Pharmaceutical experimental design
著者
書誌事項
Pharmaceutical experimental design
（Drugs and the pharmaceutical sciences, v. 92）
Marcel Dekker, c1999
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注記
Includes bibliographical references and index
内容説明・目次
内容説明
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 DesignA* offers broad, detailed, up-to-date descriptions of designs and methods not easily accessible in other booksA* reviews screening designs for qualitative factors at different levelsA* presents designs for predictive models and their use in optimizationA* highlights optimization methods, such as steepest ascent, optimum path, canonical analysis, graphical analysis, and desirabilityA* discusses the Taguchi method for quality assurance and approaches for robust scaling up and process transferA* details nonstandard designs and mixturesA* analyzes factorial, D-optimal design, and offline quality assurance techniquesA* reveals how one experimental design evolves from anotherA* 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.
目次
1. Overview 2. Screening 3. Factor Influence Studies 4. Statistical and Mathematical Tools 5. Response Surface Methodology 6. Optimization 7. Variability and Quality 8. Exchange Algorithms 9. Mixtures 10. Mixtures in a Constrained Region of Interest
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