A contemporaneous log of AI use across a project. The same record feeds journal disclosure, sponsor audits, and EU AI Act documentation. Build it as you write — reconstruction at submission time is unreliable. For the principles behind this template, see Review and Accountability and Declaring AI Use.Documentation Index
Fetch the complete documentation index at: https://playbook.pharmatools.ai/llms.txt
Use this file to discover all available pages before exploring further.
How to use this template
- Start the log at project kickoff, not at submission. “What tool did I use in week 2?” three months later doesn’t survive audit.
- One log per project, deliverable group, or workstream — whatever your client or sponsor SOP defines as a unit.
- Log every non-trivial AI use. Spell-check is generally exempt; everything else benefits from capture.
- Store the log in the shared project location, not in a personal note. Audit trails that aren’t shared aren’t auditable.
- Retain per the longest applicable timeframe (sponsor SOP, journal author guidelines, regulatory archiving). Default is the project’s record-retention period.
Project header
Fill in once at kickoff. Update if scope or ownership changes.| Field | Value |
|---|---|
| Project name | [e.g., Drug X Phase 3 primary publication] |
| Deliverable type | [e.g., Primary publication / regulatory submission / promotional leave-piece] |
| Sponsor / client | [Sponsor or client name] |
| Agency (if applicable) | [Agency name] |
| SOP reference | [e.g., ABC-SOP-0042 v3.1] |
| Project lead / owner | [Name and role] |
| Accountable reviewer | [Name and role — the named human responsible for sign-off] |
| Log start date | [YYYY-MM-DD] |
| Log location | [Folder path or project file where this log is stored] |
AI use entries
One row per discrete AI use. Add rows as you go.| Date | Deliverable / section | Tool + version | Scope of use | Source inputs | Reviewer | Outcome | Notes |
|---|---|---|---|---|---|---|---|
| 2026-05-04 | Manuscript Discussion section | Claude Opus 4.7 | Drafting (initial) | Trial CSR sections 11–14; key messages doc v2 | A. Smith | Accepted with edits | Two paragraphs rewritten to add HR confidence intervals |
| 2026-05-05 | Manuscript Methods section | Claude Sonnet 4.6 | Editing for clarity | Existing draft section | A. Smith | Accepted as-is | Light copy-edits only |
| 2026-05-05 | All references (40) | RefCheckr (closed-loop) | Reference verification and rewrite | Source PDFs of all cited references | A. Smith | 3 rewrites accepted, 1 manual edit | Closed-loop output reviewed; one claim required manual rephrasing |
| 2026-05-08 | Visual abstract | Nano Banana 2 | Concept image generation | Brief prompt + key messages | M. Jones | Accepted | Caption updated to flag conceptual nature |
Field guidance
- Date — when the AI was used, not when the entry was written.
- Deliverable / section — be specific enough that a reviewer can locate the work product. “Manuscript” alone is not specific; “Manuscript Discussion section” is.
- Tool + version — always include both. “Claude” without a version is undefined when reviewed six months later.
- Scope of use — one of: Drafting, Editing, Translation, Verification, Synthesis, Image generation, Other. Match the categories used in Declaring AI Use.
- Source inputs — what was given to the AI? Source documents, prompts, prior drafts.
- Reviewer — the named human who checked the AI output. A blank reviewer field means an unaccountable AI use; the row is not yet complete.
- Outcome — Accepted as-is / Accepted with edits / Rejected / Pending review. Clear all pending entries before sign-off.
- Notes — brief context: what changed, what didn’t, what was flagged.
Sign-off block
Complete at deliverable finalisation.| Field | Value |
|---|---|
| Final deliverable version | [Version number / file name] |
| All log entries reviewed | [Yes / No] |
| All pending entries cleared | [Yes / No] |
| Disclosure language drafted | [Yes / No — link to specific snippet from the Disclosure Language Template if used] |
| Final reviewer name | [Name and role] |
| Sign-off date | [YYYY-MM-DD] |
What this log supports
A single log feeds four downstream uses:- Journal disclosure — entries become the basis for the AI-use statement, with the Disclosure Language Template as the wording reference.
- Sponsor or client audit — when asked “What AI was used on this deliverable?”, the log is the answer. Without it, you reconstruct from memory under pressure.
- EU AI Act documentation — the contemporaneous record of tool use, scope, and reviewer aligns with Article 50 transparency obligations and the general documentation expectations covered in AI Regulation in Pharma.
- Internal QC retrospectives — patterns emerge across projects: which tools cause the most rework, which scope of use produces the cleanest output, where reviewers spend their time.
Common mistakes
- Building the log at submission. “I’ll remember” is not a strategy. Weeks of AI use cannot be reconstructed reliably; entries get missed and the disclosure is weaker than it should be.
- Logging only successful uses. Rejected and revised entries matter — they show review was active, not rubber-stamped.
- Vague tool names. “ChatGPT” doesn’t tell a reviewer in 18 months whether it was GPT-4 or GPT-5. Always include version.
- Missing the reviewer column. A log entry without a reviewer name is an unaccountable AI use. Complete the row before treating the entry as logged.
- Storing the log in a personal note. If a colleague needs the log during your absence and can’t find it, the audit trail isn’t auditable. Store in the shared project location.
Related
- Review and Accountability — the principle this log operationalises
- Declaring AI Use — the disclosure principle the log feeds
- Disclosure Language Template — ready-to-paste wording derived from the log
- AI Regulation in Pharma — the regulatory expectations this log helps meet
Last reviewed: 4 May 2026 · 6 min read