Testing the performance of pure spectrum resolution from Raman hyperspectral images of differently manufactured pharmaceutical tablets

Balázs Vajna, Attila Farkas, Hajnalka Pataki, Zsolt Zsigmond, Tamás Igricz, György Marosi

Research output: Contribution to journalArticle

34 Citations (Scopus)


Chemical imaging is a rapidly emerging analytical method in pharmaceutical technology. Due to the numerous chemometric solutions available, characterization of pharmaceutical samples with unknown components present has also become possible. This study compares the performance of current state-of-the-art curve resolution methods (multivariate curve resolution-alternating least squares, positive matrix factorization, simplex identification via split augmented Lagrangian and self-modelling mixture analysis) in the estimation of pure component spectra from Raman maps of differently manufactured pharmaceutical tablets. The batches of different technologies differ in the homogeneity level of the active ingredient, thus, the curve resolution methods are tested under different conditions. An empirical approach is shown to determine the number of components present in a sample. The chemometric algorithms are compared regarding the number of detected components, the quality of the resolved spectra and the accuracy of scores (spectral concentrations) compared to those calculated with classical least squares, using the true pure component (reference) spectra. It is demonstrated that using appropriate multivariate methods, Raman chemical imaging can be a useful tool in the non-invasive characterization of unknown (e.g. illegal or counterfeit) pharmaceutical products.

Original languageEnglish
Pages (from-to)45-55
Number of pages11
JournalAnalytica Chimica Acta
Publication statusPublished - Jan 27 2012



  • Chemometrics
  • Hyperspectral
  • Imaging
  • Mapping
  • Micro-Raman
  • Pharmaceutical

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Environmental Chemistry
  • Spectroscopy

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