Using Historic and/or Current Trial Results to Predict the Success of a Clinical Program
*David Allan Burt, GlaxoSmithKline 

Keywords: Assurance, Success, Prediction, Heterogeneity, Meta-Analyses

Heterogeneity of clinical trial results is a common issue that is encountered when conducting meta-analyses, but traditionally ignored when making internal decisions about the progression of a clinical program. During this presentation, we demonstrate the impact that study to study heterogeneity can have on the predictive probability of success for a future clinical trial. We will then provide between-trial predictive methods (both frequentist and Bayesian) that take into account trial to trial variability. We will also briefly describe how to compute cross-validation measures for the between trial prediction, how Phase 2 to Phase 3 bias can be estimated and incorporated into the predictions, how to predict multiple future trials (i.e. 2 pivotal Phase 3 trials both achieving success), and how between trial predictions based on historical competitor data can easily be used to assess the probability of demonstrating superiority and/or non-inferiority versus the active competitor.