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Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
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Bioequivalence and Statistics in Clinical Pharmacology (Hardcover, 2nd edition)
Loot Price: R3,667
Discovery Miles 36 670
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Bioequivalence and Statistics in Clinical Pharmacology (Hardcover, 2nd edition)
Series: Chapman & Hall/CRC Biostatistics Series
Expected to ship within 12 - 17 working days
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Maintaining a practical perspective, Bioequivalence and Statistics
in Clinical Pharmacology, Second Edition explores statistics used
in day-to-day clinical pharmacology work. The book is a starting
point for those involved in such research and covers the methods
needed to design, analyze, and interpret bioequivalence trials;
explores when, how, and why these studies are performed as part of
drug development; and demonstrates the methods using real world
examples. Drawing on knowledge gained directly from working in the
pharmaceutical industry, the authors set the stage by describing
the general role of statistics. Once the foundation of clinical
pharmacology drug development, regulatory applications, and the
design and analysis of bioequivalence trials are established,
including recent regulatory changes in design and analysis and in
particular sample-size adaptation, they move on to related topics
in clinical pharmacology involving the use of cross-over designs.
These include, but are not limited to, safety studies in Phase I,
dose-response trials, drug interaction trials, food-effect and
combination trials, QTc and other pharmacodynamic equivalence
trials, proof-of-concept trials, dose-proportionality trials, and
vaccines trials. This second edition addresses several recent
developments in the field, including new chapters on adaptive
bioequivalence studies, scaled average bioequivalence testing, and
vaccine trials. Purposefully designed to be instantly applicable,
Bioequivalence and Statistics in Clinical Pharmacology, Second
Edition provides examples of SAS and R code so that the analyses
described can be immediately implemented. The authors have made
extensive use of the proc mixed procedures available in SAS.
General
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