Abstract
The present study proposes a general method for constructing pharmaceutical fingerprints in the analysis of HPLC trace organic impurity patterns. The approach considers signals in phase space and accounts for two different types of noise: additive and perturbative. The first type, additive noise, contributes to distortion of the absolute values of signal peaks. The second type, perturbative noise, contributes to variations of the retention times of signal peaks and distorts the time scale of the trace organic impurity patterns. The ability of the proposed approach to consider both types of noise significantly distinguishes it from existing methods of data analysis that are usually designed to treat only the additive noise. Analysis of the HPLC signals in phase space eliminates the problem of perturbation noise and enables detection and comparison of similar signal segments recorded at different retention times. The current study analyzes the chromatographic trace organic impurity patterns collected from six different manufacturers of L-tryptophan using three HPLC columns. For five manufacturers the variability of data recorded with the same column are in perfect agreement with the proposed model. A significant variance of parameters is detected for one manufacturer, thus indicating a possible change in its product consistency. The analysis in phase space is also used to explain the previously detected variability of HPLC signals across columns. The accompanying paper reports an application of the proposed approach for the pattern recognition of HPLC data.
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