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Response Adaptive Randomisation Clinical Trial Simulation with two Binary Biomarkers, using Gaussian Processes



We propose a method that uses a patient's two binary biomarkers to adaptively assign them a treatment within a clinical trial. This method has an initial burn-in period where each patient is assigned each treatment with equal probability. Data from previous patients are used together with the next patient's biomarker value to predict the best treatment for the next patient, using a regression procedure. The estimated best treatment is then assigned to each patient with high probability. This probability increases linearly as more patients enter the trial. This is done for each patient sequentially. This capsule only investigates the gaussian processes procedure, in a simulation based on a real trial. This simulation is used to show that the method assigns more patients in the trial to the best treatment than the fixed design with equal allocation.
Date made available2021
PublisherCode Ocean

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