Good morning, everyone. This is Steve Mah on the Tools and Diagnostics team. My pleasure to introduce Jason Kelly, CEO from Ginkgo Bioworks, to the Cowen Health Care Conference. As a reminder, if you have any questions, please email them to me at steven.mah, M-A-H, @cowen.com. Jason, I mean, I've known you many years, but, you know, do you wanna give a quick intro to folks that aren't as familiar with Ginkgo? Yeah, sure. To kind of level set us. Very happy to do that. Everyone can hear me okay? That sounds a little echoey up here. There we go. How's that? Better? Okay, good. Sure. Yeah, I'll kind of give a little bit of like a healthcare, you know, framing for what Ginkgo does. The easy way to think about what we're trying to pull off at Ginkgo is we're trying to centralize an activity that today is done in a distributed fashion. Think of it like the discovery activities associated with biotech drugs. All right? About half of your new FDA-approved drugs are coming out of biotechnology, right? In my view, they have something in common, which is essentially each one is basically putting a designed piece of DNA into a cell and then putting that cell into a particular environment that makes this drug, right? If you rewind the clock to 1982, that's putting a gene for human insulin into an E. coli cell, into a metal tank in South San Francisco at Genentech, right? Go a few years forward, right? It's monoclonal antibody DNA inside a CHO cell at AbbVie, okay? Making monoclonal antibodies, right? Cell therapy, right? Arie Belldegrun's on our board at Ginkgo, right? This is a piece of DNA inside of a T cell, okay? Going into a patient with cancer. All right? Gene therapy, right? CRISPR Therapeutics announced a partnership with Vertex, also on our board, Reshma Kewalramani from Vertex, to go after sickle cell, right? That's adding a piece of DNA into a patient cell in vivo. Everyone knows about mRNA vaccines and Moderna, right? Again, mRNA being delivered in vivo. My view on this is all those activities, the process leading up to when you put something in the clinic is essentially cycling through genetic designs, putting them into cells, testing how they perform, and then based on what you learn, iterating on those designs. The entire bet of Ginkgo is that that activity, which looks really different across all those modalities, is actually the same activity. You can centralize that activity on top of automated facilities. If you want, you know, we're right down here in the Seaport, about, you know, minutes away from here, about a 250,000 sq ft automated lab. We can talk about the technology, Steve. The idea is that work today is done in a distributed fashion across thousands of biotech companies and large biopharmas, and we believe it should be centralized into a small number of automated facilities. Now that seems crazy, right? All these companies already have their own lab setups. They have scientists in lab coats holding pipettes doing this research. How can you drive centralization? My argument would be, if you look in the tech industry in the late nineties, early two thousands, everyone had an IT department, everyone had servers and, you know, big setups in-house, you know, with those on-prem physical infrastructure and teams. Along comes the cloud with a physical scale economic and data centers. Over time, that just wins, right? People move and they have all these excuses. They don't wanna move. It's my data, it's this. I don't trust you, Amazon, whatever. Eventually the scale economic of the centralized infrastructure wins. That's the core bet of Ginkgo, is that we're finally at the point, and we can talk again about the technology, where a centralized infrastructure to do preclinical biotech drug development is gonna win over distributed infrastructure. That's the short answer. We can talk about the tech, and we can talk about the business model, Steve, about how we're pursuing that. You either believe that or you don't. If you believe that, I think Ginkgo's a good bet. If you think it deserves to be distributed for some reason. We're not. Yep. Yeah, yeah. Why don't we talk about the business model? You know, obviously this is a healthcare conference, but Ginkgo does a tremendous amount of things in like the applied, you know, applied markets, right? Whether it's flavors and fragrances, ag bio- Yeah. Food, whatnot. you know, Well, maybe just say a little bit. Yeah. About that and opportunities there, and then I'll kind of dig into therapeutic. I mean, this just kind of level set people. Sure. How the technology can be used for like, literally almost anything that's carbon based or biology based really, which is essentially everything except maybe oil drilling. Yeah, yeah. Anything involving a cell. Yeah, that's the short answer. Yeah, again, what's the right business? Let's say we're right and that you ought to centralize this activity. Okay. You know, today we have customers like Biogen, Novo Nordisk, Merck, right? They have their own research labs. Why have they outsourced work to us? Okay, we have to have something that they don't have, okay? The two things are physical scale and automation, okay? The reason this is important is the bigger your automation, think of it like a factory for making chips or cars, the lower the unit economic of the thing you're making. The case of Ginkgo, what comes out of our automation are characterized genetic designs. If you want to cycle through, as an example, at the, you know, SITC conference, immunotherapy conference a few months back, we presented data that we had done in CAR T, right. Where we made these huge genetic libraries, 10,000 libraries, tested in vivo. That scale of being able to generate those libraries, you just can't do unless you have highly automated mammalian genetic engineering running at a bigger scale than your scientists could do with a pipette. That's the first asset. Automation to allow you to try more genetic designs per research dollar. The second asset is data. As we do all that work in the lab, we do it in a systematic way. We collect the data, Steve, we should talk about this, but we have IP arrangements with our customers that Ginkgo retains the rights to reuse the IP. The second reason you work with us is you want access to our genetics, to our data, to our learning from projects we've done before. We have a project with Selecta and capsid design, that we have now a great capsid library. If folks are doing AAV therapy, they want access to some interesting capsids or work on the problem of tropism, call us up, okay? They're available as part of our data asset in our service offering. Those are the two things, the automation and the services or, sorry, the data are the reason people contract with us. Yeah. All right. What's the business model? Very, very fancy CRO is the easy way to think about it with a pharma hat on, okay? Folks are contracting research to us. They're paying us a fee to do the work over the period of a project, might be from like one to two years of research fees. The big difference between us and a traditional CRO, like, you know, someone doing animal trials like a Charles River or small molecule libraries, you know, like a WuXi, is that we, number one, take a royalty or take milestones or equity, some type of value share on the product, on the drug product that is gonna get produced with our platform. That's different than a traditional CRO. Number two is this IP arrangement I mentioned earlier. We're retaining rights to reuse the IP for other projects, also different than a traditional CRO. Other than that, it's a research services business, right? And we, you know, got now 96 active projects. As, you know, to answer your question, Steve, about 34% are pharma. In pharma? Okay. Yeah. Right. And then about a third are in ag and food, and then the remainder are in industrials, so things like chemicals and nutrition and flavors and fragrances, things like that. Okay. Yeah, maybe let's talk about the value proposition of each of those things, right? Obviously, you know, you talked about in your last earnings call, you know, the downstream value for therapeutics is arguably higher than some of these applied markets. Sure. If you talk about the mix and do you expect to keep, you know, about a third of your new program adds in therapeutics or do you expect that to grow? A good question we get all the time is like, "Hey, it seems like biopharma is a much bigger research market for biotech than, say, fragrances." That would be true. It would seem like the value of a therapeutic drug is much greater than the value of a, you know, nutritional ingredient. Also true. Okay, why didn't we just start offering our services business in the best market for it, biopharma, when we, you know, started the company now 15 years ago, but say over the last 10 years, why not? The answer was, I have to convince you to not use your internal team, but rather to outsource to me in order to get you as a customer of Ginkgo. Like, I am not a product company. I don't have my own pipeline of drugs. I can't just think I'm so smart and my technology is so good that I could develop a drug. I have to sell a customer on it. If I were to compare the delta between internal R&D at a fragrance company in biotech and Ginkgo's platform eight years ago, we were better than them. They're a bunch of chemists. They're not biotech people, right? They weren't any good at biotech. I had to convince them biotech mattered in their industry, but I was better than them at it. Eight years ago, I could not have walked into Biogen. I could not have walked into Novo Nordisk and incredibly said my platform was better than theirs. Why? It was a lot smaller back then, right? I'm running a scale business, right? As our infrastructure gets bigger, it improves with scale, like a data center or a chip fab. It's only been in the last, say, four years or so, Steve, that we've gotten into biopharma at all. Right. Right. Right? And that is a function of the improvement in the technology. Now where will I go? Oh, you better believe more biopharma, because now we've proved it, right? Like, we are signing up. Again, this is not my opinion, this is the opinion of our customers, that we can win deals in that area, that we have something to offer proprietary, and it's such a better market than some of the places we got started in. Yeah, I think you should expect us to do a lot more biopharma over the next 2-3 years. Then, you know, who knows, right? I think the wild card in all this is that the technology gets substantially better. As the difference between what you can do with an automated facility and at the lab bench improves, maybe new markets open up. Yeah. Yeah. Okay. Let's talk about the scale, of you know, your foundries. I know you just opened Bioworks7. Yeah. Let's spend a little bit of time on that and, you know, is, you know, is that sort of driving a lot of new partnerships? Yeah, I'd say the two big things that drive our partnerships are, well, let me say this. Biopharma in general is, like, very data hungry in terms of choosing to work with us. We like to give tours of our facilities. We can show the total output of our genetic engineering in mammalian, but, like, what's really carried the day is, as we've been doing programs over the last two and a half years, we now have interesting data that they see, "Okay, you can build, whatever, that many CAR T designs. You can build that much in AAVs. You can do this much in microbiome." We can just show them the scale of the data. It's not on exactly their drug, obviously. It was with somebody else on something different, but it's in their modality. That's the biggest driver. is like the proof in the pudding data with something close to what they're interested in. Not exactly what they're interested in, but close. The other thing is we did eight acquisitions last year. We acquired a, for example, a company called Circularis. Okay, it's a circular RNA company. It's not Orna, okay, right? It's not like the famous ones, right? It doesn't have much of a pipeline of its own, but it had really good technology. It also had great technology around promoter screening. It's like a reusable asset in the genetics. That has quickly turned into some great conversations around new deals in circular RNA. That type of asset is also useful for in our hands. Yeah. more than it's useful in a small biotech, because we have the sales relationships. We can put it on top of our automation and quickly demonstrate interesting new things. There's also that as part of the sales process too, it's a unique IP. Okay. Yeah. Got it. How do you get your partners to sign off that you can use this IP? You know, I mean, most biopharma- Yeah. -are pretty secretive about that. Touchy about that. Yeah, sure enough. Yeah. Not an easy discussion. Yeah. I would say, for starters. Our basic argument to the industry is that the isolation of genetic componentry across thousands of companies is reducing the odds of success collectively of getting drugs to market. Okay? Like, if someone develops a better capsid over here, that is not the whole drug, right? That's a piece of the drug. Like, what is the payload is a whole separate thing to innovate on. Why, if you are over here coming up with some great ideas for a payload, do you have to use a substandard capsid for your application just because somebody else with a totally different idea, they're the ones who happen to invent the capsid. This is a joke, right? Like, if you look at how the software industry operates as a comparative example, enormous amount of exchange of the functional componentry. Like, no one owns the if then statement. No one owns a for loop in software. We've agreed there are certain low-level functions that are better off exchanged, and then what you are selling is the higher level combinations of those functions in proprietary pieces of code. This is the direction genetic medicine needs to move to, or we're going to be stuck in this world where the genetic medicines are embarrassingly simple, right? Like one or two genes, almost no regulation. Like, these things are a joke, right? Like, if you want to be able to unlock the true potential of biology, look at the complexity of a T cell. We should be hitting a lot more in how that machine works with much more complicated genetic perturbations. We're not going to do that if all of the assets are split among 100 different T cell companies. Okay? What I'm creating is a walled garden in which everyone gets to share the reuse of the IP. Just like if you logged into Apple's ecosystem for the iPhone, and they would give you a bunch of functions that make it a hell of a lot faster to develop an app. That's going to be the same thing if you're on top of Ginkgo's platform. It's going to be easier to develop genetic applications because I'm driving an IP regime that is not typical. Yeah. -in the wider industry. We're very aggressive about that. We hold the line on that. If people don't like it, then go back to your guy at the lab bench with a pipette, ultra-low throughput, right? you know, and try to compete. Yeah. No, no, that's a great analogy. Staying on the foundry and the capacity. You know, your business model is pretty dependent on adding new partnerships. You know, you just said at your last earnings call you're going to add, you know, about 100 this year. Yep. So- We did 59 last year. Yeah. Can you talk about the, you know, capacity of the foundries? You guys need to build out more? Yeah. Increase automation, you know. Sure. What's going on? Yeah. We track a couple things about this, right? Like one of the biggest metrics, this is why, you know, I've talked about this for years, Steve, is adding new programs onto the platform because they add value to Ginkgo in two ways. One, they are the license for us to build bigger facilities. Yeah. Okay? Right. If you don't think you're going to sell a lot more cars, you're pretty scared to build the bigger factory. If you don't think you're going to sell a lot more chips, you're pretty scared to build the bigger factory with better economics. Signing up customers is our license to build bigger, more efficient factories. Okay? The second reason we like signing up new deals is the IP reason, because each one is a new opportunity to generate some data that might be what helps us get the next deal. Yeah. Okay. Okay? Now, we have to be able to deliver on those. We're actually in an interesting spot. I would say, we acquired last year a company called Zymergen out in the Bay Area that brought in a bunch of new automation and software technology. We did eight acquisitions last year. It was a lot. We did kind of like an expansionary move in response to signing up a lot of new deals. This year, what I'm trying to do is keep basically, like, our expansionary spending a lid on it and really focus on driving efficiency on our platform. In other words, with the assets we have, what can we do to improve our capacity output through integrating that new automation from Zymergen, driving bigger scale, improving the software, all those things. I like this because it means that on the end of this year, I think we'll have a more, like, efficient platform to clone out as we expand more in the future. That's sort of like what this year is about when it comes to it comes to, like, our scaling. Historically, we've just kept adding. This year I'm trying to drive a little more efficiency because I think we're, like, a little... We added a lot, and I think we can actually make it more efficient this year. Okay. Yep. All right. We're signing up, you know. What we basically do is sign up programs, and that adds more and more demand on top of the platform, and the platform team has to keep up. Yeah. Yeah. Yeah. Yeah. Maybe let's talk about that. How are you guys able to. You know, if you're doing 100 a year. Yeah. that's gonna be one every three or four days, right? Yeah. How do you guys pay for all the contracts? Yeah. Yeah. This is a very, very good question. couple of things. One of the fellows on our board is Shyam Sankar from Palantir. he taught me how, like, Palantir has, like, a deal team function. Mm-hmm. Which basically their job is to, like, move make deal making a lot more efficient. We created that three years ago now. We have a team that's really just dedicated to making deals close after the sales team has gotten the customer convinced that they should do something with us. How do you make the actual process of close more efficient? That's one thing. Like, be very good at enterprise sales and be very good at deal making. The other thing you can do is try to make the deals more standard. Like get a customer to not want as much customization in the deal. All right? We have done something along those lines. We announced Ginkgo Enzyme Services, which is basically a more standardized offering to the market, specifically around one type of cell engineering, improving an enzyme. That's a much more cookie cutter deal. It's kinda more take it or leave it. It's an experiment on our side in making deals close faster by trying to shape the customer demand into, like, a square peg. Right? The reality is, most of the market, because in-house, they have infinite flexibility with their internal R&D team, they want custom stuff. Mostly it's getting efficient at closing custom deals. Okay. I think we're best in class at that, but we can definitely get better. Most people look at deal-making like one-off stuff. You know, like I'm doing a whatever, I'm buying an asset or something from a pharma company. It's not meant to be like a machine. You're a CRO, and it's not much of an argument because you're giving away the farm on every deal, right? You're like, "Oh, you keep the IP, you da, da." You know, right? Like, there's not much to the deal because the CRO is not retaining much of the value. We're in between, right? Like, we're keeping value, so it's more of a negotiation, but I can't have each one be like, buying a drug asset. Yeah. Yeah. Yeah. What about, like, your existing partners when they expand, like, the scope of their partnership? Oh, that's way easier. It's obviously faster, right? Yeah. Dramatically. Yeah. The, yes. It's much easier to do inside sales, for sure. The, you know, the challenge is, like, you need to build a relationship with a customer before you get a lot more of those. That's point number one. We have done that, like companies like Givaudan in the fragrance industry went from a pilot project four years ago to now a big relationship. We do a lot of programs with them. We're already seeing this with some of our... Like in biopharma, it's pretty cool. We, we haven't talked about this, but some cell engineering is around discovery, some cell engineering is around manufacturing. Like, our program with Merck, for example, is a develop enzymes to replace certain chemical steps in their API process. $144 million program. That's a manufacturing program. What's interesting is we can get into a company for either manufacturing reasons or discovery reasons and then cross-sell. Either cross-sell from research to manufacturing or, like, if we're in one modality in research, go to a different modality, right? Yeah. You know, we can play anywhere where there's stuff. I do like inside sales in the long run, but, like, in biopharma particularly, Steven, today, most of our new deals are new logos. Okay. Right? Because we're just new in that industry, right? Our deals that we have with existing players, we don't have as much track record yet to greatly expand. Yeah. It's so valuable for me to get someone new, right? Right. Right. Right. Right. Like, that's another, you know. Like, we're talking to companies that never even heard of us in biopharma, right? Like, that's not the case in the chemicals industry. Like, everybody knows us. Right. Right? In biopharma, like almost, you know, I bet 20% of the companies have even talked to us. They're like, "Well, really?" It's early in the game, you know? Okay. Yeah. Yeah. maybe just to follow up on that, is there any particular area you're receiving some more interest in therapeutics? Is it gene therapy, vaccines, RNAi? You know, what? It's kind of a mixed bag. I would say like, cell and gene therapy is probably the most. Cell and gene therapy. Okay. Cell and gene therapy. Okay. Like, we don't do a lot in antibodies. Today, there's a lot of people that do antibodies. Cell and gene is good. The nucleic acid drugs, like RNA stuff, we have interesting things. I mentioned the circular RNA and stuff like that. Yeah. Yeah. Yeah. Yeah. Okay. Those types of areas. Okay, got it. Got a question from the audience about Bioworks7. Oh, yeah, sure. looks like cell and gene therapy is a big push. Did you build Bioworks7? Yeah. Okay. Yeah. for the interest you were seeing, or did you kind of anticipate the interest? We kinda... Yeah, so we made a bet in the mammalian... So just to again, maybe I'll take one step back. I said at the beginning, right, like making a biotech drug, our argument is it is the same regardless of exactly what modality you're in. It is finding the right piece of DNA in the right cell in the right place equals the drug. What is Roundup Ready Corn? The right piece of DNA in the right cell in a greenhouse in St. Louis in 1988, right? Like, it is the same, right? Like being able to design biology, we believe, is completely market agnostic. Okay, let's take what we did four years ago when we moved and we wanted to say, "Hey, we'd only been working in bacterial cells and fungal cells. We hadn't been working in mammalian cells yet." How difficult is it for Ginkgo to move into mammalian? Culturing infrastructure is very different. The way you grow mammalian cells is very different than how you grow bacterial cells. We had to build out, you know, totally different types of containment and things like that around certain parts of the automation and all that. Okay, fine. What is not different? DNA synthesis, right? We, you know, we acquired a company called Gen9. I think Devin said no, but we acquired a company called Gen9 now six years ago as a competitive twist, that they do in-house DNA synthesis for us. The DNA does not care if it's ending up in a plant cell, a mammalian cell, or a bacterial cell. Same. What about our, all of our metabolomics? Okay, we pop cells open, we run them through mass specs at ultra-high throughput. We're really good at this. You know, we're doing acoustics in the mass spec, all kinds of fancy stuff. Does that care? Not really. That infrastructure is extremely reusable for mammalian. I'd say about 60%-70% of our foundry was already useful for mammalian. What you're hearing with Bioworks7 is me bringing online a lot of the culturing, a lot of these things that are the parts that were specific to mammalian, we needed more of that. We had done a few small work cells, just like, again, if you come visit, you'll see it, but it's like a robotic arm in the middle of a bunch of equipment and rails and all this stuff. We had done some of those, but we hadn't had a dedicated pure play mammalian facility. That's what the new facility is. Yeah. Okay. In general, I wouldn't think of it like that's where we do everything associated with mammalian, it's just not, right? All of the DNA synthesis infrastructure is mammalian also, right? A big fraction of what we're building now is going into mammalian just 'cause more of our customers are mammalian. Yeah. That nothing changed over there. All that changed was the orders going in from the scientific teams now were asking for pieces of DNA that were designed for mammalian cells, but that infrastructure was immediately useful because it is common purpose. Does that make sense? Yeah. Yeah, that makes sense. Yeah. Yeah. How big is Bioworks7? I haven't seen it yet, but, you know, I'm assuming it's got, you know, it's got a lot of tissue culture hoods and incubators. It's mostly, work cells. Like, it's again, like, because Ginkgo is not like what your mental model is a person with a pipette in their hand in a hood. Yeah. That's not how we work at Ginkgo, right? Okay. What you'll see is big boxes with HEPA filters and robotic arms and lots of equipment inside them. Okay. Anyway, yeah, you should come check it out. We have about, like, the whole facility down in South San Francisco is about 250,000 sq ft. $250 total. Yeah. Okay. Okay, cool. Yeah. Maybe in the last, five minutes, you know, let's maybe pivot over to the other aspect of your business, which is kind of misunderstood. Yeah, yeah, sure. Biosecurity. Yeah. You signed all these partnerships with all these international groups, including Ministry of Saudi Arabia. Yeah. You know, could you spend some time on, like, how you're gonna monetize that? Sure. And, like, you know, what's- Yeah. What's kind of the end goal? Yeah. Let's all frame it for folks. How did I get into all this stuff? My background, did a PhD in bioengineering back at MIT. I graduated in 2008. We started the company out of grad school. We had this interesting experience back at MIT that when we got there around 2002, where this field of synthetic biology, which is really what we're on about here at Ginkgo, was getting formed on the academic side. There was a group of academics coming together. You know, Tom Knight, who's our co-founder, Drew Endy, Pamela Silver at Harvard, George Church, who were sort of either engineering-minded biologists or biology-minded engineers. They were kinda hanging out and saying, like, "Maybe some of the principles of engineering and computer science will be applicable to DNA code," and sort of like trying different things and seeing what were stupid ideas and what were good ideas. One of the seeds that got planted very early was, if we're successful, if we make it as easy to engineer and program a cell as it is to program a computer, that seems scary. Okay? Right? biology is powerful stuff. infectious disease is scary stuff. If we have the distribution of the tools of designing biology like we've distributed the tools of programming computers to everybody in this room, if they so desire, how do you do it safely and responsibly? That was baked in very early on. We had all kinds of people come by, FBI, WMD, all this stuff, right? I just wanna mention that philosophical point, 'cause then along comes COVID and we're like, "Oh my gosh, this is the moment to build out biosecurity infrastructure." Think biosecurity like cybersecurity. In other words, alongside the tools of programming computers, we built cybersecurity to do it safely. Alongside the tools of programming cells, we're gonna build biosecurity. Ginkgo got involved, okay? We didn't do any of. We didn't do diagnostics. We didn't do. We helped out on some companies working on vaccines and therapeutics, but we don't do that ourselves. But what we did do was things that we felt were not existing markets, like surveillance. For example, in 15 states around the country, we did thousands of schools, like weekly school testing, okay. That's not actually without getting into the FDA issues, but, like, it is a. The point of it is not like you're sick and you're going to get care-seeking behavior at the hospital and get a diagnostic test. It's just Tuesday, and you get tested on Tuesdays to try to reduce outbreaks in your school during Omicron or whatever. That was our first foray, and then that expanded into a program with the CDC and to similar work at airports, where what we're doing is we're collecting wastewater from planes and anonymous samples from passengers coming in from different countries specified by the CDC and looking for variants. We sequence all the positive cases. BA.2, BA.3, first cases of Omicron in the U.S. found in our airports program, okay? We're now doing this, as we mentioned, in a number of other countries, you know, in Qatar, couple countries in Africa and so on. The idea is eventually to have a equivalent of like radar or satellite monitoring for the weather, but a permanent set of infrastructure that if we're gonna be grown up about handling infectious disease in a future where it's easier to engineer biology, you just gotta have. We are seeing support from governments to do that. We- They are deploying money, the different governments? Yeah. Okay. All right. Yeah. We're excited about this. It's very early, but it's going fine. Yeah, you'll see us do more of that this year. Okay. Got it. Final question? Given your cash balance, should we expect more M&A? We ended last year with $1.3 billion in the bank. That's another thing I think that makes us a bit unique in this current market. We did a couple big deals last year. Yeah. both acquiring, a R&D asset from Bayer in agriculture and acquiring Zymergen. I think you'll see us do some smaller things. Okay. That, yeah, that's sort of our plan there. Okay. mostly it's use that cash pile to give us time to get to royalties and milestones on the deals we have. Okay. All right. Great. Well, we're out of time. Yeah. We went through a lot. I really appreciate it, Jason. Yeah. Steve, thank you. Thanks a lot. Appreciate the time. Thanks, everybody. Thanks.