Spatial Omics Patents: Who Leads, Where the Gaps Are 2026
- 39.4% concentration. The five leading assignees hold 562 of 1,428 records in scope — a field with a genuine head, not a flat crowd.
- +82% filing growth 2021-2024. Filings rose from 145 to 264 across those three years, with 2024 the highest year on record so far.
- Momentum is cooling at the very top. Several of the earliest, largest filers show sharp year-on-year declines in the latest year — a leadership reshuffle may be underway.
Filing growth compares 2021 (145 records) with 2024 (264) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 1,428 records in scope (CR5), not by the ranked leaders only.
What the spatial omics patent record shows
Spatial omics — methods that preserve a molecule’s physical location within a tissue while measuring its identity or expression — sits at the intersection of sequencing chemistry, imaging and computational biology. The search covers 1,428 records published between 2015 and the 2026 cut-off, combining spatial-profiling terminology with core molecular-biology claim language such as sequence alignment and expression level. Publication lags filing by roughly eighteen months, so the most recent one or two years in any trend understate real filing activity.
The dataset spans core sequencing-and-detection claims through to bioinformatics and therapeutic-activity classes, showing a technology that has moved from a single-instrument idea into a multi-layered claims environment spanning chemistry, hardware and software.
Filing trend and technology composition
Two views of the same 1,428 records: how filing volume has moved year over year, and which IPC subclasses carry the claim density.
Filing trend, 2017-2026
Filings climbed from 51 in 2017 to a peak of 264 in 2024, including +82% growth between 2021 (145) and 2024 (264). 2025 and 2026 figures are still filling in under publication lag and should not be read as a slowdown.
Technology composition by IPC subclass
C12Q (measuring/testing involving enzymes or DNA) covers 55.2% of the 1,428 records, with C12N (genetic engineering) at 28.4% and G01N (material analysis) at 24.9%. Bioinformatics (G16B, 13.0%) and combinatorial libraries (C40B, 7.1%) are smaller but distinct claim tracks; a record can carry several classes, so shares sum above 100%.
Shares are the percentage of the 1,428 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Spatial Omics Patent Landscape with Eureka
This page is one run against one query. Ask Eureka your own question about spatial omics patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited records in the corpus
US20240338955A1 — exploration apparatus for molecular marker and physiological activity information in tissue
The filing (Portrai Inc., 2024-10-10) describes an analysis apparatus that receives a tissue image carrying a bound labelling material, spatially maps that image against transcriptome information tied to the same tissue location, and extracts the transcriptome information for downstream analysis of distribution or physiological activity.Abstract text lightly edited for length; reference numerals from the original filing retained.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US9593365B2 | Methods and product for optimising localised or spatial detection of gene expression in a tissue sample | 590 |
| 2 | WO2018091676A1 | Method for spatial tagging and analysing nucleic acids in a biological specimen | 526 |
| 3 | WO2012140224A1 | Method and product for localised or spatial detection of nucleic acid in a tissue sample | 437 |
| 4 | US10030261B2 | Method and product for localized or spatial detection of nucleic acid in a tissue sample | 382 |
| 5 | US20200277663A1 | Methods for determining a location of a biological analyte in a biological sample | 380 |
| 6 | US20140066318A1 | Method and product for localized or spatial detection of nucleic acid in a tissue sample | 348 |
| 7 | WO2020176788A1 | Profiling of biological analytes with spatially barcoded oligonucleotide arrays | 336 |
| 8 | WO2014060483A1 | Methods and product for optimising localised or spatial detection of gene expression in a tissue sample | 307 |
| 9 | WO2020123320A2 | Imaging system hardware | 289 |
| 10 | US20210155982A1 | Pipeline for spatial analysis of analytes | 285 |
Citation counts reward older records that have had more time to accumulate references — treat them as a signal of influence on the field, not of current technical importance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the data means for filing strategy
Three findings that shape where a new filing is likely to land, and where it is likely to be blocked.
The top of the field is genuinely concentrated
The five leading assignees together hold 562 of the 1,428 records in scope, and the top ten hold 759 (53.2%). That is a steep drop-off from a leader at 299 records to a tenth place at 31 — foundational spatial-detection claims are locked up early, and new entrants are filing around rather than through them.
Filing volume nearly doubled in three years
Annual filings rose from 145 in 2021 to a peak of 264 in 2024, the highest year on record. That growth sits mostly in the C12Q and C12N classes that carry the core detection chemistry, suggesting the surge is chemistry- and workflow-driven rather than purely software.
Software claims are present but still a minority track
G16B bioinformatics classes appear on 13.0% of records versus 55.2% for core C12Q detection claims. Software-layer claims — image registration, spot deconvolution, cell-type assignment — are filed far less densely than the underlying wet-lab methods, which is where open claim space is most visible.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to spatial omics patent landscape, with the prior art for and against each one.
Who is filing, and where momentum is shifting
The ranked leaders are dominated by the instrument and sequencing platform originators, but the latest-year momentum data suggests that dominance is not static.
A clear single leader, then a steep drop
The top-ranked assignee holds 299 records, nearly five times the tenth-place figure of 31. This is not a flat field of similarly sized filers — early platform originators built a substantial lead before the rest of the field caught up.
Several established filers are pulling back
Multiple assignees that built large early portfolios show sharp year-on-year declines in the latest year, some dropping to zero filings. That pattern is consistent with either portfolio maturity or a shift in R&D focus away from the claim areas this search covers, rather than exit from the field entirely.
Research-institute pairings anchor the densest collaboration
The strongest co-assignee pair in the dataset — a research institute and an affiliated university — appears on 55 records, well ahead of the next-strongest pairs. Dense academic-institutional collaboration is a structural feature of this field's top tier, not an isolated case.
| Assignee | Recent year | YoY |
|---|---|---|
| California Institute of Technology (Caltech) | 3 | -50% |
| 10x Genomics, Inc. | 2 | -88% |
| President and Fellows of Harvard College | 1 | -80% |
| The Board of Trustees of the Leland Stanford Junior University | 1 | -83% |
| Encodia, Inc. | 0 | -100% |
| The Broad Institute, Inc. | 0 | -100% |
| Spatial Transcriptomics AB | 0 | — |
| Massachusetts Institute of Technology | 0 | -100% |
Where to take this next
The landscape points to specific next questions rather than a single conclusion.
Check freedom-to-operate against the top-cited records
The five most-cited records in this corpus anchor core spatial-detection methods and are worth a direct claim read before committing to a detection-chemistry approach.
Explore citation networkTrack the leadership reshuffle
Several of the largest early filers show steep pullbacks in the latest year. Watching who fills that space over the next publication cycle will show whether new entrants or existing mid-tier filers are absorbing it.
Monitor assignee activityProbe the bioinformatics layer for open claims
With G16B classes on only 13.0% of records against 55.2% for core detection chemistry, the software layer — registration, deconvolution, annotation — carries comparatively thinner claim density.
Run a white space searchFrequently asked questions
The dataset's ranked leader holds 299 of the 1,428 records in scope, with the top five assignees together holding 562 records (39.4%). This is a genuinely concentrated field: the drop from the leader to the tenth-ranked assignee, at 31 records, is steep. That said, momentum data shows several of the largest early filers pulling back sharply in the most recent year, so today's ranking may not describe tomorrow's leader.
Yes, through the last complete year of data. Filings rose from 145 in 2021 to a peak of 264 in 2024, an increase of 82% over that span. Figures for 2025 and 2026 appear lower, but that reflects the roughly 18-month lag between filing and publication rather than an actual slowdown, so those years should not yet be read as a decline.
Core detection chemistry dominates: C12Q (enzyme and DNA-based measuring and testing) appears on 55.2% of the 1,428 records, and C12N (genetic engineering) on 28.4%. Bioinformatics claims under G16B appear on only 13.0% of records, and therapeutic-activity claims under A61P on 11.5%, indicating that the wet-lab and instrument layers are more densely claimed than the software and clinical-application layers.
The comparatively thin filing density in bioinformatics (G16B, 13.0% of records) and combinatorial chemistry libraries (C40B, 7.1%) relative to core detection chemistry (C12Q, 55.2%) points to open claim space in data-processing methods — spatial multi-omics fusion, automated image-to-transcript registration and multiplexed proteomic readout are specific candidates worth a dedicated freedom-to-operate check before filing.
The five most-cited records in this corpus, including US9593365B2 and WO2018091676A1, describe foundational methods for localised or spatial detection of gene expression and nucleic acid in tissue samples, with citation counts as high as 590. High citation counts reflect years of accumulated references in an older record, not necessarily current commercial importance, but these particular filings sit close to the root of the field's core detection methods and are a sensible starting point for any freedom-to-operate review.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.