It’s been a long and winding road for synthetic biology. The first wave of publicly-traded companies emerged in the late 2000s and early 2010s. Many were founded on the promise of engineering microbes to produce renewable fuels, which could ease supply constraints and price volatility. It’s easy to forget now, but before fracking came along the world was legitimately worried about Peak Oil.

Unfortunately, all efforts to manufacture cost-competitive microbial fuels crashed and burned. The technical obstacles were too great. The economics simply weren’t there. Although a few companies pivoted, many closed their doors for good. But that was hardly the end of synthetic biology.

Advances in the last decade have set the stage for a second wave of companies to launch onto the public markets. Better funded, more specialized, and equipped with a deeper understanding of biology, many of these companies appear better positioned to navigate the road ahead. For example, DNA synthesis leader Twist Bioscience (NASDAQ: TWST) went public a few years ago, whereas the vertically-integrated industrial biotech Zymergen (NASDAQ: ZY) went public months ago. Ginkgo Bioworks, seeking to become the Amazon Web Services of biology, is expected to go public in the coming months through a record-setting SPAC. The company will grab $2.5 billion in cash, a $15 billion valuation, and the highly-coveted stock ticker $DNA — last wielded by Genentech — in the process.

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Investors shouldn’t expect a smooth ride ahead. Similar obstacles that stunted the first wave, namely economics and manufacturing scale-up, remain unresolved. It appears many Wall Street analysts have absolutely no idea how to think about this emerging space. Then again, many investors are probably wondering, what the heck is synthetic biology anyway?

Considering synthetic biology will slowly creep into industries not typically associated with biology — from digital data storage using DNA to manufacturing metallic nanoparticles for next-generation batteries — investors will need new frameworks to understand the challenges and opportunities ahead. To introduce investors to the space and discuss some of the leading publicly-traded companies in it, 7investing Lead Advisor Maxx Chatsko nerded out with one of the godfathers of synthetic biology, Stanford University bioengineering professor Drew Endy.

Professor Endy’s goals are to enable civilization-scale flourishing and a renewal of liberal democracy. He helped launch new undergraduate majors in bioengineering at both MIT and Stanford, and also the iGEM competition, a global genetic-engineering “Olympics” enabling thousands of students annually. His past students now lead companies like Ginkgo Bioworks and Octant. He is married to Christina Smolke, CEO of Antheia, the essential medicine company. Endy served on the US National Science Advisory Board for Biosecurity (NSABB), the Committee on Science, Technology, & Law (CSTL), and the Pentagon’s Defense Innovation Board (DIB). He currently serves on the World Health Organization’s (WHO) Smallpox Advisory Committee and the International Union for the Conservation of Nature’s (IUCN) Synthetic Biology Task Force. Esquire magazine recognized Drew as one of the 75 most influential people of the 21st century.

Publicly-traded companies mentioned in this podcast include Amyris, Cisco, Codexis, Hewlett Packard, Intel, Google, Moderna, Qualcomm, Twist Bioscience, and Zymergen. Ginkgo Bioworks was also discussed, which is expected to become a publicly-traded company in the second half of 2021.

7investing Lead Advisors and Drew Endy may have positions in the companies that are mentioned. This interview was originally recorded on June 3rd, 2021 and was first published on June 8th, 2021.

Drew Endy co-founded DNA synthesis company Gen9, which was acquired by Ginkgo Bioworks, and he owns shares of Ginkgo Bioworks as a result. Additionally, Ginkgo Bioworks co-founders Jason Kelly and Barry Canton were PhD students under Drew Endy at MIT.

Timestamps

00:05   Introduction

02:31   The awesomeness of iGEM

07:52   What is synthetic biology and what makes it different from everything that came before?

09:05   The tools that power genetic engineering (recombinant DNA, polymerase chain reaction, and DNA sequencing)

10:42   The tools that power synthetic biology (DNA synthesis)

11:57    Parallels to semiconductor chip fabrication

15:00   The tools that power synthetic biology (coordination of labor)

15:00   The tools that power synthetic biology (coordination of labor, abstraction layers / user interfaces)

17:25   Reproducibility, standardization, and operational mastery of the cell

23:35   The Space Race vs. The Life Race

25:09   Personalized computers (PCs) vs. Personalized biomakers (PBs)

33:45   Are first-mover disadvantages an obstacle for investors? A discussion on DNA synthesis and Twist Bioscience

37:45   All about the business model, more Twist Bioscience

46:02   A discussion of Ginkgo Bioworks and Zymergen

55:43   The last major bottleneck for synthetic biology

1:00:05   Dropping the “bio” prefix as a hallmark of success

1:02:26   Joules, bits, and atoms

1:04:34   What are the largest challenges and obstacles facing synthetic biology?

1:08:50   The bionet and the importance of networks effects for biology

1:14:40   When will Drew stop avoiding barbers?

Transcript

Maxx Chatsko 00:05
Hey everyone, I’m 7investing Lead Advisor Maxx Chatsko. I cover biotech and renewable energy here at 7investing. You might not have heard of me too much on the podcast because I don’t do too many podcasts. But Simon’s been twisting my arm behind the scenes and so I thought, “Hey, you know, let’s kick this back off and get back in the podcast game.” And what better way to do that than to talk about one of my favorite topics, which is synthetic biology.

Maxx Chatsko 00:32
Individual investors might have heard of this term over the years. In the early 2010s, a lot of industrial biotech companies were pursuing biofuels. They were making engineered microbes, pursuing these large, gargantuan fuel markets. For technical and economic reasons, it just didn’t work out. A lot of those companies went bankrupt, some pivoted and are still with us like Amyris or Codexis, and many more pivoted. And then just over the last 10 years, it might have seemed kind of quiet, but really behind the scenes, in the private markets, a lot of companies were building new technologies or specializing in specific areas of the market. And that’s kind of built like a much stronger foundation for where we are today and the beginning of this decade. So just in the last year, we’ve had what feels like a second wave is coming. We have Zymergen recently went public. Gingko Bioworks is about to go public. And these are two of the best-funded startups in the space. So to get a better understanding of synthetic biology, there’s really no one better to talk to than Drew Endy. So Drew, thanks for taking some time out of your day to talk to me.

Drew Endy 01:36
Maxx, great to be here with you. Thanks for inviting me to join together today.

Maxx Chatsko 01:40
Yeah. Drew is a professor at Stanford and he was previously professor at MIT. He started the bioengineering degree programs at each of those institutions. He’s also a co-founder of the iGEM Competition. iGEM stands for “international genetically engineered machines.” It’s where universities from all over the globe get teams of students together, and they compete against one another, to design something with reproducible biological parts in different fields and tracks. Then they come together for the Jamboree in Boston every year in the fall, and they get judged and scored and ranked, and there’s award ceremonies, and it’s a beautiful thing. And Drew, I could keep going on, your, just the highlights from your career would be like 10 pages long. So I guess the best way to put it is, I consider you the godfather, one of the godfathers, of synthetic biology — I hope you haven’t sold the movie rights yet.

Drew Endy 02:31
Yeah, I mean, when things happen, there’s lots of parents. I think you’re touching upon some stuff that’s really meaningful to me, but mostly because it’s about the reality of how much can be done with biology. How much can be built with biology. And we need people to do that. I helped start the programs at MIT and Stanford and that was a great experience, but many people helped with that.

Drew Endy 03:00
The beauty of the iGEM Competition, if you’ve never heard of synthetic biology, maybe you’ve heard of a software competition or car building competition. But imagine a genetic engineering competition. That’s what we’ve got. iGEM is maybe 6,000 students a year now and 400 schools. It’s actually moved from Boston to Paris, and is home based there now going forward. And one of the things we’re working on behind the scenes is, how do we make that not 6,000 students a year, but 600,000 students a year or 6 million students a year? And thinking about the infrastructure that has to be developed underneath the educational activity.

Drew Endy 03:43
Of course, what’s amazing about students, I can’t remember– an anecdote I got from Jim Plummer, one of the previous Engineering Deans at Stanford, it was either from Hewlett or Packard, who related to him that the best thing about Stanford was it brought students to Silicon Valley, and then they left the university and went and did actual things. So then, one of the neat things about iGEM is people have the iGEM experience and then they go do actual things. So I think about Ingrid Swanson and the iGEM project from the University of Washington that then became a startup company, PVP Biologics, that was invested in by Takeda out of Japan and eventually acquired. They had developed a new protein therapeutic for treating gluten intolerance, and so that was an example of a student project. You think about student projects in software going from a classroom to an acquisition, or a market success or real success in less than a decade, but it was Ingrid and her project with PVP [Biologics] that was like, in less than a decade, they went from an idea and an iGEM project to a half billion dollar acquisition. And so it’s just like, huh. And you mentioned Ginkgo in the opening. And of course, I know those folks well. That’s another example of an iGEM project growing into a corporation that’s still ongoing. Yeah, but anyway, great. Great to be here. Good morning from California.

Maxx Chatsko 05:09
Yeah, a growing list of companies that have started as projects, or at least the team met or had the project from iGEM. I judge that competition every year. Is it– so it’s actually in Paris? I didn’t, I’m out of the loop. I gotta go to Paris if I want to judge it now?

Drew Endy 05:23
It’s been a strange time, right? I mean, we’re all we’re all reeling from the “one nine” [COVID-19]. The big decision last year was whether or not iGEM– and so there was obviously not a physical jamboree in Boston. You didn’t want to bring 5,000 people to the Hynes Convention Center. You don’t have a super spreader event. And so the the jamboree was actually virtual. And it was a success. I mean, really good projects were done all over the place. It was tricky. Like the Stanford team in 2020, for the iGEM, they decided to work on diagnostics of viral pathogens — obviously inspired by the pandemic. And the question they asked at the start was, “Why do I have to go somewhere else to get a test? If I’m infected, I’m infected right where I am. Why do I have to go somewhere else? Or, why do I have to take a sample and send it somewhere else? Couldn’t my body just tell me if I’m infected?”

Drew Endy 06:18
And so they developed a project called SEED — self-replicating embedded environmental diagnostics — but I call it the “purple booger project”. Sorry to be so blunt. Imagine you have a friendly microbe living in your sinuses and it’s sampling the nucleic acids in your environment infecting you. If nothing’s infecting you, your mucous is a normal color. If you’re infected with an influenza strain, your mucus turns bright orange. If you’re infected with a coronavirus strain, your mucus turns bright purple, right? Like I’d rather have a real-time, run-time, all-the-time diagnostic platform telling me what’s going on with me. So that’s their iGEM project. We couldn’t get them into the research labs on campus because of the county shutdown, the public health shutdown, but they ended up doing their experiments in the DIYbio makerspace in Mountain View and were able to get enough preliminary results that we brought that back into the hospital’s catalyst program. And they’ve been doing ongoing research to bring that forward into a new company. So like, yeah, iGEM’s happening, but so strange everywhere. It went virtual, but it’s still happening. It’ll be virtual this year and then probably in 2022, that’s when we might feel comfortable getting people back together. But I defer to you, are you ever gonna travel again?

Maxx Chatsko 06:50
Oh, yeah, I can’t wait. I really want to get back out there and tour factories and so you don’t? You want to stay all cooped up?

Drew Endy 07:37
Well, you know, like, I’m not really cooped up. As you can see–

Maxx Chatsko 07:40
I see that!

Drew Endy 07:41
I’m pretty happy never traveling again for work. I can imagine that real, real, real fine. I like traveling at lightspeed, this is much better.

Maxx Chatsko 07:52
So maybe, let’s back up a few steps. And you know, maybe just start off with one of the simple questions because our audience is a little more generalized. It’s seems like a simple question, but “what is synthetic biology?”

Maxx Chatsko 08:04
And you made a recent presentation, where you kind of took issue with the interchangeability of terms. And I love that, because I always hate that we use the term “biotech” and “biopharma” interchangeably. In the public markets, “biotech” is applied to any small drug developer — you don’t even have to be developing a biologic drug! It drives me absolutely insane. I don’t know why we can’t be more precise with our terms. So you said, “Hey, you know what? There’s ‘engineered biology’ and ‘biotech’ and ‘synthetic biology’, but these are all distinct things. And we shouldn’t really shy away from that. We should hold up synthetic biology as its own approach to biology.” So, what the heck is synthetic biology? What makes it different from everything that came before?

Drew Endy 08:46
Yeah, thank you for that, Maxx, and I’m with you a lot. I think a lot of people are lazy. For reasons, right, so it’s okay, but it’s not okay. Let’s start with genetic– I’ll give you, there’s sort of two answers to your question, but I’ll give you the engineer’s answer.

Drew Endy 09:05
Let’s start with genetic engineering. What’s genetic engineering? Well, genetic engineering starts with the ability to cut and paste DNA. That was pioneered in the 1970s with recombinant DNA and gives birth to the biotech sector as we know it starting around 1980. Genetic engineering is based on this core tool of cutting and pasting DNA. Around the same time two other tools appeared. One is called PCR for polymerase chain reaction. And that lets you take a small amount of DNA and just make lots of it so that you can work with it more easily. So that’s a second tool in the toolkit. A third tool that appears in the mid to late 1970s, and really gets going in the 1990s, is sequencing of DNA. The ability to take a molecule of DNA that’s a physical object and read it out so that you have an abstracted representation, the letters or bases of DNA, the As, Ts, Cs, and Gs.

Drew Endy 10:01
I would say the first generation of biotechnology is powered by these tools of genetic engineering: Recombinant DNA, polymerase chain reaction, and DNA sequencing or DNA reading. These are the — there’s other tools, of course — but these are the new tools that appear starting from the mid 70s to mid 90s, that really impact workflow and change what people can do.

Drew Endy 10:24
So that’s all great. That’s not going away, that’s powering a whole bunch of equity, whether it’s pharmaceuticals or agricultural or materials manufacturing. But there’s more tools, right? Things keep getting developed. So, what are the tools in the toolkit that synthetic biology brings to the table?

Drew Endy 10:42
The first one is synthesis, the synthesis of DNA. So synthesis of DNA gets worked out from a chemistry perspective by 1980 and it gets commercialized by the mid 80s. Applied Biosystems and others were making beautiful machines, DNA synthesizers, that could simply synthesize short fragments of DNA called oligomers, or ligand nucleotides, that might be 40 letters long or 100 letters long — ATTATA — you know, 40 of those letters. And by 1985, Applied Biosystems captured the market. They were selling the machines, they were selling the chemical cartridges, the ink for the machines, they were selling the service contracts, and they shut down their R&D team because they had “solved” DNA synthesis. Now, you might not know about Applied Biosystems or your audience might not know about them because they’re not around anymore. They got acquired and then that thing got acquired, and so on and so forth. And I didn’t know about any of this until I went to a meeting and was showing up saying, “Hey, synthetic biology would like even better DNA synthesis.” What do I mean by that?

Drew Endy 11:57
When I first started teaching at MIT in 2002, one of the things we wanted to do was take inspiration from the work of Lynn Conway. Now, Lynn was an electrical engineer working at Xerox PARC back in the 70s. She was working on semiconductors and semiconductor design and manufacturing. She and Carver Mead recognized that there was a lot of expense associated with the fact that in order to get a chip built, you had to really know the people at the chip foundry and follow their rules to get something built on their fab. And if the people operating the lithography systems were a little bit hung over, you know, maybe the masks didn’t totally align, and good luck with that run. And so she and Carver figured out how to decouple the design of integrated circuits from their manufacturing on silicon. This gave birth to the VLSI Revolution, the very large scale integrated electronics revolution, that then leads to the microprocessor. So we were talking with Lynn about what she had done to figure out how to decouple design electronics from manufacturing electronics. Parsing those lessons, we took that back and said, “We’re gonna do the same thing for the biotechnology workflow. You are going to be a designer of DNA, Maxx, and I’m going to be the builder of DNA. You’re the architect, I’m the contractor.” By specializing, we’ll be able to do more together. That’s the gist of it. Does that make sense? Just in general, like a high level?

Maxx Chatsko 13:30
Yeah, it does. That’s a good timeline–

Drew Endy 13:33
I know I’m giving this– let me loop back to synthetic biology. But I’m just trying to explain sort of how we got here. DNA synthesis turns out to be a key tool that would let us decouple design of biology from construction of biology. Because if I could get DNA synthesis working really well, you could be the designer and I could be the builder. That’s tool number one of synthetic biology, although it was implemented as chemistry in 1980. The practical reality of accessing DNA synthesis as a tool was not mature, and is still maturing. Twist [Bioscience] being a pioneering example of that.

Drew Endy 14:10
Let me make this real for you. When I ordered DNA in 2003, for a gene the price of that is $4 a letter. Every time I press the T key, or the A key, or the C key, or the G key on my DNA printer, I’m spending four bucks. A gene is going to be 1,000 letters. So, a gene encodes an enzyme that might do one thing. So every time I’m doing like one little operation in a cell, it’s $4,000 just to print the DNA. One of the things synthetic biology has done is celebrate DNA synthesis as a strategic technology and improve that technology. The price of building genes is now down by about a factor of 100. Although it’s interesting, we should talk about this, it’s actually coming up in price over the last couple years. That’s interesting in terms of economics.

Drew Endy 15:00
Anyway, we got recombinant DNA, PCR, and sequencing. Now we’re gonna have DNA synthesis, or DNA print. Then there’s two more things. One is coordination of labor. How do I do something where I am so that you can use it where you are without having to talk to me? So this is enabled by standardization that allows for coordination of labor. We see this all over technologies, whether it’s the stone aqueduct in Segovia made from regularized blocks, or the fire hydrants and hose couplings that are standard so that if the city over there is burning down I can bring my fire truck and help. So, standards allow for coordination of labor. That was the second big idea that makes synthetic biology build on top of genetic engineering. And the third big idea is abstraction. So abstraction is an abstract concept. Here’s how to think about it. When you send an email, you’re not programming zeros and ones into the computer. You’re using these high level functions that get compiled down into the physical reality of the electronics. And there’s an abstraction stack that does that down compilation with high reliability. Biology is super complicated, right? So we could immediately pivot the whole conversation into TAA TAC CGA CTC ACT ATA GGG AGA like, what’s that? Hey, you know, you know, that sequence, right, Maxx? You know what that does, right?

Maxx Chatsko 15:04
No idea!

Drew Endy 16:25
It’s a consensus promoter for the T7 RNA polymerase that initiates transcription and that’s the sequence they use to make the RNA for the COVID-19 RNA vaccines, you got to get that polymerase going. But, like, who wants to memorize all those sequences? I only know a few because I only have so many computer login passwords. So instead, you just want to say, “that’s a go signal”, that’s like a “make RNA signal.” So that’s abstraction, like this idea that you can manage complexity.

Drew Endy 16:50
Let me zoom out. Synthetic biology builds on genetic engineering by improving the workflow, DNA synthesis to decouple design and fab, standards to enable coordination of labor, and abstraction to manage complexity. If we can advance these things that we have now, then the complexity of things that can be made and routinization of the manufacturing process. Meaning, I really mean the prototyping of the biology process, not the downstream manufacturing, that can be just better managed. And yeah, blah, blah, blah.

Maxx Chatsko 17:25
That’s great. I think reproducibility and the standardization is such an important point to emphasize. If we took the analogy of a jet engine. A modern jet engine is a very complex piece of machinery. There’s thousands of components. There’s a lot of different engineering fields that go into that, right? Advanced material science and engineering, fluid mechanics, thermodynamics, but we can design modern jet engines because we can model them on a computer, we can plug it in. We can know the air coming in, how many rotations, and thermal expansion of the blades so they don’t blow up and hit the sides when you’re at 30,000 feet into a million pieces. We know the temperature of the air coming out of the back. And that, the ability to model a jet engine, is really key to being able to build these modern jet engines in the first place.

Maxx Chatsko 18:11
If you’re an investor, just someone out there is not really tuned into biology have never worked in a lab, you might think that a single cell is actually a very simple component of biology, but it’s not. A single cell is orders of magnitude more complicated than that modern jet engine. And we still don’t have the capability to model even a single cell. So what are some of the obstacles there? What are some of the advances we need to make in order to really be able to model a cell and gain this kind of mastery of biology?

Drew Endy 18:46
That’s a good question, Maxx. And it’s a research question, right? As an aside, the other definition of synthetic biology is learning by building in a scientific context. I’m just gonna acknowledge that and then come back to your question.

Drew Endy 18:58
You make a good point, let me read it back. The fundamental unit of life is a cell. This is the object that’s enclosed in a membrane that’s got DNA, it’s got biochemical functionality. It can move, oftentimes, it can do stuff. All of the life we tend to think about from microbe to person to plant to tree are made of cells. To your point, there is no cell that’s perfectly understood. Like not one cell on earth is perfectly understood. There’s not one cell that’s fully modeled. There’s not one cell for which every component inside it, that’s essential to the cell working, is understood.

Drew Endy 19:35
I just want to pause there and acknowledge that because of that reality, you see various commercial activities adopting certain configurations. The way I describe it is, they are going to be Edisonian. They’re going to be getting better at tinkering and testing, because you can’t perfectly predict or model how the actual biological system is going to behave. You operationalize that by saying we’re going to try a lot of things as smartly as we can, and then see what works and then build on that. Right? The significance of the fundamental ignorance in biology, meaning, we don’t yet completely understand the fundamental unit of life, means the commercial sector is going to be Edisonian. And the big capital investments into platforms are our reaction to that reality.

Drew Endy 20:22
As a researcher operating an academic lab, I spent a lot of my time, my job is to live 10 to 15 years in the future. We’re thinking about how do we fill in that fundamental layer? How do we get to full understanding of a cell so that the commercial sector transitions from tinker and test to more rational design at the cell scale? I would say that we’re at the starting line of of doing that. Meaning, for the last six years or so, my lab and others all over the world have been working through what’s the problem with not fully understanding cells and — I should say problems — and what new tools do we need to figure it out? You’re right to pick up on modeling as one of the issues, but there’s also issues of measurement and just making. Everybody, I would bet many people, be familiar with the nursery rhyme Humpty Dumpty?

Maxx Chatsko 21:21
Yeah.

Drew Endy 21:21
You know, Humpty Dumpty sat on a wall, had a great fall, all the king’s horses, all the king’s men, couldn’t put it–. So it’s like, if you took, one of the things we can’t do today is, I can’t take a cell and take it apart and collect all the molecules and put it back together and have the cell again. It’s just like, the things aren’t in the right places, I can’t physically do that. I know, I have all the things that are sufficient, but I can’t do it. That’s an example of like a type of fundamental challenge.

Drew Endy 21:46
Another challenge, and I don’t want to belabor it too much, what math do we use to represent the behavior of molecules making up cells? You talked about an airplane. Well, that’s going to be, what math do we use to represent the flow of air or the wing through the air? It’s gonna be fluid dynamics — and fluid dynamics is complicated math. But it’s been complicated math we’ve been working with for centuries. And so we have a good mathematical framework that we believe is well grounded in the physics and then we use the digital computer to throw numerical integration methods at it. So we can design an airplane on a computer and build that thing. And it flies, right? Like, the test flight is the first flight. That’s because we have the modeling framework, right? The inside of a cell is very different.

Drew Endy 22:35
It’s like, imagine a burrito, but the burrito, all the things inside your burrito, are independently moving around spontaneously. And so it’s like a self-mixing burrito and yet it has order. So, the math is very different. We now know what the math is and so we’ve basically been porting over math from colloidal biophysics. I had a student defend his PhD on Tuesday of this week. And it’s the first time in that defense, I’m like, “Yeah, we’ve got them. We’ve got the modeling framework to do forward design of cells.” He’s admitting designs that I think will work when we build cells. Like, you can make a cell go faster, or slower, or whatnot. The physics engine feels right. It’s like a video game. The video game has a physics engine. Is the physics engine any good? And I would say 20 years ago, the physics engine sucked for cells, for modeling cells. And like, this week, I’m feeling like we’ve got the right we’ve got a pretty good physics engine upgrade.

Drew Endy 23:35
Anyway. So. The 1960s had the space race. This was about humanity, for the first time, getting up out of the gravity well of the earth. I think the 2020s are gonna have the life race. Nobody’s really using these words except for me right now, but that’s okay. By life race what I mean is, this is going to be the decade where we, the scientists and engineers working in synthetic biology, learn how to build a cell and cells from scratch, and operate them. I think that could happen and as soon as 1,000 days, so Thanksgiving 2024. We’re at the starting line now of the life race, because we have the tools that we can use to solve the problems in terms of building cells. But that’s more of a fundamental comment. I don’t think that’s showing up on the marketplace yet. But I would be very surprised if the market of 2030 and 2025 wasn’t being influenced by just filling in the fundamentals of bioengineering at the cell scale.

Maxx Chatsko 24:49
So let’s live, let’s keep going 10 years, 15 years in the future. One thing about biology is that it’s inherently scaled down. It already operates at the microscale and the nanoscales. This kind of gives, you know, it points in the direction–

Drew Endy 25:02
[points to large tree behind him] And the macro scale. And the macro scale. You’re right. You’re right. It’s a “yes and” at all scales.

Maxx Chatsko 25:09
Right. So maybe the building blocks, I should say, at the micro and nano scales. Now, you know, I guess like the analogy would be, in the 1950s, computers took up the size of a room. And now we have personalized computers and smartphones in our pockets that are basically supercomputers from 60 years ago anyway. Biology seems to be moving in that direction, right? Like, it’s inherently predisposed to being distributed. And that looks quite a lot different from anything we have today. Today, we have personalized computers. Maybe in the future, we have personalized synthesizers or something, right? Like, you can send me designs, I have a pest in my vegetable garden, and you can send me some topical that’s going to only target that pest. So what does that future look like? I mean, how far away are we from that? Does that interplay with some of the commercialization of biology or does it disrupt it or kind of both?

Drew Endy 26:06
Yeah, thank you for those questions, Maxx. Biology teaches us in nature that all atoms are local. A leaf doing photosynthesis is getting the photons where the leaf is getting the carbon from the air where the leaf is, it’s getting the water and stuff from the soil. So biology teaches us that all atoms are local. This implies that we can build locally, we can build very sophisticated things locally, to the extent we have biotechnology that can be deployed locally, using the atoms that are local, and the energy that’s local. This is mostly not the world we live in today.

Drew Endy 26:46
We live in, in the West, we live in an industrial economy that selects for centralization of manufacturing and industrialization of biotechnology. The type of biotechnology we have today, I would call industrial biotechnology. We don’t have the personal or the local biotechnology to a great extent, yet. The first principles analysis would suggest that biotechnology eventually has to be local, too. I don’t think it’s an “either or” situation. But I think it’s a “yes and” situation. We’re going to have big fermenters in Minnesota and we’re going to have the possibility of distributed biomanufacturing.

Drew Endy 27:25
Now, I’m going to call that a possibility right now. Because, frankly, the United States, we don’t have industrial policy anymore. My entire professional career has been shaped by decisions made in the 1980s and carried forward, where we basically abandoned industrial policy as a nation state. The sectors people are more familiar with of electronics and networking and information technology, they all were built and benefited from nation state level industrial policy that was quite sophisticated and quite significant domestically. The situation we’re in is that it’s really the private capital, the investment markets, that are determining how the resources are flowing to sculpt the forms of technology that get developed.

Drew Endy 28:12
Let me read it back in a complimentary way. Technology is not technology, it depends on the form of the technology. So to your point, a computer is not a computer, it depends on who can use the computer where, for what purpose. In the 1960s, we had industrial computers. In the 1970s, we prototype the personal computer. The personal computer is not a revolution in transistor physics. It’s not a revolution in the word “computer.” The “personal” part is the revolution. My sense is, we’re going to get personal biomakers, or the PB, in addition to the PC, but I think it’s going to come from the entrepreneurial activity and the private capital sources to prototype that, absent some big change in how the United States is operating. Maybe we’ll get industrial policy again, but it’s been a 20 year uphill battle.

Drew Endy 29:12
For example, here’s a postcard, regardless of what you think is happening in the market today, do you think DNA is important as an object?

Maxx Chatsko 29:23
Yes.

Drew Endy 29:24
Yeah, and that’s because it like encodes all of living systems, right? Everything we care about that’s alive. All of the bioeconomy is built with DNA. So I could keep going. I can say “DNA is the industrial polymer of the 21st century.” It’s got to be the most important one. If not, it’s certainly going to compete for it. It’s like, what is our strategy? What is our collective strategy for DNA? We thought of computing as being important, we had strategic computing initiatives. If we think of DNA as important, what’s our strategic DNA initiative? We don’t have one! It’s insane. It’s collectively nuts. What this means is it defaults into the private marketplace.

Drew Endy 30:06
My first briefing of the DARPA director in 2003 contributed to the cancellation of public funding for better DNA printing because it was only perceived as causing bioterror risk, not as being beneficial. Yet, 20 years later, it’s the synthetic RNA vaccines built on DNA synthesis that are saving the day. We desperately do need strategic policy around these emerging texts and collectively in the public realm we don’t right now. The investment community, both retail and other, are the people who are shaping the forms of technology that are emerging.

Drew Endy 30:45
So you’re asking, how soon until we got the PB? Basically, as soon as somebody decides to go invest in it. There’s no first principle, physics law that makes it impossible. The value of the platform so created would be much richer when we get to full understanding of a cell, because then you could download content and plug it in, and it would work the first time as opposed to turning into a research project, they have to do tinker and test. So a lot of pieces have to fit together.

Drew Endy 31:16
I can say it differently. Let me try and summarize. Synthetic biology is a teenager, like it’s 18 years old, it’s about to become an adult and go into the world. And this is the decade that it’s happening. There are many experiments happening, both laboratory experiments and business experiments, but this is the decade where synthetic biology goes from demonstrations of being real to it’s going to become whatever it’s going to become. There are a lot of examples of failures, but there are enough examples of successes that keep piling up that are hard to ignore.

Drew Endy 31:55
I can give you an example of– I’ll give you an academic example and I’ll use one that I know well. So I’ll admit to my conflict. This is a project from my wife’s lab at Stanford, Christina Smolke, and her student, Prashanth [Srinivasan]. In October of last year, they published an academic paper in Nature showing that they could make scopolamine by brewing. Scopolamine is a drug for treating motion sickness, you have a patch on your neck, or sometimes it’s used, I understand, for Parkinson’s. This natural product chemical used as a medicine, scopolamine, we normally get it from growing plants from the Nightshade family. You grow up a plant and you extract the chemical and then it goes into the medicine. Prashanth showed how you could reprogram the biochemistry of Baker’s yeast or brewers yeast, instead of taking in sugar and making ethanol — wine — it takes sugar and makes scopolamine. If you look at that paper, there are only two authors on that paper, Prashanth and Christina, and this is somebody doing an enzymatic pathway that’s 30 or 35 different components. One person was able to do that because we got coordination of labor, reusable parts, abstraction, synthesis. If one graduate student is able to do that in the year 2020, then we’ll see if Christina and her company can bring it to market successfully or not. There’s there’s plenty of examples like that showing up. I think there’s a lot of business risk for sure, but the reality is falling into place.

Maxx Chatsko 33:45
Let’s let’s stick with distributed biology. You brought up some good points. It’s not just necessarily “personalized” is revolutionary, but this also affects maybe geopolitical concerns across borders as well. Oftentimes in biotechnology, I’m always fascinated, it’s almost like there’s this first mover disadvantage sometimes, right? One example might be CAR-T cells. Ten years ago, we thought they were God’s gift to biotech, and now we’re kind of seeing some of the limitations in manufacturing or toxicities. We’re kind of already investing in things like natural killer (NK) cells or bispecific antibodies. So in 10 years, it went from “Amazing! We can cure cancer with this potentially!” to now like, “Yeah, let’s invest in some other stuff.” I think synthetic biology is, I mean, that’s moving so quickly. Are there any first mover disadvantages to some of the companies in the space? They’re making giant investments in these centralized facilities, robotics labs. Or even like Twist Bioscience, right? What if enzymatic synthesis comes out? So like you said, it’s not necessarily they can’t adapt, it’s “yes, and” maybe.

Drew Endy 34:49
This is a good point. Let’s use DNA synthesis and that sector quickly. We’re talking about Twist, which is an ongoing concern. I had involvement in two companies before that, Codon Devices and Gen9, also operating in gene synthesis. One of the things I can share from those experiences is some of the complexities of operating in the marketplace.

Drew Endy 35:13
For example, if you’re building genes and your customers would like the price to be cheaper, and cheaper, and cheaper. Let’s say you’re going from when we started Codon at $4 a base pair and we’re trying to get to $0.04 a base pair. That means the cost of your products going down by a factor of 100. To make the same top line revenue, the volume through your vat has to go up by a factor of 100. So you’re doing 100 times more work to make the same top line revenue. How’s Wall Street going to like that? It’s like, where’s the growth?

Drew Endy 35:42
Well, it’s growth in volume, but not growth in revenue. So, if you misprice your contracts a little bit, you’re like, “Well, our COGS [cost of goods sold] are gonna get better and better and better. So we’re gonna win this contract by losing some money for the first six months of the contract, but making it up when we reduce our COGS on the last 48 months of the contract.” That’s a reasonable thing to do on your sales team. But if you mistime that a little bit, you cash out, your runway is gone. It’s a really, you’re basically making a commodity product that’s a customized commodity product. It’s always going to be DNA, but the sequence is always gonna be a little different. It’s a really interesting business to be in with very interesting market dynamic challenges.

Drew Endy 36:26
So, you know, I defer to you as the expert on the financial sheets. But one of the things I like about Twist is, when I look at their financial reporting, I think it was somewhere around 2018 to 2019, they’re reporting their revenue and their cost of revenue, and around 2018 to 2019 the cost of their revenue was less than the revenue earned. Now, of course, they’re still losing money, because they’re doing all sorts of other things. But it appeared to be the case that the core of the business became profitable a few years ago. I view that as a major qualitative accomplishment for the business. They still have to grow and become profitable overall, but it means that there’s something working in the core that’s valid. I defer to you and others to understand that better. But I look at it like, how much does it cost you to do what you’re doing? And how much money are you making by doing what you’re doing? And what’s your net relationship with money? Are you making money? Are you just spending money? And so I’m looking for those transition points in the businesses, right, when did they change their relationship with money? Because those are the things that are going to be ongoing concerns because it’s just gonna have free revenue to reinvest. But I do want to acknowledge the trickiness of navigating this from a market dynamic perspective.

Maxx Chatsko 37:45
Yeah, that was one of the things in the first wave of companies with biofuels, right? They chose the wrong markets, the tech wasn’t there. I mean, I remember touring Solazyme and they had rows and rows of like five and 10 liter reactors. Like you can’t, that’s not gonna work. Now, we’ve scaled that down to mini bioreactors at 250 milliliters or smaller in some applications. So Twist is an interesting example. They’re scaling the business, they’re growing pretty quick, profitable or gross profit anyway, investing a lot of money to continue scaling, they have a lot of cash. So that’s good. I think just because of the investments they’re making, that they might not be profitable for a while, like operating income, but nailing down the business models here has still been a challenge and remains a challenge even for like Zymergen or Gingko Bioworks. Like Gingko, they’re trying to be like the AWS of biotech or synthetic biology, and I’m not sure the R&D revenue model is perfect. You really do have to commercialize products at the end of the day. So there is that mismatch still of we’re getting the tech and the R&D down, and then actually, in the market, there’s certain things that Wall Street cares about that are quite a bit different.

Drew Endy 39:03
I want to come back and talk about Gingko a little bit because I’m curious how you see it. But let me let me offer a comment about Twist. From outside of Twist, I’m a customer of theirs. I used to be a competitor with Gen9 and Twist competing, but Gen9 got acquired by Ginkgo and so I have a little bit of equity in Gingko, incidentally, when we get to that, so I’m long Gingko, just to disclose.

Drew Endy 39:31
In addition to being a customer of Twist, in addition to appreciating that when I look at the core of the business, yeah, they’re still losing money, but they’ve got a core that at least as they’re representing it on the financial stage looks promising. And the growth is really impressive. There’s another thing I can say honestly about Twist and this links back to some of our earlier talking points. If I’m talking to somebody in the United States Senate, a senator, I’m going to say that, without blinking because I really mean it, Twist is a national strategic asset for the United States of America. What else do we got? It’s our best high-throughput, domestic, onshore DNA synthesis platform. In addition to everything else that’s happening, with a straight face to anybody, I’m gonna say this is a national strategic asset. So we have to do everything– when Twist came to me and said, “We need to raise your prices a little bit.” I said, “Good! Because I want you to be an ongoing concern. I’m not, you know, just great. Like, make sure you’re still around.” So that’s a pretty strange situation to be in. And I don’t value that, but there’s definitely value there.

Drew Endy 40:42
If we talk about Ginkgo, should we talk about Gingko a little bit?

Maxx Chatsko 40:44
Yeah, well, just to stay with twist for a little bit. We can go to Ginkgo real quick.

Drew Endy 40:48
Yes.

Maxx Chatsko 40:50
Yeah, that’s interesting. For some of these valuations, it is interesting. And I observed, like when Ginkgo announced they were going public, Wall Street has absolutely no idea how to think about Gingko Bioworks. They don’t have frameworks, they don’t have models, they have no idea what they’re, like, they’re totally lost. So that’s interesting to me, because it suggests that there might be an opportunity if there is a mismatch in the understanding of the business and then what’s possible five or 10 years from now. And I see the same with Twist, like you said. It’s the only player in the game. So that does suggest that needs a premium.

Drew Endy 41:20
Yeah. And let’s be a little bit careful, right? What game are they playing? They’re playing the high throughput, most affordable DNA synthesis at the core of their DNA synthesis offering. There are other people in the space like IDT, Integrated DNA Technologies, but Twist is really the corporation doing the high-throughput, high-volume, low-cost fab. When I look forward into the DNA synthesis space, we’re just in Generation One, Two of DNA synthesis technology. You can project out five generations, there’s going to be enzymatic synthesis, and so on and so forth. I don’t view enzymatic synthesis as displacing what Twist is doing, is high throughput, low cost. I think there’s room in the market for multiple form factors of synthesis. And you’ll have centralized high-throughput synthesis complemented by distributed local synthesis. You know, just like there’s many different types of computer offerings, there’ll be many different types of DNA print offerings. You’d have an industrial printer, you have your desktop printer. They’re all printers, but they’re different printers. And everybody can make a good market by differentiating.

Maxx Chatsko 42:28
That’s an interesting point. Because they [Twist Bioscience] tend to get that question a lot. And I’ve had that question. What happens when enzymatic synthesis comes up? Twist might just transition to that, but there’s multiple, there’s room for more.

Drew Endy 42:40
Yeah, and the answer, in my view, the answer is “Great!” Twist will keep growing their core industrial print business because the world will need industrial print. Period. Full stop. Will the world also need local print? Absolutely. If Twist keeps growing revenue and whatnot, these emerging things will be easy acquisitions. Right, so so like one of one of the things that goes on in the DNA synthesis business is everybody focuses on the synthesis part, like how you actually organize the atoms into the polymer. But if you want to scale your synthesis business, one of the things you also have to do is you have to organize the bits, the information. For a viable synthesis business, the bits and the bases have to flow together. And if you have the world’s best DNA printer, but you’re using Google Sheets to manage all your orders and you don’t have good IT, you’re dead, because you won’t scale. Most of the most of the companies in the space always focus on the physical operation first, and completely missed the complexity of scaling the it. Twist got hit with that, they navigated it successfully through their acquisition of Genome Compiler and so on. But it’s like a classic, we get the physical stuff working like “Oh, my gosh, we have to handle it.” So, it’s a tricky space to operate in. And I think if enzymatic happens, maybe Twist buys into it or they just keep going, it won’t matter to what they’re doing.

Drew Endy 44:12
But you make a good point. Right before the pandemic, we worked with the White House to do America’s Bioeconomy Summit in late 2019. This was under the auspices of the Office of Science Technology Policy, so it’s the nerd side of the White House, the science and technology side of the White House. And we’re having the Bioeconomy Summit. See how there’s something funny going on there with words? The nerds are having a summit at the White House about the economy. Aren’t there other people at the White House who handle the economy? Yeah, the economists. So, why is it that we’re not having the Biotechnology Summit? Why do we have to call the nerd thing the Bioeconomy Summit? And in part, it’s because people don’t understand biotechnology, to your comment about Wall Street, and how to think about things. It’s interesting to acknowledge that puzzle and just recognize that.

Drew Endy 45:09
I’m grateful to be here today. You know, I’m sure some people are hearing this and they’re going, “What’s this guy talking about?”, but a lot more of that is welcome. Because I think the reality is people talk about the 21st century being the “bio century”, but we’re in the third decade of the bio century, we can’t be hiding it under other things like “economy”, we have to be talking about the economy and the reality of it, too. And so, I just want to acknowledge that puzzle and would welcome anybody wanting to work on that more. Like, let’s become mutually literate about the economics and the technology together? Yeah.

Maxx Chatsko 45:47
Yeah, absolutely. I saw it once in a talk years ago, we talk about genomics and proteomics and transcriptomics, and one of the most difficult omics is economics.

Drew Endy 46:01
I love it.

Maxx Chatsko 46:02
Sticking with that with, the industrialization of biology, or maybe it’s more accurate to say the biologicalization of industry, like Ginkgo Bioworks or Zymergen. These are big, centralized robotic labs. They’ll do your R&D for you. And these are companies that maybe traditionally don’t have that investment, like flavor and fragrance companies or specialty chemical companies, they’re not set up for biotech. You can maybe have a contract with Ginkgo or zymogen or whoever, to make some ingredients, pay them for the R&D, and so on. So, you said you want to talk about that, I guess just my high level thoughts.

Maxx Chatsko 46:34
They’re [Ginkgo Bioworks] gonna go public through a SPAC is the plan. I’m sure that was negotiated in more favorable times for growth stocks. I’m curious to see how that holds up, if they, in the coming months, if they do go public, but it was a $15 billion dollar valuation. So it’s like 100 times sales. And it’s not just about sales, I think it’s the type of sales, so that non-recurring R&D revenue is going to be tough, I think, on Wall Street. But the way I read it, I think Ginkgo optimized for the capital raise, so they’re gonna get $2.5 billion in cash in addition to whatever they have right now — and they’re already one of the best-funded companies out there. They’re burning a lot of money, making a lot of investments, but $2.5 billion dollars in cash is no joke. I don’t know, if you want to weigh in on anything with the how they’re pursuing that or what’s ahead for them.

Drew Endy 47:20
Yeah, and let me just be straight. As mentioned, through the Ginkgo acquisition of a company I helped start years ago, Gen9, I have a little bit of equity in Ginkgo. Two of the founders were my PhD students at MIT, including Jason [Kelly], the CEO, and Barry Canton. But I’m not inside Gingko. So, I just want to admit to that, too, and so anything I would have to offer are just how I how I sort of see things overall. I thought your analysis on Twitter hit a lot of marks. They’re getting a lot of capital, when I look at their burn rate, the capital they have is decade of runway. Now, they probably have ambitions that would take off faster than that, for sure, but that’s a lot of freedom to operate.

Drew Endy 48:12
Some other things I can observe about Gingko. And at a personal level I’m actually quite proud of this from afar. How many companies when the pandemic hit actually changed what they were doing to help?

Maxx Chatsko 48:26
Yeah, that’s true.

Drew Endy 48:28
Not very many. And so and so what do you make of the fact that you’ve got this company that actually was agile enough at the scale they’re operating to do things to help? Like help with making the RNA vaccines and help with backstopping testing for public schools across the country. Like, holy cow! So, there’s a signal there that there’s something about this organization. If you didn’t know anything about the organization, you’re looking at an organization that’s a corporation that’s agile enough to, on the dime, actually make contributions to society in an emergency. I just didn’t see that very much. Like, I didn’t see other companies in the biotech space who could have done stuff like that, doing stuff like that. That’s kind of interesting. And I think I’m being understated. It suggests that this team knows how to operate a pretty sophisticated team of hundreds of people to do useful things.

Drew Endy 49:26
Let me let me zoom out and come back in. When Ginkgo was getting started, nobody knew what to think about Ginkgo. I remember when they were leaving the laboratory and like, what are they gonna do? They didn’t know. Of course, this is over a decade ago, I remember talking with Tim O’Reilly, like, should he invest in Ginkgo? Like, I have no idea! What are they gonna do? And Jason makes a lot of fun of me for that one, right, because that wasn’t good advice to Tim on my part.

Drew Endy 49:54
Now, the first innovation I saw with Gingko, and I think you’ve touched upon this, is not a technical innovation, but a business innovation. It’s the fact that they’ve defined the product as the organism. I still remember coming from a workshop in DC and Jason was very clear, like, adamant. He’s like, “The organism is the product.” Like what are you talking about? He was, “The organism is the product.” I’m like, “Okay…” The context for that statement is Amyris and what becomes Zymergen– so I should also disclose I have exactly one share of Amyris, which I bought it in the spaces of $30. I bought that share so I could speak as a shareholder of Amyris to the Board of Directors. It didn’t work at the time, but I tried. And so Amyris invested in their rapid yeast strain engineering platform, RYSE, automated strain engineering. Beautiful platform, hundreds of millions of dollars. And they didn’t let anybody else use it. Only Amyris could use it.

Drew Endy 50:52
And I remember talking with Lynn Conway, who we discussed before, Lynn opened up access to the chip fabs. And so I asked Lynn, “How did you convince the companies who had invested into the silicon fabs to let other people run processes on their fabs?” She immediately wrote back with seven rationalizations that she used to open up access to the chip fabs back in the 80s. I immediately forward that into Amyris, to the founders. Like, “You got to open up your fab and here’s what Lynn says about it.” We couldn’t get that to happen. Basically, my view of Amyris, and this is this is not Amyris today, this is Amyris in its first generation, they over capitalized in the fabrication platform relative to what that platform could support in the market, because the product was the ultimate product used in the marketplace. When Ginkgo says the organism is the product, they’re putting a business-to-business interface in place and wrapping up their offering, so that you might have a chance of getting scaling downstream. Let’s come back and talk about that in a minute. So, the first innovation in Ginkgo, in my mind, like really significant innovation, is a business innovation. Defining their product as an organism and not trying to own all of that, letting other people, other corporations benefit from that. That was and remains a radical approach. Zymergen attempted this in their initial instantiation, but has pivoted to vertical now, so far as I can tell. I’m not inside Zymergen, but they seem to have gone more traditional to sort of own up, so to speak. Would you agree with that?

Maxx Chatsko 52:25
Yeah, they’re [Zymergen] scaling in certain verticals. I bet they’re gonna come back around, maybe open it up a little bit. Their pivot is what markets they’re focusing on. So that’s a little bit different for Zymergen. But yeah, that would be correct.

Drew Endy 52:38
That’ll be really interesting. Like, that’ll be really interesting if they loop back. If I think about Zymergen or Ginkgo as an experiment with risk, like, where are the risks? It seems to me like there are two big risks.

Drew Endy 52:56
One of the risks is, it’s easy to prototype biology that demonstrates you can do something, but then you have to actually bring that to market. So I could prototype something in a laboratory, but that’s not going to earn me revenue. What’s going to earn me revenue is an actual manufacturing process that actually results in people buying something and using it — that downstream set of activities. You could have the best bioworks in the world that’s doing the prototyping in Boston, but if you don’t have something that’s going to scale to go to market, good luck. That’s one thing that limits scaling.

Drew Endy 53:30
The other thing that limits scaling, at least I used to think this, would be property rights and patent claims. If you’re doing high-throughput fabrication, how do you get freedom to operate on all the things you’re doing? Because there’s patents all over the place in biotech. Long ago, I’m looking at Ginkgo and I’m going, “Okay, these are going to be the two major risks: Property rights claims and scaling of the downstream processing [and] going to market.” How are they managing those risks? Well, the property rights claims you can manage with money. It’s actually pretty easy to solve if you have money. You can basically buy freedom to operate and they appear to be doing that well. I think they’ve solved that problem and that’s pretty good.

Drew Endy 54:15
So then, the remaining the risk or problems, so far as I see it is, the scaling and the going market. If you’ve got your bioworks and you can prototype out the wazoo, how do you make sure you’re getting into the real world at scale? This is where the architecture of “the organism is the product” combined with their JV approach and other things like that seems like another innovation within the corporation. I see that there’s ambiguity, it’s like, “How do we value this stuff as a potential investment? How do we evaluate equity stakes in other biotech startups and other sorts of partnerships?” I’m gonna let you and others solve that problem, because I think that problem is going to get solved ultimately.

Drew Endy 55:02
But what I like about it is, it seems like the architecture of the solution is correct. In other words, if you’re one company and you try to do all the scale up and go to market, good luck, you just can’t scale that. If you create an ecosystem that allows many people to work together with you on the scale up and going to market, I think that’s plausible. I think that’s the best-in-class approach. There’ll be market dynamic questions on how it plays out, but I think it will work. It’s just a question of, how long does it take to play out? But I think they’ve got the right business-to-business architecture.

Drew Endy 55:38
I’ll just pause there, I have one more thing to say about it that might help make sense of it, but what do you think?

Maxx Chatsko 55:43
I think you’re right. So maybe just to summarize that, we have bottlenecks in synthetic biology. We’ve kind of been kicking them further downstream with every advance every so many years. It’s no longer in working with DNA necessarily, or sequencing. It’s no longer really in R&D. I mean, there’s still bottlenecks, of course, there’s data bottlenecks now, you’re generating so much data, how do you work with it all?

Maxx Chatsko 56:08
Now, the biggest, most obvious bottleneck that’s remaining is still the scale up and the manufacturing. That’s my background, just scaling up fermentation. On the one hand, in biologic drugs, we see a lot of contract development manufacturing organizations, CDMOs, coming out and that’s becoming more popular. Drug developers want to focus on clinical trials and then hand off their manufacturing to someone else. Maybe we’ll see that in biology. I don’t see, necessarily, the proper amount of thought or investment in the manufacturing side of things yet. We still need like a Ginkgo-level event for manufacturing, in my opinion.

Maxx Chatsko 56:47
And I think right now, I mean… I don’t know. I don’t know if we can decouple that yet. I know there’s companies out there working on it, but like Zymergen for instance. Not to poopoo them, but they hired people to run their manufacturing teams that worked at Apple and Lego. That’s not how you do it. Like, what do you guys doing? Maybe that can help with procurement of starting materials and things, but you need people who understand biology to be in charge of your biomanufacturing, in my opinion. But yeah, I think you hit it on the head.

Drew Endy 57:22
Let me read that back because I think you’re right on target. One thing that’s really important to note is the workflow had bottlenecks that were just in the R&D and prototyping at the bench and then other parts. If I read back what you’re saying, we’re at the final bottleneck. Now, it’s the bottleneck of scale up and go to market for the whole sector. That’s the problem that’s getting solved now. And if we loop all the way back to some of the fundamental stuff like operational mastery of the cell that’s getting solved too, but on the marketplace right now, we’re now hammering away at the final bottleneck. Ginkgo’s got this approach, which is scaling through partnership, hammering away at that.

Drew Endy 58:00
I want to pull back from Ginkgo for a second and hammer on something bigger than that. So you’re making a great point. And remember, we’re operating without industrial policy as a nation. We should probably… We had the interstate system, we should have the biostate system. We should be building biofermentation, biomanufacturing capacity in every district of the House of Representatives, 435. We should have the Bio Belt. We should be spending $25 billion a year on domestic biomanufacturing capacity. And not just the physical plant, but the people who know how to do it. People who are actually skilled at operating these facilities and making high value products that are high quality. We are not like educating that group of people at the scale we need.

Drew Endy 58:49
I had a really interesting call with a with a mid cap firm out of Boston. They were observing what was happening in the sector and they had done very well over the last couple decades in the information sector by investing in the support industries, the things needed to make a data center work. What are all the businesses that exist in supportive data centers? What are all the businesses in support of the internet? The Cisco, right, but things that most people will never hear about. Because they need to be there, they’re part of the infrastructure from a business perspective and they make a lot of money. They don’t make 100 fold, 100,000 fold return, but they make like 20% growth year on year on year in perpetuity. So that was pretty interesting, but that type of investor was appearing and anticipating that the bioeconomy developing this decade was going to have opportunity for business that was in support of scaling the bioeconomy. And I think that’s right. And I wish it was complemented by smarter public policy and we’re working on that, but we don’t have it right now. I just want to acknowledge that.

Maxx Chatsko 1:00:05
Yeah, in one of your recent interviews, that’s a good point. You said, “We operate with this idea that biology is something that happens to us. It’s not something we act upon.” And that really needs to change in order for us to have a national strategy on the bioeconomy. And that is the economy. It’s not the bioeconomy. Like one day, we’re going to drop the prefix. If you remember from ethanol, in the early days, in the early 2000s, we used to say “bioethanol.” We don’t say “bio” anymore, we just say “ethanol”. How else are you gonna make it? I think, hopefully, my grandkids will be like, “Yeah, Grandpa, how else would we make concrete? It’s not bioconcrete, dude. Like, what are you doing?” So that change in mindset is really important, I think.

Drew Endy 1:00:49
I’m with you, 100%. It reminds me of the Semiconductor Research Corporation’s synthetic biology roadmap from late 2018. Semiconductor Research Corporation — like Intel, Fairchild, Qualcomm — why do they have a synthetic biology roadmap? It’s exactly to your point, they believe in 30 years that Tom Knight was correct and we’re going to be growing inorganic computers. We’re not going to call it the bioeconomy. It’s just gonna be like, this is how we do stuff.

Drew Endy 1:01:22
What’s amazing to me about that roadmap is it’s not just this fantasy from 30 years out in the future, it’s, this is what we’re doing this year, and next year, and the next five years. And then the next five years is a very plausible roadmap with intermediate deliverables in the marketplace, like data storage, abiotic data storage in the DNA tape as an earlier possibility. But then, what’s also confusing to me is it’s not happening like that. That one roadmap from the SRC would seem to imply we should be, just in the United States, investing about $6 billion a year in R&D to make that roadmap come true and to the best of my knowledge we’re not. So you could either complain about that or just go, “Wow, that’s a kind of interesting opportunity. If the whole the whole semiconductor sector believes this is the future, and it’s not being invested in right now, if we can find the right opportunities along the way, there’s just like sustained growth opportunities for next three decades.” That happens to get to the future we want for everything.

Drew Endy 1:02:26
Let me read it back. Just one thing at a high level, that may be helpful. As a corporeal being, as a human, I need three things from a first principles physics perspective. I need energy, I need knowledge, and I need stuff. I need joules — j-o-u-l-e-s –, I need bits, and I need atoms. I can quantify how much joules, bits, and atoms I need. And we can quantify that for the whole of civilization. So if I’m thinking about investment and I’m thinking about society, not only is this true for me, it’s true for all of us.

Drew Endy 1:03:00
How much energy does civilization need? Twenty terawatts — and we’re gonna need more. How are we getting the joules? How are we getting the bits? How are we getting the atoms? The synthetic biology sector, well, biology operates at the intersection of joules, bits, and atoms at a local scale and a planetary scale. If you’re investing in synthetic biology sector, it’s an investment in the thing that’s using energy and information to wrangle atoms. So, it’s an investment in the atoms platform, the atoms wrangling platform. Does that make sense?

Maxx Chatsko 1:03:33
Yeah, absolutely.

Drew Endy 1:03:35
Yeah. Does your portfolio have blended balance across the joules, bits, and atoms sectors? Are you only investing in the bits or joule sector? And the bio play is sort of an investment in all three, but certainly weighted into the atoms.

Maxx Chatsko 1:03:52
That’s a great analogy. I love it.

Drew Endy 1:03:54
Yeah, and it also sort of depends on what future you want to live in for you and your family. Do you want to live in a future that’s dominated by joules and bits, and you’re going to digitize your body? Good luck with that. And live in the cloud or are you actually going to live in reality, a corporeal three dimensional reality, with atoms? In which case, you probably want to be supporting biotech.

Maxx Chatsko 1:04:12
Yeah, I prefer that future.

Drew Endy 1:04:14
Yeah. I just want to acknowledge, where I live, not everybody. There’s two tribes out here in this regard. There’s the tribe of joules and bits, who want to digitize the brain, and that’s not going to work. And then there’s the tribe of joules, bits, and atoms, which I’m part of. So anyway.

Maxx Chatsko 1:04:30
Well, I support your tribe, Drew.

Drew Endy 1:04:32
[laughs] Alright.

Maxx Chatsko 1:04:34
I significantly underestimated how much time we might go. I know you have a hard stop soon. So maybe just to close it out. We’ve kind of touched on some of these, but just to remain objective, what are some of the bigger challenges and obstacles facing synthetic biology? We’ve touched on some of these, they may be economic or societal or technical or political or whatever it might be, just to give readers a little dose of objectivity here.

Drew Endy 1:05:02
We’ve covered them. So let’s just read them back, but try and get it clear.

Drew Endy 1:05:08
At a fundamental level, we don’t understand the basic unit of life, the cell, completely. We know a lot about it, we’re about two-thirds done, but we’ve got one-third to go. This is the decade where the fundamental unit of life, the cell, gets figured out well enough to build cells. That completely unlocks building with biology. And so, you should anticipate significant qualitative change and what becomes possible. Even though many things are now possible, many more things are going to become possible. This is a very dynamic space and dynamic market that’s deeply coupled to fundamental investment and tooling and fundamental science. So be prepared to be surprised in positive ways.

Drew Endy 1:05:53
A second thing we touched upon is, it’s one thing to demonstrate something in an academic paper, or another thing to demonstrate something in a startup. That’s an incremental demonstration. But it’s a whole other thing to bring that into the marketplace. When you write software and you demonstrate your app to your team and your startup, you can ship that as bits and it goes out on infrastructure that scales. When I demonstrate something in bio, and of course it’s encoded by DNA, I ultimately have to bring atoms to market, not just bits. There’s a whole physical scaling process of bringing the atoms to market at the scale, the actual stuff, the matter is needed. There’s opportunities to support that economically and make money. But also, when you look at the companies that are betting on scaling, think carefully about how they’re scaling their capacity to wrangle atoms to manufacture stuff, and what their solution is to that puzzle. And I think we correctly identified that is the last big puzzle to solve to unleash the promise of first-gen synthetic biology.

Drew Endy 1:07:02
There’s a couple other things which we’ve touched upon. We have a hard time as a society talking about biotechnology, for reasons that are valid. I have a class we teach in the D school out here and we do an “I used to think and now I think” exercise with the students. One of our students this last quarter, she said, “I used to think that emerging technologies happened to me. And now I think that I happen to emerging technologies.” In other words, she acquired agency and became a protagonist with respect to constructing a future she could love. With biotechnology, I think we’ve inherited a lot of dysfunction from the first-generation of genetic engineering — GMOs, bioethics, this and that. We need to learn how to fall in love with biotechnology. The country that wins the geopolitical race of biotech is going to be the country that figures out the cultural puzzle of falling in love with biotechnology.

Drew Endy 1:08:05
As an aside, this is one of the things that’s pretty interesting about Gingko. They’re operating cultural products, their magazine Grow, is a really interesting product. They are doing the work that IBM did to explain to people what computers were and what a business machine would be in the 1940s. Ginkgo is shipping, not just product that’s like the actual atoms you’re using, they’re also shipping cultural product. That’s crazy rare. So falling in love with biotechnology as a culture seems pretty important.

Drew Endy 1:08:42
Now, there’s one more thing which we didn’t touch upon at all and I’m not sure, should we get this, like the one more thing, bonus topic. Should we do it or not?

Maxx Chatsko 1:08:48
Let’s do it. Lay it on me.

Drew Endy 1:08:50
Oh, God. Okay. So, this comes back to urgency and things that your comment about first-mover disadvantage. People use past experience to project and everybody knows the caveats. With emerging technology, one of the common cliches is Moore’s Law, the exponential increase in computer power. And so that’s appeared in genomics and synthetic biology because of improvements in DNA sequencing and synthesis. When you’re operating in a Moore’s Law domain, one of the things you think about from a competitiveness perspective is keeping up.

Drew Endy 1:09:37
The core of Moore’s Law is your better computer will help you make a better computer will help you make a better computer. That better tools help make better tools help make better tools, and that piles on and gets that exponential amplification. If you fall behind on an exponential, it becomes harder to catch up because the people in the lead accelerate away from you. This triggers sort of an urgency around keeping up on an exponential. And that’s certainly true in a way in synthetic biology, but I think completely misses the point. The other laws that are at play in synthetic biology and biotechnology and the bioeconomy more broadly are related to networking strategy.

Drew Endy 1:10:21
I’ll give you an example from academia. The number one law school in the United States of America is in New Haven, Connecticut at Yale. Why is that? It’s because the college students who want to go to law school, don’t know who the other best students are going to be. Even if they could figure out who those people were, you couldn’t organize a Zoom meeting and you couldn’t get everybody to agree to go to one place. Like New Haven, like really? That’s called a coordination problem. And so what’s emerged over the centuries is the answer to that coordination problem appears, it’s Yale Law School, and it solves the problem that the college undergraduates have. Another example of a coordination solution is search. Where are we going to go to search? Probably Mountain View, probably Google. As soon as things go on networks– Oh, and by the way, just to explain it. Anybody who links — this goes back to Joy’s Law — anybody who links a web page to another web page is working for Larry [Page] because he’s going to create value from that labor, even though he doesn’t send them a paycheck.

Drew Endy 1:10:21
How do you create strategies that benefit your organization from the labor of others and create value? Ginkgo is positioning itself, I think, to create coordination solutions on a networked bioeconomy. They may not fully understand this yet, but they’re doing it. Maybe they do understand, I don’t know, but it looks to me like they’re there. They’re there. They’re implementing a coordination solution. If they pull that off, they won’t get displaced. I mean, there might be another coordination solution in China, but pretty much that’ll be that.

Drew Endy 1:10:21
Networking strategy is how people act in relation to each other and how value is created on the basis of how people did an act in relation to each other. The two laws that I think are most [useful] are Metcalfe’s Law and Joy’s Law. Metcalfe, after Bob Metcalfe, [says that] the value of the network is the square of the nodes connected on the network. If we’re just talking, we have some value. But now if a third person could talk to either of us, we each get to have two more conversations, and so on. And it just keeps going up with that square exponential. Joy’s Law is a little bit more subtle. It’s an observation that most people don’t work for your company. Most of the labor that create value for your company, you don’t give them a paycheck. And it begs the question, what do you do about that? How do you exploit that reality that most people don’t work for your company?

Drew Endy 1:11:18
So Gingko, in its early form, if we just use them as a case study, they were using the rhetoric of Moore’s Law. You know, DNA printing is getting a lot better, we’re buying most of the DNA print capacity in the world — bigger, bigger, bigger, faster, faster exponential improvements. But what’s actually impressive, is they’re implementing network strategy. They’re creating a coordination solution, which is where people go to get the biology they want. Coordination strategies appear within networks. The interesting thing about coordination strategies is that once they form, they’re very hard to displace.

Drew Endy 1:13:33
And so that’s very different than an exponential strategy where you could get displaced, because somebody will leap ahead of you and then you’re behind. But coordination solutions, if you become the go-to place to do something, you’ve got to, and it’s not quite the same as like what I see on the chatboards, like “they have a moat.” Like no, that’s not really a moat. It’s an immovable object. The coordination solution, once it’s entrenched, you just don’t move it.

Drew Endy 1:13:33
Yeah, anyway. Well, so we didn’t touch upon that at all, but I just want to emphasize biotechs going on the network. And as soon as the network appears, you get network strategy opportunities. My prediction is, in the year 2030, we’re going to be more comfortable using words like the PB, the personal biomaker, and we’re going to be more comfortable using words like the “bionet.” And we’ll be more familiar with design anywhere, grow anywhere. But that’ll have to be made true. And that’ll all have to be made true right now in the absence of coordinated industrial public policy. It’s really up to the private investor and the markets to figure out these opportunities, in the meantime.

Maxx Chatsko 1:14:40
Well said. I could talk all day about the bionet with you, Drew. So thanks for joining me today. And you know, where can people find you? Or should they not find you, leave him alone? You’re @DrewEndy on Twitter, I think, right?

Drew Endy 1:14:53
Yeah, that’s valid. And as you can see, I’m hiding out on campus and avoiding barbers for the foreseeable future, we’ll see what happens next.

Maxx Chatsko 1:15:03
Alright, well you stay safe out there, hunker down, you’re not traveling anymore, but we’d love to have you back on the podcast in the future.

Drew Endy 1:15:11
Maxx, really great to connect with you and I’m long grateful for benefiting from your analysis. I really appreciate what you do and the constructive sense of reality you bring to this important space. So I would look forward to talking again, my pleasure. Absolutely.

Maxx Chatsko 1:15:30
Thank you. I appreciate that.

“Drew Endy is a bioengineering professor at Stanford who studies synthetic biology. His goals are to enable civilization-scale flourishing and a renewal of liberal democracy. Prof. Endy helped launch new undergraduate majors in bioengineering at both MIT and Stanford, and also the iGEM competition, a global genetic-engineering “Olympics” enabling thousands of students annually. His past students now lead companies like Ginkgo Bioworks and Octant. He is married to Christina Smolke, CEO of Antheia, the essential medicine company. Endy served on the US National Science Advisory Board for Biosecurity (NSABB), the Committee on Science, Technology, & Law (CSTL), and the Pentagon’s Defense Innovation Board (DIB). He currently serves on the World Health Organization’s (WHO) Smallpox Advisory Committee and the International Union for the Conservation of Nature’s (IUCN) Synthetic Biology Task Force. Esquire magazine recognized Drew as one of the 75 most influential people of the 21st century.”

https://2020.igem.org/Team:Stanford
https://www.nature.com/articles/s41586-020-2650-9