Bayesian adaptive designs provide a critical approach to improve the efficiency and success rate of drug development that has been embraced by the US Food and Drug Administration (FDA). This is particularly important for early phase trials as they forms the basis for the development and success of subsequent phase II and III trials.The objective of this book is to describes the state-of-the-art model-assisted designs to faciliate and accelerate the use of novel adaptive designs for early phase clinical trials. Model-assisted designs possess avant-garde features where superiority meets simplicity. Model-assisted designs enjoy exceptional performance comparable to more complicated model-based adaptive designs, yet their decision rules often can be pre-tabulated and included in the protocol—making implementation as simple as conventional algorithm-based designs. An example is the Bayesian optimal interval (BOIN) design, the first dose-finding design to receive the fit-for-purpose designation from the FDA. This designation underscores the regulatory agency’s support of the use of the novel adaptive design to improve drug development.FeaturesRepresents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trialsDescribes the up-to-date theory and practice for model-assisted designsPresents many practical challenges and issues arising from early-phase clinical trialsIllustrates with many real trial applicationsOffers numerous tips and guidance on designing dose finding and optimization trialsProvides step-by-step illustration of using software to design trialsDevelops a companion website (WEBLink) to provide easy-to-use software to assist learning and implementing mod

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