How do I set up sample tracking software for plates and barcodes across a multi-user synthetic biology lab?

Here’s a practical way to set up sample tracking software for plates and barcodes in a multi-user synthetic biology lab.

1) Start with the workflow, not the software

Before choosing tools, map the full lifecycle of a sample:

• Receipt / creation: where does the sample first enter the system?
• Aliquoting / plating: how are plates and wells generated?
• Transfers: when samples move between tubes, plates, freezers, incubators, or instruments
• Processing steps: PCR, transformation, sequencing, glycerol stocks, etc.
• Storage: freezer box, rack, shelf, incubator, plate stack
• Consumption / disposal: when a sample is used up or discarded

For each step, define:

• unique sample identifiers
• who can create/edit records
• what must be scanned
• what metadata is required
• what events are logged automatically

2) Use a hierarchical object model

For plates and barcodes, the cleanest model is usually:

• Project
  • Sample
    • Container
      • tube / plate / well / box position
  • Aliquot
  • Derived sample
  • Event log

A good setup usually distinguishes:

• sample identity: what the biological material is
• physical container: where it is
• location: where the container is stored
• history/events: how it got there

For plates

Represent plates as:

• plate-level object with barcode
• well-level objects with coordinates: A1–H12, etc.
• optional child samples in each well

For barcodes

Use barcodes for:

• tubes
• plates
• racks/boxes
• maybe even instrument runs if needed

Best practice: every physical item gets a unique, non-reusable barcode.

3) Define barcode standards

Pick one barcode format and enforce it.

Recommended rules:

• Use a standard symbology like Code 128 for 1D or DataMatrix/QR for compact labels
• Encode only an internal ID, not human-readable metadata
• Human-readable text on label should be short and redundant
• Make barcodes globally unique across all items
• Never recycle barcodes

Typical label contents:

• barcode ID
• object type: sample, plate, box
• optional short project code
• optional check digit

Example:

• PLT-00018472
• TUBE-00922311
• BOX-00004491

If you expect small tubes and harsh lab conditions, DataMatrix is often better than QR because it can fit on tiny labels.

4) Choose software that supports audit trails and multi-user control

For a multi-user synthetic biology lab, the software should have:

• role-based access control
  • admin
  • scientist
  • technician
  • read-only
• immutable audit trail
  • who changed what and when
• barcode scanning support
  • handheld scanner or webcam
• plate maps
  • well-level tracking
• location tracking
  • freezer, shelf, rack, box, slot
• sample lineage
  • parent/child relationships
• API or import/export
  • for LIMS integration, sequencing, automation
• concurrency controls
  • avoid two users editing the same item incorrectly

If you’re deciding between commercial and open-source:

• Commercial LIMS: faster to deploy, more support, higher cost
• Open-source / custom: more flexible, lower license cost, more setup burden

5) Design the database around events, not just current state

A common mistake is only storing “current location.” Better is to store both:

• current state
• full event history

Track events like:

• created
• received
• labeled
• moved
• aliquoted
• plated
• scanned in/out
• consumed
• discarded
• thawed/refrozen

This helps with:

• traceability
• mistake recovery
• regulatory compliance
• debugging experimental issues

6) Set up plate handling conventions

For plates, standardize:

• plate type: 96-well, 384-well, deep-well
• orientation: where A1 is
• well naming convention
• accepted statuses:
  • empty
  • loaded
  • incubating
  • sealed
  • archived
  • used
• whether wells can contain:
  • one sample only
  • pools
  • mixed populations

Also define what a “plate sample” means:

• Is each well a distinct sample?
• Is the whole plate one assay unit?
• Do you need both?

Usually you want both:

• plate as a container
• wells as child containers/aliquots

7) Make scanning mandatory at key transitions

To reduce manual errors, require barcode scans for:

• sample receipt
• plate creation
• moving storage location
• entering/exiting freezer
• starting/ending assays
• disposal
• transfer between users or benches

Minimize typing by using:

• scanners that act like keyboards
• prefilled forms
• dropdowns for common metadata
• plate-map batch entry

8) Handle multi-user permissions carefully

In a shared lab, define ownership and locking rules.

Suggested approach:

• Samples belong to a project and optionally a custodian
• Users can:
  • view all project samples
  • edit only samples they own or are assigned to
  • move shared samples if authorized
• Critical actions require confirmation:
  • destroy sample
  • overwrite metadata
  • merge records
• Use checkout/lock status for plates being actively processed

9) Integrate storage location tracking

Set up a location hierarchy:

• building
  • room
    • freezer
      • rack
        • box
          • position
    • incubator
      • shelf
      • stack position
    • bench area

Each storage unit should ideally have a barcode too. Then samples can be moved by scanning:

1. sample barcode
2. destination location barcode

This reduces location ambiguity and enables fast inventory checks.

10) Support batch operations

Synthetic biology labs often work in batches. Your software should support:

• creating many samples from one source
• plate transfer maps
• bulk relabeling
• bulk status updates
• import from CSV
• export to CSV/Excel
• copying metadata across wells or samples

For example:

• create 96 derivatives from one parental strain
• generate plate maps from a design file
• upload sequencing results linked to sample barcodes

11) Connect to instruments and automation if needed

If you use liquid handlers, plate readers, thermocyclers, or sequencers:

• link run IDs to sample/plate barcodes
• import output files automatically
• store instrument metadata
• map results back to wells/samples

For automation, expose an API so robots can:

• reserve plates
• read/write barcodes
• update sample states
• record transfer events

12) Set up SOPs and training

Software alone won’t fix tracking problems. Write short SOPs for:

• labeling new samples
• scanning procedures
• plate creation
• aliquot creation
• movement between locations
• handling damaged/unreadable barcodes
• correcting mistakes

Train all users on:

• barcode placement on tubes and plates
• using scanners correctly
• not creating duplicate records
• when to escalate issues

13) Run validation before full rollout

Test with a small pilot:

• one project
• one freezer
• one plate format
• 2–5 users

Validate:

• barcode readability
• scan speed
• duplicate prevention
• location accuracy
• plate/well mapping
• permissions
• audit logs

Then expand gradually.

14) Build in error recovery

You will eventually have:

• damaged labels
• unreadable barcodes
• wrong scans
• missing records
• duplicate entries

Plan for:

• reprint with audit trail
• barcode aliasing only when necessary
• manual override with approval
• discrepancy reports
• periodic inventory reconciliation

15) A good minimal implementation

If you want a simple but robust starting point:

• Database: PostgreSQL
• App: web-based front end
• Authentication: lab email/SSO
• Barcode: DataMatrix or Code 128
• Scanner: USB barcode scanner
• Entities:
  • projects
  • samples
  • plates
  • wells
  • locations
  • events
  • users/roles
• Features:
  • create sample
  • print label
  • scan move
  • plate map view
  • audit log
  • CSV import/export

Recommended rollout plan

1. Map your lab workflow
2. Choose barcode format and labeling rules
3. Define sample/container/location data model
4. Implement or configure software
5. Pilot with one team
6. Add plate maps and batch tools
7. Integrate storage and instruments
8. Train everyone and enforce SOPs
9. Audit and improve monthly

If you want, I can also help you with one of these next:

• a database schema for samples/plates/barcodes
• a software feature checklist
• a barcode labeling standard
• a workflow diagram for a synthetic biology lab