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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.
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.
Molecular Modeling of the Sensitivities of Energetic Materials,
Volume 22 introduces experimental aspects, explores the
relationships between sensitivity, molecular structure and crystal
structure, discusses insights from numerical simulations, and
highlights applications of these approaches to the design of new
materials. Providing practical guidelines for implementing
predictive models and their application to the search for new
compounds, this book is an authoritative guide to an exciting field
of research that warrants a computer-aided approach for the
investigation and design of safe and powerful explosives or
propellants. Much recent effort has been put into modeling
sensitivities, with most work focusing on impact sensitivity and
leading to a lot of experimental data in this area. Models must
therefore be developed to allow evaluation of significant
properties from the structure of constitutive molecules.
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