10x Genomics Positions Spatial Biology as Center Stage as AI Fuels New Wave of Customer Demand
By Irene Yeh
January 14, 2026 | At the 44th Annual J.P. Morgan Healthcare Conference, 10x Genomics announced a strong ending to 2025, generating $166 million in Q4 and totaling more than $520 million at the end of the year. With great anticipation for 2026, 10x Genomics remains centered on their mission on accelerating understanding of biology to advance human health, particularly in the single-cell and spatial biology areas. The key challenge, however, is biology being “very, very complex,” according to Serge Saxonov, CEO and cofounder. “The key to understanding biology is to understand what is going on at the cell level,” explains Saxonov, calling the cell “the fundamental unit of biology.”
Previous generations of tools only produced a general reading of cell profiles, but 10x Genomics has developed tools and software that provide researchers with high-scale single-cell and spatial analysis, offering a way to examine samples at a cellular level. Saxonov reported that over 10,000 papers in scientific journals have used the platforms developed by 10x Genomics, and it looks like demand will continue to increase.
The Increasing Demand in Single-Cell and Spatial Biology
Chromium is described as 10x’s unambiguous leader in single-cell analysis due to its consistent performance, extensive ecosystem of publications and protocols, and support of a wide range of applications. Despite single-cell showing benefits, much biological research has not yet transitioned to these methods, but Saxonov reports that there has been a new wave of interest in single-cell over the past year, driven by emerging applications, large-scale artificial intelligence (AI) projects, and expansion of translation research. One of 10x Genomics’ most recent products, the Flex assay, for example, delivers substantial gains and is quite sensitive, particularly in tissue-based studies.
Along with single-cell biology, spatial biology has also made its place as an important part of 10x Genomics’ portfolio. The Xenium platform generated strong customer enthusiasm, with users reporting exceptional data quality and running their tools “around the clock continuously.” Spatial biology offers the ability to measure molecules, cells, and tissues together, unlocking new potential discoveries and opportunities in biological research.
While adoption of the tools is not universal yet, Saxonov states that expanding access, improving ease of use, and driving down costs are central goals of the company.
Where Does AI Fit in All This?
AI is now considered a key factor in many modern research innovations. “AI has huge potential to transform the understanding of biology, but the key thing it needs is data. The thing is, the potential data—scale of data—in biology is essentially inexhaustible,” says Saxonov. Yet, historically, there has been a lack of tools capable of generating data at that scale.
10x Genomics builds tools that will ultimately fully simulate cells and tissues in silico, virtual cells. The idea is increasingly viewed as feasible because of progress in both AI methods and experimental platforms that can generate large, cost-effective, and biologically relevant datasets. In this context, AI is not just an analytical tool applied after experiments are completed, but a driving force that can shape how experiments are designed and executed.
To Saxonov, this is a big shift in how the industry thinks about research. Much of the research data fed to these models are observational in nature, measuring cells, samples, and populations, which provide valuable insights and supports analytical tasks. But perhaps the biggest “game changer” is data from perturbation experiments, which systematically alter the state of cells and observe the resulting effects. Examples include CRISPER-based and Perturb-seq-based edits, epigenetic modifiers, chemicals, and drug libraries. Not only do these perturbation experiments detail cell activity, but they also link cause and effect, thus enabling a deeper understanding of biological mechanisms, and are particularly powerful for training AI models, creating faster workflow, and allowing more precise drug discovery.
Demand for these approaches is rapidly rising, especially within biopharma, with increasing numbers of projects and profiling tens of thousands to millions to even billions of cells now.
But these are large experiments that require huge undertakings. To support this shift and demand, data quality and reliability are critical. “Garbage in, garbage out,” as Saxonov puts it. Platforms need to work consistently across conditions and deliver high sensitivity and cell recovery. 10x Genomics is working toward this goal by partnering with The Cancer Research Institute to build a massive dataset called the Discovery Engine to accelerate advancements in immuno-oncology through high-resolution molecular data and AI. The dataset will serve as a foundational resource to understand the mechanisms of drug response and ultimately get the right drugs to the right patients.
The Future of Single-Cell and Spatial Biology
As single-cell and spatial biology continue to grow in demand, their roles in translational research will continue to expand. Saxonov cites three reasons for this growth. First, there are increasingly more therapies but no good understanding of with which therapies to treat which patient. Second, there is a need for biomarkers, signatures of response, and enabling precision medicine. And third, the company’s products have made advancements over the past few years and are well-equipped to handle large cohorts of studies in translational areas. As translational research has been confined to basic research due to limitations in scale, cost, workflow complexity, and sample compatibility, 10x Genomics’ tools can address these restrictions. Saxonov reports that customers have already made efforts to launch translational projects across different areas, scaling up the number of studies and helping with understanding biology, discovering biomarkers, and aiding precision medicine.
With these new innovations, Saxonov is hopeful about the reaches translational research can go. He states that translational research is a driver behind biopharma adoption. Single-cell and spatial tools can be used for drug development, from early target identification to clinical trials. There is also potential for later stages, such as biomarker detection to determine how a patient will respond to a certain drug.
For the clinic, there is also diagnostic use, with physicians already inquiring about deploying single-cell and spatial analysis in routine patient care. However, in order for diagnostics applications to happen, two requirements need to be met: robust clinical evidence and reliable clinical deployment. To help with this, 10x Genomics plans to continue supporting customer-led evidence generation while directly collaborating with partners to make diagnostic single-cell and spatial tools possible. Saxonov announced two more partnerships with Dana-Farber Cancer Institute to work on oncology applications and Brigham & Women’s Hospital to expand on autoimmunity research. The company also plans to build a CLIA-certified laboratory.