An Adaptive Bayesian Approach To Dose Response Modeling
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An Adaptive Bayesian Approach to Dose-response Modeling
Clinical drug trials are costly and time-consuming. Bayesian methods alleviate the inefficiencies in the testing process while providing user-friendly probabilistic inference and predictions from the sampled posterior distributions, saving resources, time, and money. We propose a dynamic linear model to estimate the mean response at each dose level, borrowing strength across dose levels. Our model permits nonmonotonicity of the dose-response relationship, facilitating precise modeling of a wider array of dose-response relationships (including the possibility of toxicity). In addition, we incorporate an adaptive approach to the design of the clinical trial, which allows for interim decisions and assignment to doses based on dose-response uncertainty and dose efficacy. The interim decisions we consider are stopping early for success and stopping early for futility, allowing for patient and time savings in the drug development process. These methods complement current clinical trial design research.
An Adaptive Bayesian Approach to Continuous Dose-response Modeling
Clinical drug trials are costly and time-consuming. Bayesian methods alleviate the inefficiencies in the testing process while providing user-friendly probabilistic inference and predictions from the sampled posterior distributions, saving resources, time, and money. We propose a dynamic linear model to estimate the mean response at each dose level, borrowing strength across dose levels.
Adaptive Design Methods in Clinical Trials
With new statistical and scientific issues arising in adaptive clinical trial design, including the U.S. FDA's recent draft guidance, a new edition of one of the first books on the topic is needed. Adaptive Design Methods in Clinical Trials, Second Edition reflects recent developments and regulatory positions on the use of adaptive designs in clini