Clinical Trial Dataset Anonymisation with anonym.plus

Prepare a participant-level file for sharing without one byte leaving your desk.

Trial dataset anonymisation is the removal of participant identifiers before a file is shared. It supports MHRA clinical-trial transparency requirements and ICH E6(R2). anonym.plus runs offline and keeps the measured values readable.

When this applies

The MHRA asks a sponsor to share participant-level results. Names, free-text fields, and rare dates must be hidden first.

How anonym.plus handles it

  1. Load the file (CSV, XLSX, PDF, or DOCX) into anonym.plus.
  2. The tool scans columns and free text for direct identifiers.
  3. Local OCR pulls text from any scanned supporting page.
  4. Confirm the flagged participant names, dates, and places.
  5. Replace each one with a steady token across the whole file.
  6. Save the cleaned copy on your device with no network call.

What you need to provide

Patient data entity types detected

Categoryanonym.plus entity typeExample
NamesPERSONJames O’Brien → [PARTICIPANT_1]
Event datesDATE_TIMERandomised 02/02/2026 → [DATE]
LocationLOCATIONManchester, England → [REGION]
EmailEMAIL_ADDRESSj.obrien@example.co.uk → [EMAIL]
Free-text IDIDScreening SCR-0091 → [SCREEN_ID]
NHS numberMEDICAL_RECORD_NUMBERNHS 512 345 6789 → [LOCAL_ID]

Compliance achieved

Anonymise clinical trial datasets offline — see plans & start free →

Limitations & cautions

MHRA transparency expects a risk assessment, not just field removal. The tool strips direct identifiers and flags rare values like an unusual age. You still judge whether quasi-identifiers in combination could re-identify a participant before release.

Frequently asked questions

What does MHRA transparency require for trial data?

The MHRA expects sponsors to publish or share participant-level data with identifiers removed and a documented justification of the method. Removing direct identifiers is the first step toward that submission.

Can it process spreadsheet columns?

Yes. Load a CSV or XLSX and the tool scans both column values and free text. It applies the same token to a repeated name across every row.

Is the published file still useful for analysis?

Yes. Numeric outcomes and timing offsets remain. Only direct identifiers are swapped, so the file keeps its scientific value.