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.