Using Predictive and Advanced Analytics to Enhance Risk-based Monitoring (RBM)

1 hour, 2 minutes

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September 03, 2015

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Executing clinical studies using risk-based Monitoring (RBM) methodologies is reducing risks in clinical development, while improving patient safety and study quality. New capabilities of advanced statistical monitoring and Predictive Analytics are enabling the identification of potential patient safety issues and actionable insight into clinical trial performance.

Predictive and Advanced Analytics use unique statistical algorithms specifically designed for optimal RBM execution. The capabilities combine inputs across multiple variables including operational performance and study clinical data to provide unprecedented insights into potential study risks.

By attending this webinar you will understand the application of analytics to identify potential risks before they occur, and to target the right action at the right place at the right time. This is a major step forward in improving quality, safety and productivity in the next generation of RBM execution.

Key Learning Objectives:

  • Learn of new capabilities being used in risk-based monitoring study execution
  • Understand how you can improve site performance with advanced statistical monitoring
  • Optimize site performance and improve patient safety using Advanced and Predictive Analytics

Key Messages to be delivered:

  • Sponsors can reduce risk and execute RBM studies with confidence by partnering with Quintiles
  • You can improve patient safety and site performance with new Predictive and Advanced Analytics integrated into Quintiles’ RBM approach
  • Quintiles is seeing results of improved efficiencies, data quality and patient safety from its next generation RBM approach 


Rajneesh Patil
Director, Clinical Development Productivity and Quality

XiaoQiang Xue
Director, Predictive Operational Analytics