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RWD-native EDC · CRCs / Site coordinators

CuRE Capture

AI-driven validation EDC — clinical research data entry that catches errors at the keystroke.

Part of Clinical Operations

What it does

AI-driven validation EDC — clinical research data entry that catches errors at the keystroke. Prevents work before it becomes work: AI checks reduce queries, SDTM mapping starts at capture, and validation evidence is ready from day one.

Key capabilities

  • CRF authoring + data capture
  • AI-powered validation at the field level
  • Query management workflow
  • 21 CFR Part 11 audit trail
  • Multilingual eCRF + UI localization (per-locale labels, language switcher)
  • Mid-study amendment form-version data migration
  • Central-lab data loading + reconciliation
  • MedDRA/WHODrug dictionary upversioning + batch re-coding
  • End-of-study archival casebook PDFs
  • AI-targeted (risk-based) SDV selection
CuRE Capture — investigator dashboard with a portfolio overview and a per-study enrollment, validation, and open-query heatmap
Sandbox preview — synthetic demo data

What sets it apart

  • Prevents work before it becomes work: AI checks reduce queries, SDTM mapping starts at capture, and validation evidence is ready from day one.
  • Handles the mid-study amendment: forms are versioned and in-flight subject data migrates across the amendment — the disqualifier most EDCs fail.
  • Blinding firewalls, local-lab loading, and offline capture round out the site-facing capture surface.
  • AI validation is contextual, not just range checks — catches inconsistencies across forms and prior visits.
  • Audit trail is cryptographic-hash-chained (Part 11 + Annex 11), not a soft log.
CuRE Capture · Validation EDC
Live demo — synthetic data, runs in your browser

Catch a bad value as it's entered

Enter values into a sample case report form and watch Capture's edit checks fire — an out-of-range lab or a physiologically implausible vital auto-raises a data query on the spot, with a 21 CFR Part 11 audit attribution. Fix the value and the query clears; break a cross-field rule and a new one appears.

Case report form · Visit 3

Subject 1042 · edit a value and validation re-runs on the spot.

g/dL⚑
mmHg⚑
mmHg
%
mEq/L
Auto-raised queries
2 open
error·HemoglobinOPEN

Hemoglobin value 10.2 g/dL is outside the reference range (12–17.5). Please verify the source.

source: AUTO·System·rule range_hemoglobin
error·Systolic BPOPEN

Systolic BP value 166 mmHg is outside the reference range (90–140). Please verify the source.

source: AUTO·System·rule range_systolic_bp

Each query is raised by the same field-save validation core CuRE Capture runs — the out-of-range comparator, cross-field consistency checks, template rendering, and the active-query de-duplication guard, all computed in your browser. In the product each auto-query is written with a 21 CFR Part 11 audit trail (source AUTO, opened by the system user, timestamped and hash-chained) and routed to a coordinator; here nothing calls a backend.

Why this is more than a toy

The validation running here is Capture's actual field-save auto-query core, ported dependency-free from the monorepo (apps/capture/…/data-capture/auto-query-service.ts): the out-of-range comparator, cross-field consistency checks, the query-template renderer, and the active-query de-duplication guard, producing the same QueryFlag shape (source AUTO, status OPEN, system-attributed). In the product each query carries a hash-chained 21 CFR Part 11 audit trail and routes to a coordinator; here it all runs client-side on synthetic data. No backend.

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See CuRE Capture in action

Every research ecosystem is unique. Let's discuss how CuRE can be configured for your needs.

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