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

That's our queue. We'll get started. Well, thank you very much for joining us. I'm Matt Sykes, life science tools and diagnostics analyst at Goldman Sachs. I have the pleasure of introducing Anna Marie Wagner, Head of Strategy at Ginkgo Bioworks. And Anna Marie, thank you very much for joining us.

You're welcome. Thanks for having me.

Maybe we'll just start off with sort of a brief overview of some of the key accomplishments sort of in the first half of this year and what you're sort of most excited for...

Yes. So I think one big theme that you've seen in Ginkgo really over the last year, but certainly, I think, accelerating in 2023, is a movement into biopharma. Ginkgo, obviously, our roots was in -- we're an industrial biotech. Candidly, when we were just starting out, I think folks viewed us as a few MIT grads and some robots, and the idea of going to sell into a place like Biogen or Novo Nordisk or Merck at that stage was almost laughable. And so we really had to earn our credibility and our chops, delivering for customers in industrial biotech and sort of slowly moving up the curve in terms of the technical sophistication of our customers. Starting in kind of 2018, 2019, we started really investing in our mammalian cell engineering capabilities. And as those scaled and then being able to benefit from our broader platform, we were able to much more credibly go into biopharma and offer a much more complete service to customers that really, for the first time, have their own internal capabilities that were very, very, very strong. And so for us, it's a really important validation point because it's a very different sale to talk to a customer about, hey, we might be able to enable a new area of innovation for you that you've never even thought of being able to do yourself before versus now talking to customers about this thing that you're trying to do, we think we can help you improve the probability of success and do that better. So we're selling into an existing market for R&D rather than a brand-new market for R&D, and we're seeing a lot of growth in that space. And so I know folks have been chatting about a challenging macro environment. We see something very different actually because we're offering customers a pretty unique value proposition in this kind of an environment where rather than having a relatively fixed base of R&D costs that are hard to manage and scale up and down as your kind of capacity for innovation funding changes, we offer you a much more variable approach to doing R&D and investing in innovation and one that hopefully drives higher probabilities of success. And so in many ways, this is a really unique environment for us to be able to demonstrate our value-add to customers across all industries, but in particular, right now, biopharma.

Got it. Maybe on that point, because I think it's an interesting dynamic where the macro environment could be a benefit just given the platform that you have. As you think about emerging biotech, which has its own issues with funding, but also large pharma, which, based on some of the commentary we've heard sort of year-to-date, it seems like there's some reprioritizing of R&D budgets. You and I have talked in the past about the challenges in the long sales cycle of going after a large pharma, almost competing internally with their R&D that they have. But if they are reprioritizing some of the things they're spending on, maybe that offers an opportunity for Ginkgo. Maybe talk about them, but then also the emerging biotech, too.

Yes. So I wear 2 different hats at Ginkgo. So in addition to sort of our capital markets work, I also lead our M&A function. And we're seeing really opportunities on both sides, both our [ BB ] sales efforts, enterprise sales efforts as well as M&A. We are certainly seeing a world where all companies have to think about their priorities very carefully, whether that means trimming back on certain areas and certain modalities or it means trimming the pipeline within their areas of focus. We are seeing all companies prioritize. Again, for Ginkgo in biopharma, we are going from 0 to 1. So it's much more a question for us and the market impact on us on whether customers are interested in even having a conversation about outsourcing R&D, which is not something that they've really done before. Like the way that a biopharma customer interacts with a contract research organization today is asking that CRO, can you please do this thing that I could do in-house, but really don't feel like doing for me? But they are controlling the questions that are being asked. They're directing the work that is being done, and they are interpreting the results from that work. When a customer comes and works with Ginkgo, they're giving us a problem and a challenge that they don't know how to solve. And they're asking Ginkgo scientists to come up with a solution to do the work to interpret the data and to give them a product that works, and that is a much deeper trust-based relationship. And it's that question that our customers are really wrestling with. And I think this market environment does create an opportunity for them to revisit the way that they approach R&D. And on the macro cycle, while, yes, customers are prioritizing now, we aren't penetrated in the market yet today to experience the change of that prioritization. We are really going after this market for the first time. And customers are in an interesting headspace where they're open to exploring, well, okay, I've just shut down a facility and fired 1,000 people, but maybe this would be a relatively low-risk, low-cost way for me to continue to explore this area of innovation that I think will be important for us in the long term, and that can open up some conversations for us.

Got it. Maybe pivoting towards AI, which I think has been sort of a large portion of sort of what Ginkgo does for some time now before AI became really popular. Maybe just talk a little bit about how you're leveraging some of the possibilities through Ginkgo AI. And is there kind of any other exciting developments you can share with us around Ginkgo's role in using AI?

Absolutely. Yes, it's funny, Ginkgo, has, I think, been a little bit quiet about AI historically, even though computational tools are quite core to what we do for our customers because, candidly, until the last 6 months or so, most of the conversation around AI and biotech was focused on, well, we've created some special algorithm that allows us to discover new things in the public data. And our view has always been that the algorithms will likely be commoditized, if not fully open sourced in kind of a mature state of this world. And what actually differentiates companies in this space will be access to high-quality training data and the ability to then use and fine-tune those models over time using insights that are generated because it is very hard and very expensive to create data that gives you biological insight, in other words, mapping genotype to phenotype. And one way to think about Ginkgo and the assets that we've built are that the foundry is effectively, in addition to doing experiments that generate customer results, each of those experiments is effectively doing that. It is -- we engineer the cell with some certain genotype, and we're measuring now what that cell does or how that protein binds. And so that information, which sits in our code base is, from our perspective, quite unique and valuable data that we can use to train models going forward. We already use these tools extensively in the areas you would expect, DNA design, protein engineering, our highly computational services that we utilize at Ginkgo. And I think you'll see the penetration of computational methods increase at Ginkgo over time. And what that does for us is it frees up foundry capacity to ensure that the physical experimentation that we're doing is really driving incremental learnings and incremental data versus having to sort of redo the same experiment multiple times for multiple customers, and that gives us more physical capacity to take on more programs, harder programs and then leverage that data again in the future for new customers.

Got it. As you take on new programs, there's the upfront fees that you generate, but then there's also the downstream economics, and you guys have described both in great detail over the past number of quarters. But as you think about today's environment and what programs you want to attract, how are you making that decision point? I think it just needs a term toggling in the past. Like how are you thinking about that toggle in terms of upfront fees versus downstream economics, which there's a bit of a duration mismatch sometimes where some projects get to be a little bit outside of your control and, therefore, realizing the economics downstream can take some time? But how are you thinking about that mix at this point?

Yes. I would probably characterize it less as a toggle and more of a kind of a continuous knob that we can turn. And look, I think in a perfect world and in areas where we have very high confidence in technical success and ultimately then in commercial success, it allows us to lean into downstream value. And you do see certain areas where we can offer a highly, highly differentiated offering to the market because our underwritable probability of technical success is so differentiated. So for example, in enzyme engineering, this is a service offering that we released into the market sort of last year talking about, hey, Ginkgo happens to be really good at enzyme engineering, you should call us if you have those challenges. At our conference, our annual conference we hosted in April, we announced that going forward, obviously, we have to underwrite each program, but that for programs that qualify in our enzyme engineering services, we'll take success-only payments for that specific workflow. And that's because we can underwrite an extremely high probability of success for those projects, but that's not something our customers are used to. Our customers are still used to failing. Our protein engineering are spending a really long, hard and expensive slog doing that. And so we can create a technical success-based milestone that, for us, creates a highly profitable service, but for our customer is a value proposition that they cannot find elsewhere in the market. But for most of our programs today, we are still in that world of -- there's a lot that needs to come together to create technical success for a customer. And so we are charging services fees sized to the amount of work we think we need to do. And in this type of a capital markets environment, I think we are focused on ensuring that the services alone get us to a point where we have sustainable profitability over a reasonable period of time. And so we are focused on managing the business to that without having to rely on discrete commercial milestones or a big royalty hitting. And so certainly, in this environment and until those downstream economics start playing a bigger role in our P&L, we will, I think, turn the knob towards the pieces that are in our control, which are the services revenues and the technical success milestones.

Got it. And you touched on it briefly, but I'd like to get a little more detail on the enzyme services offering, which you launched earlier this year. Can you talk maybe a little bit more about that offering and how that could drive further penetration in the biopharma market?

Yes. So enzymes are an interesting one for us. It's a -- engineering proteins is something that we do across effectively all of our programs. Even if the ultimate product is a small molecule, the way you're going to make that small molecule is engineering a set of proteins that will catalyze certain chemical reactions that then ultimately produce that molecule, whether inside a cell or outside the cell. And so we now have hundreds of programs that we've done protein engineering on and for some of those programs, multiple proteins. And so we have a lot of experience and a lot of data on the types of proteins. We're good at engineering, the types of improvements we can get on a variety of different dimensions, whether it's binding affinity or thermostability or some other -- or manufacturability, some other dimension. And so when we're working with customers, it's also, as I mentioned, a highly computational endeavor for us now. We use [ log ] machine learning techniques there. And so it is both very what we call foundry friendly for us to run; in other words, it doesn't require a lot of bespoke and like highly managed foundry services or program management. It can run very efficiently on the foundry and utilize a lot of computational tools instead. It's very, therefore, cheap for us to do the work at Ginkgo, and it's very underwritable from a probability of success perspective. And so again, with our customers, we can talk to them about what is the value in having this enzyme. Whether, again, they need an enzyme with particular characteristics or they need to manufacture an enzyme or any protein more cheaply, those are programs where we can lean into that probability of success metric and charge them success-only payments.

Yes. That was the next question actually, the success-based payment strategy. Can you talk about how that could potentially augment the financial profile of Ginkgo over time as that kind of gains momentum? And what is the rationale behind starting that success-based program strategy?

Yes, again, it's underwritable for us. So we don't think that there's an overly material difference in the amount of risk we're taking on versus charging the services revenue, but it does allow us to capture more value because the customer views that as a highly differentiated proposition. So if they are thinking, well, I can spend $3 million, but I think there's only a 50% success rate, and so I'm really thinking about this as a customer at $6 million, and we tell them, we'll charge you $5 million if it's successful or $7 million if it's successful. They might think about that differently or it's a good trade. And so whereas they might have only paid $3 million if we were charging them upfront, they might pay $5 million on success. And based on our underwritten success rate that we believe, in this case, it would be a very, very good trade. But what's unique is that this is a market that's already defined. There are other companies that provide enzyme engineering as a business that our customers are -- have been working with or have been talking to or have thought of. And so again, as I sort of started the conversation, it is, in many ways, much easier to talk about things that Ginkgo can do for our customers that are already recognizable to our customers. And one of the reasons that we picked enzyme engineering is that not only is it an area that we're quite good at today, it is also an area that our customers recognize and that our customers have leveraged service providers to do historically. And so there is a nice market point of comparison that makes it easier to have those conversations with our customers.

Got it. And then just on cell engineering business overall, can you talk about the cost profile and how you could moderate that over the next year or so? I mean you spent -- a lot of the CapEx is done in terms of some of the investments you've made. In terms of sort of the OpEx that goes along with that, how do you see that, as your business scales, how do you see that OpEx profile changing?

Yes, it's a great question. And in our Q4 call, we talked, as I think many companies are today, about how we're driving efficiency in the business. I'd say about a year ago, we started feeling like we were getting a little bit capacity constrained. And one of the things we invested in was a proper kind of industrial operations team. They literally went around the foundry with clipboards watching machines and how often machines were being utilized and watching employees and figuring out, hey, what time here is productive versus unproductive. And what we've discovered, and I think it was, on one hand, obvious, on the other hand, not, is that we have a lot of capacity. And the investments that we're making are really around how can we reduce the lag between handoffs? How can we increase the utilization of certain pieces of equipment? How can we reduce unproductive time for our employees? Like you shouldn't have to watch a robot run. You should be able to go do something more productive. Is there a software investment that we need to make to enable that for you? And so right now, we actually feel very, very good about our ability to scale programs and, therefore, revenue without making investments in OpEx at nearly that same pace. And again, as I mentioned, we're certainly focused on our path to profitability; I know investors are as well. And that is the core underlying driver of that is we do feel like we have ample capacity today in our existing infrastructure, both people and capital, to grow.

Got it. Maybe talk a little bit about, I don't think it gets discussed enough, but sort of the competitive landscape and what you're hearing and seeing? And how has the competition in the space evolved over the past few years? And I think I know the answer to why Ginkgo is differentiated. But I would love to hear kind of your view as you kind of look at the last couple of years and then look forward, how has the competitive landscape changed, in your mind?

Yes. So there are really 2, I'd say, sources of competition to Ginkgo. We are typically not RFP-ed by a customer. So customers are not saying, hey, I have this big project, I'm calling all the cell engineering companies to come bid on it because, candidly, there aren't a lot of companies that offer cell engineering services across modalities in the way that Ginkgo does. We're quite unique in the way that we have approached the world. Our main competitor is the customer's in-house team. And so again, it is that sale of should you be doing this thing that you're doing today in-house, in-house? Or should you be considering leveraging Ginkgo and the scale and the IP code base that we can provide to go after this project? In certain areas, and this is more prevalent in biopharma, there are vertical niches where folks with our business model has been able to kind of achieve critical scale and critical mass in that vertical. And for the most part, those are areas we've sort of chosen not to play historically because there's a lot of low-hanging fruit elsewhere. So the canonical example there is antibodies. As an example, there are a number of different companies who provide antibodies as a service. We are -- we've done antibody programs. We're certainly capable of doing it. But it's an area where, let's say, there's not as much of a gap between what is available to customers and what we can provide. And that's just because there's inherently a trade-off always between scalability and flexibility. And the flexibility that we've invested in to be able to work on many different modalities means that in a specific area, folks have really invested in building a very specialized workflow. There is benefit to that specialization in that narrow niche. But we wouldn't run into those players in any other areas. What we're observing that's really interesting to us is as we scale generally across all industries and modalities, we do still see benefits in those areas of specialization. So we've talked about enzyme engineering already. Enzyme engineering was sort of like antibody discovery where we weren't really marketing that as a service historically. There were other providers that could do enzyme engineering as a service as a core product. But what we realized is because we're doing protein engineering across all of our projects, we are actually really darn good at protein engineering as a general matter. And so we are now able to compete effectively in that niche and in that vertical with players that focus solely on that. But really, what we focus on is how can we compare and provide value to a customer's in-house team.

Got it. And as you think about diversification across end markets, I mean the value of having a platform is you can kind of go where the activity is and you can be fairly agnostic, but you also don't want to back yourself into a sort of lack of diversification on end markets. So as you think about bringing on new programs, do you think about sort of end-market diversification? Or do you target biopharma where synthetic biology has proven to work versus maybe industrial where it's still very early stages? How do you think about that end-market mix over time?

Yes. So I think what's important to remember there, especially if you talk about are you backing yourself into a corner, is that our programs are using a common platform. So it's not like when we sell a biopharma customer, they're just using the biopharma platform. There are certainly elements of our platform that are more relevant to a biopharma program. So some of our mammalian engineering capabilities are going to be more relevant in biopharma, but those programs are still using our DNA synthesis capabilities, our protein engineering capabilities, our NGS team. They're using common infrastructure that are shared across all different industries and all different program types. And so we're still able to see those benefits to foundry improvements of scale even as the mix shifts over time. So I think that's important. But certainly, we are still selling actively into customers across all industries. I think what you're observing right now, though, is just the natural evolution of the mix of our business towards biopharma just given the size of that market relative to the size of the industrial biotech or agricultural markets. There is a bit of a macro overlay there. But other than impacting kind of where our sales team spends their time, it doesn't have such dramatic impacts on the platform, although that certainly does impact certain areas of investment.

Got it. And a few quarters ago, you removed guidance on the downstream and which I can understand is a difficult thing for us to forecast, the visibility is challenging. Could you talk about any active programs that you've announced in the past that you're excited about in terms of sort of their progression and kind of how we should be thinking about sort of downstream over the next year or so?

Yes. So look, I think, certainly, as Ginkgo matures and has a recurring base of royalties and downstream value, we will be much easier to model. I think we all agree on that. What I focus on much more is less did some milestone hit in some quarter, which is helpful, but to me is not as material as did this customer with a very good in-house team choose to work with Ginkgo. Because to me, that is much more evidence of Ginkgo's competitive advantage than whether or not we got some monetary results from the commercial success of the customer program, which has just as much to do with the customer being good at clinical trials as it does with us being good at delivering for a customer technically. When we sign a new deal with a customer, they're looking at the results from our other programs in their area or in relevant areas. Like they can really digest about technical information and then choosing to work with us, that to me is the leading indicator of Ginkgo's competitive advantage. When we have that competitive advantage, there are lots of ways to monetize it. As we talked about earlier with the knob, right, we could choose to just make a ton of margin on services. We could choose to give away the services for free and take really high royalty rates relative to what we do now. I think today, we're in a happy medium. And I do think there are plenty of opportunities both for, certainly, for technical success milestones, but ultimately for commercial milestones as well in the coming years. But I think folks have a tendency to focus more on those than the real information that, candidly, that provides.

Got it. Maybe pivoting to biosecurity for a minute. As the business sort of transitions away from the COVID testing, what areas are you most excited about in biosecurity as you kind of look over the next year?

Yes. I continue to be really, really excited about the potential for biosecurity. It is so obvious to Ginkgo, but also to our partners, both in the U.S. with the CDC and internationally, that we need to build this infrastructure. I think the challenge is really understanding how that infrastructure is going to be built and exactly what that looks like. But what Ginkgo earned as a leader in COVID response was the right to sit at the table and help develop the plan for that infrastructure. The way that we think about it is kind of a bio-radar, right? We all have weather on our phones because we built a radar system around the world that tells us when things are brewing in the Pacific that are going to ultimately hit us here or hit Mexico, and we need the same sort of tool for biology. Had we had a bio-radar in place in 2019, we would have been able to see that novel coronaviruses were emerging. Maybe those weren't a concern, but we would have been able to start paying attention to that. We would have been able to start thinking about what are the vaccines that would reflect this. We would have been able to put in place public health policies. Maybe masking would become mandatory in a certain province. We would start testing individuals when they showed up with symptoms in a hospital weeks or months before we actually did. We would have thought about travel restrictions to certain regions where we were seeing outbreaks. And we would have hopefully been able to prevent -- keep COVID to be something that looks more like SARS or MERS that was more localized than something that became globalized. We didn't have those tools. But those are the tools that we're talking about building with governments around the world. There are very strong network effects there. This is going to have to be a global cooperative. There are also strong economic impacts. If you think about where biosecurity may matter most, it's not for public health, which is where most of us think about it, it's food security. Biology is what we eat, right? So a disease or fungus that impacts corn supply or rice or soybeans would have a massive global economic and food security impact. A new avian flu that impacts our chicken supply would have a massive impact. And so some of the programs we're talking about are also -- right now, we do wastewater on plants, but shouldn't we be doing wastewater on feedlots? Shouldn't we be doing soil samples of crops around the world, around the country? And so again, I think what's challenging about the biosecurity business is that it's so early stage, and we're still in this process of concepting what these tools would look like. But I think at Ginkgo, at least, it's quite obvious that this is going to be a very large and important industry. And we're very proud of the fact that we've earned a leadership position there and are now working with a number of governments to help design that and implement it.

Just following up on biosecurity. I think back in Q1, you said that about 20% of Biosecurity revenue was recurring in nature up from under 10% in Q4. How do you maximize the recurring revenue model of Biosecurity?

Yes. So again, when we -- so the -- I think, to be clear, like proof will be in the pudding on how recurring biosecurity contracts are. These are all brand-new contracts, it's not like the software industry. But when we talk about the sort of more recurring elements of our model, it's these federal contracts and these international government contracts which are really around establishing infrastructure. I think what you'll ultimately see is sort of a peacetime, wartime framework, right, where there will be almost a peacetime business model, which is really around building and maintaining infrastructure. Those are probably large government contracts, relatively low margin. I think those will scale over time as we start concepting what that infrastructure needs to look like in the first place. And then I expect you'll have a sort of a wartime component to that, which is when you do find outbreaks, whether local or larger, there's a rapid response infrastructure that very quickly boots up to handle that. Vaccine development, therapeutic development, public health response, testing infrastructure then very quickly have to stand up. And so I think the initial scaling is really that ever-ready infrastructure that we would be concepting and potentially running, and then you would have these moments where that business would need to scale up quickly in order to respond to emerging threats.

And then just last question on biosecurity. You talked in the past like you're doing work in Africa and all around the world. It's a global business. But I think it's also fairly low capital-intensive or people-intensive the way you structure it. Can you talk a little bit about how that's structured? Because as we see these contracts go global, I think the first instinct is, well, that's going to be a lot of people.

That's sounds expensive, yes.

Yes. But maybe kind of educate us a little bit more on what that looks like.

Yes, it's a great question. So this is a key learning of ours during the initial COVID response in the U.S., when we started working with schools, there was definitely an option there, do we build locally? Do we centralize and everything is getting shipped to Boston? Or do we partner locally? And for a number of reasons, we decided that, to the extent possible, we wanted to partner with local institutions. It was certainly important for the region. It allows them to contribute. It leveraged the assets that they already had in place so that we could run a very asset-light business model. So just as an example, what we've been doing with the COVID testing work and the variant tracking with the CDC is that samples are sent to local labs for initial processing. So if you're interested to know if COVID is present or not, yes or no, a local PCR test can handle that for you. We developed protocols, but we tech transferred those to local labs. And then what we help with is, okay, those positive samples, let's do variant tracking. Let's actually sequence those and analyze those to help identify whether new variants are emerging in these samples. And so we were the first to identify a couple of the Omicron variants. And so that's the work that we maintained in-house because we already have a well-established NGS infrastructure, and that was an easy way for us to leverage our existing infrastructure for those. I think for countries, it's a similarly important question where, in addition to thinking about what is the right biosecurity infrastructure, many countries are also thinking about and how does this tie into my long-term strategy for building a robust bio-economy in my country. And so building local genomics institutes and bio-informatics training for the local population is actually a very important component to some of the conversations that we're having with governments. And so really, our role today is almost as a consultant and a systems integrator where we're working with them to design what that infrastructure looks like. Many of the components of that system will be services that we offer and we can deploy, whether it's our analytics dashboards or our wastewater programs or something like that, and that sort of library of tools will grow over time. But then we're also able to bring to bear the integration sort of service on other components that we don't need to own in-house, right? So we can work with a large sequencing company, as an example, a tools company that makes sequencers to help deploy those sequencers in country, help train up local -- the local population and how to leverage those, run, operate those so that you're also building a more robust economic infrastructure for those countries. So yes, we continue, as we expand internationally, to be really focusing on the data, the genomics, the pieces that we can do well and ensuring that infrastructure is really being built on a local level in those countries and can be operated locally.

Got it. In the time we have left, why don't we talk a little bit about M&A that you spent a lot of time on.

My favorite topic.

You have a significant amount of cash in the balance sheet, which has been a great asset for you. You've made a number of acquisitions for the past year, mostly bolt-on. I just would love one high level, how are you thinking about capital deployment as it relates to M&A in terms of size, area? And then two, maybe a couple of highlights from some of the recent acquisitions that are sort of proof points of the strategy that you've laid out?

Yes. I think 2023 is going to be a very unique year for M&A for Ginkgo. It's really the first time, I think, where we've had the opportunity to acquire platform assets without taking on a lot of the sort of product assets that are typically formed around these. And there are [ instances ] that the biotech industry has been held back by the fact that platform assets are only as valuable as the lead pipeline drug. And as the capital markets have softened, those pipelines are not getting funded in the same way, and there isn't really a home for platform assets. There aren't natural acquirers other than Ginkgo. And so we've emerged as a really attractive partner to sellers to be able to potentially valorize their platform technologies in service of our customer base. But what it means is that we've been able to structure, again, very capital-light transactions where the bulk of the economics in these deals are structured as downstream value sharing. So if we get paid a royalty after using this technology, we will share those economics with the seller, but we're not paying huge upfronts for these companies. These are effectively IP acquisitions. And so there's very low operating costs to these acquisitions, but we're able to bring a tool kit that our customers historically haven't had access to because they've been tied up under therapeutic pipelines that were fully in-house. And so we're looking at a number of assets that look like that. StrideBio is a company that there is an asset we acquired a couple of months ago in the AAV capsid engineering space that sort of set this model, and we've seen a ton of customer interest coming out of that. And so really looking to replicate that through the year.

Not a bad time to be looking at M&A in this time?

We have a very robust pipeline.

Great. Well, that's all the time we have. Anna Marie, thank you very much for joining us. Appreciate it.

Thank you.