Ginkgo Bioworks Holdings, Inc. (DNA) Earnings Call Transcript & Summary

Hi, everyone. I'm Anna Marie Wagner. I'm the Senior Vice President of Corporate Development for Ginkgo Bioworks. Thank you so much for joining us today as we announce the business combination between Ginkgo and Soaring Eagle Acquisition Corp. Today, you'll hear from Jason Kelly, our Co-Founder and CEO; as well as Harry Sloan, the CEO of Soaring Eagle; and Dr. Arie Belldegrun, the founder of Kite Pharma and Allogene Therapeutics, both of whom will be joining our Board of Directors. And now for the most exciting part of the presentation, I wanted to share that on the call today, we'll be making some forward-looking statements, which involve risks and uncertainties. We refer you to the slides accompanying today's presentation and the 8-K filed today by Soaring Eagle with the Securities and Exchange Commission for further information regarding these risks and uncertainties. We'll also be referring today to certain non-GAAP financial measures, including foundry billable revenue, net present value and adjusted EBITDA that we use in measuring our financial performance. A reconciliation of these non-GAAP measures to their nearest comparable GAAP counterpart, where available, can be found in the appendix of this presentation, which has also been posted to our Investor Relations website at ginkgobioworks.com/investors. Before getting to Harry, Arie, Jason and the Ginkgo story, I'll start with a short overview of what we're announcing today. More information can be found in the investor presentation. We're extremely excited to announce that we have signed a definitive agreement to merge with Soaring Eagle in a transaction valuing Ginkgo at a pre-money equity value of $15 billion. Upon the completion of the combination, Ginkgo will become a public company and will be trading on the New York Stock Exchange under a new ticker, which I'm going to try to keep under wraps for a few more days so you can certainly feel free to guess. We expect the transaction to generate proceeds of $2.5 billion, which Ginkgo will use to further scale our horizontal platform for cell programming. These proceeds consist of $1.725 billion of cash in the Soaring Eagle Trust and a $775 million fully committed pipe, including anchor investments from Baillie Gifford, Putnam Investments and Morgan Stanley Investment Management. All proceeds generated will go towards building the business. We're very excited about our partnership with Soaring Eagle. And as sponsors of the transaction, they both invested directionally in the pipe and have agreed to convert 30% of their promote interest to an earnout structure in support of their strong long-term view of Ginkgo's potential. With that, I'm thrilled to turn the call over to Harry Sloan, the CEO of Soaring Eagle, to kick us off. Harry, take it away.

Well, thank you, Anna Marie, and it's a great pleasure for myself and my partners at Soaring Eagle, Jeff Sagansky, Eli Baker to be announcing this transaction with Ginkgo today. We've had a number of successful SPAC mergers. But what we really prefer and what we think works best for a SPAC are these companies that we call category of one. These are companies that are not only leaders in their field, but actually created the field themselves. And this is certainly the case with Ginkgo and synthetic biology. Now our 2 previous deals from last year, DraftKings and Skillz, like Ginkgo also are platforms that benefited from very powerful network effects in their platforms. So when we raised the Soaring Eagle SPAC, which was our seventh, it was about 2 months ago, we were introduced to Ginkgo by one of our Board members, Josh Kazam, who is partners with Dr. Arie Belldegrun, who you may know is one of the most successful biotech founders and industry leaders. He is behind -- he's the founder of such companies as Kite, Allogene, Kronos. He probably has more breakthrough therapies approved by the FDA in the last decade than anybody including immunotherapy with Kite. Anyway, it was with Arie's very deep knowledge in life science and his excitement about Ginkgo, which caused us to decide to partner, which is kind of unprecedented with a SPAC where the SPAC partners with real industry expertise. And together, Arie and us are doing this transaction. We're both going to join the Board. We're both investing heavily in the pipe as well. So we feel, Arie and I, that by raising this $2.5 billion, the $1.725 billion from our SPAC and the $775 million pipe, $2.5 billion total. By raising that money, we're going to be able to create with Jason a massively scaled company that will continue to lead the synthetic buyout revolution, but also can create deeper moats around the business. It's been a terrific experience for both Arie and I getting to know the 5 founders, who have been together for 20 years of Ginkgo, but not just them, all of the employees share this sense of mission and purpose. And beyond that, they also have a very specific execution strategy. And it's that strategy that Jason Kelly, the founder is going to talk to you about. But first, I want to turn this over to Arie also to say a few words. Arie?

Thank you, Harry, and good afternoon. My name is Arie Belldegrun, and I'm an academic physician and a scientist and in the past 25 years, involved in building biotechnology companies with the sole focus of bringing innovative and life-saving therapies to patients. In that context, I'm excited to join the Ginkgo family as a Board member with the hope of expanding the opportunities to life science by using the state-of-the-art technologies available at Ginkgo to assist biopharma companies and expedite their drug development. We live in an era of revolution in biology and in life science, which is not only driven by better understanding of fundamental molecular genetics but also by technological advancements of tools like DNA sequencing, gene editing, DNA synthesis, bioinformatics, machine learning and computational biology. Synthetic biology takes advantage of all of these technologies to engineer cells, whether they are yeast cells or mammalian cells and reprogram cellular DNA. It has a potential to create technological advancements in everything from therapeutics to food to materials. I believe that the greatest future, however, for this opportunity of synthetic biology is in the area of biotech, drug development and drug manufacturing. The opportunity for ultra-high throughput screening of compounds, selection of drug candidates, rational therapeutic design and the opportunity to effectively synthesize therapeutics from cells at a scale will increase efficiency of drug development and significantly reduce cost of production. Areas like engineering leading medicines, so-called cell therapy, gene therapy, engineering proteins like cytokines and biologics will all have benefits from synthetic biology. My personal interest in synthetic biology dates back over 5 years ago when we made our first entry to this space by acquiring technology developed in academia at UCSF, University of California, San Francisco, in the area of CAR-T or chimeric antigen receptor T and cell groups. T cell, cell groups. It is very quickly became apparent to us that while powerful, the technology is labor-intensive and requires significant resources beyond the capability of most small biotech companies. So when I first visited with Jason Kelly, the foundry at Ginkgo, I was impressed by the platform developed there to engineer biology and the investments made in software, in automation, in robotics, while incorporating the latest technologies in gene sequencing, DNA synthesis and all the rest is technology that I've described. And I thought that I would buy into this great vision of the founders and their capable team behind Ginkgo. So Harry, I'm so pleased to be working with you together in developing this vision.

Arie, thank you for bringing this to us. And now let me turn it over to Jason Kelly, the founder of Ginkgo.

Thanks, Harry. So I'll give a little extra color on the Eagle folks. It's obvious we talked to a bunch of SPAC sponsors. And I think a few things got us really excited to work with the Eagle team. So number one, adding Arie to the team is a huge value driver for us here at Ginkgo. So in the last year, we've done more and more in the area of therapeutics, starting with our work in COVID-19 vaccines and expanding from there into more and more in nucleic acid therapies. And Arie is really sort of -- just had such a brand in cell and gene therapy. And if you want to do the kind of large commercial partnerships that we do with pharma companies, you need breakthrough technology and you also need credibility with that community. And so we've got the technology here at Ginkgo and Arie gives us a big speed-up in terms of speaking the language of sort of big pharma, big biotech to get these deals done. So thrilled to have Arie join the team. Also the Eagle folks invested directly in the pipe with their personal money. We'd like to see people putting their money where their mouth is. And then finally, they've been doing SPACs for nearly a decade. So they're operationally excellent at this, and we want to get back to building the business. So velocity in the process here was really important. So Harry and Arie and the team really thrilled to be working with you on this. And so I'm going to dig in now a little bit on sort of the story of Ginkgo. I'll share a little bit on my background and then highlight some of the key sort of competitive moats around the business, how we're planning to scale the company and also some of the key KPIs for us as a public business. So a little on my background. So I was originally technically trained. I did my undergrad at MIT in chemical engineering, stayed on for a PhD in biological engineering. And that was where I actually met the other founders of Ginkgo. So there's 4 of us doing grad school together. And then the fifth founder was a professor at MIT, Tom Knight, and I'll show you a picture of Tom I quite like. Right here on the left. This is Tom in 1972, the early 70s at MIT. So Tom was a professor in electrical engineering computer science. And to give you a sense of the era, that machine in the middle of the photo there is a mini computer, right? So Tom came up doing punch card computing, mainframes, early ARPA network at MIT, taught the semiconductor design course for many years, dyed in the wool electrical engineer. Mid-1990s, he decides interesting thing to program in the future not going to be computers, it's going to be cells. And his core insight was, look, inside of every cell is digital code in the form of DNA, right, A, T, Cs and Gs, it's not 0s and 1s, but you can read that code with DNA sequencing, genomics, and you can write that code with DNA synthesis, DNA printing. And if you can read and write code and you have a machine to run it, well, that's programming, right? And so Tom, to his credit, in his 40s, starts taking undergraduate biology lab classes at MIT. He sets up a wet lab in the computer science building and shifts his focus from programming computers to programming cells, right? But he's still the same guy. So when we looked at the sort of biotech industry and how we did this work, he recognized certain similarities to what he had seen in software. So when he looked at the computer industry, he noticed, the end applications were often market specific, right? So you had certain software for electronic medical records or for something in media or telecom and so on. But the low-level tools that you use to program a computer, okay, so think the programming languages, the operating systems, the chips that executed the code, well, those were common across all markets. And Tom's view was, well, the reason for that was that at the heart of the computer was common code, right? All that software at the top, all ran on the same low level 0s and 1s on the computer. And so when he looked at biology, he saw the same thing. At a low level, every cell runs on DNA. It's A, T, Cs and Gs, it's common across all of life and the underlying machinery in those cells that execute that code also the same. And so why was it that in the biotech industry, you had each company developing its own sort of custom technology stack vertically rather than big horizontal platforms like we saw in computing. And so Tom's view was, it's common code, we have to build those platforms. And so he really set us on that journey. It was an old picture of us here at MIT, but we met Tom in 2002, and the founder has been working together that whole time on basically the same problem. What is the core technology that makes it cheaper and easier and faster to program a cell, right? What application? Who cares, right? That was never really what motivated us, right? The underlying platform, what was the motivation. Now today, fast forward, Ginkgo has $100 million joint venture with Bayer Crop Science to engineer microbes to produce fertilizer, right? That's a $70 billion market, 4% of global greenhouse gas, big impact and big market opportunity. We work with Roche in antibiotics. We did a Sprint project with Moderna last March around vaccines. We worked in the animal-free meat space. Really exciting end applications that we're quite proud of, but what gets us up every morning is the underlying platform that makes all those applications possible, okay? So I wanted to land that because that impacts our business model, how the technology gets built and everything else is really rooted in this fundamental idea that we are a platform-first company. So I'll make one other point about this as to like why we're taking the company public now. So COVID-19, like I said, this is a silver lining, but there is an impact of COVID-19, which is that biology is on the public's mind, right? If you look, proteins are on the cover of New York Times, right? I was on 60 minutes 3 weeks ago. My parents know what PCR is all of a sudden. And if I want to explain cell programming to people, I can explain that you got a piece of mRNA code put in your arm, it's going to turn yourselves on, make a little protein and set up your immune system to get us out of this mess, right? That is a visceral opportunity to communicate with the public about cell programming, and it's a great moment for us to come out as Ginkgo and say, listen, we're going to make that common platform, that sort of Amazon Web Services, that Windows, that universal infrastructure that makes it cheaper and easier and faster to program cells. And so I do think it's a unique moment. I'll also point out computers are amazing, right? They're programmable machines, they get better every year. But at the end of the day, they move information around, right, they move bits. And so if you look at the industries they disrupted, it was all the information-based industries, media, telecom, finance, advertising, things like that. What they didn't disrupt, hamburgers, right, physical goods industries. Biology, on the other hand, is programmable. When you put a different code in, it does different things. But it doesn't move information around. It moves atoms around. And so if you think about the industries that are going to get disrupted, it's all your physical goods industries. And these are some of the biggest sort of environmental and social challenges we have. If you look at the UN sustainability development goals, they land in these areas of pharmaceutical, biotechnology, industrial and environmental cleanup, food and ag, consumer technology, electronics manufacturing, things like that. All these physical industries are ultimately going to have a much bigger impact from cell programming than we ever saw from computer programming. And so from a standpoint of ESG and having impact on these bigger problems, I think cell programming is one of the best tools in our toolbox coming up. So here's a slide that explains a little bit about kind of the market. So for folks that are deep in the life sciences sector, you can see at the top, a set of our customers. At the bottom, we have our sort of like technology suppliers that we would roll into a common horizontal platform. And I'll talk in a minute about what that platform looks like, but just to put us in the ecosystem. All right. So I want to talk a little bit about the unit of work that we do for our customers, what we call a cell program. And the basic idea -- and actually, I'll give you an example from one of our customers. So -- as Motif FoodWorks is a company in the animal-free meat space. So to give you an idea of kind of what cell programs are capable of. So if you're familiar with Impossible Foods, if you ever had a bite into an Impossible Burger, it's a veggie burger. You bite into it, it bleeds. That's a bit weird, right? There's not a lot of blood in plants. So where are they getting that from? And so what they've done is they found the gene for hemoglobin, what makes blood red, the protein. And then they took brewer's yeast, the kind of yeast you would use to make beer, and they take that DNA code of the hemoglobin, they put it into the yeast. They brew it up and effectively a brewery except instead of beer coming out of it, hemoglobin comes out. And then they add that back into a burger and suddenly, it smells right and tastes right and cooks right. The Impossible Whopper at Burger King nationwide in the U.S., right? That is, in my view, the first really truly disruptive product in the beef space in probably 100 years, enabled by, at the back end, a cell program that has producing a magical ingredient in there that gives that burger its meaty taste, right? And so Motif wants to do a similar thing. They want to pursue a whole range of different animal proteins that otherwise wouldn't be available in plants and then make those available to food developers, so that we can have more Impossible burgers. And so they came to us with that SPAC, get me a yeast that produces these animal proteins. And so we did a 1-year and 9-month project where we went looking through hundreds of different cell -- different proteins. Identified ones of interest to Motif, put them into that yeast, optimize the yeast. So we made lots of changes to the genome, the code of the yeast to make it produce more of that protein. -- then within a year, we were producing enough protein that they could put it into applications testing like a yogurt or a burger. And then within another 9 months, we had tuned that yeast up enough to produce ultimately kilograms of that product in a commercial setting, so like in a pilot scale setting. And so that project, that's sort of 1 year, 9 months. That's a cell program. And at the end of it, we gave our customer 2 things: one, a tube with that yeast in it, with the genome that has the code that does what they want for their SPAC; and then a licensing agreement that says you can use the IP that's embedded in this code, all right? And for that, we get paid in 2 ways. So during the 1 year and 9 months, we get paid on a usage basis. Think like a cloud computing provider you would pay for use of their data center. Same idea, except instead of a data center, we're charging for use of our foundry, right? So right behind me here in Boston, we have about a 200,000 square foot facility, I'll show you a video of, where we've use automation to do lab work. And so we charged to kind of do that work during the 1 year, 9 months. And then at the end, in exchange for the code that we've written, we would take a value share on the end products, okay? And so that could either be a royalty on the sale of that animal protein or in lieu of the royalty, in the case of Motif, we could take equity in the company instead for the work that we did in the lab. And so that gives us some way to reach into the end value of the app. So those are the 2 ways we make money from a cell program. And I'll show you in a minute the kind of TAMs for those opportunities and also how that's looked over time for us in terms of money that's come into Ginkgo. All right. So before I do that though, why does somebody work with us to do a cell program in the first place, right? Why not do it themselves? And the reason they work with us is, we have 2 proprietary assets that they want to get access to. One is what we call our foundry. And so I talked about this already, but it's basically -- if you want to get a PhD in bioengineering in MIT, like I did, it's basically 5 years of standing at a lab bench, moving clear liquids around a bench by hand, all right? It's not -- it's real work. And so what we've done is we've taken that work, that lab work, and we've moved it on to robotics and automation, and we've standardized it. And I'll show you some stats from that in a minute. But importantly, by automating it, we've created a scale economic. And this is kind of similar to being an auto manufacturer or a chip -- microchip fabricator, like the bigger your factory, the lower the cost to do the work. Same exact idea in our foundry. And we've been roughly tripling the output of that facility and having the cost for those lab operations annually, and I'll show you some data on that in just a minute. And then the second asset we have is what we call our code base, and it's a data asset. As we do these projects, we learn more and more about how to program cells and then Ginkgo retains that IP and data, so that we can use it for future projects. And so every project we do actually benefits customers in the future because we can retain some of that data and learnings and share it across projects. And so that's why people come -- can work with us is to access those 2 things. And so just to show you a little viscerally, what's going on in our foundry, here's a video of our new facility, Bioworks 5. [Presentation]

So what you're looking at here are these independent cars that can move on these magnetic track. It's a material transport system, and it allows us to move that little plastic plate you just saw. There is one example of a piece of laboratory consumable that you would use in doing the lab work of cell programming. That car system brings those little plates over to these green robotic arms that you see here and what we call a work cell. It's basically an arm that can move that laboratory plateware onto a set of equipment. And that equipment could be different things on different work cells. Sometimes it's something simple, like a plate sealer and desealer, something like a centrifuge or a piece of analytical equipment. At the end of the day, there is sort of a roughly standardized set of lab equipment you use to get your work done. And we want to make all that equipment available on different work cells around a facility like this. And so what you'll see as you look down one of these lines here like you just saw, a line of cars moving on the track and then alongside that track a set of work cells. We have 3 lines like that running through Bioworks 5, it's in about an 18,000 square foot room. And the key idea here is to take the sort of human error out of the laboratory work associated with cell engineering and to drive scale. And so this is our newest facility. In fact, in the numbers I'll show you in a minute, none of the contribution -- Bioworks 5 does not contribute to those yet at all. There's a facility that will be coming online later this year. And so the gains we've seen have been actually using what we call walk-up automation, like you saw some videos of scientists putting plates onto machines, right? That's a higher level of labor utilization. We have probably about 20 to 30 people running one of our current walk-up automation facilities. In a fully automated facility like this, it would be more like 4 or 5 operators. So we get more leverage out of the infrastructure and reduced operator error. Scientists can spend more time on doing design. And so that's an example of our newest facility and where we're headed, one of the key drivers for reducing costs, which is automation. So I just want to talk for a minute before I move on about our Board here at Ginkgo. So we're very fortunate. We have a great set of independent directors. Shyam Sankar who's the COO at Palantir and Christian Henry have both been on the Board for more than 4 years. Shyam is excellent -- is operationally excellent. The way that actually Palantir sells in the market is the sort of big enterprise deals. It's actually quite similar to the way Ginkgo does our work in terms of the commercial side. And then Christian Henry, long-time CFO at Illumina, more recently the CEO of PacBio. Christian, just long time public market CFO has helped us think about what numbers we should be tracking internally, how to have accountability around meeting those and building up that muscle at Ginkgo over the last 4 years. They'll both be staying on, Shyam as the Comp Committee Chair and Christian as the Audit Committee Chair. And then finally, our Board Chairman, Marijn Dekkers, was the last CEO of Bayer and prior to that CEO of Thermo Fisher. Now he's actually the fellow who bought Fisher and sort of created a lot of the structure of what is the modern Thermo Fisher. And so we're really lucky to have Marijn. He's been a great help with us in the strategic direction of the company. And then we're adding Arie, like I already mentioned, and we're excited about that and Harry as well. Okay. So I want to highlight just briefly the TAM, the market opportunity for those 2 sources of revenue for Ginkgo from our cell programs. So on the foundry revenue side. So when people pay us on a usage basis during that year and 9 months, like I mentioned for Motif. It's usually up to about a 3-year project. This is the market we can go after. This is a report from Piper that shows in 2020, about $33 billion being spent on cell engineering. So $21 billion on labor, $12 billion on spending at companies like Thermo, on sort of the laboratory tools and reagents. That's kind of like -- if I were to draw analogy like on-prem IT for servers, and we're suggesting, why don't you move that to the cloud? And so there is -- it's just worth noting a big spend across thousands of R&D projects happening in the biotech industry, in the chemicals, ag and pharma biotech, where people are spending money to do this work by hand. And we're suggesting that R&D budget could be better spent on foundry revenue at Ginkgo and utilizing our infrastructure, so you get more leverage per dollar. And then the second way, the second TAM for us is, again, we do that reach in, the value share on the apps developed on our platform. This is kind of like an app store business model. And the market, this is from McKinsey report from last year, is $2 trillion to $4 trillion for bioengineered products like that Impossible Burger as an example. And so we see an enormous opportunity there, and the more our platform improves, the more this market should be able to come into being. And so we want to be a big enabler of driving these bioengineered products and take a small piece of that big pie. All right. So I want to highlight one thing that's great about Ginkgo is we have validated the platform over the last 6, 7 years in terms of showing its relevance in different markets. And so we started in consumer tech, things like flavors and fragrances, industrial, environmental, a lot of products in the chemicals industry, ag, food and nutrition, pharma biotech. So you can see more than 70 programs we've done in partnership with customers over the last several years, and you can see some of those customers here, right? So we worked with some of the biggest flavor and fragrance companies. We worked with Cronos, which is -- has a large ownership position from Altria up in Canada. It's a Canadian cannabis company, so basically do similar things like that heme, except instead of producing a protein -- animal protein, we've been engineering cells to produce these cannabinoids. So instead of growing a big deal of cannabis, you would instead just run a brewery and produce those same cannabinoids to help with the cost of goods in that industry and scale. We work with Cargill and Ajinomoto, some of the biggest sort of animal feed players in the world. Genomatica in chemicals. We just announced a deal several weeks ago with Corteva, one of the biggest ag companies. I mentioned that $100 million joint venture with Bayer Crop Science to work in the fertilizer industry. We work with Roche in antibiotics and Synlogic for gut bacteria. I mentioned the project we did last year with Moderna. Enormous range of end markets and for us to work with someone, we don't develop our own products. So all of these cell programs are launched in partnership with a third party. And so that's another way, again, to kind of show that our platform has relevance in a wide range. I want to show some specific numbers from the foundry, so you get a sense of our scale, right? And so on the right-hand side, this is a key metric for us internally. It's what we call a strain test. It basically means I've made a deliberate change to the genome of a cell, so I've changed the code. I've grown it up and then I've run some test on it. And so every time we do one of those tests on an engineered cell, it counts as a strain test. And so we went from doing 10 to 100 strain tests per day back in 2015 to 10,000 to 100,000 strain tests per day now. Roughly, you can see they're about 3.5x increase annually in the number of designs we can try. And why that's important, it's kind of like software developers iterating through different versions of their code. You never get it right the first time. And so by being able to try more designs per dollar, which is what I'll show you on the next slide here, we get to have a better chance of success for our customers when we take on a cell programming project. And so if you look, the cost for us to do a strain test has fallen from nearly $1,000 back in 2015 down to the tens of dollars today. And so that falling cost is, again, a huge advantage for us in terms of value we can give back to customers, so that they can get more out of that R&D budget that I was mentioning earlier. All right. The other thing I want to mention, so that's really the foundry. I also want to talk about the code base. And the origin of the code base is actually when Tom first came into biology from computer science. And he asked the question, okay, so you guys are programming, I see that. It's DNA code, you can read and write it. That makes sense. Where are the code libraries, right? Like you're telling me you write new code, but you don't build on the preexisting code that other people have written and debugged to make your more complicated programs? And the answer is, no. You know that the state-of-the-art today in biotechnology is you pull some technology out of an academic lab and you keep tweaking it in your company and you take it to market as sort of a one-off project. There isn't this sense that you are accumulating reusable assets that have been carefully curated to make them reusable for someone in the future that didn't develop it in the first place. And that's what we've been doing here at Ginkgo. We're very deliberate about how we collect the data and do the work we do in the lab so that we can accumulate assets that we can reuse in the future for projects. So to give you an example, I mentioned this project we did for Motif. Well, we made a lot of changes to that yeast to make -- to be able to produce a lot of these animal proteins. Well, we had another company come to us recently, a company called KALO that wants to do a similar thing where you would produce sort of human proteins that might be relevant in cosmetics as an example of a project. And so what's exciting is we can use that same yeast, right? So we could bring that yeast to bear if it's relevant to the projects here to help reduce the amount of time you would need to do that R&D project. And that's because at the end of the day, that intellectual property accumulates here at Ginkgo rather than that having it split and fragmented across hundreds of different companies across the industry. And ultimately, our view is the whole industry benefits from this because there is so much -- a company in the food space doesn't care if somebody in pharma or cosmetics makes use of some genetic assets that were developed in their projects. There's no harm to them. But today, a lot of that value is lost as that code is spread across all these different companies in the industry. And so that's a real opportunity. And so this ends up being the sort of positive feedback loop with the company. As every time we add a new program, our scale goes up in the foundry, which reduces our costs. Reduced cost leads to more programs signed up by customers, which leads to more code base, which increases the odds of success. And so the more programs we add, the better we get at doing this, the more customers come to work with us. It's that value we give back to customers that allows us to have that sort of app store revenue feature where we can value share on the downstream products. And so that's really what we're spinning up. And so I'll highlight how we're going to add all those new programs because that to me is the real key driver of value for us in the future here at Ginkgo. So how do we add programs today, right? So these are a couple of indicators of sort of how we do our sales at the company. So one of the things I'll highlight is inside sales. So this is a customer, one of our older customers, and many of our customers are in the last couple of years like the nature of the scale of the business. But one of our older customers that we did our first project with 4 or 5 years ago. We went from that first proof-of-concept project to now 11 projects with that same customer. So one of the ways we're going to grow the number of programs, and you'll see in a minute, I want to grow from 23 new programs in 2021 to more than 500 new programs in 2025. One of the ways we'll do that is we'll do right by the customers we've just signed up recently. We just added Corteva. Listen, there's a big R&D budget in ag biotech companies. If we do well with them on the first projects we do, I hope 3 or 4 years from now we'll be able to grow business with them just like we did with this customer. The other way that we are able to grow business is we demonstrate the utility of the platform in an area we haven't shown it before. So this is a great example of this is the project we did with Moderna last year. That was the first time we had ever shown the utility of our platform in nucleic acid therapies. There's a lot of nucleic acid therapies out there. There's a lot in gene therapy. There's other vaccines, like the follow on work in our DNA vaccine company and so on, manufacturers. That is because we were able to show utility and then get follow-on business in that category. There are many categories like that, that Ginkgo has not yet shown where our general purpose platform could be useful, right? Again, things like antibodies, cell engineering and so on, some of the areas we're excited to move into with Arie. Those are all opportunities for us because we haven't proven the platform there yet. We run our sort of sales pipeline. I mentioned Palantir earlier. We have a large commercial team. It's enterprise sales. We have good visibility into our pipeline. And so this where we would expect to bring in new deals in 2021. We're aiming for 23 new programs. You can see there's sort of split across those 6 different markets I mentioned earlier, a little bit of a bias into pharmaceuticals. I think that's likely to be the case for the next couple of years at Ginkgo. I see enormous opportunity for us in therapeutics. It's really the biggest R&D budget in biotech today. And so I think you'll see us doing more and more in therapeutics. But we're not sort of picky, right? We don't have to have a strong opinion about exactly what market is going to be the next great market for cell programming. We need to be paying attention and good community builders so that we know when there's a new area for cell engineering, and we can go lean in and help out there. And that's exactly what we did with nucleic acid vaccines, and we see that should happen again and again if we do our job right. I'll mention we want to get to -- just to highlight it, show you the numbers, go from those 23 new programs in 2021 to 500 new programs in 2025. So how are we going to do that? So some of that is going to be showing we can work in an area, show that we can do stuff in antibodies, expanding with existing customers, taking someone who's 1 program today to 10 programs 3 or 4 years from now. Some of it is just the platform getting better, right? Yes, as we have more code base and bigger scale foundry, I can just offer more value to customers, so I should drive more demand. But then the other one is this idea of an ecosystem. And this is a picture from our Annual Meeting, Ginkgo Ferment, one of the things -- a lesson we learned from folks who have operated in the software industry, so think like the cloud computing companies today or the operating system companies in the '90s, who wanted people to develop applications on their platform. To do a good job at that, you have to build community, the community of the app developers that want to build it and are going to do well by building on your platform. And so part of that is having the best platform, which I think we will and do. Also, it is all of the other things it takes to develop and launch an app, right? And so we have an annual meeting. It's similar to what you would like -- what you see in these technology companies. Ginkgo Ferment we held our first one in 2018, second one in '19. And that -- we have been investing in a variety of ecosystem services to wrap around that platform. So we have what we call the Ferment Consortium. This is a $350 million investment consortium among some of our largest investors to back new companies on top of Ginkgo's platform. We help with manufacturing. We helped Cronos acquire a facility up in Canada to be able to manufacture those cannabinoids because they had never done fermentation before. Our team, our deployment team, we have a 30-, 40-person team there that can help app developers get comfortable with other -- with contract manufacturers and get their products made. On the regulatory side, we file our intellectual property. We are able to kind of handle some of those things for smaller companies that then give them a benefit as they're trying to launch these products. Partnerships. We have large companies and small companies at Ferment. There's real opportunities. The bigger companies want to see new technologies. They're looking for companies to acquire. And then trust and credibility. We had an editorial in the New York Times 4, 5 years ago around GMO labeling, when that was a big issue. We were been doing a ton in biosecurity over the last year, including things like K-12 testing and things like that. Like these are real opportunities to explain to the public how to think about cell programming as a new technology, just like companies in the '90s explained personal computers to people or even all the way back to IBM in the '50s explaining computers in the first place. We really see that, that's part of the job here if we want to be the ecosystem provider. Okay. So those are the ways we really want to scale up and create that additional demand on the platform. And we actually already signed, in the first quarter this year, 7 new cell programs, 4 of them were inside sales and 3 with new customers. So we're well on our way to our targets this year. All right. So we'll talk a little bit now about kind of the KPIs for Ginkgo as a public company. So as a reminder, there's 2 ways we make money on those cell programming projects, foundry revenue and downstream value share, right? And the foundry revenue comes in during that first, say, 1 to 3 years, where we're actually doing the cell programming, the development project for the customer. And then once we provide the engineered cell and it goes to market, then we would make money via either a royalty or in lieu of a royalty equity, and we often do this with smaller companies, equity in the company that's launching the product. And that's sort of our version of sort of an app store revenue stream. All right. So let me give you a little bit of historical numbers and sort of how that had looked for us in the past. So on the foundry revenue side, this is pretty straightforward, right? And so one of the things I would highlight that's interesting is if you look at the cost to do a cell programming project at Ginkgo, back in 2014, the deals I did in '14 and '15, 100% full burden cost. We were -- from customers getting less than 20% of the cost being paid in revenue from the customer. So Ginkgo was bearing 80% of the cost. Now why was that? Well, I was asking for intellectual property rights to go into my code base and also royalty or equity as a value share on the back side. And my platform going back 4 years, substantially worse than it is today, right? I've been basically doubling the efficiency of the platform annually over that period of time. In fact, if you look back on that slide where I showed the numbers, I had a dotted line that showed horizontally the cost for a scientist of the bench doing this work today. And today, we beat that scientist about 5 to 10x cheaper when we benchmark the work. Back in 2014, '15, that was actually more expensive. So it'd be more expensive than your own R&D team doing this. And so you can see we held the business model, but we gave on the economics on foundry. Now what's happened over the last 6 years is our platform has improved. We've been able to capture more of that foundry revenue spend of the cost of a program covered by the customers to the point where last year, about 80% of the program cost was paid by the customer. And we expect as our costs continue to fall, we can start to actually make a margin on that foundry revenue in the future while still retaining those intellectual property rights and that sort of royalty or equity value share. All right. And so that's sort of the left side. And the great thing about it is, it's pretty predictable, right? We are doing these deals are often 1- to 3-year contracts. We have good visibility. The majority of my revenue in 2021 on the foundry revenue side was actually booked prior to the year starting. So I like that as a public market metric for us. On the downstream value, there are sort of 2 ways we can talk about this. One is sort of predictable and one is unpredictable. I will cut to the chase and say we went with the predictable one. But to give you a sense of our choice on the -- what is unpredictable is when is, say, the project with Roche going to complete and give us a royalty on that drug sales. Who knows, right? It could be a year out, it could be 5 years out, right? Like there's a lot of variability in that process. Which programs of all the programs ongoing at Ginkgo are going to be the ones that technically succeed and which ones won't? Also unpredictable, right? What's predictable on the other hand, is how many new programs will I do in the next quarter, right? That sales cycle -- 6-month sales cycle on these large customers, we have good visibility into how many new programs we're going to do. We did 7 new programs just in the first quarter of this year, right? 4 were inside sales, 3 were new customers, right? We have good visibility into those 23 I'm trying to hit this year. I feel good about our ability to add new programs. And then what I can also say is, all right, what has a program been worth historically to Ginkgo, so that as we add a new program, investors could give us credit for that sort of implied value of that new program regardless of which one is going to be successful. And so if you look at the last -- since 2017, have been 54 deals that we either have a royalty or in lieu of a royalty equity in the partner company. And so the royalty ones, the challenge is they take a while, right? I don't get a royalty until not only have I completed the technical work but the customer commercializes that product and then I get value back on the sales, right? So only some of our earliest programs in things like flavors and fragrances give us royalties today. We don't have great data there. But on the equity, what's interesting is when I give an engineered cell to a partner, they can go off and raise money. And those investors will look at the technical asset we provide to the customer, look at the end market opportunity in that space and make a rational decision about what that means for the value increase in the company. So we get their embedded knowledge in the valuation of our equity positions in these partners. And so across those 34 programs, about $0.5 billion in equity that Ginkgo owns. And so that works out to about $15 million kind of NPV per program. right? And so one of the ways we thought about it is, okay, periodically, as we get more data in these 2 categories, we can share that out with investors so that they can get a better view over time, sort of the average value of a program at Ginkgo, right? And so if you go to the next slide, you can see the -- we can share into the future, the revenues on the foundry side. And those to us look again sort of like a life science tools company. In the future, we can take a life science tools like margins on those. And then on the program side, we can project a number of new programs. And I talked about how we want to scale that from those 23 programs this year to more than 500 in 2025. And then with some regularity, provide an update on sort of what has been that historical value, both on the equity and as we get more data on the royalty side as well. And that's sort of how we roll up the valuation. One of the things we thought about hard was what is the appropriate valuation to take income out to ultimately settle that $15 billion valuation. And the reason we landed at that was if you just look at the foundry revenue and put sort of kind of multiple similar to our like fast-growing life science tools companies for that category of revenue, that gives you about $11 billion of value in the company, depending on what numbers you pick there. And so we like that, that could carry a good chunk of the valuation of the company alone. But then, of course, you have the other half of our business. It's a $2 trillion to $4 trillion TAM in bioengineered product, and Ginkgo is going to capture a portion of that through our sort of like app-store-like value capture. And so you can look at those number of new programs, what they've been worth historically and come to a valuation for that half of our business as well and add that to the foundry revenue. So that sort of gave us confidence that we're in a good place with that $15 billion. And then we also have upside to that, both in our biosecurity business like the work we've been doing in K-12 testing nationwide here in the U.S. and then also some of the work we're doing on the vaccine supply chain work. And so those are -- that was sort of how we got to thinking about the valuation. All right. So I think I'll end it there. I want to thank you all for your time. I've been in this field for 20 years since we're back at MIT. And I think this is a really unique moment. COVID-19 has shown globally the power of biology to make it obvious to everybody. It's happening right alongside the tools to program biology getting easier and easier and easier at places like Ginkgo. And the opportunity for good in the world with this technology is enormous, right? It really does unlock, I think, solutions for challenges in climate change, in food security, water security, medicines down and down the list. Engineered biology, in my view, programming cells will be more impactful in the next 50 years than computers were in the last 50. But it is -- we're made on biology. It is technology that requires careful stewardship. And for the last 10 years, I've been building this technology here at Ginkgo with a team that has put their blood, sweat and tears into this. I trust them with this technology. I think they're going to build it out with care. And we appreciate you all having the confidence and trust in us to do that as well. Thanks again for your time.