Choosing a biobanking lims or biobank lims: tracking aliquot lineage and freezer position rather than tests, holding consent scope against every vial, what biological sample storage owes in temperature history, and the lims sample management, lims sample tracking and biological sample management questions a general laboratory system does not answer

What the system has to hold

1. Aliquot lineage, from collection to the vial in your hand. A parent specimen becomes aliquots, which become derivatives, which are sometimes re-aliquoted. The system must hold that tree, so that a question about one vial can be answered about its parent, and so that a consent withdrawal reaches every descendant.
2. Position to the box and the slot. Freezer, rack, box and position, with the box map visible. Searching a minus eighty freezer with the door open destroys the samples around the one you are looking for, and a system that stops at the freezer number has not solved the problem it was bought for.
3. Consent scope against every sample, not against the study. Which uses are permitted, under which approval, until when. The question asked of a biobank is always about specific samples and a specific proposed use, and a system that cannot answer it forces a conservative refusal.
4. Temperature history beside the inventory. An excursion affects the samples that were in that unit at that time, so the monitoring record and the inventory have to be joinable. Held in separate systems, an excursion becomes a manual reconstruction at exactly the wrong moment.
5. Request, approval and distribution as a workflow. Biobanks issue material against approved requests, and the record of who asked, who approved, what was shipped and what is left is the audit. Handling that in email and a spreadsheet is where biobank inventories stop matching reality.

Physical audit, and the number nobody wants to measure

Count a sample of boxes against the system and record the discrepancy rate. Every biobank has one, and knowing it is the difference between a collection you can offer to a collaborator and one you hope is right.

Audit after any move, any freezer failure and any change of staff. Those three events account for most of the drift between an inventory and a freezer.

Barcodes and the cold

Labels have to survive liquid nitrogen, frost and handling with gloves, and two-dimensional codes on the vial base read far more reliably than a side label under frost. Retrofitting labelling onto an existing collection is a large project, so decide early.

Scanning at every transfer is what keeps the inventory true. A workflow that relies on someone typing a position is a workflow that will drift.

Planning for the failure

Know where the contents of the largest freezer would go, who moves them and how long it takes, before anything fails. Backup capacity and a written plan are worth more than a better cabinet without one.

Alarms have to reach somebody who can act at three in the morning. An alarm that flashes in an empty room documents a loss rather than preventing it.

Common questions

Why not use a general LIMS for biological sample management?

Because a general system is built around tests and a biobank is built around stored aliquots, their lineage, their consent and their position. Everything works, awkwardly, and the awkwardness compounds at scale.

How detailed does location tracking need to be?

To the position in the box. Anything coarser means searching with the freezer door open, which harms the samples around the target, and it makes a physical audit impossible to complete.

What happens when a donor withdraws consent?

Every sample descended from that donation has to be findable and actioned, which is exactly why lineage has to be held as data. A system that cannot walk the tree makes withdrawal an unverifiable manual exercise.

Should the biobank system hold the analytical results too?

Usually it holds what was measured on a sample and points at the analysis, rather than being the analytical system. Keeping the biobank's job to custody and the laboratory's job to testing keeps both data models honest.

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