Operationalizing CDISC Biomedical Concepts as a Semantic Layer for EHR-to-EDC Data Transfer, AI-Grounded Extraction and Metadata-Driven Study Configuration

About this session

Part of Session 6, Track C: Integration/Interoperability (Chair: Jim Box, SAS).

CDISC Biomedical Concepts(BCs) offer a powerful foundation for connecting clinical research metadata across the data lifecycle. This presentation describes an implementation that positions BCs as the foundational semantic layer of an eSource platform, enabling automated EHR-to-EDC data transfer, AI-Grounded clinical data extraction, standards-driven data visualization and metadata-driven study configuration from a single concept library.
Our approach organizes BC metadata as a knowledge graph, capturing relationships between data element concepts across domains and built on a standards-agnostic canonical layer inspired by triangulating across FHIR, CDASH, OMOP and other reference models. This graph structure, combined with crosswalks to healthcare and research data standards, makes all captured data semantically coded and machine-readable, regardless of study-specific CRF structure or sponsor naming conventions. This allows us to automate transfer and normalization of EHR data into CRF data. That combined with our study builder tool, this also enables us to map EHR data to any eCRF.

Speakers

• MM

  Miten Mistry

  Paradigm Health

  Speaker

• AD

  Abhishek Dabral

  Paradigm Health

  Speaker