Adaptive designs are increasingly used in clinical trials. The Drug Information Association's Adaptive Design Scientific Working Group (ADSWG) works to foster collaboration among regulatory agencies, academia, and pharmaceutical and biotech companies to further the science of adaptive clinical development. The ADSWG Survey Subteam has collected data on the usage of adaptive designs in clinical research from multiple sources, including a recent ADSWG survey regarding the perception and usage of adaptive designs in academia and industry for studies between 2008 and 2011, as well as barriers to usage; a literature review examining publications of adaptive design methodology and usage between 2000 and 2011; and a trial registry review of adaptive design references from 1996 to 2011. The comprehensive results of the ADSWG 2012 survey are provided in this article with comparisons to our previous 2008 survey, the literature and registry reviews, and recent surveys carried out by the US Food and Drug Administration (FDA) and the European Medicines Agency. Results of the ADSWG 2012 survey illustrate that industry and academia are showing more enthusiasm for adaptive trials, accompanied by an increase in the number of trials using designs described as less well understood in the FDA draft guidance on adaptive designs, published in 2010. The increased use of these methods in exploratory trials is consistent with the FDA draft guidance. The survey also identified several examples of successful marketing applications supported by confirmatory trials utilizing adaptive designs that were considered, at least at the time of the draft guidance, as less well understood. While some of the technological barriers to adaptive design usage identified in the 2008 survey are now less common, there are several important persistent barriers to usage. Organizations can help overcome these barriers through education, preplanning, and early engagement in discussions with the regulators.
Keywords: adaptive design; early stopping; interim analysis; sample size reestimation; treatment selection.