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Statistical Support of Risk-Based Monitoring
Session Chair(s)
Jonathan Haddad, MPH
HIV Disease Area Head, Clinical Statistics
GlaxoSmithKline, United States
Risk-based monitoring (RBM) is rolling out across the industry and new guidance documents have given industry a shove out onto the dance floor. Clinical statisticians have long been pressed by their study teams to identify analysis-oriented data queries to support data quality. Other aspects of RBM include statistical process control and signal-detection to evaluate performance and identify problems, areas in which clinical statisticians can make important contributions. This session will cover the role of the clinical statistician in the suppport of RBM, through several case studies by sponsors and contract research organizations.
Learning Objective : Discuss statistical methods used to support risk-based monitoring (RBM); Describe the areas of potential contribution by clinical statisticians to RBM plans; Identify several statistically-oriented approaches to RBM support.
Speaker(s)
Risk-Based Monitoring: Case Studies of Successful Implementation
Jill Collins, MS
INC Research, United States
Executive Director, Global Operations management, Innovation
Integrating Central Statistical Monitoring in a Quality by Design Approach for Clinical Trials
Francois Torche, MBA
CluePoints, Belgium
Chief Product & Technology Officer
TransCelerate’s Data Integrity and GCP Misconduct Detection Best Practice Recommendations for Clinical Statisticians in the Context of RBM
Yodit Seifu, PhD
Ferring, United States
Senior Project Statistician