Ginkgo Bioworks Holdings, Inc. (NYSE:DNA) Q2 2023 Earnings Call Transcript

Ginkgo Bioworks Holdings, Inc. (NYSE:DNA) Q2 2023 Earnings Call Transcript August 10, 2023

Anna Marie Wagner: Good evening. I am 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 some 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. Today, in addition to updating you on our strong quarter, we’re going to dive deeper into our continued progress on driving operational efficiency across our platform, some recent customer successes and our expanding government relationships.

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, #Ginkgoresults or e-mail at investors@ginkgobioworks.com. Alright. Over to you, Jason.

Jason Kelly: I’m super excited to be chatting with you all today and celebrating a strong quarter for our team at Ginkgo. I always start with a reminder that our mission here is to make biology easier to engineer. And as we dig into the strategic sections today, you’ll see the progress we’re making on that mission, particularly on our path to profitability, driving efficiency through the scaling of our platform. I’m also proud of the work the Ginkgo team has accomplished this quarter as we continue to scale our platform. We had 105 active cell engineering programs on the platform this quarter, representing 44% growth over last year. Alongside that, we are delivering more work for customers. So we saw a 72% growth in cell engineering services revenue this quarter versus the same quarter last year and we’re driving that growth efficiently.

We’ll dive into what is enabling this productivity improvement in the next section. On the customer side, remember, in Ginkgo’s business, customers are choosing to some of the R&D work they might have considered doing in-house. And to state the obvious, they hire bar to meet at the largest, most sophisticated companies, where Ginkgo really has to showcase our scale of automation in assets that they have to add something to the considerable resources those companies have already in-house. And so, I am super excited to see the progress at Novo-Nordisk, Merck and Sumitomo who are among our most technically advanced customers. We’ve expanded our relationships with all of these customers in the last couple of months on the basis of strong performance and delivery on their programs.

You’ll see us sharing more with you on this customer success in the future. Our performance and balance sheet are unique in our market, and I’m really excited to capitalize on these assets in the coming months and years. We continue to have a strong multiyear runway with over $1.1 billion of cash on our balance sheet. That margin of safety gives us the runway to march towards profitability, both by improving the margin on our service fees via operational investments, and you’re going to hear about those from me later on this call and eventually as well by reaching downstream value potential from our portfolio of programs. One more piece of exciting news before I hand it back to Mark to dive into our performance more deeply. I’m really thrilled that Shyam Sankar has agreed to be Ginkgo’s Board share to provide his leadership.

Shyam is currently the CEO of Palantir and joined our Board about 8 years ago. So this is give you some perspective about a year after Ginkgo. And so Shyam has seen Ginkgo go grow from about 50 people to our current scale as a company today. And the intuition that he has built up over the last year is about that interface between biotechnology and what he’s learned being on the Board of Ginkgo and the tech industry that he’s natively at Palantir, I think is going to be particularly invaluable for Ginkgo go coming up, especially now that you see new technologies like generative AI that are opening even more opportunities for biotech and tech to work together. Shyam’s experience building Palantir is going to be absolutely critical for us coming up.

So we’re super happy to have him taking over as Board Chair. I am also happy to report that our current Board Chair, Marijn Dekkers will be staying on our Board as he hands the reins over a chair to Shyam. I’d like to take a minute to personally thank Marijn for the effort he put into growing me and the senior management team at Ginkgo as leaders over the last 4 years. In his first year on the Board, Marijn would spend a day or more, a week, I think go meeting with our executives them grow as leaders, which has been absolutely critical as we took the company public, we’re going to have that sort of institutional knowledge stay with the company on our leadership team. Marijn was coming in at the time from being the CEO of Bayer in 2016.

And I’ll be honest, often large multinational company CEOs do not fit in fast growth company start-up culture. But Marijn was quite special in his 30s, he was tapped to turn around a struggling company called Thermo Electron. And Brian led the acquisition of Fisher created Thermo Fisher and designed really the dominant business model in the life science tools industry still to this day. Ginkgo has similar ambitions to redesign how biotechnology R&D is conducted across the industry. And I really want to – I want to personally thank Marijn for his contributions, working with me directly to get our business model right here at Ginkgo. That is going to be a huge part of delivering on our mission of making biology easier to engineer. And so I will always be thankful to Marijn for that contribution to Ginkgo.

I look forward to continuing to work with both Marijn and Shyam in the years to come. Alright. Now, let me hand it over to Mark to give a little more color on our financial performance this quarter.

Mark Dmytruk: Thanks, Jason. I’ll start by discussing our cell engineering business. We added 21 new cell programs and supported a total of 105 active programs across 63 customers on cell engineering platform in the second quarter of 2023. This represents a 44% increase in active programs year-over-year with significant growth in the biopharma, food and agriculture and industrial sub-segments. Cell engineering revenue was $45 million in the quarter, up 2% compared to the second quarter of 2022, which had benefited from a large onetime mile statement. Importantly, when excluding the impact of downstream value share, cell engineering services revenue was up 72% year-over-year. This is our largest ever quarter for cell engineering services revenue and demonstrates the strong progress we’ve made in adding new programs and customers, driving platform efficiency and program execution.

Now turning to Biosecurity. Our Biosecurity business generated $35 million of revenue in the second quarter of 2023, a solid result in line with expectations as this business transitions away from K-12 COVID testing services. We are continuing to gain traction on an international scale, now totaling 11 countries with either active programs, pilots or MOUs and including a new MOU with Panama, our first program in Latin America and an important international hub. Biosecurity gross margin was 49% in the second quarter of 2023, which benefited from a mix shift to higher-margin product sales. We have also expanded our U.S. government partnerships domestically with new programs that span both our cell engineering and Biosecurity priorities with IARPA and DARPA, which Jason will discuss in the strategic section.

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 $73 million in the second quarter of 2022 to $104 million in the second quarter of 2023, representing growth and capabilities, particularly from our acquisitions in the fourth quarter of last year, including Bayer’s Ag biologicals facility and Zymergen. G&A expense, excluding stock-based comp, increased from $48 million in the second quarter of 2022 to $80 million in the second quarter of 2023. The increase in operating expenses and G&A, in particular, was impacted by several significant onetime costs in the quarter, the majority of which was non-cash.

We provide additional details on this in our adjusted EBITDA reconciliation in the appendix. Excluding these onetime items, services revenue grew roughly twice as fast as operating expenses as we start driving efficiencies on our platform. Stock-based comp, you will notice a significant step down in stock-based comp again this quarter, similar to what we saw in Q1 of this 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 starting to roll off. While the bulk of that adjustment is done, about 60% of the total $62 million stock comp expense in the quarter is still related to RSUs issued prior to us going public. Additional details are provided in the appendix to this presentation.

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 nonrecurring 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 $75 million compared to negative $24 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 second quarter of 2023 was $14 million, which includes an expansion of our process engineering lab.

In terms of our outlook for the full year, we continue to target 100 new cell programs. This represents rapid sequential growth and will require our team to launch more programs than we ever have before. This target is supported by a strong late-stage pipeline as well as operational investments we have made to improve our program launch process, which Jason will discuss in the next segment. We are, however, seeing a divergence between our program starts and our revenue due to both some market pressure in the industrial biotech segment affecting program size as well as strategic decisions we have made to structure programs with more fixed pricing and milestones, which impacts the timing of revenue recognition. While we are excited about the work we’re launching, we now expect our cell engineering services revenue to land in a range of $145 million to $160 million for the year.

A quick note on some of the strategic decisions we’ve made. As we’ve structured more customer contracts as fixed pricing with milestones, we recognized less revenue in the early phases of a program. For example, we have recently achieved an $11 million cash milestone from a customer as part of a larger contract. But because of the large size and relatively early stage of that program, Ginkgo will only recognize about $1 million of that as revenue in 2023 with the rest recognized over the course of a multiyear program. Similarly, we believe our success-based pricing model is a unique value proposition in the market and also a strong opportunity for Ginkgo to capture additional value on delivery. However, the nature of those programs means that revenue is only recognized at the end of the program.

And so a subset of programs launching in Q2 and beyond will not have any revenue recognition in 2023. We remain confident in our pipeline and are seeing improvements in the unit economics of our programs but are updating our guidance to reflect these timing and market dynamics. As for Biosecurity, we maintain our original guidance of $100 million, as discussed in previous quarters, the end of the public health emergency represents a significant shift in the business and the second half of the year is expected to look very different with the K-12 business largely rolling off. We restructured the business accordingly, refocusing our resources on the federal and international opportunities to build lasting Biosecurity infrastructure. I’ll also just mention that while we do not provide EBITDA or cash flow guidance, our internal forecast for cash flow have not changed for the year despite the lower revenue guide because in some cases, we receive cash ahead of revenue recognition.

And in addition, we have moved to thoughtfully constrained cash expenditures as we’ve driven efficiencies across the platform. In summary, we’re pleased with our overall progress in the business while navigating a challenging macroeconomic environment. We’re continuing to scale our business with strong program additions and the largest quarter of cell engineering services revenue we’ve ever delivered, and we continue to manage our balance sheet and cash flows in a long runway while obtaining flexibility to capitalize on near-term strategic opportunities with $1.1 billion of liquidity at quarter end. And now, Jason, back to you.

Jason Kelly: Thanks Mark. Ginkgo just had its strongest quarter in core services performance. We started and signed more programs than we ever had before and we drove higher platform output and thus higher services revenue than we ever had before. I’m going to dive into the drivers behind this in more detail coming up, but I also want to address why we’re taking guidance down despite the strength. So part of this is some market weakness, right. We have seen industrial biotech, particularly the venture funding in that space dry up. This is certainly having a near-term impact, largely in terms of potentially smaller sizes of programs that we’re seeing when we’re signing customers up this year in industrial biotech, although we’re still seeing growth in new programs really across all market segments.

But the other factor that Mark mentioned is our deal structures, in particular, the success-based pricing model we introduced for some of our offerings that Ginkgo back in April. And I want to spend a minute on this because I think this pricing model is frankly a trade worth making, even if it means we see less revenue than we were hoping in the second half of the year. And the way I like to think about success-based pricing, so to give you an analogy. If you look back in the early 2000s, Google popularized this idea of pay-per-click ads, right? And prior to this, the dominant model was pay per impression, right? So things like a banner ad, right? And the issue with an impression is you don’t really know if it’s worth anything to you as a customer, right?

You’re going to show it up there. You don’t know if the person is going to click through and go to your website and customers could have very different opinions about the odds of success of that impression, whereas the paper click adds offer surety to the customer of the value, and so they sold at a much higher price than impressions and ultimately replaced impressions as a model largely. I look at the R&D service business today, and it feels a lot like those banner ads, okay? So an R&D services company says to a customer, we will do a good job with the work, right? But ultimately, the technical success of that work is unpredictable, right? Whether we’ll meet the spec you want, we’ll do what you asked, but will it succeed, “Hey, that’s not our problem.” Success-based pricing that can goes introducing is our version of pay-per-click.

The customer knows they’re getting something of value. And that is a weapon for our sales team to drive better conversions and hopefully, better pricing over time, although it does mean that we won’t recognize that revenue until we complete successful programs. And so that pushes out in your revenue from new program signed. Overall, I’m really excited about this pricing innovation. It is good for customers. It’s good for Ginkgo and it is built on the reality that our platform scale is moving some programs, not all, but some class of programs we’re doing at Ginkgo from really what I’d consider R&D with uncertain outcomes and pricing to reflect that and moving them into the bucket of engineering, where we can start to offer customers much more certainty of the value they’ll receive that sort of pay-per-click.

And that is a big part of our mission of making biology easier to engineer here at Ginkgo to move to that world of more surety. Okay. So first, I want to spend a minute about how Ginkgo is driving towards platform profitability by unlocking productivity gains in our technology. The second topic today is I’m excited to be able to talk to you about some of our most recent customer success stories and how we are penetrating large existing biotech R&D bids. And then finally, we typically spend most of our time talking about commercial customers in cell engineering, I did want to take a moment to talk about our government relationships more broadly as we get a lot of questions about that, and we’ve announced a few recently. We’ve been working on government contracts for about a decade now, and they’re some of our most innovative programs.

And especially as Biosecurity transitions, I’m excited about the convergence between cell engineering and biosecurity that I’m seeing. So looking forward to talking about that. Okay. Let’s jump in. So I like this flywheel slide because it shows why customers continue to bring their business to Ginkgo, right? So when we’re going out and offering our service platform to customers, those customers are choosing us because they want cell engineering that is less risky. I talked about that with our success-based pricing faster and cheaper than they could do in-house. But today, I want to look down at the bottom part of that flywheel and talk about how as we add more customers and more domain and we get to build a bigger platform and how a bigger platform drives improved economics and efficiency at Ginkgo.

So we’ve taken a lot of us in this journey from the history of the semiconductor industry. So if you look up in the upper left there, electronics used to be largely manufactured by hand, right? This is in sort of the vacuum tube of electronics, right? And with the advent of Palantir semiconductor manufacturing technology, places like Fairchild, and eventually Intel and so on, electronics manufacturing saw an enormous scale economic. In other words, you could automate Palantir semiconductor manufacturing. And so the cost per transistor on the chips fell dramatically. And this ultimately became called Moore’s Law. You can see that down in the quarter, which is this exponential improvement in chip quality and reduction in cost that ultimately took consumer electronics from being just TVs and radios in the 1950s and dramatically expanded the electronics market.

So it’s in almost everything today. Well, that’s – this is sort of – we’re in that 1950s era when it comes to cell engineering today, right? It’s being done by hand and that high cost and the low quality of that ultimately limits the market for biotech today to really therapeutics and some agriculture products. We believe the potential is much bigger for biotech and our hope is that by automating these processes, we can drive our own version of Moore’s Law and get a scale economic that will ultimately move biotech into these new markets. And much of our focus, really, history of Ginkgo, but certainly over the last 8 years as we started tapping into venture capital and could invest in increasing automation infrastructure at scale, has been to broaden the platform to serve starting with different species of different markets, notably in the last 4 years, we added mammalian cells to our previous infrastructure in microbial and fungal.

That’s been really important in pharmaceuticals. So there’s been this big broadening of the platform, while all running it through the common infrastructure across these more than 100 active programs we talked about earlier. About a year ago, there was an opportunity to start to drive increased scale, not just through adding more infrastructure, but through better operations and utilization of the existing infrastructure with better processes. And so to support that, we hired and built a world-class operations or industrial engineering, it’s often called team who do – who did a deep diagnostic of the platform. Literally diving in with clipboards and going around and tracking exactly how much utilization we have of different equipment in the foundry, how people are using their time and so on.

And the sort of industrial engineering nerdy terms for this are overall equipment effectiveness, OEE, and overall people effectiveness, OPE. And so we tracked all that across our systems. And we saw through that diagnostic that we could see a process improvement that could drive 1.7 to 5x higher throughput in how we use our equipment and nearly a 3x productivity improvement without needing major hand additions. And so this is why you’re going to see already this quarter by coming this year in general and into the near future is we’re going to be adding many additional programs. We’re going to keep signing up programs while constraining our total spending at the company level. And that’s where the rubber is going to meet the road on our continued operational improvements in the second half of this year.

And I’m happy for you all to be watching how that plays out this year as we strive to meet those goals. And I think it’s really the most important thing that we’re doing at the company right now. Now as we started to deploy some of the ops teams recommendations, we’ve already been seeing great results. So that’s part of the reason we just had a record quarter for program additions and cell engineering services revenue. This is driven by several improvements, including operational debottlenecking and accelerating our program launch process. We diagnosed through that process that we could reduce the time it takes to start programs at Ginkgo. And already this year, we’ve reduced program launch time leads by 48% through various process improvements.

And by the way, it’s not just a matter of days. It takes a long time to launch programs at Ginkgo. So we were able to cut 9 weeks out of our internal processes as part of this. And so you can imagine that the knock-on effects of driving these efficiencies. Our team can handle more projects, and we believe we can ramp up programs faster. Separately, on the cost side, we are driving significant in-year cost reductions by reducing high fixed cost items such as real estate expenses, professional fees as well as driving down – driving up overall team efficiencies. Okay. So the bottom line is that we believe with the cash we have today, alongside these near-term operational improvements are really key this year, we’re going to drive growth while keeping expenses in line and we have ample cash runway and a path to profitability as a result.

Alright. So successful execution is what drives real value. And so this brings me directly into our second strategic topic of the day, how we are delivering on projects for customers and how that drives loyalty and the thing I’m most excited about coming up, which is the penetration of large existing R&D budgets at a certain class of customers. So as a reminder, Ginkgo operates across a wide breadth of major industries with both start-up customers and large customers. We’ve had to become experts in alliance management in order to scale across all this. And one of the things we pay close attention to is how are we doing with customers, right? Are we delivering on their specs? Are they coming back for more work? Are they satisfied with the service they’re getting from Ginkgo?

And while it’s really hard to create sort of apples-to-apples comparisons in our industry, one of the things I’m most proud of is that returning customers typically account for over third of our new programs every year, even as we’ve accelerated growth and broken into new industries. This is our greatest mode of competencies, right? Customers have to choose to use Ginkgo’s platforms. We have this nice check with reality in terms of whether they’re coming back. And I want to highlight a few of those examples today. So I mentioned we’re a horizontal platform. And so we’re industry agnostic. And so what we find are – it’s often a more relevant variable then end market in our customer engagements is actually the state of the company.

So on the X-axis, you can see that here. They’re a small company or a large company. And then on the Y-axis, the other big thing we look at is how much in-house biotech R&D does this company already do, right? Are they a pharma company where the majority of their R&D is going to biotechnology or a chemical company or actually majority of their R&D spending goes to petrochemical research. And so where you fall on these two variables really affects the relationship we’re building with those companies and how we grow with them, okay? So on the left half of the chart, start-ups are a great early customer for Ginkgo. In other words, early in our life as a platform. They are often built natively on Ginkgo. So this is kind of like you think of the mid- to late 2000s where you had startups launching like cloud native on Amazon and things like that.

This is the equivalent, right? So they’ll start platform native here at Ginkgo without building up their own labs. We’ve seen a bit of that. However, they typically – they have this kind of sign wave here where they’ll come on and off the platform depending on whether they’re in the R&D phase, like things like a drug company that’s spending a bunch of R&D to develop their therapeutic then they go into the clinic, to run a clinical trial and they don’t want to spend on R&D, right? They want to save that capital for their trials. And then on the back end of that, if they do well, they come back and want to expand again in R&D on our platform. And so in this way, we grow with them, right? In other words, we do well in that second half, but it is a question of how well they’re doing?

And sometimes in the middle, you’ll see these start-ups drop off the platform just because they’re not doing R&D work during that period or they’re doing a lot less. Okay. On the lower right, we have more industrial-oriented mature companies that have relatively stable R&D by just say these big R&D budgets. And the key dynamic in this segment is how quickly will they adopt biological tools and solutions, right? So in other words, like if you look at the chemical companies, most of your chemicals today are made with chemical engineering, right? Not biological engineering yet. So we were excited this year to work with Solvay to establish their biotech innovation hub here in Boston, and we’ve had long relationships with Sumitomo, Givaudan and Roberta.

And so these are all companies that are leading in helping this market move more and more into biotechs. Even though they have big R&D budgets, we really care that they start to bet more on biotech. And it’s similar to what I was talking about earlier with electronics, right? As Moore’s Law improved the fundamental technology, more markets started to adopt electronics, right? We want to see the same thing happen with biotech in this category. That’s how this category grows for us. And then I think if they do make that choice, and we’re already in there, like we are in places like Solvay early on, we have the opportunity to grow with these customers as they grow their biotech R&D budgets. And so I think it’s a real – it’s a sticky fit for us, but you’ll see us grow with their appetite for technology.

A recent example of this is Sumitomo. We signed our first deal with Sumitomo back in 2021 to develop more sustainable bio-based chemicals. And based on the successful progress in that program, we’ve since launched two new programs with them in broader areas of their business. One other customer worth highlighting here is Givaudan, one of our earliest customers. And they have a commercial product that we help them make in those early days now, coming out of into technology. We continue to work with them today, signing a larger platform collaboration a couple of years ago. Okay. The upper right is the category that I want to spend a little kind of focus your attention on today in particular. So I’m most excited about this because it’s one of the newer areas for us to march into, but it really is the one I think that has the most near-end potential.

So for a long time, it was very hard for Ginkgo to sell into players in this space, right? And the reason is not to state the obvious, but these companies have big existing biotech assets. So unlike a startup or a large chemical company that’s kind of new to biotech, a place like a Merck or a Novo, they have huge biotechnology infrastructure built over a decade. So the bar to have something that is additive to what they have is much higher. So that’s the challenge there. But as we demonstrate success with these companies, we have the opportunity to really grow into their existing R&D budget because they are already bought in on biotechnology. And so we’ve had a couple of great recent success stories that I want to highlight briefly. So Novo Nordisk is a great example of a recently launched program.

It’s rapidly started showing technical success and progress and then unlocking a broader operation opportunity. Quick success stories like this with major customers open the door to broader relationships. And we’re seeing that, right? So just on Monday, I was happy to announce a second broad collaboration with Merck. This builds on our biocatalysis deal that you saw us announced late last year. This is exciting because this is a different group within Merck than our first program. And it highlights how, as we get to know a customer, they have a chance to see where our platform can apply across their whole R&D enterprise and help their scientists developing and manufacturing therapeutics, not just with the group we started in. So we have a ton of respect for partners like Novo and Merck.

They have a really high bar, let me tell you, and they push it go to get better. And so we’re very excited about the progress with them and expanding with that. Okay. I want to make sure it’s clear that just because we often talk about our private sector relationships that our government programs are some of our most innovative and they help push the platform forward in a lot of ways. And so we are planting the seeds of the Biosecurity industry. You’ve heard me talk about that a lot in previous calls. The customers for that market are ultimately governments worldwide. And we reflected a bit on how instrumental our U.S. government partnerships have been since Ginkgo started the company. Some of our earliest seed funding came from the National Science ambition, right?

We’ve been privileged to work with DARPA, the same agency that launched the Internet and many other technologies and about a half dozen programs over the years. And what’s unique about the government as a customer is that they don’t only think about products that would be useful today but also the critical infrastructure necessary to allow whole new product categories and industries to flourish in the future. As I mentioned, this is a big idea from my standpoint for all of the synthetic biology industry is how are we able to open new markets up in the future new applications. And I think the government can be a real leader there. So as an example, there was a press release from Ginkgo, you look at the date, 2018, when we started working with several government agencies on a range of Biosecurity programs is obviously 2 years before COVID ultimately demonstrated to the world that we need to be making much bigger investments in Biosecurity in the future.

And so I think that type of forward-looking activity is exactly why these places like IARPA and others exist. And so in the last couple of months, in particular, we’ve added a couple of great new programs with both DARPA and IARPA, which is like kind of the intelligence agencies, version of DARPA. And the most recent program with DARPA is focused on cell-free protein synthesis – so being able to make proteins without a sell producing the protein to enable rapid high-yield distributed production of human therapeutic proteins supporting national security objectives. So being able to make something in a place that would otherwise be hard to make it, allowing for both rapid response and to emerging threats as well as a more stable supply chain.

IARPA, that program, has collaborated with us previously on programs such as [indiscernible], which you can think of sort of like a radar for genetic engineering, like we check and look at a sequence and we say, was it engineered, all right? Imagine why that might be useful. And most recently, the new program is focused on biosensors, that continuously record and storage genetic expression data. So think of it kind of like the flight recorder in an airplane, IARPA and DARPA like these analogies to like what is it that already exists? Okay. So think of it like that cockpit reporter, recording what’s going on. Well, we want to have that same idea for what’s going on inside of cells to understand the mechanisms of action for emerging threats and to be able to respond efficiently.

Okay. So you might be picking up on this theme. But one of the things I’m most excited about as we make this transition to our Biosecurity business is that the interface between Biosecurity and cell engineering is getting stronger. Across the biosecurity value chain, our cell engineering business is both benefiting from the insights coming back from that monitoring business we’re building out internationally and then it’s contributing valuable tools back to that Biosecurity work, right? New types of sensors and things like that, that you can imagine deploying in the future. This is particularly strategic as we leverage more AI tools across our platform, where the structured and unstructured data sets are becoming increasingly strategic and valuable.

Okay. In summary, I’m really excited about the great work the team delivered on this quarter. They should be really proud of it. And I’m looking forward to continuing the efficiency gains from scale in our platform that are already paying dividends for the company. Alright. Now I’ll hand it back to Anna Marie for Q&A.

Anna Marie Wagner: Great. Thanks, Jason. As usual, I’ll start with the question from the public. And then just reminding the analysts on the line that if you’d like to ask a question, please raise your hand on soon, and I’ll call on you and open up your line. Thanks, everyone.

Q&A Session

A – Anna Marie Wagner: Alright. Welcome back, everyone. As usual, we’ll start with a retail question, and then I’m just going to go down and the order folks raise their hand. So Rahul, you’ll be up first, and I’ll open your line. The first question comes from Brandon A 797 on, I think it’s called X now, is it called X, Twitter. Do you envision a robotics brute force heavy future, an AI software computational future, a mix of both? Or is there another path in order to make biology easier to engineer? And why do you believe it’s the best approach?

Jason Kelly: Yes, it’s a super good question. And it’s something we’re paying a lot of attention to at Ginkgo considering we’ve made large investments in laboratory automation. I think that’s one of our strongest assets of the company today. So the easy way to think about this is – and we’ve been spending a lot of time looking at what’s going on with generative AI and other spaces, is that you’re going to have I think, ultimately, sort of foundation models in the biology space. And then you’re going to train those models using kind of task – what I call task-specific data training on top of those foundation models. And this is the sort of data that would be specific to, say, for example, the activity of an enzyme or the binding of an antibody or whatever it might be, some aspect of a feature of biology that you can’t get just from the raw kind of DNA unstructured data that might train more of a foundation model.

And so how do you get that sort of task-specific trading data, automation with a foundry, right? So I actually think Ginkgo is in a very strong position today where we can generate that type of TAS-specific data to train up models on top of large foundation models in biology. But also, our customers, I think, will come to us and ask us to generate that type of training data as they’re all becoming more aware of the value of large data sets in biology. And I’ll make one last point on that. I talked about this extensively during the call. It’s hard for us to go in and convince companies that have large existing infrastructure and lots of R&D scientists and things like that to outsource to our infrastructure, it’s a change in how they do their work.

So one thing that’s great about the AI revolution is all of those companies are asking the question, well, could I – I know my people are good and how I do my research today is good, but if I had access to this huge data set, could I do something different? Could I add to how I do my work today? And the answer to that, I think, is going to be yes, in biotech, and that’s going to play really well into Ginkgo’s current automation infrastructure and where we’re headed with AI tools.

Anna Marie Wagner: Thanks, Jason. Alright. Rahul, I’ve just opened up your line, and you should be able to ask your question.

Rahul Sarugaser: Terrific. Can you hear me okay?

Anna Marie Wagner: Yes.

Rahul Sarugaser: Thanks so much. Henry, Jason, Marie. [indiscernible] Thanks so much for taking our questions. I just want to quickly start by taking the [indiscernible] project appeals to me as a Star Wars Nerd sounds pretty awesome.

Jason Kelly: I’m glad that landed. Yes.

Rahul Sarugaser: So clearly there be some big changes in the deal structure that you’ve announced the fixed base pricing, the success base. So could you give us a little more color into how you’re seeing this evolving into the Q3 pipeline? And then also now looking forward in the future years, as the backdrop changes, is there a potential for a reversion to the previous model or some sort of hybrid?

Jason Kelly: Yes. So I’m super excited about this. I tried to again get it across in sort of some of my statements, but I’d love to add to it, Rahul. So again, if you think of what – like what we offer is fundamentally R&D services to the market, right? And why is something coming out of a company’s R&D budget and say not their cost of goods for a products? And the answer is because R&D is a special thing. It’s the thing you spend money on and you kind of hope it works, right? And in pharmaceutical industry, the odds of success are particularly low, but even in other industries, the fragrance industry, chemicals, food, there’s still research projects that may or may not work. Our view is biotechnology as a whole, like genetic engineering, you might even use the term engineering, all of it falls squarely in the R&D bucket today.

Everyone considers it to be unpredictable. And so what we’re doing is we’re finding that at a certain scale of infrastructure at Ginkgo and a certain amount of previous learning and training models and all the things that we can use to drive predictability in the work. Once we know a certain class of project is predictable, I want to turn to basically make that obvious to the customer. And this is the point I was trying to make about like Google offering pay per click instead of pay per impression. It is obvious if you only pay them when you get a click that the ad must have driven a click. And I want it to be – you only pay us when you get a project that works because that it’s obvious to you as a customer, you’re getting a project that works and your bar for paying for that is much higher, and it might even be able to come out of a budget that isn’t the R&D budget, which would be particularly exciting to me.

And so I’m really excited about this direction. It does have this on like our projects take a while. And so in particular, in the second half of the year, as we’re signing deals now that has success-based pricing if it’s more than a 6-month project because of the nature of how they count it work, all that’s coming next year. And so that just is what it is. But I wouldn’t expect us to revert back. I think this is something that ultimately is better conveying the value I’m giving to customers. What I’m hoping is to expand the aperture of the types of programs I could offer this for. Today, as you would have seen maybe at Ginkgo Ferment, it’s in the kind of enzyme and protein space. But we haven’t expanded that success-based pricing to other areas yet.

But I’d love to – it’s just a question of when we’re ready.

Rahul Sarugaser: Great. Thanks, so much for taking our question.

Anna Marie Wagner: Thanks so much, Rahul. Matt Sykes from Goldman Sachs. I’ve just opened you’re line, you should be free to chat.

Matt Sykes: Hey, good afternoon. Thanks so much for taking my question. Maybe just following up on Rahul’s question on success-based pricing. Could you talk about maybe what you expect the average duration of those success-based pricing programs to be? And sort of what you envision as sort of a percentage of programs that are going to be success based? What I’m really trying to get at is if the phasing of the revenue is going to change to kind of help us model a little bit better, how do we kind of size the success-based programs without sort of actually disclosing how many that are in the pipeline – or sorry, that are active?

Jason Kelly: Yes. Mark, I don’t know if you want to comment on this a little bit. I can say that for the types of programs we’re going after, for success space, which again is in this area of sort of enzyme design and protein production. These are shorter time line contracts, right? So think of the order 6 months, a long one would be a year, something like that. But Mark, you should probably chime in on some of the other questions there.

Mark Dmytruk: Yes. So the average duration, let’s say, in that sort of 6 to 12 months range with some plus or minus around that range. So they are much faster duration programs. They are also lower in program size. So, that is a smaller budget. When you think about, Matt, like the sort of revenue per quarter from a program, therefore, it would be lower – we would expect it to be lower than what you seen as an average in the past, but that is also somewhat mitigated by the lower duration, right. So, the amount of revenue that we are able to, in effect, sort of push through in a quarter. So, that’s sort of one side of it. The other side of it is the revenue recognition. So, for a success-based program, you have to push all of the revenue, even though you are progressing it over the 6 months to 12 months, you have to push all of that revenue to the end of the program.

And so that’s going to affect the phasing in the way that’s sort of new for Ginkgo. So, that’s – and then in terms of kind of the percent of programs, I guess the way I would think about it is if you just think about 2023, so the 100 program target. So, let’s just call it kind of a round number. We have 70 more programs to go. So, we do expect the success-based payment type program to be a meaningful component of the 70 programs to go. It’s not like half, for example, it’s not the majority. It’s less than that, but it’s a meaningful component of the 70 programs to go. So, if that helps you a little bit in terms of thinking about percentage of total business.

Matt Sykes: That’s really helpful. And then just one follow-up. As we are, again sort of on the modeling side for the services business for cell engineering, as we look at sort of the growth of that revenue, should we be thinking about that as generally all organic? I know there is like buyer payments and things like that to come in. But just in terms of like the $26 million from Q2 to $44 million this year. Is that sort of generally thought of as organic? And is it how we should think about it, or are there kind of acquisitions in there as well?

Mark Dmytruk: Yes. Generally, yes, you should just think of it as organic. We do have a large contract with Bayer. But remember, that was a contract we acquired in effect after the – or as part of that acquisition. It wasn’t a book of business. That was in effect given to us as part of that transaction, so.

Matt Sykes: Got it. Thank you very much.

Anna Marie Wagner: Thanks Matt. Alright. Edmund from Morgan Stanley, I have just opened up your line. Edmund, if you are trying to speak you are on mute.

Matt Sykes: Hey guys. Thanks for taking my questions today. In terms of the reduced guidance in cellular engineering, I was wondering if you guys can parse out how much of the adjustment was driven more by the fixed price in milestone-based contracts versus success-based pricing models versus margin weakness?

Jason Kelly: Yes. Mark, do you want to speak to that one?

Mark Dmytruk: Sorry, could you repeat…

Jason Kelly: He broke up a little bit. Yes, I think it was sort of how do you want to – why don’t you guy repeat yourself, Edmund, sorry?

Matt Sykes: On the reduced outlook for cellular engineering, I was wondering if you guys could parse out how much of the adjustment was driven by more fixed price and milestone-based contracts versus success-based pricing models versus market weakness?

Mark Dmytruk: Yes. I would say – so if you think about the reduction from the $175 million plus, certainly, the majority of that reduction is because of the timing of revenue recognition. And I would say the timing of revenue recognition, it’s about 50-50, the fixed price sort of milestone component and the success-based payment component. And then the remainder would be sort of the market impact that we are seeing in terms of – on the industrial biotech side. So, does that help, Edmund?

Matt Sykes: Yes. No, that’s very helpful. And then in terms of your success on the payment model, I am just wanting to check if I heard correctly. It’s finally only available in the enzyme services offering. Is that correct?

Jason Kelly: Yes. It’s enzyme services and also like protein production. So, it doesn’t have to be – it would be like a protein manufacturing. And we would do – remember, customers are coming to us like a spec they want to hit, right. Like, I would like a protein at this titer, right, and a certain class of protein. If our scientists look at that and say, hey, that’s a real stretch, we would be interested in doing it still, if you want to take the research risk on it, but this is – our view is that’s a risky project, and you still want to do it. That would be more of a non-success based project, we will get paid more traditionally. But if it falls in our bands, then we would price it as success-based. And so we do that analysis, but yes, it’s in the area of enzyme design and also in the area of protein production.

Matt Sykes: Got it. And then on your IARPA contract, that sounds very interesting. Can you tell us more about this study every quarter and share some economics behind the contract. And should you be successful with these biosensors be leverage new Biosecurity business, or could there also be applications in cellular engineering as well?

Jason Kelly: Yes. I guess would be I don’t know what we have released exactly on the contract economics.

Anna Marie Wagner: Financials aren’t released, but go ahead, otherwise.

Jason Kelly: Yes. I mean I could just generally speak to the opportunity and I would say in biosensors broadly. And this is a – what I like about these programs is they are usually pushing the envelope of what you can do with the technology, but – so where do biosensors play. So, one is absolutely, you can imagine being able to sort of deploy things in the field that are able to sense and ideally record what’s going on with like the sensing apparatus of biology, which is pretty powerful, right. Like this is the reason that bombs sniffing dogs are walking around airports, right. You all factory system, things like that or sort of powerful distributed sensor system. So, that’s one application. And you do see interest, again, for a variety of reasons for that type of technology.

The other is in our foundry, right. So, if you can use biosensors for certain types of features of performance of a cell, then you can incorporate those into the cell itself that you are – where you are engineering the rest of the DNA and use that to have like an in vivo check for the performance of your genetic design. When you can pull that off, you can really scale up the number of designs you can test per dollar. So, we have a whole group here at Ginkgo that does that sort of kind of strain selection type activities where there are real experts in generating biosensors really to make our projects less expensive and higher throughput for customers. So, that’s part of the strength we can leverage here with IARPA too. So, we have been doing this for a while, but it is new to imagine some of the things you could do with it out in the field.

Anna Marie Wagner: Thank you so much, Edmund. Madeline from William Blair. You are at. I have just opened up your line.

Unidentified Analyst: Hi. Thank you so much. This is Madeline on for Matt Larew. One question, I feel like this has covered a little bit in the deck, but you recently announced a lot of new programs with organizations that you have done previous programs with. Can you talk at all, do the economics differ for repeat customers, or is there any sort of bulk economics deal that you do with customers that you know you will do multiple programs with?

Jason Kelly: Yes. So, I don’t think we – other than what we would have announced publicly like project-to-project, I don’t think we have like specified on a particular customer. But I would say two things. In general, I think our – doing future projects with customers gets in a better position because the first project is like a kick in the tires, pilot. Remember, again, we are a different way of doing things, right. So, people are often just trying to wrap their arms around whether Ginkgo can really hold up, what it sounds like we can hold up in practice for them. And so that, I would say, in the general trend is we get better deals over time. You also brought up this idea of like what we would call like an umbrella deal, Yes, the answer to that is yes.

We have set that up with now a number of our longer term customers where we can make it easy to add new programs without renegotiating a gigantic IP contract and all the pricing and everything else. That is great. I am very excited to see more of that. You have to remember, we are very early in penetrating these markets, right. Like a lot of the deals, I mean it’s great, they are getting new deals, but a lot of these deals are like first deals with a customer and then you have to prove ourselves and then we can expand to an umbrella. I mean each one of those customers could fan into – particularly for the larger companies into a lot of future business for us. But we are very much at the beginning. So, we do love when we get a customer to an umbrella contract.

It has happened a few times now. But yes, it’s a great thing to get to.

Unidentified Analyst: Great. That was super helpful. And then just one more for me, I think last quarter, you said about 20% of the Biosecurity revenue was anticipated to be recurring. Is there any way you can give color on what you would expect that for this quarter and how you see that trending long-term as some of the K-12 revenue rolls off?

Jason Kelly: Yes. Mark, do you want to speak to that?

Mark Dmytruk: Sure, I will take that. So, a similar sort of number in Q3 – or in Q2, but more – I think more importantly, if you just think about the back half of the year. So, if the guidance of $100 million plus it implies, call it, $20 million or so of revenue in the second half of the year, you should assume that the K-12 has largely or almost completely rolled off out of that number. So, that kind of gives you a bit of a sense of what the sort of exit run rate in that business is based on sort of what we know today, based on the business and the contracts that we have in play today. And you should assume, of course that there is a significant pipeline of opportunities that we are looking to sort of close or even just activating on some of the memorandums of understanding that we have signed in various countries, getting those into kind of a revenue stage. But that’s sort of the current state right now.

Jason Kelly: Yes. I would echo that. Our general – and we have been saying this for now 2.5 years in Biosecurity. It is a combination of an emerging market and a pandemic, which had a lot of volatility. And so we were always basically telling you what we had in hand and not trying to overstate where things would go and then doing our best to add new large contracts as they pop up and then letting them know when that happens. And so we will keep doing that. I think that’s still the right way for us to try to do our best job guiding for you all. But other than that, I would second Mark’s comments.

Unidentified Analyst: Great. Thanks so much.

Anna Marie Wagner: Thanks Madeline. Alright. Steve Mah from Cowen. I have just opened up your line.

Steve Mah: Okay. Great. Thanks for the questions. Of the 21 new program adds, could you provide some color on what industry sectors these new program adds were in? Any color would be appreciated on any particular areas of strength and has there been any deviations from what you have seen previously on the new program adds?

Mark Dmytruk: It’s the same story, Steve, as we have seen in the past, which is the program adds are coming from pretty much across the sectors that we play in. I mean biopharma was a contributor, but industrial was a good contributor. The slide early in the deck, there is a slide that kind of bridges the current active program count. And so you can sort of back into roughly like what’s happening with the industries, but it’s the same. But again, we are pretty happy the adds are coming across all the industry segments.

Steve Mah: Okay. Thanks. And then if I could sneak one in. How should we think about the gross margin of the Biosecurity business now that you are getting away from K-12? Thank you.

Mark Dmytruk: Yes. I would say that you should expect us to target a gross margin as we develop that business in that sort of kind of 40% plus or minus range. If you go back and look at the history of Biosecurity, it was – it fluctuated quite a bit, sometimes from quarter-to-quarter, but you could sort of draw a line and say, well, that’s sort of where it normalizes. So, when we think about sort of where we would like to be with that business. That said, it’s in effect a new business now. And so it will take us some time to figure out sort of where the right sort of normal gross margin is. It took us a while with Biosecurity until we got to a certain scale before we even started seeing sort of a normalized gross margin. So, it’s going to be the same type of evolution, I think it’s going to take some time to get to something that’s kind of normalized, but that’s how we are trying to target it.

Jason Kelly: Maybe the one thing I would add, Steve, on your first question around the program adds. We had closed a certain number of deals per quarter and then we also have like our general sales pipeline and how that all fields. Like I do want to – since a lot of the team listens to this, I do want to give a shout to the commercial team I think that really has done building up what is now a really valuable pipelines sort of sales machine that I think is unique for this type of selling this type of like R&D, advanced R&D services or whatever you want to call it that we do here. So, it feels healthier than it’s ever felt. So, that’s really exciting to me going into the latter half of the year, so yes.

Anna Marie Wagner: Thanks Steve. Alright. Mark Massaro from BTIG. I have just opened up your line.

Mark Massaro: Great. Can you hear me?

Anna Marie Wagner: Yes.

Mark Massaro: Well, thanks for the time, guys. I am curious what percentage of your work is related to enzyme design in protein production. I would love a little more insight on that as it relates to cell programs or maybe just cell engineering revenue as a whole. And then Jason, you indicated that – this may be the first call where we have heard that you may expand the success based structures beyond that initial program. And you indicated that you might do that when you are ready. So, I guess what would constitute readiness? And how should we think about the timing of that transition?

Jason Kelly: You want to do the first one, Mark?

Mark Dmytruk: Yes. I think we would ask to get back to like the percentage of revenue that comes from enzyme and design and protein production, we would have to get back to you on that. That’s just the cuts that I don’t look at.

Jason Kelly: On the – what constitutes something moving into the success based domain, it is largely to do with, are we seeing enough requests from customers that are sufficiently similar to a type of program. We have done enough of to have a good sense of where our probability of success is. That is the basic calculus. And so because we – because protein engineering and protein production are sort of like subcomponents of so many programs at Ginkgo, we have actually done a ton of that across the hundreds of projects that have been going on. And so we have accumulated good data, and so we felt like we could go out and still have a good sense of what our success rate would be. That’s what we have to get to in order to move to other areas.

So, if it’s a brand new area we are in, we got to get some reps, so we have an idea of kind of what it looks like. And then we also have to see is there enough similar stuff coming in from customers where we have a feeling that this program, while slightly different, still would have similar success rate probability as the last one. Does that make sense?

Mark Massaro: It does. That’s helpful. And then my second question. Obviously, you lowered the cell engineering revenue guide, but you didn’t lower the cell program guide. I am curious if you could just elaborate on your funnel. Obviously, you need 66 in the back half of the year from 34 in the first half. I guess is some of your confidence around hitting that guide related to some of the transition to the success-based structures. Any sense on funnel would be helpful?

Jason Kelly: Yes. And I mentioned this on – to answer that with Steve. So, I think like I have said, I would generally feel like this is the best position we have been in for like health of sales funnel, certainly since we started talking to you all and really in the history of the company. So, I generally feel good about that. We obviously still have a big number to hit in the second half of the year compared to where we were in the first half. I would say it is not like overwhelmingly because of success-based pricing. That is just a feature that for the types of customers that do that work. It is a way for us to close deals more efficiently and like, hopefully, over time, more economically for Ginkgo favorable. And so like – that’s really what’s driving that.

That is I would say what’s driving our confidence in program counts in the year is really just the sales infrastructure we have been building. And so – and I think that has remained major growth in the last year, and that’s paying off now. So, it’s really more from that. And we do have decent visibility into that because we have the Hubspot being in the funnel and where everybody is and all that stuff. So – and our deals don’t close in two weeks, right. So, it’s – we have some visibility. We don’t know exactly when they are going to close, but we know when they are closer to the end, so.

Mark Massaro: Okay. Great. Thank you.

Anna Marie Wagner: Thanks Mark. Alright. Last but not least, before we run out of time here, Gaurav from Berenberg, I have just opened up your line.

Unidentified Analyst: Hi. This is Annabel on for Gaurav. Thank you so much for taking the question. Going off of Mark’s last question, could you elaborate a bit on how much macro headwinds are affecting new programs, if at all?

Jason Kelly: So, Mark can comment on how much. I will say the answer is yes in the category of industrial biotechnology, right. So, Ginkgo serves agriculture biotech, pharma biotech, industrial biotech. Those are the three big existing biotech markets. There is also, you could imagine, other future market building materials biotech. There is a few companies like that, but not a lot, okay. So, those three big categories, I think someone like that start-ups in the sort of industrial or new food, animal-free meat, all that area. That stuff has gotten really squeezed just you can bank interest rates and tightening in venture capital and things like that. That has really created headwinds in that space. And what that’s done, doesn’t mean we can’t work with people.

In fact, in some ways, it drives people to outsource a little more for cost savings, but it does kind of shrink the appetite for deal size like Mark was mentioning earlier. And so that I would say is really more of a market headwind. You don’t see it quite as much in the therapeutic space because like that industry just has a little – got a little more momentum behind, you see a little bit. But the industrial sector is one where certain categories just aren’t going to get funded now and that are a little more out there. And then that’s just the reality of where we at in the venture capital ecosystem today. Mark, I don’t know if you want to comment on that?

Mark Dmytruk: Yes. I mean that covers – just to maybe reiterate the point that I made earlier. If you think about the reduction in the guide, the majority of that reduction I would attribute to timing of revenue recognition. A part of that is success-based payments, but part of that is just the way that the fixed price milestone contracts are structured. But the rest is the impact of what I would just call the market on industrial biotech specifically.

Unidentified Analyst: Okay. Great. Thank you so much.

Anna Marie Wagner: Thanks Annabel. Alright. We are at time. Before we go to any closing thoughts, Jason?

Jason Kelly: We haven’t talked too much about it, but I did – my first category of strategic topics was around adding lots of programs without greatly increasing our company-wide spend. And so I do think that those efficiency gains in the platform are a big part of our motion in the second half of the year, again, for the Ginkgo folks that are listening, like delivering on being able to do all those new programs in a more efficient way, like seeing the yields that we expect from the transformation team and sort of industrial engineering like I spoke about. I am excited to pull that off, and that’s something I think you all can watch through the numbers here, but that would be a really exciting efficiency push on our way towards profitability. So, that’s maybe the other thing that we just didn’t cover much in the questions, but I think it’s important. Thanks everybody.

Anna Marie Wagner: Thanks.