Multivariate methods in developing an evolutionary strategy for tablet formulation

The aim of this study was to develop a new strategy for choosing excipients in tablet formulation. Multivariate techniques such as principal component analysis (PCA) and experimental design were combined in a multivariate des ign for screening experiments. Of a total 87 investigated excipients, the i nitial screening experiments contained 5 lubricants, 9 binders, and 5 disin tegrants, and 35 experiments were carried out. Considering a reduced factor ial design was used the resulting PCA and partial least squares (PLS) model s offered good insight into the possibilities of tablet formulation. It als o offered solutions to the problems and clearly gave directions for optimum formulations. Further, it offered several alternatives for achieving quali ty formulations. Additional experiments conducted to validate and verify th e usefulness of the model were successful, resulting in several tablets of good quality. The conclusion is that a multivariate strategy in tablet form ulation is efficient and can be used to reduce the number of experiments dr astically. Combining multivariate characterization, physicochemical propert ies, experimental design, multivariate design, and PLS would lead to an evo lutionary strategy for tablet formulation. Since it includes a learning str ategy that continuously incorporates data for new compounds and from conduc ted experiments, this would be an even more powerful tool than expert syste ms.