Comparison of classification approaches applied to NIR-spectra of clinical study lots

NIR-spectroscopy combined with pattern recognition approaches is applied to classify samples of clinical study lots in the pharmaceutical industry. The performance of linear discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K-nearest neighbour (KNN) method is evaluated on a tablet data set and a capsule data set. To establish a classification model a strategy is followed, which is described in this work. Frequently, in the pharmaceutical industry, several batches of the same clinical study lot are produced. We tested whether it is possible to merge several batches in one class for modelling or, instead, whether it is necessary to model each batch individually.