A key questions in general for chromatography and in particular for drug discovery is whether a given peak of interest represents co-eluting components. By using an algorithm in the LC/MS ChemStation to determining the number of components in a chromatographic peak. ( Just calculate a numerical value to characterize the degree of dissimilarity of the peak spectra, a so-called similarity factor, based on the match of the peak spectra to one another.)
Two Curves
In Summary, the threshold curve, represented by the broken line, gives the range for which spectral impurity lies within the noise limit. Above this threshold, spectral impurity exceeds the spectral background noise and the similarity curve intersects the threshold curve indicating an impurity providing the reference and noise parameters have been sensibly chosen.
Two Curves (1) Similarity curve: The mathematical fundamentals used in the similarity curve calculations are those used for the purity factor, however they are displayed in another format. All spectra from a peak are compared with one or more spectra selected by the operator, an apex spectrum for example. The degree of match or spectral similarity is plotted over time during elution. An ideal profile of a pure peak is a flat line at 1000.
(2) A threshold curve: shows the effect of noise on a given similarity curve. The effect increases rapidly towards both ends of the peak. In essence, a threshold curve is a similarity curve with background noise contribution.
