Clinical Data Integration and Analytics

Clinical Data Integration and Analytics

Problem Statement

This large global pharma company needed a centralized approach to data. Specifically, its goals were to:

  • Implement a global central data hub across the U.S. and Europe.
  • Integrate clinical and relevant safety data to support safety data reconciliation and benefit risk assessment and associated reporting.
  • Establish the ability to integrate data managed by external business partners through a secure platform.
  • Improve internal advanced analytics capabilities.
  • Streamline the process and time requirements to respond to health authorities and to defend product claims.

ClinHUB is a unique source-system agnostic data aggregation platform specifically designed for clinical research. ClinHUB was purpose-built as a data lake, the data approach of preference for leading companies like Facebook and Google. With ClinHUB, the pharma company was able to:

  • Integrate large volumes of complex data from internal systems and external partners, including cloud based sources.
  • Leverage a metadata-driven framework to automate data extraction and transformations.
  • Compile Dynamic View Engines providing customized views of ingested data based on user needs from trial operations, data management, and biostatistics.
  • Enable Information Views at various levels, i.e. Study Specific and Study Independent.
  • Standardize captured clinical data to support user analysis/reporting through a Linear Data Model flow.



  • A metadata-driven dynamic and automated solution.
  • Data standardization for regulatory guidelines.
  • Framework for data mining & innovative future capabilities.

Key findings


faster data loading and integration


real-time data access speed


in required change control processes

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