Pharmaceutical Experimental Design
Taylor & Francis

Pharmaceutical Experimental Design - Paperback / softback

Edition: 1st Edition
Subjects: Maths & Science, Probability & statistics
ISBN13: 9780367447748
Published: 23 Aug 1970

Format - Paperback / softback
By Gareth A. Lewis

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Regular price A$99.20
Sale price A$99.20 Regular price A$124.00

Pharmaceutical Experimental Design - Paperback / softback

Regular price A$99.20
Sale price A$99.20 Regular price A$124.00
Product description

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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