PHG · REV 2026.10 For laboratory research use only. Not medical or dosing guidance.
Peptide Handling Guide Storage, handling and documentation for research peptides
Document
QA-08
Section
Documentation & quality
Revised
Sources checked

Lot Traceability: Connecting Results to Material

Every vial, aliquot and result should trace back to a lot and its certificate. How to set up a simple traceability chain in a research lab and why it pays off when results change.

2 min read

Bench card

  • Traceability means you can follow material from supplier lot to experiment, and back.
  • Carry the lot number through every derived container: solution, aliquot, dilution.
  • Record which lot and aliquot each experiment used.
  • When results shift, lot records let you test whether the material changed.
  • Keep the COA, receipt record and preparation records together by lot.

Traceability is the ability to follow a piece of material forward from the supplier’s lot to every experiment that used it, and backward from any result to the exact material behind it. It is the difference between “the peptide stopped working” and “aliquots from lot B prepared on 3 March show a new oxidation peak”.

The chain

  1. Supplier lot, with its COA.
  2. Receipt record: date, condition, storage location.
  3. Stock solution: ID, lot, preparation details.
  4. Aliquots: IDs derived from the stock ID, with box positions.
  5. Experiments: which aliquot, on which date.

Each link is a record that names the one before it. If any link is missing, the chain breaks at that point.

A simple ID scheme

Level Example ID Built from
Lot L24-0381 Supplier’s lot number
Stock solution L24-0381-S1 Lot + stock number
Aliquot L24-0381-S1-07 Stock + aliquot number

Short IDs fit small labels, and the structure lets anyone reconstruct the chain from a single tube.

When results change

When an assay drifts or fails, traceability turns a guess into a test. Pharmaceutical manufacturers follow a formal process for out-of-specification results, described in FDA guidance, that starts by checking for laboratory error before suspecting the material. A research lab can follow the same logic:

  1. Check the experiment: reagents, instruments, calculations.
  2. Check the material’s history: which lot, which stock, how old, how many thaws, any excursions.
  3. Compare with another aliquot, another stock or another lot.
  4. If needed, test the material by HPLC and MS and compare with the COA.

Switching lots

Lots differ. When moving to a new lot mid-project, record the change, and consider a side-by-side comparison in your assay. Keeping a reference vial of the earlier lot at −80 °C makes this possible later.

References

  1. US FDA. Good Laboratory Practice for Nonclinical Laboratory Studies, 21 CFR Part 58. eCFR
  2. US FDA. Current Good Manufacturing Practice for Finished Pharmaceuticals, 21 CFR Part 211. eCFR
  3. ICH Q7. Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients (including section 11.4, Certificates of Analysis). International Council for Harmonisation, 2000. ICH
  4. US FDA. Investigating Out-of-Specification (OOS) Test Results for Pharmaceutical Production. Guidance for Industry. FDA
  5. US FDA. Data Integrity and Compliance With Drug CGMP: Questions and Answers. Guidance for Industry; 2018. FDA

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