The reliability of clinical trial findings is determined by statistical significance when comparing treatments with controls. If a therapeutic approach works in one out of 20 patients, it would be considered statistically insignificant because of the variations within the test group and the drug’s development may be abandoned. Alternatively, researchers may re-test the therapy in larger cohorts of patients to see if it might reach statistical significance. If a treatment does reach statistical significance in larger cohorts of patients, the drug could potentially be approved, even though a considerable fraction of patients did not respond to it. Now a days, patients are often stratified into treatment and control groups based on animal studies, which as stated, often fail to mimic the outbred nature of humans. This approach has hindered publication of novel findings and the development of personalized medicine where individual variations are appreciated during the trials and interpretations of the results.