Abstract
Statistical modelling and experimental design (SMED) are essential tools for the development and understanding of complicated products and processes. SMED allows efficient experimentation in which all or a large subset of factors are together varied over a set of experiments, in contrast to the traditional approach of varying only one at a time. An overview of the SMED methodology and the generalization of statistical design to multivariate design is presented. The following examples illustrating the use of these methods are discussed: (1) use of factorial designs to improve drug solubility; (2) testing the robustness of an analytical method; and (3) use of multivariate design to select the solvent in analytical method development.
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