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Model-assisted Bayesian designs for dose finding and optimization :methods and applications /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Model-assisted Bayesian designs for dose finding and optimization :Ying Yuan, Ruitao Lin, J. Jack Lee.
其他題名:	methods and applications /
作者:	Yuan, Ying
其他作者:	Lin, Ruitao,
出版者:	Boca Raton, FL :CRC Press,2023.
面頁冊數:	xiii, 219 p. :ill. ;25 cm.
標題:	Drug developmentStatistical methods.
ISBN:	9780367146245 :

Model-assisted Bayesian designs for dose finding and optimization :methods and applications /
Yuan, Ying(Professor of biostatistics),

Model-assisted Bayesian designs for dose finding and optimization :methods and applications /Ying Yuan, Ruitao Lin, J. Jack Lee. - 1st ed. - Boca Raton, FL :CRC Press,2023. - xiii, 219 p. :ill. ;25 cm. - Chapman & Hall/CRC biostatistics series. - Chapman & Hall/CRC biostatistics series..

Includes bibliographical references and index.

Bayesian Statistics and Adaptive Designs -- Algorithm and Model-Based Dose Finding Designs -- Model-Assisted Dose Finding Designs -- Drug-Combination Trials -- Late-Onset Toxicity -- Incorporating Historical Data -- Multiple Toxicity Grades -- Finding Optimal Biological Dose.

"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. Features Represents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trials Describes the up-to-date theory and practice for model-assisted designs Presents many practical challenges and issues arising from early-phase clinical trials Illustrates with many real trial applications Offers numerous tips and guidance on designing dose finding and optimization trials Provides step-by-step illustration of using software to design trials Develops a companion website (www.trialdesign.org) to provide easy-to-use software to assist learning and implementing model-assisted designs Written by internationally recognized research leaders who pioneered model-assisted designs from the University of Texas MD Anderson Cancer Center, this book shows how model-assisted designs can greatly improve the efficiency and simplify the conduct of early-phase dose finding and optimization trials. It should therefore be a very useful practical reference for biostatisticians, clinicians working in clinical trials, and drug regulatory professionals, as well as graduate students of biostatistics. Novel model-assisted designs showcase the new KISS principle: Keep it simple and smart!"--

ISBN: 9780367146245 :NT$3588

LCCN: 2022017949Subjects--Topical Terms:

181868
Drug development
--Statistical methods.

LC Class. No.: RM301.25 2023

Model-assisted Bayesian designs for dose finding and optimization :methods and applications /
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505 0 $a Bayesian Statistics and Adaptive Designs -- Algorithm and Model-Based Dose Finding Designs -- Model-Assisted Dose Finding Designs -- Drug-Combination Trials -- Late-Onset Toxicity -- Incorporating Historical Data -- Multiple Toxicity Grades -- Finding Optimal Biological Dose.
520 $a "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. Features Represents the first book to provide comprehensive coverage of model-assisted designs for various types of dose-finding and optimization clinical trials Describes the up-to-date theory and practice for model-assisted designs Presents many practical challenges and issues arising from early-phase clinical trials Illustrates with many real trial applications Offers numerous tips and guidance on designing dose finding and optimization trials Provides step-by-step illustration of using software to design trials Develops a companion website (www.trialdesign.org) to provide easy-to-use software to assist learning and implementing model-assisted designs Written by internationally recognized research leaders who pioneered model-assisted designs from the University of Texas MD Anderson Cancer Center, this book shows how model-assisted designs can greatly improve the efficiency and simplify the conduct of early-phase dose finding and optimization trials. It should therefore be a very useful practical reference for biostatisticians, clinicians working in clinical trials, and drug regulatory professionals, as well as graduate students of biostatistics. Novel model-assisted designs showcase the new KISS principle: Keep it simple and smart!"-- $c Provided by publisher.
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700 1 $a Lee, J. Jack, $e author. $3 1011720
830 0 $a Chapman & Hall/CRC biostatistics series. $3 508409