The power of the network
Building impactful AI models for real-world results
The future of drug development is generative, but an AI model is only as good as its training data, which is why 10x Genomics is working on a standard for "AI-ready" biology by providing the high-resolution, multi-modal context required to de-risk targets and stratify patients with unprecedented precision. By uniting high-quality biological data with cutting-edge AI, 10x Genomics provides the foundational "ground truth" necessary to build trustworthy virtual cells and accelerate the entire drug development lifecycle.
This mission is powered by a network of strategic partnerships, such as the transformative initiative with the Cancer Research Institute to profile over 500 million cells from 20,000+ samples, creating the massive training sets required for AI models to predict immune response and vaccine efficacy.
Beyond immunology, 10x Genomics is bridging the gap between the lab and the clinic by unlocking archival data through collaborations with PharosAI and MOSAIC, utilizing the Xenium spatial platform to digitize thousands of NHS and other clinical samples so that AI can correlate spatial tissue architecture with real-world patient survival.
This effort to map tissue complexity extends to the TISHUMAP initiative with A*STAR, which uses the Xenium platform to perform large-scale spatial omics on 2,500 FFPE tissues, supported by smart software pipelines for massive data processing and target discovery. To further deepen the industry's understanding of gene function, 10x Genomics’ technology supports massive-scale foundation models like the Billion Cells Project with the Chan Zuckerberg Initiative and Xaira's X-Atlas project, which generates a high-quality Perturb-seq atlas across 8 million cells. These high-resolution datasets also fuel the Arc Institute’s Virtual Cell Atlas, which profiles over 300 million cells to train AI models capable of predicting how cells will react to specific perturbations.
To ensure these insights are actionable for Biopharma, 10x Genomics is actively eliminating the "Bioinformatics Burden" through streamlined analytical partnerships that democratize high-dimensional data. This includes a collaboration with Anthropic to allow researchers to query datasets using natural language via Claude for Life Sciences, as well as a partnership with BioTuring to provide NVIDIA GPU-accelerated workflows that slash time-to-insight by moving data directly from the 10x Genomics Cloud into advanced visualization environments.
Additionally, a partnership with Ultima Genomics combines high-quality single-cell data with ultra-low-cost sequencing, allowing Biopharma to scale ambitious AI projects more economically. The result is a seamless path from high-throughput discovery to validated clinical assets, inviting leaders in the field to leverage 10x Genomics in building the future of medicine.
For more details on how 10x Genomics is uniting AI and biology to power the next generation of therapeutics, visit the 10x Genomics AI Solutions page.
Meet Flex Apex
GEM-X Flex Apex (formerly GEM-X Flex v2) accelerates drug development by delivering massive scale and sensitivity. Profile up to 1 million cells per lane and multiplex 384 samples to transform complex tissue mapping into high-throughput clinical insights.
To address the logistical hurdles of collecting fresh tissue or profiling archival samples, GEM-X Flex Apex introduces high-throughput protocols designed for the real world. Our new plate-based, xylene-free dissociation protocol enables the simultaneous processing of up to 96 FFPE sections in a standard 96-well format. This heat-based method is significantly faster than traditional protocols and avoids harsh chemicals, unlocking the retrospective power of archival clinical blocks without sacrificing sample complexity.
Furthermore, for anti-cancer screening, our new adherent cell protocol delivers whole-transcriptome results at single-cell resolution in less than a week. As we show in a recently presented poster1 performing a 384-plex colorectal cancer screen, this workflow successfully identified distinct pathway responses—including the inactivation of MAPK and the activation of p53—across multiple cell lines following drug treatment. As the only platform designed to accommodate the full spectrum of clinically relevant sample types, Flex Apex delivers the efficiency needed to move from the bench to the clinic with confidence.
To examine the data behind our 1 million cell milestone, you can have a look at the poster of Wu et al.1 and download our updated Flex Apex product sheet and Chromium X Series assay compatibility brochure to explore how this assay can accelerate your discovery pipeline.
Publication highlight: Single cell sequencing goes retrospective
The study "Robust detection of clinically relevant features in single-cell RNA profiles of patient-matched fresh and formalin-fixed paraffin-embedded (FFPE) lung cancer tissue" (Trinks et al., 20241), marks a significant milestone in making single-cell technology more practical for clinical research. It demonstrates that archival formalin-fixed paraffin-embedded (FFPE) tissue blocks—the standard for hospital pathology—can reliably replace fresh tissue for single cell RNA profiling. By benchmarking patient-matched fresh, cryopreserved, and FFPE lung cancer samples, researchers found that FFPE blocks not only preserved clinically relevant transcriptional signatures and signaling pathways but actually revealed higher cell diversity than fresh samples. Conversely, cryopreservation was found to be prone to artifacts in clinical settings. This breakthrough allows researchers to perform high-resolution single-cell analysis on vast retrospective cohorts, linking cellular heterogeneity directly to long-term patient outcomes and therapy response.
Key findings
- Single-cell studies typically require fresh tissue, which is difficult to collect and process immediately during surgery.
- Standard FFPE (paraffin-embedded) blocks—which can be stored for years—provide high-quality data that matches or exceeds fresh tissue in cell diversity.
- While individual gene expression varied slightly due to technology, "module scores" for signaling pathways and clinical signatures were highly correlated between fresh and FFPE samples.
- Researchers can now use existing biobanks to conduct massive retrospective studies, correlating single-cell data with years of patient survival and treatment data.
1Trinks, A., et al. (2024). Robust detection of clinically relevant features in single-cell RNA profiles of patient-matched fresh and formalin-fixed paraffin-embedded (FFPE) lung cancer tissue. Cellular Oncology. doi:10.1007/s13402-024-00922-0
Tip: Curious to know more about how FFPE tissue analysis can benefit your research? Read "A pathologist’s perspective: Advantages of using FFPE tissues for single cell analysis", our interview Dr. Philip Bischoff, a resident pathologist and clinical scientist at Charité University Hospital in Berlin and co-author on the above mentioned paper.
Also see the recording of Dr. Bischoff's presentation at the Heidelberg Multiomics Symposium "Robust Detection of Clinically Relevant Features in Single-cell RNA Profiles of Patient-matched Fresh and Formalin-fixed Paraffin-embedded (FFPE) Lung Cancer Tissue".
Where to meet us
We are attending High-Content CRISPR Screening Conference in Vienna on 18-19 March. Hear from Peter Smibert, our Vice President of Biology during CRISPR Screening with Single-Cell Readout session on March 18.Webinar recordings
Did you know that all our webinars are available to watch on-demand? Here's a selection of our webinars exploring the possibilities of the Flex assay.
- Mastering high-throughput single cell gene expression with plate-based Flex. Speaker: Sravya Ganesh, Technical Support Scientist, 10x Genomics
- From archive to insight: The high-throughput revolution for FFPE and fixed clinical samples. Speaker: Stephen Hague, Sr. Manager, Science and Technology Advisors, 10x Genomics
- Explore Innovative Techniques to Overcome Sample Challenges and Improve Data Quality in Clinical Trials. Speakers: Emma Bell, Senior Scientist, Roche; Emilio Yangüez, Senior Scientist, Roche. Also see Hatje, Klas, et al. "Comparison of single-cell RNA-seq methods to enable transcriptome profiling of neutrophils in clinical samples." Cell Reports Methods 5.9 (2025) — The webinar covers the research detailed in this publication
- Single cell analysis of FFPE tissue: Experiences and considerations from a pathologist’s perspective. Speakers: Angela Churchill, Sr. Product Marketing Manager, Single Cell, 10x Genomics; Philip Bischoff, Resident Pathologist | Clinician Scientist, Charité - University of Berlin
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