Recent developments in the area of integrated process and product design have shown that products can be designed in terms of their properties with out committing to any specific components a priori. However, the identification of suitable candidate molecules that satisfy a set of property targets is still a challenging issue. While current techniques make use of group contribution methods (GCM) to design molecules, there are many properties which can not be estimated by GCM. Furthermore, not all possible atomic arrangements and structures can be represented in GCM. Hence, there is a need of an efficient methodology for the design of structured molecules. One such approach to structured product design is to combine property clustering with decomposition techniques. This approach first utilizes multivariate characterization techniques to describe a set of representative samples, and then uses decomposition techniques such as principal component analysis (PCA), to find the underlying latent variable models that describe the molecule's properties. The orthogonal nature of these models allows for group-based interpretations and property predictions which can be utilized to design new molecules not found in the original set of molecules. In this work a case study of the design of an excipient for an acetaminophen tablet is presented.