White Cell Differential Patents: Who Leads, Where the Gaps Are 2026
- 74.1% concentration. The top five ranked assignees hold 197 of the 266 records in scope — a field where claim space is already tightly held near the top.
- One dominant class. 94.7% of records carry a G01N material-analysis classification, while optical (G02B) and image-processing (G06T) classes sit in single digits — a sign of where filing has not caught up to the underlying technique.
- Peak filing in 2023. Filings reached 13 that year before the count trails off toward the data cut-off, consistent with normal publication lag rather than a real slowdown.
Top-5 share is the combined record count of the five largest assignees divided by all 266 records in scope (CR5), not by the ranked leaders only.
What this landscape covers
White cell differential methods cover the instruments and algorithms that classify leukocyte populations from a blood sample — fluorescence flow cytometry, nucleated red cell detection, blast flagging and the review logic that decides when a sample needs manual follow-up rather than automated reporting. This landscape draws on 266 published records filed or published between 2015 and the July 2026 data cut-off, spanning hematology analyzer makers, reagent and dye chemistry, and the software layer that turns raw scatter and fluorescence signals into a reportable differential.
The record set sits almost entirely inside material analysis and testing (IPC G01N), with smaller but present activity in mixing apparatus, lab consumables, bioreactor hardware, optics and image processing. That spread points to a field where the core measurement method is heavily claimed and the surrounding tooling — sample prep, optics, image analysis — is comparatively open.
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Filing trend and technology composition
Two views of the same 266 records: how filing has moved year over year, and which IPC subclasses the claims actually sit in.
Filing trend, 2017–2026
Filings ran from 6 in 2017 to a peak of 13 in 2023, before tapering toward 2026. The most recent one to two years will read low on any chart of this kind — publication typically lags filing by around 18 months, so 2025 and 2026 figures are still filling in.
IPC subclass composition
G01N (material analysis and testing) covers 94.7% of the 266 records, confirming this is fundamentally a measurement-method field. B01F (mixing), B01L (lab apparatus) and C12M (bioreactor and enzyme apparatus) each sit under 10%, and G02B (optics) and G06T (image processing) are lower still — each record can carry more than one class, so these figures do not sum to 100%.
Shares are the percentage of the 266 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on White Cell Differential Methods with Eureka
This page is one run against one query. Ask Eureka your own question about white cell differential methods and every answer comes back with the patent numbers behind it.
Try EurekaMost-cited records and a representative recent filing
Sample testing method and sample analyzer
The filing describes a sample analysis system that pairs a hematology analyzer with a controller, a transport device, a slide-preparation device and an image-capture device: when an initial analysis result meets a preset condition, the system routes the sample for slide preparation and imaging rather than reporting the automated result directly.Filed by Shenzhen Mindray Bio-Medical Electronics, published 2023-10-05.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5939326A | Method and apparatus for performing automated analysis | 320 |
| 2 | US5891734A | Method for performing automated analysis | 317 |
| 3 | US5631165A | Method for performing automated hematology and cytometry analysis | 291 |
| 4 | US6350613B1 | Determination of white blood cell differential and reticulocyte counts | 241 |
| 5 | US6136612A | Sulfo benz[E]indocyanine flourescent dyes | 165 |
| 6 | US6524858B1 | Single channel, single dilution detection method for the identification and quantification of blood cells and… | 137 |
| 7 | US5874310A | Method for differentiation of nucleated red blood cells | 127 |
| 8 | US5656499A | Method for performing automated hematology and cytometry analysis | 127 |
| 9 | US5917584A | Method for differentiation of nucleated red blood cells | 92 |
| 10 | WO1997013810A1 | SULFO BENZ[e]INDOCYANINE FLUORESCENT DYES | 88 |
Citation counts favour older records simply because they have had longer to accumulate citations inside this corpus — treat them as a marker of influence on later filings, not of current commercial relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the numbers mean for a filing decision
Three read-outs from the assignee ranking, the technology composition and the citation table.
The core method is not open ground
With 197 of 266 records held by five assignees, and 93.6% held by ten, a new entrant filing on the core differential-counting method is filing into dense, well-mapped prior art rather than a gap. Freedom-to-operate work here needs to start from the leader's portfolio, not the field average.
Claims cluster on the measurement, not the optics or software
G01N carries the overwhelming majority of records, while optical systems (G02B, 3.8%) and image-data processing (G06T, 2.3%) are thinly claimed by comparison. That gap suggests the detection method itself is well covered, but the optical path and the image-processing layer that interprets its output are comparatively under-claimed.
Influence sits with older automated-analysis filings
The most-cited records in this set describe automated hematology and cytometry analysis methods, several from the 1990s. Their citation counts reflect decades of accumulation inside this corpus, not that the underlying claims are still commercially load-bearing — treat them as foundational references to design around, not as today's competitive front line.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to white cell differential methods, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Becton, Dickinson and Company | Wardlaw Partners | 19 |
| Becton, Dickinson and Company | WARDLAW STEPHEN CLARK | 11 |
| Becton, Dickinson and Company | LEVINE ROBERT AARON | 11 |
| Wardlaw Partners | WARDLAW STEPHEN CLARK | 11 |
| Wardlaw Partners | LEVINE ROBERT AARON | 11 |
| WARDLAW STEPHEN CLARK | LEVINE ROBERT AARON | 11 |
| Becton, Dickinson and Company | WARDLAW STEPHEN C | 10 |
| Becton, Dickinson and Company | LEVINE ROBERT A | 10 |
The strongest co-filing pairs in this data set are concentrated around a small number of related entities, with 10 co-assignee pairs recorded overall — a sign of licensing or joint-development relationships clustered at the top of the ranking rather than spread across the field.
Who holds the ranked positions, and where the gaps sit
The assignee ranking returned by this dataset covers 36 companies, counted in records — it is the full ranking the data endpoint returns, not a top-50 or top-100 cut.
One assignee sets the floor for freedom-to-operate work
The leading assignee alone accounts for 93 of the 266 records in scope, well ahead of fifth place at 16 and tenth place at 9. Any new filing strategy in this space should map against the leader's claims first.
A steep drop after the top ten
Filing counts fall away quickly outside the top ten — fifth place holds 16 records and tenth place holds 9, after which the ranking thins into single-digit and single-filing entrants. That tail is where smaller instrument makers and academic assignees sit.
Collaboration clusters around the largest holders
The strongest co-assignee pairs in the data link the leading hematology-analyzer holder with related partnership and individual-inventor entities, suggesting long-running joint development rather than one-off cross-licensing.
| Assignee | Recent year | YoY |
|---|---|---|
| Iris International Inc | 0 | — |
| Abbott Laboratories | 0 | — |
| Becton, Dickinson and Company | 0 | — |
| Wardlaw Partners | 0 | — |
| Beckman Coulter Inc | 0 | — |
| Accellix Ltd | 0 | — |
| Coulter Electronics | 0 | — |
| Coulter International Corporation | 0 | — |
Where to take this next
The dataset points to a concentrated core and a thinner set of adjacent branches. Two ways to act on that.
Map the leader's claim boundaries
Before filing on core differential-counting methods, work through the leading assignee's granted claims to find where its coverage actually stops rather than assuming the field-wide average concentration applies evenly.
Explore assignee claims in EurekaTest the under-claimed branches
Optical path design, image-processing for blast flagging and staining chemistry all show materially lower filing density than the core method — worth a focused search before ruling out room to file.
Run a white-space search in EurekaFrequently asked questions
The assignee ranking in this dataset is led by a single company with 93 of the 266 records in scope, well ahead of the fifth-ranked assignee at 16 and the tenth-ranked assignee at 9. The top five ranked assignees together hold 197 records, or 74.1% of all 266 records, and the top ten hold 93.6%. That means most freedom-to-operate analysis in this field should start with the leading holder's portfolio rather than treating filings as evenly spread across the market.
Material analysis and testing (IPC class G01N) appears in 94.7% of the 266 records in scope, making it by far the dominant classification. Mixing apparatus (B01F, 8.6%), lab apparatus (B01L, 7.5%) and bioreactor or enzyme apparatus (C12M, 5.3%) follow well behind, with optics (G02B) and image processing (G06T) each under 4%. Because a single record can carry several IPC classes, these shares add up to more than 100%, and they should be read as coverage intensity rather than a breakdown of the whole field.
Filing activity in this dataset ran from 6 records in 2017 to a peak of 13 in 2023, with the count tapering toward the 2026 data cut-off. A precise growth rate is not computable from this data because fewer than four complete years remain once publication lag is accounted for, and the 2025-2026 figures will read artificially low simply because publication typically lags filing by around 18 months. Readers should treat the last one to two years of any trend chart as provisional rather than a real drop-off.
The clearest gaps sit outside the core G01N measurement method, in branches such as optical path design for scatter and fluorescence detection, image-processing algorithms for blast flagging, and the decision logic that sets manual-review rates for abnormal samples. These branches carry visibly lower filing density than the core differential-counting method itself, which suggests the underlying technique is well claimed but the tooling and software layers around it are not. Any team considering these areas should still run a freedom-to-operate check, since low density is not the same as no prior art.
US20230314296A1, filed by Shenzhen Mindray Bio-Medical Electronics and published in October 2023, describes a sample analysis system that links a hematology analyzer, a controller, a transport device, a slide-preparation device and an image-capture device. Its distinguishing feature is the routing logic: when an initial analyzer result meets a preset condition, the system automatically moves the sample to slide preparation and imaging rather than issuing the automated result. For competitors, this is a workflow-level claim on the automated-to-manual-review handoff, not a claim on the underlying differential-counting method itself.
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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.