Workshop in Biostatistics
|DATE:||January 14, 2016|
|TIME:||1:30 - 3:00 pm|
|LOCATION:||Medical School Office Building, Rm x303|
|TITLE:||Frasian biomarker designs for randomized trials with adaptive enrichment|
Assistant Professor, Department of Biostatistics, University of Washington, Seattle
The biomedical field has recently focused on developing targeted therapies, designed to be effective in only some subset of the population with a given disease. However, for many new treatments, characterizing this subset has been a challenge. Often, at the start of large-scale trials the subset is only rudimentarily understood. This leads practitioners to either 1) run an all-comers trial without use of the biomarker or 2) use a poorly characterized biomarker that may miss parts of the true target population and potentially incorrectly indicate a drug from a successful trial.
In this talk I will discuss a class of adaptive enrichment designs: clinical trial designs that allow the simultaneous construction and use of a biomarker, during an ongoing trial, to adaptively enrich the enrolled population. For poorly characterized biomarkers, these trials can significantly improve power while still controlling type one error. However there are additional challenges in this framework: How do we adapt our enrollment criteria in an “optimal” way? (what are we trying to optimize for?) How do we run a formal statistical test after updating our enrollment criteria? How do we estimate an unbiased treatment effect-size in our “selected population”? (combating a potential selection bias) In this talk we will give an overview of a class of combined Frequentist-Bayesian clinical trial designs that address these questions.