Pharmaceutical fingerprinting in phase space. 1. Construction of phase fingerprints

Citation
Ti. Aksenova et al., Pharmaceutical fingerprinting in phase space. 1. Construction of phase fingerprints, ANALYT CHEM, 71(13), 1999, pp. 2423-2430
Citations number
22
Categorie Soggetti
Chemistry & Analysis","Spectroscopy /Instrumentation/Analytical Sciences
Journal title
ANALYTICAL CHEMISTRY
ISSN journal
00032700 → ACNP
Volume
71
Issue
13
Year of publication
1999
Pages
2423 - 2430
Database
ISI
SICI code
0003-2700(19990701)71:13<2423:PFIPS1>2.0.ZU;2-4
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 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.