Studying Unidentified Impurities in Drug Substances by the Application of Multivariate (Principal Component and Cluster) Analysis

Abstract

One of the most important quality characteristics of a drug substance is its impurity profile, which is defined as a description of the identified and unidentified impurities in a drug substance. The impurity profile very often constitutes an identifier of a particular drug substance and its associated method of manufacture. It is always desirable to determine the chemical structure of any unidentified impurity, since this very often suggests the origin and ways of controlling impurities during the manufacturing process. Unfortunately, however, this is not always economically and technically feasible. In this article, the application of multivariate analysis (principal component and hierarchical cluster analysis) is illustrated through a case study carried out in a bulk chemical plant, where the main goal was the detection of potential underlying structures in the relationships among the impurities making up the impurity profile of a drug substance. These underlying structures in turn might suggest hypotheses about the origin of unidentified impurities.