AAPS 2016

Adaptive trial designs a 'prospectively planned opportunity,' says BMS

By Melissa Fassbender contact

- Last updated on GMT

Adaptive trial designs a 'prospectively planned opportunity,' says BMS

Related tags: Clinical trial

The most successful adaptive design trials are “designed by nature,” said BMS at the AAPS annual meeting and exposition this week in Denver, Colorado.

Adaptive clinical trial design is not a new concept, but the approach has been gaining traction as the industry looks to increase efficiency and reduce costs.

Peter Trimboli, Group Leader, Drug Supply Management at Bristol-Myers Squibb (BMS) told the audience yesterday at AAPS 2016 that an adaptive design is a “prospectively planned opportunity​.”

Changes are made by design, not on an ad hoc basis​,” he said, adding that the most successful adaptive design trials “are designed by nature​.”

Trimboli explained changes are made based on analysis of interim data after asking “where do we stand now​?” He described this interim analysis as a “window for course correction​.”

On the contrary, in traditional clinical development if something is not going as expected, “there is not much we can do​,” said Trimboli. But, in adaptive design, “maybe there’s a way​,” he said – because researchers can change course.

However, there are concerns on the use of adaptive designs, mainly for pivotal studies, despites their potential to improve efficiency and success rates of drug development.

As such, Trimboli said it’s essential to present the validly and integrity of the trial despite modifications. “That’s a key critical element that an adaptive design has to meet​,” he added.

The challenges

According to Trimboli there are several challenges in conducting adaptive trial as they specifically pertain to forecasting drug supply – although simulation software tools can substantially reduce overages, he said.

For success, drug supply planning for adaptive trials needs to be closely coordinated with statistical design to strike the best balance between statistical efficiency and drug supply feasibility​,” Trimboli explained.

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