Spatial Proteomics Patents: Who Leads, Where the Gaps Are 2026
- Filing peaked in 2021 at 63 records, then eased to 53 by 2024 — a -16% shift over that span, not a collapsing field.
- Five assignees hold 51.5% of all 297 records, and the top ten hold 76.8% — concentration that starts early and stays tight.
- G01N material analysis touches 46.5% of records, while image processing under G06T and G06V sits far lower, near 12% each.
Filing growth compares 2021 (63 records) with 2024 (53) — 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 297 records in scope (CR5), not by the ranked leaders only.
What's being claimed, and by whom
Spatial proteomics and multiplexed staining sit at the intersection of tissue biology and instrumentation: methods for imaging mass cytometry, cyclic staining, and antibody panel validation that let researchers map dozens of protein markers onto a single tissue section without destroying it. The patent record in scope spans 297 published records filed between 2015 and mid-2026, concentrated around problems that are easy to state and hard to solve cleanly — signal spillover between channels, metal isotope tag design, and batch normalization across imaging runs.
The filing curve shows a field that grew fast, cycled through a peak, and has since settled rather than stalled. Because publication lags filing by roughly 18 months, the most recent one to two years in any chart will always look thinner than they eventually turn out to be — read the tail with that in mind, not as a signal of declining interest.
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Filing trend and technology composition
Two views of the same 297 records: how filings moved year over year, and which IPC subclasses carry the claim density.
A peak in 2021, then a manageable pullback
Filings rose from zero in 2017 to a peak of 63 in 2021, then eased to 53 by 2024 — a -16% change over that three-year span. That is a normalization after a surge, not evidence of a shrinking field; 2025 and 2026 figures will keep revising upward as publication catches up with filing.
Material analysis dominates; image processing lags
G01N (material analysis & testing) appears on 46.5% of the 297 records, well ahead of C12Q (28.3%) and A61K (21.5%). Image-side classes — G06T image processing and G06V image recognition — sit at 12.1% and 11.8% respectively, notably lower than the wet-lab and assay classes despite spatial proteomics being fundamentally an imaging problem.
Shares are the percentage of the 297 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Spatial Proteomics and Multiplexed Staining with Eureka
This page is one run against one query. Ask Eureka your own question about spatial proteomics and multiplexed staining and every answer comes back with the patent numbers behind it.
Try EurekaThe most-cited records in this space
Analysis methods for multiplex tissue imaging including imaging mass cytometry data
The invention relates to methods for multiplex tissue imaging by methods such as imaging mass cytometry (IMC) and methods for analysis of imaging mass cytometry data. In various embodiments, methods are provided of cell-of-origin analysis and mutational analysis, coupled with spatial parameters derived from tumor clusters in the tumor microenvironment; which reveals signature marker profiles and therapeutic targets for treating cancers including diffuse large B cell lymphoma.Filed by Cedars-Sinai Medical Center, published 2022-10-20 as US20220336058A1.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20210090694A1 | Data based cancer research and treatment systems and methods | 712 |
| 2 | WO2021091611A1 | Spatially-tagged analyte capture agents for analyte multiplexing | 153 |
| 3 | US20220326251A1 | Spatially-tagged analyte capture agents for analyte multiplexing | 124 |
| 4 | US11592447B2 | Spatially-tagged analyte capture agents for analyte multiplexing | 101 |
| 5 | US20230228762A1 | Spatially-tagged analyte capture agents for analyte multiplexing | 83 |
| 6 | US20190347557A1 | Generalizable and Interpretable Deep Learning Framework for Predicting MSI from Histopathology Slide Images | 76 |
| 7 | US11808769B2 | Spatially-tagged analyte capture agents for analyte multiplexing | 64 |
| 8 | WO2019070755A1 | Methods and compositions for detecting and modulating an immunotherapy resistance gene signature in cancer | 61 |
| 9 | US20220367053A1 | Multimodal fusion for diagnosis, prognosis, and therapeutic response prediction | 57 |
| 10 | US20240053351A1 | Spatially-tagged analyte capture agents for analyte multiplexing | 53 |
Citation counts favour older records inside any searched corpus — read them as a signal of influence on later filings, not as a ranking of current technical importance.
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Browse MCP servers →What the data means for a filing decision
Three patterns worth acting on before drafting the next claim set in this space.
The top of the field is dense, not diffuse
Five assignees hold more than half of all 297 records in scope, and the top ten hold 76.8%. New entrants filing broad method claims on core imaging-mass-cytometry workflows are filing into occupied ground; differentiation has to come from a specific application, marker panel, or normalization step, not from the general workflow.
A peak, then a settle — not a decline
Filing rose to a peak of 63 records in 2021 before easing to 53 by 2024, a -16% change. Given the roughly 18-month lag between filing and publication, 2025-2026 figures are still incomplete; treat the recent dip as a return to a steadier baseline rather than as evidence the field has stalled.
Wet-lab assay claims outweigh image-processing claims
G01N material analysis appears on nearly half of all records, while the two image-side classes, G06T and G06V, sit near 12% each. For a field built on multiplexed imaging, the algorithmic layer — segmentation, spillover correction, batch normalization software — looks comparatively lightly claimed relative to the assay and reagent side.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to spatial proteomics and multiplexed staining, with the prior art for and against each one.
The assignee landscape
73 companies and institutions make up the full ranking returned for this dataset — not a top-50 or top-100 cut, but the entire ranked list for these 297 records. Filing is led by a mix of instrument makers, cancer research institutes and diagnostics companies, with academic-industry co-assignee pairs appearing repeatedly near the top.
A single leader well ahead of the field
The top-ranked assignee holds 41 records, noticeably ahead of fifth place at 27 and tenth place at 11 — the drop-off from first to fifth is steep, then flattens into a longer tail.
Academic-institute pairs file together repeatedly
Ten co-assignee pairs appear in the data, with the strongest research-institute pairing sharing 23 records and a second pairing sharing 19 — a pattern consistent with grant-funded, multi-institution cancer research programs rather than single-company R&D.
Several early leaders show no recent-year filings
A number of assignees that were active earlier in the dataset show zero filings in the latest year, including multiple research institutes with -100% year-on-year change. That does not necessarily mean exit — it is consistent with the publication lag — but it does mean recent competitive attention has shifted toward whoever is still filing.
| Assignee | Recent year | YoY |
|---|---|---|
| Singular Genomics Systems Inc | 1 | -80% |
| AmberGen Inc | 0 | -100% |
| Massachusetts Institute of Technology | 0 | — |
| Evelo Biosciences Inc | 0 | — |
| The Broad Institute Inc | 0 | -100% |
| Dana-Farber Cancer Institute Inc | 0 | -100% |
| BostonGene Corp | 0 | -100% |
| University of Zurich | 0 | — |
Where to take this next
The dataset points to a few concrete next steps depending on what you're trying to decide.
Check freedom-to-operate against the top 10
With 76.8% of records held by ten assignees, any new filing in core imaging-mass-cytometry or cyclic-staining methods should be checked against that group's claim scope before drafting.
Run a freedom-to-operate search →Look at the image-processing gap
G06T and G06V classes sit far below the assay-side classes in share of records, suggesting the algorithmic layer of spatial proteomics is less densely claimed than the wet-lab side.
Explore the IPC breakdown →Track the co-filing institutions
Repeated academic co-assignee pairs suggest active, ongoing research programs; watching their newest filings is a reasonable proxy for where the science is heading next.
See assignee momentum →Common questions about this landscape
This dataset covers 297 published records filed between 2015 and mid-2026, searched across terms like spatial proteomics, multiplexed immunofluorescence and imaging mass cytometry combined with antibody panel validation, signal spillover, cyclic staining and related concepts. That figure counts records, which is the level the assignee ranking uses. Because publication lags filing by roughly 18 months, the true count for 2025 and 2026 filings will keep rising as those applications publish.
The field is led by a single assignee with 41 records, well ahead of the rest of the ranking, with the top five assignees together holding 51.5% of all 297 records and the top ten holding 76.8%. The leaders are a mix of cancer research institutes, university technology offices and diagnostics companies rather than a single dominant commercial player. Beyond the top ten, filing spreads across a long tail of 73 ranked assignees total, many with only one or two records.
Filing rose steadily to a peak of 63 records in 2021, then eased to 53 by 2024, a -16% change over that three-year span. That reads as a normalization after a surge rather than a slowdown, and figures for 2025 and 2026 are still incomplete because of the typical 18-month gap between filing and publication. Judging momentum from the most recent one to two years alone would understate current activity.
G01N, covering material analysis and testing, appears on 46.5% of the 297 records, making it the single most common classification, followed by C12Q (measuring and testing involving enzymes or DNA) at 28.3% and A61K (medicinal preparations) at 21.5%. Image-processing classes G06T and G06V sit lower, near 12% each, despite spatial proteomics being fundamentally image-driven. A record can carry more than one IPC class, so these shares add up to more than 100% and should not be read as a single pie chart.
The clearest gap sits in the algorithmic and software layer — spillover-correction algorithms, automated antibody panel design tools, and cross-platform batch normalization — where IPC shares (G06T and G06V near 12%) trail well behind the assay and reagent side (G01N at 46.5%). Cyclic staining methods focused specifically on tissue preservation during repeated staining cycles are another comparatively thin area. Any new claim in these branches should still be checked against the top ten assignees, who together hold 76.8% of all records and may have adjacent method claims even where the specific sub-area is lightly filed.
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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.