Good evening. I'm Megan LeDuc, Manager of Investor Relations at Ginkgo Bioworks. I'm joined by Jason Kelly, our Co-Founder and CEO; and Mark Dmytruk, our CFO. Thanks, as always, for joining us. We're looking forward to updating you on our progress. As a reminder, during the presentation today, we'll be making forward-looking statements, which involve risks and uncertainties. Please refer to our filings with the Securities and Exchange Commission to learn more about these risks and uncertainties. Today, in addition to updating you on the quarter, we're going to dive deeper into a few case studies of how we're seeing our mission to make biology easier to engineer, come to life as well as provide further details on our diverse program pipeline and the growth opportunities we see in biosecurity business. As usual, we'll end with the 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 at #GinkgoResults or e-mail us at [email protected]. All right. Over to you, Jason.

I'm super excited to be chatting with you all today. I always start with a reminder that our mission at Ginkgo is to make biology easier to engineer. As we dig into the strategic section, you'll see the progress we're making on that mission, particularly with our AI efforts and our strong pipeline of active programs. We pursue this mission on behalf of a diverse group of customers. This is one of my favorite slides, having a customer list that ranges from agriculture to consumer goods, to chemicals to therapeutics is common for a horizontal tech platform, but it's pretty unique in biotech. It makes sense because all these diverse programs benefit from the scaling of the same underlying technology at Ginkgo. We've added programs with several new customers this quarter, including smaller companies like Nosh Biofoods in the industrial biotech field and Exacta Biosciences in the ag space, as well as large companies like Pfizer in pharma in addition to new programs with many of our existing customers. We took a view early on at Ginkgo that scale would be needed to drive our mission. And you see that reflected in our business model as a platform service provider. We had 116 active programs on the platform this quarter, representing 36% growth over last year, and our highest active program count ever. As our foundry scales, our data generation capabilities scale in turn. You can see this on the slide comparing some of our internal assets to public data assets. Our ability to generate data at scale for customers, paired with our existing code base, is a big part of the reason customers choose to work with Ginkgo, particularly as leveraging generative AI becomes a bigger priority for our customers. For those of you that tuned into our Investor Day, and I encourage you to watch the YouTube recording if you didn't, you know that we're using this data to build AI foundation models and fine-tune applications for biological engineering. Our recent partnership with Google is helping fuel this in the last quarter, and I'm proud of the progress the team is making on track with our plans. In fact, we've already achieved the first milestone in our partnership with Google. The reality is that biology is getting easier to engineer. We're really excited about that, what that opens up for our customers, better medicines, more resilient food systems, cleaner industry, but it has not lost on us that the advancement of biological engineering tools, particularly when coupled to advancements in AI, creates risk. We're sitting at the intersection of several exponentially improving technologies, and the world is grappling with how to keep up with the pace of change and limit the risks these technologies create. Our biosecurity business works hand in hand with our cell programming business to address this challenge. Helping build early warning systems and decision support for national security and public health is going to be critical to protecting against the potential misuses of these technologies, along with anything Mother Nature throws at us. I can't emphasize enough the synergies between these businesses. It's clear that there's an unmet need for biosecurity, but the question is, who is best positioned to grow into this large addressable market? We think Ginkgo is well positioned to do it as the tools we're building in our cell engineering business help provide the foundation for biosecurity. Likewise, our close connection to a biosecurity platform that is highlighting emerging threats allows us to be a better partner to our vaccine and therapeutic partners, ideally enabling us to make more effective countermeasures earlier in the risk cycle. And you're going to hear from me a bit in the strategic session about how we're building all that in biosecurity. 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 with the cell engineering business. We added 21 new cell programs and supported a total of 116 active programs across 76 customers on the cell engineering platform in the third quarter of 2023. This represents a 36% increase in active programs year-over-year, with significant growth in the biopharma and the food and agriculture verticals. Notably, we added 10 new biopharma programs in the quarter, a record number of new programs for any particular market segment in one quarter. Cell engineering revenue was $37 million in the quarter, up 51% compared to the third quarter of 2022, driven by our significantly expanded customer base. Now turning to biosecurity. Our biosecurity business generated $18 million of revenue in the third quarter of 2023 at a gross margin of 62%. Both revenue and gross margin benefited in the quarter as we closed out our last remaining K-12 COVID testing contracts. We're continuing to gain traction on an international scale, now totaling 14 countries with either active programs, pilots, or MOUs. Concentric is also progressing its bioradar offering with multipathogen detection and new efforts in zoonotic disease monitoring while also building a suite of next-generation biological intelligence capabilities, including AI-based epidemic forecasting. 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 compensation, increased from $74 million in the third quarter of 2022 to $123 million in the third quarter of 2023, representing growth and capabilities, particularly from our acquisitions in the fourth quarter of last year. G&A expense, excluding stock-based compensation, increased slightly from $59 million in the third quarter of 2022 to $62 million in the third quarter of 2023, supporting the growth of cell engineering revenue and the integration of prior year acquisitions. You will also see that we recorded a $96 million noncash impairment charge on a Zymergen lease facility, which Zymergen exited in the third quarter. While our full accounting for the Zymergen bankruptcy is not yet complete, we expect to deconsolidate the Zymergen financial statements effective October 3, 2023. In the fourth quarter, our accounting is expected to result in removing all Zymergen multiyear lease liabilities, along with its other financial accounts. Stock-based compensation. You'll notice a significant drop in stock-based compensation this quarter, similar to what we saw in Q1 and Q2 of this year. As a reminder, this is because of the catch-up accounting adjustment relating to the modification of restricted stock units when we went public has mostly rolled off at this point. While the bulk of that adjustment is done, about half of the total $54 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's important to note that our net loss includes a number of noncash income and/or expenses as detailed more fully in our financial statements. Because of these noncash 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 $84 million compared to negative $72 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 third quarter of 2023 was $4 million. Moving on to our outlook for the full year. In terms of big picture, we're expecting total revenue of $250 million to $260 million in 2023, in line with previous guidance. Now looking at the details and starting with new programs, based on third quarter results and pacing of new opportunities, we're now targeting 80 to 85 new cell programs in 2023. We continue to see growth in pipeline opportunities. However, the pacing of pipeline conversion has been impacted by both macroeconomic conditions as well as the fact that our cell programs are a complex enterprise sale. While we have undertaken several initiatives in the past year to address these two challenges, including process improvements through our contracting cycle, success-based pricing, and a focus on the biopharma segment, all of which have helped drive our metrics in the right direction overall, we have not yet fully solved the pacing issue, particularly as deals get into the final stages. I'll also note that in addition to our formal new program target, Ginkgo signed several tech licensing evaluation agreements in the third quarter, which allow customers to evaluate more advanced assets, such as the capsids we acquired from StrideBio. These customers might then execute a license agreement to continue using the asset. We did not include these deals in our program count as they do not involve foundry work. However, they do represent a new potential source of revenue for Ginkgo. Moving on to revenue. We're updating our cell engineering revenue outlook to be in the range of $145 million to $150 million. This is inclusive of $4 million in downstream value share we have recognized year-to-date through September 30. As for biosecurity, based on year-to-date results, we're increasing our revenue guidance to land in a range of up to $110 million. Fourth quarter revenue will be driven by federal and international partnerships, supporting pathogen monitoring and biosecurity infrastructure development as the K-12 COVID testing business ended in the third quarter. In summary, we're pleased with the overall direction of progress and continue to focus on scaling the business as we finish out the year. We remain focused on driving new programs to the platform in this challenging macro environment. We're excited about the significant traction we have made in the biopharma segment. And we continue to manage our balance sheet and cash flows to maintain a long runway while maintaining flexibility to capitalize on near-term strategic opportunities, with over $1 billion of liquidity at quarter end. And now, Jason, back to you.

Thanks, Mark. This quarter has been strong for Ginkgo. Our partnership with Google positions us well in utilizing AI for DNA and protein design. Additionally, our deal with Pfizer signals real commercial progress, which I will discuss shortly. However, I need to explain our revised guidance for cell engineering. As a young public company, we are building relationships and want to set ambitious yet attainable goals. Therefore, we are adjusting our guidance for cell engineering services revenue to $140 million to $145 million, down from our previous estimate of $145 million to $160 million. This adjustment is mainly due to the reduction in industrial biotech venture capital and smaller program sizes in that sector, as well as fewer new programs in Q3 than anticipated, which impacts Q4 revenue. I would like to highlight the importance of new program counts, as this is a key metric indicating our operational growth at Ginkgo: we improve with scale. We had 21 new programs this quarter, which was below our expectations; however, our enterprise sales infrastructure is stronger than ever. Notably, our new program with Pfizer demonstrates our commercial capabilities. This drug discovery deal in mRNA therapeutics is significant because drug discovery is harder to sell than manufacturing R&D deals, which have been our previous focus in biopharma. We must convince customers to outsource work to our platform that they prefer to handle internally. Moreover, as mRNA is a new and emerging drug modality, it shows our leadership potential. Importantly, this deal was successfully negotiated by our commercial and deal teams, demonstrating our scalability as an enterprise sales team. Closing such deals typically requires the engagement of the CEO and leadership team of small biotech companies when partnering with large biopharma firms like Pfizer. Ginkgo's ability to regularly close deals of this magnitude gives us a strategic advantage, a result of strong work and team building led by Jen, our commercial team head. If we achieve the high end of our updated guidance of 85 programs, it translates to 30 new program starts in Q4, which would signal our scaling efforts within the enterprise sales infrastructure and something I will be monitoring closely. With this updated guidance, we expect 36% to 44% growth in new programs and 32% to 37% growth in cell engineering services revenue year-over-year. Growth in scale is beneficial for Ginkgo, and I’m pleased with this rate. Now, I'd like to discuss our three strategic topics. First, I will share customer case studies illustrating our AI technology applications. Second, I'll provide insights into the programs we find most exciting and our overall program pipeline. Lastly, I'll outline our vision for the future of biosecurity as it relates to national security and its connection to cell engineering. Let’s begin. First, I want to discuss how AI integrates with Ginkgo's other assets and present case studies of its applications. We've previously talked about our foundry and code base. Our foundry, our automated labs in Boston, generate data at reduced costs as they scale. This data feeds into our code base, which can be reused across various customer programs. This enables us to leverage insights from one project to expedite the development of another. The data assets we possess can also train large AI models, influencing the experiments we conduct as we refine these models. We recently announced our partnership with Google Cloud, which will bolster our development efforts. This collaboration provides scalable compute power at favorable rates for training large foundation models and represents Google’s commitment to funding our model development as we reach certain milestones. We’re already on track to complete our first cash milestone and expect to achieve the second soon. One way we measure our progress in making biology easier to engineer at Ginkgo is by reducing the costs associated with achieving successful outcomes for our customers. This cost is influenced by three factors: the cost per unit operation, the number of unit operations required per design cycle, and the number of cycles a project undergoes. If AI enhances the quality of our designs, we can decrease the size of the libraries we use, leading to savings and better use of automation. Reducing the number of cycles required for a project significantly accelerates timelines, which is often more critical to our customers, particularly in biopharma, than budget constraints. I want to share two case studies showcasing how we’re improving these metrics. The first case study involves an enzyme engineering program we began this year. A customer approached us with an enzyme that another service provider had produced, but it was not meeting market demands. We tested various enzyme designs, utilizing our efficient screening capabilities to find an optimal solution. In the first design cycle, we discovered an enzyme that was 21 times more effective than what the customer provided, highlighting the speed and accuracy of our AI models. The second case study focuses on production rather than enzyme optimization. Here, we were able to achieve a 12.5-fold improvement in production of a small molecule compound in our first experiment, exceeding what the customer wanted us to accomplish by the end of the first year. This was possible due to the extensive knowledge within our code base. By the conclusion of the program, which took only 10 months instead of the originally projected 3 to 5 years, we achieved a 50-fold improvement, driven by machine learning and enzyme enhancement. These examples demonstrate the effectiveness of integrating our AI tools into customer engagements, and I'm enthusiastic about the potential they hold. Now, turning to our pipeline of customer programs, it's crucial to note that Ginkgo does not have its product pipeline. Instead, we have a pipeline of customer programs that we’ve negotiated and secured contracts for. In Q3, we achieved our highest number of active programs ever, with pharmaceuticals representing a significant portion of this. Additionally, I'm pleased to share where these programs stand in terms of maturity. As a result of our platform's strength, we're able to pivot to areas with greater demand as industrial biotech faces challenges. Our visual representation of these programs shows an impressive scale, reflecting the activity across various stages. This chart highlights programs that have reached over 50% completion, illustrating the relative progress we've maintained in an industry that often tracks a smaller number of drug assets. As some programs advance to 100% completion and customers choose to move forward, they enter commercialization. Currently, we have several programs actively being commercialized and a few that are fully commercial, generating royalties or equity for us. We are optimistic about expanding our pipeline in the upcoming quarters. Now, I want to touch upon the emerging national security focus on biosecurity and Ginkgo's role in this arena. Recent discussions have emphasized the intersection of AI and biology. Our leadership has been actively engaging in these conversations, recognizing that biosecurity must be prioritized. Despite its potential for misuse, ensuring public health is essential as nature presents its own challenges. The advancements in AI tools are driving governmental focus on responsible technology deployment in this area. Ginkgo has built biodefense tools in response to various needs over the years. We see significant investment gaps in monitoring and analytics within biodefense, where most funding has historically been geared towards rapid response measures after incidents occur. The fallout from events like COVID has shifted perspectives, driving governments to seek proactive detection and prevention systems. Our bioradar product exemplifies this effort, enabling continual monitoring of pathogens across various environments. We're expanding our monitoring capabilities beyond COVID to include over 30 pathogens, and our recent partnership expansion with the CDC exemplifies this commitment. We're also working on detecting agricultural and zoonotic threats, employing AI tools to enhance our analytical abilities. Our collaboration with partners funded by the CDC will develop predictive capabilities to foresee disease spikes, mirroring how forecasting is done for weather phenomena. Additionally, our BIOINT platform will play a pivotal role in national security by providing critical insights into biological risks. This capability will aid decision-makers in effectively neutralizing biothreats before they escalate. I believe our biosecurity and cell engineering efforts are mutually beneficial, with data generated from biosecurity bolstering our cell engineering initiatives, and vice versa. In summary, I am thrilled with our progress this quarter, notably in demonstrating our commercial capabilities with Pfizer and our relationship with Google in the AI space. I am eager to continue our growth trajectory in the ensuing periods. Now, I will turn it back to Megan for the Q&A session.

Great. Thanks, Jason. As usual, I'll start with a question from the public. Thanks all. Okay. Welcome back, everyone. Our first question comes from Clifford Long on Twitter. What milestones will be tracked to measure Ginkgo's success in building DNA's AI? What metrics can you share that will track the accuracy improvements when building AI over time?

Sure, I can take that one. Yes. So I think one of the things that's very interesting about Ginkgo is we have a lot of ongoing programs today. And so I think the first place we'll see the application of AI is in driving efficiency of all of that ongoing work. So you saw some examples of that in the slides I showed. But a big part of what we're trying to do next year is add lots of new programs while keeping a lid on our operational expenses. You will see that, in part, driven by the efficiencies we're going to gain in AI. And then secondly, I think in the longer term, AI represents an interesting interface to our platform. So I think we'll ultimately be able to open it up more directly to customers through AI tools. And so that's something we're excited about and part of the model building we're doing with Google.

Great. Thanks, Jason. We'll start opening it up to analysts now. Tejas from Morgan Stanley.

Good evening. Can you hear me okay? Perfect. So Jason, one quick question for you. Just in terms of the later program adds here and the implied sort of cell engineering guide for the fourth quarter, how should we be thinking about 2024? Consensus has you doing about $300 million in cell engineering revenue, but you guys are sort of in that $40 million to $50 million quarterly run rate at the moment. So are there any sort of like missing pieces there that we should be thinking about as we think about the year-over-year progression?

Yes, we are not providing guidance for 2024 yet. Our primary focus is on aggressively expanding our enterprise sales efforts and enhancing our ability to add new programs to the platform. I'm pleased to see that the number of active programs on the platform is increasing, and our capacity to manage more work has also significantly improved. This contributes to our excitement for the upcoming year. We will provide guidance in the next call.

Fair enough. And then one on just the tech licensing evaluation deals that you mentioned. Obviously, early days still, and you're not including them in the program count, but can you just give us some context around how meaningful a contribution this could be? And over what time frame do you expect sort of some early wins based upon your conversation so far?

Yes. So I would think sort of single-digit millions in terms of potential licenses or kind of lower double-digit millions and potentially some wins, certainly, within the next 12 months.

And maybe the only thing I would add to that, I think it will be an interesting thing for us to think about in the long term. Obviously, we have certain definitions for what makes for a major program at Ginkgo that gets added to our program count. I kind of hope over time we have more assets in our code base that can be more easily directly licensed into customers. That's obviously great. It's revenue back to us without a bunch of work. So I think those are nice things to see.

Next up, we have Steve Mah from Cowen.

Great. Can you hear me? Great. With regards to the new program adds, can you give us a sense if there's any particular partner class, which is harder to get over the deal signing goal line? And what specifically are you guys going to be doing to improve the deal closing timeline? If I heard correctly, it looks like you said your enterprise sales team is rightsized. So if it's rightsized, what exactly are you doing to kind of improve the deal closing timing?

Yes. I'll speak to it generally. If you want to add anything, feel free. I know the timing is something you consider carefully. First, I don't think we're fully optimized with the current size of the enterprise sales team. What excites me is that out of 21 new programs, 10 were in biopharma this quarter. We previously discussed that in biotechnology, biopharma has the largest R&D budget. Therefore, I'm most excited about our potential to grow in that market. We initially focused on industrial biotech before entering agriculture partly because that sector had less in-house capability. Ultimately, Ginkgo persuades clients to outsource to our platform rather than handling tasks internally, and that was a more straightforward case for a startup industrial biotech company compared to a giant like Pfizer five years ago. However, during this time, the venture capital environment for industrial biotech has become more challenging, creating obstacles for us in adding new programs. Nevertheless, we've expanded our enterprise sales team, as demonstrated by our recent Pfizer deal in biopharma. Expect us to continue growing that team.

Okay. Got it. And then with regards to any particular partner class being harder or easier to get over the goal line? Can you give any color on that?

I believe startups in industrial biotech are currently facing challenges. It used to be a strong area for us due to our good reputation and several successful examples. However, the market is experiencing significant strain because venture funding has diminished. Despite this, I remain optimistic about the long-term potential. Industrial biotech is an intriguing market. Our mission is to simplify the engineering of biology. What makes industrial biotech appealing is that, unlike therapeutics that involve human application, the processes in industrial biotech typically occur in controlled environments like steel tanks, making the path to predictability clearer. While I think we will improve in drug design within therapeutics, there's an inherent unpredictability involved with human applications that's difficult to overcome. Industrial biotech is likely to progress in engineering more rapidly. However, we still have to navigate the fluctuations in investor interest.

Okay. Cool. And then maybe a quick one on biosecurity. Mark, on the gross margins, we've noticed that they ticked up as you're exiting and the mix shift goes away from the K-12 testing. But how should we think about the go-forward run rate ex K-12 testing?

The go-forward run rate on margin or on revenue?

Gross margin?

Yes. So I would more or less ignore what happened in Q3 as you think about go forward. So we benefited on both revenue and gross margin from the closeout of some legacy K-12 contracts. And so there was some, what I would just call, like one-time revenue, and some of that came through a good gross margin that hit in the first half of the quarter. And so that's why you saw the pop in Q3. It's not because the newer business, the new federal and international business is sort of a higher portion of the mix and is somehow higher gross margin. It isn't. So just to kind of reiterate what I've said in the past, we don't know how the gross margin will evolve, but we're certainly targeting something around that 40% range, once we get to kind of an appropriate scale. But as you saw, when we were building the business to begin with, the gross margin did fluctuate quite a bit until we got to the right sort of scale. But we certainly think about our target margin in that 40% kind of plus or minus range. We'll see sort of how it evolves over time.

Thanks, Steve. Next up, we have Derik De Bruin from Bank of America.

So, Jason, you've added a number of new programs considerably. I guess how should we think about, 2 points, like, one, what's your related party revenues exiting this year? And I'm sure it's down quite a bit, I'm sure. Just a little bit clarity on that. And any preliminary color on sort of like cash burn, particularly as you sort of get rid of the legacy Zymergen? Just how should we sort of thinking about cash burn metrics from here?

Yes. I might pass that question to Mark and then follow up at the end to provide some additional insights because I think Mark will have the numbers.

The exit rate on related party revenues is expected to see a significant decline compared to previous years. There is some fluctuation when looking at this year's quarter-to-quarter figures, which have been disclosed. You'll notice that there are variations, but overall, it is certainly much lower than last year. I expect that the mix shift has mostly already occurred at this point.

Do we have the percent this quarter? It was on....

Yes.

We'll pull it up for you, Derik, but sorry. But keep going, Mark, and we'll get it back.

In the appendix to the earnings deck, the related party mix was about 25% of revenues in the third quarter. Compared to the past, when it was around 70%, it has decreased significantly. I expect it to be even lower than that.

Yes, could you please restate your question about cash burn?

If you consider our expectations for finishing this year, we do not provide guidance on cash burn. However, if you look at the cash flow statement from Q3 year-to-date and extend that, taking into account the deconsolidation of Zymergen cash, you would see an increase in cash burn. This extrapolation would suggest a total around $400 million for this year, and we anticipate improvement next year.

Got it. And then one final one, if I can. Significant expectations for more downstream value in 2024?

Sorry, I missed the beginning of the question. Would you mind....

Yes. You had about $4 million that you're including in terms of like downstream value this year. Does that number go up next year? There are more milestones. And sort of going back to Tejas' question on trying to get a revenue number, which I know you're not going to answer, but I got to try.

We are not providing guidance on downstream value share for this year. While we shared our current status, it's dependent on various commercial programs reaching specific milestones for them to generate value shares, including potential royalties down the road. We plan to continue this approach. I understand the desire for more transparency, and we are sharing details about our program pipeline. As our numbers grow, we hope to offer more insights. On a related note, the landscape has changed; previously, we saw much activity from new companies on our platform, but due to tighter venture capital conditions, that segment of our customer base has diminished. This shift has meant moving from early-stage entrepreneurs using our platform to larger customers like Pfizer and Merck. This highlights the adaptability of our platform business model, which is crucial as we navigate changing market conditions, especially as we scale. Regarding cash, we ended the quarter with over $1 billion. We are very cautious about cash management and appreciate that Ginkgo improves with scale. However, achieving downstream value requires careful financial planning to ensure we do not run out of funds. We are focused on this aspect as we move forward.

Thanks, Derik. Next up, we have Michael Freeman at Raymond James.

I really appreciate you all adding the swimmers plot on project maturity. I think that provides a lot of insight into what’s happening within the Ginkgo platform. However, one gap in the data visualization is what occurs between 100% completion and commercial readiness. I’m curious about what Ginkgo can do to assist its partners in addressing the necessary work that needs to be done between these two stages.

Good question. The straightforward answer is to have enough programs that balance things out. In other words, we can't be solely responsible for everything from animal-free meat to cannabinoids to new pharmaceuticals to agricultural traits. The wide range of products makes it challenging for us to play a major role in ensuring that the downstream processes of cell engineering are successful for our customers. However, as Ginkgo grows and more of the world utilizes our platform, investments that generally assist biotech products in progressing will result in significant benefits for us. For now, I'm focused on bringing more people onto the platform, and it's really up to them to handle the downstream work. Realistically, Ginkgo needs to concentrate its resources on improving platform efficiency to optimize fees relative to spending and successfully leverage downstream value sharing.

I understand. Another important aspect of a biotech or biopharma swimmer's plot is the number of patients or programs that face failure. You mentioned that not all programs reach full completion. I'm curious about how we can gauge the reasons for program failures and what percentage of programs typically do fail. Additionally, what factors lead you and a partner to decide that a program is finished?

Yes. I would like to share more on this over time. Currently, I want to gather more data from the pipeline, as that is what's primarily holding me back. I believe that eventually we will be able to provide you with this information. In terms of what drives our decisions, we establish technical milestones that are agreed upon with each customer, as we typically receive payment upon meeting those targets. These milestones are the benchmarks for success, and ultimately, they are agreed upon with the customer. However, challenges arise because these targets can vary from program to program, making some initiatives more difficult than others. Since we are not dealing with standardized products, this variability adds to the complexity of our modeling efforts.

Thanks, Michael. Next up, we have E.V. From Goldman Sachs.

Just filling in for Matt tonight. Following up on new programs, could you maybe just give an update on what you're seeing in the sales funnel from customers. I think in the past, you said there's a lot of potential of new programs in the funnel. Are you seeing some of these conversations being pushed out due to capital conservations as we've seen many headlines from pharma, R&D cuts? Is there anything else you're hearing from customers on program cancellation?

There may be two different questions there. You asked about program cancellations at the end, but I'll hold off on that for a moment since it's a slightly different topic. Regarding the sales pipeline, it remains very strong. Mark mentioned this briefly in his comments; one challenge we encounter is the timing of the close. We often start certain programs before finalizing deals with customers to expedite the process. We do this as we approach closing the deal with the customer. We currently have many such situations. Overall, I feel good about our position going into the upcoming quarters. I’m pleased with our sales infrastructure and pipeline. Those aspects are solid. However, I anticipate some quarter-to-quarter variability in what gets finalized. Sometimes it will go in our favor, and sometimes it won't. I believe that reflects Mark's general point about the timing challenges associated with complex enterprise sales. But overall, I am satisfied with the situation.

Yes, that's helpful. And then on program cancellations. I mean more on like the biotech programs or projects not like your programs, does that make sense, kind of the difference there?

Yes. I think that's true across the industry. The good thing about biopharma is Ginkgo's penetration into that industry today is like rapidly small. So like even though that is true, we're still talking to like companies that have never even talked to us before. So like it's not as if, oh well, we've got this level of penetration and they're backing off. And it's also not like industrial biotech, where it's kind of gone to, right, like it's really tightened up a lot. There's still a good amount of funding, certainly at the large biopharmas, but even at the small ones, people are still pursuing research and most of them have not given Ginkgo a serious look yet. So that all bodes well for our enterprise sales team to go around and talk to people and show what we got.

Okay, great. That's super helpful. And then one more. You gave a lot of detail on biosecurity at the Investor Day. Nice to see the guidance raised there. Could you talk through the competitive environment in that market? Obviously, it's very new and emerging. But has anything come up when talking to customers with other players you're seeing in that space?

No, I've outlined three key areas: monitoring, decision-making, and response. In terms of response, it involves the entire biopharma industry and vaccine developers. Ginkgo has primarily concentrated on monitoring and decision-making. There are examples like Verily, which is working on wastewater analysis in the U.S. alongside a smaller company called Biobot. These companies are engaged in some level of monitoring. However, on the airport front, there isn’t much activity currently. We are primarily focused on persuading stakeholders that this initiative is valuable, and I believe we are making significant headway. The challenge lies more in establishing the necessary infrastructure and securing funding rather than competing directly in a saturated market. Overall, our main objective is to elevate the visibility of biosecurity as a category, which is not overly competitive at this stage.

And I think we have time for one more question from the public. This one comes from the investor inbox. Please provide more details on the recent Pfizer deal, specifically, what does Ginkgo need to do to earn the $330 million mentioned in the recent press release?

Yes, I can provide more details on this. What we included in the press release outlines what we can share about the deal, highlighting that we will receive research payments as well as milestone payments upon transferring the asset to the customer, who will then advance it through processes like clinical trials. Additionally, there is potential for royalties. Generally, this is common across many biopharma deals. Typically, we will have milestone payments associated with drug development; the approach differs for manufacturing R&D, which we have conducted with partners like Biogen and Novo Nordisk. In drug development, milestones may occur when the asset successfully completes Phase I, Phase II, or Phase III clinical trials, and there will be a royalty once it is commercially available.

Great. Thanks, Jason. That about closes it out. Do you have any closing thoughts for us today?

No, other than to say, like I mentioned, I'm really quite proud of the infrastructure that's being built on the enterprise sales side. I think it is unappreciated how difficult that is because we are selling something different. There are CROs out there selling what I would consider straightforward research services, like providing something that you pretty much know could be done by anyone else, and doing it cheaper or whatever. Ginkgo is selling high-end drug discovery, which is a much more complicated sale. So to be able to do that at scale, I believe it will be valuable for us in the long run. I'm happy to see that.

All right. Thanks so much. That concludes this quarter's earnings call. Talk to you all next quarter.

Thanks, everybody.

Thank you.