The rate-limiting factor in the discovery of novel antidepressants is the inefficient methodology of traditional multicenter randomized clinical trials (RCTs). We applied a model-based approach to a large clinical database (five RCTs in major depressive disorder (MDD), involving 1,837 patients from 124 recruitment centers) with two objectives: (i) to learn about the role of center-specific placebo response in RCT failure and (ii) to apply what is learned to improve the efficiency of RCTs by enhancing the detection of treatment effect (TE). Sensitivity analysis indicated that center-specific placebo response was the most relevant predictor of RCT failure. To reduce the statistical "noise" generated by centers with nonplausible, excessively high/low placebo responses, we developed an enrichment-window strategy. Clinical trial simulation was used to assess the enrichment strategy applied before the standard statistical analysis, resulting in an overall reduction in failure of RCTs from ~50 to ~10%.