To complete the review of the platform, you'll meet Patrick Boyle, our Head of Codebase, who will help you understand what biological code base actually is and how we leverage it to support our customers. You'll also meet Claire Laporte, our Head of Intellectual Property, who helps not only protect our platform and the IP we've created, but also works to ensure our customers have strong IP so they can successfully commercialize their products. Once you've gotten an introduction to the platform, we'll introduce you to some of our customers across industries and from small startups to large corporations. You'll meet Jennifer Wipf, our Head of Commercial for Cell Engineering, and Ena Cratsenburg, our Chief Business Officer, who together help identify and structure new collaborations and ensure customer success. As part of this, we'll also highlight how we've enabled new companies to start on the platform, helping bring together the capital, strategic partnerships, and of course, access to our platform that accelerates innovation. You'll meet the leaders of Motif, Allonnia, and the newest company building on our platform in the personal care space, who are building businesses in remarkably different end markets but have leveraged Ginkgo's platform since day one. We hope that by now you're excited about the potential for biological innovation in the world. Alongside that potential is an imperative to treat biology with care. We'll feature 2 segments that help illustrate how we think about this imperative. First, we look at the need for a global biosecurity infrastructure and how Ginkgo thinks about the role of biosecurity in building our business. We'll also have a conversation about the role of ESG at Ginkgo and in investing more broadly. To wrap up our prepared remarks, I'm going to sit down with our CFO, Mark Dmytruk, to get a financial update and talk about some of the most common questions that I get from investors on our business model, our projections, and valuation. We'll end with a live Q&A where our team will be available to answer questions submitted on the OpenExchange streaming platform as well as via Twitter at Ginkgo. With that, I'm so excited to be able to introduce you to my friends and colleagues here at Ginkgo. We'll get started with a conversation with our founders. I'm super excited about this part of Investor Day. One of the really secret superpowers of Ginkgo is that we have a five-person founding team that's been working together for 20 years and actually still likes each other. I thought I would give you all a chance to meet the other founders here at Ginkgo, and we just kind of do a little bit of a rap session, I guess. Maybe I'll kick it off. Austin, Reshma, you joined Tom's lab, when was that? I joined first in 2001. Yeah, I joined the year after in 2002. This was at MIT, 2001. How did it happen? What drew you to Tom in the first place? Had you done biology before you met Tom? I did not, but Tom's background also inspired me. He had built a bio lab in the computer science building and had taught himself biology, and his vision of programming cells as the next iteration from programming computers really inspired me to learn and get into biology. Yes. Tom, how did that happen exactly? It's a bit of a strange leap, I'll say. In around 1990 or so, I decided that the end of the interesting things happening in computer science was pretty much upon us. I was just looking around, what's the next interesting thing to do? We were. Computing was over. Yeah. Right. Yeah, computers. I was looking around for the next thing to do, looking at what was going to be the next technology that was going to be important, and looking at how we could make semiconductors, and the next generation of electronics, with the precision that would be required to work at that scale. It looked to me like it was going to be chemistry, and more specifically, it looked like it was going to be biochemistry. That was a major motivation. As in biology was going to build the chips. Yeah, that's right. Was it called synthetic biology at that point? No. We called it cellular computing. I see, okay. No. When did it start getting called synthetic biology? Probably 2003 or so, I'm guessing, somewhere around then. Is that right? When did you arrive on the scene? I showed up at MIT in the fall of 2002, and I think you had maybe just figured out the name synthetic biology as an analogy to synthetic chemistry. Yes. The idea is you use chemistry to synthesize things, we're going to use biology to make things, and so that's why. The unique thing that came out of MIT's synthetic biology working group arguably was the idea of focusing on the underlying tools and technologies and trying to convert it into more like a mature engineering discipline, as Tom had seen happening in computers. Yeah, not just the tools, but also I think a very important aspect of it was the idea of standardization. Yeah. The idea that you could reuse components, that you could design them once and use them many times. What today we call our Codebase. Back then it was this concept of we had standard parts in other engineering, from screw threads to computer functions. Why can't we have them in biology? Barry, our CTO, you head up our technology platform development today. If you look back What do we have right? What do we have wrong? Right? Does it feel like a straight line from the MIT synthetic biology working group to Ginkgo today? Oh, absolutely. Yeah, absolutely. We nail it all perfectly. Oh, that's so laughable. Yeah. Next question. No, that's really interesting to think about. I think some general themes have remained really true, and we have followed through on those. I'm thinking about approaching the technology from an engineering standpoint has been true. I think bringing to bear the learnings and technologies from other disciplines, whether it be computer science or operations research or whatever else, electrical engineering, I think we have done a good job of bringing all of those themes and concepts into the way that we do our work. Leveraging robotics, leveraging software wherever possible. You can take a tour of the Ginkgo foundries without seeing all that. There's a lot of robots, yeah. There are a lot of robots. I think there are certainly things that where we haven't gotten as far as we would like, nor has the field arguably. I think it's a healthy way to think about it. More of a meta point there is that it's probably good for us to be careful about when we use analogies versus when we just are direct about the beauty and complexity of biology as its own thing, rather than trying to fit biology into prior engineering disciplines. Reshma, speaking of the sort of beauty and wonder of biology, right? What got you into it? How did you start with it? Biology itself, I fell in love with working in a lab at the University of Utah. Baldomero Olivera is a professor there, and he studies these venomous cone snails. Venomous cone snails. Yeah. Beautiful. They're amazing. Okay, I'll nerd out for a second. They're these little marine snails that live in coral reefs all around the world. Some of them basically spear fish, so they literally have a harpoon that they can spear a fish with and inject it with neurotoxins to paralyze it. Others catch fish with nets. The purpose of this meeting is to get the public excited about programming biology. These neurotoxins have now been used as pain relief and other sort of therapeutic drugs and as amazing tools for neuroscience. Anyways, I just thought these snails were super cool, and that is how I fell in love with biology. When I met Tom, I realized that we could actually program biology and take the next step. Yeah, cool. that was my journey. Well, Tom, you should talk about iGEM because that was probably the other biggest community-building exercise. What does iGEM stand for? The International Genetically Engineered Machine competition. The teams compete to do something cool, an experimental system that they build over the summer and demonstrate, come together in November typically, or October, end of October, and sort of impress one another. Show off. Okay, off. Okay, yeah about how wonderful- What was the winning project from the first year? I actually don't remember. I do remember because I was in that competition. Okay. Well, you see, this competition idea really worked. It was UT Austin. It was kind of cool. You put down bacteria on a plate, they grew into a lawn, and then you would shine light on it, and the ones where the light hit would change color. No. They made the first bacterial Polaroid. Oh. Which was okay. It was cool. I was a judge at that competition. They deserved to win. Yeah, they deserved it. How many teams were in it last year? Oh, I don't know, $350, something like that. Yeah, from all- From all around the world. Yeah, it's like thousands of students. Huge participation from China. Yeah and Europe. Yeah, South America. Maybe even South America. Yep. Yeah. Yeah, what I love about it is you go and you tour around, and everybody's so fired up about what they can do with biology. The beauty of the iGEM teams, to me, is they have no idea what will or won't work. They try all this stuff and, oh, surprise, some of these things that everybody else would have told them won't work actually do work. Yeah. I think one of the things is they're early enough in their education that they don't realize how hard some of these problems really are. They're willing to try things that you and I wouldn't have. This feels like us in 2007. All right. That's what I would say. It's like you just don't know any better. That's right. Then you're like, well, at least if I go off on this journey with people I enjoy being with, it's not going to be a miserable life, so let's give it a freaking swing. I thought there's much more to it than that, right? That's right. Naivete is your friend, I think. Naivete is your friend big time. I couldn't agree more. Lo, Ginkgo was born. Yeah. Well, I feel like that's the reality. Well, I guess, yeah. What'd you think when we came in your office, Tom, to tell you about Ginkgo? Do you remember that? Ginkgo. Well. Unnamed company. We didn't have a name yet. Yeah, we didn't have a name. It was called Ginkgo. We came into your office and said, "We're thinking about starting a company. Yeah, well, I think my first reaction was, "Can I join you? I think an important part of the logic was that academia is great for doing hopefully blue sky, high-risk research, and what we believed at the time was that what synthetic biology needed was engineering industrialization, and things that could better be done, arguably, in a commercial context than an academic context where. Yeah it's about publishing papers. I think at least for me, looking back, I think that was an important part of the logic about why taking what was essentially the same mission and moving it from an academic context into a commercial context would allow us to do something cool. Right? Yeah. I feel like that's always been true about Ginkgo. It's been sort of a mission. There was a larger mission and goal for it. It wasn't like, "Oh, I just want to build a company and flip it," or anything like that. Very clearly from day one, that wasn't the case with us, and I think the team that's joined around us as a result reflects that. Right? Like you're buying into Ginkgo, you're basically buying into now 500 zealots that want to make biology easier to engineer and are going to keep pushing that for the long run. I think it starts all the way back at that point in time, I think. Yeah, I think we've always had sort of a long-term point of view, I think quite a bit longer than a typical company in the space. I think by being a mission-driven company, we were optimizing on our mission above anything else, right? I think that's what let you tolerate a lot of pain in the early years, right? Yeah. We would do all sorts of crazy things, apply for every grant under the sun just to try to keep things afloat before we really saw traction. Yeah, I think we signed our first few commercial contracts in 2014. Yeah, thereabouts. sort of what led us to then have the confidence to join YC and take off from there. I think it helped to set the bit of what it means to be a fast-growing tech company. I think we had the solid mission fit. I think we had Tom's long-term vision that said, "Look, if we build into this and follow these technology paths, there's a big thing waiting for you. If that's true, you should just grow like a tech company." Right? That's what we learned at YC, right? It was like, if you lean into it and you bet on scale, and you have a business that benefits from scale, it'll pay off. Just keep betting. It's interesting, because I can't remember when that sort of economy of scale and build scale idea really took hold. Would you date it back to 2014, to YC? I think that's when we started seeing the Well, I don't know what year it was, probably two years later that Tom picked up on the fact that the output of the facility had been tripling the last couple of years, and our costs had been halving, and we started to say, "Oh, we should own that metric and actually meet it internally." That was all around that same time. It was around 2017, definitely not earlier than that, because we had about 3 years of that sort of Knight's Law progress under our belts, and it started around 2015. One of the things that I think was different about the company also was the idea that we should be building a computer platform for the technology really from day one. There was this realization somewhere along the line that what we needed to do for people was the whole project. We're going to program a cell for you like we program a computer, and what you're going to get at the end of the day is the finished cell. That suddenly meant we had to do all these things. Once we landed on that business model as being the right business model, the amount of technology and infrastructure that had to be under one roof was daunting. It was the right. I think our first principles view was, this is the right product to put out the door if you want to meet the mission of make it easier to engineer biology, well, sell people a programmed cell. Right? That felt great. Yeah. It just meant we had to build technology. Yeah 10 years. Right? The other thing that it mandated was that we would have to work on a lot of those projects at the same time. Yeah. If that was going to be our product, well, we would need to have a bunch of them. I think therein lies the core of the horizontal platform idea. Yeah. What that pushes you to do is to ask, "Okay, how can I work on diverse projects at the same time, and what does the platform have to look like to do that? This is the game we're playing, right? This is how I see it, and I just think it's new to biotech, right? I think one of the things about Ginkgo is we're a little bit outside the mold of biotech. We've taken a lot of lessons from Tom and semis. We've taken lessons from business models and app store economics and things like that, and we'll see. Well, I think amongst the founding team, and the way I describe it to people is on paper, the four of us, not Tom, but the rest of us sort of look identical. I feel like you could literally swap out our resumes for each other, and you wouldn't know the difference. That's accurate, yeah. I think what's happened with the founding team is that we've essentially speciated over the years, right? That's a great term. We all started as the same common ancestor, and then it speciated into our own niches in the company, and I think that was pretty key to us sticking together for almost 20 years now. I feel like we benefit also because the vision is very tight. In other words, it's a lot easier for us to push in our directions without getting off the rails, in part because all the way back to Tom, it's been a tight mission for so long. Having folks then who have that history, going back to the foundation of the field, then managing the company, that is such an unfair advantage. I also think that the trust that we've built up over time, and that speciation into special roles now, or into specialized roles, has also extended to the entire leadership team of Ginkgo, right? I agree, yeah. We operate in a way where we are very comfortable sort of trusting each other, pushing power and responsibility down in the organization, and I feel like we've sort of tried to bake that into the culture. In the leadership team, it was very natural to bring in other folks and trust them with large amounts of responsibility to make decisions for Ginkgo, because that's how we operate with each other. It's sort of just a natural extension of that. Yeah, as the platform scales up, I think it's just more and more true, right? That's one of the things I'm excited about as we're making the company public and the company's getting bigger, is just more folks invested in the success of the organization across the whole team. I think we're laying the groundwork for that culturally. I'm really excited about it. Austin, you spend a lot of time engaging with other startups in the ecosystem around Ginkgo. How do you think about it? How do you think about what's sort of coming behind us and how do we engage with them in a healthy way? Some of this, I think, comes down back to our painful start, right? Many years of scrounging for resources and trying to get started. I think our vision of making biology easier to engineer is, how do we not have other startups go through the same pain? Having gone through that ourselves, we understand sort of what those companies need and how we could provide those services to those companies. I think it'd be extremely rewarding if we can get to the point where companies are being created because Ginkgo exists. If we are enabling new companies, I think that would be a dream for me. Yeah. It's been kind of like a weird year for biology, a weird year and a half with COVID. I think there's suddenly this awareness that biology is powerful stuff, which has maybe been obvious to us, but I think, again, people take biology for granted, haven't noticed it as much. Here we're opening up. We're going to make biology as easy to program as it is to program computers, and we're going to open that platform up so that kids can do it, use it someday. How do we do it? How do we do it safely and responsibly? I think this is actually a topic that we've thought about even since the very beginning. Yeah. If you think back to our days at MIT, we had a lot of conversations about biosecurity, biosafety, how do we create a community around this technology that ensures that use is the technology overwhelmingly for constructive purposes. I actually kind of Drew a lot. Yeah seeding a lot of these conversations, both with us and with the community at large, right? Bringing a lot of non-engineers, non-scientists. Yeah. Yeah. We had anthropologists- Market scientists. Yeah. Market scientists. Yeah. artists, designers. Policy people. social scientists, policy folks. I think that's always been baked into even the origins of the field, and I give Drew a lot of credit for that. I think now at Ginkgo, as we're faced with like, "Hey, we have this incredibly powerful platform. We're potentially going to open it up to startups, to a broader set of folks, maybe ultimately to kids, then how do we continue to ensure that it's used for good, right?" I think baking in a cultural value both inside the company and without, around caring how our platform is used is super important, because these are not easy questions, right? Part of the reason why I think that's how we frame it, right? We care how our platform is used. Yeah We're not actually saying we have all the answers. We just care what the answers are. Yeah. What I'm excited about at Ginkgo is a culture of establishing that across the whole team, right? Because you end up with ultimately thousands of people caring how the platform is used. Their diverse backgrounds, their ability to sort of help us see that what's coming. You need a diverse community, right? I think we've learned from every other technology that if you have just a narrow slice of society who's developing and using the technology, then that bias is it to only benefit that narrow slice, right? Yeah. You need a diverse team of people who are building and using the technology if you actually want to see around all the possible corners and all the ways things can go wrong. who feel like they own the place so that they make wise choices about. Yeah how to do it that balance of growth and impact. Yeah, 100%. I'll ask our, sort of, I'd say the number 1 question I get from investors, which is, whether in our lifetimes we will see dinosaurs back. I'm going to ask for just a thumbs up or thumbs down from each of you on this question right now at the same time. Wait, are we giving thumbs up that it's going to happen? That it will happen. that it's a good idea? Thumbs up means that we will see them in our lifetime is the thumbs up. Something that looks like a dinosaur or literally. Yeah. It can look like a dinosaur. Yeah, they're not trying to get too technical here. Right. We're not trying to get back to. What about birds? Where are we on birds? Birds, I understand birds are dinosaurs, but everyone knows what they mean when I say dino. When I say dinosaur, it means something. We include fire? Is that the? No, that's dragons. That'll be a second one separate. Those haven't existed. You want, like, a. to my knowledge. scaly-looking thing that didn't actually exist? Yeah, it can have stupid feathers, but it needs to be big, and it needs to be. Like a brontosaurus. You want a brontosaurus. Okay, yeah, a brontosaurus. Do we have to be scared of it? Yes. Okay. Big enough where you're scared. Yeah, you wouldn't want it in a room with it alone. Okay. All right. Sorry, what is the thumbs up and down mean? Thumbs up means that we're going to have them. Yeah, they'll happen. In how long? In our lifetimes. Oh, okay. Austin's lifetime. All right, all right. Here we go. There should be a question of if we're going to extend our lifetime. Yeah. Okay, don't go down that rabbit. Let's not talk about it. We're in Boston. All right, 1, 2, 3. Yes. All right. Well, the last 20 years have been an absolute pleasure to build this with you. Excited for the next 20 or infinity with Austin. Really, thanks for the time, guys. Thank you. I'm super excited for our first Investor Day here at Ginkgo. I'm going to have a little bit of time with you up here at front before we dive into a whole bunch of different elements of the company, and I thought I'd use just a moment to give you a little bit of the architecture of Ginkgo, and highlight some of the key questions that I frequently get from investors, that I think are worth highlighting up front. The core idea behind Ginkgo is that you can program a cell, like you program a computer, because it runs on digital code in the form of DNA. It's A, T, Cs and Gs, not zeros and ones, but you can read that code with DNA sequencing and write it with DNA synthesis. If you can read and write code, and you have a machine that'll run it, you can program it. We've known that you got to hear just a fun conversation with me and my co-founders. This is an idea that goes back 20 years ago to when we met at MIT. What we've had to figure out in the intervening years are both how to build the technology to do that in a way that drives scale and value into the business, and then what's the right business model? How do you commercialize this idea of compiling and debugging genetic code? Let me drill in a little bit. On the technology side, the number one thing to understand that's different between computer programming and cell programming is that cell programming is a physical process. In other words, when I compile DNA code, I literally have to build a molecule. Like A, T, C, those are chemicals. I do polymer synthesis to build that piece of DNA and install it physically into a cell. Well, as a result, we need physical facilities to compile code. It's not just virtual, like on a computer. You'll get a tour of our foundry from our platform leads, and you'll see 200,000 sq ft of physical infrastructure, robotics, and automation. The key business implication of that infrastructure is it improves with scale. Just like Ford or Intel. The more of it you do, the cheaper it gets. That's one of the key competitive moats around the business is as our platform gets bigger, we can offer something more valuable to our customers. You'll also hear about it on the data side. As we do more cell engineering, we learn more. You'll hear from our head of Codebase about that, how we build up that data asset that also makes us offer a better product year over year to customers. That is the source of value at Ginkgo. Simple as that. Compounding technical scale. How do you harvest that value? We actually spent a lot of time thinking about what is the right business model for this, and one of the obvious ones would be, well, hey, use that platform, go make your own products. You have this great platform. Why don't you go become a therapeutics company or something like that? There's a lot of money in the therapeutics industry. One of the things we realized was that would be a mistake, because once you pick a narrow window of products, you end up building a smaller, less general platform. It's not as good as if you serve everybody and work on everybody's products. Importantly, we decided our customers are a lot better at launching products in these markets than we would ever be. Just in the last three or four months, we've announced deals with Biogen, one of the largest therapeutic biotech companies, with Corteva, one of the largest ag biotech companies, and with one of the largest flavor and fragrance companies in the world. In addition to new deals with startups in the cosmetics industry, and other new small companies pioneering applications for cell programming. We will never be as good at launching a therapeutic as Biogen or an ag product as Corteva, or we have our long historical relationship with Bayer. They are the product developers. What Ginkgo does is we basically provide a common horizontal platform to program cells and take that work off their plate. They don't have to have their own scientists doing it by hand at the lab bench. Instead, our robotics and automation, our data assets are available to them. That sounds good. Good value to the customer, improves with scale. How do you make money? The key big value capture for Ginkgo is in taking a piece of the value of those products. Think app store ecosystem. The big mobile phone companies spend a lot of investment making great ecosystem for you to be able to launch an app and make a whole bunch of money as a product developer in their app ecosystem, and they take a piece of that pie. Exactly the same business model we have here. We're going to take a piece, either through a royalty on the sale of that drug or that fragrance, or in lieu of a royalty, if you're a smaller company, we could take equity in the company. That value, that is the long-term value of Ginkgo. One of the key questions we get is, how do you think about valued at $15 billion, how do you think about justifying the valuation of the company? How is it ultimately going to be worth many more multiples on that value in the future? The answer is, the market for cell programs is going to dwarf the market for computer programs. These are the physical goods, food, building materials, medicines, all of the physical things in our lives ultimately are biotech products, and they just don't know it yet. Getting a small piece of that pie will ultimately really drive the overwhelming majority of the value here at Ginkgo. We do get paid also. We have foundry revenues. People pay us as we do the work for them. Ultimately, the long-term value is actually in that sort of app value capture, long-term value share, and that's a key thing for investors in the company to really understand. That's the kind of investors we're looking for, are people that understand that long-term opportunity for Ginkgo in that area. Finally, I'll mention, we've been doing more and more work in the area of biosecurity. This is something that's actually really important to me. As our platform gets better and we make it as easy to program cells as it is to program computers, doing that safely and responsibly requires biosecurity. Just like we need cybersecurity for computers, you're going to need biosecurity for cell programming. What's fortunate for Ginkgo is it's actually turning into quite a nice business that's growing quickly. You'll hear from that team as well today. Really excited to welcome you here to the Investor Day and enjoy the show. One of the questions that I get most frequently from investors, once they feel like they understand a little bit about cell programming and what that's going to do for the world is, okay, but what is it that Ginkgo actually does in the foundry? What is the work that you do? We figured the best way to help explain that was to just show you directly, to walk you through the foundry. We'd obviously love to have you in Boston in person to walk through, but in the meantime, I'm going to ask Barry to take you through a video tour of the foundry and introduce you to some of our leaders across software and automation who help make what we do in the foundry possible. He is also going to introduce you to Patrick Boyle, who is our Head of Codebase, which incorporates all of the biological data and parts and strains that we use, in conjunction with our foundry, to enable projects for our customers across the entire cell programming landscape. Barry, take it away. You've already heard a lot today about the foundry, but you may well be wondering, what do we mean when we talk about our foundry? First of all, the foundry is one of the key pillars of our platform that we've been building at Ginkgo over the last 13 years, and I'm really excited to be able to show you some more of the detail about that today. Ordinarily, I'd love to be bringing you on a physical tour of our foundries and showing off the people, the technologies, the instruments, the robots that we've been developing over the past number of years. Today, I hope to still be able to bring you inside the foundry as best as we can and expose you to all those incredible technologies. You're also going to get to hear from some of my wonderful colleagues. You're going to hear from Kristen Tran, who is our head of automation. You're going to hear from Jamie Cho, who is our head of software. You're also going to hear from Dave Treff, who is our head of DevOps and IT. You're going to hear about how all those different disciplines and technologies come together to power the Ginkgo foundry. One of the first questions that we always get from folks is, what is our foundry and what do we do in there? That's a very reasonable question because foundries and this concept of programming biology is foreign to almost everybody who hasn't been doing it for 20 years, like the team at Ginkgo. I'm going to start there, and let's talk a little bit about, well, what actually happens in our foundry, and what is the overall process of programming biology? For us, it typically starts with an interaction with a potential partner or customer, where we jointly develop the concept of a cell program that will help that customer make a new product or a better version of an existing product. Through those conversations, we'll develop a specification for the cell program that we're going to build with them. Once we've reached that agreed-upon specification, the work is turned over to our cell designers, who will refine and develop the concept and the specification of how we're going to make that cell program. They'll continue to develop that using Codebase from our collection, as well as nature's code base, the cells and genetic assets that are out in nature. Our designers will bring those different pieces of code base together to develop a detailed design. We put all of our best learning, accumulated over many cell programs, into those early designs. Once we have those detailed designs that are specified at the level of DNA sequences, all in a computational manner, those designs are handed over to our DNA synthesis and our build teams. Their task is to take those conceptual and computational designs and turn them into reality in the lab. That starts typically with DNA synthesis, where we print out the new DNA sequences that our cell designers have come up with. Once we have those new DNA sequences, our build teams will take those DNA sequences and put them into the genomes of cells that we want to work with. We will finally, at this stage of the process, use sequencing technology, DNA reading, in order to make sure that we've made all of the right modifications to the DNA inside the cells that we're working with. Now we have a real-life cell in the lab that is the physical instantiation of our designer's concept, and now the next question is: how does that cell perform? To answer that question, we hand those newly programmed cells over to our test teams, who bring together a wide array of different capabilities that we use in order to understand how those new cell prototypes that we've been building perform. Do they meet the customer's specifications? Do they nearly meet the customer's specifications? Do we still have a lot of work to do? Those test teams use technologies like mass spectrometry, liquid chromatography, high-throughput screening, next-generation sequencing in order to understand what's happening inside the cells that we've built and to measure the performance of those cells. Typically, we will find that some of those prototype cells perform really well, some perform so-so, and some don't perform well at all. All of that information across many different designs, we'll integrate together and use it to come up with a new round of designs. We will iterate through that process of designing, building cells, testing how they perform, until we meet the customer's specifications. A lot of the technology in our foundry is oriented towards making that process as efficient as possible and investing in the tools and technologies that allow that process to happen faster and with a higher probability of success than has been possible previously. When you see inside our foundries, and when we're able to bring you physically to our site at Ginkgo, what you're going to see is, first off, what looks like a lab, but also a little bit different from a normal lab. That's because for our foundry to be efficient, what we've had to do is start with a conventional lab and then bring a lot of concepts in from manufacturing, from operations research, in order to build scalable, high-throughput, automated processes that allow us to more quickly and effectively program cells for our partners. What you will see in our foundry is not the typical row after row of benches with a scientist working at each bench. You will see some of that in our foundries, but what you will see more and more of is sophisticated instrumentation, robotics, liquid handling instruments, and a wide array of sophisticated and complex machinery and instrumentation. That we use to amplify and multiply what our scientists are able to do in our foundry. We bring the best in robotic and software automation together with the unique skills and insights that humans have in order to be able to program cells more effectively with a higher probability of success than would ordinarily be possible. What you'll hear in the labs, what you'll hear in our foundries, is you'll hear relatively loud hum of equipment, of robotic arms, of instruments moving liquids back and forth. You'll hear that hum of activity that is largely consisting of robots and instruments scaling up and powering the work of our foundries. It's essential to our foundry that we be able to run many, many designs or prototypes through every step of that process in order to minimize the overall timeline of a project or a cell program to develop a cell that meets the customer's specification. Not only do we want to be able to look at thousands or tens of thousands of prototypes for every cell program, we also want to be able to work on many cell programs at the same time. Today, we work on tens of cell programs in the Ginkgo foundry at any point in time. In the future, we want to be able to work on hundreds of cell programs at any given time. When you put all of that together, you find you have a complex, multi-step process of designing, building, and testing cells. You want to be able to do that process at scale with tens of thousands of prototypes within each program. We want to be able to do many programs at the same time. The result of that is that scale, logistics, operations, the throughput of our foundries, becomes really, really important. Those robotic and software automation paired with what humans can do means that overall our foundry can do way more work and way more cell programs than would be possible by people alone. This really leads in nicely for you to hear from Kristen Tran, our head of automation, who will tell you about all of the incredible robotic automation that we use throughout the Ginkgo foundries. At Ginkgo, we try to automate as much as we can. We start with small-scale automation, really accessible stations for scientists and engineers to walk up to, really easy for them to start using. Once we actually start scaling up, we can actually start stringing these operations together seamlessly on an integrated work cell, which really allows us to really take off on that scale. It really allows the scientist's output to increase 10X, 100X, 1000X, and really, that's our goal. We want to maximize that. We want to automate as much as we can, and really whatever they're going to let us do, we'll try it. Instead of having a scientist go from station to station, we have this centralized robotic arm that's going to handle all of the samples, and it's also going to record everything, and it's going to produce that valuable data that we need for our cell programs and for our Codebase. What my team and I do as automation engineers, we like to look at what the physical activities people are doing in the lab. We're engineering cells, and that requires a lot of precise handling of samples. What my team does is we take these activities in the lab that scientists are manually doing, such as pipetting, and we actually make a custom integration. We integrate these in a work cell. With that custom integration, not only can we really control the timing and the precision of the activities, but we can actually track everything within our software so that all of the data can be collected, and all of that can be reused for future engineering projects. For automation, in addition to automating manual processes that a scientist would normally do with a bench, we can actually go beyond human capability and miniaturize certain reagents and certain reactions. An example of this is with our acoustic liquid handler that can actually dispense nanoliter droplets of liquid. With one of our core processes, we were actually able to miniaturize the reaction 50x. In addition to that, it increases the speed and the output. Our scientists are able to produce hundreds to 1,000x more output that they can trust and that they're able to go back to and reflect and really iterate on their process and on their design. I think there is a misconception that we're trying to replace the activities that certain people do in the lab. The way that we look at it is we really want to augment the ability of a scientist. We want to increase their ability to perform experiments in the lab. We want to give them the peace of mind that it's going to be done faithfully, that it's going to be done with high precision and high quality. With these different scales of automation, they can actually increase their output and create more valuable data for them to iterate on their process. Something that's really special about Bioworks5 is, in addition to the large scale that it provides, there's actually all of this really interesting new technology where we're able to sense the success of each operation. You can tell whether or not an operation failed, was successful, and record it. We use different types of sensing technology, including acoustics, light-scattering sensing, light proximity sensors, and pinhole cameras. What's really great is we implemented this in Bioworks5 in our latest facility, but we can actually take that technology and apply it to all the different scales of work that we do throughout the foundry. All of this technology that we're developing in Bioworks5, we always have an eye on, well, where else can we leverage this? What else can we automate? Where else is this going to be valuable for us? Really, that's how we develop our automation. We are always thinking about it in like, what are these new tools, and how can they be even more helpful to Ginkgo and to our scientists. A lot of resources went into building Bioworks5, but something that's really unique about the automation at Ginkgo is that we have our own custom integration and software integration. We work really closely with our colleagues in digital technologies. We have a great relationship, what we do is we try to think like, how can we leverage all of that technology that's already out there and make it really useful for Ginkgo, and leverage it in a flexible way to apply to multiple programs. Our infrastructure through custom automation and custom software can actually be applied throughout the foundry. It can be applied for different cell programs. It can be applied for different organisms, and it's kind of amazing the diversity of scientific processes that can be performed on the same set of infrastructure. I think we're only really able to do that because we have this in-house development team, both on the automation side and on the software side, as well as the DevOps side. We all work together really collaboratively to make sure that that integration is as seamless as possible, and we're constantly thinking about how can we scale, how can we be more efficient. We always have to pair that with flexibility, which is always quite the challenge, but it's a really fun challenge. All of our engineers at Ginkgo are really interested in being the ones that solve that problem, and it's been pretty amazing to see what the teams are capable of. We get to work really collaboratively with our engineering partners to create new technology, to create new capabilities on existing robotics. In addition to that, sometimes we even have custom partnerships where we are able to create something truly unique for Ginkgo. Bioworks5 is a really prime example of this, where we leverage existing high-throughput manufacturing technology, but we are able to apply it to the synthetic biology space. The process of designing DNA, which must seem like a very abstract concept, really involves using computers to go from ideas down to detailed DNA sequences that can be thousands or tens of thousands of letters of DNA long. Because those DNA sequences are very long, and because we'd like to be able to design many of them at the same time, we've built a suite of design tools, computational design tools, that our designers can use in order to come up with the best possible DNA designs for every cell program they're working on. When you see our designers working, what they're really doing is interacting with software tools, many of which are proprietary, that allow them to stitch different pieces of DNA together computationally in a quick and efficient way, almost as easily as you can drag and drop objects in a software package. Those objects are actually DNA sequences that we are subsequently going to print out. Once we've done that computational design process, which really looks almost like an architect or an engineer interacting with computer-aided design, then we move over into the lab. DNA printing, again, that's a very abstract concept. Does it look like a desktop printer that you might have at home? What does it look like? It's a lab operation, but it uses increasingly advanced, sophisticated technology in order to make the operation of printing DNA as cost-effective and reliable as possible. We work with partners such as Twist Bioscience, to use their proprietary technology for printing out, literally using inkjet printer technology to place individual DNA bases together in the right sequence so that we get the new DNA sequence that corresponds to what our designers have developed in our computer-aided design tools. DNA printing really looks like a very, very complicated printer. Thereafter, once we have short printed DNA sequences of, say, 100 bases long, we next need to stitch those 100 base sequences together into 1,000 or a 10,000 base sequence of DNA that encodes a gene for a protein or a set of genes for a metabolic pathway. That operation, stitching those short pieces of DNA together, is again a lab operation, and it looks like a lot of liquid handling. It looks like a lot of moving small volumes of liquid from one source to a destination and mixing lots of different liquids together. That's a process where we rely very heavily on liquid handling automation to scale the amount of DNA molecules that we can build at the same time for many cell programs. Once we put that DNA into the cells, that process, again, really just looks like a liquid handling process. We take a little tube of cells, we take a little tube of DNA, we mix some of the DNA into the cells, we treat them with some heat and some chemicals, and that helps the cells take up the DNA inside them and integrate the new DNA into the genome of the cells. Once we have that operation done, we grow the cells. We start with a tiny tube with just a handful of cells in it that have the new DNA, and we allow those cells to grow so that we have millions or billions of copies of that newly programmed cell. Those cells grow in either small bioreactors that look like miniaturized versions of fermentation systems at a brewery, or it happens in plates that have hundreds of individual wells in them, so that we can grow many different populations of cells or many different prototype cells at the same time. Once we have those cells grown up, we have lots and lots of cells, then the next step is often to sequence them. DNA reading, that's the process by which we read all the DNA that's in the cell and make sure that we've put the right DNA into the cell. That's an operation that happens on very sophisticated instruments, and the machine streams data to our proprietary databases and our data lake here at Ginkgo. That data contains all the DNA sequences that are found in those cells. That's, again, a computational or a digital process. Once we know that those DNA sequences are right, then we move on to measuring the performance of those cells. What that looks like is taking the cells, observing them via instrumentation that can, say, look at the levels of particular molecules or identify particular molecules that are being made by those cells, and really allow us to look inside the metabolism of the cell or the behavior of the cell, so that we can understand how its performance matches up to what we expect. When you see our testing operations in our foundry, what you'll generally see are collections of instruments that are 24/7 taking small samples from a culture of cells and chemically analyzing those samples to understand what's in there, so that we can understand how those cells are performing. You'll see in the Ginkgo foundries, there is an enormous amount of work happening across many different cell programs at the same time. All those physical operations, all that work that's happening, is very hard to track unless you have really good software tools to manage the operations of the foundry and also to collect all of the data and metadata that is being produced across all of those operations, and bring all of that data into a location, like a database, and into a format that our scientists can analyze what's happening and decide what to do next. We've invested an enormous amount of energy and time over the last 12 years building proprietary software tools that are completely critical to the operation of our foundry, so that we can operate at a scale that would be hard to operate at otherwise, and at a level of quality and sophistication that would be impossible without dedicated software tools that were built specifically for our operation. Who better to tell you about that than our Head of Software, Jamie Cho. The software we build is uniquely tailored to Ginkgo's foundry's needs. Our software team has a lot of the same traditional skills that you see on other software teams. They know how to program in Python, in Ruby, Rails, and React, and all of those skills. What's really special about our team is we are all passionate about biology, and in fact, our mission is to make delightful software that makes biology easier to engineer. Ginkgo's unique focus on engineering biology at scale means that we have to build a software platform that can handle that level of scale. We have powerful workflow systems that allow us to generate and execute really complex laboratory workflows for actually manipulating that DNA and transforming it into organisms. This is a seamless process that the software enables. Likewise, we have built the platform so that it can actually pull data automatically from instruments and analyze that data, feeding it back to the beginning of the design, build, test, ferment cycle. Our laboratory workflow software actually keeps track of everything that's happening inside the lab. A lot of these workflows are automated such that when instruments are processing the data and actually return the data, we're able to analyze it automatically and refer it back to the originating samples that generated that data. This all happens seamlessly. Integration of all of those different components is really important when you're dealing with data sets as massive as the data sets that we're generating every day. This degree of integration really enables us to keep track of what's going on and then feed that information back into the current design, build, test, ferment loop. What's even more exciting is because we can keep track of all of this stuff, we can also apply it to future programs and get a head start on those, and this is what we call Codebase. Not only have we had to build a huge amount of infrastructure in our labs, in our foundries, with equipment and people and processes, the same applies to data. We're generating a huge, massive amount of data across our operations every day. That data is being managed by our software, our proprietary software, it's really all built on a layer of digital infrastructure that was built specifically for our foundry. You're going to hear today from Dave Treff, who's our head of DevOps and IT, about that digital data infrastructure that we've been building. Usually companies that are big build big but inflexible, slow-to-change infrastructure. Small companies will build smaller and flexible, much more flexible, much more changeable infrastructure. At Ginkgo, we build big and fast and very changeable. I have to change stuff constantly. One of the things that we do is everything that we buy, for example, let's say we're buying some network equipment, we look at each piece of network equipment that's in the whole network or any computers that are in the foundry or anywhere, and we look at it and go, "Okay, we're going to buy this today." Can we make it go faster next year? Can we upgrade it so that it has more capacity for more data? Because of, primarily, it's Knight's Law. If I was asked to do a three-year plan, for example, we do 4x every year, so it's 4x this year, it's 16x next year, it's 64x year after that. I have to have 64 times, or I have to plan for, anyway, 64 times the amount of network, the amount of compute, and the amount of storage that's available. I've never worked anywhere like that. This is not normal. Well, it's really fun, I will tell you that. This is the most fun job I've ever had in my life, and you look at me, I've had a few jobs. What we do is we just stay ahead of the scientists. We buy bigger pipes, we buy bigger equipment. All of our software we make, and we have to make it because it doesn't exist. The way we design our networks is obviously for things like resilience and I mentioned upgradeability and flexibility and blah, blah, but we also have, there's probably, I don't know, maybe 12 different types of data that come out of these machines. We have to handle all of them, and we have to get it to the software that we write, which is all bespoke, and then we have to shuttle that around, and we have got to store it, and we've got to make it so that Patrick and his folks can find it, because that's the Codebase. We have built a custom network with lots and lots of security controls in them that go all the way down to the bit level. There's security on the wire, there's security on the software, there's security in all the network switches. One of the other things about that is, that's really hard to do. You can't just do that. You can go out and buy it, but do you trust it? No. You really want to do it yourself. What we did is we hired a couple of ex-military three-letter agency people who have a lot of stories they can't tell us, and they have been designing and helping us build our network and all of our processes to be secure. What that does is obviously gives us a lot of peace of mind. Other companies outsource all that stuff. We want to keep it in-house. The output of our foundry is a new cell, a programmed cell that does what our partner and our customer needs it to do. That may not be all that they need. Sometimes, our final product is the programmed cell, and we're able to hand that off to our partner for commercialization and production. Sometimes, that cell needs to operate in a manufacturing process that we can help develop, perhaps in conjunction with our partner, or perhaps we do the work to develop that manufacturing process. Sometimes, what our customer or our partner really needs is just a final product. They need a compound, they need a molecule, they need a protein that they can use for perhaps their application testing or to go directly into sales channels. In those cases, Ginkgo's product is the cell, the process, and whatever that cell is intended to make. We can help the partners close the gap from the newly programmed cell that we've developed for them to their final product. We have those capabilities across our foundry and across our locations. A core premise of our foundry is that most cell programming projects follow a conceptually similar workflow. We've already talked about it, designing cells, building them, and testing their performance, and iterating through that loop. That insight means that we can build a general-purpose foundry that runs that general workflow for many cell programs at the same time. Why is that helpful? It's helpful for one very important reason. By running many cell programs at the same time, we unlock economies of scale. We're able to make sure that our foundries are at a higher level of utilization. Each individual piece of equipment is at a higher level of utilization so that we can make better use of fixed costs, or capital investments, and amortize those expenses across many cell programs and many operations. By working on many cell programs at the same time, we're also increasing our learning about how to do this process better. We're increasing the number of code-based assets that we have available to us that we can then use to make subsequent cell programs easier, as you'll hear later from Patrick Boyle. By working on many cell programs at the same time, we are able to reduce the individual costs of any given cell program. By doing so, we can increase the probability of success of those programs. We can reduce the cost of those programs, and that's value that we can offer to our partners. By working on many cell programs at the same time in our foundries, we unlock economies of scale, which makes the overall process better. By doing so, we then get to work on more cell programs at the same time, and there's a virtuous cycle there where more cell programs translates into greater economies of scale and better value for our partners. You can really think of the Ginkgo foundry as being a combination somewhere in between a lab and a factory. That's why we don't call them labs, we call them foundries, because we wanted to differentiate them from a conventional lab. Why foundry? Well, we're using the term foundry that was popularized in the semiconductor industry, where a foundry is really a chip fabrication facility that relies on very sophisticated equipment, very complex processes in order to be able to make an incredible product, a semiconductor chip. We thought that was a great inspiration for what a cell-programming lab of the future could look like with investment. That's why we call them foundries. One other reason why we like to make the, or draw the connection to the semiconductor industry is because we've been greatly inspired by Moore's Law, the observation that over more than 30 years of development in the semiconductor industry, the complexity or the sophistication of semiconductor chips doubled roughly 18 months. It did so by virtue of investments in the foundational tools and technologies of making semiconductor chips. Our belief, the premise of Ginkgo, is that with investment in tools and technologies, we can see a similar compounding improvement in the technology and in what we are able to deliver to our partners, as was observed with Moore's Law in the semiconductor industry. You may think that that's speculation. We believe that we are seeing that trend happen. We can empirically track the operations of our foundry. We can track how much work we're doing, we can track how much it costs us to do that work, and we can observe trends in how that amount of work and that cost of work is changing over time. What we're incredibly excited about is that over the course of the last five or six years, we've been able to see an exponential improvement in the amount of work that we do and an exponential reduction in the cost of that work on a per-unit basis. That concept of exponentially increasing output from our foundry and exponentially decreasing cost to do the work, we call Knight's Law. It's a nod to Moore's Law that you've heard about. It's also a nod to my co-founder, Tom. Knight's Law at Ginkgo is really the result of an enormous number of people's hard work over many years, and if we want to give recognition to one person who helped inspire so much of that work, we couldn't come up with anyone more perfect than Tom. The reason that we're able to maintain Knight's Law, and the reason that we expect that we're going to be able to maintain Knight's Law for many years to come, is because we're constantly evolving the technology and the tools and the operations of our foundry. We bring in new technologies that allow us to reduce variable costs. We bring in new processes that are more efficient, that save steps, that can operate at higher throughput. One particular example of that that I want to highlight is advances in being able to combine many prototypes together in a single well or a single tube. Instead of needing to dedicate 1 tube per prototype, in which scenario our scale is limited by how many tubes we can push through the foundry every day, by combining many prototypes inside a single tube, and we can, in some cases, combine hundreds of thousands or millions of individual prototypes in a single tube. That really unlocks incredible new levels of scale and throughput through our foundry. We call that one multiplexing. That's just one of the kinds of technologies that we're, on an ongoing basis, introducing into our foundry. What that means is what we've been showing you today is the Ginkgo foundry of 2021. We really look forward to seeing you again soon, when we'll be able to show you some of the new technologies and operations that we're bringing into our foundry and are helping to drive our ability to program cells. I've been really fortunate to be part of the Ginkgo journey for nearly 5 years, and in that time I've seen 1 foundry go to now just recently opening the fifth foundry in the company at a scale that just, quite frankly, blows my mind. What the team's really been able to do is take all of the best of the life science technologies that are out there today and put them together in such a way to create an unprecedented scale, and you can see it as you walk through the different foundries, from the first foundry to now the most recent, highly automated fifth foundry. When I sit and walk around the foundry and talk to people, I just get blown away every time because I think about the implications of what this could be and how this can change all different kinds of markets and create all kinds of different opportunities for people everywhere. Codebase is a term that we've borrowed from the software world. You may have heard people talking about what we do at Ginkgo as programming DNA. We have DNA sequencing, which is the ability to read DNA synthesis, which is the ability to write DNA. Put those two things together, and effectively, you're writing code. Codebase in the software world is really a way of thinking about what are the things that we've learned over the course of writing software programs that can be repurposed and reused for writing new programs? A programmer today working on a new application would say, "Let me check out a library or a module from this code base to build a new application." They're not writing every new application from scratch. There are lots of tools available to make that easier. What we're trying to do at Ginkgo is basically build up all the experience that we have from doing all these programs, is saying, what are the biological programs from previous work that we've done, and make them available to our programmers to use in subsequent projects, so that we're not starting each new project from square one, but can start on a basis of reusable biological assets or code base that we can put into new programs. The really cool thing about biological code base is that it starts with nature. Unlike every other engineering or programming discipline, biology has actually been designing new things for 4-plus billion years. The idea is we can actually start by looking into nature to look at genetic programs that have been produced via evolution as our starting point. One of the interesting things about biology is that there is a lot of digital information stored all around us. There's much more biological information out there than you may be aware of. For example, you may know that you have a trillion cells in your body. On top of those trillion cells, you also have a trillion bacteria living in your body. Think about just the density of information that's encoded in all of those organisms. Another example for this is soil. You may think of soil as just dirt. Soil to us is an interesting place to look for new genetic programs. To give you an example, we had a project that involved chemistry in the soil where we decided to sequence some soil to find new genetic activities. Take 50 milliliters, so that's about a shot glass worth of soil, run that through a sequencer. What you find, and what we found, is you identify 30 gigabases of new DNA information. A base pair is about a bit, that's 30 billion bits of new information. All those bits represent potential new genetic programs that we can use in different contexts. Multiply that times the rest of the world, you can understand that 4 billion years of evolution has created a lot of biological diversity, and therefore genetic programs that have been invented by biology that can then be identified and developed here at Ginkgo to build the next genetic program. Every time we do some sequencing like that, we're looking for new genetic functions. We test those in our foundry, and as we characterize those functions in the foundry, we record that digitally so that we can go back and reuse those genetic parts later. code base at Ginkgo really benefits from and exists because of the foundry. Effectively, you can think of the foundry as a way to do scalable experiments. Really the scale that we have in the foundry allows us to collect so much information. It wouldn't have made sense to try to record information in this way until we had this method using a foundry to systematically create thousands of data points for every project. Today we've done more than 10 million strain tests, That information can be used to make sure that we're progressively making better decisions when we're designing new projects. Today at Ginkgo, we have certain programs that have looked at 30,000-40,000 genes. We're taking more shots on goal, iterating through more designs, that we can more rapidly engineer a working and functional organism for that customer. That's what the foundry can do. Codebase is important because we want to take all that information that we're learning from that one project and apply it to the next one. You can think about, as we grow foundry capacity year-over-year, I want more and more of that capacity to be pointed at brand-new things. Like doing projects that we've never done before, working in enzymatic pathways that we've never worked in before, because the Codebase knowledge that we're building up means that we don't have to repeat some of those same experiments that we've done previously. The cool thing about biology is that given that biology all evolved from a common ancestor, a lot of biochemistry is shared across a huge diversity of products that are made by nature. That means we're progressively learning more and more about what nature can do. Each new project will borrow more from our preexisting Codebase, that's like characterized genetic parts and programs that we've done before, which frees up even more foundry capacity for all the new stuff we're doing. It's a virtuous cycle where we grow foundry scale, collect more data, and can make better use of that foundry scale on the basis of the data that we've already collected in our Codebase. Another way to think about Codebase is how many different sequences do we sift through when we're looking for a new genetic function. Today, we have a database that includes about 3.4 billion sequences collected from the broader world. These are sequences that have been collected by all of the biological community and provided on public databases, and then we have another 400 million sequences that we've collected over the years that are proprietary to Ginkgo. That gives you almost 4 billion sequences to play with. Again, what I find exciting about that is sequencing, as you may know, is getting cheaper and cheaper and more scalable each year. The cost of sequencing has fallen a millionfold over the last 20 years. Ultimately what that means is in terms of looking for new genetic sequences and new genetic code, we're really just getting started, and those hundreds of millions of sequences that we have today represent a small sliver of the sequences that we'll be using a few years from now to identify new gene functions. In many ways, Codebase is a literal parts library. We have genetic sequences that we have in our databases that correspond to actual DNA sitting in a freezer that an engineer can put to use in a new project. The data about those parts, the performance data, is what helps us make good decisions there. Ultimately, what's cool about Codebase is that it is physical. It is genetic sequences that can be repurposed. It is organisms that we've used across a large number of programs. That ability to identify new genetic parts out in nature and then put them to work in our foundries is one of the things that I'm really excited about because as our foundries grow, so does our ability to identify new genetic functions and learn from nature. Ultimately, what we're trying to do as engineers is making sure that we're learning from the 4 billion years of genetic experimentation that have already happened ahead of us. That's a tremendous resource that you just don't have in other engineering disciplines. We actually can learn so much from what nature's already done for us, and we finally have the tools to do that. How does Codebase benefit our customers? We have 2 different types of customers. Many of them actually are cell programmers in their own right. They've been engineering biology for many years. They have deep expertise in their organisms and in their programs. Again, they've been very focused on a certain set of products. What CodeBase offers is saying, "Here are all the genetic parts that we've looked at over the course of doing dozens of different programs," probably working on organisms and market verticals and applications that have nothing to do with what this customer is working on. Yet, because biology is really cool, we often find functions that can be repurposed for those customers. They're automatically benefiting from the dozens of programs that we've performed on day one. The other type of customer that we work with, these are product companies. They're really focused on developing compelling new products with biology. They're interested in formulation, generating new materials, basically trying to get products to consumers. What CodeBase offers them is they don't need to build out deep expertise in terms of what genetic design to use when trying to overexpress a new gene in a new system. They can work with us and we can say, "Your product resembles another project that we've done before. Therefore, we can start with this host organism that produces precursors for your project," or, "We can start with this host organism that's very talented at producing protein. Here are genetic approaches that have worked before. We can apply that to your particular program." Ultimately, for those customers, it means they spend much more of their time thinking about how to make their products rather than trying to think about the organism that makes their products, which is really our job. How does Ginkgo as a horizontal platform differ from the traditional way of engineering organisms? Many of our predecessors in this space would have focused on a very narrow set of products to produce. Imagine that you're starting a new biological product company today. If you didn't know that Ginkgo existed, what you would probably do is you'd go out and you'd hire 20 PhDs. They'd all work at the bench. They'd be very smart, come up with good ideas. A lot of person-hours of work would go into engineering a small number of engineered organisms. If you're lucky, you'll end up with a product at the end of that. At Ginkgo, what we're doing is instead you have a five-person team because they're making use of the foundry to do most of their work. They're starting from a point where they can, say, start with an existing protein expression strain that we've already developed. A lot of the initial work you would do just to get started has already been done. The know-how and approaches you'd use to leverage the foundry to look at thousands of new prototypes to rapidly optimize your strain, those are lessons learned that we've incorporated across dozens of projects. Ultimately, what we offer to customers who are trying to start new programs, create new biological products, is that they don't have to assemble those 20 PhDs. They don't have to build all of that institutional knowledge that will only live on in a single product. They can benefit from the institutional knowledge that we've collected across dozens of programs. One way that we're thinking about CodeBase is how do we actually package CodeBase as more understandable, both for our cell programmers but also for our customers? One organizing principle that's been really useful in software are what are called SDKs. That stands for Software Development Kits. An SDK will give you the tools to program in that language. It'll give you some example libraries, some code base that you can use to build higher-order programs, and also give you documentation. You put those things together, and a new programmer can get up to work quickly working in a new programming language. We're trying this out at Ginkgo, calling them CDKs or Cell Development Kits. Effectively, what a CDK is for Ginkgo is taking an experienced organism that we've used across a number of different programs, so we know that it has robust performance. We know it grows well in a fermenter, works well in our automation and our foundry, so the robots can work with it. Importantly, we also have tools. Our foundry tools can be applied to that organism. Combine that with documentation, you basically have a platform that enables us to help our cell programmers get up and running quickly with a new program. For example, with the Dyadic organisms that we're bringing over, these are filamentous fungi. What we're doing is we're building a fungal CDK, which will basically take those organisms, make sure that we have foundry tools to do all the things that we can do in the foundry with these organisms, and use that to build out a number of different programs focusing on protein expression and enzyme expression. Ultimately, what that does is it creates not only the playbook for executing these types of programs, but it also builds out the tools and documentation. Again, leveraging hard-won lessons from software to say, "Let's make sure that these projects are repeatable and that we never make the same mistake twice on a program." CDKs are just one organizing principle for that. What's exciting about Codebase is that we're just getting started. We've accumulated more than 10 million strain tests since we've opened our foundries, and each of those strain tests generates data that helps us inform how we should use our foundries better. Ultimately, you've probably heard of Knight's Law, and that means that year over year, our ability to generate data continues to grow. Really, we're just learning how to collect and catalog that data in better and better ways. That's really where we start to see the benefits of these dramatically falling cost curves in DNA sequencing and synthesis. It's not just about reading and writing code, but learning from that code. If we're able to learn at the same rates that we've been able to improve the underlying technology, biology is going to get a lot more easy to engineer over the next few years. My name's Claire Laporte, and you've just heard about foundry and Codebase from some of the other folks here, and I'm here to tell you about what that means from an intellectual property standpoint, how we protect it, and what it means for our customers. I came to Ginkgo in 2018 after 28 years at a law firm. I was doing patent trial work, and I also advised little companies that were getting ready to go public or get acquired, deal with their intellectual property problems. I came to Ginkgo to develop a strategy for the IP of this rapidly growing company and to figure out how to fit IP into the unique situation of Ginkgo. Ginkgo is like a giant invention factory where literally hundreds of brilliant ideas are made every single day. The question is, what do you do to protect all of that? You can't patent hundreds of new things a day. That would take an administrative empire, which is certainly not an efficient way to run a company. We protect most of our intellectual property with trade secrets. Maybe I should just back up and talk about the difference between patents and trade secrets for a moment. Patents are very important for a lot of biotechnology companies especially. They're a government-granted, limited monopoly that lasts for about 20 years after you apply for the patent. To get the patent, you have to make a lot of disclosures, explain your whole invention, and then when your patent expires, that knowledge is dedicated to the public. Whereas a trade secret is something that is intellectual property because nobody knows it, and you never disclose it. They never expire, but they don't add to public knowledge. The amount of work that is required to get a patent is very, very expensive. As a matter of sheer volume, because of the massive number of inventions made at Ginkgo every day, we are focused mainly on trade secrets. We also have between 50 and 60 patent families and many other starter patents, essentially, that have not yet matured into families, but will at some point. Just to step back and explain what that means, a patent family is essentially like a seed. You make one disclosure of what your invention is, and then you can use that to obtain patents all over the world, in China, in Europe, in Japan, in India, in the United States. Each one of those patent families essentially represents a group of related patents. From the patent families that we have so far, we have over 200 issued patents and also a very large number of patents that are pending and are still undergoing examination in national patent offices all over the world. We have a bunch of them that are very much at a starter stage, what are called provisionals, and those will mature to be patent families at some point as well. When Ginkgo makes a new invention, a lot of times what that means is that design engineers or protein engineers will come up with designs for literally thousands of possible proteins or enzymes, biological parts and pieces that can perform a particular task. They'll use all their knowledge about biology, our Codebase, to come up with that large set of candidates, which then through our foundry, we're able to screen and figure out which ones actually work. When you have the opportunity to try that many things, when you have that many shots on goal, you score a lot of goals. What that means is that in any particular campaign where we're trying to find one of those important things that is going to make a product for one of our customers, we might have something like 50-100 hits that come out of our process. The question is, well, most patents relate to one hit. How do you cover 50-100 hits in a single patent? What we're starting to do is actually make patenting a part of the services that we perform for our customers. We're going to own those patents, but they're going to get a limited exclusive license to a very broad patent that covers an entire hit set and actually provides them with a much broader scope in their market than they would get if they had done this themselves and had found one sequence that worked. The synthetic biology industry has been plagued by not fully thinking through the consequences of agreements and contractual commitments that it made. There have been problems where people have committed their platform essentially exclusively to one particular customer in a field. Of course, what that means is that if that customer doesn't do very well, the technology can lie fallow. It also really limits the ability of the company that is supplying the technology to be able to work with others and to generally advance the science that is going to make biology easier to engineer. I've worked pretty hard to try to develop a transaction structure that allows every customer that we have to benefit from all the previous work that we've done while still also retaining some of that benefit for our future projects. In general, we give, as I mentioned earlier, a limited exclusive license to our customers over patented IP, but we provide a non-exclusive license to unpatented IP and also to the background, to all that other stuff that we invented before we ever encountered that customer. When a company comes to us and is interested in making a particular kind of project, the expectation will be that we'll get into that kind of contract where you essentially give away the store, and you say, "Okay, I'm not going to work in that area anymore. You're going to get exclusivity to all the stuff that we invent." Sometimes I think they're a little disappointed when they learn that we don't give that kind of exclusivity. I think that eventually our customers come to realize that our platform is what it is and gives them the power that it gives them because of the fact that we haven't provided that kind of exclusivity. I worked on a project recently where we had done something in the animal feed industry, and we were able to take some of those learnings and use them for plasmid DNA production, which is really super important right now in the global pandemic that we're facing. I think that our customers are increasing in sophistication to understand that we really are trying to hit that sweet spot where we do provide them with a real advantage for having invested with us, but we also are keeping our platform moving and growing and continuing to improve so that we can keep making biology easier to engineer. I see a deep parallel between the heterodox and transformative approach that many companies, including Palantir, are taking in transforming information technology. I see that same parallel with what Ginkgo's doing with the foundry, with biology, manufacturing, and so much more, everything physical in the world. Another aspect of Ginkgo that I find incredibly exciting is the compounding opportunity of the Codebase. It's not just data for data's sake, but data that gives you true decision advantage and builds a moat around the business by building and advancing fundamental understanding of the science. Now that you hopefully have a little bit of a better taste for what it is we actually do, we want to help you understand what that does for our customers. I'm going to introduce you here now to Jennifer Wipf, who's our Head of Cell Engineering Commercial, and Ena Cratsenburg, our Chief Business Officer, who are going to introduce you to a number of our customers and help explain how we think about building real partnerships with our customers and enabling their programs to succeed. Jen, Ena, take it away. Hi, I'm Jennifer Wipf, Head of Commercial here at Ginkgo Bioworks. I'm Ena Cratsenburg, I'm the Chief Business Officer at Ginkgo. We just took you on a tour of our foundry, and you learned about our massive data and codebase. We want to talk to you about our customers, how we work with them, and give you a little bit of insight into what a cell program looks like. As you've just heard, our mission is to make biology easier to engineer. What that means is that we are relentless in the pursuit of building a world-class cell engineering program to enable our customers to develop very innovative products and solutions. Our customers are amazing innovators who have great ideas of how to use biology to solve world-class problems. At Ginkgo, cell programming can take on many different forms. It could be improving an ingredient for fermentation, inventing a novel therapeutic, creating bio-derived chemicals that replace products that are currently made with petroleum. We do stuff like enzyme work that would go into baking and brewing. We're working on solutions for bioremediation, the list goes on and on. There are many things we can do with cellular computing. Many of the partners that we work with have their own R&D teams. That's right. Especially in pharma. Yeah. Why would they come work with Ginkgo? I think what's really interesting is to see how Ginkgo actually complements our customers' R&D efforts. With sophisticated customers, like many of our pharma partners, they have an extensive R&D organization, and they do their drug discovery and development really, really well. But what we do and what we offer is really an extension of that capability. We have a cell programming platform that is extensive, that has a lot of experts who know how to do cell programming, that really plugs into what they're doing in terms of developing new therapeutics or looking for ways to improve the manufacturing process. As we've seen with some of the latest news, we are working with pharma partners on improving mRNA production. We're working with pharma partners on gene therapy, and the list goes on. There's just a lot more we can do there that we're really excited about. We recently announced a deal with Biogen, where we're working with them to develop next-gen AAV-producing vectors. What's exciting to us about that is gene therapy has a lot of promise to address a lot of unmet medical needs, cure a lot of diseases, but manufacturing has been a challenge. It's difficult to manufacture gene therapies for diseases that have high dosage needs or for diseases with large patient populations. What we're doing with Biogen is to figure out how to use our high-throughput automated foundry, along with our ability to come up with all sorts of different constructs and designs and really go through, rapidly, this design test cycle to allow us to figure out the optimal constructs that would give us the highest producing, most efficient AAV production platform. Tell me about the types of customers that we have? We have customers of all different sizes that span across many different markets. We've just talked about some of our pharma customers. As you've indicated earlier, our cell programs are really broad and diverse. We have customers that are working in different markets, whether it's consumer products, in industrial chemicals, in bioremediation, baking, and brewing. We also have customers that range across many different sizes. We have Fortune 500 customers, we also have emerging new startups, and a bunch of customers in between. Once we enter into a collaboration with our customers, and we put together a technical development plan, what happens? First, we assign a dedicated program team. These are experts in how to use the foundry and how to leverage Codebase. It's not just that program team that works with our customers. They're the orchestrators of the technical development plan. They leverage the massive scale of our foundry and Codebase to execute on that plan. They're able to tap into the 200,000 sq ft of foundry space that folks saw earlier, and the massive amounts of data that provide a starting point, a head start, really, on how we can move the project forward. On top of that, all the experts, all the experience that we have accrued from the years of working on different cell programs, it's amazing to see that our customers who are working on a specific program can access this massive infrastructure consisting not only of hardware, our foundry, software, the Codebase, but also the expertise of people who can actually execute the program well. That's right, Ena. Our teams are able to leverage experts throughout the foundry to run through design, build, test, ferment cycles, to run an iterative engineering approach to reach the outcomes that our customers need. Take us through what actually happens when we engage a customer and start a cell programming project. When we start working with customers, we set up a cross-functional joint steering committee, and this is a team of people who are looking after both the technical and the commercial elements of that cell program. We find that through the process of often our first cell program, we identify next areas of interest for our customers. They start to view us as a strategic thought partner, as technical advisors, and we understand more about their strategic interests and how biology can help support that. We find that this joint steering committee often identifies new areas of interest for our customers, new cell programs that we can work on next. One of the things that we can offer to customers is the ability to flex up or flex down their R&D resources and their spend. What that means is that they don't have to spend a bunch of capital to build out lab space and automation at the scale that we have. Even if they decided to do that, they wouldn't have the years of experience. Absolutely building the scale and building the code base that we have. We've been at this for over a decade now. Yeah. What kind of new customer conversations are you having? I've been doing BD in the synthetic biology world for the past decade and a half, and what's really exciting to me is to see that as the synthetic biology platform becomes more and more mainstream, there's a lot more interest and understanding of what the platform can do. Because of the success that we've had with our existing customers, we're getting existing customers talking to us about doing more projects. Those existing customers, as they launch new products, make the synthetic biology platform more real, and that attracts more and more customers. The diversity of customers we're seeing and the speed at which we're getting really good traction with customers who want to use our platform has really accelerated in recent years. We're getting a lot of inbound inquiries from customers about what can the biology platform do for them. They're asking us questions that actually allows us to think more creatively about how our platform can be applied. I'm more excited than ever about our pipeline, more excited than ever about the possibilities of synthetic biology, and I think it's only going to explode from here. One of the things that gets me very excited about Ginkgo is the enormous breadth of applications where our platform is relevant and can lead to breakthrough innovations. We've purposely developed a corporate structure that will allow us to do that, so we don't just focus on one or two or three markets, one or two or three applications, but have set up the capability to be meaningful to a lot of different industries with partners, obviously, that have deep expertise in those industries. That, to me, is the optimum leverage of what Ginkgo has built over the last 15 years. Well, Motif is a food technology company, and we're here to create plant-based foods that people actually crave. That's kind of a high bar when you look at where the industry's at today, where consumers really aren't getting what they expect from their plant-based foods. They don't taste right, the texture's not right, the nutrition's not where it needs to be. We believe those gaps exist today because the basic science of how to formulate with plant-based foods isn't really well-known, and technology tools to really create ingredients that make a difference to close those gaps hasn't existed. From an ingredient standpoint, the technology that Ginkgo brings to the table and that we partner on is a huge unlock to deliver those properties. Plant-based food, this is really popular right now. How is Motif going to compete? Well, the plant-based market is exploding right now in food, and we're really well-positioned to take advantage of a lot of that growth. One of the reasons we can do that so effectively is because of our partnership with Ginkgo and the great technology platform that Codebase and Foundry give us to develop new ingredients that don't exist anywhere else. The ability to create foods within this space that really taste the way people expect them to taste, that perform the way consumers expect. Think of a burger that actually tastes meaty and that has the right texture to have pieces of the meat stick between your teeth. Think about cheese that's gooey and melty and stretchy. We can enable those types of foods with the technologies that we're building together. How has the Ginkgo partnership helped enable you to build some of that technology? The real advantage to our partnership is the thought partnership that we have as a combined team. We're very close partners, and we're colleagues in this effort. Also, the advantage technology of the foundry and Codebase really provide us with a competitive advantage that nobody else in this industry has. We can literally screen thousands and thousands of variants of potential ingredients all at the same time, faster than anyone else can, and pick the ingredients that perform the best in plant-based meat, dairy, or nutrition applications. We can move faster than anybody because of Ginkgo's technology, and we know how to make all that technology work in food better than anyone else in the industry can. When you have an idea about a technology need for food and you come to Ginkgo to talk about that need, how does that work? The technology base at Ginkgo is amazing, the intelligence of the people, the team at Ginkgo, is also second to none. We're very fortunate to work with such amazing scientists. We start at square one with an idea of what kind of functionality and food are we trying to target, and we work together to identify the best way to generate those targets using the foundry. We start from the very initial phases of what does the screening have to look like, what's our approach going to be to design the right organisms to make those ingredients. That process can take anywhere from a few to 6 months, and we're together every step of the way until we actually have an organism in our labs that we can grow and scale up to commercial production. Once Ginkgo has done the engineering of the organism, how do we work with you to put that into market to make that real? When we receive material from Ginkgo, it's not just a handoff of a microbe. It's handover of all sorts of information and insights that enable us to quickly go to commercial scale and actually produce ingredients for these applications. It's a full body of knowledge that's transferred, the thinking, the partnership, and the conditions that allow us to be successful from day one when we go into a commercial environment. You've been with Motif for 2 years, and you've seen a bunch of change. How does that pace compare to competitors or to other people who are working in synthetic biology? The innovation cycle here is breakneck speed, and that's enabled by the throughput of the foundry, and again, the talent of the team at Ginkgo and the way we work together in our partnership. I've been here for less than two years, but I've seen already more experimentation, more iteration, and innovation than I've seen in most of my time in the industry. Everything is fast here, for sure. Yeah. Let's talk a little bit about the products. What's it like when you've tasted one of these products that we've been making for the first time? We've actually gone into actual market applications. We're actually selling a prototype product now in a food service environment, which contains Motif ingredient that we collaborated on to produce. To be able to be in that situation less than two years from inception is just astounding. The feedback we've received on these products is incredible. We're finding that our product is beating market incumbents and performing at a higher level than what you can buy in the store today. Why are your investors excited about Motif? They're excited by exactly that combination you mentioned earlier. They see the value in the advantage technology that Codebase and foundry bring to the table. They see the team at Ginkgo, how they work with the Motif team. They see our partnership, and combining that incredible technology on the front end with our ability to execute and commercialize in the food industry with all the experience we have, that's a combination that they can't find anywhere else, and it's very compelling from an investment standpoint. We're going to invent new ingredients that the industry's never seen, and we're going to do things from a science standpoint and an innovation standpoint that will really change the world of food in ways that are hard to predict now. Sounds delicious. I can't wait. Thanks, Mike, for talking to us today. I really enjoyed it. Thanks, Jen. It's great. We have the industry expertise, and you have the overall platform that plugs in. I would say it's like if I wanted to start an e-commerce company, I wouldn't try and build a data server farm. I would go to Amazon and say, "Hey, we need to get hosted on your platform." I think there's really no overlap. It's designing the organisms. They're fungible. The cannabinoid we make are fungible with what we grow and extract, so we already have the products, at least the base products, in market. It's then innovating and adding new cannabinoids and tweaking the brand messaging. I also think one of the things that's amazing, the fermentation facility is a great example where we were looking at Koman, and then someone knew that, hey, there's a facility that might be available. While that's not part of the collaboration initially, just teaming up and saying, "All right, we're going to work together to go and find this facility and retrofit it and scale it up." To me, especially given the equity relationship, it's a full partnership. Joyn was actually launched and founded back in 2017, October of 2017, the vision was to bring together the agricultural and microbial expertise at Bayer with the synthetic biology expertise at Ginkgo and marry the two together with the vision of engineering microbes for agricultural solutions. That was the basis for the company. In 2017, when we launched it was me halftime. I remember that. As the interim CEO. Fast-forward to today, Joyn Bio is 75 employees. We've got about 50 of them in Boston here cohabitating with the Ginkgo team and another 20 in California in Woodland at a Bayer site doing our plant science work. That's great. It's been an exciting- Yeah adventure for us as we've sort of essentially pioneering the use of and the approach of engineering microbes for agricultural solutions. That's really the key thing. It's been a great partnership between both Bayer and Ginkgo to drive this, and Joyn is the beneficiary of being the joint venture that has these two highly supportive parents. It's actually been, from the very beginning, has been very much a team effort. Yeah. I think what you have to understand is that microbe or that chassis that we're using. In its natural form, there are no microbes that do this. With Ginkgo, we're able to use the foundry and the technologies that Ginkgo's developed to essentially go through what Ginkgo will call design, build, test. We'll find a starting point. We'll find a microbe that has some baseline activity, and then with the help of the Ginkgo and the foundry technology, we'll go through iteration after iteration. Yeah the amount of nitrogen that's fixed and the amount of nitrogen that's being transferred, or the high throughput. Yeah. The scale that Ginkgo brings is something that not only a small company like Joyn, but even somebody like Bayer doesn't have. Yeah. Right. It's extremely unique to Ginkgo, and so that's why this partnership between the two, taking the agricultural and microbial power of Bayer and then combining that with Ginkgo as a partner for Joyn, that's why we're in such a unique position. Yeah compared to anybody else out there in terms of the resources, the tools, the technology, and even the knowhow. Yeah that's there, that all has to go into doing something nobody's ever done. Historically, we had seen that products were created in a way where it was really you needed a quality product, it could hit cost, and there was performance. It's the quality, performance, cost as the main drivers, and now we're seeing the brands who are coming to our table who are saying, "We need Genomatica. Sustainability is the driving cause." They're saying, "We need sustainability, we also need cost, and we also need performance," and we're able to bring it to life and bring it to scale. What synthetic biology reminds us is that sustainability is the how we can deliver in a new way, and it takes collaborations like our partnership with Ginkgo and other folks to bring this work to life and to accelerate the changes. Our partnership with Ginkgo Bioworks has been really fruitful. They work with us to understand our needs and identify the areas in which their technologies could help advance our goals. Ginkgo built systems to express the COVID-19 antibodies we had discovered, and they tested the antibodies for our spike protein binding and neutralization activity. Pairing our computational antibody discovery platform with Ginkgo's foundry was instrumental in validating proof points for our COVID-19 program. Ginkgo hasn't just been incremental arms and legs. It allowed us to scale our platform's tangible output. With the addition of Ginkgo's complementary methods, we've been able to evaluate more of our computed sequences than we otherwise would have been able to within our budget. Together, we've been working on molecules with exciting potential relevant to the COVID-19 pandemic, while at the same time laying the technological groundwork for responding rapidly to future threats. Hello, I'm Dr. Arie Belldegrun, a physician scientist, and a UCLA professor, and a Ginkgo investor and incoming board member, and I have with me three outstanding scientists and leaders in the biotech and life science industry. Today, you will hear some of their ideas from that discussion. We spoke about the value of synthetic biology, or syn bio, for the biotech and pharma world, and the potential of Ginkgo's value and contribution to the space. Enjoy. Let's first talk about synthetic biology. To me, this is really a continuum of the recombinant DNA technology. Now in the genomic era, we understand the functions of many genes, and what we can do now is not only understanding the functions of the genes, but what different segments of each gene does in producing protein. Now in the current genomic era, we can piece different parts together and come up with gene that can do much better than what the natural gene does. I think this is really the synthetic biology at the core, and now what Ginkgo, I believe, is doing is industrializing the process of synthetic biology. I've been involved in the chimeric antigen receptor drug development for the last 8 or 9 years, and when I think about the chimeric antigen receptor itself, that is an outcome of a synthetic biology. Chimeric antigen receptor doesn't exist in nature. It is pieced together using three or four different genes, you come up with a protein that will enable the T cells to do its job much better in seeking out and destroying the cancer cells. This is not just a science fiction. There are four FDA-approved products using chimeric antigen receptor technology, and there are thousands more in development as we speak right now. What the Ginkgo biology scientists have done is modularizing the synthetic biology to make this occur in a much more efficient and speedy way. Something like chimeric antigen receptor technology from the inception of the idea, which occurred in the late 1980s, to actually perfecting the so-called the second generation that we are all using, it took about 15 years, and we are still looking for a better chimeric antigen receptor construct. I think this can be done in a much speedier way, not in 15 years and hopefully in a matter of months, and that's where Ginkgo is coming in. There's three key areas that synthetic biology can have an impact on gene editing. First, the What's important with gene editing enzymes is to be able to sample the genome, that is, to edit any base anywhere. If we focus on RNA-guided nucleases, the CRISPR-Cas systems that allow you the greatest flexibility, those systems are dependent upon a primer that can see the nucleotide sequence that one wants to target, but they have to see adjacent to that primer what's called a PAM or protospacer adjacent motif. Otherwise, you can't target your specific sequence. As editing becomes more precise, the enzymes that are available being developed by the current crop of companies, Streptococcus pyogenes Cas9, Staphylococcus aureus Cas9, Cpf1, have very limited PAM sequences, and you can only target against those PAM sequences. Your primer must be preceded or followed by those PAM sequences. I think there's several immediate applications that come to mind for development of synthetic biology and Ginkgo's platform in the application to therapeutics. Perhaps the most immediate one, and one that I think is perhaps going to be most important, is development of new antibiotics. We have a collaboration with Roche that is looking at antibiotics that can treat some of the gram-positive organisms that are difficult otherwise to treat. Another area that I see as very promising is in the high-throughput production of protein therapeutics. Most of the proteins that now are being produced are using primarily natural amino acids. I think as we go to more challenging targets in the protein therapeutic space, that increasingly we're seeing those proteins, including a small number, but a very important number, of unnatural amino acids. I think that there's a huge opportunity to use recoded bacterial organisms that may be able to simply express those specific unnatural amino acids in a more natural way and avoid the use of chemical processes during the synthesis. What is the signature we look for when starting or ideating a new strategic venture? That signature actually has 3 pieces or 3 prongs. We're usually looking for a large market opportunity where biotechnology has had a toehold but been under-leveraged or under-invested, where typically we see that innovation is siloed out and potentially under-resourced. Then second prong, where we can aggregate that work on Ginkgo's platform in order to take advantage of our economies of scale, de-risk technical risk, and accelerate programs so that we can develop multiple solutions and products. Third prong, we look for opportunities where we can partner with corporate strategics or seasoned executives that have deep network and expertise in a channel. The advantages of strategic ventures are fairly clear. These companies are born day one with immediate access to Ginkgo's cell programming platform, mature, de-risked, with 400-plus scientists ready to rock day one and take programs. They don't need to, for instance, take and undergo that typical lag time that startups have of booting up their own technical team, hiring their own engineering team, developing their own lab. Right? Instead, they can orbit around their customers, around their product development, around their application science, the things that will eventually drive the core value for those businesses. We think of this as a classic division of labor by comparative advantage, although it's actually startlingly rare in venturing, where typically companies spend their first years of life and their first rounds of investor capital actually building up and proving out their technical platform. Here, we think we've obviated that. As I said, instead of focusing on engineering or cell engineering, these companies can maniacally instead concentrate on product development, end market applications, et cetera. That's where they build up expertise and build up capability. As a result, these strategic ventures team look very different than the Ginkgo team. They look complementary to the Ginkgo team. In the case of Motif, for instance, you see world-class food scientists. You see sensory experts, people who are really well-versed in understanding how ingredients can be formulated and mixed to solve texture, taste, other sensorial problems, and create new experiences for consumers in the food space. At Allonnia, there are teams and folks who are well-versed veterans in the bioremediation space, process engineers that can marry biology with mechanical, physical, chemical systems that can then be deployed onto sites to remediate waste problems. Neither of these companies needs to have a team to build out a cell engineering platform. Ginkgo obviously covers that. But I'd say by far the most critical element for success for these opcos is the leader. What's needed in every case is this alchemical mixture of someone who has a powerful vision for how biology can transform or disrupt an industry, someone with an expert understanding of their field and the gravitas to bring along customers and peers, and someone who has that aptitude for translating a new technology, in this case, biology, into their market. I think the relationship with Ginkgo is really a game changer for Allonnia. Using biology for waste has been around for decades, and it works, but it's inefficient in how it's used today. The use of natural biology has limitations, and Ginkgo's role in progressing the ability to read and write DNA is really unique and affords much more capabilities to Allonnia's solutions than have ever been possible before. It gives us more shots on goal with their foundry and Codebase. An example of this is we're working on a biosensor contaminant project, and so we're looking to create a biosensor that detects contaminants in the field. We're working with Ginkgo to develop this. Through that work that we've been doing over the last couple of months, is we've been able to test 100 trillion constructs. 100 trillion. To me, that's amazing, and it's something that was never possible before and could never be done manually. I think this is a great example of how their capabilities is really allowing us to be more successful in the development that we're trying to do. We are, of course, relying on Ginkgo to do biotech work, which enables us to remain focused on our industry and what we are good at. We don't have to build out the technical infrastructure, which is expensive and costly and risky on the biotech front, nor do we have to hire a massive team for that expertise. We're able to rely on Ginkgo for the biotech work. We'll have, of course, some very important biotech expertise, but we don't have to build out the team nor the infrastructure. We view this as an agility play for us. It allows us to be agile, it allows us to be very efficient with our capital as well, and to focus on our industry and what we are good at. If you think about the tool set of the industry thus far, effectively for as far as we've known of the personal care industry, it has relied on extracting the ingredients that we use from the world around us, whether it's relying on petrochemicals, animals, and then more recently, plants. This is certainly a way of sourcing ingredients, presents challenges and problems from a sustainability standpoint. We believe that by turning to biology and biotechnology, we can not only solve some of those sustainability challenges, perhaps more importantly, and what we're most excited about, start to open up entirely new possibilities in beauty and personal care around the types of actives we talk about, the types of actives we formulate with functionality and performance, and fundamentally changing how we construct formulations and products. We're going to create new food experiences for people, and by doing so, help the industry convert more people over. That's only possible because our partners at Ginkgo can really deliver on the platform of analyzing the opportunities and discovering things that I don't have to build the infrastructure to do. I have to have the knowledge of what should we be looking for, and then how to apply it. I think that is the true essence of the partnership that allows us to be aggressive in the other areas. I would say, and the proof will be in the pudding over the next several years, we will surpass the other players who are really trying to create better-tasting plant-based foods. I think we already have quite a bit of the proof in a very short amount of time, in that the products that we have developed with our new technologies inside, in consumer testing and in sensory testing, outperform pretty much all the products on the market today. Obviously, we're in a hurry to get those into the market. That would have not occurred if we weren't able to balance Ginkgo's power in what they do and us building a company with unique sets of powers that complement those. We are going to have a pipeline of innovative, differentiated ingredients that will not only solve existing problems, but push in to new white space for this industry. That in and of itself is valuable and powerful. We have unique access to that, very much so because of our relationship with Ginkgo Bioworks. Effectively, we have access to this multibillion-dollar platform that is able to do this work for us at a speed and a cost that makes this viable in this industry. It enables us to stay focused on the application area that we are experts in. We get to stay focused on the formulation and the analytical piece so that we can confirm how we bring these ingredients to market in an experiential way that is still powerful and high-performing. There is a Ginkgo sphere, which Ginkgo has a whole series of connections in different industries, different applications, different products, and different people that think differently. First of all, it is exciting. It is great to be tapped into. The other CEOs of companies that have spun out of Ginkgo or partner with Ginkgo, we connect with one-on-one or in a group. We leverage that network to help each other out. We leverage that network to get new ideas. First of all, just the partner companies create one network. Then, Ginkgo was built with great investors. We have definitely built relationships with many of them. We're excited to bring in some new investors that complement those, and I think that network of investors has also created opportunities that we would not have seen previously. The other thing is, Ginkgo has an unbelievably diverse set of people in the company. As we've learned more about the people in the company, it's helped us connect. The reverse of that is, I think that Ginkgo has realized that we've built an interesting company with quite a few smart and interesting people, and that network goes both ways. Hey, everybody, I'm Matt. I'm the Chief Commercial Officer at Ginkgo. Really excited to be here to talk about biosecurity. I know we just spent a bunch of time talking about the amazing products being built on the platform. I think this is a really important connective piece to that. Just like in any industry that grows, if you think about computing, and you think about the digital revolution, it wouldn't exist without really powerful cybersecurity tools. From our standpoint, this amazing ecosystem that we're building on top of the Ginkgo platform, we also have a responsibility when we think about the care we use in engineering biology to integrate security tools over time into everything we're doing with our partners, into their products, to make sure that we're engendering the right kind of development. It's really deeply built into who we are about how much it's important to care about how our platform is used. Biology is such a powerful tool, it's something that we have to be thinking about when we're thinking about applications of our technology. We have to be thinking about it when we're thinking about the security around biology. Today, we have this amazing group of people that have come to Ginkgo, as advisors and as part of the team, to really help us think about how to do that security piece in a really powerful way. I'm excited to have with us General Thomas Bostick. General Bostick was the head of the U.S. Army Corps of Engineers, then in a way that's really close to our hearts, moved over to be a biotech executive and has been just a great mentor for us and an advisor for us at Ginkgo. Renee Wegrzyn runs all of our biosecurity efforts focused on the U.S. government, has joined Ginkgo in the last year from 10 years at DARPA, just brings this amazing set of experiences that has been really helpful for us as we think about what our role and responsibility are, both on the culture side, but also on the technology side. Andrew Weber, who has this amazing set of history and stories around 30 years of engaging in this world. How do we protect ourselves from bio threats and from other things that exist on this planet, and has just this wealth of knowledge about how governments around the world work. Most recently in government, was an Assistant Secretary of Defense in the Obama administration focused on these issues. Really excited to be here today to have the opportunity to talk about biosecurity in the context of what we're building here at Ginkgo. Maybe I'd love to just start with you, Andrew Weber. We're coming out of COVID-19. Certainly, the world is engaged with biology over the last year in a way that maybe is different in the last century. How much should we be thinking about biosecurity, and how are you thinking about the next decade? Well, we're living through the largest biological event of our lifetimes, and we've seen an acceleration in the technologies that are helping us get through this. It's been an amazing amount of progress. I think we're at this inflection point, and it's a little bit like we were in the early '90s with the internet and the smartphones. We have this new sector of the economy that's really launching now, and it's enabled by the digitization of biology, the ability to program cells, and we're just tapping into that now, and it's going to change everything. We have an opportunity, though, to bake biosecurity into it now and not have that vulnerability that we've seen in the cyber world, where they didn't really think about designing cybersecurity into the systems from the beginning. Now there's a huge investment in playing defense. I think we also have an opportunity to establish the norms for this new sector of our economy and to establish some taboos, what not to do with this amazing power that's been unleashed. Tom, I'll go to you. I alluded to it, but this incredibly unique combination of deep national security experience running massive organizations in the U.S. Army, and then existing in the biotech ecosystem. How would you address the same question? Why, after all, what we fundamentally believe is that biology and making things out of biology will transform economic output in the next 5, 10, 50 years. How have you engaged in that topic? What has changed? What are the things on your mind as we think about this interplay between security and economic outcome? Well, thanks, Matt. It's great to be here. I loved being a senior advisor at Ginkgo. What I'd say is that I spent much of my life on the national security side of the house with Department of Defense, as you pointed out. I was building better dams. Now I'm building better DNA. That was a difficult transition, but it's a transition I was very happy to make because I truly believe that biology has a chance to make a huge difference in the future of our world that we live in. Much of it's going to come down to trust. When you think about biosecurity is the facilitator for the bioeconomy, but it's going to do that by building trust. By building trust, what I'm saying is that people need to feel comfortable. They need to understand what's happening to them. When scientists do things, people most often trust that solution in times of crisis, and the crisis could be COVID, and you've seen many people trust the science and trust the scientists take the vaccine. If you're in stage 4 cancer and there's a new immunology solution, people will trust that even though there's some risk there. When you think about where the world is going with many, many more people on the planet in the next 30 years, we need that trust not to exist just at the extreme of crisis, but throughout our daily lives. A good example is what Ginkgo is doing with K-12 pool testing. The kids going to school in the middle of a pandemic. They're doing that because the teachers, the mothers and fathers, aunts and uncles, and the children trust that they're in a secure facility in the school. They trust that because of the biosecurity platform that Ginkgo is providing. What we're doing in K-12, really it's this mindset shift. It's this mindset shift from we use biotechnology in healthcare purposes only. What we're doing in K through 12 is really offering schools the ability to test classrooms as cohorts and generate data like they would generate testing data or any other type of data in a school setting to make better decisions. If we imagine a world with hundreds, thousands, tens of thousands of products made in this incredibly powerful, efficient way coming off of the Ginkgo platform, you're saying let's not just have security in the extremes, an mRNA vaccine that's massively amazing to bring us out of our current crisis. We're also saying let's have consistent, regular security and trust throughout. Renee, I think that's, especially as you've thought about this transition from DARPA into building this at Ginkgo, what is it about what we're doing that gives us this unique advantage to build the tools to generate this trust that you're talking about, Tom? Coming from DARPA, what have you seen, and what is it that you reflect on there? I do see very much that Ginkgo is in some ways almost like an DARPA of the private sector, and what I mean by that is when I was at DARPA, we were building breakthrough technologies for national security, and so really Ginkgo is using its platform to create the next breakthroughs for the bioeconomy, and it's not prescribed to a single application. At the end of the day, it's food security. It could be K through 12 testing, but it's really based on this platform, and we were successful in bringing K through 12 testing and in helping respond on the vaccine side of things, not because we're a pandemic preparedness company. It's because we're a platform company that is able to pivot and respond to what that challenge. A year of powerful biology, here it was the pandemic, but it's the powerful response of what our platform gave, where we could respond, and we're going to use that in the future for our customers. Bring us your challenge. Maybe it's the supply chain issue is the next thing we deal with. Maybe there's an outbreak in agriculture that actually brings an economic threat to our shores. We're going to be ready to respond because we've built a platform to do that. You were incredibly important in building our K-12 testing program. I think connecting a couple of these pieces would be really helpful for us to understand. At this point, our lab network, that we've partnered with to qualify to run testing across the country, has enough capacity to test every student teacher in America, right? That gives them this data layer to be comfortable in knowing, like any other piece of data, what's going on with COVID-19 in their communities. Can you just share a little bit about what you did differently to bring biology to these communities that had never really engaged with something like test every kid, every week? Yeah. The Baltimore City Schools example, I think, is a really great one in the way that Ginkgo approached the challenge. Rather than go to Baltimore City and say, "Hey, we have the solution. This is what you should do." We came to them and told them what we think we're capable of, but really wanted to listen to them and understand, what do you need, actually, and what is going to be workable in your communities? This wasn't a single conversation. This was many, many conversations over many days and weeks to understand how can we be on the same level, and does this work for your students? Does this work for your parents? Because the parents have to give consent, of course, for their students to be in the testing program. We knew if we got that right in Baltimore City and invested the time, that that would allow us to then bring that to other cities in a much easier and a faster way, and that really did prove to be the case, that we were able to scale to now thousands of schools across the United States. What could you imagine with your kind of DARPA hat on? Crises create opportunities to change how we do things to better prepare ourselves for the future. Right. Every major crisis in human history, things have come out of it, right, that are unique and different. We're testing kids across America in schools. What do you see that turning into if we get it really right as a country or as a world? What could that do to prepare ourselves in the future? Andy, I'm going to ask you the same thing in a second. I'm going to give you two answers because I think there's a scientific way, and there's a cultural way that you can answer that. The first is, kids are really excited about having this technology. Our creative team has really made an effort. There's even comic books that the kids have now, so they can learn about the testing. Going back to the lab network, what I'm really excited about on the technological side is not what those labs are doing now, it's what those labs were doing before COVID, right. We partnered with labs that were doing environmental monitoring. They were looking at wastewater. They were sampling from the environment. There were labs that were doing cancer diagnostics, labs that were doing 100 tests a week to 100,000 tests a week. There's so much potential in that network now that we are working with those partners and how can we really leverage that going forward to continue to understand our biological environment now connected through this digital layer that we've built to really be ready for what's next. Andy, in your last job, or if you look forward, if you had a network, the ability to monitor in an anonymized way what was going on in the biological ecosystem, how would that have changed what you could have done or how we would have prepared as a country? Yeah. Well, these technologies and the distribution of them widely are going to give us the capability of having that weather map, where you get the weather report every day for infectious disease everywhere in the world, real time. That will allow us to nip epidemics in the bud. The information piece, the genetic sequencing piece, it's all coming together, and I think because of the COVID crisis, the application of these biotechnologies has leapt ahead a decade in just a year. Now we've made that much progress. We'll sustain it and improve upon it, and the benefit to humanity will just continue to grow. When you think about biosecurity, it is an early warning. It's trying to identify the infectious diseases early on, so you prevent the sort of damage that we saw with COVID, with deaths and infections and people getting sick. I think in the future, just like you talked about earlier with cybersecurity, leaders will be asking what's their biosecurity strategy, how do they approach this so that the company is more resilient. I think in the future, you're going to see chief operating officers briefing boards about their biosecurity strategy. That biosecurity strategy in all these different companies are going to have to lean on the private sector expertise that can deliver on that. I think that's going to be ubiquitous as well, and we've seen it already with what's happened in COVID-19. The question is how does that get extended? How much are boards willing to invest? I will tell you that with my public and private sector experience, it's a tough decision. How much do you invest in almost preventative maintenance? Some folks are willing to take risks, and when you take that risk, you pay a lot more on the back end as opposed to doing it on the front end. How do you see Ginkgo continuing to engage with the Department of Defense, some of the other governmental research organizations? What's that interplay with just the continued innovation spirit at Ginkgo, and where can we continue to use that as part of this development, both in biosecurity and otherwise? Six years ago, the co-founders came to me for help. It's amazing how respected they are in the Department of Defense as leaders of this new sector of our economy that has applications across the Department of Defense and the Department of Health and Human Services. It's been an education process. At this point, when the government thinks about this, they turn to Ginkgo, they turn to the leadership here because they know that that's where the capability lies. We're in all of these communities across the country now and really focused on using testing as a data generator so that people can make decisions on a classroom level or a grade level and not on a community-wide level, right. This is the idea that these are decision tools to make better, more nimble, sophisticated decisions. They're in schools, right. Obviously, the current administration has invested massively in testing in schools, and we're playing a huge role in supporting that. Andy, as you look towards the future, right, I think we see lots of different opportunities out of a crisis that we've given schools and other parts of the community new tools. What could this be used for as we go forward? What are the other ways to build on this infrastructure that has now been laid as a country or as our communities? Well, I see it as part of an early warning system, a weather map, if you will, for infectious disease, so we can see those storms coming and actually prevent them from happening. There's such a visual reaction to somebody when you say "forecasting," right? You think of the weatherman, and here's his forecast. What we haven't really talked about yet is our dashboards. Not only are we generating this data where we've developed the capability to digest that information and then give that to a decision-maker who might not have a PhD in molecular biology but can say, "Wow, okay. My rates have been going up," and look at my rates relative to the community. Oh, by the way, this last month, I tested 100,000 kids. These are really important points that the decision-makers can bring forward to know how to move. I'm really excited about that interface with the communities. I'd actually be really curious, Tom, like you, running an organization that is global, like Army Corps, what were the tools that you worked with that helped you make those decisions? One of the things I was going to follow up on both of your excellent points is that I've been involved in a lot of disasters and responding to those disasters. In some places, you'll find people are prepared more than others. Florida, they've seen a lot of hurricanes, and places where earthquakes, and their operations center. What Ginkgo has done with this capability that it's placed out there with K through 12 is almost like a public-private partnership on a grand scale. A lot of these cities and towns and communities and states have not had to respond in the way that some other states have had to respond with disasters. I give huge kudos to what Ginkgo has done in that particular way, not directly in the K through 12 testing, which has been huge, but really macro level, how does the public and private partnership come together in a way that makes meaningful change? The Corps' system is to work with governments, just like Ginkgo has done. I stood back in awe to watch Ginkgo do what maybe the Corps would do. We're not experts in schools. I see a lot more public-private partnership, and Ginkgo has helped to facilitate that at the tactical level all the way up to the state. Well, that was great, Tom. Thank you. To everybody here, but also in the spirit of the whole company, this has been a really amazing, hard, challenging, fulfilling year, and I appreciate all the work that you all have done to help us try to have the impact that we've had, both on the biosecurity front, but also on the platform build front. Look forward to many years to come, and thank you all for your guidance and work, and very much appreciate your time. Well, thank you, Matt. Thank you, Matt. Good afternoon, thanks for joining us again. We just finished up this great conversation on biosecurity and the importance in building that kind of an infrastructure as this kind of technology really takes off. To continue this conversation about care, I'm thrilled to bring two luminaries in the field of impact and ESG into this conversation to really kick off a conversation on the role of sustainability and ESG topics in investing. Just brief introductions here. Katherine Collins is the Head of Sustainable Investing at Putnam Investments. There, she manages several sustainable equity funds totaling over $7 billion. She collaborates more broadly with portfolio managers and analysts on integrating ESG into their investing theses across the roughly $200 billion that Putnam invests. Prior to joining Putnam, Katherine founded and ran Honeybee Capital Foundation, which was an independent research company focused on sustainable investment issues, and did that after nearly 20 years as an equity research analyst and portfolio manager at Fidelity Investments. We're also joined by Governor Deval Patrick, who's a founding partner at the Bain Capital Double Impact Fund, which is an $800 million private equity fund focused on scaling mission-driven companies, and previously served two terms as the governor of Massachusetts following a long career in both public service, including as the Assistant Attorney General for Civil Rights under President Clinton, and in the private sector as the general counsel for both Texaco and Coca-Cola. Thank you both for joining me. Thank you. I'm really excited to dig in. Thank you. Maybe just to get us started, Katherine, you manage over $7 billion of dedicated, sustainability-oriented capital at Putnam, and not to mention your impact on the broader portfolio. That is a lot of capital. Just curious, how did that happen, and what have been your goals with those funds? Well, it is a lot of capital, and it's an honor to steward it. First of all, it's not just me. I manage the portfolios with my colleague Stephanie Dobson. We have a dedicated sustainable investing team. Even more important than that is the fact that our team is embedded in the equity research team at Putnam, and that really is the key to how things came about. Putnam took the time in planning for this team and this effort overall to step back and say, "How can we approach sustainable investing in a way that it extends our traditional strength as active, long-term, fundamental managers?" Instead of setting up this team as an island unto itself or a boutique down the hallway or an administrative function, they really took the time to plan for this team to be part of our core equity research process. The portfolios that you mentioned and everything else comes from that foundation of long-term, integrated, fundamental research. That's really the key to everything, is recognizing sustainability issues as core, long-term, strategic issues that are relevant for any business leader and any investor. Yeah. I want to second what Katherine says, that we have to think about sustainability as an integral and central part of all investment decisions, all business decisions, and frankly, all government decisions. I think that for me, all of this is in the frame of how we shift and must shift from a focus on short-termism to long-term value. What we've been trying to do at Bain Capital, and I feel really, really great about the success we've had, is to demonstrate that choosing between doing good and doing well, between financial return and measurable social or environmental impact turns out to be a false choice all along. I want to dig into that topic because I think there's definitely a perception that impact investing must have lower returns, and you're describing it as a false choice, of all. I think that perception exists either because ESG-oriented companies must obviously not care about profits because they're optimizing on some other dimension or maybe the more neutral pushback is that it's just a smaller potential investable universe, and so it must be more competitive. Obviously, you've heard that concept before, but you've both raised real amounts of capital against this within very large institutional investment firms that I know personally definitely care about returns. I'm curious how you then think about the critique you described as a false choice, Governor Patrick, but I'd love to dig into that a little bit more. I'll start and simply say that when we were organizing the Double Impact Fund at Bain Capital, it was the first impact investment fund at any institutional investment firm, any private equity firm. We made a decision to strive for superior returns, not as a value judgment for what others may do, but because we wanted to demonstrate that you didn't have to make that choice if you didn't want to. You might choose to, but that you didn't have to. We chose sectors in which to invest, where we knew we could generate that sort of return: health and wellness, sustainability, broadly described, education and workforce development. All of these are secular trends with an awful lot of activity. There are great mission-driven companies that are in the lower middle-market, middle-market in North America who are looking for value-aligned capital so that they grow because they are concerned that the investors come along and say, "We'll take it from here. We like what you've done," but that the mission will get lost as they grow. I'm delighted that as the first fund is now deployed and the second fund is well underway, I believe we are in the top quintile of the Cambridge Associates measure, not just of impact investing funds, but of middle-market funds, regular rate middle-market funds. That is what we're trying to show. You can do this at scale, you can do it over time, and it is about thinking about and organizing toward and being intentional about long-term value to all stakeholders instead of just short-term return for a handful of shareholders. It's interesting, the theory and the math of traditional finance and neoclassical economics is really zero-sum math. There's a reason for this really strong root of either/or thinking on this topic. The bridge to me, there are two bridges that are important. One we just touched on is relevance. As soon as you recognize sustainability issues as relevant to long-term business success, all kinds of doors open up. The second key is the short-term, long-term element that Governor Patrick just mentioned. Once you get past a decision that might be hard in the first week or the first month and really extend your time horizon, it's amazing how much alignment there is between something that is sensible and additive from a sustainability perspective and also sensible and additive to company performance. Our premise at Putnam and the goals of the funds that I'm running are very explicitly to seek out companies where excellence in sustainability is making the company stronger. It's not just that they happen to be managing these things in parallel and are doing a good job at both. It's that one is fueling the other in a direct and positive way. Just as one small proof point, it's not forever, but our two lead public equity portfolios just hit their 3-year anniversary, which is very important in the public equity world. Our Sustainable Leaders portfolio at that anniversary mark was roughly 400 basis points annualized ahead of the S&P, and our Sustainable Future product, which is solutions innovation-oriented, was about 600 basis points ahead of its benchmark, the Russell Midcap Growth benchmark. To Governor Patrick's point, those are great numbers, not just within a little slice of ESG-centric portfolios. Those are just great numbers, and I think are proving out that thesis. I think Katherine is exactly right. What we want is whatever kind of investing professionals are doing is to be intentional about the impact of that investing on multiple stakeholders. That is a fact of investing. Every business decision has some kind of impact. If you're intentional about the impact beyond the shareholders, then you get better outcomes. It turns out, I think you get better return as well. Maybe to just end our time together here, a couple of questions for each of you. Adi, I'd love to just selfishly understand what themes you're most excited about in this area. What, over the next 5 years, do you think is going to maybe drive the most impact or be the most important areas of focus for your funds? Just given the audience today, I thought it might be helpful for you to just share any thinking or advice on how they might incorporate some of these ideas or themes into their own strategies if they're approaching it really for the first time. One of the tools that we've used for a number of years is this big, giant thematic map. Honestly, it got a little bit sprawling. We recently reorganized it under a publication called "Investing to Thrive." It's got three main layers. One layer is individual thriving, health and human wellbeing. The second is thriving systems and society, with a lot of really interesting complexity within that layer. The third is thriving planet, supporting life as we know it. A few of the themes that are highlighted in that report, and really interesting and important to us from an an investment perspective, are also interesting and important, I think, to Ginkgo and companies like it. 1 is the movement towards circular economy, where we're thinking much more of the economy as an ecosystem as opposed to this linear extraction and disposal kind of model that came with the industrial era. A lot of implications there for all types of materials, all types of logistics, all types of consumer-oriented companies. Really thinking about that full life cycle has implications across almost every type of business that we look at. A 2nd main area of focus is thinking about natural solutions and biological solutions. Almost everything that we invented synthetic, mostly hydrocarbon-based chemicals for in the last century can be solved, and solved potentially better, with biological solutions. Again, there's a wide range of implications there across lots of different sectors and products and types of companies. Those are 2 of many areas on that map. I'll note that the ethos there again is asking this question, what is needed for thriving? We're not looking for innovation or developments that are clever. We see a lot of investment ideas, and there are a lot of very successful companies that just do something kind of cool and neat, but maybe not so essential in the grand scheme of the world. Those can be fantastic businesses. Sometimes they can be fantastic investments. There's a real much rarer tier of companies that I would put in the wise category. These are companies that are doing something truly innovative, but they're doing it with a care and attention to the long term that we've been talking about today that really might create some essential foundational capabilities in the world that didn't exist before. Like, ooh, when you see that kind of opportunity, that is a really exciting one. Not without risk, for sure. If that care isn't there, it can be disastrous. Boy, when those things combine, it can be really powerful. That's what we're seeing in terms of themes and some of the areas that we're focused on from an investment perspective. For all of those executives and all of us, lots and lots of other people, to your second question, Ana Marie, sorting out what it means to have rigor around environmental, social, and governance standards has to be understood as more than compliance. Compliance is important. That's not what I'm saying. What it is you're doing to lead, what it is you're doing to stretch, and how intentional you are about that, as distinct from having a bragging point or a marketing detail on the side, is the sort of thing we are looking for. I'll say just one last thing. My team is tired of hearing me say that I am, but I will say, I am confident that there is a regular wave widget company out there that hasn't thought at all about ESG or its sustainability potential, where a private equity investor with the right team and the right executive leadership could take that widget company and turn it into a high-impact enterprise. One day, we will start to do that. When we start to do that and show that it can be done and that it can generate alpha on the financial side as well as on the impact side, everything changes. I love that, Governor Patrick. We've actually, I've observed the same thing from our standpoint where, Katherine, you mentioned earlier that biology can impact just about everything. I've gone and I've spoken at chemicals conferences, and they're full of oil executives from Texas who've never thought about biology in their industry and how could that be applied. Governor Patrick, I think you're absolutely right. There are so many industries where from our perspective, kind of an environmental solution or which may actually have a real business and long-term kind of strategic impact as well, just isn't even on the radar yet. Could, in fact, be one of the most important strategic business drivers for these companies going forward. I get really excited as well about finding those pockets that just haven't even thought about it yet, and finding a way to demonstrate the value and take these very large, established industries and help drive impact there. That's certainly one of the core sort of tenets and values of what we're doing at Ginkgo. Have really appreciated you being a sounding board to us and to the industry more broadly. Can't thank you both enough for joining us today. I think you're both luminaries in this field and innovators in the field and are clearly having an impact far beyond your funds. Thank you so much for joining us this afternoon, and wish you the best. Great to be with you. Thank you. What a joy. Stay tuned. You just saw how care is really embodied in how we think about the platform. It's really not just because we think it's the right thing to do, although, of course, we do, but it's because we really believe that this is critical to building a sustainable business. We wanted to follow these sessions about care with a session about our financial performance. For the final session today, I wanted to introduce our CFO, Mark Dmytruk, and then virtually our CAO, Chief Accounting Officer, Marie Follin, who couldn't be with us in person today, and talk about how this business model has matured and evolved and answer some of the questions that I know you and I get a lot from investors, and try to shed a little bit more light on those topics. Thanks for joining us, Mark. Can you share a little bit about your background? Happy to do that. I joined Ginkgo as the new CFO about 6 months ago, and I've spent about the past 20 years in the life science space. I spent 10 years with Thermo Fisher Scientific, and the past almost 10 years with Syneos Health, the global CRO, contract research organization, serving the biopharma industry. Prior to all of that, I had a career with Ernst & Young. Great. Marie, you can join us virtually. Could you introduce yourself quickly for everybody? Absolutely. I'm sorry I couldn't be there with you in person. Marie Follin, I work here at Ginkgo. I'm the Chief Accounting Officer. Prior to this, I have been at big institutional companies in controllership roles, a variety of different roles focused on accounting, reporting, internal controls. Prior to that, I was with Ernst & Young for 10 years as a senior auditor. Great. Well, I know I, for one, am very glad that you joined us, and you've been a great asset to the team. I thought, sort of selfishly, I get asked a lot of questions by investors and thought we could use this time to help bring a little bit of color to those. To set the stage, we obviously have these two core elements of our business model. The first being, the foundry revenue, which is just as customers pay us to use the platform on a usage basis. We have this downstream value component, and part of that is a more traditional milestone and royalty model, which you can ascribe a value to through some projection modeling. We also have this equity component for some of our transactions, which we'll accept in lieu of a royalty, particularly with earlier-stage companies. The interesting thing about those is, we can look at the historical data that we have on how third-party investors have put a value on that. That really does help us think about the cumulative value of these programs on a combined basis. One of the questions that I get on this point is how do we think about the margin profile of the business given the difference in timing in these different elements of the model? The first thing that you have to recognize is that the numbers you're looking at, both historically and in our projection period, are only the foundry revenue line. All of that downstream value share that we've been talking about, and as you know, that'll contribute ultimately at a 100% contribution margin when it flows through. We're done doing the work at that point. Exactly, yeah. None of that is in the numbers and therefore in the margins that you're looking at. Just to talk about the foundry revenue line, you can see that we are projecting that by 2024, we'll be approaching break even on the EBITDA line. I would expect that it would mature into a 20%-30% EBITDA business line. Why 20%-30%? Yeah. It's a very typical margin profile of a life science tools company or a pharma services company, and I've worked in those two industries for the past 20 years. That's the foundry revenue line. The question really becomes, okay, how do you then think about the downstream value contribution? The way we think about it internally is we do factor that downstream value share in when we think about the pro forma sort of economics and margin of a particular program. When we sign a new customer on for a new program, and just to take an illustrative example, let's just say that we've got a program that is going to cost us $4 million of work to deliver over the next, call it, two years. Our fully burdened cost, $4 million, we would charge the client $5 million of foundry revenue, foundry usage revenue for that. That's the 20% margin, EBITDA margin for your foundry business you're talking about. Yes. In the sort of mature state for Ginkgo, we would have a 20% EBITDA margin, that's exactly the $5 million less the $4. That's your foundry revenue. On top of that, we would negotiate a downstream value share. Today, based on the data that we have, we are seeing that the downstream value share is worth about a $15 million net present value per program. What does net present value mean? How do we get those numbers? What do they represent? The $15 million net present value is a risk-adjusted NPV. We have looked at the probability of both technical success and commercial success. We are not saying that every program will be commercially successful, but once you risk adjust for that, the net present value for all programs is $15 million. How did we come up with the 15? That is based on actual experience of programs that are in flight to date and have been over the past couple of years, and it is more specifically calculated with reference to those programs where we have an equity interest. The advantage with those is that they are marked to fair market value by third-party investors. We do have a reference point. We can look at what investors are valuing a particular customer at. We know our% ownership in that customer, and so we have a reference point to get to the $15 million NPV. Yeah. In that way, it's really not even entirely academic, because what you're saying is there's real demand from investors for kind of these equity positions at a certain value. That is how we came up with the $15 million number. It sounds like we're making a choice, to own those equity positions or royalty streams rather than sort of monetizing them upfront via the customer or their investors. We could, in theory, just sell that equity investment today to one of the third-party investors at that valuation, and then we would be bringing that cash in today. Just to follow on that, if you take that example where we have $5 million of revenue for the foundry revenue and then $15 million that we monetize today for the downstream value share, that would be a total cash inflow for that program of $20 million. That's on a program that would cost us $4 million to deliver. When you look at that margin profile, you'll see it's about an 80% contribution margin. That's how I think you would expect to see the Ginkgo margin profile trend up to over time. That seems like a really high margin profile. Why does that feel right to you? What do we look at that makes that feel sort of on a blended basis appropriate for the business? Yeah, it's certainly higher than what you see in pharma services or life science tools, but more comparable to what you see in software or the biopharma industry, where intellectual property is a key component. That's one of the core features of the Ginkgo business model is that we are bringing intellectual property via our Codebase and also our foundry capability to a client. We're able to negotiate those kinds of downstream value economics more comparable with those other industries. This whole conversation about what is equity worth today and can we monetize it now versus later, it sort of reminds me of another question that I get asked a lot, which is when would we choose to eventually sell down an equity position that we might own, why would we do it this year versus next year? Will we hold it forever? How do you think about that? I think that's something that we will be evaluating over time, but the short answer is as long as Ginkgo is continuing to contribute value to that customer, we would look to hold onto our equity interest in that customer. We do expect to expand the number of programs with many of our clients. If the customer reaches a point where the work that we've done, the organisms that we have transferred over are fully in the market, and at that point in time, the equity value in what we've created is fully realized, then that would be at the point in time at which we would look to be down selling our position or exiting an equity position. With these multiple components of our business model, obviously there can be some complexity on how and when it shows up on the P&L. I thought it'd be helpful for Marie, just walk us through some of the accounting. Mar, can you help investors understand sort of what they'll see over time as the model matures and as these downstream value elements start being realized? Royalty and milestone-based revenues, those are the more traditional revenue streams that most of you are probably familiar with. The equity stakes, that is a little bit different. Ginkgo is a little bit different in that. You may or may not see that equity on our balance sheet. That's because of the accounting rules and whether the nature of the company is a public company or a private company. You certainly will see the value of that equity come through downstream when we sell the shares. That could come through as other income or revenue at that time. Because it is so unique, it's a little bit difficult to forecast. From a fulsome accounting perspective, it's difficult to see that in advance. For that reason, we're going to continue to provide more information and more clarity throughout the course of this process to help you become more acclimated with it, since it is a bit unusual. How would an investor, if it's not going to show up on our balance sheet, how would investors be able to think about the value of programs where we might have an equity position? What can they look at? A couple of things. First of all, you should look at our program counts, and that's a key metric we're going to be talking a lot about. How many new programs have we signed up in this time period, this quarter, or this year, and what's our cumulative program count? Because remember, even if we're done performing R&D services for a given program, we still have a right to either a royalty or an equity interest. The cumulative program count is an important metric. Then the $15 million net present value number that we've talked about, again, that's based on real data and historical data, but we will have more experience with that data point as well in time. With that, I think that was a really helpful overview of some of the questions that I get a lot, and I know you get a lot from investors. Maybe now we can just flip to a quick review of the historical financials. I'll pass that to Marie to help walk us through that. Marie? In 2020, we increased total revenues to $77 million from $54 million in 2019, 40% growth. The drivers of that growth included our increase in foundry revenues, as well as the launch of our biosecurity offering. Again, foundry revenues represent what we get paid from customers for usage on those foundry programs. This is the most predictable component of our revenue, and we typically earn foundry revenue from a particular program over the course of 2 to 3 years. We increased the total number of active programs generating revenue from 36 in 2019 to 49 in 2020, and that is despite the impact from COVID-19. This includes 18 new programs in 2020, and in total, we worked with 22 active customers. Our loss from operations in 2020 increased to $137 million. That's driven mostly because of our higher R&D expenses. Those higher R&D expenses supported the growth in foundry operations as well as enhancements in foundry and the Codebase assets and, of course, the development of this biosecurity offering. We ended 2020 with about $380 million cash in hand. Let's talk a little bit about how we thought about internally building up the projections for the business, both for 2021, of course, but then the longer-term projections. How do you think about it? What gives you confidence in those numbers, and what should we be looking for? If you look at our projections in 2021, we're expecting $150 million of total revenue, and that comprises about $100 million of foundry revenue and $50 million of biosecurity revenue. We based the 2021 projections on 2 areas where we had high confidence, which was, firstly, number of programs that were already in backlog, and therefore we have to just execute against those. The budgets have been established, and the work had already been signed up with the client. Secondly, the conversion in the near term of a portion of our pipeline, which was most probable. That's really what 2021 is based on. Just because of the nature of our business, we have pretty good visibility into the next 18 months of revenue at any given point in time, and that's just because of the programs that have been signed. There's a relatively long sales cycle in our programs. We sort of know what's realistic in the next 18 months. When you go outside of 18 months in the longer term, you can see that by 2025, we're expecting to be bringing on at that point in time about 500 new programs on an annual basis onto the platform. Seems like a big number when you look at what we're doing today. It is a large increase. When you triangulate it against the total number of R&D projects that are being done today that could be done on the Ginkgo platform, it's really a very small market share. When you then layer onto that the fact that Ginkgo is participating across all industry verticals, it's not just biopharma R&D projects that we're trying to bring onto the platform, the agriculture, the food tech, et cetera, just the vast addressable market. We again get confidence in that 500 number. Finally, again, just as a reminder, with each new program that comes on the platform, we improve our cost structure because of the foundry scale economic. That's an improvement we expect to be passing along to our customers in terms of some of those cost savings. Secondly, the codebase gets more valuable. So we think when you look at the whole picture together, we think that the 500 program count by 2025 is very achievable. Just to give you kind of a footnote before we wrap up on financials, really just two points. The first is that the projections, a reminder, the projections I just discussed do not include any downstream value share revenue, income, or cash flows. The second footnote is around our biosecurity revenue. You will see that we are not projecting out our biosecurity revenue beyond 2021. The 2021 projection of $50 million is based really on just the bookings that we have to date. Because of the significant uncertainty in how that market is going to develop, we just felt it best not to try to predict it. However, we do believe there is a long-term business in biosecurity. We believe we are well-positioned to be a leader in that business. As soon as we have more definition on how that market is evolving, we would anticipate providing projections on how that will trend as well. Well, thanks again, Mark, for joining me here and helping answer some of the questions that we get a lot from investors. We're going to flip over now to doing the Q&A. If you haven't already, feel free to submit any questions via the OpenExchange platform or via Twitter at Ginkgo. I'm assembling those, and we're going to turn over in just a moment to the executive team that you've met over the past few hours to answer as many of those questions as possible. Thanks so much again for joining us, and we look forward to hosting you in person hopefully again soon. Well, that was pretty impressive. Hi, I'm Harry Sloan from Soaring Eagle. Thank you for joining us the last couple hours. You've had a chance to learn about Ginkgo's technology platform and its very disruptive model. We at Soaring Eagle were attracted to Ginkgo because we see it as a true category of one company. That's a company that's not only the leader in its field but is actually the creator of the field itself, which is synthetic biology. We've partnered on this deal with Dr. Arie Belldegrun. He's a leader in the field of cell and gene therapy. We believe that our team at Soaring Eagle is uniquely positioned to lead this investment into Ginkgo. Over the last few months, we've been so impressed with the sense of mission shared not only by the five founders, but all the employees we've met at Ginkgo. You've now had an opportunity to meet this team and learn more about the company they've built and will continue to build. We're excited to significantly capitalize this company for growth, building on the truly unique platform of the foundry, the code base, and again, this incredibly talented team. We're confident about the value we believe Ginkgo will create, not only for the investors, but also for the world, driving health and sustainability at a global level. Again, I thank you all for attending. Well, thanks for spending a few hours with us today for Ginkgo's first Investor Day. Ginkgo is a mission-driven company with a long-term vision. We've been really fortunate in the investors we've had to date, who really believe in that vision, believe in the team that was pulling it together. We're excited for a new phase as we take the company public and bring along a whole new set of investors that share our vision for how biology can change the world. Thanks again. All right, welcome back, everybody, thanks for staying with us for the last few hours for our very first Investor Day. I'm thrilled to be here with my friends and colleagues at Ginkgo, who you just heard from over the past few hours, who are going to answer some of the questions that have come in through the platform and via Twitter. Jason, there was one that came in that was one of my favorites, I'm going to throw the first one to you. Vince on Twitter says, "Listening to SRNG at Ginkgo's Investor Day. Pretty sure 95% of investors have no idea what these people are talking about, even though they're trying to explain the science. Everyone is waiting to hear the business revenue potential as opposed to the science behind Ginkgo." Casa Nicolitas says, "Can you cover the basics in your own words? What does Ginkgo sell? To which customer? For what cost? What's the business model in a couple sentences?" I'm going to give you 30 seconds. Let's see if you can do it there. Awesome. I love it. Yeah. The core idea behind Ginkgo is cells run on digital code in the form of DNA, kind of like computers run on zeros and ones, cells run on A, T, Cs and Gs. Because you can program them, we should expect there's going to be app developers, right? Folks who want to program cells to do new things, take those to market, and make money doing it. Ginkgo, simply, we're an app store, right? We provide tools to folks that want to program cells to do new things, to make it easier and faster for them to do it, we help them bring those cells to market. In exchange for that, they pay us. They pay us both while we're developing the cell, and we get, just like you would in a mobile phone app store, we get a piece of the value of the app. That's how we make money. That was pretty close to 30 seconds, so I'll give it to you. On StockTwits here, Odd Marketable Securities says, "Fancy video with lots of fancy words. Some fancy words I haven't heard them say. $15 billion and $150 million of revs. They're doing a lot of talking to not address the elephant in the room." Let's address the elephant in the room. How do we get to a $15 billion valuation with $150 million of revenue this year? Yeah. I'll touch on this app store idea again here. There's two ways we get paid. We get paid while we're developing a cell for a customer. They pay us, effectively, fees for using the facility I'm sitting in front of, and that Barry and Kristen walked you through earlier, our foundry, on a usage basis. Right? In 2021, we guide towards $100 million, out of that $150 is foundry revenue from using that facility. Okay? Straightforward to understand. The app store side of the business, though, ultimately, we are going to get a piece of the value of those program cells for customers back to Ginkgo. That's a new idea in biotech. It's actually been a very successful business model in tech, but in biotech, you haven't really seen it. People tend to develop their own apps, right? If you're a Genentech or a Roche, you've got a drug, you own that thing 100%. You're really a product company. Well, Ginkgo's not a product company, we're a platform. When these apps get developed, we get a piece either through royalties or through equity in the companies that are developing those applications, and that comes back to us in the long run. Right? In the near term, that's not where the revenues are coming, but over time, as those apps go to market, that's going to be, in my view, the lion's share of the value of the company. That's not included. If you look at our projections in the financial model, you and Mark walked through this in the video, that's all foundry revenue. It doesn't include that value coming back to us through royalties or equity in the applications. If you look at our numbers, we ended last year with 48 cell programs like that. We're adding 23 new programs this year, 7 just in the first quarter. The rate we're adding these is going up dramatically. When you see news, for example, last week, Motif FoodWorks announced a more than $250 million fundraise. That's great news for Ginkgo shareholders because we have a good chunk of equity in Motif because they're an app developer on our platform. When Cronos says they're going to market with a cannabinoid, that's good news for Ginkgo, right? So that's the part of it that ultimately is justifying the $15 billion valuation. It's really where the majority of the value of Ginkgo's going to come from in the future, that app store. Great. Thanks, Jason. A bunch of questions have come in on the platform around, I think, folks who are building their models and trying to get under the hood and get under the weeds. Mark, I was hoping, one of the topics we didn't cover in the last session was really some of the underlying drivers of the model and in both the foundry business and the downstream, how would you guide people towards their modeling endeavors around this business? Yeah. I guess the way that we think about it is we start with foundry capacity and our ability to improve throughput in that capacity. As you know, and as we've discussed, one of the tenets of our strategy is to get more programs on the foundry. As we get more programs on the foundry, that drives a foundry scale economic. It also pushes us to make investments in technology, which gives us productivity improvements. You start with foundry capacity and how much of that do we have and how quickly can we add to that. We're then sort of focused in getting more programs on the foundry. That drives a scale economic, that builds Codebase. All of that in turn enhances the value proposition. That scale economic results in a cost savings that we can pass on to our customers, and so we do that. It also, like I said, enhances the Codebase, which makes what we're offering more valuable, and it makes the next project easier and faster. Collectively over time, and we've talked about that flywheel, what you see is the revenue is increasing and us taking on more programs and the overall company profitability starts to improve. As you've seen, we're expecting to start approaching breakeven on the EBITDA line around end of 2024, sort of roughly speaking. What you're seeing there in terms of the driver is really we're just leveraging our R&D and SG&A infrastructure on a higher revenue base. None of that includes the downstream value shares. The other sort of core driver of the business is that you will start to see the monetization of either royalty or equity interests also contributing to the bottom line. Great. Thanks, Mark. You mentioned that the sort of first element of the model is capacity. Barry, you talked a lot about Knight's Law. I think folks find that concept really interesting, how the hell do we keep Knight's Law going? What gives you confidence that we can maintain that going forward? What are the top challenges that you see? Great question. One we always like to talk about. I have to say that neither I nor anyone at Ginkgo can predict the future. I'll note that neither could Gordon Moore in 1965 when he made the prediction that ultimately became the Moore's Law that we know today. Instead, he saw a trend, which we have seen, and we have shown you all, and he saw no fundamental physical reason why that trend could not continue. All that was required was continuing investment driven by tremendous commercial opportunity, and we believe that the exact same conditions are true today in synthetic biology. We just need to do the work. To be more practical about the answer, Knight's Law is driven by automation and miniaturization of the way we do the work in our foundries. We have a lot of low-hanging fruit still to be captured, or still to be collected in terms of how we do that work and how we automate it, and that's just using the technologies that are mature and available to us today. As we work with our partners, folks like Twist and Berkeley Lights, and as we see how their technologies are improving, we can see how we're going to be able to continue to increase the scale and drive down the unit cost of the. work in our foundries. In the midterm, we look at those kinds of technologies for better DNA printing, better measurement of how cells are performing, greater miniaturization as being the drivers of Knight's Law. As we look to the longer term, the reality is that cells and DNA are really, really tiny, and they make copies of themselves very easily. What that points to is the ability for us to really miniaturize our operations and our work down to the scale of individual cells and molecules. In the kind of multiplex library-based work we do already, we're able to realize that potential in certain cases today, and in the future, in many cases or most of the cases of the projects that we work on. We see both near, mid, and long-term ways to continue to drive the scale and the efficiencies that are going to drive Knight's Law. Great. Thanks, Barry. Patrick, I think Codebase is always an interesting topic for folks, and it definitely is part of Knight's Law, but we don't have the same kind of historical metrics that we've been able to plot out for people around Codebase. So, we get a lot of questions around how do you measure Codebase? What metrics should we be looking for? What are you going to report on? So we'd love you to just talk a little bit about how you, as the head of Codebase, how you think about measuring Codebase and really what matters there. Yeah. That's a great question. I think we're still trying to wrap our heads around Codebase and how best to quantify it. For us, there are two key factors that we try to keep track of. One is just sheer quantity, and that's really where we leverage the scale of the foundry to make sure that we're basically sourcing, generating, and characterizing as much unique biology as we can year-over-year, right? From my perspective, we actually rely a lot on Knight's Law to say if we are actually scaling the ability of the foundry to improve the number of operations we can do year-over-year, from my perspective, that means we can continue to drive the quantity of new Codebase that we can develop. Now, how do we use that to actually help our customers achieve their goals faster? That's where quality comes in. One of the metrics we use for quality is how often are we actually reusing particular Codebase assets, right. Some really important stuff sits on the shelf for a year or more before we find the right opportunity to reuse it. Certain things we go back to over and over again, and that's what we're trying to really quantify into what we're calling Cell Development Kits, basically playbooks that we can apply over and over again, reusing valuable Codebase that has been proven over the course of multiple projects. Again, Knight's Law means that we can really deliver on quantity and mine through that for useful information and useful new strategies and designs, but ultimately, reuse is how we measure quality and something that we pay a lot of attention to. Great. Thanks. Oh, just one addition. Oh, go ahead. Yeah. Patrick, I think the CDK is an inspired name, right? This is coming out of software development kits, right? As I understand it, this is part of the package you get as part of engaging with a mobile phone ecosystem, right? If you want to develop an app, you get from Apple, an SDK, and it helps you put the button on the phone in the right place. It's existing code that makes it easier to launch an application. In exchange for that, because that's a valuable thing for a developer, Apple's getting to take a toll on those apps that get developed, right? This is very much in line, even the naming of things here, this idea of the CDK. We think the evolution of genetic engineering and cell programming, we're taking lessons from software to do it. I think this is what I'm really excited about, is these CDKs. Thanks, guys. Just rounding out the capacity topic. An important driver of our capacity is also just our operations and how well we function together as a team. Obviously, folks have seen our sort of vision for the future, and that involves a lot of growth. Reshma, this is my own question. This one didn't get submitted. I just like talking about it. Yeah, I'd love to just ask you what you see as the biggest operational hurdles and how you think about scaling up an organization like Ginkgo over the next 4 or 5 years. I think we really think about the challenges of scaling on two fronts. The first is really around our culture, right? We talk a lot here at Ginkgo about growing our culture, and that's because for a mission-driven company like Ginkgo, our team is fundamental and instrumental to Ginkgo's success overall, right? The biggest impact we can have on our team is really fostering a culture here at Ginkgo that helps us attract the best talent, retain the best talent, and really, I think at the end of the day, culture has a huge outsized influence on that team's performance, right? Again, team performance equals Ginkgo's success. We really like to think about our culture as not just who we are today, but who we aspire to be. Continuing to grow our culture as we grow the company, I think is fundamental to being able to scale effectively. I think the second front that we think about, sort of the operational challenges of scaling, is really around all the normal things like organizations have to do when they scale, right? They need to specialize roles, they need to add organizational structure, they need to introduce process, right? I think Ben Horowitz actually writes really eloquently on this topic. He talks about how you need to give ground grudgingly to this stuff, right? At Ginkgo, we really try to balance, we know as we grow, we need to add specialization, we need to add process, we need to add structure to our organization. We don't want to get ahead of our skis on that, because there's a cost and an overhead to all of those things. Striking that right balance of giving ground grudgingly to adding those things to our company as we grow is really important. We're really fortunate because we have board members like Christian Henry and Shyam Sankar, who have led fast-growing technology companies, and so they've been a great source of advice and guidance as we grow. Yeah, I totally agree. All right. Going back to Mark's answer earlier, first input is capacity, then we actually have to go find some demand. Ena and Jen, and Matt, we're lucky to have you guys on the phone because you lead our commercial business. Maybe, Ena, I'll start with you. We got a question from Vera Analytics on Twitter, saying, "How far into the future do you generally have visibility on bookings, and what are the limits on that visibility?" I might just ask you to talk about our sales cycle and process and what that looks like at Ginkgo and the visibility that Vera's asking about. Yeah, that's a great question. Thank you for that. Let me start with the deal process to really provide a bit of context to that question. When we work with a potential customer on a project, we really start with a collaborative process. We sit down with our customers to define what are their strategic requirements, and from that, we define the specific technical needs and how our foundry can actually support that. That's when we get the early start of really figuring out what the project looks like. We enter into a parallel path of the technical teams really discussing with our customer's technical team on the specific requirements under what we call a Technical Development Plan. In that Technical Development Plan, we'll define the deliverables, the milestones, the objectives, the timeline, et cetera, and the budget associated with those programs. At the same time, the commercial discussions also take place, and we have a cross-functional deal team that really drive those discussions forward, going from figuring out what the framing of the deal looks like, what the term sheet looks like, all the way to negotiating the final terms of the agreement. That includes all aspects ranging from economics and intellectual property terms. Once we complete that negotiation process and the technical teams have a defined and approved TDP in place, we then kick off the project, and that's where the commercial operations team really takes center stage and liaise with the customer to not only implement the collaboration internally at Ginkgo, but also to foster the communications to make sure that the collaboration is as transparent and as successful as possible. The deal process is not a 2-week process. It takes time to make that happen. We have a number of deals that are moving through this deal process at any single point in time. We're constantly monitoring and reviewing the status of these deal negotiations as it moves through the different stages in the pipeline. The pipeline includes deals that are ranging from very mature conversations where we're in deep discussions on the definitive agreement, all the way to early-stage conversations where we just signed a CDA with a customer and trying to figure out what the projects are that we will collaborate together, and we have everything in between. During this process, as we get more and more visibility into the technical development plan and understand what our deliverables would be, we have better indication of what our revenues will look like. By the time the TDPs are in place, we have very good visibility into the revenues that we would expect. Great. Thanks, Ena. That's the first half of the question, which is how do we win customers, we have to actually deliver for customers. Jen, you've in the past run our commercial operations team, you run both commercial operations as well as business development. We got a couple questions on scale-up and for customer success. From, I'm not even going to try to pronounce this person's name on Twitter, Topguard, I think, "What do you do to ensure a successful scale-up to commercial production? Do you have pilot facilities or do you leave all that to the customers?" From Dominic Doe on Twitter, "The bottom line, how fast can you scale a molecule? At what size tank? How many molecules have you scaled? At what size production? This is the bottleneck for synthetic biology." How are you doing that? Can you jump in? Yeah, sure. Jason mentioned earlier that we share a piece of the value for the programs we work on for our customers. That means we don't just send over a vial of engineered organisms and say, "Good luck." Instead, we have a deployment team that has expertise in the fermentation scale-up, downstream process development, QA/QC. They work both in the lab we have here in Boston at headquarters, also with some mid-scale pilot partners that we have, and also a contract manufacturing organization. We have a tolling arrangement for some products that we do make ourselves. That team has worked on a variety of commercialization efforts. We've scaled a number of compounds, including flavors and fragrances, proteins, other chemicals, many of which are on the market today. You talked about what to what scale, so that's highly dependent on the product that we're making, and so production scale is relative to the customer. On the very high end, we've scaled up processes up to several hundred thousand liters. Some higher value compounds, production scale is, some might think it's quite small. We work with customers in different ways because our customers have a variety of expertise in production themselves. That might mean that we're transferring processes directly to them, to their pilot facilities or their production facilities. That might mean we are partnering with them to find a supply chain manufacturing company that will work for them. In some cases, they're on the market to buy a facility themselves, and we've helped them do that as well. A variety of models that we work with customers. They are all oriented around getting products to market. You asked a question about how fast is this. I think time is highly dependent on scale, familiarity with the processes, what the capital requirements are, if people have a facility themselves, because we work on such a wide variety, it's hard to answer that directly. We do have a couple tricks up our sleeve to speed that up. One of that is that we have an iterative nature of engineering organisms, so often we're able to transfer intermediate strains that they can start working with right away. That both gives us feedback back into our engineering process as well as speeds up the scale-up to commercialization. Great. Thanks, guys. Maybe I'll add one small bit to it, just again, to hammer home this idea of the app store. One of the things you're going to get on the tech side by participating in an app store ecosystem is they're going to help you with distribution. They want your app to get out to as many customers as possible because the mobile phone company's going to be collecting value every time you sell that app or when someone does a purchase through it. Very much the same, GenCem Operations, we want these cells to go to market because Ginkgo's going to get value back when they do. This is an adjacent capability to our cell programming. It's kind of like, yep, Apple gives you the program, the SDK, and the distribution. Ginkgo's going to give you the CDK, and we're going to help you with deployment and fermentation through our partner network. That's 100% in line with our business model here. Helpful clarity. Thanks, Jason. You're getting good at the 30-second explanation. Maybe we won't get those comments on our next Investor Day. We love those comments. Thanks, Ena and Jennifer Wipf, for the help understanding how we work with our customers and come up with those collaborations. Maybe just we can now touch on a couple areas of growth that I think are really capturing everyone's attention, and those two sectors are pharma, which is certainly a real growth area for us, especially over the past year, and then biosecurity. Maybe, Ena, starting with pharma, we got a question also from Vera Analytics. A lot of questions from Vera Analytics. What areas can Foundry be most readily applied to right now in the biopharma sector, and what is Arie Belldegrun's vision? Arie is unfortunately not here with us, although we're thrilled he's joining the board. Ena, can you talk a little bit about how we're approaching pharma and what pharma sees in our platform right now? Yeah, definitely, thank you again for the question. We're super excited to have Ari on board. We're really looking forward to working with him and getting his insights and advice into some of the areas that we're really excited about. This is huge for us. There are many areas in pharma that we're really excited about, and it ranges everywhere from the drug discovery and development process at the front end to the manufacturing process at the tail end, once a drug candidate has been FDA approved. Just to give you an example of some of the projects that we've done so far. In the area of mRNA vaccines, which now we all know how valuable they are and what they can do, we've worked with Moderna, and we're working with others as well in the space in the production of key raw materials in the manufacturing of mRNA vaccines. It's going to be an area that we will continue to focus on, and we're really excited about the different possibilities of using the platform to improve the manufacturing process for these important therapeutics and life-saving therapeutics in many instances, especially as those are being used for cancer. We have a deal that we announced not too long ago with Biogen, where we are developing a next gen AAV production platform for gene therapy, and that's a really exciting area for us to be digging deep into. We previously have signed a deal with Roche, where we use our genome mining platform to discover novel antibiotics. That is less in the manufacturing side and more in the upfront drug discovery and development side. Along the same category of drug discovery and development, during COVID-19, we worked with a small AI-enabled drug discovery company called Photion. They are now acquired by AbCellera, where we used our foundry to help express and screen thousands of antibody candidates that they have uncovered during their computational process and find those that are neutralizing against COVID-19. That's an exciting area that we look to do more in the antibody discovery and development area. We're also working with others to improve the manufacturing of APIs, small molecules, and biologics. We're also excited about cell therapy. There's a lot we can do in the area of cell therapy, whether it is to optimize the CAR-T constructs to make them ultimately more efficacious and more manufacturable, as well as working with manufacturers of cell therapy to help make their process more robust. The way we see pharma is that as the pharma sector continues to use biology as a way to develop novel therapeutics or discover or improve these newer modalities, we'll continue to see new applications of the Ginkgo Foundry to help solve specific biology cell programming problems. What we're seeing is precisely that. As more of these new pharma companies and big pharma companies are looking for specific ways to address the near-term challenges, they now see that cell programming is a very valuable enabler to help them get to their ultimate goals. Anna's on mute. It's never too late in the pandemic to figure out how to unmute yourself. That's one really important growth area for us, of course. Thank you, Ena. The second area that's obviously been newer and really impactful is biosecurity, and specifically this year, K-12 testing. Matt, I'd love you to talk about. Another elephant in the room, I think, is what happens to biosecurity when COVID's over? I think we're all hoping and praying that life gets back to normal. What happens to this business in 2022, 2023? Yeah, thanks, Anna Marie. Look, I think the first part of this is everybody's experience. I think it's very clear that globally, COVID has shown us the need for this forward-thinking, technology-first integrated approach to biosecurity. Biology has caused massive damage over the last year, it's something that we feel very strongly and have been working on as a team for the last 15 months that we can do something to help. That's a pandemic moment, right? The second piece is really important if you think about building a biological engineering platform, doing what we are doing, building an app store, you use the digital revolution as a metaphor, right? Cybersecurity is a massive business to enable the digital ecosystem to work. There will be a massive industry at some point in biosecurity to power this biological manufacturing revolution. That is something that we feel very strongly about from a platform standpoint, that because biology is so powerful, we also need to be building the tools of biosecurity for that purpose. For us, there's this two-sided mission orientation to build the platform in a secure and transparent and caring way with biosecurity tools, but also to help respond to pandemics. This is not the last pathogen that will have pandemic potential. The direct question of what happens to the business is really an interesting one. It's pretty clear to us it's a matter of scale and timing, not really of whether it will develop. We're seeing indications that governments are taking the response to this pandemic very seriously. Private companies are thinking about what biosecurity looks like. In the U.S. alone, we think that the reports are $16 trillion of economic output, GDP loss due to this pandemic. People are saying we should spend $20 billion-$40 billion a year to protect the world from the next pandemics. We're one of the major providers of K-12 surveillance testing across the country, something that's a new thing that people haven't done in the past. We're excited about it, but we're also cautious because we're still in the midst of the pandemic, right? From a standpoint of what we're looking at, how we're thinking about it, how we're guiding our partners and otherwise, it's both of those. Excited, important long-term mission component, and being cautious about setting how and on what time that will become a really large and robust market. Ultimately something that we care deeply about and are spending a lot of time on. Thanks, Matt. A second element of care that's I think really important to us relates to a really nice question that we got in that says: How and where do you draw the line with requests either from, and this is for you, Jason, from either commercial or government sources that may raise ethical concerns because of the potential uses from the results? Are you prepared to deny requests that cross that line despite potential revenue losses? Yeah, this is a super good question. Matt touched on this. We do think it's really important to note that we do care how our platform is used in the world, right? As we enter an era where you can program cells like you program computers, that's a big deal. Biology is responsible for our food, our atmosphere, clean water, as we're living through this pandemic, our public health. Starting from a footing that we do care what happens with our platform, it isn't just as simple as, well, whatever someone pays for. It is an important line to draw. I'll point out, one of the things that was really interesting during COVID. Actually, I think Governor Patrick touched on this during the Investor Day presentation. He said it's a false choice between doing good and making money, being a successful company. It's not quite so simple. I agree with that. I think people frequently imagine, okay, the thing you're not going to do and not make money doing. What we also saw during the pandemic is it was so volatile. Things were moving so quickly, and there were all these questions of, like, can you do that? You would make these decisions to say, well, I don't know. Is it going to get schools open? Is it going to help this thing in society? Right? Those are caring how your platform is used, too, right? It can also be ways that would actually lead to expanding the business if it's the right thing to do, right? I do think this is an important topic going forward. I'm not going to pretend we have it all figured out. It's going to be a collective question for society, how we want to deploy engineered biology in the future. We want to start by saying we care how the platform is used. Thanks, Jason. We're just about out of time, so I'm just going to do a couple more questions. The next set are for me, but I just like the Twitter handles, so I'm going to read them all. It's around the process here for the SPAC transaction. @SPACdoggydog wants to know when we expect the ticker to change to DNA. A couple other folks asked, what's the status of the S-4? When do we believe the final one will be filed? How's the process going, and when is this expected to close? Nothing at this point that would indicate any change in the timing. We're still expecting to close in the third quarter of this year. We have received the first round of comments from the SEC and would expect to file our first amendment sometime next week. We can't control the timing of SEC review, but still expect that we'll be closing in the third quarter. Obviously, at this point, can't provide a precise date, but we'll update folks as that goes. The last question here is for you, Jason. They're 2 that are related. Kosta Michailidis wants to know, how long till I can code up a full-on fire-breathing dragon in my garage because then I can launch my dragon-toasted bagels business. Chris Oswell would like to know if he can be the first one to fly a dino. Yeah. 20 years Yeah. That's Kosta then. Are you making Chris a promise? Defer to our Head of Codebase, Patrick, the man who's designed more synthetic DNA than anyone on planet Earth. Patrick, what's your estimates on dragon? I'll add a ±5 years to that estimate, just to have some error bars. What did you say, Jason? 20 or 25? Yeah. All right. 15-25 years, Kosta will be able to code up a full fire-breathing dragon in his garage. Yes. Chris is going to be able to be the first one to fly a dino, or you're going to reserve that right? I think we'll have to have a charity auction. Oh, no, I like that. Okay. Charity auction. All right. You heard it here first. You could apply for a job here at Ginkgo. If you want to be the first one on the dragon, you should be working here. Yeah. You need to make the dino. Flying dinosaurs is Chris's question. Yeah, you need to make the dinosaurs. Okay. All right. Well, I know we're about out of time here, and everyone's spent a lot of time with us today learning about the business. Just want to say a heartfelt thank you to everybody for joining us today and spending your time learning about Ginkgo. Jason, I don't know if you have any parting thoughts, but we're wrapping up the day here and look forward to being able to host you guys in person hopefully next year. Thanks everybody for the time today, really. It's wonderful to have a chance to speak with you all.