Higher patient satisfaction with antidepressants correlates with earlier drug release dates across online user-generated medical databases.

Studies establishing the use of new antidepressants often rely simply on proving efficacy of a new compound, comparing against placebo and single compound. The advent of large online databases in which patients themselves rate drugs allows for a new Big Data-driven approach to compare the efficacy and patient satisfaction with sample sizes exceeding previous studies. Exemplifying this approach with antidepressants, we show that patient satisfaction with a drug anticorrelates with its release date with high significance, across different online user-driven databases. This finding suggests that a systematic reevaluation of current, often patent-protected drugs compared to their older predecessors may be helpful, especially given that the efficacy of newer agents relative to older classes of antidepressants such as monoamine oxidase inhibitors (MAOIs) and tricyclic antidepressants (TCAs) is as yet quantitatively unexplored.