Samples are typically grouped by patient visit and unique accession numbers that are assigned by the kitting provider.
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This data often serves as a fundamental organizing mechanism behind sample metadata.

Every patient is assigned a unique, anonymous identifier that protects their privacy while making it possible for them to be identified.
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Demographics like DOB and sex are used to demonstrate that a patient meets study inclusion criteria, and can be used to stratify patient data during downstream analysis.

Sponsors and vendors must understand where every patient sample came from so they can accurately track enrollment at each site, address site performance issues, and more.

Labs require collection dates and times for every sample collected so they can ensure that samples were analyzed within the stability period for the assays performed.

Sponsors and labs often require administrative questions to demonstrate inclusion criteria, determine whether reflex / optional testing is needed, etc.

Tissue processing and analysis can be complicated because of the various processing methods and tissue types that can be accepted for clinical research.
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It’s important for labs and sponsors to understand all of the details about a tissue sample so it can be properly processed and analyzed.