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Pharmaceutical Experimental Design
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Pharmaceutical Experimental Design

Book Details

Format Paperback / Softback
ISBN-10 0367447746
ISBN-13 9780367447748
Publisher Taylor & Francis Ltd
Imprint CRC Press
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 2nd, 2019
Print length 512 Pages
Weight 680 grams
Product Classification: Probability & statisticsChemistry
Ksh 11,950.00
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This book presents an integrated approach to statistical experimental design to pharmaceutical development, covering all important methods applied to solve the more usual pharmaceutical formulation problem while avoiding mathematical difficulties.

This useful reference describes the statistical planning and design of pharmaceutical experiments, covering all stages in the development process-including preformulation, formulation, process study and optimization, scale-up, and robust process and formulation development.Shows how to overcome pharmaceutical, technological, and economic constraints on experiment design!Directly comparing the advantages and disadvantages of specific techniques, Pharmaceutical Experimental Design· offers broad, detailed, up-to-date descriptions of designs and methods not easily accessible in other books· reviews screening designs for qualitative factors at different levels· presents designs for predictive models and their use in optimization· highlights optimization methods, such as steepest ascent, optimum path, canonical analysis, graphical analysis, and desirability· discusses the Taguchi method for quality assurance and approaches for robust scaling up and process transfer· details nonstandard designs and mixtures· analyzes factorial, D-optimal design, and offline quality assurance techniques· reveals how one experimental design evolves from another· and more!Featuring over 700 references, tables, equations, and drawings, Pharmaceutical Experimental Design is suitable for industrial, research, and clinical pharmaceutical scientists, pharmacists, and pharmacologists; statisticians and biostatisticians; drug regulatory affairs personnel; biotechnologists; formulation, analytical, and synthetic chemists and engineers, quality assurance personnel; all users of statistical experimental design in research and development; and postgraduate and postdoctoral research workers in these disciplines.


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