Many authors and clinical trial designers advocate the use of minimization algorithms to allocate subjects to study treatment. The main reason cited for the use of minimization is to ensure balance on important covariates, especially in the design of small clinical trials. Few authors discuss the downside to the use of minimization. Recently, a biologic product was presented to an FDA Advisory Committee. The primary study used a minimization algorithm to assign subjects in a 2:1 ratio to either treatment or placebo. The result from a re-randomization test was statistically non-significant, while the result from a standard test was statistically significant. In this presentation, we will discuss the case study in detail and explore possible reasons for the difference in the study findings.