In clinical trials, we randomize to ensure the blind. But even the most secure randomization algorithms, which provide the least predictability, have a real risk of unblinding when implemented.
In this webinar, Calyx’s Head of Statistics and Product Support Services, Malcolm Morrissey shares his experience on how to identify the randomization implementation options that can lead to unblinding of the block size and other potential risks that could result in selection bias at the site.
He’ll review how to mitigate this risk, which is increased during events outside of the normal randomization process; this includes live study data transfers and study-specific features such as forced randomization and cohort rules.
After a brief presentation, Malcolm opens the floor to your questions – ask him anything!
Associate Director, Statistics and Product Support Services, Calyx
Malcolm Morrissey obtained a PhD in Statistical Inference in 2001 and since has had broad experience as a research associate, statistician, and manager in the pharmaceutical industry. He joined Calyx in 2005 and currently manages a team whose duties include supporting and developing randomization and medication management algorithms for clinical trials managed by IRT.