A technical, compliance-focused engineering reference for building, validating, and scaling Electronic Data Capture (EDC) synchronization pipelines.

🌐 Visit the live site →

clinicaldatapipeline.org is a growing, in-depth reference library for the engineers and data managers who move clinical trial data from source to submission. Modern trials have shifted from periodic batch exports to continuous, API-driven synchronization between EDC platforms and downstream analytics, pharmacovigilance, and regulatory environments. This site treats those pipelines as what they are: mission-critical, validated systems that must stay deterministic, observable, and defensible under inspection.

Every page pairs architectural reasoning with production-grade Python — idempotent extraction, schema-versioned transformations, immutable audit trails, and validation logic you can defend during an audit. No toy examples: each code block targets a real clinical context and calls out its regulatory relevance (21 CFR Part 11, EU Annex 11, ALCOA+, GxP).

• Clinical data managers (CDMs) scoping audit boundaries, query workflows, and data-integrity controls
• Biotech / pharma Python & ETL engineers building and operating extraction and transformation layers
• Regulatory and quality teams who must demonstrate that every byte moved between systems stays attributable

The library is organized into three connected areas, each linking from high-level architecture down to copy-ready implementation guides.

Deterministic, auditable Python ETL that moves EDC data securely from source to analytics — API orchestration, rate limits and backoff, async polling, pandas-based cleaning, change-data-capture, Apache Airflow orchestration, and dead-letter recovery. Includes vendor-specific guides for Medidata Rave, Oracle InForm, and Veeva Vault CDMS.

Compliant data architecture end to end: CDISC ODM vs CDASH mapping, SDTM domain-by-domain transformation (DM, AE, LB, VS, SUPPQUAL), ADaM derivation (ADSL, ADAE), audit-trail boundaries, EDC API design, HIPAA-grade security, role-based access control, and computerized system validation (IQ/OQ/PQ, 21 CFR Part 11 audit-log design).

Generating clinical queries and managing discrepancies with deterministic validation: automated range checks, cross-form rules, threshold tuning, CRA routing, the full query lifecycle (raise → route → resolve → close), and CDISC CRF annotation for discrepancy tracking.

• 51 in-depth guides and growing, each written to a consistent, engineering-first standard
• Runnable, annotated Python for real clinical trial scenarios
• Hand-authored, accessible SVG diagrams — architecture, data-flow, sequence, and state diagrams that adapt to light and dark themes
• Structured data (JSON-LD) and clean, accessible markup throughout
• Deeply interlinked so you can drill from concept to implementation and back

• Eleventy (11ty) static site generator
• Hand-authored HTML, CSS, and inline SVG — no heavyweight front-end framework
• Deployed on Cloudflare Workers

npm install      # install dependencies
npm run build    # build the static site into _site/
npm run serve    # local dev server with live reload

• 🌐 Live site: www.clinicaldatapipeline.org
• 📚 Ingestion & Sync Pipelines: /automated-edc-ingestion-sync-pipelines/
• 🏛️ Architecture & EDC Standards: /clinical-data-architecture-edc-standards/
• 🔎 Query & Discrepancy Management: /clinical-query-generation-discrepancy-management/

_{© Clinical Data Pipeline & EDC Sync Hub — a technical reference for clinical data engineering.}