Cryo-EM Patents: Who Leads, Where the Gaps Are 2026
- Filing peaked in 2022 at 21 records, then eased off — this looks like a maturing claim space rather than an accelerating one.
- G01N and H01J dominate the IPC mix, each covering roughly two-thirds of the 94 records, while bioinformatics and AI-adjacent classes stay under 14%.
- The leading assignee holds 21 records against a fifth-place count of 10, so the field has a clear leader but not a runaway monopoly.
What this landscape covers
This landscape tracks 94 published patent records at the intersection of cryo-electron microscopy hardware and structural biology workflows: grid preparation, preferred-orientation mitigation, detector and phase-plate design, resolution, and cryo-ET tomography. The search combines technique-level free text with IPC classes spanning material analysis (G01N), electron optics (H01J) and bioinformatics (G16B), which keeps the scope centred on instrumentation and sample-handling claims rather than downstream biology.
Coverage runs from 2015 through the 2026-07-31 cut-off. Because publication typically lags filing by around 18 months, the most recent year of activity in the trend chart understates true filing volume and should not be read as a drop-off on its own.
Filing trend and technology composition
Two views of the same 94-record dataset: filing activity by year, and how records distribute across IPC subclasses. Because a single record can carry several IPC classes, the composition shares add up to more than 100% of the record total.
Filing trend, 2017–2026
Filings rose to a peak of 21 records in 2022, roughly double the 9 recorded in 2017, before easing in subsequent years. The 2026 figure is partial and should be read against the publication-lag caveat above, not as a signal that activity has stopped.
IPC subclass composition
G01N (material analysis and testing) and H01J (electron and discharge tubes) each appear in roughly two-thirds of the 94 records, confirming this is fundamentally an instrumentation and sample-characterisation field. C07K (peptides and proteins), G16B (bioinformatics) and the smaller AI- and imaging-adjacent classes (G06T, G06N) sit well below that, marking the analytical and computational side of cryo-EM as comparatively lightly claimed.
Shares are the percentage of the 94 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Cryo-Electron Microscopy for Structural Biology with Eureka
This page is one run against one query. Ask Eureka your own question about cryo-electron microscopy for structural biology and every answer comes back with the patent numbers behind it.
Try EurekaRepresentative and most-cited filings
WO2025199620A1 — Cryo-electron microscopy sample preparation system, and modules and methods for operating same
A system, modules and various methods are provided for cryo-EM grid preparation that can achieve a high throughput with parameterized multi-grid handling. The system can be configured to be scalable, updatable and future proof by using an open architecture and modular design. The system described herein can address problems with preferred orientation, timing, optimization, time-resolution experiments, particularly for new particles and techniques.Filed by Neoglacia Inc., published 2025-10-02 — one of the most recent entrants addressing grid-preparation throughput and preferred orientation directly.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20160351374A1 | Thin-ice grid assembly for cryo-electron microscopy | 27 |
| 2 | WO2021067940A1 | Sample supports and sample cooling systems for CRYO-electron microscopy | 23 |
| 3 | US20220189579A1 | Protein complex structure prediction from cryo-electron microscopy (cryo-em) density maps | 12 |
| 4 | WO2015134575A1 | Thin-ice grid assembly for CRYO-electron microscopy | 11 |
| 5 | WO2015004158A1 | Rotavirus particles with chimeric surface proteins | 11 |
| 6 | US20220291098A1 | Sample supports and sample cooling systems for cryo-electron microscopy | 8 |
| 7 | US11605524B2 | System for sample storage and shipping for cryoelectron microscopy | 8 |
| 8 | US9786469B2 | Thin-ice grid assembly for cryo-electron microscopy | 7 |
| 9 | US11525760B2 | Gas phase sample preparation for cryo-electron microscopy | 6 |
| 10 | CN110337706A | 用于低温电子显微镜的可冻结流体单元 | 6 |
Citation counts reflect influence within the searched corpus and skew toward older filings; treat them as a signal of prior-art density, not of current commercial importance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
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Three patterns stand out once the filing trend, IPC composition and citation data are read together.
Activity has plateaued since the 2022 peak
Filings climbed from 9 in 2017 to a peak of 21 in 2022, then declined in the years that follow. Combined with the publication-lag effect on the most recent year, this reads as a field where the core hardware claims are largely staked out rather than one still in a land-grab phase.
Instrumentation claims dominate over computation
G01N and H01J together anchor most of the corpus, while G16B (bioinformatics) sits at 13.8% and G06N (AI-based computing) at just 6.4% of the 94 records. Reconstruction and prediction software is claimed far less densely than the physical grid, detector and phase-plate hardware it depends on.
Thin-ice grid design anchors the prior art
The most-cited record in the dataset, US20160351374A1, addresses thin-ice grid assembly — a problem that recurs across several of the other highly-cited filings, including its later WO counterpart. Grid and sample-support design is the densest prior-art cluster a new filer will need to search around.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to cryo-electron microscopy for structural biology, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Brandeis University | Novartis AG | 10 |
| Brandeis University | Children's Medical Center Corporation | 10 |
| Novartis AG | Children's Medical Center Corporation | 10 |
Only three co-assignee pairs appear in the dataset, each linking the same three organisations at a count of 10 — a narrow but recurring university-industry collaboration rather than a broad partnering pattern.
Who holds the claims
The assignee ranking covers 23 companies and research institutions, counted by patent family. The leader holds 21 records; by fifth place that falls to 10, and by tenth place to 3 — a clear leader with a long tail of single- and few-filing entrants rather than a flat field.
One organisation sets the pace
The top-ranked assignee holds 21 of the records in the ranking, well clear of the rest of the field. That concentration sits alongside academic and research-foundation names rather than a single dominant commercial player, reflecting cryo-EM's roots in structural biology labs.
A cluster of active mid-tier filers
Fifth place in the ranking holds 10 records, indicating a group of organisations filing steadily rather than opportunistically. Several of these are university technology-transfer bodies and research foundations, consistent with cryo-EM's origins in academic instrumentation development.
Momentum has cooled across most named filers
By tenth place, filing counts drop to 3, and recent-year momentum data shows most tracked assignees at 0 filings in the latest year. This is consistent with the plateau seen in the overall filing trend rather than a sign any one player has withdrawn.
| Assignee | Recent year | YoY |
|---|---|---|
| NEW YORK STRUCTURAL BIOLOGY CENT | 1 | 0% |
| MiTeGen LLC | 0 | -100% |
| Brandeis University | 0 | — |
| Novartis AG | 0 | — |
| Wisconsin Alumni Research Foundation | 0 | — |
| Children's Medical Center Corporation | 0 | — |
| Osaka University | 0 | — |
| The Rockefeller University | 0 | — |
Where to take this
The dataset points to specific next steps depending on whether the goal is freedom-to-operate, licensing or new filing strategy.
Check grid-preparation prior art before filing
Thin-ice grid assembly and sample-support design carry the heaviest citation weight in this dataset. Any new hardware filing in that space should be checked against the most-cited records first.
Explore grid-preparation prior art in EurekaWatch the computational side for new entrants
G16B and G06N classes remain comparatively lightly claimed relative to the hardware classes. That gap is worth monitoring as AI-based reconstruction and density-map interpretation tools mature.
Track bioinformatics filings in EurekaMap the long tail of single-filing assignees
With filing counts dropping sharply past the top few ranked assignees, several single- or few-filing entrants may hold narrow but relevant claims worth individual review.
Run an assignee deep-dive in EurekaCommon questions
Within this dataset of 94 records, the ranking of 23 assignees shows one organisation clearly ahead with 21 records, compared to 10 at fifth place and 3 by tenth place. The leading names include academic and research-foundation bodies alongside industry, which reflects cryo-EM's origins in university instrumentation labs rather than a single dominant commercial supplier. Anyone doing freedom-to-operate work should treat the top few assignees as the first stop, then check the long tail of few-filing entrants for narrower but still-relevant claims.
Filing activity rose from 9 records in 2017 to a peak of 21 in 2022, then eased in the years since, which points to a plateau rather than continued acceleration. The most recent year in the trend is partial and understated because publication typically lags filing by around 18 months, so recent activity should not be read as a hard drop-off. Overall the pattern looks like a field where core hardware claims are largely staked out.
Hardware and material-analysis claims sit mainly in G01N and H01J, each covering roughly two-thirds of the 94 records in scope. Bioinformatics claims sit in G16B at 13.8% of records, and AI-based computing methods in G06N at 6.4%, both well below the hardware classes. This gap suggests reconstruction, density-map interpretation and AI-assisted processing are less densely claimed than the physical grid, detector and phase-plate technology they operate on.
WO2025199620A1, filed by Neoglacia Inc. and published 2025-10-02, describes a scalable, modular cryo-EM sample preparation system built for high-throughput multi-grid handling, aimed specifically at problems with preferred orientation and timing during grid preparation. Its open-architecture, parameterized design is the key claim element to review for anyone building automated or high-throughput grid-preparation tooling. Because it is a recent filing, its practical blocking effect will depend on how broadly its claims are construed relative to the older thin-ice grid assembly prior art already in the dataset.
The clearest gaps sit in the computational layer: AI-based density-map interpretation, automated preferred-orientation correction, and cryo-ET tomography workflow automation all show low representation relative to G01N and H01J hardware claims. Phase-plate manufacturing methods and multi-grid throughput systems also look comparatively thin given how central they are to modern cryo-EM workflows. These are the branches worth a closer novelty search before committing to a filing strategy, since hardware-adjacent claim space is already dense with prior art.
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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.