Scientist reviewing analytical data

AI Data Review

A full run reviewed in seconds - not a full day.

Upload run exports and study documents. A rule engine checks each run against ICH M10 or your SOP; an AI reviewer explains what needs attention - quoting the documents it relies on.

What is checked in every run

Calibration

Standards per level, LLOQ and ULOQ, minimum levels passing.

Quality controls

Per level and overall, dilution QCs, QC count against the protocol.

Blanks & carryover

Analyte and IS interference in blanks after high samples.

Internal standard

IS response window and missing IS, retention-time shifts.

Repeats

Above ULOQ, IS response, failed run - each with reason and action.

ISR

Selection, pairing and evaluation of incurred sample reanalysis.

Data integrity

Duplicates, missing IDs, unparseable or ambiguous values flagged.

Protocol

Calibration and QC levels, range and dilutions against the study set-up.

All relevant data

Run files, documents and scans - together

Several run files at once, every worksheet read. Add the protocol, method, SOPs, investigations, sample manifest, chromatograms and instrument logs - PDF, Word, Excel or scans.

  • Scans read on the server, confirmed by the uploader
  • Samples missing from the manifest found automatically
  • Repeats without a documented reason flagged
  • Protocol LLOQ, ULOQ and IS compared with the set-up
Analyte IS Retention time (min)
Verifiable AI

An AI reviewer that has to show its sources

The AI reads the relevant passages of your documents and the SOPs and guidelines linked to the study.

  • Every quote checked word for word against the document
  • Unverifiable statements removed and listed
  • Rule-engine verdicts are final - the AI is advisory
  • Local AI by default; cloud AI only with QA approval
Study protocol · p.12 AI reviewer "Dilute and re-analyse with a dilution QC" [D1 p.12] ✓ quote verified

From upload to approval

  1. Upload
    Run exports and study documents; the system reads every sheet and lists what it used.
  2. Check
    The rule engine produces run verdicts and findings in seconds; document cross-checks run automatically.
  3. Review
    The scientist dispositions every finding; the AI review points to evidence.
  4. QC check
    Second-person verification of each finding; queries go back to the scientist.
  5. QA approval
    Review and approval with electronic signature; the study dashboard shows every run.

See AI Data Review on your own run files

A 45-minute walkthrough of method development, AI Data Review and the compliance controls - with your own run files.