Good day and thank you for standing by. Welcome to the TWIS Bioscience Fiscal 2026 Fourth Quarter Financial Results Conference Call. At this time, all participants are in listen-only mode. After the speaker's presentation, there will be a question and answer session. To ask a question during the session, you will need to press star 1-1 on your telephone. You will then hear an automated message advising your hand is raised. To withdraw your question, please press star 1-1 again. Please advise that today's conference is being recorded. I'd like to hand the conference over to your first speaker today, Angela Bidding, SVP of Corporate Affairs. Please go ahead.

Thank you, operator. Good morning, everyone, and thank you for joining us to review Twist Bioscience's fiscal 2026 fourth quarter and full year results and business progress. Our earnings release is available at www.twistbioscience.com. With me today are Dr. Emily Leproust, CEO and co-founder, Dr. Patrick Finn, President and COO, and Adam Laponis, CFO. We will discuss our business progress, financial and operational performance, and growth opportunities, followed by questions. As a courtesy to others, please limit yourself to one question and then re-queue. This call is being recorded. The audio will be archived in the investor relations section of our website and available for two weeks. During today's presentation, we will make forward-looking statements within the meaning of U.S. federal securities laws. These statements generally relate to future events or future financial or operating performance. Our expectations and beliefs regarding these matters may not materialize and actual results are subject to risks and uncertainties that could cause them to differ materially from those projected. These risks include those set forth in the press release issued earlier today and those more fully described in our filings with the Securities and Exchange Commission. Our forward-looking statements are based on information available to us today, and we disclaim any obligation to update them except as required by law. We will also discuss adjusted EBITDA, a financial measure that does not conform with generally accepted accounting principles. This measure may be calculated differently from similarly titled measures used by other companies. A reconciliation of historical gap and non-gap financial measures and information about our forward-looking non-gap guidance are included in our earnings materials available in the investor relations section of our website. With that, I will turn the call over to Emily.

Thank you, Angela, and good morning, everyone. Fiscal 2026 was a pivotal year for Twist. We accelerated top-line revenue growth, delivered positive adjusted EBITDA in the fourth quarter, and expanded our capabilities for the opportunities ahead. On slide 3, we reported that fourth quarter revenue was $126.6 million, up 28% year-over-year. This is our 15th consecutive quarter of sequential growth. On slide 4, full-year revenue reached almost $460 million, up 22%, and more than $30 million above our initial 2026 guidance. Over the last three years, revenue grew at a compound annual rate of 23%, with NGS applications growing 24%, and ESPS growing 22%. Full year gross margin reached 52.4%. Fourth quarter adjusted beta was positive at $2.2 million, delivering the milestone we committed to several years ago. These results demonstrate the strength of our platform and the discipline of our team. It took years of work to build and iterate the manufacturing infrastructure we have today. And as we scale our infrastructure, we have Oslo expanded our commercial reach and now serves thousands of customers routinely. Thank you to every twister who brought us here. Crossing adjustable data break-even provides us with more options for how we run Twist. We intend to invest our profits in the capabilities, capacity, and people that can drive top-line growth moving forward. On slide 5, for those new to Twist, we write DNA on silicon. By miniaturizing the chemistry by 99.8%, we manufacture a million unique DNA sequences in parallel using a very small fraction of the materials required by traditional methods. We believe our proprietary platform gives us a structural advantage in cost, scale, and speed. This enables us to provide customization at scale for our customers. And as L-Scales becomes more personalized, we believe the need for custom manufacturing at scale grows exponentially. and who else was built for that future. A new product introduction or NPI engine drives volume onto the chip. Each launch builds on our manufacturing infrastructure, expertise and commercial reach, allowing us to serve more of our customers' workflows and enter new applications. Over the course of the last several years, through the introduction of new products, our serviceable addressable market has expanded from $2 billion to $7 billion with Line of Sight to $13 billion by 2030. Today, our solutions help customers discover medicines, develop diagnostic tests, and advance research across industries. Each new capability expands what customers can do with SWIFT. AI-enabled drug discovery is a powerful example of our NPI engine at work. Turning to slide six, I asked customers to use AI to design more molecules to explore more targets The amount of experimental work they can pursue expands. Those designs need to become physical molecules. The molecules need to be tested, and the results need to be consistent and useful enough to continuously improve model performance. TWIST brings those steps together. We manufacture our DNA, express the proteins, and then test those proteins to generate characterization data. Our role becomes more valuable as the numbers of sequences grow and the experiments become more demanding. Because every customer is different, there are many paths they can choose when pursuing AI-enabled drug discovery, and we build tools to create value across each of them. Customers can buy individual genes or pool DNA and do the experimental work themselves. They can buy protein and run their own assays, or they can use our full workflow from DNA synthesis through protein expression and characterization. All of these roads lead to Twist. There are multiple ways to access our platform. It's creating a revenue opportunity for Twist. We do not need every customer to follow the same path. Every path offers quality, speed, and scale. As AI expands what customers can design, we give them the means to build and test it. Our leadership in this market is built on the ability to execute that work at scale. It is grounded in the manufacturing platform we have spent more than a decade building and in the capabilities we continue to add on top of our strengths. In fiscal 2026, we expanded automation across the business with a particular focus on protein expression and characterization. We introduced complexity enabling us to accept the vast majority of sequences up to seven kilobases. We license the B-Body by specific technology, a robust platform conducive to our high-throughput automation capabilities. And in late October, we launched Twist X-ray Screening Antibodies, a cell-free offering that delivers proteins in as few as five days and characterization data in as few as eight business days. AI drug discovery delivered an exceptional year. orders more than doubled and revenue grew 175% from $21.5 million in fiscal 2025 to $59.1 million in fiscal 2026. Existing customers returned for repeat design, build, test, learn cycles and new customers chose Twist as their build and test partner. Our reported AI discovery revenues for both years reflect the customer we could clearly identify through their orders all stated focus on AI drug discovery. Over the last 18 months, we have seen a pattern emerge across successive customer cohorts. Customers start with a pilot order, typically from $10,000 to $100,000. They then place model building orders, often multiple millions of dollars, properly for characterization data. After digesting the data over a quarter or more, customers return to conduct actual drug discovery providing novel targets and sequences for us to build and test. These recurring discovery orders typically range from $250,000 to $1 million in iterative cycles until they have the antibodies that are ready to advance to preclinical development. Then, they start the process of discovery again with a different target. In general, the run rate revenue for a given customer exceeds model building revenue, and across the business, we believe we will see significant growth in both model building and discovery for many years to come. From conversations with customers and potential customers, we believe AI will continue to enhance how drugs are discovered. Based on the same conversations, customers believe they will need more DNA, more protein and more data to support AI drug discovery and we believe we are still early in this opportunity. Our customers' funnel continues to grow. The revenue opportunity remains robust, and we expect AI drug discovery to remain one of our fastest-growing product groups in fiscal 2027, with orders momentum accelerating throughout the year. We are seeing the durability of the customer base, with several cohorts of customers returning in a similar pattern. Our focus today is to ensure we have the capacity for the demand we expect is coming. Over the last 12 months, we increased protein and antibody manufacturing capacity by almost 200% and expanded characterization capabilities by 2 to 5 times, depending on the assay. Moving forward, we are significantly expanding capacity across our DNA, protein, and characterization workflows to support larger customer programs and capture growing demand. These investments go beyond adding equipment. We are automating the automation. Increasing throughput and improving turnaround times across the full workflow. We're also adding another characterization lab in our existing Oregon facility as we continue to expand capacity to stay ahead of customer demand. For many of our characterization assets, this means another 5x capacity expansion versus where we existed fiscal 2026, giving us the ability to go with existing customers, serve new customers, and convert demand into revenue. Turning to slide 7, nucleic acid therapeutics exemplify another large opportunity to expand our platform. These therapies use DNA or RNA to achieve a therapeutic effect. Researchers working on mRNA, antisensory nucleotide, and small interfering RNA need to make and evaluate hundreds of thousands to millions of unique sequences. That plays directly to our strength of customization at scale. Personalized cancer therapy illustrates the potential. In one approach and development, researchers identify mutations in a patient's tumor and design mRNA therapeutic sequences intended to help the immune system recognize and attack their unique cancer. Each patient needs many different sequences. Producing those sequences at scale with consistent quality and traceability for our customers who delivered those therapies to patients is directly in line with the challenges to which it was built to address. We already supplied DNA templates and siRNA for selected customers, including DNA used in investigational therapies being evaluated in clinical trials. And in fiscal 2026, we expanded complex genes and research-grade DNA preparation options to support more demanding preclinical work, which is the underlying input for advanced mRNA therapeutics. Supplying the materials for companies developing mRNA therapeutics is a natural next step. Today, we offer research-grade mRNA to selected customers through early access, with a high throughput offering in development. For personalized cancer therapies to reach millions of patients, manufacturing must become faster, more efficient, and more affordable. Our ambition is to bring the economics of our platform to this emerging market, supplying the molecules and manufacturing capabilities our customers need. We are building this opportunity in stages. Early clinical programs generate modest revenue, but supporting customers now positions us to grow with them when their therapies advance, just as we did in liquid biopsy. This is a medium to long-term opportunity, and we believe that we do not need a material contribution from nucleic acid therapeutics to deliver our growth in the coming years. Slide 8 NGS is delivering strong growth today. Fourth quarter revenue grew 24% year-over-year and 6% sequentially, driven by diagnostic customers. Two weeks ago, we launched MRD Express commercially, and we are seeing strong interest in this unique and important product. We expect MRD Express to drive growth next year and beyond. To take a step back, molecular residual disease, or MRD, refers to traces of cancer that remain after treatment. Tumor-naive MRV tests use shared cancer biomarker associated with a particular cancer, and the same panel of biomarker will be used to monitor all people with the same type of cancer. We serve many customers that use our panels within their tumor-naive assays. Where Twist further differentiates itself is in the supplying panels for tumor-informed tests. Because tumor DNA varies from person to person, tumor-informed MRD assays use these unique tumor signatures to create a personalized panel that is then used to monitor for recurrence. As you can imagine, sensitivity is a key focus for our customers developing these tests. Recent studies demonstrated that tests, including thousands of probes, result in increased sensitivity, and we believe thousands of variants will be necessary to drive success in the broader market over time. We have a future in which our customers' MRD testing reaches millions of assays each year. We think that demand requires individualized panels at a normal scale, building directly on our ability to manufacture millions of unique DNA sequences in parallel. For this market, we are also building ahead of the demand we are seeing, providing security for our customer supply chain at this scale. In addition to MRD, Our sequencer-agnostic NGS portfolio spans different target enrichment, laboratory preparation, and other sequencing components. In fiscal 2026, we introduced laboratory preparation solutions for all genome sequencing applications, including rare disease and population genetics. This prior group is growing rapidly. Turning to slide 9, we raised approximately $425 million in net proceeds through an equity offering and at the market sales. This capital gives us flexibility to expand AI discovery characterization capabilities, prepare for MRD growth, and act on emerging opportunities. Moving forward, we will apply the discipline that brought us to positive adjusted EBITDA and invest ahead of demand, improve efficiency, and build capabilities that can generate attractive returns while remaining adjusted EBITDA positive. We have shown that we can build new capabilities and turn them into growth, as we have with antibiotic characterization and data. Next, today we'll discuss how we are expanding capacity and improving the speed and efficiency of our workflows.

Thanks Emily, and good morning everyone. Our customers want to test more sequences, explore more complex molecules, and move programs faster. Our job is to deliver the right molecule with the right quality on time, then do it again at greater scale. On slide 10 in fiscal 2026, we expanded capacity across DNA synthesis, protein solutions, and NGS through automation and capital investment ahead of demand. We are connecting production steps and strengthening digital systems to process thousands of different proteins and generate tens of thousands of data points every day. In fiscal 2026, we introduced approximately 30 automated systems and workflows, increasing throughput and speed across protein expression, antibody characterization, MRD and NGS. We bring capacity online in stages, guided by customer demand to shorten the time from a customer's design to their next informed decision. We have capacity available to serve additional customers today and we're investing now to support the larger, more complex programs we see ahead. Our strong balance sheet allows us to invest in CapEx to support multiple areas of opportunity across the business. And in many cases, this is an investment in specialized instruments. And while it's relatively easy to add equipment for automation, buying an instrument is only the beginning. The real work begins by designing the efficient processes Engineering the connections between machines and writing the software that makes the workflows operate reliably at scale. We have spent the last decade building our team that designed the processes, connects the equipment, and enabled proprietary software to allow operators working around the clock to operate sophisticated machines consistently, improving the efficiency and speed. We're always driving to increase speed, efficiency and economics, and our experience in automation engineering provides added differentiation from our peers. Today, we have 10 DNA writers operating, with two installations planned in the months ahead and four more on order. With all 16 operating, we will have capacity to manufacture more than 50 million pieces of DNA daily, supporting AI drug discovery, nucleic acid therapeutics, MRD and other applications. On slide 11, MRD Express puts that capacity to work. Each panel is designed around individual tumors variants with consistent requirements for quality, reproducibility and speed. This is precisely the challenge our platform was built to address. Across these markets, we're adding capacity ahead of demand and making existing capacity more productive. Customers gain faster delivery and the ability to bring us more of their workflow. Twist gains opportunity to grow revenue and improve manufacturing efficiency. Delivering for customers today and building for the next challenge is how we earn repeat business and how we operate as a supply chain partner that can keep pace as programs grow in volume and complexity. With that, I'll turn the call over to Adam.

Thank you, Paddy. On slide 12, we accelerated growth Revenue for the fourth quarter was $126.6 million, compared with $99 million in the fourth quarter of fiscal 2025, an increase of 28% year-over-year and 7% sequentially. For the full year, revenue was $459.4 million, compared with $376.6 million in fiscal 25, growth of 22%. On slide 13, DNA synthesis and protein solutions revenue was $61 million in the fourth quarter, up 33% year-over-year and 8% sequentially. Full-year revenue was $221.9 million, up 32%, reflecting therapeutic growth and adoption of our broader DNA protein and characterization capabilities. We shipped 401,000 genes in the fourth quarter and approximately 1.3 million for the full year. We also manufactured genes used internally to produce proteins and characterization data. Year over year, annual gene ship volume grew 43%, while volumes used internally more than doubled. Both categories support AI drug discovery and other applications generating revenue through gene sales or the proteins, data, and discovery services we deliver. On slide 14, NGS applications returned to growth above 20%, consistent with our guidance in February. Fourth quarter revenue was $65.7 million, up 24% year-over-year and 6% sequentially, driven by diagnostic customers. Full year revenue was $237.5 million, up 14%. Our top 10 NGS applications customers accounted for approximately 40% of NGS applications revenue in the quarter. We served over 700 NGS applications customers, including 190 customers adopting our products. On slide 15, looking at revenue by industry. Therapeutics revenue was $43.9 million in the quarter. Full year revenue grew by $51.8 million to $162.3 million, up 47%. This includes $59.1 million from AI drug discovery customers, an increase of $37.6 million, or 175% over fiscal 2025. All of this revenue sits inside our therapeutics line, with therapeutics growing well above the company average this year. Our reported AI revenue captures only what we can clearly categorize as AI. We know that traditional drug discovery, pharma, and biotech customers are also adding AI programs alongside their traditional approaches. As we move forward, drawing a clear distinction will become much more difficult. Diagnostics revenue was $45.2 million in the quarter, growth of 23%, and $154.3 million for the full year, growth of 13%. Academic and government revenue was $16.1 million in the quarter, an increase of 21%. For the year, revenue grew 13% to $56.6 million. Industry and applied revenue was $6.6 million in the quarter, growth of 12%. Full year revenue was $24.2 million. Global supply partner revenue was $15 million in the quarter, an increase of 18%. And $52 million for the year, growth of 13%. On slide 16, Geographically, America's revenue was $78.8 million in the fourth quarter, an increase of 38% year-over-year. EMEA revenue was $38.7 million, growth of 12%, and APAC revenue was $9.2 million, growth of 28%. Turning to slide 17. Fourth quarter gross margin was 53.1%, compared with 51.3% a year ago. Full year gross margin was 52.4%, Operating expenses excluding cost to revenue were $91.7 million for the fourth quarter and $380.3 million for the full year. Our fiscal 2026 investments supported commercial execution, digital infrastructure, and expanded capabilities across the business. On slide 18, adjusted EBITDA was positive $2.2 million in the fourth quarter. For the year, adjusted EBITDA was a loss of $35.9 million. Capital expenditures were approximately $20 million, including tenant improvements in the fourth quarter and $48 million for the full year. As Patty discussed, this spending supports expanded characterization capabilities, automation, and additional DNA writers. Turning to slide 19, we ended fiscal 2026 with $582 million in cash, cash equivalents, and short-term investments. This includes $424.8 million and aggregate net proceeds from our public offering and at-the-market program. Over fiscal 2027 and fiscal 2028, we expect approximately $150 million in capital expenditures for capacity, automation and software, plus more than $30 million in landlord-funded tenant improvements. We anticipate these planned investments will expand our long-term capacity to support more than $1 billion in annual revenue within our existing facilities at scale. We will fade deployment ahead of the demand we see coming. Turning to slide 20, we enter fiscal 2027 with strong momentum across DSPS and NGS and clear visibility into our first quarter outlook. AI drug discovery, oncology diagnostics, academic and government customers, and new products give us multiple drivers of sustained growth. Our capacity and automation investments position us to capture demand and improve productivity as volumes scale. The pace of margin expansion reflects depreciation and manufacturing costs as new capacity comes online before reaching planned utilization, partially offset by productivity improvements. These investments expand the revenue capacity of our existing facilities and improve productivity as volume grows. Over fiscal 2027, margin outlook includes the cost of bringing that capacity online. The combination of commercial momentum broader capabilities, and disciplined investment supports our revenue growth outlook above 20% in fiscal 2027. Consistent with our historical approach, we have built our initial outlook around the demand and delivery timing we have a high degree of confidence in converting to revenue during the year. For fiscal 2027, we expect total revenue of $550 million to $560 million, representing growth of approximately 21% at the midpoint. Our initial full-year revenue guidance assumes $100 million in AI drug discovery revenue. This reflects the customer programs, lead funnel and delivery schedules we can forecast with a high degree of confidence today. We see additional opportunities in expanding programs with both existing customers and new customer programs that are not fully reflected in our initial full-year guidance. We expect sequential growth in DNA synthesis and protein solutions and NGS applications throughout the year. Gross margin of approximately 52.5% to 53%. Positive adjusted EBITDA for the full year. Capital expenditures of approximately $75 million as part of our two-year investment plan, excluding landlord-funded tenant improvements. For the first quarter of fiscal 2027, we expect revenue of $130 million to $132 million, representing growth of approximately and NGS, with each product group growing about 25% year-over-year. With that, I'll turn the call back to Emily.

Thank you, Adam. On slide 21, we measure progress in revenue growth, growth margin and adjusted beta. In fiscal 2026, we grew revenue 22%, expanded growth margin and delivered positive adjusted beta in the first quarter. Moving forward, we are building on that strong foundation. A twist We make our own weather. We grew through COVID. We grew academic revenue when funding was under pressure. We expanded our biotech customer base when capital was scarce. Our diversity across products, markets, and customers gives us resilience and multiple ways to grow. We believe healthcare is moving towards personalized diagnosis, treatment, and monitoring. AI is accelerating what customers can design, turning those designs into millions of unique molecules With consistent quality is the next challenge. Twist was built to deliver a customized solution at scale. To provide an analogy, making spaghetti for two is easy. Now imagine a million people placing a million different orders. Every dish has to be right. Every plate has to arrive on time. Delivering that takes an entirely different system designed for customization from the start. That is the challenge we build trees to solve in biology. Our platform and automation makes custom at scale possible. As healthcare becomes more personalized, the world will need millions of unique molecules made reliably and efficiently. We are building the infrastructure for that future. We bring startup energy and enterprise discipline to everything we do. We move fast, stay close to customers, and turn emerging needs into new capabilities. We hold ourselves accountable for the quality, reliability, and scale our customers depend on. We build twists for where biology is going. We have the platform, the people, and the capital to lead. Now, we intend to turn that advantage into sustained growth. We are just getting started. Operator, please open the call for questions.

Thank you. At this time, we'll conduct a question and answer session. As a reminder to ask a question, you'll need to press star 11 on your telephone and wait for your name to be announced. To withdraw your question, please press star 11 again. Please limit yourself to one question. Please stand by while we compile the Q&A roster. And our first question comes from Sabun Nambi of Google IAM. Your line is now open.

Hey, guys. Good morning. Thank you for taking my question. AI revenue exceeded initial expectation in 2026. You guided 200 million for 2027, which is the same number you've been talking about for a while. But now it's off of a higher base, I believe approximately 60 million. With this in mind, I have a few questions. Yes, your revenue target is impressive, and it's still robust growth, but it's a moderation, especially given how you have described the market opportunity. Why would growth moderate? Do the error bars skew to the upside? How much of this is accounted for in backlog? And can you speak to the order growth? Thank you so much.

Yeah, thanks, thanks, Subbu, for the question. Indeed, we see the growth accelerating for the business. In Q1, we had a 17% revenue growth, 19% in Q2, 23% in Q3, and now 28% in Q4. So I think as a business, we're doing well. We are very confident in the potential for us to achieve a triple-digit percentage order growth in fiscal 2027 for AI drug discovery and also convert more orders into revenue within the year. And you're right that our initial guidance is for $100 million in AI drug discovery revenue. And those are and so on. We see that there is meaningful upside on top of that assumption and really there are two things for us to do. The first one is to add more capacity. That part of the business is growing really fast and keeping ahead of the demand is key so it's totally now in our control. And then the second is to add workflows. In Android Discovery, same as in traditional Android Discovery, not everybody wants to do the same thing. And so, for instance, two weeks ago, we've added a cell-free workflow. And that's an example of an expanded workflow for us. We really like the cell-free. It's a better margin for us. It's faster for customers. And then we have a unique advantage where we're the only ones to be able to do cell-free for longer protein, such as IgG, where others are limited to mini-bino and DHH. This is the guide that we have high confidence in today, but there's a lot of upside on top of it.

Thank you. One moment for our next question. Our next question comes from the line of Matt Gattop of Stevens. The line is now open.

Hey, good morning, and thank you for taking my questions. Maybe following up on Subbu's question, you know, Given the AI expectations, or at least the AI print for FY26 and the expectations for FY27, I think it would suggest that you're expecting roughly mid-single-digit growth in the underlying DSDS business. So can you just speak to the underlying characteristics of that market?

Thank you. Yeah, so I think the characteristics of the The AI business that we're saying is that, first of all, it works. The quality of the binding data, the quality of the developability data that our customers' models are producing is on par with what you can get with in vivo, in vitro. And so the science is working. We are seeing that, yes, people come first with model building, which is great. But then they are converting to true drug discovery programs where they declare a target. And then they go through the discovery process and move to preclinical development and come back with another target. And that business, that run rate business is very sustainable. It's bigger than the initial model building and so we can see that it's a business for the long term. The other characteristic that we are seeing is that people want more and more different ways of doing drug discovery. Even within one company, they may have started with arrayed drug discovery where They're getting one sequence per tube, and they get one data point for each well. And there's still a lot of demand for that, but we're also seeing customers saying, you know, we need to grow the number of data points. that we can study, and the price per data point has to drop. And those customers, they're very much looking for ways to do what we call pooled discovery. So instead of having one sequence in one well, now you have thousands, hundreds of thousands, maybe millions of different sequences in one well, in one tube. And that's a really great match for us in how we make our DNA. So we've solved the making of the DNA and the protein, but then you have to characterize each of those and you have to go do pool discovery. So we're seeing extension of the workflows in that direction. Another characteristic, and maybe I'll stop there, is we're also seeing that, of course, the AI-native logistics companies, they are moving at a very fast clip, but we're seeing more and more people getting into it. where maybe a year ago it was just a few companies and maybe there were some questions as to whether the science would work. I think now in companies that were doing traditional drug discovery we see more and more of excitement about AI. So definitely a great time for us to be in business. It's great that... We are one of the leaders and it's a perfect match for the platform that we have. We are very much looking for continued growth in this coming year.

Thank you. One moment for our next question. Our next question comes from the line of Brandon Smith of TV Commonwealth. Your line is now open. Brendan, your line is not open. Can you unmute? One moment for our next question. Our next question comes from the line of Doug Senkel of UBS. Your line is not open.

Good morning, everyone. Thank you for taking my question. So you guided to around $100 million of revenue growth year over year in fiscal 27. Around $40 million of this is attributed to AI as you guided to, I think about 67% growth there. What drives the other $60 million? How much is mRNA? How much is liquid biopsy? How much is biopharma excluding AI? And how much is traditional synbiome?

Yeah, Adam, do you want to take us through those numbers?

No, absolutely. Doug, great to hear you. Thank you for the question. When we look at the overall business year over year, excluding AI drug discovery, we're seeing the actual total growth of the business accelerate. We're really excited to see NGS be above 20% in Q4. You know, we guided that back in February, and to be at 24% in Q4, it feels good. and we see that continued momentum in the business in NGS. We also recognize on the DSPS side of the business, particularly in therapeutics, many of our customers who are shifting towards AI drug discovery and many of our reps are focusing on the hypergrowth that's happening in AI drug discovery. So that does have an impact on the pace of growth elsewhere, but we are forecasting to be still over double-digit growth for the rest of the business outside of AI drug discovery this year and actually seeing that growth accelerate year on year. So really excited to be there. And again, we'll continue to provide updates as the year continues.

Thank you. We'll move on to our next question. Our next question comes from Vijay Kumar of Evercore. Your line is now open.

Hi Emily, good morning and thank you for taking my question. I guess one on this AI topic, you know, back when the CQ call, you noted you continue to expect triple-digit order growth in fiscal 27 as well. And I, you know, I think Adam made a comment about it's going to become increasingly difficult because traditional pharma customers are ordering and it's going to be hard to delineate, you know, AI revenues from traditional pharma. One, are you still expecting triple-digit AI order growth in fiscal 27? And the comment that Adam made, will you be disclosing AI numbers going forward? And sorry, the last one, you mentioned sources of upside, if you could just elaborate on them. Thank you.

Yeah, we are committed to sharing AI revenue through 27. who always want to be as transparent as we can with our investors without tipping our competition too much. That's the fine line we're doing. And as Adam mentioned, yes, it's getting harder for us to know when there is a previously traditional drugs group whether they switch to AI or not. I think in all of us, in all of our lives, we're using AI more and more and more and the boundary becomes blurred. But what we'll do is report AI drug discovery for groups that we're sure they're doing AI and maybe it's a little bit undercounted. But that's what we will do. In terms of upside, there's a lot of levels for us to push. There's the level of first finding more customers. Another level is launch more workflows to capture more wallet share of customers. The sell-free launch is one example of that a couple of weeks ago. And then when we launched the MRD Express, that's the opportunity to push over the fence customers that maybe would want to do the MRD our way with thousands of probes. but waiting five days for a bespoke panel while five days is actually quite amazing to ship thousands of probes for thousands of customers at once. Actually, we've heard from customers that actually five days, that was too long. And so that's why we rose to the challenge and developed a process that could do it in 24 hours. So that's and another lever for us. And then we probably have a few more surprises along the way that, again, we don't want to keep our competitors, but our NPI engine is really productive. And now that we've turned as a CBTA breakeven, we'll be able to reinvest our profit. I think we're going to become even more of a dendrous animal.

Thank you. One moment for our next question. Our next question comes from your line is now open.

Yeah, hi, Emily and team. Thanks for taking my question. Look, you have a number of growth drivers, but clearly that's one that's come up front is AI and obviously a big part of the conversation, just given what that intelligence can actually do for drug discovery and the good in the world. So, you know, I mean, I'm hearing from you that you have significant demand coming That's very clear. You're building CapEx. You're getting writers. You're building lab automation quickly. But look, you just did 175% growth in AI revenues. You're projecting somewhere just shy of 70% growth for FY27 and revenue for AI. But your order growth, the triple-digit order growth, I hear you. You are, again, validating that. But I'm just trying to understand, is there some dynamic here in terms of revenue versus order timing? Is there anything that we need to keep in mind with respect to the conversion of those revenues from orders to revenues that's giving you sort of the 70%, nearly 70% growth versus the triple digit growth in revenue itself? And maybe just last part of it, if I could, What does triple digit growth in orders mean? Is that somewhere like really north of 100%? Is this 200%? Can you put a number to it? I appreciate the comments here. Thank you.

Thank you, Puneet. There's no end to the dynamics between orders and revenue and that's why we try to clean up and I give the revenue number for both 25 and 26 to make it very clear. And so by triple digit percent growth, we mean triple digit percent growth. So last year we had 175%, right? Yes, this year... What we can take to the bank today, guaranteed, is $100 million. And we also see a lot of upside. Some of that upside, if we want to realize it, we need to have the capacity. And so that's great. It's in our hands. And so we remain confident that we will be able to to deliver triple-digit percentage growth in orders and revenue for fiscal 27. But today, the forecast with high confidence today is $100 million, with more to come. As you know, us, over many years, we now have had 15 consecutive quarters of revenue growth. And we strive to absolutely crush every quarter. And here we think that we are set up for that.

Thank you. One moment for our next question. Our next question comes from the line of Matt LaRue of William Blair. It is now open.

Hi, good morning, everyone. I wanted to ask on the planned investments for capacity, you know, obviously a big step up over the next couple of years is help us understand what the mix of sort of expanded scale of existing capabilities versus the CapEx that's dedicated to new capabilities. And given that you're making kind of this scale of investments Right now, it might be helpful to understand how the breadth of ordering is on AI. I guess what I mean is, you know, how many companies you're able to classify as truly making AI orders this year versus last versus the order funnel now. Again, just to kind of get a sense of what you're seeing that supports your decision to make all these investments.

Thank you. Paddy, you want to take that one?

Yeah, I've got that. Excuse me. Hey Matt, thanks for the question. Good to hear you. I mean, you know, if we start at the top, you know, I think I said in the comments that adding the fundamental writer capacity, it's a great place to start. And, you know, we're going from something in the order of 32 million oligonucleotides or building blocks per day to going north of 50 million oligonucleotides every single day, which is absolutely incredible capacity. and when you move downstream from the DNA synthesis platform, I think what we showed in slide 10 was really balanced and disciplined deployment capital. NGS customer growth in the applications continues to go up, you know, in the way that we understand the market and the knowledge we have of our customers. We're making sure that we're ahead of that demand. And things like MRD Express and tumor-informed The AI Drug Discovery Opportunity What we can see there is we're meeting our customers where they're at. We'll deliver DNA, protein data, whatever it is that we need, and we're really starting to understand what that demand is over time. And so in driving into that opportunity, we're adding capacity to deliver multiple thousands of proteins and antibodies every day, and then obviously multiples of that number of data points per day. And as we understand the customer demand and needs, we're obviously investing to get ahead of that. That's where we stand right now.

And to build on what Patrick said, that capacity has been coming. We've been deploying it, we've been talking about capacity, and that's why we did the fundraising in the summer. So the plan, the trends are on track.

Thank you. One moment for our next question. Our next question comes from Matt Stanton of Jefferies. Your line is now open.

Thanks. Maybe on MRD, how should we think about the ability for that to accelerate here into 2027? I think it added a point or two in 26. You have new programs launching, next-gen assays, new products with MRD Express. How should we think about the ability for MRD to accelerate here into 27 than any finer point in terms of what the guide contemplates for a contribution from Thank you for the question. When you look at what we did in 2026, we guided to one to two points of growth from MRD. We definitely delivered on those expectations, but we're seeing significant growth from MRD in terms of percent growth, but it's really early days in that commercial adoption, so it's a bit of a lot of small numbers. of the growth rate in 2025 to 2026. We don't expect the growth rate as a percentage to slow. So the dollar growth continues to expand more rapidly as we go into 27 for MRD. And we see that potential not just for 27, but 28 and beyond. And as Patty mentioned, some of the investments we're making today, things like new riders, those things take 12 to 18 months to install and build out. So we're building not just for the capacity Thank you.

One moment for our next question. Our next question comes from the line of David Westenberg of Piper Sandler. Your line is now open.

All right. Thanks for taking the question and congrats on the good quarter here. So DNA synthesis and protein solutions grew at 33%. Well, gene shift grew even faster. Can you talk about how that was reflected in Mix in terms of AI customers versus traditional customers, protein versus genes here, and how should we think about pricing over the next few years here? And I'm going to be a bad boy and slip in a second one, but on the AI revenue characterization, can you give us just a few details about how you're categorizing it? Is it like... The project they're telling you about, are they specifically telling you it's AI? I just want to get a little bit more color on how you're going to characterize it and go for a basis because you said it is difficult. Anyway, sorry if you answered that and that went over my head, but thank you.

Yes, thanks for the question. The volume of genes is going up. It's growing, yeah, we love it. It's just growing very, very fast. And you're right that the gene volume is growing faster than the revenue, and that is because we price the base. And there's broadly two big categories of genes. One of the genes that encode for protein, those are big, average 1,500 bases, and genes that encode for antibodies, and those are small, about 600 to 800 bases. And since we price per base, while both categories are growing, the category for human antibodies is just growing way, way faster. And so there's a mix shift, but it just reflects that We're doing well on protein and we are doing really well on antibodies. As far as the characterization of the revenue, maybe to reiterate, if it's an AI company, if it's a native AI drug discovery company, that's easy. If they purchase data, that's easy to put in the AI bucket. I'm sure that there are customers that buy DNA from us or IGD from us that are derived from AI and we don't know. We don't really care. We care about the revenue growth, the growth margin, and the profitability.

Thank you. One moment for our next question. Our next question comes from the line of Kyle Mixon of Canaccord January. Your line is now open.

Yeah, hey guys, thanks for the questions. Congrats on the progress. So if we assume you double revenue by 2031, fiscal 31, like you said at the investor day, and then you kind of grow the core low doubles, you know, low teams, I guess, and it kind of implies AI revenue of only 200 million by fiscal 31. So it kind of raises the question of how long this AI revenue tail lasts. Are you thinking about that, you know, the capacity and the demand among pharma and frontier labs amid the risk that these entities start their own AI web lab work as well? Thanks.

We think it's long-lasting, just the science works, right? And the science is broad-based. If you look back at cell and gene therapies, maybe everybody was working on one target. In this case, it's just broad-based. We think it's going to last. And yeah, maybe some customers will build their own lab. That's totally fine with us. They're going to need proteins. They're going to need DNA. And all roads have to go through twist. So we don't see that as a problem. That's a feature of the twist approach is we provide a variable menu and we'll meet our customers where they are.

Thank you. One moment for our next question. Our next question comes from the line of Luke Sergar of Barclays. Your line is now open.

Great. Thanks for the question. I want to ask one on the AI and then I want to touch on MRNA. So on the AI side, you're doing the build out. You talked about having a little bit of upside there from your $100 million in orders and revenue. You know, is that contingent on capacity coming on in the back half? And then on the mRNA side, you guys talked about this being a bigger opportunity to you guys than the potential size of the AI piece. Can you just kind of give us a quick, you know, where you fit within that workflow, how you're fitting now, like where that's going, what the revenues are now, and like what's embedded in 27?

Yes, very little is embedded in 27. Right now we are servicing the clinical trials that are ongoing and so you can look, it's not a lot of patients. The opportunity for us is once those trials are completed and then medicine is being delivered personally to millions of people, that's when someone will have to make the DNA So we want that to be us. Someone will have to convert that into RNA, and that may be us, or that may be the customers who are open to all options. And so it's a longer-term opportunity for us, but that's what we do well at Twist, is we plant seed now for the future. And then on AI, yes, capacity is being added every week. So we have a very active program. It's a well-oiled machine. And as we add capacity, we unleash our sales team to go sell it.

Thank you. One moment for our next question. Our next question comes from the line of Robert Bamberger of Baird. The line is now open.

Yeah, thanks for taking my question. Just on gross margins, at the midpoint, fiscal 2027 adds about $96 million of revenue and $52 million of gross profit, so about 55% incremental gross profit conversion there.

So how do we bridge that to the 75% to 80% underlying contribution framework you've discussed in the past?

And then with that investment program running through fiscal 2028, will it take until fiscal 2029 for reported incrementals to get back toward that level, or can they recover sooner than that? Adam? No, happy to take the question. So we've talked a lot about the 75% to 80% drop through, and that doesn't change. And we've achieved that benchmark since opening the Fact of the Future in Portland, and that still holds across both DSPS and NGS as we look. In 2027, as I mentioned in the call, we expect to invest about $75 million in CapEx for the capacity expansion and automation ahead of demand. That represents approximately $15 million per year of depreciation on that, or about two to three points of gross margin headwind, which we expect to offset from the drop through revenue in 2027. We do expect to continue to see gross margin expansion in 2027, just not at the same pace as we've seen in priors. And so as the business matures, we continue to see a path to a 60% gross margin in the future. That said, we're really managing the business to maximize the gross profit dollars the business We talk about making sure we'd rather run a $2 billion business at a 50% gross margin than a $1 billion business at a 60% gross margin. So as we move forward, the commitment to remain adjusted EBITDA positive and not go backwards on gross margin is there, but really we're focused on making sure we optimize the revenue growth and the gross profit dollars. Thank you.

Thank you. One moment for our next question. Our next question comes from the line of Brandon Smith of TD County. Would you guys now open?

Great. Apologies for the audio lapse earlier, guys, but thanks for looking me back in. I wanted to ask one more on DSPS. And apologies if I missed it, but are you able to actually confirm how many customers fall into that AI data orders bucket at this point and really what the mix of that base is specifically? I'm really trying to understand If that's exclusively kind of a couple of AI needed biotechs in a frontier lab, or if you're actually seeing kind of in real time expansion of that customer bucket in a material way. And I guess within your assumptions for next year, how many customers do you expect to be kind of placing those AI orders of the course of 27? And, you know, really trying to unpack like, you know, how much of the growth next year is coming from existing customers placing more data orders versus like biotech and pharma customers now placing those increasingly too and adding to that bucket. So just any color on the growth breakdown would be great. Thanks.

Adam? Yeah, no, happy to. So, Brian, what we're seeing is every, as Emily mentioned in the call, every one of those cohorts as we move over the last 18 months, an expansion of the number of customers engaging in AI drug discovery. It started off, you know, some of it was in big pharma, some of it was in native AI discovery, and then it's moved on and progressed. We've added even some of the Magnificent 7 and some of the larger hyperscalers to the mix. But the mix predominantly relies on customers that, A, we've had in the past, and B, who are focused on drug discovery, not just the tech companies. So we see that customer group expanding over time. We've seen it expand sequentially almost every quarter since we started. And as we look forward, we expect that to expand. We talked last year about being dozens of customers So there is some degree of concentration, but we see that continuing to diffuse as the more and more folks are turning to AI drug discovery as part of their workflows.

Thank you. This concludes the question and answer session. I'll now turn it back to Emily Leproust, CEO and co-founder, for closing remarks.

Thank you for joining us. We have a history of turning ambitious goals into results, and this year was another proof point. Our ambitions for TWIS keep growing. and so does our ABD team to deliver. Thank you.

Thank you for your participation in today's conference. To conclude the program we now disconnect.