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A Bayesian design and analysis for dose-response using informative prior information.

Michael K Smith·Scott Marshall
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Abstract

We wish to use prior information on an existing drug in the design and analysis of a dose-response study for a new drug candidate within the same pharmacological class. Using the Bayesian methodology, this prior information can be used quantitatively and the randomization can be weighted in favor of the new compound, where there is less information. An Emax model is used to describe the dose-response of the existing drug. The estimates from this model are used to provide informative prior information used for the design and analysis of the new study to establish the relative potency between the new compound and the existing drug therapy. The assumption is made that the data from previous trials and the new study are exchangeable. The impact of departures from this assumption can be quantified through simulations and by assessing the operating characteristics of various scenarios. Simulations show that relatively modest sample sizes can yield informative results about the magnitude of the relative potency using this approach. The operating characteristics are good when assessing model estimates against clinically important changes in relative potency.

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AlgorithmsAnalysis of VarianceBayes TheoremClinical Trials, Phase II as TopicComputer SimulationDose-Response Relationship, DrugHumansModels, StatisticalResearch DesignSample SizeTreatment OutcomeJournal Article

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Michael K Smith, Scott Marshall. 2006. A Bayesian design and analysis for dose-response using informative prior information.. https://doi.org/10.1080/10543400600860535

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