Application of self-organizing maps for the classification of chromatographic systems and prediction of values of chromatographic quantities

Abstract

The applicability of self-organizing maps (SOM) for the classification of chromatographic systems or components of chromatographic systems based on data taken from literature is shown. The SOM approach is compared to dendrogram and principal components analysis (PCA) approaches. It has been shown that the distance between classified objects could reveal linear correspondence with quantity to be optimized, e.g. resolution, so it can be applied in the chromatographic method development. SOMs can also be applied for prediction of chromatographic quantities. It is shown that SOM-based response surface modeling is comparable to triangular presentation of mobile phase composition response surfaces.