In clinical trials, each specific inclusion and exclusion criterion eliminates a percentage of the potentially eligible population from trial participation and thus increases the time and effort needed for enrollment in a study. Drug developers often do not have data on how these criteria affect the pool of potentially eligible subjects for their trials and, hence, they cannot factor in the impact of these criteria when designing a study and planning the time needed to complete it. Consequently, drug developers often have ambitious timelines that are unrealistic and can lead to actions that may interfere with the ability to separate the efficacy of drug versus placebo. To investigate the effects of inclusion and exclusion criteria on study enrollment, the authors quantified the effects of the inclusion and exclusion criteria commonly used in antidepressant registration trials (ARTs) by applying these criteria to the population treated in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. In essence, the STAR*D study population was used as a surrogate for the general population of individuals with major depressive disorder. The effect of each criterion commonly used in ARTs was assessed in terms of the percentage of the STAR*D population that would have been excluded individually and collectively (i.e., when all criteria were applied at once). For continuous criteria such as age and severity of depression, the resulting effects have been presented graphically. Collectively, the typical inclusion and exclusion criteria used in ARTs would have eliminated at least 82% of the STAR*D population. This result means that more than 5 times the number of subjects would have to be screened to find a population that would meet the typical inclusion and exclusion criteria for an ART, directly determining the screening effort required in terms of both resources and time. Thus, developers of antidepressant drugs can use the data from this study to plan the recruitment effort required and to weigh any potential benefit of each criterion alone and in aggregate versus their cost in terms of recruitment support and time. These data also graphically illustrate for prescribers how restrictive the population likely to be enrolled in ARTs is relative to the patients whom they treat with such medications.