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Optimizing Efficiency & Quality in EDC Implementation​


Robust data collection is the cornerstone of any clinical trial. Yet in the face of increasing trial complexity, timeline pressure, and talent scarcity, too often leaders face quality and speed challenges in managing Medidata RAVE database build activities.

Delayed electronic data capture (EDC) set up has multiple impacts including lower R&D productivity, reduced patient enrolment, and increased costs. At the same time, a poor-quality build can lead to inaccurate, incomplete data, and issues with regulatory compliance. These negative impacts can ultimately lead to the failure of a trial, wasting time and resources.

In this webinar, Grant Williamson, Senior Director Clinical Programming, and Siba Noolu, Senior Manager, QC at eClinical Solutions will share their strategies for achieving both quality and speed in Medidata study start-up. They will explore best practices for database design, and approaches to streamlining the setup process for accelerated database go-live. Additionally, Williamson and Noolu will discuss how to embed quality throughout the database build through people, processes and technology. Attendees will come away with valuable insights on how to efficiently and effectively set up EDC (Electronic Data Capture) databases for their clinical trials, while promoting the highest standards of data quality.

This webinar covers best practices based on our experiences implementing EDC within Medidata Clinical Cloud, however the principles for assuring quality and speed are generalizable across EDC platforms.

What You Will Learn

  • How to instill a quality focus throughout the set-up process
  • The role of communication in assuring both quality and speed
  • How to combine tools, processes and people to enable accelerated study-start up and reduce cycle times

This 30-minute webinar will conclude with a 15-minute live audience Q&A. Please submit any questions in advance of the webinar via the registration form.

Who Should Attend?

  • Clinical Operations
  • Clinical Data Management
  • Clinical Programming


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