H1ST-AI-DEN-002 · Task 2.1
Your data managers deserve better than transcription
Every hour your team spends retyping source values is an hour not spent on the judgment only they can bring. The Source Data Extraction Agent ingests source documents — visit notes, lab reports, ECGs, and worksheets — runs OCR and named-entity recognition to lift out the values that belong in the CRF, and strips PHI before anything leaves the source layer. Manual transcription becomes a reviewable, structured extraction, with every value linked back to its source.
The grind you know
Your source data arrives as scanned PDFs, faxes, and free-text notes, and someone on your team keys it into the EDC field by field while someone else double-checks every entry. It's slow, it's easy to fat-finger, and later — during monitoring — every one of those values has to be traced back to the exact line it came from. It's transcription work that never really ends.
Part of the Clinical Data Capture family
Source-document extraction & query automation.
Every hour your team spends retyping source values is an hour not spent on the judgment only they can bring. The Source Data Extraction Agent ingests source documents — visit notes, lab reports, ECGs, and worksheets — runs OCR and named-entity recognition to lift out the values that belong in the CRF, and strips PHI before anything leaves the source layer. Manual transcription becomes a reviewable, structured extraction, with every value linked back to its source.
Drop in scanned or native visit notes, lab reports, and worksheets — OCR handles image-based files automatically.
Clinical NLP lifts out the data points, maps them to CDASH fields, and removes PHI before the values are shown.
Data managers confirm flagged low-confidence values, then push the cleaned, structured data into the EDC.
Capabilities
Reads scanned and native source documents through Paddle OCR, then applies clinical named-entity recognition to identify labs, vitals, medications, and dates as discrete data points.
Maps extracted entities to CDASH variables and expected CRF fields, so values land in the right form with the right units rather than as loose text.
Detects and removes all 18 HIPAA Safe Harbor identifiers at the point of extraction, keeping PHI out of downstream review and audit views.
Every extracted value carries a link back to the page, region, and confidence score of its source, so monitors can verify against the original document in one click.
In practice
Where the agent shows up in the day-to-day of a live trial — the moments the grind usually lives in.
A site uploads a batch of scanned visit notes, lab reports, and worksheets that would otherwise be keyed in by hand. OCR and clinical NLP lift the labs, vitals, medications, and dates out as discrete values, mapped to CDASH fields, so your team confirms rather than transcribes.
The source documents are full of patient names and MRNs that must never reach a downstream reviewer or audit view. All 18 HIPAA Safe Harbor identifiers are removed at the point of extraction, so PHI stays out of the layer where your team is working.
During monitoring, every posted value has to be traced back to the exact line it came from. Each extracted value carries a link to its source page, region, and confidence score, so verification against the original document is one click instead of a document hunt.
Proof
Figures shown are pre-launch targets based on internal benchmarks, not guaranteed outcomes.
Paddle OCR
OCR
Gemini / Anthropic LLM
LLM
Who it's for
Compares submitted data against expected fields to find gaps, then generates context-aware queries to close them.
Learn moreRuns the full query lifecycle — auto-populating responses, tracking status, and escalating by age, type, and priority.
Learn moreReads source documents with OCR and clinical NLP to surface review findings, each with a confidence score.
Learn morePeace of mind
Every output is generated inside a validated, audit-ready platform, kept under human-in-the-loop control, and mapped to the regulatory and CDISC standards this agent supports.
Walk through it on your own workflow with a clinical-trials expert — no pressure, no obligation, and honest answers, including on the limits.
