Ginkgo Bioworks Holdings, Inc. (NYSE:DNA) Q1 2023 Earnings Call Transcript May 10, 2023

Ginkgo Bioworks Holdings, Inc. misses on earnings expectations. Reported EPS is $-0.11 EPS, expectations were $-0.09.

Anna Marie Wagner: Good afternoon. I’m Anna Marie Wagner, SVP of Corporate Development at Ginkgo Bioworks. I’m joined by Jason Kelly, our Co-Founder and CEO; and Mark Dmytruk, our CFO. Thanks as always for joining us. We’re looking forward to updating you on our progress. As a reminder, during the presentation today, we’ll be making forward-looking statements, which involve risks and uncertainties. Please refer to our filings with the Securities and Exchange Commission to learn more about these risks and uncertainties. So, we just hosted our annual conference Ferment and all that’s geared towards our customers understanding why customers are choosing Ginkgo is important to our investors. And so we’re going to spend some time today recapping some of the themes from that event.

As usual we’ll end with a Q&A session and I’ll take questions from analysts, investors, and the public. You can submit those questions to us in advance via Twitter #Gingkoresults or e-mail at investors@gingkobioworks.com. All right. Over to you Jason.

Jason Kelly: Thanks Anna Marie. I’m super excited to be chatting with all of you today. We just hosted Ginkgo Ferment, our big meeting. We had about 1,000 people there in person, plus folks on the live stream as well. In my keynote, I reminded the audience that at Ginkgo we’re not spending our cash just on clinical trials or field trials or cosmetic launches, these are sort of end product activities that our customers are doing. At Ginkgo, we’re spending our capital on improving our platform for our customers. So, a big goal today was learning from our customers about what they want us to build and I firmly believe that if we deliver on those requests then we ultimately deliver for all of our investors. We do right by our customers we do right by all of you.

So, you’re going to hear a lot more from me today about why customers are choosing to sign up for Ginkgo’s platform and what I heard at Ferment. When we launched Ginkgo one of the big criticisms of our whole model was that a general purpose platform would not work in biotech, right? It might work in the tech industry, but in biology the lab work you do to engineer a mammalian cell is just too different from the lab work you do to engineer bacterial cells to get that working on a common robotics platform and automated for example or the data and machine learning models that would be relevant in the biopharma industry would never port over to work in agriculture. So, I’m happy to say we are proving these people wrong. This is a sampling of our customers at Ginkgo.

We have some of the largest biopharma companies in the world now, Novo Nordisk, Merck, we just announced a large deal with BI chemical majors like Sumitomo just announced last quarter, Solvay longtime customers like Givaudan, one of the largest flavor and fragrance companies in the world. Ag majors, Corteva, Syngenta, just joined the platform this last quarter and our large long-term customer Bayer in agriculture. Importantly, that’s the top of this chart, if you look out at the bottom, you’ll see all the startups in the same range of industries, right? And these are the companies that are working to make the new disruptive innovations in these markets. This breadth of our platform and business model being able to work across such a wide range of industries and customer scales, it is a real strength for Ginkgo and we’ll talk about that later.

One of the best things about this year’s Ferment was that the majority of the folks that went up on stage were our customers, right? And so you had amazing customers joining us on panels, we heard 12 lightning talks from customers about what they were building by leveraging Gingko’s platform. And that’s really important, right? People in the audience and on the live stream that are thinking about joining Gingko’s platform, they might like to hear from Ginkgo folks, but they really want to hear from people like them that are getting value out of using our platform. And so I think we did a nice job of doing that. I really encourage you to watch — all those videos are up on YouTube and you should check that out. And I think the diversity of what our customers are building with the platform gets folks really excited and it also gets people thinking about outsourcing from our platform as they hear those different applications.

I’ve shown this flywheel to you all before, but it’s important to highlight that our customers help make our platform better. So we improve with scale. And it’s a scale economic things like auto manufacturing plant or a chip fab or things like that right? As we add new customers we can invest more in our platform and our platform improves. We get larger facilities and then which drops our cost and we learned from the data from one project to make another project faster and less risky. And so even though all of you our investors should be excited when we add a new customer to the platform, I think our customers should also be excited every time they see a new announcement of a customer joining Gingko’s platform because they are getting better infrastructure out of that.

And so that’s why it’s so exciting that in 2022, we increased our active program by 60% and the rate of new program additions by 90%. That’s why I talk about these numbers it shows that the flywheel is spinning for our customers. And we expect to keep driving improvements that pay off for decades to come for our customers. Okay. I’m going to hand it over to Mark who’s going to walk you through our Q1 financials and then we’re going to dive in on some of the key themes coming out of Ferment. Over to you Mark.

Mark Dmytruk: Thanks, Jason. I’ll start by discussing our Cell Engineering business. As a reminder we now refer to Cell Engineering revenue rather than foundry revenue as it is more reflective of the business. You’ll see that updated throughout our 10-Q. We added 13 new cell programs and supported a total of 97 active programs across 60 customers on the Cell Engineering platform in the first quarter of 2023. This represents substantial growth and diversification and programs relative to the 64 active programs in the first quarter of 2022 with strong growth coming from the pharma and biotech and the food and agriculture segments. We added several large new customers to the platform including Boehringer Ingelheim, Syngenta, Solvay and a new program with Sumitomo in addition to a good mix of programs with earlier-stage customers across industries.

As Jason mentioned, we think both of these customer segments are important. It’s an important validation of our capabilities when we add large multinational customers like BI and Syngenta who have strong internal R&D capabilities but we’re also very proud of our ability to enable the next generation of leaders. Cell Engineering revenue was $34 million in the quarter, up 59% compared to the first quarter of 2022. As you can see in the charts at the bottom of the page, this growth was driven entirely by our services revenue with third-party customers and is reflective of diversification in the customer base. Now turning to Biosecurity. Our Biosecurity business generated $47 million of revenue in the first quarter of 2022 a solid result as this business transitions away from K-12 COVID testing services.

Importantly over 20% of this revenue came from what we believe will become more recurring sources such as federal and international contracts while that proportion was well under 10% in Q4 of last year. Biosecurity gross margin was 52% in the first quarter of 2023, which benefited from some onetime items. You can see on the right that we’re really thinking about this business globally now and not just domestically. We believe there will be strong network effects in this business as biology does not respect borders. We have now collected samples from flights originating in 72 countries through our airport program. We believe this type of infrastructure can provide an early warning system for future biological threats. And now I’ll provide more commentary on the rest of the P&L.

Where noted these figures exclude stock-based compensation expense which is shown separately. Starting with OpEx. R&D expense excluding stock-based comp increased from $57 million in the first quarter of 2022 to $115 million in the first quarter of 2023. G&A expense, excluding stock-based comp increased from $42 million in the first quarter of 2022 to $84 million in the first quarter of 2023. These operating expense items increased year-over-year as expected as we invested in our platform in various functions to support our growth during the past year and layered in the four acquisitions we closed in the fourth quarter of last year. Included in these numbers in the first quarter of 2023 is approximately $19 million of one-time M&A and integration-related expenses.

Stock-based comp, you’ll notice the significant step down in stock-based comp year-over-year. As a reminder, this is because of the catch-up accounting adjustment related to the modification of restricted stock units when we went public is rolling off. Over 60% of the total $75 million stock comp expense in the quarter related to RSUs issued prior to us going public. To help folks model this more precisely, we have provided a new appendix slide in this deck for your reference. Net loss. It is important to note that our net loss includes a number of non-cash income and/or expenses as detailed more fully in our financial statements. Because of these non-cash and other non-recurring items, we believe adjusted EBITDA is a more indicative measure of our profitability.

We’ve also included a reconciliation of adjusted EBITDA to net loss in the appendix. Adjusted EBITDA in the quarter was negative $100 million compared to negative $1 million in the comparable prior year period. The decline in adjusted EBITDA was attributable to both the higher run rate of expenses in cell engineering and the as-expected decline in Biosecurity revenue. And finally, CapEx in the first quarter of 2023 was $19 million, reflecting foundry capacity and capability investments as well as leasehold improvements. CapEx was impacted by timing of equipment purchases and projects and we would therefore expect lower levels of CapEx on average in subsequent quarters this year. In terms of our outlook for the full year, we are reaffirming our guidance for 2023 including 100 new cell programs, at least $175 million of cell engineering revenue, driven by services revenue, with additional revenue potential from downstream value share and at least $100 million of Biosecurity revenue.

As we shared in our last quarterly update call, we expect our new program additions and revenue to ramp during the year and believe we have a solid backlog and pipeline to support our outlook In conclusion, we’re pleased with our overall progress in the business, while navigating a challenging macroeconomic environment. We’re adding new programs to the platform in a way that improves the platform and balances both near-term and long-term economics. We are focused on our cost structure with new investments in spend generally targeted to discrete areas, such as our mammalian capabilities and we continue to manage our balance sheet and cash flows to maintain a long runway while retaining flexibility to capitalize on near-term strategic opportunities, with $1.2 billion of liquidity at quarter end.

And now Jason back to you.

Jason Kelly: Thanks, Mark. It’s always exciting to me to see new customers signing up for the platform. And I want to highlight that we actually spend a lot of time talking to our current customers, including running an annual customer survey to learn how they’re using the platform and importantly, how can – you can make the platform better. So I want to share a little bit about what we’ve learned on why our customers are choosing to outsource to our platform in the first section. Now our customers are specialized in their vertical markets right? They’re a pharma company, an industrial biotech or an ag company. We are not right? I think as a general platform. So I want to talk about these service offerings that Ginkgo is launching so that we can better speak in the language of our customers when we’re offering our general platform.

And then finally, I’m also really excited about the progress our Biosecurity business is making around the world. And so I’m going to end there with a few comments. Okay. Let’s dive in. All right. So I showed this slide before, but I do want to I want to pause on it just again for a minute to highlight how unique it is to have this range and breadth of customers on the platform both in terms of size and range of industries. And so one of the things we wanted to ask is why are these folks getting on the platform, okay? And we did this by again surveying and talking with folks and things like that. I think this is a really nice quote from one of our larger customers he’s Brian VanDahl at Novo Nordisk and he said, Science is currently undergoing a revolution.

Large-scale data sets coupled with AI is opening up a greater opportunity space within biology. We no longer have to limit ourselves to the questions that can be addressed by traditional research methods. And we heard more from Brian on a panel at Ferment I encourage you to watch. I think this is a key idea, right? Pretty much every business right now regardless of market is asking is there some large data set that I can train a generative AI model on it’s going to have an impact on my business. That’s true if you’re a car company, finance media whatever it might be. And it’s also true if you are running a biotech R&D department right now in biopharma or BioAg, right? And so I think this does represent and highlights one of the — I want to show is the first example of what we’re hearing as feedback from customers.

So the — that we get more data per R&D dollar at Ginkgo using our infrastructure. And this is important to generate those large data sets. Secondly, we access not just that single customer’s data but because of the way Gingko’s platform works and our IP works we’re actually able to give a customer access to the data and learning across all the projects that have been happening on Gingko’s platform. And then they’re not just left on their own to figure out how to navigate that. Many of these companies are new to doing these sort of large-scale data science efforts they have access to Gingko’s data scientists in order to navigate that data. Third, companies want to launch work quickly on the platform all right? And this is endemic in biotech.

The rate and speed the biotech works is too slow. Fourth, if you’re a smaller company there’s an enormous upfront cost to building out a laboratory. We want to just cut that out in terms of the cost and spending for new companies trying to do cell engineering. They should be able to use our services rather than build their own lab. And then finally often you have a big R&D department that’s a big fixed cost sort of using space and using equipment in a facility. We want to replace that with a variable cost service and we’ll talk about why that’s particularly important in pharma. So I love this video. This is the new technology that’s coming out of our acquisition from Zymergen. These racks these are basically — I would consider this to be the best sort of flexible automation platform out there.

And the reason I highlighted this at Ferment was if you are a customer developing a therapeutic drug or you are working on a new agricultural product you should not have to be a world’s expert in laboratory automation, right? If you wanted to use say cloud compute you do not need to be a world expert in data center architecture right? You leave it up to the cloud computing companies to do that. Our argument at Ginkgo is these are the sort of technologies we are going to focus on so that our customers don’t need to and that they have access to the absolute latest in technology for getting more data per R&D dollar. That’s on us. And you see this when you look at quotes, for example, Marcus Schindler, CSO at Novo Nordisk. He said, they work with Ginkgo because of our ability to rewrite genomes to engineering new bespoke biological system.

So being able to make engineer at the scale of a whole genome. That wasn’t something they could do in-house, right? Alphonse, at Biogen, I was there when we did the deal, a large number of design ideas that Ginkgo could work through and this was to help them with aid the manufacturing. So again that scale of activity data per R&D dollar being so much bigger at Ginkgo. Importantly that’s the data from your project. You do want to get more data out of that. But boy a lot of other biotech work is going on in the world. And it would be really nice, if you’re trying to train up a model for example of your particular system that you were able to draw on data from other people’s work. And this is something that the tech industry is benefiting from dramatically.

If you look at how these new models are being built, they’re being built on huge data sets across lots of different assets around the Internet and so on. In biology a lot of that data today frankly is being stow-piped across thousands of different companies. And so one of the things Gingko’s been doing is accumulating that all in one place so that you can train models on much bigger data assets. And we have many different examples of this I’m just going to get one. This is some of the proprietary genomic data we have. So sequence genomes largely from microbes and metagenomic sequencing from companies like Radiant Genomics at Lodo on Warp Drive Bio and work we’ve done at Ginkgo. And just in this chart you can see the size comparison of our proprietary data to what’s out there in some public databases.

And this is means that our customers can go and get access to this and find a new protein or a new enzyme or a new natural product and here’s a quote from Sumitomo the great transparency and sophisticated data set was Gingko’s strengths. So that transparency having access to this I think is critical and unique to Ginkgo to be able to get that range of data. Also at Merck they talk about the professionalism and experience of Gingko’s employees. So again having these experts who can help you navigate all this and similarly — similar comments from Givaudan. Great quote up here. So Nicholas Ohler over from Lygos, Chief Technology Officer there. He said Gingko’s entire team was quite talented, but the early results on one of our projects are stunning and supports Lygos’ mission of accelerating the world’s transition to high-performing sustainable products.

Okay. What’s interesting about this is this project you could you look at it when we announce it, it was like six or nine months ago, recently. And so how do you get stunning results in that short period of time in biotech? And the answer is you’re not starting from scratch. So you’re building on both existing hydro, but infrastructure that you can turn on immediately and also large code base of what we would call it like IP and genetic assets that you can make use have to go faster right? Trent from Microba SVP Therapeutics Gingko’s expertise and resources have moved our drug discovery project along at a pace that just would not be possible either using internal resources or by a traditional CRO approach okay? And so again this is access to a scale and speed that you wouldn’t otherwise get and Bob Reiter at Bayer, Head of Crop Science talking about the open innovation approach in other words accessing external service providers instead of doing it in-house bring higher-quality biological solutions and innovative technologies to the market faster.

And so I think these types this type of speed is one of the key advantages that our customers are seeing on the platform. Next I want to talk about, one of the ones that gets to be really excited for small companies. So if you have a chance I would encourage you to go watch Jasmina’s talk from Ferment. And so what’s cool about Jasmina is she is the CEO of Arcaea. She gave a talk at Ferment — last Ferment, which was about 1.5 years ago. And at her talk this time she said year and half ago I was up here announcing that we had launched the company. I raised money and we’re launching Arcaea. And then here I am year and half later and I’m showing you my first product. And so that type of speed in biotech even in this cosmetics biotech I don’t really care.

That type of speed is really unheard of. And the reason it was possible is normally when you raise a venture around as a start-up biotech company, the first thing you do is you call Alexandria real estate and start being shown very expensive overpriced real estate in Kendall Square and go look for a lab and then you start to go up and buy a bunch of expensive equipment and stock that lab and you start hiring scientists. And nine months or a year later, you’re doing serious work. Here within weeks, able to deploy high throughput automation at Ginkgo to work on these projects. And that is why we’re able to go so much quickly. And also what save journey the cost of needing to build out that lab in the first place. Hugely valuable to small start-ups in the biotech place.

And by the way, this is something that was absolutely seen with Internet companies and cloud computing in the mid-2000s, right, the Perth of AWS and these companies that could start cloud native unallowed them to save on building out server box. And so I think that’s a real similar opportunity here in the biotech sector. Okay. So this is an important point. I think from a standpoint of the industry’s efficiency. So if you look at an average small biotech company, at the beginning, that dotted line in the middle there is sort of like their R&D teams. They hire an R&D team. They do all that work. They get the lab. They get it going and here it is, okay? Prior to having your drug going into clinical trials and animal studies and so on like locking your candidate, you wish you had more R&D, right?

If you have more R&D, you’d get to a better candidate. If you add more R&D capacity, you’d go faster, right? But you’re like, you don’t want to hire too many people and so on, so you kind of keep it at this level and you get to the best candidate you can get. And then off you go, you go into animal studies and clinical trials. Well, now suddenly, you wish you had less R&D spending, because you’re trying to conserve cash, get that clinical trial result and show that your new application in pharma works. And once you get a good result, well, now you want more R&D again, because you want to build out a really robust bigger pipeline in that area, okay? So that’s the sort of sign way there. Not efficient to how we’re doing it now or either overshooting or undershooting and then importantly in a tight capital market that middle dip turns into R&D team layoffs, which is what we’re seeing across the industry today for small biopharma companies.

So our suggestion would be wouldn’t it be better to be having your scientists accessing that type of capability a smaller team, accessing that capability as a service. So that when you need a lot at the beginning you got it. When you need less in the middle you turn it off and then you turn it back on later. And we have some groups that are doing that. You can see Kristen of Prokarium, Dave of Synlogic, talking about how Prokarium is now dedicated to driving our lead program into clinical trials this year while leveraging our partnership here with Ginkgo to accelerate our discovery work, right? So I really like that. I think that’s a good way to make the whole industry more efficient. All right. So I want to say this and I think that’s a message that I gave at Ferment and I think it was like well received by folks in terms of why you might want to use the platform, right.

So, let’s say you want to — you hear all that. You’re like, I really want to use Ginkgo platform. So what do you do about it? Well, the first thing you could do is just go to our website and click on a link that says work with us, and you’ll get an e-mail from our scientists and folks on the commercial team and they will ask you how you use — what are you trying to accomplish and how could Gingko’s platform be relevant. But some people look at that and say, I don’t have time for that conversation. I really want to know is Gingko’s technology relevant to my application. I want to know that ahead of time. And so in order to solve that problem, we launched Services. And the first service we offered was Ginkgo Enzyme Services. And I’m going to talk more about that in just a minute.

But that was to basically say, if you’re doing enzyme work, this is the full suite of things we have at Ginkgo that can help you out and come hear from our scientists and we’ve got webinars and things to show you how it all works. That was really well received over the last half year or so and is driving a lot of like funnel for us in terms of new customers getting on the platform. So at Ferment, we’re happy to announce four new services: Ginkgo Microbe Services, Ginkgo Cell Therapy Services, Ginkgo AAV Services and Ginkgo RNA Therapeutic Services. And you can see here I highlighted a few recent acquisitions, the Ag Biologicals R&D group from Bayer that, we acquired in StrideBio acquisition, which I’ll spend a minute on a second and Circularis in circular RNA.

Those assets are also available to our customers as part of these services. And so there are virtual events things coming up that, I encourage you to take a look at, if you’re interested in these things. I do want to dive in just for a minute on the StrideBio. This is super exciting to me. A, the technology is very cool and I won’t belabor it, but these are folks who are really just leaders in doing the protein structure around these AAV capsids and identifying key regions of the structure that would be worth modulating to work on some of the key challenges in gene therapy. And in fact a lot of people knew this about Stride, right? So when we announced the acquisition, we had just an enormous amount of inbound interest from folks, who are saying, hey, can I get access to these capsids can I incorporate this into my gene therapy products.

And we have 30 active conversations going on right now that other folks that called us or folks that we reached out to that we knew would be interested in this sort of thing. And so I do think this idea of — behind this it’s not just Stride’s assets. It’s all Ginkgo’s automation. You can see that on the left there and all being able to build many large designs. It is the combination of unique assets plus Ginkgo’s platform, plus our ability to go out and sell and do commercial work and be good alliance managed partners and we just have experience now more than 100 R&D projects on the platform where we’re working with all these different customers in our history. That’s a real skill set. It allows us to harvest value from these platform assets where other people wouldn’t find it.

And then importantly, we also structured these deals in order to best take advantage of that for Ginkgo. So you’ll see us aligning most of the cost of the deal being put into things like downstream value share milestones and things like that for the partner. We would love to do more and more of those types of acquisitions. It’s something we’re actively looking to do. I think the StrideBio is a real case study of what works well for both sides. This asset just does. It’s a lot more valuable once it’s up on Ginkgo’s platform, and the folks — the previous owners of Stride don’t really benefit from that. Okay. So I want to talk about a really exciting updates on how we’re doing some of our services. So the number one request we get from customers is to improve to better technically de-risk cell engineering.

So like the three thing customers care about, they want it to be less risky, they want it to cost less and they want to be faster. But the one they really want the most is to be less risky all, right? And you see this — some folks like Nick at Lygos hey as a CTO of a growing company what can I possibly do better than work with Ginkgo to de-risk my plans right and Keith of Optimvia, the likelihood of success for our project specifically was seen to be improved, with the technical capabilities at Ginkgo. We love that we can — some people get that we can make things more technically successful. But a lot of people don’t, right? Like we’ll go to folks, and say listen in our experience doing a project like this we have like a 90% success right here, it’s really going to work and they’ll be like I don’t believe you.

And it’s not a problem about Ginkgo, it’s a problem about biological engineering, right? Like, this is considered to be R&D. Like it’s just – it might work and it might not, right? So one of the things that I’m going to — I’m doing to combat that is for our most mature services so this is in our Enzyme Services — Ginkgo Enzyme Discovery Service, Enzyme Optimization Service, Protein Expression Service, we are moving to a success-only payment. In other words, again, these are for shorter duration high probability projects and we bet them. If we succeed you pay us, if we don’t you don’t, right? And this is to move away from the model today, or if you work with a CRO or someone else in the research space, it’s sort of like if you ask someone to build a house for you, and on the day that you’re going to move in, the house fell down and they said, well, yeah, write me the check anyway like at least I tried, right?

And that’s what research work looks like. And so we think with our platform, we can start to again by treating biology like an engineering discipline and driving scale, move this to more an engineering discipline and then price like an engineering discipline, like we get paid when it works. And so we think this is really exciting. I think it’s about a week and a half since we announced this. A lot of excitement about this. It is a new way to — it’s a new type of offering on the market really. And we think it’s one that Ginkgo could really do well at and our customers are going to love. Okay. Last thing, I want to talk about is our progress in Biosecurity. I think, we are — you see this with AI. You see it with just sort of COVID and Bio in general.

I think like there’s a lot of disruption happening in the world right now, it is important for the folks building these types of technologies to approach them with care, right? And I think if you look at the history in computer science, alongside increasingly powerable computers and network computers and so on, you add the birth of the field of cybersecurity whose job was basically to ensure that we could do all that type of computing activity with a level of safety both economic and national security. As the tools for engineering biology get more sophisticated, more widely distributed, alongside that we should be building up the tools of biosecurity. It’s very analogous. And we have an interesting thing, where fortunately those tools today are still like, mostly centralized and relatively weak.

It’s not like everybody is able to be engineering cells in their basement or whatever in the garage, but that — I do see that day coming in the future. So, we want to be building out biosecurity tools in advance of that. Separately, nature as we saw with COVID-19 throws off malicious biological code already, right? It is doing a lot more of this than we are as humans. And so, these tools are also amazing tools of public health in the interim period, while the tools of bioengineering are falling in costs and becoming more widely distributed. So, we can kind of work on a public health problem, while also getting ready for sort of the DNA age, just like we had to get ready for the computer age. I’m really excited by the range of expansion of our biosecurity platform.

This really originated — many of you are familiar with the work we’re doing in sort of school testing and prisons and things like that. A lot of that work obviously is drawing down at the end of the COVID emergency order here in the US. But alongside that, we were fortunate to be working with the CDC for example in airports in the US doing things like collecting wastewater, anonymous sampling from passengers and sequencing to look for new variants. And many of you remember this, but first sequence BA2 and BA3 coming out of this program to detect in airports. We think of it like a radar system, right? We’ve been working to expand that internationally as the some of the folks that were either already deployed in or have MOUs with or expanding into some of the flags up there.

This is not the only place that you would like to have persistent monitoring, right? You’d also like to be doing this in places, where we’re congregating a lot of animals, right? So, animal agriculture, honestly, you’d also like to look after it for plants. Agricultural pests as well in the future as well as doing things like hospitals and nursing homes and in crisis settings like we’re doing work in Ukraine for example. I do see a shift that we’re trying to pull off. You can see it on the right-hand side of the slide, where we are increasing the amount of sort of federal and international work we’re doing with folks like the CDC and other countries. That’s really the thing to watch in the second half of this year is we’re going to be working to make that shift from our programs domestically to these international programs, where we see good interest.

And we see a real opportunity for like a network effect, where one country is going to be very interested in the data happening at other airports. And interestingly, what the magic of international airports is flights are coming in from all over the world. So, these international airport programs, we see — we now tested samples and done the sequencing and so on from I think more than 60 countries coming into these to these airports. So having these nodes out there having that data globally, it’s sort of interest to every country, not just the country that we’re testing in. And so we’re really excited to see that develop, but it is an early and a new market. All right. So I’d like to end on this slide. I am super excited — ferment going be barred up.

But this year was just amazing like to see all of our customers talking about the platform to hear direct feedback about what it is we can do to make it better. That feedback loop is really working at Ginkgo and it gets me excited. And I think as we’re doing all that and making it better by implementing biosecurity globally, we get to do all that with care. So thanks for the time today, and pass it to Anna Marie for Q&A. Thanks.

Anna Marie Wagner: Great. Thanks, Jason. We’ll switch to Q&A in a few moments. Before we do, I wanted to get through a couple of housekeeping items. In my role, I respond to a lot of investor e-mails, and I’d like to make it easier for all our investors to benefit from the questions that are being asked. And there’s been a couple of recurring themes. So I’ve added two new slides into the appendix materials that I’m hoping will be helpful. The first which Mark alluded to provides more clarity around stock-based comp. And in summary the vast majority of the stock-based comp, we’ve recorded since going public is related to shares granted prior to going public. That’s been a common source of confusion. So, hopefully, that will help clarify that as well as provide some modeling tools around what’s left.

The second slide provides some additional details on stock sales by our founders. This data is all publicly available, but some of the market data providers don’t accurately pull our share counts, because they sometimes exclude different classes of shares. As you’ll see on the appendix slide our founders still own over 400 million shares. That represents over 20% of the company. They did have some mandatory sell-to-cover transactions when their RSUs were settled and have put in place small 10b5-1 plans. But both of those are dwarfed by their core holdings most of which sit in illiquid Class B shares. So I’m hopeful that those slides are helpful.

Q&A Session

A – Anna Marie Wagner : Now we’ll move on to Q&A. As usual, I’ll start with a question from the public and remind analysts on the line that if they’d like to ask a question to please raise their hands on Zoom, and I’ll call on you and open up your line. Thanks all. All right. It looks like everyone has managed to reconnect. So we’ll go ahead and get started. The first question as I mentioned always comes from retail. This comes from Mark De [ph] on Twitter. Since the number of projects is the best leading indicator for future platform revenues, how do you feel about your original forecast of adding 100 projects for 2023 when looking at the pipeline of projects are you on track?

Anna Marie Wagner: All right. Thanks so much. So a final call if there are any other questions to raise your hand but we are just about at time. And so for once Ginkgo hosted a call that didn’t run over new KPI for me. And we’ll let Jason go catch this next flight. Appreciate everyone joining us this quarter and we’ll see you next time.

Jason Kelly: Thanks, everyone.