14:17.396 --> 0:14:19.916
<v Speaker 1>trait in a coworker, and the one piece of advice

0:14:19.956 --> 0:14:21.956
<v Speaker 1>she'd give to somebody who is trying to solve a

0:14:22.036 --> 0:14:32.356
<v Speaker 1>hard problem. Now let's get back to what's your problem? Now,

0:14:32.396 --> 0:14:35.196
<v Speaker 1>it's just the lightning round. Can we do the lightning round? Absolutely?

0:14:35.716 --> 0:14:38.836
<v Speaker 1>What's your favorite micro organism? E coli? That's what I did.

0:14:38.916 --> 0:14:42.476
<v Speaker 1>My PhD on tell me why E Coli is great? So.

0:14:43.516 --> 0:14:46.916
<v Speaker 1>Equali is this little microbe. It's found in every person's gout,

0:14:47.116 --> 0:14:49.356
<v Speaker 1>smells awful, smells like pooh. Right, it's part of what

0:14:49.476 --> 0:14:52.676
<v Speaker 1>makes your poo smell like pooh. And we did a

0:14:52.756 --> 0:14:56.476
<v Speaker 1>project when we were at MIT mentoring a group of

0:14:56.556 --> 0:14:59.836
<v Speaker 1>undergraduates to change the smell of ecali to smell like

0:14:59.876 --> 0:15:02.516
<v Speaker 1>weren't a green and bananas. So while Eli gets a

0:15:02.556 --> 0:15:06.796
<v Speaker 1>bad rap for smelling bad, You can actually reprogramage to

0:15:06.796 --> 0:15:09.956
<v Speaker 1>smell pretty good. What's your favorite trade and a co worker?

0:15:10.196 --> 0:15:13.196
<v Speaker 1>Passion and curiosity? What's your least favorite trait in a

0:15:13.276 --> 0:15:16.996
<v Speaker 1>co worker? Self promotion? If you have a ten minute

0:15:17.036 --> 0:15:18.476
<v Speaker 1>break in the middle of the day, what do you

0:15:18.556 --> 0:15:22.476
<v Speaker 1>do to relax? Take a walk through the lapse? What

0:15:22.836 --> 0:15:25.116
<v Speaker 1>is one piece of advice you would give to somebody

0:15:25.196 --> 0:15:27.836
<v Speaker 1>who's trying to solve a hard problem? Better to try

0:15:28.236 --> 0:15:31.836
<v Speaker 1>and fail than not try at all. It sounds trite, right,

0:15:31.996 --> 0:15:36.116
<v Speaker 1>but you know, the way I could get myself to

0:15:36.196 --> 0:15:38.476
<v Speaker 1>a place where I felt comfortable, you know, making the

0:15:38.556 --> 0:15:41.876
<v Speaker 1>leap and starting a company is that, you know, starting

0:15:41.916 --> 0:15:44.196
<v Speaker 1>a company working on really hard problems, you may or

0:15:44.276 --> 0:15:47.756
<v Speaker 1>may not succeed, right. You just don't know. It's a crapshoot, right,

0:15:48.116 --> 0:15:50.316
<v Speaker 1>And so what you want to do is be able

0:15:50.316 --> 0:15:53.076
<v Speaker 1>to get to yourself to a place where you'll never

0:15:53.236 --> 0:15:56.476
<v Speaker 1>regret try, right. And the nice thing about hard problems

0:15:56.556 --> 0:15:59.716
<v Speaker 1>and important problems is that it's very hard to regret

0:15:59.836 --> 0:16:07.436
<v Speaker 1>working on them. Rash Machete is the co founder and

0:16:07.556 --> 0:16:11.356
<v Speaker 1>chief operations officer of ging Go Buy Awards. Today's show

0:16:11.556 --> 0:16:14.796
<v Speaker 1>was produced by Edith Russolo, edited by Robert Smith and

0:16:14.996 --> 0:16:18.196
<v Speaker 1>engineered by Amanda kay Waugh. Our theme music is by

0:16:18.236 --> 0:16:21.956
<v Speaker 1>Luis Gara. A huge team of people makes this show possible.

0:16:22.356 --> 0:16:27.036
<v Speaker 1>This team includes, but is not limited to, Jacob Weisberg, Milobell,

0:16:27.156 --> 0:16:30.716
<v Speaker 1>Leta Mulad, Justine Lang, Heather Fame, John Schnars, Kry Brody,

0:16:30.796 --> 0:16:35.076
<v Speaker 1>Carli Nigliori, Christina Sullivan, Jason Gambrel, Grant Hays, Eric Sandler,

0:16:35.156 --> 0:16:39.556
<v Speaker 1>Maggie Taylor, Morgan Rattner, Nicole Morano, Mary Beth Smith, Royston Baserve,

0:16:39.796 --> 0:16:43.716
<v Speaker 1>Maya Kanig, Daniella Lakhan, Kazeia Tan and David Clover. What's

0:16:43.756 --> 0:16:47.276
<v Speaker 1>Your Problem is a co production of Pushkin Industries and iHeartMedia.

0:16:47.676 --> 0:16:50.876
<v Speaker 1>To find more Pushkin podcasts, listen on the iHeartRadio app,

0:16:51.036 --> 0:16:55.156
<v Speaker 1>Apple Podcasts, or wherever. I'm Jacob Goldstein and I'll be

0:16:55.276 --> 0:16:57.916
<v Speaker 1>back next week with another episode of What's Your Problem