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

Great. Good afternoon, everybody. Thank you for joining us. Welcome to the Jefferies 2021 Global Healthcare Conference. I'm Brandon Couillard, I cover the life science tools and diagnostics sector here at the firm. Very pleased to have Ginkgo Bioworks with us at the conference this year. The company just announced the becoming public through a SPAC transaction, which is expected to close in the third quarter. Certainly, one of the most exciting stories in the broader synth bio space. Here to tell us a little bit more about everything that they're working on, Anna Marie Wagner, SVP of Corporate Development. I'll turn it over to you, Anna.

Thanks so much, Brandon. And one of my favorite things about the fact that we are becoming a public company is I now get to do forward-looking statements, [ in fact, reporting ]. So I'm going to go ahead and start with that. And we'll, obviously, be making some forward-looking statements today. Those involve risks and uncertainties. We did file our Form S-4 with the SEC. So I would refer you to the Form S-4 for more information about those risks and uncertainties. We'll also be referring to some non-GAAP financial measures, including Foundry Billable revenue, net present value and adjusted EBIT that we use when we measure our financial performance. And a reconciliation of those is available as well, where it's available in the S-4. So we refer you to that. It's with the SEC under Soaring Eagle. So look, we always start everything with our mission. Our mission is to make biology easier to engineer. And what that means is it really comes from this philosophy that our founders have had, in particular, Tom Knight. There's a photo here from the 70s. Tom is the guy on the left with the beard with his master's thesis. He comes from the computer industry and lived through decades of building the infrastructure that made computers easier to engineer. And recognized in the early '90s, he had sort of gotten bored with computer programming at this time. And recognized that biology in the same way that computers run on digital code, biology ran on digital code. It just happens to be A, C, T, and G instead of 0s and 1s. And so to his great credit makes a sort of mid-life career switch from computers into biology and really wanted to apply those same engineering -- that same engineering mindset that he'd applied to the computing industry over the past several decades to biology, which at that point and, frankly, still today, it largely had been a craft art. So our founders met in Tom's lab and one of the [indiscernible] at MIT in the early 2000s. They've been working together for just about 20 years now on this mission. One of the things that gets us most excited today is the cell programming really for the first time, has become very widely understood. The power of biology has never been more apparent. Coronavirus has largely shut down the world for well over a year now. But at the same time, biotechnologies, and in particular, biological vaccines, mRNA vaccines is what's helping us overcome this pandemic. And so the awareness of the role of cell programming in our lives, in our security and our health has never been more apparent. Jason, our CEO, was on 60 Minutes just a month or 2 ago, which gives you a sense of just how mainstream this technology is starting to become, which is really exciting for us to see as we try to bring this concept to the masses. But we're, of course, excited about the much broader set of potential applications. Biology makes stuff. Whereas computers move atoms around, they communicate information, biology is the core building block of everything in our lives. Obviously, our bodies, but also our food, the raw materials for our buildings. And it is the architecture of kind of the key building blocks of everything around us. And so -- well, most people, and we're obviously at a health care conference right now, most people think about synthetic biology as a therapeutic application, a health care application, that's obviously one really important and really exciting application for biotechnology and for synthetic biology. But we get really excited about the much broader set of application areas for it and the potential for biology to really address our biggest challenges in the world today. So there are a few things that I really want to land and say, we only have a short time together. And I would refer you to, we've got many more presentations and podcasts and all sorts of things on the website, I'll refer you to those to get a deeper sense of Ginkgo. But there's just a few things that I really want to land. The first is that we are this horizontal platform. I mentioned all these different industries that we serve, and that's really unique in biotechnology. It's very easily recognizable in the computer technology industry, but novel here. And so this chart here really shows how we think about the organization of this kind of emerging synthetic biology space. We have great technology companies. We've got folks like Twist and Thermo and PacBio and Illumina, who are making the tools, the machines the underlying technologies that are solving some of the core capabilities needed for cell programming, things like DNA synthesis and DNA sequencing. And then at the top of the page, we show that what we call the program layer, the applications. So these are the actual products that are being made using synthetic biology as a technology. And so we show here some of the companies that we've worked with over the past several years, but this is a much broader space across a range of applications. Now historically, what happened was this platform layer that Ginkgo is building didn't exist. And so all of the application companies had to vertically integrate, had to build their own labs, hire -- so hire their own scientists. You had to be a biologist to know how to program biology. In the same way that 60 years ago, you had to be an electrical engineer to know how to program computers. Obviously, we've built the layers of abstraction and computing so that [ lay ] people, my 4-year-old even, can program computers. What Ginkgo is trying to do is build that infrastructure in the middle to help abstract away from the underlying technologies to help innovators access that technology more easily to accelerate the pace of innovation in this industry and enable more and more applications and really help everyone benefit from the shared learning across these applications on our platform. So Ginkgo is really taking -- we're sort of breaking down the industry and adding this platform layer to enable more applications to develop cost effectively. All right. So one of the most common questions that I get is, well, what is it that Ginkgo actually does? And so I'm going to spend just a second on this page, which helps explain that. But basically, a customer comes to us and they give us a spec. Now for some of our customers, they're really sophisticated. They've got their own R&D teams. They have ideas of how the biology is going to work, and we'll partner very closely with their scientists to have a kind of joint research development plan. Some of our customers have no biotech expertise whatsoever, but they have an idea of what they want a product to be? What they want to make? What the characteristics of that would be? And so we'll meet the customer where they are, and we'll develop what's called a technical development plan around that project to enable the production of whatever products, whether it's a molecule -- a small molecule or a protein or a series of proteins to enable their product of interest. Once we've developed that technical development plan, we then execute the work. And we execute that work on our platform, which includes 2 key components. Now, one is what we call the foundry, basically, a really big wet lab. It benefits from advanced automation and robotics and software, proprietary software that we built to help drive those workflows through the platform. And then all of that work leverages the second asset, which we call our code base, which is the sort of cumulative learning of everything that we've done over the past 12 years on the platform and everything we'll do going forward. And it includes biological tools. It includes genetic code that we can reuse, really good enzymes, really good starting places. And then it includes organisms that we've highly engineered to be really efficient at certain tasks, making proteins, for example. And so we use those 2 assets to develop sort of production host, production methods for the products of interest for our customers. And then what comes out is what we call a cell program. And that is a cell that produces the material that our customer is interested in and then the methods for production, so that our customer can then take that to go manufacture it and produce and commercialize their product. And what we really focus on is everything that's shown in the middle here. We've now done that in over -- for over 7 new major programs across a diverse set of end markets. We sort of went out these markets in reverse order of sophistication in some ways, where we started in areas that didn't have any biotech capability and where we were really -- their only way to access biotechnology in their industry, places like flavors and fragrances or petrochemical, things like that. And then we moved into more and more sophisticated markets that had have real biotech expertise in-house, but still see the value of leveraging our scale and our code base in order to bring their products to market faster or with a higher probability of success. And again, we've worked across markets with both very large market-leading customers. And these are companies that have very large, highly sophisticated in-house teams that do biotechnology, but still see the value of partnering with Ginkgo. Just small start-ups who are able to forego the investments in kind of the fixed infrastructure of a lab and then the team and really focus their resources on the things they are particularly good at, product development, formulation, branding, marketing, things like that, while leveraging our expertise to help get them products to actually go sell faster. So just as to wrap up the sort of what do we do, I'll give you a quick case study or example here. This is one of our customers Motif FoodWorks. They are making animal-free proteins. So things, dairy, egg, meat, things like that. How do you make cheese stretched the right way, and meat taste meaty and egg coagulate in the right way when it's cut. How do you utilize and access those proteins without the animal, that's Motif's mission. And so here, this just shows a pathway of a program with us. We did everything from identifying potential proteins for this project, screening those proteins to see which we're going to be -- which we're going to perform the best for Motif. And then engineering the actual pathway so that in this case, the yeast cell produces that protein at very high levels. And then iterating on that to optimize the production for them so that they could go bring that product cost effectively to market. And so within just under 2 years, they had products that they could go test with customers in order to bring new innovation to the space, which is an incredibly rapid turnaround processes in this industry. So then how big is this market? There are a couple of things that I just want to land here. We've sort of shown you how we work in the market. There are really 2 pockets of demand that we are tapping into. One is the existing market for the actual R&D work. So we make money in 2 ways: one is that our customers pay us for the work that they're doing on the platform for that sort of design, build, test cycle that they're doing, and we estimate that that's about a $40 billion market today. And it's just segregated into small labs all around the country and a few large companies, but really very siloed into their pockets. And so one of our -- one aspect of our business model is tapping into this very large market for existing R&D. But then the much larger, more exciting opportunity is for us to tap into the value of the products that are being enabled by the platform. And if the $40 billion market is the investment that is the investments that are being made to develop products, it holds that the market for those products is obviously much larger then we have justify that investment. And here, we reference the McKinsey study that would estimate that there's a $2 trillion to $4 trillion TAM for bioengineered products. And again, across a range of industries. Health care is an important piece of this and has been one of the earliest adopters of biotechnology. But across the gamut from food and agriculture to our building products, we'll be seeing biotechnology getting share. And so the second element of Ginkgo's business model is that we take a share with our customers of those end products because we are uniquely able to enable them to make those products, we are able to participate in the downstream value of those products. All right. So that's just a little bit on what we do in the market that we're playing in. The second thing I sort of want to land with you is how do we do it? And why are we well positioned to continue to be the sort of the platform of choice in this space. So I mentioned the foundry and the code base, I'm just going to spend a little bit more time diving into what each of those are. This just gives you a little tour through the foundry. We constantly iterate and improve on our foundry technology and our footprint. So this shows you the last, call it, 8 or 9 years of development in the foundry, where we just added increasing levels of automation and sophisticated tools and workflows in our foundry. And what that's led to is an exponential scaling in our capacity. So this is a really interesting and important internal metric for us. We call it Knight's Law after Tom Knight, and sort of homage to Moore's law. So on the right-hand side here, this is the output of the platform. And what we see is that the platform sort of for normal years has tripled to quadrupled its capacity every year. Obviously, during COVID, we shutdown the platform for several months under kind of the state shutdown, but we've been exponentially increasing that capacity. And it's through a range of technologies, it's through increasing automation, increasing the throughput, miniaturizing reagent volumes so that we can use less reagent and increase the throughput of these reactions and obviously, yes, expanding our footprint as well. But this is a really important metric. Now one way we could've driven that capacity is we could have tripled to quadrupled our footprint every year, our cost every year. What's important is to recognize that's not what we did. And what we've instead seen is a scale economic. So every year as we've tripled to quadrupled the capacity, we've also seen a halving of unit costs as we've done that work. And that's really important because it means as we continue to scale the foundry, and we continue to increase utilization, reduce reagent volumes, improve our technology, we continue to improve the cost profile of the work that's being done on our platform. When that compares to a sort of status quo or an alternative that is largely remaining constant because the way that biotechnology research is done today primarily is a person at a lab bench pipetting things with their [indiscernible] hand. Every now and then they might use a small robotic system, but it's a very manual process today. And so it doesn't improve with scale. If you want to do twice the amount of work, you want twice the number of scientists or it takes you twice as long. At Ginkgo, we don't have to make that trade-off. We're able to increase our scale while decreasing the unit cost as we go forward. And all of our customers, therefore, benefit from that scale and from the fact that we are making our platform available to others, they -- each of our customers benefits from that, which is important. So that's the foundry. It's really about scale economics. The second asset is our code base. Again, this is -- this includes a range of assets from organisms to raw genetic code to actual biological tools. And we get that code base from a couple of places. One is we certainly have benefited from the fact that there -- where there are 4 billion years of evolution that have created a lot of really interesting tools that we can study and learn from out in the wild. But a really important source of code base for Ginkgo is the engineered code base. It's what we learn when we do an engineering project or what we develop when we do one of those projects. And importantly, our ability to then reuse that work. So this is a quick little example. Again, with Motif, I showed you that case study earlier, we were engineering yeast to make proteins really effectively. We're working with a new company on a personal care space but also wants to make proteins. And in this case, things like collagen or keratin for hair care and skin care. And we'll be able to use that same yeast as a starting point, which we already know produces proteins really well, and it's been engineered to produce proteins well. So that has the potential to shave a lot of time off the development cycle for that company and is now a major asset for the company. And so what you're probably picking up on now, and this is really the crux of Ginkgo's platform is that [ there's a virtual cycle here ]. As the platform scales, we see those foundry economics improve. But also we generate code base, which makes -- which improves the direction of our experiments in the first place. And then therefore, improves the probability of technical success. And then all of those things lead to a really strong customer value proposition, which not only drives our growth, but also allows us to participate in the downstream economics of the programs that we're creating. All right. So I just want to do a quick dive here on what we're building. So we are -- over the past several years, we've really been in the mode of proving the platform and proving the business model, establishing some really nice proof point. And as we come out of the SPAC transaction, we're really focused now on scaling that. And so we are expected to projecting to be able to scale up to 500 new programs being added to the platform every year in 2025. And then that compares to on the order of 22 programs that we've been adding this year and last year. And so where is all that growth coming from? One element of it is growth within existing customers. And so this is a very sticky business. We provide a very high value proposition to our customers. And so we're able to grow with them over time as they scale. And as we land in new customers, particularly customers with very large internal R&D budgets, we have the opportunity to really deepen our penetration with those customers. Another element of it is just the proof points that we've established within new categories. So as an example, last year, we worked for the first time ever in nucleic acid therapies. And it was publicly announced that we were working with Moderna to help improve the production of one of their key raw ingredients to make the COVID vaccine. That has been subsequently led to additional programs in the nucleic acid therapeutics space as well as in some of the key processing enzymes for those nucleic acid vaccines. So it's kind of created a whole new market segment for us, just by virtue of having that proof point. So as we diversify, it allows us to grow more quickly in those spaces. We've seen really strong momentum just in 2021, signing large new collaborations with Corteva and Biogen, leaders in their field. Another one that hasn't been publicly announced, a leader in its field in the [indiscernible] space and also launching new -- working with new companies that are being launched, such as the spin-out in the personal care space. What we'll see is that it will likely mix a little bit more towards health care and pharma in the near term as we sort of gain our fair share in that space. It's the most recent end market that we've entered into. And so we'll be will be -- you'll see some faster growth in that segment versus others, but you will continue to see Ginkgo have a broad horizontal strategy and serving many different end markets. One of the other ways that we drive this is just we're building a real ecosystem here. And so we're seen as a real partner to our customers and not just a service provider. And we've taken kind of a book out of the playbooks of some of the large horizontal technology platforms in the importance of really building this community in this ecosystem. And that has a number of different elements to it from not just the R&D work that we're doing with them, but also helping them get access to capital manufacturing capability, help with regulatory work, building that community, introducing them to potential partners and really helping set the stage for this industry as a whole, building trust and credibility around it as well. So this is a really important element of our growth story. All right. And I'll just end quickly with a quick review of our business model. So again, just as a reminder, we've been over this earlier, but we make money in 2 ways. The first is what we call foundry revenue. It's predictable, kind of service-based revenue that is paid upfront for the performance of a program. And then we also participate in the downstream value of the program. We're very flexible on how that's structured. It can be in the form of equity, it can be in the form of royalties or milestones. But we do focus on ensuring that we're participating in that downstream value and aligning our interest with our customers. What's really important is that we've seen real value in both of these places. So as the platform matured, we demonstrated on the foundry side of the business, our ability to fully cover the cost of doing the program on the foundry. So 5 years ago, Ginkgo was unproven. We were effectively subsidizing the platform. And over time, as the platform has become just frankly better. And as we've driven efficiency in the foundry, we've been able to demonstrate sort of the unit economics on just the foundry side of the business. But it's important to recognize that the downstream component is incremental to that. And so as we look at the combined unit economics of these businesses, we effectively have a sort of moderate margin foundry business with an incremental downstream value capture that it yields sort of mature business that has very attractive margins over time. So just very quickly looking at how this matures over time. Those 500 new programs over time yield a business on the foundry side that is kind of scaling up to about $1 billion in 2025. And then each of those programs has then the potential for that downstream value, which again, we estimated about $15 million on a net present value of the day it's signed. And so that's how we think about the value of the company here, where you have the foundry business as in a traditional life science tools company. And then you've got this downstream, accumulating downstream value that will be recognized over time. I'll also mention that we have biosecurity business that has taken off quite nicely, which we're not providing guidance around yet or long-term forecast around, but we are expecting to do [ about $15 million ] of revenue this year as well as some ancillary programs that we launched that have some near-term potential that's not being projected. So I'll wrap up there. There are a couple of slides here just about the transaction with Soaring Eagle. And we're thrilled to partner with them, thrilled to be adding Arie and Harry to the Board and really helping accelerate our entry into biotech. But with that, I will end. I think we're running a little bit late here. So I'll wrap it up. And if we have a minute or 2, we can take some questions.

Great. Unfortunately, we're out of time Anna Marie Wagner, thanks so much for being here and giving us that overview. We look forward to you being a public company and having the chance to interact again. Thank you again for being here and everyone on the line for joining us. Have a great day.

Thanks, Brandon.