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 ty
pes of noise: additive and perturbative, The first type, additive noise, co
ntributes 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 p
atterns. The ability of the proposed approach to consider both types of noi
se significantly distinguishes it from existing methods of data analysis th
at are usually designed to treat only the additive noise. Analysis of the H
PLC signals in phase space eliminates the problem of perturbation noise and
enables detection and comparison of similar signal segments recorded at di
fferent retention times. The current study analyzes the chromatographic tra
ce organic impurity patterns collected from six different manufacturers of
L-tryptophan using three HPLC columns. For five manufacturers the variabili
ty of data recorded with the same column are in perfect agreement with the
proposed model. A significant variance of parameters is detected for one ma
nufacturer, thus indicating a possible change in its product consistency. T
he 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.