Multivariate Analyses of a Production Formulation Optimization Experiment

Abstract

Three prominent multivariate statistical analyses, canonical correlation analysis (CCA), principal component analysis (PCA) and CAS-Regression analysis (CAS-R) are appropriately applied to the formulation optimization data associated with Product-T for determining a set of key excipient/process variables and a set of key response variables to be used in monitoring the future performance of the optimizated formula. CCA which considers both sets of variables simultaneously in a single analysis, successfully delineated two key parameters, one for each set. PCA which considers only the response variables concurred with the CCA results and CAS-R which considers each response variable separately also concurred. Even though CCA is a predominant technique, adjunct results of PCA and CAS-R could be supplemented for a comprehensive interpretation. It is recommended that all three analyses be carried out and interpreted appropriately.