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Checklist Plug-and-play starting point AI & Automation

Checklist: AI-Assisted Submission Content Review

A plug-and-play review checklist a qualified author or approver runs before AI-assisted content enters a regulatory submission: grounding, claim traceability, numeric and citation verification, human authorship, records, and change control, with pass/fail/NA and a signoff.

Document type: Checklist

Read and copy the template below into your own quality system. It is a generic starting point for your own internal use, provided as is, with no warranty; see the Terms and License. Adopting it does not by itself create compliance.

This is a ready-to-use checklist a qualified author or approver runs before AI-assisted content enters a regulatory submission. It is the last gate that confirms the content is grounded, every claim traces to a verified source, the high-risk specifics were checked, a named human authored and owns it, and the records and change controls are in place. Mark each item pass, fail, or N/A with a note, and do not release content with any open fail. Replace every <<FILL: ...>> placeholder with your own specifics. A filled specimen follows. Verify each cited regulation against the current source before you rely on it.

Checklist control

FieldEntry
Checklist titleAI-Assisted Submission Content Review
Document number<<FILL: CHK-ID, e.g. CHK-AIRA-002>>
Version<<FILL: version>>
Content deliverable<<FILL>>
Program / product<<FILL>>
Reviewer<<FILL>>
Date<<FILL>>

1. Classification and system

#ItemP/F/NANoteReference
1.1The AI use is classified (internal intelligence, assistive draft, or conformance check), not direct-to-recordSOP 5.1
1.2A named human author is recorded as accountable11.100
1.3The AI system and version that produced the draft are recordedsupplier assessment
1.4The content was grounded in the correct source documents by retrievalSOP 5.3

2. Claim traceability and accuracy

#ItemP/F/NANoteReference
2.1Every factual claim traces to a named source that actually supports itALCOA+
2.2Every numeric value (limits, results, doses, dates, identifiers) was verified against source individually5.3
2.3Every regulatory citation was checked against the primary reference5.3
2.4Any statement the model flagged uncertain was resolved from source, not left as the model’s guess5.3
2.5No fluent-but-unsupported statement remains (no plausible prose standing in for a checked fact)5.3

3. Human authorship

#ItemP/F/NANoteReference
3.1The author performed a substantive review, not a rubber stamp (editing extent recorded)5.4
3.2The author is trained on the AI’s known failure modes5.4
3.3The content is approved through the controlled document workflow with a Part 11 signature11.50, 11.70

4. Records and change control

#ItemP/F/NANoteReference
4.1A record of the AI involvement (system, version, sources, authoring, review) is retained, scaled to risk5.5
4.2Drafts and source links live in the controlled document system, not an AI tool’s chat history5.5
4.3If this content is a labeling change, it went through controlled change management, not AI output alone5.6
4.4If the vendor model changed since last use, a known-content re-check was completed5.6

5. Signoff

FieldEntry
All items pass or are justified N/A<<FILL: Yes/No>>
Open fails (must be zero to release)<<FILL>>
Reviewer signature and date<<FILL>>
Approver signature and date<<FILL>>

6. References

21 CFR Part 11, sections 11.50, 11.70, 11.100; ALCOA+ data-integrity attributes. FDA draft guidance on AI to support regulatory decision-making (January 2025, draft); EU draft Annex 22 on artificial intelligence (7 July 2025, not in force).

Confirm the current version and status of each reference before issue.


Filled specimen

The following shows section 2 completed for an example CMC quality summary section, so you can see the expected detail. The values are illustrative; replace them with your own.

#ItemP/F/NANote
2.1Every factual claim traces to a supporting sourcePass41 claims, each mapped to the development report or specification
2.2Every numeric value verified individuallyFail then PassSpecification limit for an impurity read 0.20% in the draft; source said 0.15%; corrected and re-verified
2.3Every regulatory citation checkedPass2 citations, both confirmed against the primary reference
2.4Uncertain statements resolved from sourcePass1 flagged value supplied from the batch record
2.5No fluent-but-unsupported statement remainsPassFull read against source completed

In this example item 2.2 caught the single most dangerous AI failure on regulatory content: a confident, well-written but wrong specification limit. The reviewer did not release until the value was corrected against source and re-verified, which is exactly why the individual numeric check is a hard gate rather than a skim.

Common inspection findings this checklist prevents

  • A wrong specification limit or result in fluent text that no one checked against source.
  • A fabricated or mis-numbered citation reaching a submission.
  • Content approved with a nominal author who did not actually verify the substance.
  • A labeling change driven by AI output without controlled change management.

How to adapt this checklist

  1. Point the reference column at your own SOP section numbers.
  2. Keep item 2.2 as a hard gate: no numeric value ships unverified.
  3. Add rows for content-type-specific checks (for example a redline completeness check for labeling).
  4. Require zero open fails before release, and record any N/A with a reason.
  5. Confirm every regulation in section 6 against the current published version and status before issue.
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