10x Genomics, Inc.

Hello, everyone. Thank you for joining us, and welcome to the 10x Genomics second quarter 2026 earnings conference call. After today's prepared remarks, we will host a question and answer session. If you would like to ask a question, please press star 1 to raise your hand. To withdraw your question, press star 1 again. I will now hand the conference over to Cassie Corneau, Head of Investor Relations and Strategic Finance. Please go ahead.

Thank you, and good afternoon, everyone. Earlier today, 10x Genomics released financial results for the second quarter ended June 30th, 2026. If you have not received this news release or would like to be added to the company's distribution list, please send an email to investors at 10xgenomics.com. An archived webcast of this call will be available on the investor tab of the company's website, 10xgenomics.com, for at least 45 days following this call. Thank you so much for joining us today. and factors that could cause results to differ appears in the press release 10x Genomics issued today and in the documents and reports filed by 10x Genomics from time to time with the Securities and Exchange Commission. 10x Genomics disclaims any intention or obligation to update or revise any financial projections or forward-looking statements, whether because of new information, future events or otherwise. Joining the call today are Serge Saxonov, our CEO and co-founder, and Adam Taich, our chief financial officer. We will host a question and answer session after our prepared remarks. We ask analysts to please keep to one question so that we may accommodate everyone in the queue. With that, I will now turn the call over to Serge.

Thanks, Cassie, and good afternoon, everyone. I will start with a brief overview of our second quarter performance. Then provide an update on Atera. And finally, discuss several broader trends that are reshaping biological research and creating new opportunities for our business. Revenue for the second quarter was $151 million. During the quarter, we recognized $1.6 million of licensed and royalty revenue in connection with our settlement with Takara. Excluding non-recurring settlement revenue in both this quarter and the prior year period, Q2 revenue was $149 million and grew 3% year over year. The story of the quarter was the extraordinary customer response to Atera. We're highly encouraged by the engagement across the research ecosystem and the very strong early order flow. At the same time, our on-market products showed sustained strength. withdrew of robust growth in chromium consumable reaction volumes, reflecting expanding usage across a broad range of applications. In spatial, Xenium utilization continued to perform exceptionally well, reinforcing its position as the leading platform for spatial analysis today. Our launch of Atera is still, by far, the biggest highlight of the year. On our last call, I discussed Atera's core capabilities, many of which were not thought possible within a single platform. It delivers step-change advances across a range of features, including throughput, Plex, and sensitivity. Atera enables spatial whole-transcriptome profiling with single-cell sensitivity at scale, The promise of spatial has always been that it represents the convergence of molecular, cell, and tissue biology. ATERA is poised to deliver on that promise to provide researchers with a fundamentally more complete view of biological systems and answers to many questions that were previously out of reach. You may remember that we said initial customer reception exceeded our expectations. which were already very high heading into the launch. Since then, customer enthusiasm has only gotten stronger. This has translated into a strikingly large number of orders in a very short amount of time. The momentum we're seeing is remarkable for a platform that was completely unknown to our customers only a few months ago. We believe customers' enthusiasm should only increase as they learn more about the system and see what it is able to deliver in their hands. Similarly, we're seeing strong demand for Catalyst Research Services, a program for customers to submit their own samples to be run on ATERA in our lab. We expect sample processing to begin alongside ATERA's commercial availability. Catalyst Research Services is designed to support a range of customer needs, from generating initial pilot datasets to providing flexible and ongoing access for routine research to enabling researchers who do not yet have access to an ATERA instrument. The strong demand for the service is another encouraging leading indicator for the future of the platform and the breadth of its impact. Our vision for Atera was to build the cornerstone platform that enables scientists to interrogate a full spectrum of research questions with the versatility and scale needed to resolve the complexity of biology. It is gratifying to see that vision start to come to life as customers describe how they plan to use Atera. We're seeing engagement from universities, academic medical centers, and biopharma companies pursuing research across nearly every major disease area, from oncology across dozens of tumor types to neurodegeneration, autoimmune and inflammatory disease, cardiometabolic conditions, kidney transplant biology. The list goes on. That diversity is also evident in the specific research questions being asked. Customers are interested in applying the platform for foundational cell and tissue atlasing, mechanistic studies of how disease actually develops, monitoring response to novel immunotherapies and cell therapies, and for early biomarker and translational work. Just as importantly, customers are planning to integrate Atera into the routine fabric of their research. Researchers within academic medical centers, for instance, are planning to deploy it across the entirety of their translational oncology programs. We're hearing similar conviction from industry, where senior R&D leaders at top biopharmaceutical companies are investing in Atera with the belief that spatial biology will fundamentally change how they approach drug discovery and development. We built ATERA as a long-duration, upgradable platform with capabilities that will continue to expand over time. ATERA's extensive roadmap includes workflow automation, base-by-base spatial sequencing, and the addition of protein multiomics. With that in mind, during the quarter, we took an important step to enhance our proteomics capabilities with the acquisition of Protein Tech Genomics. Protein Tech Genomics brings deep expertise and differentiated technologies for measuring proteins in multi-omic context. We believe integrating rich proteomic information alongside spatial transcriptomics will further expand the biological questions ATERA can address and continue to strengthen the platform. The intensity of the early interest and the spectrum of customer applications are reinforcing our conviction that Atera is poised to transform how we measure and understand biology. When you look back at the history of our industry, every now and again, a new platform comes along that reshapes markets and changes how science is done. This is a very rare but profoundly exciting occurrence. We built Atera with exactly that ambition, and the early signs suggest it is on that trajectory. Turning to single-cell, I want to highlight a few major trends driving the business. First, our customers are adopting our platforms for larger, more ambitious studies. Over the past several quarters, products like Flex Apex have enabled a new generation of this work, particularly in biopharma and translational research. One way we're supporting the shift is through our recently introduced whole blood workflows that stabilize samples at the point of collection, enabling longitudinal research, distributed sample acquisition, and access to archived material. Second, there's a growing interest in additional modalities and multiomics, an area that has always been a strength of our portfolio and a focus of our investments. Last quarter was a particularly great example. We launched a new GemX version of our Multium product, significantly improving researchers' ability to measure epigenetics and gene expression from the same cell. This unlocks new dimensions of biological context and has been met with positive early customer response. Furthermore, our protein tech genomics acquisition expands and complements our existing multi-omics capabilities. It provides us with the largest single-cell protein panels on the market and allows us to offer more complete solutions for customers to measure gene expression and proteins on the same cell. Finally, a significant trend in single-cell has been an increase in large-scale perturbation experiments to map biological mechanisms and resolve causality. We're finding that Flex Apex is becoming the standard assay for these experiments because of its scalability, robustness, and sensitivity. While we see significant Flex Apex adoption across all customer segments, the uptake of Apex in Biopharma has been particularly strong, driven by the application of perturbation screening to target identifications. The value of these studies is also increasing because of the progress in AI, which helps drive mechanistic insights from the large amounts of data generated by these experiments. As we have discussed before, we believe AI represents a significant and structural tailwind for our business. AI has enormous potential to transform biology and human health, but realizing that potential depends on generating vastly more of the right kinds of data. The key bottleneck for AI-driven progress in biology is the same bottleneck we identified when we started the company. Biology is incredibly complex. We understand only a tiny fraction of it, and solving that complexity requires measuring biological systems at massive scale and high resolution. We build single-cell and spatial technologies for precisely that purpose, which is why they're now being deployed by so many of our customers to train AI models. In fact, AI, as an influencer of demand, is now becoming pervasive across our customer base. Today, most significant biological data generation efforts are conceived, at least in part, with the goal of training AI models. On the academic side, there are multiple well-known pioneering efforts, such as those led by CZI and the ARCA Institute, dedicated to building virtual biology models. but we're also seeing a wider shift where more of basic scientific research entails training AI models. This shift is driven bottom-up by decisions of individual scientists as well as top-down by philanthropic and government funding priorities such as those outlined in recent proposals from the White House. A similar shift is also starting to happen by pharma with a rapid growth in AI-focused investments. Initially, much of the AI work in drug development has focused on the chemistry side of the process, on creating molecular interventions once a target is known. Going forward, we expect increasing investments to be made in modeling biology at the cell and tissue level to unlock new targets and to predict drug response in patients. We believe this is where the biggest bottlenecks are and where there are the greatest opportunities to transform drug development. This work is also precisely what our tools enable and why we anticipate a very large opportunity for our technologies over time. Most pharma companies now have strategic mandates to leverage AI to speed up drug development and increase the probability of success. At the same time, there's a rapidly growing number of biotech companies that seek to transform drug development using AI. More and more of them are focused on building sophisticated virtual models of human biology. The vast majority of the companies building such models are using 10x single-cell and spatial technologies. Customers overwhelmingly choose our products because they deliver the highest data quality, the largest scale, the widest biological context, and the most powerful multi-omics capabilities. It has become increasingly clear in the field that all of these considerations are critical for building high-quality, generalizable, and useful models. Jens Durruthy Researchers who previously required dedicated computational experts are starting to analyze complex datasets through natural language interactions with AI agents. We believe that will make single-cell and spatial analysis accessible to a much broader community of scientists while increasing the value of the underlying data. Together, these trends reinforce our conviction that single cell and spatial biology are foundational to the future of basic science and drug discovery research. AI is increasing both the demand for high-quality biological data and the ability of researchers to extract insights from that data. We believe those two forces will reinforce one another over the coming years. Now, as we have discussed previously, we envision a significant opportunity to extend our technologies into clinical diagnostics in the future. Realizing that opportunity requires generating robust clinical evidence on large patient cohorts. We're continuing to make progress on our internal efforts to generate such evidence in oncology and in autoimmunity. This quarter, we announced new partnerships with the Cleveland Clinic and with the Lausanne University Hospital to identify bar markers of response to therapy across multiple oncology indications. Taken together, this quarter demonstrates the strength of our strategy and continued execution across our business. We advanced a game-changing new platform, sustained strong momentum in our core consumables business, and deepened our engagement with customers through high-impact partnerships. We continue to build a stronger company operationally and financially, giving us the flexibility to invest for the long term. Our technologies are at the nexus of some of the most powerful trends transforming biology and medicine. The upcoming years are going to be profoundly exciting and we're uniquely well positioned for the opportunity ahead. With that, I will turn the call over to Adam.