Good evening. 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 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. I'll take questions from analysts, investors, and the public. You can submit those questions to us in advance via Twitter, hashtag #GinkgoResults or email at investors@ginkgobioworks.com. All right, over to you, Jason. 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. 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, by 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. 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 outsource some of the R&D work they might have considered doing in-house. And to state the obvious, that is a higher bar to meet at the largest, most sophisticated companies, where Ginkgo really has to showcase our scale of automation and data assets. They, they have to add something to the considerable resources those companies have already in-house. And so I'm 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 these customer successes 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 multi-year 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 Dmytruk to dive into our performance more deeply. I'm really thrilled that Shyam Sankar has agreed to be Ginkgo's Board Chair and provide his leadership. Shyam is currently the CTO of Palantir and joined our board about eight years ago. So this was, to give you some perspective, about one year after Ginkgo did Y Combinator. Shyam has seen Ginkgo grow from, you know, about 50 people to our current scale as a public company today, and the intuition that he has built up over the last years about that interface between biotechnology and what he's learned being on the board of Ginkgo and the tech industry that he's in natively at Palantir, I think is going to be particularly invaluable for Ginkgo 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. We're super happy to have him taking over as Board Chair. I'm also happy to report that our current Board Chair, Marijn Dekkers, will be staying on our board as he hands the reins over of chair to Shyam. I'd like to take a minute to personally thank Marijn for the efforts he put into growing me and the senior management team at Ginkgo as leaders over the last four years. You know, in his first years on the board, Marijn would spend a day or more a week at Ginkgo, meeting with our executives, helping them grow as leaders, which has been absolutely critical as we took the company public, and we're able to have that sort of institutional knowledge stay with the company on our leadership team. Marijn was coming in, you know, at the time from being the CEO of Bayer in 2016. You know, I'll be honest, often large multinational company CEOs do not fit in fast growth company startup culture. You know, Marijn was quite special. You know, in his 30s, he was tapped to turn around a struggling company called Thermo Electron. You know, Marijn 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. You know, Ginkgo has similar ambitions to redesign how biotechnology R&D is conducted across the industry. I really 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. I will always be thankful to Marijn for that contribution to Ginkgo. I, I look forward to continuing to work with both Marijn and Shyam in the years to come. All right, now let me hand it over to Mark to give a little more color on our financial performance this quarter. 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 the 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 subsegments. Cell engineering revenue was $45 million in the quarter, up 2% compared to the second quarter of 2022, which had benefited from a large one-time milestone payment. 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. 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 one-time 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 one-time items, services revenue grew roughly twice as fast as operating expenses as we start driving efficiencies on our platform. Stock-based comp. You'll 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 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 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 $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. 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 impact 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-$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 recognize 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 multi-year 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 have 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 forecasts 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 constrain 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 in the largest quarter of cell engineering services revenue we've ever delivered, 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 $1.1 billion of liquidity at quarter end. Now, Jason, back to you. Thanks, Mark. Ginkgo just had its strongest quarter in core services performance. We started and signed more programs than we ever have 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. I also wanted to address why we're taking guidance down despite this strength. Part of this is, is some market weakness, right? We've 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. We're still seeing growth in new programs really across all market segments. The other factor that Mark mentioned is our deal structures, in particular, the success-based pricing model we introduced for some of our offerings at Ginkgo Ferment back in April. I want to spend a minute on this because I think this pricing model is it's frankly a trade worth making, even if it means we see less revenue than we were hoping in the second half of the year. The way I like to think about success-based pricing, to give you an analogy, if you look back in the, in the early 2000s, Google popularized this idea of pay-per-click ads, right? Prior to this, the dominant model was pay per impression, right? Think like a banner ad, right? The issue, issue, with an impression is you don't really know if it's worth anything to you as a customer, right? You know, you're going to show it out there. You don't know if a person's 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 pay-per-click ads offered surety to the customer of the value, and so they sold at a much higher price than impressions, and ultimately replaced impressions as a, as a model, largely. I, 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, a good job with the work," right? But ultimately, the technical success of that work is unpredictable, right? Whether we'll, 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, that Ginkgo's 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-year revenue from new program signs. 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. That, that is a big part of our mission of making biology easier to engineer here at Ginkgo, is to move to that world of more surety. Okay, first, I, I, want to spend a minute about how Ginkgo is driving towards platform profitability by, 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 budgets. Then finally, while 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. You know, 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. Looking forward to talking about that. Okay, let's jump in. I, I like this flywheel slide, because it shows why customers continue to bring their business to Ginkgo, right? 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, you know, I talked about that, with our success-based pricing, faster and cheaper than they could do in-house. Today, I want to look down at the bottom part of that flywheel and talk about how, as we add more, more customers and more demand, we get to build a bigger platform, and how a bigger platform drives improved economics and efficiency at Ginkgo. We've taken a lot of cues, in this journey from the history of the semiconductor industry. If you look up in the upper left there, you know, electronics used to be largely manufactured by hand, right? This is in sort of the vacuum tube era of electronics, right? With the advent of planar semiconductor manufacturing technology, you know, places like Fairchild and eventually Intel and so on, electronics manufacturing saw an enormous scale economic. In other words, you could automate planar semiconductor manufacturing, and so the cost per, you know, transistor on the chip fell dramatically, and this ultimately became called Moore's Law. You can see that down in the corner, which is this exponential improvement in chip quality and reduction in cost, that ultimately took consumer electronics from being, you know, just TVs and radios in the 1950s and dramatically expanded the electronics market. It's in almost everything today. Well, you know, 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, and that high cost and the low quality of that ultimately limits the market for biotechnology 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 a Moore's Law and get a scale economic that will ultimately move biotech into these new markets. You know, and much of our focus, you know, really, in the 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, you know, starting with different species, different markets. You know, 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, you know, these more than 100 active programs we talked about earlier. About a year ago, we saw that 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. To support that, we hired and built a world-class, you know, operations or industrial engineering, it's often called, team, who did a deep diagnostic of the platform. You know, literally, diving in, you know, 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. The, and the sort of industrial engineering nerdy terms for this are overall equipment effectiveness, OEE, and overall people effectiveness, OPE. We tracked all that across our systems, and we saw through that diagnostic that we could see a process improvement that could drive, you know, 1.7x-5x higher throughput in how we use our equipment, and nearly a 3x productivity improvement, without needing major handout additions. This is why what you're gonna see already this quarter, but, but coming in, in, you know, this, this year in general and into the, into the near future, is we're gonna be adding many additional programs. We're gonna keep signing up programs while constraining our total spending at the company level. That's where the rubber is gonna meet the road on our continued operational improvements in the second half of this year. I'm happy for you all to be watching how that plays out this year as we strive to meet those goals. I, I think it's really the most important thing we're doing at the company right now. Now, as we started to deploy some of the ops team's recommendations, we've already been seeing great results. That's part of the reason we just had this, you know, record quarter for program additions and cell engineering services revenue. This was 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, already this year, we've reduced program launch time leads by 48% through various process improvements. By the way, it's not just a matter of days. It takes a long time to launch programs at Ginkgo. We were able to cut nine weeks out of our internal processes as part of this. You can imagine that the knock-on effects of driving these efficiencies, you know, 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 and professional fees, as well as driving down, or driving, up overall team efficiencies. Okay, the bottom line is that we believe with the cash we have today, alongside these near-term operational improvements, which are really key this year, we're going to drive growth while keeping expenses in line. We have ample cash runway and a path to profitability as a result. All right, successful execution is what drives real value. 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. As a reminder, Ginkgo operates across a wide breadth of major industries, with both startup 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, you know, with the service they're getting, from Ginkgo? 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 a third of our new programs every year, even as we've accelerated growth and broken into new industries. This is our greatest vote of confidence, right? You know, customers have to choose to use Ginkgo's platforms. We have this nice check with reality in terms of whether they're coming back. I wanna highlight a few of the those examples today. I mentioned we're, we're a horizontal platform, and so, you know, we're industry agnostic, and so what we find are... It's often a more relevant variable, than end market in our customer engagements is actually the state of the company. On the x-axis, you can see that here, you know, are they a small company or a large company? 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, where their, where their majority of their R&D is going to biotechnology or a chemical company, where actually the majority of their R&D spending goes to petrochemical research? Where, where you fall on these two variables really affects the relationship we're building with those companies and how we grow with them. On the left half of this chart, startups 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. You know, that this is the equivalent, right? They'll start platform native here at Ginkgo without building out their own labs. We've seen a, a bit of that. However, they have this kind of sine wave here, where they'll come on and off the platform, depending on whether they're in the R&D phase. Like, think like a, a drug company that's spending a bunch of R&D to develop their therapeutic. They go into the clinic to run a clinical trial, and they don't want to spend on R&D, right? They wanna save that capital for their trials, then on the back end of that, if they do well, they come back and wanna expand again in R&D on our platform. 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. Sometimes in the middle, you'll see these startups drop off the platform just 'cause they're not doing R&D work during that period, or they're doing a lot less. On the lower right, we have more industrial-oriented, mature companies that have relatively stable R&D budgets, that is, big R&D budgets, and the key dynamic in this segment is: How quickly will they adopt biological tools and solutions, right? 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. 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 Robertet. These are all companies that are leading in helping this market move more and more into biotech. Even though they have big R&D budgets, we really care that they start to bet more on biotech. It's, it's similar to what I was talking about earlier with electronics, right? As Moore's Law improved the fundamental technology, more, more markets started adopting electronics, right? We wanna see the same thing happen with biotech in this category. That's how this category grows for us. Then I think if they do make that choice, and we're already in there, like we are at places like Solvay early on, we have the opportunity to grow with these customers as they grow their biotech R&D budgets. So I think it's a sticky fit for us, but you'll see us grow with their appetite for biotechnology. A recent example of this is Sumitomo. We signed our first deal with Sumitomo back in 2021 to develop more sustainable bio-based chemicals. 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. They have a commercial product that we helped them make in those early days now, and coming out of Ginkgo's 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 wanna spend a little, you know, kind of focus your attention on today in particular. I'm most excited about this because it's one of the newer areas for us to march into, but it, it really is the one I think that has the most near-in potential. For a long time, it was very hard for Ginkgo to sell into players in this space, right? The reason is, not to state the obvious, but these companies have big existing biotech assets. 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 decades. The bar to have something that is additive to what they have is much higher. That's the challenge there. 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. We've had a couple of great recent success stories that I wanna highlight briefly. 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 collaboration opportunity. Quick success stories like this with major customers open the door to broader relationships, and we're seeing that, right? Just on Monday, I was happy to announce a second broad collaboration with Merck. This builds on our biocatalysis deal that you saw us announce late last year. This is exciting because this is a different group within Merck than our first program. 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, not just with the group we started in. We have a ton of respect for partners like Novo and Merck. They have a really high bar, let me tell you, they push Ginkgo to get better. We're very excited about the progress with them and expanding with them. Okay, I wanna make sure it's clear that just 'cause 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. You know, we are planting the seeds of the biosecurity industry. You've heard me talk about that a lot in previous calls. You know, the customers for that market are ultimately governments worldwide. You know, we reflected a bit on how instrumental our U.S. government partnerships have been since Ginkgo started the company. You know, some of our earliest seed funding came from the National Science Foundation, right? We've been privileged to work with DARPA, you know, the same agency that launched the Internet and many other technologies, on about a half-dozen programs over the years. And you know, 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? I think the government can be a real leader there. As an example, here's 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. This is obviously two years before COVID, ultimately demonstrates to the world that we need to be making much bigger investments in biosecurity in the future. You know, I think that type of forward-looking activity is exactly why these places like IARPA and others exist. 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 agency's version of DARPA. The most recent program with DARPA is focused on cell-free protein synthesis. Being able to make proteins without a cell producing the protein to enable rapid, high-yield, distributed production of human therapeutic proteins supporting national security objectives. 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 ENDAR, 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? You can imagine why that might be useful. And most recently, this new program is focused on biosensors that continuously record and store genetic expression data. Think of it kind of like the flight recorder in an airplane. You know, DARPA and IARPA, IARPA and DARPA like these analogies to like, what is it that already exists? Think of it like that cockpit recorder recording what's going on. Well, we want to have that same idea for what's going on inside a cell to understand the mechanisms of action for emerging threats and to be able to respond, you know, efficiently. 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 these 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. All right, now I'll hand it back to Anna Marie for Q&A. Great. Thanks, Jason. As usual, I'll start with a question from the public. Just reminding the analysts on the line that if you'd like to ask a question, please raise your hand on Zoom, and I'll call on you and open up your line. Thanks, everyone. All right. Welcome back, everyone. As usual, we'll start with a retail question. I'm just gonna go down in the order folks raised their hands. Rahul, you'll be up, you'll be up first, and I'll open your line. The first question comes from BrandonA797 on... I think it's called X now. Is it called X? Yeah. - formerly known as Twitter. he asked- It is. - "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? Why do you believe it's the best approach? Yeah, that'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 at the company today. So the easy way to think about this is, and, and we've been spending a lot of time looking at what's going on with generative AI in other spaces, is that you're gonna have, I, I think, ultimately sort of foundation models in the, in the biology space, and then you're gonna train those models using kinda tasks, what are called task-specific data training on top of those foundation models. And, and this is, this is the sort of data that would be specific to, you know, say, for example, the activity of an enzyme or the binding of a 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, might train more of a foundation model. How do you get that, that sorta task-specific training data? Automation with a foundry, right? I actually think Ginkgo is in a very strong position today, where we can generate that type of task-specific data to train up models on top of large foundation models in biology. 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. I'll, I'll make one last point on that. I talked about this extensively, you know, during the call. It's hard for us to go in and convince companies to 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. One thing that's great about the AI revolution is all of those companies are asking the question: Well, could I? You know, 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? The answer to that, I think, is gonna be yes in biotech, and that's gonna play really well into Ginkgo's current automation infrastructure and where we're headed with AI tools. Thanks, Jason. All right, Rahul, I've just opened up your line. You should be able to ask your question. Perfect. Can you hear me okay? Yep. Yeah. Thanks so much, Anna Marie, Jason, [Kip], Mark. Thanks so much for taking my questions. I just want to quickly start by saying that the ENDAR project appeals to me as a Star Wars nerd. Sounds pretty awesome. I'm glad that landed, yeah. Clearly some big changes in the deal structure, that you've announced, the fixed-price pricing, the success base. You know, can you give us a little more color into how you're seeing this evolving into the Q3 pipeline? Then also now looking forward in the future years, as the backdrop changes, you know, is there potential for a reversion to the previous model or some sort of hybrid? Yeah, so, so I'm super excited about this. I tried to, to, again, get it across in, in sort of some of my statements, but I'd love to add to it, Rahul. Again, if you think of what -- like, what we offer is fundamentally R&D services to the market, right? Why is something coming out of a, out of a company's R&D budget and, say, not their cost of goods for a product? The answer is because R&D is this special thing. It's this thing you spend money on, and you kind of hope it works, right? In pharmaceutical industry, the, 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 know, the, if you want to even use the term engineering, all of it falls squarely in the R&D bucket today. Everyone considers it to be unpredictable. 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 of models and all the things that, that we can use to drive predictability in the work, once we know a certain class of project is predictable, I want to turn around and basically make that obvious to the customer. 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. I want it to be, you only pay us when you get a project that works, because then it's obvious to you, as the 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. I'm really excited about this direction. It does have this phenomena that, like, our projects take a while, and so in particular, in the second half of the year, as we're signing deals now, that have success-based pricing, if it's more than a six-month project, because of the nature of how the calendar works, all that's coming next year. That just is what it is. I, 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, like, as you would've seen, maybe at, at Ginkgo Ferment, it's in the, kind of, kind of enzyme and protein space. We have, we haven't expanded that success-based pricing to other areas yet. I'd love to. It's just a question of when we're ready. Great. Thanks so much for taking our question. Yep. Great. Thanks so much, Rahul. Matt Sykes from Goldman Sachs, I have just opened your line. You should be free to chat. Hey, good afternoon, and thanks for taking my questions. 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 gonna be success-based? What, what I'm really trying to get at is if the phasing of the revenue is gonna change. To kind of help us model a little bit better, how do we kind of size the success-based programs, you know, without sort of actually disclosing how many that, that are, that are in the pipeline or, or, sorry, that are active? Yeah, Mark, I don't know if you want to, to comment on this a little bit. I can say that for the types of programs we're going after, for success-based, which again, is in this area of sort of enzyme design, and protein production, these are, these are, are shorter timeline contracts, right? Think of the order six months. A long one would be one year, something like that. Mark, you should, you should probably chime in on, on some of the other questions there. Yeah. Average duration, let's say, in that sort of six-to-12-month range, with some plus or minus around that range. 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, it, it would be lower. We would expect it to be lower than what you've seen as an average in the past, but that is also somewhat mitigated by the lower duration, right? The amount of revenue that we're able to, in, in effect, sort of push through in a quarter. That's sort of one side of it. The other side of it is the revenue recognition. For a success-based program, you'd have to push all of the revenue, even though you're progressing it over those six-to-12 months, you have to push all of that revenue to the end of the program, and so that's gonna affect the phasing in a way that's sort of new for Ginkgo. So that's. 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, the 100-program target, let's just call it kind of round number, we have 70 more programs to go. We do expect the success-based and payments type program to be a meaningful component of the 70 to go. Not. It's not like half, for example. It's not the majority. It's, it's less than that, but it's a meaningful component of the 70 to go. If that helps you a little bit in terms of thinking about, percent of total business. That's, that's really helpful. Then just one follow-up. As you know, as we're 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's, like, Bayer payments and things like that that 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, and, and is that how we should think about it, or are there kind of acquisitions in there as well? Yeah, generally, yes, you should just think of it as organic. We do have a large contract with, with Bayer. 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. Got it. Thank you very much. Thanks, Matt. All right, Edmund from Morgan Stanley, I've just opened up your line. Edmund, if you're trying to speak, you're on mute. There we go. 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 and milestone-based contracts versus success-based pricing models versus market weakness? Yeah, Mark, do you want to speak to that one? Sorry, could you repeat that? Broke up a little bit. Yeah, it was sort of, how do you want to? Why don't you go ahead and repeat yourself, Edmund? Sorry. Sorry. On the, 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? yeah, I would say-- If you think about the reduction from the $175+, the, certainly the majority of that reduction is because of the timing of revenue recognition. 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. Then the remainder would be sort of the, the market impact that we're seeing in terms of on the industrial biotech side. Does that help, Edmund? Yeah, no, that's very helpful. Then, in terms of your success-only payment model, I'm just wanting to check if I heard correctly. It's currently only available in the enzyme services offering. Is that correct? Yeah, it's enzyme services and also, like, protein production, so it doesn't have to be an enzyme. It could be, like a protein manufacturing. You know, remember, customers are coming to us with, 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, that's a real stretch," we, we'd be interested in doing it still, if you want to take the research, you know, risk on it. But this is, this is our view is that's a risky project, and you still want to do it? That would be more of a, a, a non-success-based project. We would get paid more traditionally, but if it falls in our bands, then, then we would price it as success-based. We do that analysis, but yeah, it's in the area of enzyme design and also in the area of protein production. Got it. Then, on your IARPA contract, that sounds very interesting. Can you tell us more about this cellular flight recorder and share some economics behind the contract? Should you be successful, would these biosensors be leveraged in your biosecurity business, or could there also be applications in cellular engineering as well? Yeah. Yeah, I can speak to that. I don't know what we've released exactly on the contract economics. Financials aren't released, but go ahead otherwise. Yeah. Yeah. Yeah. I mean, I can just generally speak to the opportunity, and I would say in biosensors broadly, and this is. What I like about these programs is they are usually pushing the envelope of what you can do with the technology. You know, where do biosensors play? 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? There's a reason that bombs sniffing dogs are walking around airports, right? You know, your olfactory system, things like that, are, are sort of powerful, distributed sensor systems. That's sort of one application, and you do see interest again, you know, for a variety of reasons for that type of technology. The other is in our foundry, right? 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're where you're 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, you can really scale up the number of designs you can test per dollar. We have a whole group here at Ginkgo that does that sort of kind of strain selection type activities, where they're real experts in generating biosensors, really to make our projects less expensive and higher throughput for customers. That's part of the strength we can leverage here with IARPA, too. We've, we've been doing this for a while, but it is, it is neat to imagine some of the things you could do with it out in the field. Thank you so much, Edmund. Madeline from William Blair, you're up. I have just opened up your line. Hi, thank you so much. This is Madeline, on for Matt Larew. One question, I feel like this is covered a little bit in the deck, but you recently announced a lot of new programs with organizations that you've 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'll do multiple programs with? Yeah, I don't think we other than what we would have announced publicly, like project to project, I don't think we've, like, specified on a particular customer. Here, here I'd say two things. In general, I think our doing future projects with customers, Ginkgo gets in a better position because, because the first project is like a kick in the tires, pilot. Remember, again, we're a different way of doing things, right? People are often just trying to wrap their arms around whether, you know, Ginkgo can really hold up what, what, what it sounds like we can hold up in practice for them. That, that I would say in the general trend, is we get better deals over time. You, you also brought up this idea of, like, what we would call, like, an umbrella deal. Yes, the answer to that is yes. We, 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, that is great. I'm very excited to see more of that. You have to remember, we're very early in penetrating these markets, right? Like, a lot of the, the deals, I mean, it's great that we're getting new deals. A lot of these deals are, like, first deals with a customer, and then, you know, then we prove ourselves, and then we can expand to an umbrella. I mean, each one of those customers could fan into, particularly the larger companies, into a lot of future business for us. We're very much at the beginning. We do love when we get a customer to a umbrella contract. You know, it has happened a, a few times now, but yes, it's a great, great thing to get to. Great, thank you. That was super helpful. Then just one more from 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? Yeah, Mark, you want to speak to that? Sure, I'll take that. 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, if the guidance of 100+ 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. 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 contracts that we have in play today. Y- you should assume, of course, that there is a significant pipeline of opportunities that we're looking to, sort of close or even just activating on some of the Memorandums of Understanding that we've signed in various countries, getting those into kind of a revenue stage. That's sort of the current state right now. Yeah, I'd, I'd echo that. Our general, and we've been saying this for now 2.5 years in biosecurity, it is a combination of a 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, to add new, large contracts as they pop up, and then letting you know when that happens. So we'll, we'll keep doing that. I think that's still the right way for us to try to do our best job guiding for you all. Other, other than that, I'd second Mark's comments. Yeah. Great. Thanks so much. Thanks, Madeline. All right, Steve [audio distortion], or sorry, Steve Mah, from Cowen, I've just opened up your line. 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? You know, any color would be appreciated on, you know, any particular areas of strength and if there's been any deviations from what you've seen previously on the new program adds. It's the same story, Steve Mah, as we've seen in the past, which is the program adds are coming from pretty much across the, 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's a slide that kind of bridges the current active program count. So you can sort of back into roughly, like, what's happening with the industries, but it's, it's the same. Again, we're pretty happy it's. The adds are coming across all the industry segments. Okay, thanks. Then if I could sneak 1 in, how should we think about the gross margins of the biosecurity business, like, now that you're getting away from K-12? Thank you. Yeah, 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% ± 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'd like to be with that business, that said, it's in effect, a new business now. 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. It's it's gonna be the same type of evolution. I think it's gonna take some time to get to something that's kind of normalized, but that's how we're trying to target it. Maybe the, the one thing I'd, I'd add, Steve, to your on your first question around the program adds. It is. You know, we, we had closed a certain number of deals before, and then we also have, like, our general sales pipeline and how that all feels. It, like, like, I, I do wanna, you know, since a lot of the team listens to this, you know, the, the, I do wanna to give a shout-out to the commercial team at Ginkgo that really has building up what is now a really valuable pipeline, sort of, sort of sales machine that I think is unique for this type of selling, this type of, like, R&D, you know, advanced R&D services or whatever you want to call it, that we do here. it, it, it feels healthier than it's ever felt. That's really exciting to me, going into the latter half of the year. Yeah. Okay. Thanks, Steve. All right, Mark Massaro from BTIG. I just opened up your line. Great. Can you hear me? Yeah. Yeah. Well, thanks for the time, guys. I'm curious, what% of your work is related to enzyme design and protein production? I would love a little more insight on that as it relates to cell programs or, or maybe just cell engineering revenue as a whole. You know, Jason, you indicated that this may be the first call where we've heard that you may expand the success-based structures beyond that initial program, and you indicated that you might do that when you're ready. I guess, what would constitute readiness, and how should we think about the timing of that transition? ... You want to do the first one, Mark? You can do that. Yeah, I think we would have to get back to you. 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. 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've done enough of to have a good sense of where our probability of success is? That, that, that is the basic calculus. Because we-- because protein engineering and protein production are sort of like subcomponents of so many programs at Ginkgo, we've actually done a ton of that across the, you know, hundreds of projects that have been going on, and so we, we've accumulated good data, and so we felt like we could go out and, 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. If it's a brand-new area we're in, we got to get some reps, so we have an idea of kind of what it looks like. 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? It does. That's helpful. Then my second question, obviously you lowered the cell engineering revenue guide, but you didn't lower the cell program guide. I'm 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, you know, some of the transition to the success-based structures? Any sense on funnel would be helpful. Yeah, I mentioned this on the-- to answer there with Steve. I think, like I said, I generally feel like this is the, the best position we've been in for, like, health of sales funnel, you know, certainly since we started talking to you all and really in the history of the company. 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, I would say it is not, like, overwhelmingly because of success-based pricing. That, that is just a feature that for the types of customers that do that work, it is a way for us to close deals, you know, more efficiently and like, you know, hopefully over time, you know, more economically for Ginkgo, favorable. That's really what's driving that. That, that is I, I would say what's driving our confidence, you know, in program counts in the year is really just the, the sales infrastructure we've been building. I think that has really made major, you know, growth in the last year, and that's paying off now. It's really more from that. We do have decent visibility into that because we have, you know, the whole HubSpot thing in the funnel and where everybody is and all that stuff. Our deals don't close in two weeks, right? It's, we have some visibility. We don't know exactly when they're going to close, but we know when they're close to the end. Yeah. Okay, great. Thank you. Thanks, Mark. All right, last but not least, before we run out of time here, Gaurav from Berenberg, I've just opened up your line. Hi, this is [Annabelle] on for Gaurav. Thank you so much for taking questions. Going off of Mark's last question, could you elaborate a bit on how much macro headwinds are affecting new programs, if at all? Mark can, can comment on how much. I, I, I will say the answer is yes, in the category of in-industrial biotechnology, right? You know, Ginkgo serves agriculture, agricultural biotech, pharma biotech, industrial biotech. Those are the, those are the three big existing biotech markets. There's also, you could imagine other future market, building materials biotech. There's a few companies like that, but not a lot. Those three big categories, I think, some of, like the startup startups in the sort of industrial or new food, animal-free meat, all that area, that, that, that stuff has gotten really squeezed, just, you know, you can thank interest rates and tightening and venture capital and things like that. That, that has really created headwinds in that space. 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. So that, that, I would say, is, is really more of a market headwind. You don't see it quite as much in the therapeutic space because, like, that, that industry just is a little got a little more momentum behind it. You see a little bit, but the, the industrial sector is one where certain categories just aren't going to get funded now, that are a little more out there. That, that's just the reality of where we're at in the venture capital ecosystem today. Mark, I don't know if you want to, to comment on the- Yeah, I mean, that covers it. Just to maybe re-reiterate the point that I made earlier. If you think about the reduction in the guide, I, you know, the majority of that reduction I would attribute to timing of revenue recognition. Part of that is success-based payments, but part of that is just the way that the fixed price milestone contracts are structured. The rest is the impact of what I would just call the market on industrial biotech specifically. Okay, great. Thank you so much. Thanks, Annabelle. All right, we are at time. Before we go, just any closing thoughts, Jason? We, we didn't talk too much about it, but I did-- You know, my first category of strategic topics was around adding lots of programs without greatly increasing our, our, our company-wide spend. I do think that those, like, 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, the yields that, that we expect from the transformation team and sort of industrial engineering, like I spoke about. I'm excited to, to pull that off, and that's something I think you all can, can watch through the numbers here, but that, that would be a, a really exciting efficiency push on our way towards profitability. That's maybe the other thing that we just didn't cover much in the questions, but I think is important. All right. Thanks, everybody. Thanks.