There has been broad agreement for years among scientists at FDA and drug developers about the feasibility of using adaptive trial designs to increase the probability of success while reducing the time and cost of clinical development.

Yet despite the clear and urgent need to break free of the frequentist trial paradigm, use of alternative approaches such as Bayesian statistics to learn from and modify a trial while it is underway have been confined to the pages of academic journals and conference presentations. Instead, a combination of regulatory uncertainty and inertia has prevented the adoption of adaptive techniques.

"One of the barriers to advancing the science of drug development may be the regulatory process itself, which establishes tried and true benchmarks for measuring safety and efficacy that few sponsors are willing to veer from, even if a better approach clearly exists," Scott Gottlieb, FDA's deputy commissioner for medical and scientific affairs, told BioCentury.

Regulators and industry are finally moving to break the logjam.

FDA is developing a series of guidance documents designed to help companies gain approval of products based on adaptive trial designs that permit them to conduct and act on interim analyses and to dynamically adjust doses, sample sizes or randomization (see Cover Story).

Meanwhile, Wyeth is making itself a case study for closing the gap between theory and practice. The pharma company is hoping to use adaptive trials first to supercharge Phase II trials, and in the long-term, believes its "Learn & Confirm" approach could help erase the boundaries between Phase II and III studies.

First hit

In theory, drugs could be approved based on trials in which the dose, study duration, primary endpoint and proposed label indication were not established when the trial started.