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Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials (Hardcover)
Loot Price: R3,055
Discovery Miles 30 550
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Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials (Hardcover)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 17 working days
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"This is truly an outstanding book. [It] brings together all of the
latest research in clinical trials methodology and how it can be
applied to drug development.... Chang et al provide applications to
industry-supported trials. This will allow statisticians in the
industry community to take these methods seriously." Jay Herson,
Johns Hopkins University The pharmaceutical industry's approach to
drug discovery and development has rapidly transformed in the last
decade from the more traditional Research and Development (R &
D) approach to a more innovative approach in which strategies are
employed to compress and optimize the clinical development plan and
associated timelines. However, these strategies are generally being
considered on an individual trial basis and not as part of a fully
integrated overall development program. Such optimization at the
trial level is somewhat near-sighted and does not ensure cost,
time, or development efficiency of the overall program. This book
seeks to address this imbalance by establishing a statistical
framework for overall/global clinical development optimization and
providing tactics and techniques to support such optimization,
including clinical trial simulations. Provides a statistical
framework for achieve global optimization in each phase of the drug
development process. Describes specific techniques to support
optimization including adaptive designs, precision medicine,
survival-endpoints, dose finding and multiple testing. Gives
practical approaches to handling missing data in clinical trials
using SAS. Looks at key controversial issues from both a clinical
and statistical perspective. Presents a generous number of case
studies from multiple therapeutic areas that help motivate and
illustrate the statistical methods introduced in the book. Puts
great emphasis on software implementation of the statistical
methods with multiple examples of software code (both SAS and R).
It is important for statisticians to possess a deep knowledge of
the drug development process beyond statistical considerations. For
these reasons, this book incorporates both statistical and
"clinical/medical" perspectives.
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