Data Integrity in Peptide Testing Laboratories

Data integrity means that analytical records are complete, consistent, accurate, and traceable throughout their lifecycle.

ALCOA principles

Data should be:

• attributable
• legible
• contemporaneous
• original
• accurate

Expanded principles also include completeness, consistency, endurance, and availability.

Raw data

Raw data include more than the final PDF. They may include:

• original instrument files
• chromatographic methods
• integration events
• audit trails
• sample sequences
• calculations
• metadata
• instrument status

Audit trails

Audit trails record changes such as reintegration, deletion, method modification, and reprocessing. Review should be risk-based and timely.

User access

Shared accounts weaken attribution. Roles should restrict who can acquire, process, approve, or administer data.

Reintegration

Manual integration may be scientifically justified, but it should follow predefined rules and be documented.

Frequently asked questions

Is a printed chromatogram the raw data?

Usually not. Electronic files and metadata may also be part of the raw record.

Can analysts delete failed injections?

Not without controlled procedures and preserved traceability.

Why review sequence tables?

They can reveal unreported injections or selective reporting.

Is data integrity only an IT issue?

No. It is a scientific, procedural, and cultural responsibility.

Key takeaways

Reliable peptide testing requires transparent data generation and processing. Audit trails, controlled access, complete records, and independent review are essential.

References

1. FDA. Data Integrity and Compliance With Drug CGMP: Questions and Answers.
2. OECD Principles of Good Laboratory Practice.
3. ISO/IEC 17025 overview.

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TSMS Labs educational disclaimer: For laboratory research and educational purposes only. Not for human consumption. This content is not medical, clinical, or regulatory advice.