7 Checks to Find Gaps in Your Sample Oversight

Your sites, CROs, and labs each manage part of the sample journey.

But can your team see where information is missing or inconsistent between them? Use these seven checks to identify gaps that could put samples, study timelines, and confidence in your data at risk.

For each check, consider whether your team can answer confidently using current records, or whether someone needs to reconcile spreadsheets, search vendor portals, or chase an update. Those manual checks can reveal where oversight depends on a person connecting the pieces.

1. Can you follow a sample from collection through testing and link it to its result? Check whether identifiers and records match across sites, labs, and study systems. Gaps can make it difficult to establish what happened to a sample or which result belongs to it.
2. Can you identify a missing or out-of-window collection while there is still time to investigate and act? Check how expected collections are compared with reported collections, how quickly gaps become visible, and who receives the alert.
3. Can your team use incoming lab data without rebuilding spreadsheets each time? Check how formats, sample identifiers, and metadata are standardized across vendors. Differences that remain unresolved can carry into downstream reviews and analysis.
4. When a discrepancy appears, is someone responsible for acting on it before it affects downstream work? Check how mismatched identifiers, incomplete records, and potential protocol issues are flagged, assigned, and escalated.
5. Can you confirm whether a sample’s consent permits its intended use before selecting it for testing? Check whether current consent information is linked to the sample record and whether restrictions or missing documentation are visible to the team making that decision.
6. Can you spot recurring delays or data gaps across labs and studies? Check whether vendor performance is assessed using consistent definitions and reporting periods, so your team can identify patterns and decide where to intervene.
7. Can everyone involved see who owns a sample-related query, its status, and how it was resolved? Check whether the query remains linked to the affected sample record, with a clear resolution history, rather than being scattered across email and separate trackers.

_{*QuartzBio Case Study https://quartz.bio/case-study/how-a-top-5-pharma-doubled-clinical-trial-capacity-of-existing-teams/}

If several answers to these checks require someone to search, reconcile, or chase information, those are useful places to examine first. Prioritize gaps that could affect an irreplaceable sample, an upcoming readout, or a study milestone.

QuartzBio Sample Intelligence connects sample data across systems and vendors, standardizes incoming formats and identifiers, and helps teams identify discrepancies earlier.

See how QuartzBio could help address the gaps you identified.