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A dimensional warehouse for integrating operational data from clinical trials.

Michael A Farnum1, Lalit Mohanty1, Mathangi Ashok1

  • 1Covance, the Drug Development Division of LabCorp, Carnegie Center, Princeton, NJ, USA.

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Summary

A new clinical data warehouse provides timely, integrated access to pharmaceutical trial operational data. This solution enhances study oversight, risk management, and overall clinical trial performance through accessible data and metrics.

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Area of Science:

  • Clinical Data Management
  • Pharmaceutical Data Analytics
  • Health Informatics

Background:

  • Accessing clinical trial data consistently and integrating it across sources is a significant challenge in the pharmaceutical industry.
  • Existing systems often lack the necessary integration and accessibility for effective operational oversight and risk management.

Purpose of the Study:

  • To develop and present a data warehouse solution for integrating, managing, and accessing clinical trial operational data.
  • To support enhanced operational oversight, proactive risk management, and data-driven decision-making in clinical research.

Main Methods:

  • Development of a dimensional relational data warehouse architecture.
  • Implementation of extraction, transformation, and loading (ETL) processes for data ingestion and mapping.
  • Creation of a metrics engine for operational and performance indicators, coupled with user interfaces for management.

Main Results:

  • The data warehouse successfully integrates operational data from diverse sources into a canonical model.
  • The system provides timely, secure, and contextualized access to raw data and derived metrics.
  • The solution facilitates tracking study conduct, identifying risks, and monitoring operational processes.

Conclusions:

  • The developed data warehouse offers a comprehensive solution for managing clinical trial data, improving operational efficiency.
  • Integrated data access and metrics enable better risk mitigation, resource allocation, and sponsor/investigator relationship management.
  • This approach supports data-driven improvements in clinical trial conduct and performance monitoring.