Ginkgo Bioworks Holdings Inc (DNA) 2025 Q1 法說會逐字稿

Good evening. I'm Daniel Marshall, Senior Manager of Communications and Ownership. It's my third year here at Ginkgo. I spent much of that time working behind the scenes with our Investor Relations team on these earnings calls, but I'm thrilled to be joining you for the first time live on air. 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.

晚安.我是丹尼爾‧馬歇爾 (Daniel Marshall)，通訊與所有權資深經理。這是我在銀杏的第三年。我花了很多時間與我們的投資者關係團隊在幕後工作，準備召開這些收益電話會議，但我很高興第一次透過直播與你們一起參加。和我一起參加的還有我們的共同創辦人兼執行長 Jason Kelly；以及我們的財務長 Mark Dmytruk。一如既往，感謝您的加入我們。我們期待向您通報我們的進展。

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 SEC to learn more about these risks and uncertainties, including our most recent 10-K.

提醒一下，在今天的演示中，我們將做出前瞻性陳述，其中涉及風險和不確定性。請參閱我們向美國證券交易委員會提交的文件，以了解有關這些風險和不確定性的更多信息，包括我們最新的 10-K 文件。

Today, in addition to updating you on the quarter results, we're going to provide updates on our path towards adjusted EBITDA breakeven, traction with our government clients as well as new offerings and opportunities emerging for our tools businesses.

今天，除了向您更新季度業績外，我們還將提供有關調整後 EBITDA 盈虧平衡的路徑、與政府客戶的合作以及工具業務的新產品和新機會的最新資訊。

As usual, we'll end with a Q&A session and I'll take questions from analysts, investors and the public. You can submit those questions to us in advance via X, #GinkgoResults or e-mail, investors at investors@ginkgobioworks.com.

像往常一樣，我們將以問答環節結束，我將回答分析師、投資者和公眾的問題。您可以透過 X、#GinkgoResults 或電子郵件 investors@ginkgobioworks.com 提前向我們提交這些問題。

All right. Over to you, Jason.

好的。交給你了，傑森。

Thanks, Daniel. We always start off with our mission here at Ginkgo, which is to make biology easier to engineer. And then we had three objectives. And I first showed these are close variants of these about a year ago when we announced that we were going to be doing a major restructuring of the company. And these three objectives were to reach adjusted EBITDA breakeven by the end of 2026.

謝謝，丹尼爾。在 Ginkgo，我們始終以我們的使命為出發點，那就是讓生物學更容易進行工程設計。然後我們有三個目標。大約一年前，當我們宣布將對公司進行重大重組時，我第一次展示了這些是近似的變體。這三個目標是到2026年底實現調整後EBITDA收支平衡。

And importantly, doing that while maintaining a cash margin of safety. In other words, we didn't want to get in a position where we're going to need to fund raise when we didn't want to, right? We wanted to be doing that we needed to fund raise from a position of strength, but ideally not even need to fund raise. Second, we wanted to cut costs while importantly, serving our current customers. We had a lot of amazing customers, large pharma, large ag biotechs, industrial biotechs as well as the government.

重要的是，這樣做的同時也要保持現金安全邊際。換句話說，我們不想陷入在我們不想籌集資金的時候卻需要籌集資金的境地，對嗎？我們希望做到這一點，我們需要從實力地位來籌集資金，但理想情況下甚至不需要籌集資金。其次，我們希望削減成本，同時更重要的是服務現有客戶。我們有許多優秀的客戶，大型製藥公司、大型農業生物技術公司、工業生物技術公司、政府。

We want to keep serving those customers well while at the same time focusing the company. And then finally, we wanted to expand the way we sold our platform, and I'll talk more about this in the strategic section.

我們希望繼續為這些客戶提供良好的服務，同時專注於公司的發展。最後，我們希望擴展我們銷售平台的方式，我將在策略部分詳細討論這一點。

But from not just R&D solutions, where we do an end-to-end research project, but also directly as a tools business like a traditional CRO or an equipment vendor would. These were new ways to go to market to a wider set of potential customers than we had with our solutions business. So those were our three objectives, and I'm very happy to say we made progress on all of them.

但我們不僅從研發解決方案（即進行端到端研究專案）入手，也可以像傳統 CRO 或設備供應商一樣直接作為工具業務。這些都是我們向更廣泛的潛在客戶推出市場的新方式，比我們的解決方案業務還要多。這就是我們的三個目標，我很高興地說我們在所有目標上都取得了進展。

But after a year, we've just made unbelievable progress on taking out costs while still serving our customers. So we're -- I'm very happy to say we're at a $205 million reduction in our annual run rate between Q1 2024 and Q1 '25. You might remember, the target I had set was $200 million, I think, by Q3 or something of this year, like halfway through this year. We already beat that. We're moving -- we've taken actions in the first quarter that are going to improve this even further.

但一年之後，我們在降低成本的同時仍然為客戶提供服務，並取得了令人難以置信的進步。因此，我很高興地說，在 2024 年第一季至 2025 年第一季之間，我們的年運行率減少了 2.05 億美元。您可能還記得，我設定的目標是在今年第三季或今年年中的時候達到 2 億美元。我們已經打敗了它。我們正在採取行動——我們在第一季採取了行動，將進一步改善這一狀況。

Mark will mention. And so I really think sets us up to be in an incredibly strong position. And importantly, because we did it faster, we're at this place while still having $517 million in cash and cash equivalents on the balance sheet and no bank debt.

馬克會提到。因此，我確實認為這將使我們處於非常有利的地位。重要的是，由於我們行動更快，我們現在的資產負債表上仍然有 5.17 億美元的現金和現金等價物，而且沒有銀行債務。

So that, among our peers in the advanced platform technology space in the market today, I think, is a uniquely strong position. And look, biotech on the capital market is going through a tough time right now, that is challenging for the company is in it.

因此，我認為，在當今市場上先進平台技術領域的同行中，我們擁有獨特的優勢地位。看看吧，資本市場上的生技公司現在正經歷著艱難時期，這對其中的公司來說是一個挑戰。

It's also opportunity, I would say, for investors. And from my standpoint, the companies that can make it out the other side of that are in a particularly strong position as a biotechnology is, I think, a fundamental industry that's not going away.

我想說，這對投資者來說也是一個機會。從我的角度來看，那些能夠走出困境的公司將處於特別有利的地位，因為我認為生技是一個不會消失的基礎產業。

And so this sets us up to be in a place to do that. And I want to be just give my thanks to the team for what's been an incredibly difficult, challenging ton of work last year to get us to where we are, but it puts us in a very, very strong spot going forward.

因此，這為我們做好了實現這一目標的準備。我要向團隊表示感謝，感謝去年我們付出的極其艱辛和富有挑戰性的努力，才讓我們取得了今天的成就，同時也為我們今後的發展奠定了非常非常強大的基礎。

So with that, I'm going to hand it to Mark to go off over this quarter's financials.

因此，我將把報告交給馬克負責本季的財務狀況。

Thanks, Jason. I'll start with the cell engineering business. Cell Engineering revenue was $38 million in the first quarter of 2025, up 37% compared to the first quarter of 2024. The first quarter this year included $7.5 million in noncash revenue from a release of deferred revenue relating to the mutual termination of a customer agreement we had with BiomEdit, one of our platform ventures. Excluding this impact, Cell Engineering revenue was $31 million, up 10% compared to the first quarter of 2024. This increase was primarily driven by strong growth with biopharma and government customers.

謝謝，傑森。我先從細胞工程業務開始。2025 年第一季度，Cell Engineering 的營收為 3,800 萬美元，與 2024 年第一季相比成長 37%。今年第一季的非現金收入包括 750 萬美元，這筆收入來自我們與平台企業之一 BiomEdit 共同終止客戶協議而釋放的遞延收入。不計此影響，Cell Engineering 的營收為 3,100 萬美元，與 2024 年第一季相比成長 10%。這一成長主要得益於生物製藥和政府客戶的強勁成長。

In the first quarter of 2025, we supported a total of 123 revenue-generating programs on the Cell Engineering platform. This represents a 32% increase in revenue-generating programs year over year. As discussed on our last earnings call, this quarter represents the first time we are reporting the new revenue-generating program metric and are no longer reporting the original program metrics.

2025年第一季度，我們在Cell Engineering平台上共支援了123個創收專案。這意味著創收項目比去年同期成長了 32%。正如我們上次財報電話會議上所討論的那樣，本季是我們首次報告新的創收計畫指標，而不再報告原來的計畫指標。

As a reminder on the rationale here, the nature of programs that we take on with our customers has evolved significantly following our adjustments to commercial terms and the launch of our tools offerings in 2024. This new metric includes all programs that generated meaningful revenue in the quarter, including smaller programs that were previously reported as other contracts and further excludes programs that did not generate meaningful revenue in the quarter, which typically would be those programs either just starting or in final stages of completion.

提醒這裡的理由，隨著我們調整商業條款並於 2024 年推出工具產品，我們與客戶合作的專案的性質已經發生了重大變化。這項新指標涵蓋了本季度產生可觀收入的所有項目，包括先前報告為其他合約的小型項目，並進一步排除了本季度未產生可觀收入的項目，這些項目通常是剛啟動或處於最後完成階段的項目。

We believe the new metric will be more useful to analysts who are using this to model revenue. We have also updated the 2024 comparables using this new metric in the appendix. Now turning to Biosecurity. Our Biosecurity business generated $10 million of revenue in the first quarter of 2025 at a segment gross margin of 28%. Segment gross margin excludes stock-based compensation.

我們相信，新指標對於使用它來模擬收入的分析師來說將更有用。我們也在附錄中使用此新指標更新了 2024 年的可比較數據。現在轉向生物安全。我們的生物安全業務在 2025 年第一季創造了 1,000 萬美元的收入，分部毛利率為 28%。分部毛利率不包括股票薪酬。

Turning to the next slide, I'll provide more commentary on key items for the rest of the P&L. Now that we are almost a year into our restructuring, you can see the very substantial cost reductions and improvements in profitability that we have executed when compared to the first quarter of 2024.

翻到下一張投影片，我將對損益表其餘部分的關鍵項目提供更多評論。現在，我們的重組已經進行了將近一年，與 2024 年第一季相比，您可以看到，我們的成本大幅削減，盈利能力大幅提高。

As a reminder, a full reconciliation between segment operating loss, adjusted EBITDA and GAAP net loss can be found in the appendix. Starting with the more significant items in segment OpEx. In the first quarter of 2025, Cell Engineering R&D expense decreased 41% from $82 million in the first quarter of 2024 to $49 million in the first quarter of 2025.

提醒一下，您可以在附錄中找到分部營業虧損、調整後 EBITDA 和 GAAP 淨虧損之間的完整對帳。從部分營運支出中較重要的項目開始。2025 年第一季度，Cell Engineering 研發費用從 2024 年第一季的 8,200 萬美元下降 41% 至 2025 年第一季的 4,900 萬美元。

Cell Engineering G&A expense decreased 53% from $38 million in the first quarter of 2024 to $18 million in the first quarter of 2025. And while smaller in amount, you can also see a decrease in Biosecurity operating expenses by 33% year over year. All these decreases were driven by our restructuring efforts. Net loss. It is important to note that our net loss includes a number of noncash income and/or expenses as detailed more fully in our financial statements.

電池工程的一般及行政費用從 2024 年第一季的 3,800 萬美元下降 53% 至 2025 年第一季的 1,800 萬美元。儘管金額較小，但您也可以看到生物安全營運費用比去年同期下降了 33%。所有這些下降都是由我們的重組努力造成的。淨虧損。值得注意的是，我們的淨虧損包括一些非現金收入和/或支出，詳情請參閱我們的財務報表。

Because of these noncash and other nonrecurring items, we believe adjusted EBITDA is a more indicative measure of our profitability. And we are now showing you adjusted EBITDA at the segment level so that you can more clearly see the relative profitability of Cell Engineering and Biosecurity.

由於這些非現金和其他非經常性項目，我們認為調整後的 EBITDA 更能反映我們的獲利能力。我們現在向您展示細分市場的調整後 EBITDA，以便您可以更清楚地看到細胞工程和生物安全的相對盈利能力。

The significant improvement in cell engineering segment operating loss in the first quarter of 2025 compared to the comparable prior year period was due to the previously discussed drivers of improved revenue and reduced operating expenses as well as the noncash deferred revenue release within the quarter.

2025 年第一季電池工程部門的營業虧損與去年同期相比有顯著改善，這是由於先前討論過的收入增加、營業費用減少的驅動因素以及本季度內非現金遞延收入的釋放。

Biosecurity segment operating loss also improved significantly due to the primarily cost reduction efforts. Moving further down the page, you'll note that total company adjusted EBITDA in the first quarter of 2025 was negative $47 million, which was up from negative $117 million in the first quarter of 2024.

由於主要採取了降低成本的措施，生物安全部門的經營虧損也顯著改善。繼續往下翻，您會注意到 2025 年第一季公司調整後的 EBITDA 總額為負 4,700 萬美元，高於 2024 年第一季的負 1.17 億美元。

The principal differences between segment operating loss and total company adjusted EBITDA in the first quarter relates to the carrying cost of excess lease space, which you can see was $12 million in Q1 this year. This cost represents the base rent and other charges relating to leased space, which we are not occupying, net of sublease income.

第一季分部營業虧損與公司調整後 EBITDA 總額之間的主要差異與超額租賃空間的持有成本有關，您可以看到，今年第一季該成本為 1,200 萬美元。此成本代表與我們未佔用的租賃空間相關的基本租金和其他費用扣除轉租收入。

We'll continue to break that out for you going forward since that is a cash operating cost that is not related to driving revenue right now and can be potentially mitigated through subleasing. And finally, I'll just make one additional comment relating to cash burn in the quarter. Cash burn in the first quarter of 2025 was $58 million, down from $104 million in the first quarter of 2024.

我們將繼續為您詳細解釋這一點，因為這是一筆現金營運成本，與目前的收入成長無關，並且可以透過轉租來緩解。最後，我只想就本季的現金消耗發表一點補充評論。2025 年第一季的現金消耗為 5,800 萬美元，低於 2024 年第一季的 1.04 億美元。

This significant decrease in cash burn was a result of the restructuring. We expect to further reduce the cash burn run rate significantly from this level by the fourth quarter of 2025. And though we expect some lumpiness in the progression during the year due to timing of working capital.

現金消耗的大幅減少是重組的結果。我們預計到 2025 年第四季度，現金消耗率將從這一水準進一步大幅降低。儘管我們預計由於營運資金的時間安排，今年的進展會出現一些波動。

In terms of outlook for the full year, we previously issued guidance for total revenue of $160 million to $180 million, Cell Engineering services revenue of $110 million to $130 million and Biosecurity revenue of at least $50 million. We update this previously issued guidance solely to reflect the impact of the previously mentioned $7.5 million noncash deferred revenue release in the first quarter.

就全年前景而言，我們先前發布的指引為總收入 1.6 億至 1.8 億美元，細胞工程服務收入 1.1 億至 1.3 億美元，生物安全收入至少 5,000 萬美元。我們更新先前發布的指南只是為了反映先前提到的第一季 750 萬美元非現金遞延收入釋放的影響。

With this in mind, we now expect our total revenue to be $167 million to $187 million, Cell Engineering revenues to be $117 million to $137 million and Biosecurity to remain the same of at least $50 million. In conclusion, we're pleased with the substantial improvements in cash burn and profitability when looking back over the past year. In the first quarter, we continued to execute against our core objectives while navigating significant uncertainty in the macro environment.

考慮到這一點，我們現在預計我們的總收入為 1.67 億美元至 1.87 億美元，細胞工程收入為 1.17 億美元至 1.37 億美元，生物安全收入保持不變，至少為 5000 萬美元。總而言之，回顧過去的一年，我們對現金消耗和獲利能力的大幅改善感到高興。第一季度，我們在應對宏觀環境巨大不確定性的同時，繼續執行核心目標。

And with that, I will hand it back over to you, Jason.

說完這些，我就把它交還給你，傑森。

Thanks, Mark. So in the strategic section, we're going to cover 3threetopics today. The first, I want to touch again on our continued restructuring efforts and how well that's going on the cash take outside in our path to EBITDA breakeven by the end of next year. Second, there's been a lot of changes in the administration in the US government here in terms of approach to research spending and Biosecurity and things like that.

謝謝，馬克。因此，在策略部分，我們今天將討論 3 個主題。首先，我想再次談談我們持續的重組努力，以及重組對我們在明年年底實現 EBITDA 收支平衡的現金流的影響。其次，美國政府在研究支出、生物安全等方面的管理方式發生了很大變化。

And I want to just highlight that I think biotech remains a critical emerging tech in the US, and Ginkgo's well positioned for it. And then the third topic, I want to talk about our tools businesses, data points and automation. This has been our big motion over the last year is expanding into the tool space, and that's going really well, and I want to give an update on that.

我想強調的是，我認為生物技術仍然是美國一項重要的新興技術，而 Ginkgo 在這方面處於有利地位。然後是第三個主題，我想談談我們的工具業務、數據點和自動化。這是我們去年的一大舉措，即擴展到工具領域，而且進展非常順利，我想對此進行更新。

Okay. So first, I talked earlier, I'm really happy to have that highlighted in the middle of that $205 million of annualized run rate cost takeout that we've achieved in the year since we announced the restructuring. Our goal, of course, is to get to adjusted EBITDA breakeven in 2026.

好的。首先，我之前說過，我很高興能夠在我們宣布重組以來的一年內實現 2.05 億美元的年度化運行成本削減中強調這一點。當然，我們的目標是在 2026 年實現調整後的 EBITDA 收支平衡。

And so I really like this chart on the left, you can see back in Q1 2024, where we were on the cash expenses and total revenues. And what we want to do is just shrink that gray bar and grow the green bar and eventually get those to be the same size.

所以我非常喜歡左邊的這張圖表，您可以看到 2024 年第一季我們的現金支出和總收入。我們想要做的就是縮小灰色條並增加綠色條並最終使它們的大小相同。

And so we are pushing at that is the relentless focus here on the team. Again, I'm really happy to see the progress. It's going in the right direction. We already have made changes in the first quarter that you'll see reflected in the coming quarters to continue to take costs out. And hopefully, our efforts in the tools space will keep growing sales as well.

因此，我們正在努力實現這一目標，並持續專注於團隊的發展。再次，我真的很高興看到進步。一切正朝著正確的方向發展。我們已經在第一季做出了一些改變，這些改變將在接下來的幾季中體現，以繼續降低成本。希望我們在工具領域的努力也能持續推動銷售成長。

I will mention, if you look and see the segment breakout here in Biosecurity, again, Q1 2024 -- or sorry, Q4 2024 to Q1 2025., we're at $5 million on a run rate burn. That's one where we're hoping to really get Biosecurity to breakeven this year and then Cell Engineering, you can see the enormous progress we've made since Q1 of 2024 over last year.

我要說的是，如果你再看一下生物安全領域的細分市場突破，那麼在 2024 年第一季——或者抱歉，2024 年第四季到 2025 年第一季度，我們的運行率消耗為 500 萬美元。我們希望今年生物安全能夠真正實現收支平衡，然後是細胞工程，您可以看到自 2024 年第一季以來我們比去年取得了巨大進步。

But need to continue squeezing on that in order to reach adjusted EBITDA breakeven next year. So I think we've got a path to it. It will be a serious amount of work, but I've been extraordinarily impressed again, kudos to the team here at Ginkgo and all the work to date to get to the strong position we're in today.

但需要繼續努力才能在明年實​​現調整後的 EBITDA 收支平衡。所以我認為我們已經找到了解決這個問題的方法。這將是一項艱鉅的工作，但我再次對此印象深刻，向 Ginkgo 團隊表示敬意，感謝他們迄今為止所做的所有工作，使我們達到了今天的強勢地位。

And again, I don't have it on these slides here, but over $0.5 billion in cash in the bank. This has been a tough market for biotechnology. The companies I think that make it out the other side of it will be in an especially strong position. And so the fact that we're so well shored up is thanks to the team's efforts over the last year. All right.

再說一次，這些投影片上並沒有提到這筆錢，但銀行裡有超過 5 億美元的現金。對於生物技術來說，這是一個艱難的市場。我認為，能夠走出困境的公司將處於特別有利的地位。我們之所以能取得如此好的成績，要歸功於團隊過去一年的努力。好的。

Next, I want to talk about the new administration and what the US government is doing in biotechnology and Biosecurity. There was actually a great speech. I really encourage you to either watch it or read it. from the President Science Adviser, Michael Kratsios.

接下來我想談談新政府以及美國政府在生物技術和生物安全方面所做的工作。這確實是一場精彩的演講。我真的鼓勵你去觀看它或閱讀它。來自總統科學顧問 Michael Kratsios。

It's a cabinet position as of the last administration was turned into a cabinet position. And he had a great speech where we talked about how the administration was going to invest in technology and science and he said, whether in AI, quantum, biotech or next-gen semiconductors, it's the duty of the government to enable scientists to create new theories, and power engineers to put them into practice. And so what's important there is that's your short list of critical technologies for the US AI, quantum, biotech and chips, all right? So it's good to see biotech on that list.

這是自上屆政府以來變成內閣職位的內閣職位。他發表了一場精彩的演講，討論了政府將如何投資科技，他說，無論是在人工智慧、量子、生物技術還是下一代半導體領域，政府的職責是幫助科學家創造新理論，並幫助工程師將其付諸實踐。所以重要的是，這是美國人工智慧、量子、生物技術和晶片的關鍵技術清單，好嗎？因此很高興看到生物技術出現在這個名單上。

It's been on the list for a while, certainly in the last administration as well. And so I'm happy to see it's still there from the President Sciences Adviser. This is a report that came out. You might remember, I was actually sharing this commission. I'm very thankful that Senator Young is now the Chair. That's a load off me.

它已經在名單上一段時間了，當然在上屆政府中也是如此。因此我很高興看到總統科學顧問仍然在那裡。這是一份已經出來的報告。您可能還記得，我實際上是在分享這個佣金。我非常感謝楊參議員現任主席。這對我來說是輕鬆多了。

And [Michelle Rose] is the Vice Chair, the final report from this National Security Commission on emerging biotech just came out a few weeks ago. I highly encourage folks to read it. Just to quote here, we stand at the edge of a new industrial revolution, one that depends on our ability to engineer biology. So this is a bipartisan commission, obviously, Youngs Republican. I see, again, a push here really coming on the legislative side for improved reduction in regulations, new sources of funding.

副主席米歇爾羅斯 (Michelle Rose) 表示，國家安全委員會關於新興生物技術的最終報告幾週前剛發布。我強烈鼓勵大家閱讀它。僅引用一下，我們正站在一場新工業革命的邊緣，這場革命取決於我們設計生物學的能力。所以這是一個兩黨委員會，顯然，楊斯是共和黨人。我再次看到，立法方面確實在推動減少監管、尋找新的資金來源。

I think you will see this administration fund things differently than the previous administration. But I think you will still see funds continue to go out the door towards biotechnology. And importantly, our solutions business at Ginkgo is a trusted R&D service provider to the US government. So we have 28 government projects across both Cell Engineering and Biosecurity, about $180 million plus of contracted backlog or unfunded potential This is it like options on some of our contracts, depending on how things go.

我認為你會看到本屆政府的資金籌措方式與上屆政府不同。但我認為你仍會看到資金繼續流向生物技術。重要的是，Ginkgo 的解決方案業務是美國政府值得信賴的研發服務提供者。因此，我們在細胞工程和生物安全領域有 28 個政府項目，約有 1.8 億美元以上的合約積壓或未獲資金支持的潛力，這就像我們某些合約的選擇，取決於事情的進展。

And just to highlight a couple of wins since President Trump selection. We won a brand called ARPA-H REACT. This is in partnership with Carnegie Mellon, about $9 million programs for bioelectronic devices in disease treatment.

這只是強調川普當選總統以來取得的幾項勝利。我們贏得了一個名為 ARPA-H REACT 的品牌。這是與卡內基美隆大學合作的一項約 900 萬美元的項目，用於治療疾病的生物電子設備。

But then I really wanted to highlight a new program we just announced a few weeks ago called WHEAT, a $29 million funded program. And if you go to the next slide, the applications here is really around how do we bring manufacturing of critical raw materials in the pharmaceutical industry back onshore.

但我真的想強調我們幾週前剛剛宣布的一項新計劃，名為 WHEAT，這是一項獲得 2900 萬美元資助的計劃。如果你看下一張投影片，這裡的應用實際上是關於如何將製藥業關鍵原料的生產帶回國內。

And I think there's a ton of work to do here. You're already starting to see motions happen here, pharmaceutical company companies investing in manufacturing plants. That's usually around their newer drugs. We also have a lot of critical drugs that are antibiotics, a lot of frontline medications that have really been moved overseas over the last 20, 30 years. I think some of those, we do want to bring back.

我認為這裡還有很多工作要做。您已經開始看到這裡發生的動議，製藥公司正在投資製造工廠。這通常與他們的新藥有關。我們還有很多關鍵藥物，像是抗生素，許多第一線藥物在過去的二、三十年中都被運往海外。我認為我們確實想把其中的一些帶回來。

So some of that's just going to be building manufacturing plants. But what this program is, is actually to make use of weak germs. So this is -- it's an extract that comes as a byproduct of growing WHEAT. And what's cool about it is you are able to essentially take that wheat germ extract, which has all the components like the low-level components of cells, right? So this is part of the magic of biology.

因此其中一些只是要建造製造工廠。但這個計劃其實是利用弱細菌。所以這是——它是小麥生長過程中產生的副產品萃取物。最酷的是，你基本上可以提取小麥胚芽萃取物，它含有細胞低級成分等所有成分，對嗎？這就是生物學神奇之處的一部分。

Our cells, weed cells, insect cells, bacterial cells at the lowest level, the DNA, the ribosomes, the mRNA, that's all the same. And so you can actually reuse the material that comes from that wheat germ, add in a piece of DNA that say, encodes for like human insulin or another therapeutic.

我們的細胞、雜草細胞、昆蟲細胞、最低等級的細菌細胞、DNA、核醣體、mRNA，都是一樣的。因此，你實際上可以重複使用小麥胚芽的材料，添加一段 DNA，例如編碼人類胰島素或其他治療藥物的 DNA。

And then in that cell-free system in that extract actually produce that therapeutic drug. And this is not a technology that's coming out tomorrow, but this is a much lower cost source for this cell-free extract than what you can currently get on the market today, if we're able to be successful in this research project for ARPA-H. And so this is a time, I think, is, obviously, I'm excited that we're being a part of this, but I'm just glad to see the government funding this.

然後在無細胞系統中，萃取物實際上會產生治療藥物。雖然這不是明天就會出現技術，但是如果我們能夠在 ARPA-H 的這項研究項目中取得成功，那麼這種無細胞提取物的成本將比目前市場上可以買到的要低得多。所以我認為這是一個時機，顯然，我很高興我們能參與其中，但我很高興看到政府為此提供資金。

And this is the type of thing that can go solutions business where we do these end-to-end projects and deliver a scientific result. This is an example of where we're doing that for the US government. And I expect we'll see more of those. Okay.

這類事情可以成為解決方案業務，我們可以完成這些端到端的專案並提供科學成果。這是我們為美國政府所做的一個例子。我希望我們會看到更多這樣的情況。好的。

So I want to talk a little bit now about Ginkgo Biosecurity, which is the other big area where we work with the US government. We really have two big offerings, product offerings here. The first we call Canopy. And you might remember, we -- I'm not going to go into great detail, but we collect wastewater from plans, inbound planes into international airports.

現在我想談談銀杏生物安全，這是我們與美國政府合作的另一個重要領域。我們確實有兩大產品可供選擇。第一個我們稱之為 Canopy。你們可能還記得，我們​​──我不會講得很詳細，但我們收集飛機、飛進國際機場的飛機所產生的廢水。

We collect metadata, where did that plan come from. And then we look in the wastewater for a whole panel, I think we're up to like 60 now different infectious diseases. If we see them, then like if we see a virus, we can sequence it and get that variants, genomes, remember all the COVID variants, we can get the variant sequence and then give that back to the government or whoever is having us do that particular work. And so that's the actual physical collection of data. And then our Horizon platform is when we take all that data and we try to give actionable information back to decision makers.

我們收集元數據，該計劃是從哪裡來的。然後我們在廢水中尋找一整套檢測方法，我認為我們現在發現了大約 60 種不同的傳染病。如果我們看到它們，就像我們看到病毒一樣，我們可以對其進行測序並獲取變體、基因組，記住所有 COVID 變體，我們可以獲取變體序列，然後將其返還給政府或任何讓我們做這項特定工作的人。這就是實際的實體資料收集。然後，我們會透過 Horizo​​n 平台收集所有數據，並嘗試將可操作的資訊回饋給決策者。

And you can imagine there's a lot of great opportunities for AI and automated learning and data parsing there on the Horizon platform. These types of -- we think of these like almost like radar stations for monitoring for infectious disease.

你可以想像，Horizo​​​​n 平台上有許多人工智慧、自動學習和數據分析的絕佳機會。我們認為這些類型幾乎就像是用來監測傳染病的雷達站。

I mentioned airports, but absolutely, we should be doing this on ships, should be doing this at mass gatherings, military installations, embassies, BSL-3 and 4 labs, like this is a very obvious thing to me, like we ought to be monitoring the effluent like what's coming out of these labs and the surrounding area around these labs just to keep an eye on if there's a leak or things like that.

我提到了機場，但絕對地，我們應該在船上這樣做，應該在大型集會、軍事設施、大使館、 BSL-3 和 4 實驗室這樣做，這對我來說是非常明顯的事情，就像我們應該監測這些實驗室和實驗室周圍區域產生的廢水，以監測是否有洩漏或類似情況。

This type of, really, we consider a passive monitoring, like you're just looking all the time. We think it's going to be actually critical in terms of having a strong Biosecurity defense network here in the United States.

實際上，我們認為這是一種被動監控，就像你一直在觀察一樣。我們認為，對於美國來說，建立強大的生物安全防禦網路實際上至關重要。

And I think this is particularly salient coming up because, as you know, the United States has stepped out of the WHO. And if you look at how the WHO did its work, that was based on voluntary information sharing. So in other words, there'll be an outbreak in a country, and that country is equivalent of the CDC, which share that information back with the WHO. WHO would disseminate information globally. I think that's getting outdated in this era.

我認為這一點尤其突出，因為如你所知，美國已經退出了世界衛生組織。如果你看看世界衛生組織是如何開展工作的，你會發現它是基於自願的資訊共享。換句話說，如果一個國家爆發疫情，那麼該國就相當於疾病預防控制中心，它會將這些資訊分享給世界衛生組織。世界衛生組織將在全球傳播訊息。我認為這在當今時代已經過時了。

One, there's a lot less cooperation among countries at the moment. Number two, post COVID, it's very clear the economic impact of these things. So once a country has an outbreak, they got -- there's often a reticence to share that information. We even saw that with COVID itself. And also the technology has just changed a lot in the last 20 years.

一是目前各國之間的合作大為減少。第二，新冠疫情過後，這些事情對經濟的影響非常明顯。因此，一旦一個國家爆發疫情，他們往往不願意分享這些資訊。我們甚至在 COVID 本身中也看到了這一點。而過去 20 年科技也發生了巨大的變化。

And passive monitoring, like I talked about in the last couple of slides can turn like a political problem where you have to ask people for things and have the politics to have them give it to you. It's a technological problem where we're just looking. And if something happens, we see it. And just to be clear, that's how we approach cybersecurity. That's how we approach Missile Defense.

而被動監控，就像我在前幾張投影片中談到的那樣，可能會變成一個政治問題，你必須向人們索取東西，然後透過政治手段讓他們把東西給你。這是一個我們正在研究的技術問題。如果有什麼事情發生，我們就能看到。需要明確的是，這就是我們處理網路安全的方式。這就是我們處理導彈防禦問題的方法。

We don't ask did you launch a missile. We have the satellites up there looking all the time for them. And that's really how we should move to a platform like that for monitoring infectious disease. And I'm hopeful there'll be opportunities to do that as the US considers how to build our infrastructure outside of the WHO.

我們不會問你是否發射了導彈。我們的衛星一直在搜尋它們。這就是我們真正應該轉向這樣的傳染病監測平台的方式。我希望，當美國考慮如何在世衛組織之外建造我們的基礎設施時，就有機會這樣做。

Okay. I want to now talk about Ginkgo's data points and automation offerings where I've seen new deals and opportunities emerging. Okay. So about a year ago, I showed this slide for the first time. So Ginkgo is historical, the way we brought our platform to customers was through what we call Solutions, where our customer is really the head of R&D.

好的。現在我想談談 Ginkgo 的數據點和自動化產品，我看到了新的交易和機會的出現。好的。大約一年前，我第一次展示了這張投影片。因此，Ginkgo 具有歷史意義，我們將平台帶給客戶的方式是透過所謂的解決方案，我們的客戶實際上是研發主管。

So this is the person who is in charge of, say, drug development at a company like Merck or Pfizer, Nova Nordisk, some of our customers. And Ginkgo is an outsourced scientific team with access to a highly automated, unique platform here in the 200,000 square foot lab over here next to me in Boston.

這些人是負責默克、輝瑞、諾瓦諾德等公司（也是我們的一些客戶）的藥物開發的人員。Ginkgo 是一個外包科學團隊，可以使用位於波士頓我旁邊 20 萬平方英尺實驗室中一個高度自動化的獨特平台。

And we would give that customer back a scientific result. So good example is that WHEAT program I just mentioned. The customer there is a program manager a head of R&D for the government at our page, and our job is to give them back a scientific result over a period of one to two years with milestones along the way.

我們會向客戶回饋科學結果。很好的例子就是我剛才提到的 WHEAT 計畫。那裡的客戶是我們頁面上的一位專案經理，一位政府研發主管，我們的工作是在一到兩年的時間內向他們報告科學成果，並在此過程中設定里程碑。

Very similar to our commercial relationships. All right. About a year ago, we said, hey, we're going to keep doing that. We're going to do it in a more focused set of areas. That's a lot of how we took the cost down. But we're also going to start offering that very same platform, the same robotics, the same integrated systems directly to customer scientists.

與我們的商業關係非常相似。好的。大約一年前，我們說，嘿，我們將繼續這樣做。我們將在更有針對性的領域開展這項工作。這就是我們降低成本的很大一部分方法。但我們也將開始直接向客戶科學家提供同樣的平台、同樣的機器人技術和相同的整合系統。

Okay, to the many scientists that are at a Nova Nordisk or at Merck and give them tools so that they could do the job of scientific discovery. And that was a new way to go to market. I really like this chart, this curve here, I've shown this before, but on the Y axis, the idea here is as you go up the axis, you have increased customization and technical risk for the customer. And the reason I'm highlighting this is because there's a business model shift in the middle of this chart. So at the extreme left end of this, I'm designing a custom drug.

好的，對於 Nova Nordisk 或 Merck 的許多科學家來說，我們會為他們提供工具，以便他們可以進行科學發現。這是一種新的市場進入方式。我真的很喜歡這個圖表，這個曲線，我之前展示過這個，但是在 Y 軸上，這裡的想法是，隨著軸向上移動，客戶的客製化和技術風險會增加。我強調這一點的原因是因為這張圖表中間有一個商業模式的轉變。因此，在最左端，我正在設計一種定製藥物。

I'm taking all the risk on it, and I'm hoping that when I get great Phase II results or Phase III results, I can sell it to a large pharma company. I make an enormous amount of value, all right? But I take a lot of risk, and it's very custom. As you go down the chart, you have our Research Solutions business. So we are doing custom work, like every one of these customer projects is different.

我願意承擔所有風險，並希望當我獲得出色的 II 期或 III 期結果時，我可以將其出售給一家大型製藥公司。我創造了巨大的價值，好嗎？但我承擔了很大的風險，而且這是非常習慣的。沿著圖表往下看，您會看到我們的研究解決方案業務。所以我們做的是客製化工作，就像每個客戶專案都是不同的。

And it is a technical risk, like we get paid if we are successful, and we hit certain technical milestones. And so as a result, we're able to get royalties and milestones. We're able to get a piece of the customers product revenue, essentially, okay, in one form or another. That's on the left-hand side of that dotted green line. On the right-hand side, you have our tools offerings.

這是一種技術風險，如果我們成功了，並且達到了某些技術里程碑，我們就會得到報酬。因此，我們就能夠獲得版稅和里程碑。本質上，我們能夠以某種形式從客戶的產品收入中分得一杯羹。它位於綠色虛線的左側。在右側，您可以看到我們提供的工具。

And here, we are not taking a royalty. We're not taking any milestones from the customer. And what we're really offering is fee-for-service work for that customer so that they can ultimately develop their own products.

在這裡，我們不收取版稅。我們不會向客戶收取任何里程碑費用。我們真正提供的是向客戶提供收費服務，以便他們最終能夠開發自己的產品。

And that's either going to market with a traditional like CRO style business model with data points or via an equipment business model with automation. And this really does change if you go to the next slide, the solutions business is really based on longer term, but bigger upside per project.

這要么透過傳統的、帶有數據點的 CRO 式商業模式進入市場，要么透過帶有自動化的設備商業模式進入市場。如果你看下一張投影片，情況確實會發生變化，解決方案業務確實基於長期，但每個專案的上升空間更大。

We're getting a piece of that drug value, for example, in the long run, it just takes a long time. The advantage of our tools business is its near-term fees. It's a faster sales cycle, and we have many, many more potential customers for that product in any organization.

例如，從長遠來看，我們正在獲得藥物價值的一部分，只是這需要很長時間。我們的工具業務的優勢在於其近期費用。這是一個更快的銷售週期，我們在任何組織中都有更多該產品的潛在客戶。

And the reason I'm excited about this is Ginkgo has worked out the hard challenges over the last 10 years, of building out our own automation and software stack, if you go to the next slide. And this is not just hardware, it's also our code base, our operations, our data stack and everything else.

我對此感到興奮的原因是，Ginkgo 在過去 10 年裡已經解決了建立我們自己的自動化和軟體堆疊的艱鉅挑戰，如果你看下一張投影片的話。這不僅僅是硬件，還包括我們的程式碼庫、我們的操作、我們的資料堆疊以及其他一切。

And we've done this over 200 R&D projects in agricultural, industrial and pharma biotechnology. So we have the scars of knowing what works and what doesn't work when you're doing this work at a high throughput. And if you go to the next slide, our interest from customers is really around large data set generation for AI.

我們已經在農業、工業和製藥生物技術領域完成了 200 多個研發項目。因此，當您以高吞吐量執行這項工作時，我們知道什麼有效，什麼無效。如果你看下一張投影片，你會發現客戶對我們真正感興趣的是圍繞人工智慧的大數據集產生。

This has been wind in our sales as we've opened our platform up companies like Genentech and Recursion have been showing that you can use these AI models in service of drug discovery. That's meaning a lot more companies are interested in automated data generation, and that's exactly what we've built the reps doing over the last 10 years.

隨著我們開放平台，這對我們的銷售產生了積極的影響，Genentech 和 Recursion 等公司已經證明，可以使用這些 AI 模型來服務藥物研發。這意味著更多的公司對自動資料產生感興趣，而這正是我們在過去 10 年為銷售代表所做的事情。

And so that's been an excellent conversation to have with customers. Now if you go to the next slide, Ginkgo's technology is shown on the right here, that's our facility in Boston with our automated racks. I will highlight, the left-hand side of this chart, the lab bench with the Fisher catalog to order whatever reagents you need is actually a very effective way to go do drug discovery, right? It's a very effective way to go discover plant traits and things like that. It has -- it allows scientists to order what they need, when they need it.

所以這是一次與客戶進行的非常愉快的對話。現在，如果你翻到下一張投影片，Ginkgo 的技術就顯示在右邊，那是我們在波士頓的工廠，配備有自動化貨架。我要強調的是，這張圖表的左側，實驗台上配有 Fisher 目錄，可以訂購所需的任何試劑，這實際上是一種進行藥物研發非常有效的方法，對嗎？這是發現植物特性等的一種非常有效的方法。它可以讓科學家在需要的時候訂購他們需要的東西。

It's very quick. You get turned around in 24 hours, massively customizable. There's nothing wrong with the left-hand side. It just is not great at generating low-cost data points. In other words, if you want to make a lot of data an AI model or for [hydro wood] screening or things like that.

非常快。您將在 24 小時內轉變，並且高度可自訂。左側沒有任何問題。它只是不擅長產生低成本數據點。換句話說，如果你想將大量數據轉化為人工智慧模型或用於[水工木材]篩選或類似的事情。

The bench is not your friend. You do need to move on to something like robotics. And I have that on the next slide as well. These are just two different approaches that are quite complementary, right? It isn't like one has to replace the other.

長椅不是你的朋友。你確實需要轉向機器人技術之類的領域。下一張投影片上也有這個內容。這只是兩種不同的、互補的方法，對嗎？這並不意味著必須用一個來取代另一個。

That's a lot of the conversations we have with customers. It's really that, particularly as these AI models are gaining in prominence. You're going to want to have what we call a foundry basically a generalized automated facility that can be quickly reprogrammed to make new large data sets support your AI and ML teams alongside of the benches where your scientists are still doing small batch very hypothesis-driven research. And by the way, what you learn over here from the foundry and the AI models is going to inform those scientists hypotheses. Absolutely.

這就是我們與客戶進行的許多對話。事實確實如此，特別是隨著這些人工智慧模型越來越受到重視。您將需要擁有我們所說的代工廠，它基本上是一個通用的自動化設施，可以快速重新編程，使新的大型數據集與您的科學家仍在進行小批量、非常假設驅動的研究的工作台一起為您的 AI 和 ML 團隊提供支持。順便說一句，你從鑄造廠和人工智慧模型中了解到的資訊將會為那些科學家的假設提供資訊。絕對地。

That's exactly what we've seen with the Recursion and the Genentech of the world, where you can use the foundry per se, target discovery and then get in the lab at the bench and go test those targets out quickly by hand.

這正是我們在 Recursion 和 Genentech 上看到的，你可以使用代工廠本身，進行目標發現，然後進入實驗室，手動快速測試這些目標。

So that type of feedback loop, I think every major pharma, every large research institute will ultimately need to have a foundry type setup to complement their lab benches. All right. So Ginkgo data points is our first offering in this area. I'm not going to spend and talked a lot about it at the last earnings call.

因此，對於這種回饋迴路，我認為每個大型製藥公司、每個大型研究機構最終都需要有一個鑄造廠類型的設定來補充他們的實驗台。好的。因此，銀杏數據點是我們在該領域提供的第一個產品。我不會花錢，在上次財報電話會議上我已經談了很多關於這個話題。

Just a quick update on this. We launched actually just yes well, Monday our GDP A1 data set. And these data drops are very valuable for the community and they showcase the output of our data point services. So this is a really great one. There's a new preprint that came out.

僅對此進行快速更新。我們實際上在周一發布了 GDP A1 數據集。這些數據對於社區來說非常有價值，它們展示了我們的數據點服務的輸出。所以這真的很棒。有新的預印本已經發布。

You can see on the right, there's a link at the bottom to go download the data set but 246 different therapeutic antibodies. And you can see these 10 different developability assays listed on the left. And then importantly, all that data is in a really clean format for your AI or ML team to go play around with it. And so we're going to keep doing this. So you'll see us keep putting out data sets.

您可以在右側看到，底部有一個連結可以下載資料集，但其中包含 246 種不同的治療抗體。您可以在左側看到這 10 種不同的可顯影性分析。然後重要的是，所有數據都採用非常乾淨的格式，以供您的 AI 或 ML 團隊使用。因此我們會繼續這樣做。所以你會看到我們不斷發布資料集。

The data scientists love these. It creates new customer demand for us, and it showcases just what our platform can do. Okay. So I want to spend a chunk of time real quick talking about Ginkgo Automation and some of the interest we've seen around, in particular, AI reasoning models and connecting those to automated platforms in the lab. First, I want to mention, we had a big win.

數據科學家喜歡這些。它為我們創造了新的客戶需求，並展示了我們的平台所能提供的功能。好的。因此，我想花一點時間快速談論 Ginkgo Automation 以及我們所看到的一些興趣，特別是人工智慧推理模型以及將它們連接到實驗室中的自動化平台。首先，我想說，我們取得了巨大的勝利。

So we announced a week or two ago that we -- our partner and sold the system to [ARA] genetics. This is a diagnostics company building out a new facility. This is really exciting to me because on the next slide, we've obviously had a lot of success with early customers like Octant in the drug discovery space throughput increase, 88% reduction in hands-on time. They've been using the system for two years. They were our original drug discovery beta customer.

因此，我們在一兩週前宣布，我們——我們的合作夥伴並將該系統出售給了 [ARA] 遺傳學公司。這是一家正在建造新工廠的診斷公司。這對我來說真的非常令人興奮，因為在下一張幻燈片中，我們顯然已經與 Octant 等早期客戶在藥物發現領域的吞吐量提升方面取得了很大成功，實際操作時間減少了 88%。他們已經使用該系統兩年了。他們是我們最初的藥物發現測試客戶。

A lot of conversations with high throughput screening, pharma company is definitely going to buy this. But diagnostics companies is really a new market for Ginkgo. So I'm really excited to see the automation going there. And I think this is one of the exciting things about Ginkgo's platform going out as tools, okay? When we're offering solutions, we had like a much more narrow window of where we could apply, say, our automation, right?

很多關於高通量篩選的對話，製藥公司肯定會購買它。但診斷公司對 Ginkgo 來說確實是一個新的市場。所以我很高興看到自動化的發展。我認為這是 Ginkgo 平台作為工具推出的令人興奮的事情之一，好嗎？當我們提供解決方案時，我們可以應用的範圍要狹窄得多，例如我們的自動化，對嗎？

It was ultimately going up through this window of a research project associated with cell engineering. Now the automation could really go anywhere to any lab that would benefit from integrated automation. And you can see that with our RAC carts in the next slide.

它最終透過與細胞工程相關的研究項目的窗口得以實現。現在，自動化可以真正應用到任何能從整合自動化中受益的實驗室。您可以在下一張投影片中看到我們的 RAC 手推車。

The idea behind the Ginkgo Automation is we're basically creating a standardized physical wrapper around a piece of laboratory, essentially benchtop hardware. So that's a center fuse there, that orange thing inside the RAC, then we have a robotic arm.

Ginkgo Automation 背後的想法是，我們基本上是在實驗室周圍創建一個標準化的實體包裝，本質上是桌上型硬體。那裡有一個中心保險絲，RAC 裡面有一個橙色的東西，然後我們有一個機械手臂。

And then we have a piece of MagneMotion track, which is like a little railroad track that can move material along it and deliver a 96 or 384 whatever well plates to that robotic arm, the arm picks it up and puts it on to the -- in this case, center [fuse].

然後我們有一段 MagneMotion 軌道，它就像一條小鐵軌，可以沿著它移動材料，並將 96 或 384 個孔板送到機械臂上，機械臂拾起它並將其放在——在這種情況下，中心[保險絲]。

All right. And so what you've done is you've taken a piece of lab equipment that today is very custom, right? Like it's coming from some particular vendor, it's got its own software. You've got to walk up to it and interact with it and you put it inside this box.

好的。所以你所做的就是拿走一件今天非常客製化的實驗室設備，對嗎？就像它來自某個特定的供應商一樣，它有自己的軟體。你必須走近它並與它互動，然後把它放進這個盒子裡。

And once you've done that, if you go to the next slide, you can stick that RAC card together with as many other ones as you want in a line. And let's say, you add 10 pieces of equipment you wanted to integrate. We would send you the 10 carts with that equipment, you would stick them in a line and then you would use our cloud software to control it.

完成此操作後，如果您轉到下一張投影片，您可以將該 RAC 卡與任意數量的其他卡片貼上。假設您新增了 10 件想要整合的裝置。我們會向您發送裝有該設備的 10 輛手推車，您可以將它們排成一排，然後使用我們的雲端軟體來控制它。

And suddenly, you don't need to be in the weeds in the software on all 10 pieces of lab equipment because our software has parameterized control of all of them. And we didn't have to like a traditional integrated automation vendor would basically do a big custom design for you, a custom engineering project that would take a year or something to ultimately design and build and get it shipped and installed for you.

突然之間，您不需要在所有 10 台實驗室設備上的軟體中花費大量精力，因為我們的軟體對所有設備都進行了參數化控制。我們不必像傳統的整合自動化供應商那樣為您進行大型客製化設計，客製化工程專案需要一年左右的時間才能最終設計、建造並運送和安裝給您。

If we had these 10 racks available, we could send them over and put them together in a very short period of time. And so a matter of weeks. And so that is really exciting and a big change to how you build out integrated automation. The other big change other than just speed to deploy is it's expandable. So when you normally build a custom integrated setup for automation, it's built to do one thing, right?

如果我們有這 10 個機架，我們可以在很短的時間內將它們送過來並組裝起來。就這樣過了幾週。這確實令人興奮，並且對於建立整合自動化的方式來說是一個巨大的改變。除了部署速度之外，另一個重大變化是它的可擴展性。因此，當您通常為自動化建立自訂整合設定時，它是為了做一件事而建立的，對嗎？

With these RAC systems, for example, this is a system we have in Boston, we had five of these to start with, I think, are six doing NGS prep, that was like the original application. And then we were able to keep adding more racks. We now have 25 RACs on this setup. And we have a whole range of different. You can see it here, equipment that have been integrated into these systems.

以這些 RAC 系統為例，這是我們在波士頓擁有的系統，一開始我們有五個這樣的系統，我想，有六個在進行 NGS 準備，這就像最初的應用程式一樣。然後我們就可以繼續增加更多的機架。我們現在在這個設定上有 25 個 RAC。我們有一系列不同的產品。您可以在這裡看到已整合到這些系統中的設備。

We have three different sizes of RAC so that we can integrate this equipment. This is out of date. We keep adding stuff. Whatever customers want in their set up, if there's a piece of equipment haven't yet integrated, we can get it integrated in a few weeks. And so really excited about this general concept.

我們有三種不同尺寸的 RAC，以便我們可以整合該設備。這已經過時了。我們不斷添加內容。無論客戶需要什麼設置，如果有某個設備尚未集成，我們可以在幾週內將其集成。我對這個總體概念感到非常興奮。

And customers are loving this as well. You can see our booth here at the SLAs show, on the next slide. And what I like about this actually the top right corner, there was -- this is actually a JPMorgan Recursion at a party. And we said, hey, can we bring the RACs and so we were able to set them up in a few hours in the afternoon before the cocktail party and have them moving plates around. So that's the speed in terms of deploying an integrated automation setup that you just really don't see with other technology.

顧客們也非常喜歡這一點。您可以在下一張投影片中看到我們在 SLAs 展會上的展位。我喜歡這個的實際上是右上角，那裡是——這實際上是摩根大通在派對上的遞歸。我們說，嘿，我們可以帶 RAC 來嗎？這樣我們就能在雞尾酒會開始前的下午幾個小時內安排好它們，讓它們移動盤子。因此，就部署整合自動化設定而言，這是其他技術無法實現的速度。

This next slide is a picture of our facility in Boston. That's a -- it is an older picture, but that's a 25 RAC setup I was mentioning. And another thing that's unique about Ginkgo is that we actually run our own automation. This is our BSL-2 lab here in Boston to do high throughput data generation for these research projects we're doing for customers. So we have a lot of experience understanding bio validation and moving these high-throughput protocols on to integrated automation.

下一張幻燈片是我們在波士頓的工廠的照片。那是一張較舊的照片，但那是我提到的 25 RAC 設定。Ginkgo 的另一個獨特之處在於我們實際上運行著自己的自動化系統。這是我們位於波士頓的 BSL-2 實驗室，用於為客戶進行的研究項目產生高通量數據。因此，我們在理解生物驗證和將這些高通量協議轉移到整合自動化方面擁有豐富的經驗。

So one of the things I'm really excited and we have customers reaching out to us about this system, if you go to the next slide, is this application of what people are calling lab in the loop or physical AI in the lab. And so just to give you an example of this, if you were to go on to ChatGPT and click that little deep research button, and you ask it a question, instead of getting an answer in five seconds, it's going to give you an answer in like five minutes. And the reason for that, and you can even ask if you want to see it doing this, you can say, hey, show your thinking. And you'll see what's called chain of thought reasoning. And so what the model does is it says, okay, based on your -- what you've asked me to do.

因此，讓我真正興奮的事情之一就是，有客戶向我們諮詢這個系統，如果你翻到下一張投影片，就會發現這個應用就是人們所說的實驗室在環或實驗室中的實體 AI。舉個例子，如果你進入 ChatGPT 並點擊那個小小的深度研究按鈕，然後問它一個問題，它不會在五秒鐘內得到答案，而是會在五分鐘內給你答案。原因如下，你甚至可以問如果你想看到它這樣做，你可以說，嘿，展示你的想法。你就會明白什麼叫做思路鏈推理。所以模型所做的就是說，好的，基於你的——你要求我做的事情。

I've broken this problem into pieces. And for piece number one, I'm going to go call up a web browser and do some research on the Internet. And then based on that information, I get back, there's a bunch of numeric data in there, so I'm going to write a Python script to analyze that data. And based on the results of the Python script, I'm going to do some more thinking and analysis and I'm going to right to a summary. And it goes and does all that.

我把這個問題分解成幾個部分了。對於第一部分，我將呼叫網頁瀏覽器並在網路上進行一些研究。然後根據這些信息，我得到結果，其中有一堆數字數據，所以我要編寫一個 Python 腳本來分析這些數據。並且根據 Python 腳本的結果，我將進行更多的思考和分析，並進行總結。並且它完成了所有這些工作。

It's absolutely fabulous. Like you really should see it if you hadn't. But what's gotten people excited is that type of reasoning and analysis, what if you were to then connect a reasoning model like that into the physical world. And so there's a lot of activity right now, a lot of start-ups getting funded to do like robotic hands, to like pick things up and hold shirts or some electronics. But what I think is really exciting is could we give that reasoning model hands in the lab.

這真是太棒了。如果你還沒看過的話，你真的應該去看看。但讓人們興奮的是這種推理和分析，如果你將這樣的推理模型連結到物理世界會怎麼樣呢？所以現在有很多活動，很多新創公司獲得資金來開發機械手，像是拿起東西、拿襯衫或一些電子產品。但我認為真正令人興奮的是，我們能否在實驗室中將該推理模型付諸實行。

And that's how we see our RACs. They're actually like a perfect fit for this. We're able to integrate -- I mean you could integrate 100 pieces of equipment. We have one project where we're scoping that with RACs. But in Boston, for example, we already have a setup with 25 pieces of lab equipment set up.

這就是我們對 RAC 的看法。它們實際上非常適合這個。我們能夠整合——我的意思是你可以整合 100 件設備。我們有一個項目，我們正在用 RAC 來確定其範圍。但例如在波士頓，我們已經建立了一個擁有 25 台實驗室設備的設施。

And if you go to the next slide, a reasoning model could go ask that set of equipment to run some experiments and then get back really rich data, time series data, raw data files, the RACs give a whole bunch of event data, LIMS metadata about exactly what's going on inside that experiment. A lot more data than you would get if you were doing the experiment by hand at the lab bench.

如果你翻到下一張投影片，推理模型可以要求該組設備運行一些實驗，然後返回非常豐富的數據、時間序列數據、原始數據文件，RAC 提供大量事件數據、LIMS 元數據，準確描述實驗內部發生的事情。如果您在實驗台上手動進行實驗，您將獲得比這更多的數據。

These are just things that you wouldn't be collecting, just wouldn't be collecting them because you're doing a lot of small things as you work at the bench that aren't really being recorded. But everything is being recorded when it's being run on automated setups. And if you go to the next slide, you can see we've already demonstrated -- this is a 24-hour protocol without any human intervention, 10,000 Q PCR reactions.

這些只是你不會收集的東西，只是因為你在工作台上工作時做了很多小事，而這些小事實際上並沒有被記錄下來。但是在自動設定中運行時，一切都會被記錄下來。如果您翻到下一張投影片，您就會看到我們已經示範過了——這是一個無需任何人工幹預的 24 小時協議，10,000 個 Q PCR 反應。

These are the types of things we can do. This is just one example of sort is a large data set on a complex protocol being run over a long period of time. So these like long, continuous experiments, ideally with a reasoning model, controlling it and talking, being able -- having those hands in the lab is something we're really excited about, and we have a lot of customers excited about, too.

這些都是我們可以做的事情。這只是一個例子，它是在長期內運行的複雜協議上的大型數據集。因此，這些就像長期、連續的實驗，理想情況下是使用推理模型，控制它並進行交談，能夠——將這些手放在實驗室裡是我們真正興奮的事情，我們的許多客戶也對此感到興奮。

And so if you go to the next slide, I'll just say for customers tuning in, again, this is what's special about Ginkgo compared to a traditional automation vendor. Over the last 10 years, we have been building and running a highly automated lab.

因此，如果您轉到下一張投影片，我只想對正在收聽的客戶說，這就是 Ginkgo 與傳統自動化供應商相比的特殊之處。在過去的十年裡，我們一直在建造和運作一個高度自動化的實驗室。

And that's not just having the automation set up and doing one thing over and over again, it's doing many things, collecting the data off that automation, getting it cleaned up and back to the scientists. There's a whole software and data stack needed to really make the most out of these automated data foundries.

這不僅僅是設置自動化系統並一遍又一遍地做一件事，它還做很多事情，從自動化系統中收集數據，清理數據並將其返回給科學家。要真正充分利用這些自動化資料鑄造廠，需要一整套軟體和資料堆疊。

And so if you're tasked to bring AI into your research department or deploy these lab and the loop models, we're more than happy, not just to engage with you on the automation, but really on a consultative basis, to help you build out your whole technology stack internally. And we are -- we've actually started doing that for some large pharmas now as well. So these are, I think, just some of the things I wanted to update on.

因此，如果您的任務是將人工智慧引入您的研究部門或部署這些實驗室和循環模型，我們非常樂意，不僅在自動化方面與您合作，而且在真正的諮詢基礎上，幫助您在內部建立整個技術堆疊。事實上，我們現在也已經開始為一些大型製藥公司實施這項措施。所以我認為這些只是我想要更新的一些內容。

I think this whole push on the reasoning model and AI side is really exciting. And again, I want to just highlight and thank the team for an enormous, enormous amount of work over the last year. For us to be in the position where we are today, where we have growing opportunities on the tool side. We have world-leading automation. We have over $0.5 billion in the bank and our spending is under control is a far cry from where we were a year ago.

我認為推理模型和人工智慧方面的整個推動確實令人興奮。我再次強調並感謝團隊在過去一年中所做的大量工作。對於我們今天所處的位置而言，我們在工具方面擁有成長的機會。我們擁有世界領先的自動化技術。我們的銀行帳戶中有超過 5 億美元的存款，而且我們的支出得到了控制，與一年前相比，情況大不相同。

And so again, kudos to the team for pulling that off and look forward to hearing your questions. Thank you so much.

因此，再次向團隊表示敬意，期待聽到您的問題。太感謝了。

Great. Thanks, Jason. (Conference Instructions) Thanks, everyone. All right, getting started. So our first question is from x.com, and this question is from That's Brendan.

偉大的。謝謝，傑森。（會議指示）謝謝大家。好的，開始吧。我們的第一個問題來自 x.com，這個問題來自 Brendan。

The question is, does Jason think there's a possible opportunity for data points to evolve into a SaaS cloud computing product tool to compete with traditional companies in the space like Veeva Systems?

問題是，Jason 是否認為數據點有機會發展成為 SaaS 雲端運算產品工具，以與 Veeva Systems 等傳統公司競爭？

Yeah, it's actually a good question. So I mentioned this a little bit at the end, but we've been starting to do more of these like kind of, I'll call it, consultative almost like tech-enabled consulting for a large pharma company where we're actually coming in and helping them think about their data architecture and like how you should -- if you're going to run a big automated lab, what does it look like?

是的，這確實是一個好問題。我在最後稍微提到了這一點，但我們已經開始做更多這樣的工作，我稱之為諮詢，幾乎就像為大型製藥公司提供技術支援的諮詢，我們實際上是介入並幫助他們思考他們的數據架構以及你應該如何——如果你要運行一個大型自動化實驗室，它會是什麼樣子？

What software do you need to have in place to do that? What data systems you need to have in place to do that and so forth. And I think this is something that can go as a lot of very uniquely specialized expertise in.

您需要什麼軟體才能做到這一點？為了實現這一目標，您需要建立哪些資料系統等等。我認為這是一個可以融入許多獨特專業知識的領域。

There's a question of like how to go to market with that? Like do you actually want to go all the way to offering like SaaS software? Do you want to just do consultative work and then be able to bring in things like our automation technology alongside that and so on, we're figuring that stuff out.

有一個問題，例如如何利用它進入市場？例如，您是否真的想全力提供 SaaS 軟體？您是否只想做諮詢工作，然後能夠引入諸如我們的自動化技術之類的東西，我們正在解決這些問題。

But certainly, companies do make plenty of money in the cloud and SaaS base. So if we saw an opening there, I would say the research side of the house is a little different when it comes to commercial where I think you already have a lot of these tools in like pharma sales and things like that.

但可以肯定的是，該公司確實在雲端運算和 SaaS 領域賺了很多錢。因此，如果我們在那裡看到機會，我會說，在商業方面，研究方面會有所不同，我認為在商業方面，你已經擁有很多這樣的工具，例如藥品銷售和類似的東西。

But when it comes to the research side of the house, many companies are not -- don't already have in place large data infrastructure. And so again, most of the work is done at the bench. Most of it is not large data sets with the exception of things like high throughput screening. So as they build out more of that, I do think there's an opening. We'll have to see if it's a business for us, but definitely it's a place we can help, I would say.

但在研究方面，許多公司還沒有建立大數據基礎設施。所以，大部分的工作都是在工作台上完成。除了高通量篩選等情況外，大多數都不是大型資料集。因此，隨著他們進一步發展，我確實認為會出現一個機會。我們必須看看這是否適合我們做生意，但我想說，這絕對是我們可以提供幫助的地方。

All right. Now for some questions from our analysts. The first question is from Michael Ryskin from Bank of America.

好的。現在讓我們來聽聽我們的分析師的一些問題。第一個問題來自美國銀行的 Michael Ryskin。

Great. Can you guys hear me?

偉大的。你們聽得到我說話嗎？

Yeah. Hey, Michael.

是的。嘿，麥可。

Hey. How are you? Thanks for taking the question. I wanted to ask a two-parter, but on the same topic. One is on the ARPA-H news you provided. Just wondering if you could provide a little bit more details on some of the economics beyond that. We have the headline number in terms of the $29 million contract, but just thoughts on how and when that will be recognized, how that contributes to revenues.

嘿。你好嗎？感謝您回答這個問題。我想問兩個問題，但都是同一主題。一個是關於您提供的 ARPA-H 新聞。我只是想知道您是否可以提供一些有關除此之外的經濟方面的更多細節。我們有 2900 萬美元合約的總體數字，但我們只考慮如何以及何時確認這筆錢，以及這筆錢將如何增加收入。

And then related to that, you had a couple of slides where you talked about government contracts, government relationships, things like that. Just wondering what the latest on those is given the current environment with DOGE cutting back a lot of that funding? Have they been reviewed already? Are those how safe are those? And if you could talk about any take-or-pay considerations there, that would be helpful.

與此相關，您有幾張投影片討論了政府合約、政府關係等問題。只是想知道，鑑於 DOGE 削減了大量資金的當前環境，這些方面的最新情況是什麼？它們已經被審核過了嗎？這些有多安全？如果您能談談任何「照付不議」的考慮，那將會很有幫助。

So Jason, I'd be happy to take the first part of that. So the ARPA-H just in terms of economic side revenue flows. So it's a $29 million two-year contract. So you can expect generally revenue to be recognized over two years. And then I guess the second point I would just make is that from our perspective, that really significantly derisks the guide for the year.

所以傑森，我很樂意承擔第一部分。因此，ARPA-H 僅涉及經濟方面的收入流。所以這是一份價值 2900 萬美元的兩年合約。因此，您通常可以預期收入將在兩年內得到確認。然後我想我要說的第二點是，從我們的角度來看，這確實大大降低了年度指南的風險。

And so -- yeah, so I think it was very good news to be getting that from the perspective of this year.

是的，所以我認為從今年的角度來看這是個非常好的消息。

Yeah, just speak to the second part, yes, that was one of the ones we're keeping an eye on that. We had gotten awarded -- I knew we were going to get it, but we hadn't closed on contracting. So I do think, in general, like I mentioned, I think biotechnology is still on the short list of critical emerging technologies.

是的，只談第二部分，是的，這是我們正在關注的部分之一。我們已經中標了——我知道我們會得標，但我們還沒有簽約。所以我確實認為，總的來說，正如我所提到的，我認為生物技術仍然在關鍵新興技術的候選名單之列。

So I'm generally hopeful that any additional programs that we have that aren't quite contracted yet will move through. But importantly, that they'll still continue to be funding, like Mark said, the -- we was the big bogey on that for us for this year.

因此，我總體上希望我們尚未簽訂合約的任何附加項目都能夠順利完成。但重要的是，他們仍將繼續提供資金，就像馬克所說的那樣，這是我們今年面臨的最大障礙。

But in general, what's more important is like do we keep seeing the funding of advanced research in this area, we think so. And then certainly, on the Biosecurity side, there was a couple of executive orders just today related to Bio. I don't know if you saw that, but there was one on regulatory relief to promote domestic production of critical medicines.

但總的來說，更重要的是我們是否繼續看到對該領域高級研究的資助，我們認為是的。當然，在生物安全方面，今天剛頒布了幾項與生物相關的行政命令。我不知道你是否看到了，但其中有一篇是關於監管放鬆以促進關鍵藥物的國內生產的。

So that's right in line with the wheat project and generally onshoring. It's basically reducing regulation for people building out manufacturing for pharma, not something we do, but just to speak to this being a critical priority.

所以這與小麥專案和整體在岸專案是一致的。這基本上是在減少對製藥製造業的監管，這不是我們做的事情，只是說這是一個關鍵的優先事項。

And then second is improving safety and security of biological research. This is around like not funding gain of function work. But again, speaks to, I'd say, Biosecurity being on the list of things that are not being written off is not important. So I'm cautiously optimistic, but of course, you never know.

第二是提高生物研究的安全性。這就像不資助功能增益工作一樣。但我想說的是，生物安全被列入未被註銷的事項清單並不重要。所以我持謹慎樂觀的態度，但當然，你永遠不知道。

If I could -- I guess just a follow-up, Mark, on the first point on the ARPA-H. Just clarify, there's multiple partners in that, right? So is there any clarity out of time how that $29 million gets split up or --

如果可以的話——馬克，我想就 ARPA-H 的第一點進行跟進。澄清一下，這裡面有多個合作夥伴，對嗎？那麼，這 2900 萬美元如何分配，或者--

Yeah. So we're the prime, which means we will recognize all the revenue on that, and you would then see in the cost of sales or in the R&D expense and the effect of the subcontractor costs on that, but we would be recognizing the full amount of revenue.

是的。因此，我們是主要的，這意味著我們將確認所有的收入，然後你會看到銷售成本或研發費用以及分包商成本對此的影響，但我們會確認全部收入。

Okay. All right. Thanks.

好的。好的。謝謝。

All right. Our next question is from Mark Massaro, who's from BTIG.

好的。下一個問題來自 BTIG 的 Mark Massaro。

(technical difficulty) All right. Sorry, you got me now?

（技術難題）好的。抱歉，你現在明白我的意思了嗎？

Yeah.

是的。

Awesome. Thank you for the question. So I wanted to just ask a question about revenue-generating program metric. Maybe this could be for you, Mark. Just help us think about how we should be tracking the economics per program.

驚人的。謝謝你的提問。所以我只想問一個關於創收計畫指標的問題。也許這對你來說很合適，馬克。只需幫助我們思考如何追蹤每個項目的經濟狀況。

So if I'm doing the math right, it looks like the revenue per program might be down in the quarter. Can you just give us a sense for how we should think about that? Is that something that should grow? Or is it because you're onboarding newer programs that are just starting to generate revenue, it takes some time to move up?

因此，如果我的計算正確的話，看起來本季每個項目的收入可能會下降。您能否告訴我們應該如何看待這個問題？這是應該成長的東西嗎？還是因為您正在引入一些剛開始產生收入的新項目，需要一些時間才能提升？

It's actually a little bit of a mix shift from the bigger solutions deals to data point deals. So the number of data points deals went in the metric went from about 10 to 20 when you compare Q4 to --

這實際上是從較大的解決方案交易到數據點交易的一點混合轉變。因此，當你將第四季度與第二季度進行比較時，交易數據點的數量從大約 10 增加到 20--

(technical difficulty)

（技術難度）

(technical difficulty)

（技術難度）

And I recognize the new reporting structures is early days, but if I have this right, looks like your revenue (technical difficulty)

我知道新的報告結構還處於早期階段，但如果我沒記錯的話，看起來像你的收入（技術難度）

Do you think that's the right way to think about them progressing throughout the year? And then I would just be curious if you could just give us any color as to like the flavor of some of these price due in the quarter?

您認為這是思考他們全年進步的正確方式嗎？然後我只是好奇您是否可以給我們一些關於本季度到期的一些價格的詳細資訊？

So it's -- so you're going to have programs that complete and programs that onboard. And so the net impact of that means you probably are not going to see a net plus 20 quarter after quarter after quarter after quarter. You're going to have some quarters where we finish a bunch of programs. And so again, still early days, Mark, with the metric. But I think we're all keeping our eye on that trend line.

所以 — — 所以你將擁有完整的程式和可運行的程式。因此，其淨影響意味著，你可能不會看到一個季度又一個季度的淨增加 20%。我們將會有幾個季度完成一系列專案。馬克，對於這個指標來說，我們仍然處於早期階段。但我認為我們都在關注這一趨勢線。

The flavor in terms of what's in there. So there's still -- I would say, like, generally speaking, the solutions deals, of course, are bigger. The data points deals are smaller. There are just a few automation deals in the mix right now because that's really the newest of the tools offerings. We did sign a bunch of ag solutions deals in Q1, which is new.

就裡面的東西而言，味道如何。所以，我想說，一般來說，解決方案交易當然更大。數據點交易較小。目前只有少數自動化交易，因為這些實際上是最新推出的工具。我們確實在第一季簽署了一系列農業解決方案協議，這是新的。

I think it might have been the most new programs that I remember in that part of the business in a single quarter. That said, they're all relatively small in size. And so you can think of those as almost pilot in terms of scale relative to the solutions side of the business. So yes, I would just say probably like the flavor is good diversity in terms of what we're seeing with big programs, small programs across ag, biopharma, et cetera, data points, solutions.

我認為這可能是我記得的一個季度內該業務領域推出的最多的新項目。也就是說，它們的體積都相對較小。因此，從業務解決方案的規模來看，你可以將它們視為幾乎是試點。所以是的，我只想說，就我們所看到的農業、生物製藥等領域的大型專案、小型專案、數據點和解決方案而言，其風格可能具有良好的多樣性。

Great. Thank you.

偉大的。謝謝。

Thanks, Mark. All right. Next question from Tejas who's coming from Morgan Stanley.

謝謝，馬克。好的。下一個問題來自摩根士丹利的 Tejas。

Hey, guys. Good evening and thanks for the time here. So maybe a predictable question for you, Jason, just on the continued pressure on pharma and biotech here, the commentary from service providers through the starting season has gotten incrementally more cautious, I guess? Yeah.

嘿，大家好。晚上好，感謝您抽出時間。所以傑森，也許你會問一個可以預見的問題，只是因為製藥和生物技術持續面臨壓力，我猜服務提供者在賽季開始時的評論已經變得越來越謹慎了？是的。

And I guess, a lot of nebulous concerns out there, things like tariffs and reference pricing, this afternoon, we heard of the appointment of a new head of [Seaboard] today bringing vocal stances and accelerated approvals and target endpoints and whatnot. So I'm just curious as to what you're hearing from your customers, especially over the last like six to eight weeks when things seem to have ratcheted up a little bit, if you will?

我想，外面有很多模糊的擔憂，例如關稅和參考定價等問題，今天下午，我們聽說了 [Seaboard] 新負責人的任命，他發表了明確立場，加快了審批速度，設定了目標終點等等。所以我很好奇您從客戶那裡聽到了什麼，特別是在過去的六到八周里，情況似乎有所好轉，您願意這麼說嗎？

Yeah. I mean I would say, overall, it is like there is a lot of hesitancy in general around R&D services. So like I think you're just seeing, a, less outsourcing of stuff. People are like more protective of their internal teams. So that's like been headwinds for us on the solution side.

是的。我的意思是，總的來說，人們對研發服務普遍存在很多猶豫。所以我認為你看到的只是外包的東西越來越少了。人們更加保護他們的內部團隊。所以這對我們解決方案而言就像是阻力一樣。

I think if you look across the industry broadly, the like there's less demand going to like basically all CRO and equipment and tools vendors. I think that's -- and you've seen that reflected in the pressure on all of them. I mentioned this before, Ginkgo's new in the tools industry. So unlike, say, us or somebody that's like highly penetrated across the whole industry and moves with the total demand. We're more winning pie from others.

我認為，如果從整個產業來看，基本上所有 CRO 以及設備和工具供應商的需求都會減少。我認為——你已經看到他們所有人所承受的壓力都反映了這一點。我之前提到過，Ginkgo 是工具產業的新產品。因此，與我們或其他在整個行業中高度滲透並隨著總需求而變化的人不同。我們比別人贏得更多。

And so I think there's a lot of opportunity for us still uniquely in tools, but I would say the whole sector is definitely under pressure. I think that probably means places invest less in new advanced technologies, right?

因此，我認為我們在工具領域仍然有很多獨特的機會，但我想說整個行業肯定面臨壓力。我認為這可能意味著各個地方對新先進技術的投資減少了，對嗎？

Like I think you're less likely to see a lot of the current players like doing some big project to expand in a new area right now. So that's maybe good for us because we're an innovative new entrant. And so -- but I would say across the industry, I'm hearing from people what you're hearing, which is pull back on things.

就像我認為你現在不太可能看到很多當前的參與者做一些大專案來在新的領域擴張。這對我們來說可能是件好事，因為我們是個創新的新進者。所以 — — 但我想說，在整個行業中，我從人們那裡聽到的和你們聽到的一樣，那就是撤退。

But I don't know that Ginkgo maybe gets affected a little less on that when it comes to our tools business. I do think on solutions, that makes it tougher for us.

但我不知道，當談到我們的工具業務時，Ginkgo 是否會受到較小的影響。我確實在思考解決方案，但這對我們來說卻更加困難。

Got it. That's helpful. A couple of quick cleanups for Mark. Mark, can you just share some color or just ballpark numbers to help us bridge from your old program ad metrics, the new revenue-generating programs? And then I think on the last call, you guys had talked about a little bit of potential upside from tools offering and a number of pharma deals that closed in the fourth quarter.

知道了。這很有幫助。為馬克進行一些快速清理。馬克，您能否分享一些具體數據或大概的數字，以幫助我們將舊的計劃廣告指標與新的創收計劃聯繫起來？然後我想在上次電話會議上，你們談到了工具提供的一些潛在優勢以及第四季度完成的一些製藥交易。

So just curious as to how those opportunities have evolved since? And then on this pharma reshoring point, Jason, which you alluded to a little bit earlier, is there an opportunity beyond the work you're doing with ARPA-H here in your mind for Ginkgo to participate in?

所以只是好奇這些機會自那時起是如何演變的？然後，傑森，關於你之前提到的這個製藥業回流點，除了你與 ARPA-H 合作的工作之外，你認為 Ginkgo 還有其他參與的機會嗎？

All right. So why don't I start there? So in terms of bridging the old metric to the new. So the new metric very importantly, excludes programs with de minimis revenue in the quarter. So that would typically be a program that is either just starting or is in the final stages of completion.

好的。那我為什麼不從那裡開始呢？因此，就將舊指標與新指標連結起來而言。因此，新指標非常重要，它排除了本季收入最低的項目。因此這通常是一個剛啟動或處於最後完成階段的專案。

And we really, in any particular quarter in the past had quite a lot of those, like we might have had just like rough numbers 20 to 30 programs that were in a start mode and maybe similar number that we're in a final stage of completion mode.

事實上，在過去的任何一個季度，我們都有很多這樣的項目，例如，我們可能有大約 20 到 30 個處於啟動模式的項目，也可能有類似數量的項目處於最終完成階段。

And so those would be out of the mix right now completely. However, it's not a straight subtract because we're now including programs or wouldn't have been included in the past because they didn't meet the definition of what we thought of as a major program. And so a lot of the smaller data points programs or even small solutions programs wouldn't necessarily have been included in the past at all under the definition. And so those are now in the mix.

因此，這些現在將完全不再起作用。然而，這並不是直接的減法，因為我們現在包括了一些項目，或者說，過去它們不會被包括在內，因為它們不符合我們所認為的主要項目的定義。因此，許多較小的資料點程式或甚至小型解決方案程式在過去根本不一定會被納入該定義中。所以現在這些都混在一起了。

So that's like the rough bridge here. Now if you look in the appendix to the presentation, we have included a restatement of -- or I would just say the historical comparables that you need on the current metric so that you can see what it was in each quarter of last year.

這就像是一座崎嶇的橋。現在，如果您查看簡報的附錄，我們已包含重述 - 或者我只想說您需要的當前指標的歷史可比性，以便您可以了解去年每個季度的情況。

So that will help you bridge the old to the new. On your second question, upside on tools and pharma. So I think probably the best way to put it is in terms of the revenue guide, yes, the guide is still being, I would say, relatively conservative in terms of what we're expecting from tools this year.

這將幫助你連結舊事物和新事物。關於你的第二個問題，工具和製藥方面的優勢。所以我認為最好的說法是就收入指南而言，是的，我想說，就我們對今年工具的預期而言，該指南仍然相對保守。

So still in that low double-digit million dollar contribution on a full-year basis. And just to put that in context, in the first quarter, tools contributed low single-digit millions in terms of revenue. So less than 10% of the cell engineering revenue in Q1 came from the tools offering, and then we would expect that number to increase as we get through the year.

因此，全年的貢獻仍處於兩位數百萬美元的低點。就此而言，在第一季度，工具貢獻的收入僅為數百萬美元。因此，第一季不到 10% 的單元工程收入來自工具供應，我們預計隨著時間的推移，這一數字會增加。

But it's still early days, so we're being conservative there, but I would say there's upside potential on the tools side of the business, particularly on data points, I think what we're learning on automation is that is a longer sales cycle. With respect to some of the bigger -- like your point on biopharma, yes, I mean, I think we're happy with how we're executing on those deals right now.

但現在還處於早期階段，所以我們在這方面持保守態度，但我想說，業務的工具方面，特別是在數據點方面，還有上升潛力，我認為我們在自動化方面學到的是更長的銷售週期。對於一些較大的交易——例如您提到的生物製藥交易，是的，我的意思是，我認為我們對目前這些交易的執行情況感到滿意。

And I think we'll be looking to see whether or not we can expand the relationships with some of those biopharma as we execute on some of the first projects that we have with them in data points.

我認為，當我們在數據點上執行與這些生物製藥公司合作的一些首批專案時，我們會看看是否可以擴大與這些生物製藥公司的關係。

Yeah. I would say I think one of the things that the biopharma is we can get in with a proof of concept. We were adding and continue to add like new logos there, which is always exciting for Ginkgo because we have a variety of things we can sell to people. And so getting in improving ourselves and getting set up with the procurement system at these places is all just like wins for us. So that continues to work like the proof-of-concept deals.

是的。我想說，我認為生物製藥領域的一個重要領域是我們可以透過概念驗證來實現。我們在那裡添加並繼續添加新的標誌，這對 Ginkgo 來說總是令人興奮的，因為我們有各種各樣的東西可以賣給人們。因此，提高我們自己並在這些地方建立採購系統對我們來說都是勝利。因此，這將繼續像概念驗證交易一樣發揮作用。

The hope is that those then grow into larger programs and data points or maybe an automation purchase. And then when it comes to the onshoring and asked about us data. I think one application there for us would be using the automation for some of the QC on -- so it's usually a variety of different assays that are being included in the quality control for therapeutics coming off the manufacturing.

希望這些能夠發展成為更大的程序和數據點，或者可能是自動化購買。然後當談到在岸外包並詢問我們的數據時。我認為我們的一個應用是使用自動化進行一些品質控制 - 因此它通常包括各種不同的檢測，這些檢測被納入製造出來的治療藥物的品質控制中。

Those are often like can be pretty complicated experiments and can be a good fit depending on the drug for some of our automation. So that's one place I think we could play.

這些通常可能是相當複雜的實驗，並且可能適合根據藥物進行的一些自動化實驗。所以我認為那是我們可以玩的地方之一。

We obviously don't do -- we're not a manufacturer. So you won't see us like building a new site. We're not like a Lonza or something. But I do think on the automation side, we could play.

我們顯然不會這麼做——我們不是製造商。所以你不會看到我們蓋一個新的網站。我們不像龍沙（Lonza）之類的公司。但我確實認為在自動化方面我們可以有所作為。

Got it. Super helpful. Thanks, guys. Appreciate the time.

知道了。超有幫助。謝謝大家。珍惜時間。

All right. Next up, we have Matt Sykes from Goldman Sachs.

好的。接下來我們有請高盛的馬特·賽克斯 (Matt Sykes)。

Hi. This Evie on for Matt. thank you for taking my questions. So the first one, great to see the deal with [ARA]. How do you view the longer-term opportunity within the diagnostics for RACs? And then are you seeing any interest from customers in this space on a broader scale, especially given the durability of that end market versus earlier-stage R&D spending?

你好。這是 Evie 為 Matt 拍攝的。感謝您回答我的問題。所以第一個，很高興看到[阿拉]。您如何看待 RAC 診斷領域的長期機會？那麼，您是否看到客戶對這個領域有更廣泛的興趣，尤其是考慮到終端市場與早期研發支出相比的持久性？

Yeah. We think it's a great, great fit for diagnostics. I mean, what makes the RACs unique compared to like a traditional integrated setup is that it is expandable. So when you're getting a work cell set up to do whatever your particular diagnostic reaction like you're trying to predict how much demand you have, that work cell has a certain capacity. If you start to exceed that, the current industry standard is basically build a whole another work cell.

是的。我們認為它非常適合診斷。我的意思是，與傳統的整合設定相比，RAC 的獨特之處在於它是可擴展的。因此，當您設定一個工作單元來執行任何特定的診斷反應（例如，您試圖預測有多少需求）時，該工作單元具有一定的容量。如果你開始超越這個目標，目前的業界標準基本上就是建立一個全新的工作單位。

Whereas with the RACs, you could take whatever piece of equipment it is that your current bottleneck on your diagnostic process and just add a second one to the setup and potentially alleviate that bottleneck. So that's really exciting. It's also like not something that sunsets in the event that your mix of diagnostic demand changes in the future, right?

而使用 RAC，您可以採取診斷過程中目前瓶頸的任何設備，只需在設定中添加第二個設備即可緩解該瓶頸。這真的非常令人興奮。如果您未來的診斷需求組合發生變化，這也不會停止，對嗎？

So what's great about the RACs is some of the equipment is likely to be common across different protocols you're running. And you could -- if you had, say, a new protocol you brought online, let's say you wanted to add some like NGS diagnostic to your current setup, you could then add a few pieces of equipment to the very same RAC setup you had running your first protocol and add a second one.

RAC 的優點在於，其中一些設備可能在您所執行的不同協定中是通用的。而且您可以 — — 如果您有一個上線的新協議，假設您想在當前設定中添加一些類似 NGS 診斷的功能，那麼您可以將幾件設備添加到運行第一個協議的相同 RAC 設定中，並添加第二個協議。

So this is -- I mean like we're obviously biased, but like we really think of it like you're building an automation core that can be used for lots of different things rather than a work cell, that's meant to do one thing. And that's really compelling and totally changes the ROI calculation for people building out integrated automation.

所以這是——我的意思是，我們顯然有偏見，但我們真的認為你正在建立一個可以用於許多不同事物的自動化核心，而不是一個工作單元，它旨在做一件事。這確實引人注目，徹底改變了人們建立整合自動化的投資報酬率計算。

So we think we should be on the RFP and the look for anybody building a new automation facility. We got to get the word out in the market, but it's really exciting to me to see us getting this first diagnostics deal, like we really see ourselves able to play in that space.

因此，我們認為我們應該參與 RFP 並尋找任何可以建造新自動化設施的人。我們必須在市場上宣傳，但看到我們達成第一份診斷協議，我真的很興奮，我們真的認為自己能夠在這個領域發揮作用。

Okay. Great. And then on the EBITDA breakeven target for the end of 2026. What are the areas -- are you -- have you uncovered any areas of upside as you work through the cost-cutting exercises? And then on the flip side, how are you able to balance the spending to make sure that the new offerings get good initial traction commercially while also meeting the profitability goals?

好的。偉大的。然後是 2026 年底的 EBITDA 損益平衡目標。在進行成本削減工作時，您發現了哪些方面有優勢？另一方面，您如何平衡支出以確保新產品在商業上獲得良好的初始吸引力，同時滿足獲利目標？

So Jason, I'd be happy to take the first part and maybe hand the second part over to you. So we do still have room to go on cost, and that's why we upped the target to $250 million. I would say, Evie, yes, there's probably still some room after we get to that level. We largely, at this point, have taken the actions that we need to take in order to get to the $250 million. There's still a little bit of work to do there.

所以傑森，我很樂意接手第一部分，也許把第二部分交給你。因此，我們在成本方面仍有提升空間，這就是我們將目標提高到 2.5 億美元的原因。我想說，伊薇，是的，當我們達到那個水平之後可能還有一些空間。到目前為止，我們基本上已經採取了實現 2.5 億美元目標所需的行動。那裡還有一些工作要做。

So you'll start to see the impact of that part of the cost reduction roll through the Q2, Q3 numbers. But we are, I think, being careful at this point. And I'll let Jason just talk about the new opportunities.

因此，您將開始看到這部分成本削減對第二季和第三季數據的影響。但我認為，我們現在要小心謹慎。我讓傑森談談新的機會。

I wouldn't say, though, Evie, there's some like very large silver bullet upside cost reduction opportunity other than, of course, subleasing the excess space, which we all know is a challenge in this market. Other than that, we're much more into the weeds on looking at small dollar line items.

不過，伊薇，我不會說除了轉租多餘的空間之外，還有其他非常大的降低成本的靈丹妙藥，我們都知道，這是這個市場的一個挑戰。除此之外，我們也更加關注小額美元項目。

And that's where we're at right now. There aren't like these big chunks of upside anymore.

這就是我們現在的處境。不再存在如此龐大的上漲空間。

Yeah. And just a comment on the tool side. I mean you won't see us do anything pathological if that's the question, right? Like so the -- if we see opportunity where by investing in -- for example, just today, we got another data drop from data points for cell painting. This is like imaging-based data set so you can have bright field, you can do the cell painting.

是的。這只是對工具方面的評論。我的意思是，如果這是問題的話，你不會看到我們做任何病態的事情，對嗎？就像這樣——如果我們看到投資機​​會——例如，就在今天，我們從細胞繪畫的數據點獲得了另一個數據下降。這就像基於成像的資料集，因此您可以擁有明場，可以進行細胞繪畫。

These are becoming like common high content data sources for people doing like AI/ML for drug discovery, right? Like that's the first time we put out a data set like that. We'd love to do stuff like that. We already have a ton of like interest in that, a lot of people downloading it. You'll see us keep doing that, investing in new areas for data points.

對於從事藥物研發的 AI/ML 等的人來說，這些正在成為常見的高內容資料來源，對嗎？這是我們第一次發布這樣的數據集。我們很樂意做這樣的事。我們已經有大量用戶對此感興趣，並且有許多人正在下載它。您將看到我們繼續這樣做，投資新的數據點領域。

No-brainer. As long as we -- when we put out a new one, we see new customers, you won't see me stop investing and that thing. Same look like on the automation side, we see opportunities to demonstrate particular workflows and show people we put out these like white papers and demonstrations of what you can do on the RACs. I see a lot of upside in all those things. You won't see a slowdown there just to meet an EBITDA target.

毫無疑問。只要我們——當我們推出新產品時，我們就會看到新客戶，你就不會看到我停止投資等等。就像在自動化方面一樣，我們看到了展示特定工作流程的機會，並向人們展示了我們發布的白皮書和您可以在 RAC 上做什麼的演示。我看到所有這些事情都有很多好處。你不會看到僅僅為了達到 EBITDA 目標而出現經濟放緩。

But all things equal, we do see a good line of sight to getting to it by the end of '26. So it is a focus. But a lot of it is really just tightening up on the solutions side so that we have room to invest in tools. That's really the big motion.

但所有條件相同的情況下，我們確實看到了在 26 年底實現這一目標的良好前景。所以這是一個重點。但其中許多實際上只是在解決方案方面加強，以便我們有空間投資於工具。這確實是一個重大舉措。

Great. Thank you so much.

偉大的。太感謝了。

I think we have one last question. I saw another pop up, but I think we probably just have time for one more from Matt Larew, who's coming to us from William Blair.

我想我們還有最後一個問題。我看到了另一個彈出窗口，但我想我們可能只剩下時間再聽一下來自 William Blair 的 Matt Larew 的另一個帖子了。

Hey, Matt.

嘿，馬特。

Hey. Good afternoon. Thanks for taking the question. Jason, if I think back to '23, '24 when there were perhaps different, but in some way similar macro constraints with respect to biotech funding, you really were selling, we have like three weeks of positivity at the beginning of this year. The -- you're really selling one or at least just a couple of solutions. The contract structure was perhaps more onerous to get deals done in terms of longer lead times.

嘿。午安.感謝您回答這個問題。傑森，如果我回想一下 23、24 年，當時在生物技術融資方面可能存在一些不同但在某種程度上類似的宏觀限制，你確實在推銷，今年年初我們有大約三週的積極表現。您實際上銷售的是一種或多種解決方案。由於交貨時間較長，合約結構可能對完成交易更加不利。

And there was maybe more of a focus on biopharma, but I know that remains today. If I then transport it today and maybe we're entering more macro uncertainty from a variety of different angles, you now have a number of different product offerings that span content, tools, automation, et cetera.

也許人們更加關註生物製藥，但我知道今天仍然如此。如果我今天進行傳輸，也許我們會從不同的角度進入更多的宏觀不確定性，現在您可以提供許多不同的產品，涵蓋內容、工具、自動化等等。

You've opened up the way you're thinking about doing deals and different sizes and structures. But you also alluded to in your earlier comments, this inherent push-pull between the willingness to outsource. It does the same dollar amount mean that less work gets done? Or does it -- which people to do more to work more efficiently, right? So some of these tensions.

您已經公開了思考交易的方式以及不同規模和結構的交易。但您在先前的評論中也提到了外包意願之間存在的內在推拉關係。相同的金額是否意味著完成的工作更少？或者說——哪些人需要做更多的事情才能更有效率地工作，對嗎？因此存在一些緊張局勢。

And so I'd just be curious, either in the first couple of months of the year or what you're seeing and hearing from customers how you think Ginkgo can fit into if macro situation deteriorates or may uncertain, how you fit into the picture differently this time than perhaps a couple of years ago?

所以我只是很好奇，無論是在今年頭幾個月，還是您從客戶那裡看到和聽到的情況，您認為如果宏觀形勢惡化或不確定，銀杏將如何適應，這次您的情況與幾年前有何不同？

Yeah. I think the biggest thing is with the tools offering, like you can like take smaller bites and engage with us, right? Like the what I would have had '23, '24 was there a the elongated deal with in was the big R&D projects. That type of big outsourced R&D work across the industry, like pick your favorite small biotech in Cambridge. It's not getting like a large research partnership right now with like major pharmas or midsize pharmas.

是的。我認為最重要的是透過提供的工具，您可以小口小口地與我們互動，對嗎？就像我本來會在 23、24 年做的一樣，其中有一個長期交易，涉及大型研發項目。這種類型的大型外包研發工作遍布整個產業，例如在劍橋挑選你最喜歡的小型生技公司。目前它還沒有與大型製藥公司或中型製藥公司建立大規模的研究合作關係。

So that -- that's just the reality, right? So I think the thing we've done well in the last year, and again, I think this continues to speak to the flexibility of the platform we've built at Ginkgo, we're really like the core heart of it is a lot of this automation and software infrastructure and approaching a like a factory, that's proving like very durable to be able to take in different directions, all the way from industrial biotech when we first would have been talking to you through ag to pharma to now different styles, whether you're selling it to solutions and tools, I think like we're tough to kill, right? I think that's what's been proven over the last couple of years here at Ginkgo.

所以——這就是現實，對吧？所以我認為我們去年做得很好，而且我認為這繼續說明了我們在 Ginkgo 構建的平台的靈活性，我們真的覺得它的核心是大量的自動化和軟體基礎設施，就像工廠一樣，事實證明它非常耐用，能夠朝不同的方向發展，從工業生物技術（當我們第一次與您交談時）到製藥業，再到現在不同的風格，無論您是將其出售給解決方案還是被消滅工具？我認為過去幾年銀杏的情況已經證明了這一點。

And so I think that, that speaks to the strength of the platform. I would -- I do think there is some looking for silver linings, like whenever there is churn, like right now, like, for example, at the FDA, you're seeing a lot of interest around changing how we approach things like toxicology, with the government in general, a lot of issues around how we're approaching other countries, particularly China, doing our work.

所以我認為這說明了該平台的實力。我確實認為，有些人正在尋找一線希望，例如每當出現變動時，例如現在，例如在 FDA，你會看到很多人對改變我們處理毒理學等問題的方式感興趣，與政府總體上，很多問題都圍繞著我們如何與其他國家，特別是中國，開展我們的工作。

I mean, look, if Wuxi gets nuked, that's like -- that's a huge opening for us, right? Like if it's like, hey, you can't use them. then there's a lot of new CRO business to be had, right? So there are things there that could change the macro for Ginkgo specifically. We'll see, right?

我的意思是，如果無錫遭到核攻擊，對我們來說就是一個巨大的機會，對吧？就像，嘿，你不能使用它們。那麼就會有很多新的 CRO 業務要做，對吧？因此，有些東西可以專門改變銀杏的宏。我們會看到，對吧？

But I think what we've shown is get goes resilient, can will change as the market changes around us and we're not going to die, right? So that, I think, remains the case, '23 to now. And certainly, as the biggest change is us going to market with tools. which is much more favorable for this current environment in terms of what customers are up for buying. Smaller chunks, more arm's length is what the market demands right now.

但我認為，我們已經展現出韌性，可以隨著周圍市場的變化而變化，我們不會消亡，對嗎？所以我認為從 23 年到現在情況仍然如此。當然，最大的改變是我們利用工具進入市場。就消費者的購買意願而言，這對當前環境更為有利。更小的份額、更大的距離正是市場目前所要求的。

Got it. And then maybe a follow-up to that. Curious the lead generation and closes for the newer programs, data points tool, the tools offerings. Are most of those internal in the sense that perhaps you were actively engaging with the customer will be on a broader different project and then that didn't work, but, hey, something else popped up you can do or more to those external at this point as people get more awareness about them?

知道了。然後也許會對此進行跟進。好奇新程式、資料點工具和工具產品的潛在客戶生成和結束情況。從某種意義上說，其中大部分都是內部的嗎？也許您正在積極與客戶接觸，參與更廣泛的不同項目，但這種方法沒有奏效，但是，嘿，出現了其他您可以做的事情，或者隨著人們對這些外部事物的認識不斷提高，您可以做更多的事情？

It's a lot more stuff coming externally now. That's great about the tools business. Like we put these data drops up like the one we did today, and people just download it and get us the e-mails we follow up, and we've gotten chunks the business that way. It's pretty neat. So that's exciting.

現在有更多的東西來自外部。工具業務真是太棒了。就像我們今天所做的那樣，把這些數據放到一起，人們只需下載它並獲取我們要跟進的電子郵件，我們通過這種方式獲得了大量的業務。它非常整潔。這很令人興奮。

Within our close accounts, we certainly are able to expand, right? So like there's RFPs out right now for automation systems with customers that we've had multiyear engagements with on the solution side. That's obviously puts us in a really nice spot. So we do see some of that, but it's not the only source of leads. We are -- again, with the tools business.

在我們的封閉帳戶中，我們當然能夠擴張，對嗎？因此，目前我們已經向客戶發布了針對自動化系統的 RFP，我們在解決方案方面已經與這些客戶進行了多年的合作。這顯然讓我們處於一個非常好的位置。因此我們確實看到了一些，但這並不是唯一的線索來源。我們再次從事工具業務。

And ideally, I'd actually like the tools business to keep enabling smaller and smaller bite-size chunks, right? So watch us over the course of the year, hopefully be able to launch other things that let people bite off even smaller bids because I just think that's what's still selling. And so -- but yeah, but it is definitely, we're also getting external inbound now, which is nice.

理想情況下，我實際上希望工具業務能夠繼續支援越來越小的區塊，對嗎？因此，請在今年關注我們，希望能夠推出其他產品，讓人們接受更小的出價，因為我認為這仍然是暢銷產品。所以 — — 但是是的，但肯定的是，我們現在也獲得了外部入站，這很好。

Unfortunately, I think we're out of time --

不幸的是，我想我們沒時間了--

Daniel, I think I see Brendan with his hand up. So I think we can fit in one more.

丹尼爾，我想我看到布倫丹舉起了手。所以我認為我們還可以再多加一個。

Yeah, for sure. Sure. Go ahead, Brendan -- Mark, I don't really know how you do that. That's amazing. That's beyond my Zoom screens. So yeah, Brendan, I appreciate the question. Go ahead.

是的，當然。當然。繼續吧，布倫丹——馬克，我真的不知道你是怎麼做到的。太棒了。這超出了我的 Zoom 螢幕的範圍。是的，布倫丹，我很感謝你的提問。前進。

Always happy to impress. Yeah. So maybe just quickly expanding on a couple of the questions previously. Really, on the AI tools offering, can you speak maybe just a little bit more on the training data you're using for some of these models and really just where you're sourcing some of that from us because we're starting to get questions on where as there are more offering across the sector where people are sourcing a lot of this stuff from -- are you able to use partner or licensee data sets to trade back in your models or everything proprietary and generated in-house, really more so understand trying to understand how scalable some of those could be over the longer term for you guys?

總是樂於給人留下深刻印象。是的。因此，也許只是快速擴展一下之前的幾個問題。實際上，關於提供的人工智慧工具，您能否再多談談您為這些模型使用的訓練數據，以及您從我們這裡獲取這些數據的來源，因為我們開始收到一些問題，因為整個行業中越來越多的產品從人們那裡獲取大量這些數據——您是否能夠使用合作夥伴或被許可方的數據集來交易您的模型或所有專有的數據

Yeah, I can speak to that. So yes, we've got a few experiments with that. So just so you know, like the models we've put out like [AZ], for example, which is like an ESM style model trained on our both the public data plus our internal remember we acquired like Warp Drive Bio and Radiant Genomics, [Imogen], AgBio there's always like genomic assets we've piled up over time that are actually larger than the public data set, I believe, at this point or at least comparable. We trained up on that. So that is proprietary data.

是的，我可以談論這個。是的，我們對此進行了一些實驗。所以，你知道，就像我們推出的模型，例如 [AZ]，它就像一個 ESM 風格的模型，在我們的公共數據和我們內部的數據上進行訓練，記得我們收購了 Warp Drive Bio 和 Radiant Genomics、[Imogen]、AgBio，我們總是像基因組資產一樣，隨著時間的推移要起來，實際上比公共數據集要大一點，我相信至少在這相當的時間上。我們對此進行了訓練。所以這是專有數據。

I will say like I think that market is early, right? Like we're not like the ability to go to market as just a pure model company right now in the way that like the tech company able to do on the language side, I don't think is really bearing out in the market yet.

我會說我認為市場還為時過早，對嗎？就像我們現在還沒有能力以純粹的模型公司的身份進入市場，就像科技公司在語言方面所做的那樣，我認為它還沒有真正在市場上體現。

So that served as like an appetizer to help people come in for data points to like generate their proprietary data at the large to mid-size pharmas. But like just going to market like purely as a model, I don't really see it working in the market today.

因此，這就像一道開胃菜，幫助人們獲取數據點，以便在大型到中型製藥公司產生他們的專有數據。但就像純粹作為一種模式進入市場一樣，我認為它在今天的市場上並不奏效。

Certainly, people are trying it. We tried it, but it hasn't been a big revenue driver for us yet, unfortunately.

當然，人們正在嘗試。我們嘗試過，但不幸的是，它還沒有為我們帶來很大的收入。

Okay. All right. Got you. Thanks, guys. Appreciate the time.

好的。好的。明白了。謝謝大家。珍惜時間。

Yes.

是的。

Thanks, Brendan. All right. I think that's all for tonight. Just a reminder, if you have any other questions, you can always e-mail us at investors@ginkgobioworks.com. Thanks for joining us.

謝謝，布倫丹。好的。我想今晚就這些了。提醒一下，如果您有任何其他問題，可以隨時發送電子郵件至 investors@ginkgobioworks.com。感謝您的加入。

Yeah. I appreciate all the questions, everybody. Thank you.

是的。我感謝大家提出的問題。謝謝。

Thank you. Bye.

謝謝。再見。