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Activity Number: 127
Type: Contributed
Date/Time: Monday, August 4, 2014 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract #311327 View Presentation
Title: Bayesian Adaptive Dose-Finding Designs in Drug Combination Clinical Trials
Author(s): Yuehui Wu*+ and Tian Chen
Companies: GlaxoSmithKline and GlaxoSmithKline
Keywords: Dose-finding ; Adpative Design ; Bayesian Design ; Drug combinations ; Clinical Trials
Abstract:

When two drugs are combined in drug development, the toxicity rate for the combo dose is expected to be higher than the individual drug. There can also be several combo doses that have the same toxicity rate, i.e. the MTD is not unique. It is crucial to identify all /some of the combos with the same toxicity rate then carry the most efficacious combo to the later phase trial. In this case, the traditional 3+3 design which dose escalates only on one dimension may not be able to identify all the MTDs. To address this concern and propose more efficient dose-finding designs for drug combination studies, we investigated some Bayesian model based dosing finding adaptive designs similar to the well known CRM design as well as the non-parametric zone based 3+3 dosing design. The design performances are compared via simulations under different scenarios. Pros and Cons under the different scenarios as well as recommendations will be discussed.


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