Multivariate cluster analysis of pharmaceutical formulation data using Andrews plots

A multivariate clustering technique known as the Andrews Plot was applied to a set of previously published data describing a series of pharmaceutical tablet formulations. Dependent variable data were subjected to a trigonometric transform algorithm and unique sinusoidal patterns were obtained for each of 18 formulations characterized by a total of 12 granulation and tablet parameters. Three main formulation clusters were observed in close agreement with a previously published analysis of the same data set using principal components methodology. Interpretation of cluster behavior lead to conclusions closely aligned to those of the original investigators, although some alternate hypotheses also arise. Limitations of the Andrews plotting technique were explored. The method appears to have value in the analysis of complex data sets derived from pharmaceutical formulation characterizations.