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Run your analysis now →https://www.patsnap.com/resources/blog/rd-blog/preanalytical-error-reduction-patent-landscape/ · Patsnap · data cut-off 2026-07-31 · downloaded from the live page
Patent Landscape · Preanalytical ProcessingPreanalytical Error Reduction Patents: Who Holds the Ground and Where It's Still Open
- 22 published records total, with filings peaking at 8 in 2017 and tapering since — a narrow, still-forming field rather than a saturated one.
- 77.3% of records sit in G01N (material analysis & testing), while business-process classes like G06Q hold 36.4% — sample-quality logic and workflow/tracking claims are being filed side by side.
- The ranked leader holds 10 records versus 1 at fifth place, a steep drop-off that leaves most named assignees with a single filing each.
22
Published Records
US
Leading Jurisdiction
8
Active Filers Ranked
2017
Peak Filing Year
Published byPatsnap Research··7 min readSourced from Patsnap Eureka
Field Overview
What the preanalytical error reduction patent record shows
Preanalytical error reduction covers the steps before a sample ever reaches an analyzer: correct labelling, adequate volume, avoiding clotting or hemolysis, and tracking errors back to a training or process cause. The 22 records in scope, filed between 2015 and 2026, sit at the intersection of laboratory instrumentation and workflow software rather than in a single well-defined art unit. That split shows up directly in the IPC composition, where material analysis and testing (G01N) and business-process data handling (G06Q) both carry a substantial share of the same record set.
Filing activity peaked in 2017 at 8 records and has declined since, with the most recent year necessarily undercounted because publication typically lags filing by around 18 months. Read the trend as a field that had an early burst of activity around sample-integrity sensing and has not yet produced a second wave, rather than as a technology in decline.
Filing activity by year, 2015-2026
Source: Patsnap Eureka. Assignee ranking and totals. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Data & Trends
Filing trend and technology composition
The dataset covers 22 published records filed between 2015 and 2026, drawing on the eight IPC subclasses assigned across them and the receiving offices where applicants sought protection.
Filings rose to an early peak, then thinned out
Filings climbed to a peak of 8 records in 2017. Volume has been lower and more irregular in the years since, and the 2026 figure is partial because of publication lag — treat the last one to two years on the chart as a floor, not a ceiling.
Sensing and workflow logic dominate, therapeutics barely feature
G01N (material analysis and testing) appears in 77.3% of the 22 records, confirming that most claims are anchored in detecting a sample-quality problem rather than treating one. A61B (diagnosis and surgery), A61J (containers for medicine) and G06Q (business/admin data processing) each cover more than a third of records, showing that container design and process-tracking software are being claimed almost as often as the sensing step itself. A61P (therapeutic activity), by contrast, touches only 4.5% of records — this field is about catching errors, not compounds.
Shares are the percentage of the 22 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.
Go deeper on Preanalytical Error Reduction with Eureka
This page is one run against one query. Ask Eureka your own question about preanalytical error reduction and every answer comes back with the patent numbers behind it.
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The most-cited patent in this dataset
Highest-cited record
US20180059006A1 — Systems, apparatus, and related methods for evaluating biological sample integrity
ABBOTT LABORATORIES
Systems, apparatus, and related methods for evaluating biological sample integrity are disclosed herein. An example method includes scanning a sample container having a sample disposed therein to generate signal data including a first signal portion and a second signal portion. The example method includes detecting if the sample container includes a label attached to a surface of the sample container based on the second signal portion. If the sample container includes a label, the example method includes applying an adjustment factor to the second signal portion to create adjusted signal data. The example method includes determining a property of the sample based on one or more of the first...Filed by Abbott Laboratories, published 2018-03-01, cited 24 times — by far the most-cited record in this set.
Most-cited records
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20180059006A1 | Systems, apparatus, and related methods for evaluating biological sample integrity | 24 |
| 2 | US10648905B2 | Systems, apparatus, and related methods for evaluating biological sample integrity | 2 |
Citation counts reward older filings that have had more time to accumulate citations within the searched corpus; treat them as a signal of influence, not of current importance.
Publication numbers are shown where the record carries one (2 of 2 rows); clicking a row searches Eureka by that number.
Source: Patsnap Eureka. Citation counts and representative records. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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What the numbers mean for a filing decision
Three patterns stand out once the assignee ranking, IPC composition and citation data are read together.
Concentration
10 vs 1
leader vs fifth-ranked assignee
One filer, then a steep drop
The ranked leader holds 10 of the records in the assignee ranking, while the fifth-placed name holds just 1. That gap, combined with a field of only 8 ranked companies, means most of the activity outside the leader is single-filing entrants — academic bodies and small teams testing a specific claim rather than building a portfolio.
Based on the 8-company assignee ranking
Citation weight
24 citations
on the top-cited record
One sensing patent carries most of the citation weight
US20180059006A1, an Abbott sample-integrity scanning patent, is cited 24 times against 2 for the next record on the list. That imbalance points to a single foundational claim on optical/signal-based sample scanning that later filers had to cite around, rather than a broadly cross-cited field.
Most-cited records table
Technology split
77.3% vs 36.4%
G01N vs G06Q share of 22 records
Sensing claims outnumber workflow claims, but not by much
G01N covers 77.3% of the 22 records while G06Q (business/admin data processing) covers 36.4% — meaning more than a third of records combine a sample-quality sensing step with tracking or administrative logic. A filer targeting only the sensing side risks missing the workflow layer that competitors are claiming alongside it.
IPC subclass shares, 22 records
Eureka AI Agent
Looking for what nobody has claimed yet?
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to preanalytical error reduction, with the prior art for and against each one.
Source: Patsnap Eureka. Co-assignee relationships and derived observations. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
Players & Momentum
Who is filing, and where activity has gone quiet
The assignee ranking returns 8 companies and research bodies, spanning a diagnostics major, an early-stage sample-quality start-up, a university research office, and several individual academic inventors filing jointly.
Leader
10 records
ranked filings
A single diagnostics major holds the largest share
The top-ranked assignee accounts for 10 of the records in the ranking, more than the next four combined. Its filings anchor the G01N sensing cluster, including the most-cited patent in the set.
Assignee ranking, 8 companies
Momentum
0 in latest year
across every ranked assignee
No ranked assignee filed in the most recent complete year
Every named assignee in the momentum data, including the two with recorded -100% year-on-year change, shows zero filings in the latest year. That reads as a field between waves rather than one with an active leader currently pressing an advantage — though publication lag means the newest filings may not be visible yet.
Recent-year momentum by assignee
Long tail
1 record
fifth-ranked assignee
Academic co-filers cluster around individual claims
Several of the ranked names are individual academic inventors or a single institute, connected through co-assignee pairs such as V Malarvizhi with R J T Nirmalraj, Hindustan Institute of Technology & Sciences, and D Sangeetha. These look like discrete research outputs rather than a sustained filing programme.
10 co-assignee pairs recorded
Recent-year filing momentum by assignee
| Assignee | Recent year | YoY |
|---|---|---|
| Abbott Laboratories | 0 | — |
| REDDROP DX INC | 0 | -100% |
| Board of Governors of Colorado State University | 0 | -100% |
| V MALARVIZHI | 0 | — |
| R J T NIRMALRAJ | 0 | — |
| HINDUSTAN INST OF TECH & SCI | 0 | — |
| D SANGEETHA | 0 | — |
| ALBERT JEYADEVA D | 0 | — |
Source: Patsnap Eureka. Assignee-level momentum. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
What's Next
Where to take this analysis
The landscape points to a concentrated sensing claim at the top and a thin, quiet tail beneath it. Two directions follow from that.
Map the workspace around the top-cited claim
US20180059006A1's label-detection and signal-adjustment approach is the most-cited claim in the field. Before filing anything touching sample-container scanning, work out precisely what its claim scope covers and where an alternative sensing method would sit outside it.
Explore this patent in EurekaTest the under-claimed workflow branches
G06Q-classed process-tracking and G06T-classed imaging approaches to mislabelling appear far less often than G01N sensing claims. Running a freedom-to-operate check on a specific workflow or imaging angle is a faster way to find open claim space than competing directly in sensing.
Run a white space search in EurekaSource: Patsnap Eureka. Forward-looking reading of the same dataset. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
FAQ
Common questions about preanalytical error reduction patents
This dataset contains 22 published records filed between 2015 and 2026, covering methods for detecting mislabelled specimens, insufficient sample volume, clotting, hemolysis, and related workflow or training-based error tracking. That is a small, specific field rather than a broad one, and the assignee ranking returns only 8 companies and institutions in total. Because publication typically lags filing by about 18 months, the true count for the most recent one to two years will be higher than currently shown.
The ranked leader holds 10 of the records in the 8-company assignee ranking, well ahead of the fifth-placed assignee at just 1. The rest of the ranking is made up of a diagnostics-focused start-up, a university research office, and individual academic inventors who often co-file together rather than building standalone portfolios. This steep drop-off after the leader suggests one company has established an early, still-uncontested position in sample-integrity sensing.
The dominant IPC subclass is G01N, material analysis and testing, appearing in 77.3% of the 22 records and covering sensors and methods for judging sample condition. A61B (diagnosis and surgery), A61J (containers for medicine) and G06Q (business and administrative data processing) each appear in more than a third of records, showing that container design and error-tracking software are claimed nearly as often as the core detection step. Therapeutic-compound claims under A61P are rare, appearing in only 4.5% of records, confirming this is a detection-and-workflow field rather than a treatment one.
Filing activity peaked at 8 records in 2017 and has been lower and irregular in the years since, with 2026 showing no filings so far. That decline should be read cautiously: publication lag of roughly 18 months means recent years are always undercounted at the time a landscape is pulled, and there are not enough complete recent years in this dataset to state a reliable growth rate. What the data does show clearly is that no ranked assignee filed in the most recent complete year, suggesting the field is between filing waves rather than in an established growth or decline trajectory.
The gap sits between the heavily claimed G01N sensing space and the comparatively thin G06T (imaging) and G06Q (workflow/tracking) classes, which cover under a fifth and just over a third of records respectively. Combining hemolysis or clotting detection with automated error-to-training feedback loops, or using imaging-based mislabelling detection instead of the label-scanning approach in the top-cited patent, both look under-claimed relative to the core sensing art. A freedom-to-operate search focused on those combinations is likely to surface less prior art than a straight sensing-method filing.
Answers are grounded in the same dataset. Derived from a Patsnap search on Preanalytical Error Reduction covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish.Run this in Eureka MCP
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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.