Efficient sample management starts by mapping how samples actually move through your lab—from collection or receipt to processing, storage, transfer, and final disposition. Then make identity, custody, location, and status visible at each handoff; assign ownership for exceptions; and use milestone data to find delays and rework. A LIMS, barcodes, and instrument integrations can support that workflow, but none guarantees efficiency on its own.
What sample management in a LIMS covers
Sample management is the set of records and procedures that lets a lab identify, locate, route, process, and account for each sample throughout its lifecycle. In a LIMS, that commonly means recording intake, custody, processing activities, milestones, and location. The National Institute of Justice (NIJ) recommends tracking samples throughout the analysis lifecycle and using LIMS data to identify trends and bottlenecks (NIJ, National Best Practices for Improving DNA Laboratory Process Efficiency).
The underlying principles apply across research, bioanalytical, genomics, and forensic labs, but the required records and controls depend on the work and applicable quality system. A peer-reviewed set of recommendations for regulated bioanalysis emphasizes continuity of chain of custody from collection through disposal, as well as defined storage locations and conditions (Global Bioanalysis Consortium recommendations).
Map the real lifecycle before changing it
Document the path samples take today, including handoffs, queues, exceptions, and workarounds. A process map should describe actual practice rather than an idealized sequence; otherwise, software requirements may miss the steps that cause delays or errors. NIJ recommends detailed process mapping to help define LIMS needs.
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- List each lifecycle stage. Start at collection or receipt and include accessioning, preparation or aliquoting, testing, storage, transfers, and disposal where applicable.
- Mark every handoff and waiting point. Record who receives or releases the sample, where it goes, and what must happen before the next step can begin.
- Capture exceptions. Include rejected or incomplete submissions, relabeling, repeat work, equipment downtime, and other deviations that occur in the lab.
- Identify the records and systems involved. Note labels, paper forms, spreadsheets, instruments, and software used at each stage, including where information is entered more than once.
For a LIMS project, include infrastructure, barcoding, instrument and other system integrations, consumables, quality controls, legacy data, and backups in the planning map, as NIJ recommends.
Make identity, custody, and location reconstructable
At each important event, the record should let staff establish which sample was involved, who handled it, when and where the event occurred, and what happened. Define a unique identifier and the minimum information required at each handoff. Depending on the lab’s process, that may include operator, event time, location, status, and a reason for a change or exception.
Preserve lineage when a sample is divided, pooled, extracted, or otherwise transformed. A parent-to-derivative relationship helps staff trace results and handling history back to the originating material. Treat custody and lineage as workflow data, not as notes that are difficult to search or reconcile later.
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Storage and disposition also belong in the traceability record. Define storage locations and conditions; record moves; and, when relevant, retain traceable temperature monitoring and alerts. Document final disposition, including disposal, in a way consistent with the lab’s procedures and quality requirements. The bioanalysis recommendations address these controls, but their application should be interpreted in the context of the lab’s field and obligations.
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Assign ownership at handoffs and exceptions
Visible task status is useful only if someone is responsible for acting on it. Assign ownership for intake checks, exception resolution, storage moves, and disposition. In the LIMS or associated procedures, make it clear which queue or person is responsible, what information is needed to proceed, and how unresolved work is escalated. Specific roles and escalation rules are lab-specific; the goal is to avoid samples waiting in an unowned queue.
Review recurring exceptions for process or training causes. If a handoff repeatedly fails, clarify the procedure, revise the workflow, or provide focused training. Manage changes through the controls appropriate to the lab’s quality system.
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Use barcodes and automation where they fit the process
Barcodes can reduce manual lookup and transcription, but they work best as part of a defined workflow connected to the authoritative sample record. NIJ describes barcoding as a potential LIMS peripheral and cautions that the effect depends on the system selected and how its functions and peripherals are incorporated. A label and scanner alone do not fix unclear identifiers or poorly designed handoffs.
Before choosing barcode equipment, test labels and scanning on the lab’s actual containers and under its conditions. Check:
- Adhesion and readability on each relevant container type.
- Resistance to the storage temperatures and chemical exposure the label will encounter.
- Compatibility between scanners, label formats, and the LIMS workflow.
- Whether printing and reprinting are controlled and linked to the authoritative sample record.
Automate repetitive transfers or instrument interfaces when the integration is useful and has been validated for the intended workflow. Vendor descriptions of integrations or automated transfers are capability claims, not evidence of a guaranteed time saving in a particular lab.
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Measure delays before and after changes
Choose a local baseline before changing a process. Track timestamps at meaningful milestones so the lab can distinguish time spent processing from time spent waiting. NIJ recommends reviewing LIMS metrics to guide resources, monitor processing times at milestones, find bottlenecks, and assess whether mitigation plans worked.
Useful measures depend on the workflow, but may include:
- Elapsed time between defined milestones, such as receipt and accessioning or preparation and testing.
- Backlog by stage, including how long work has waited.
- Rework and exception rates, with reasons where recorded.
- Throughput over a stated period and for a clearly defined workflow or sample population.
Compare like with like: state the measurement period, workflow, denominator, and intervention when reporting a change. Check whether a shorter wait at one stage simply moved the queue downstream. The reviewed guidance does not establish a general efficiency percentage that applies to every lab.
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Choose a LIMS against documented needs
Write requirements from the process map before comparing feature lists. Include sample types and lifecycle stages, identifiers and derivative lineage, storage hierarchy, instruments and business-system interfaces, user roles, audit needs, reports, and expected throughput. For regulated work, ask the lab’s quality and compliance leads which obligations apply; there is no single compliance specification that fits every setting.
NIJ recommends considering requirements, projected customization and costs, user-acceptance testing, training, implementation, future growth, maintenance, and IT support. A cross-functional planning group helps surface operational, quality, scientific, and technical needs before purchase.
For genomics and other complex workflows, Illumina’s LIMS guidance lists sample tracking, automation, integrations, configurability, compliance-support features, scalability, and role-appropriate interfaces as selection considerations (Illumina Clarity LIMS). This is vendor guidance, not an independent comparison of products. Agilent describes SLIMS features such as workflow and sample management, barcode design, lineage, audit trails, instrument integration, and workflow visibility (Agilent SLIMS); those descriptions likewise do not demonstrate measured savings or comparative performance.
Use a consistent set of questions to compare systems or process designs:
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- Can it preserve identity, custody, location, and derivative lineage?
- Does it integrate with the required barcode, instrument, and business systems?
- Can the lab configure it as protocols change, and what support or customization is required?
- Are auditability and controls appropriate to the lab’s work?
- What implementation, training, maintenance, and ongoing IT support will be needed?
- Can its reports show milestone times, exceptions, throughput, and bottlenecks in a useful way?
Include the cost and effort of adoption, not just software capabilities. User acceptance, training, legacy-data migration, backups, and long-term maintenance all affect whether a system supports the workflow in practice.
Quick Recap
Turn the findings into a controlled improvement cycle
- Map and baseline. Document the actual lifecycle and record current milestone times, backlogs, rework, and exceptions.
- Prioritize a specific bottleneck. Use the evidence to choose one handoff, queue, or repeat failure to address rather than automating every step at once.
- Define the change and ownership. Specify the process, roles, records, and any software, label, or integration changes required.
- Test with users. Use acceptance testing and training appropriate to the change; confirm that staff can complete normal and exception paths.
- Review the result. Compare the same measures over a stated period and verify that the delay was reduced without creating a new one elsewhere.
- Maintain and revise. Keep procedures, system support, and change control current as sample types, protocols, or throughput evolve.
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