Abstract
A critical issue facing the therapeutic area of neurological diseases is the large number of failed randomized clinical trials, especially when moving from promising Phase 2 trials to failed Phase 3 trials. A common cited reason for these failures is a high placebo response rate that thereby reduces the observed treatment effect. Explanations for this higher than anticipated placebo response include small sample sizes, inadequate study designs and/or analytic methods, baseline characteristics of the trial sample, possible investigator bias and a participant's own expectations and conditional learning. Several innovative study designs and new methodological approaches to statistical analyses have been proposed to handle placebo effects anticipated or observed in double blind, randomized clinical trials (RCT's). This chapter examines current study designs being used to reduce the observed placebo response and statistical analysis methods being employed for addressing this problem in neuroscience clinical trials.
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