title: Application of independent component analysis on Raman images of a pharmaceutical drug product: pure spectra determination and spatial distribution of constituents.
abstract: Independent component analysis (ICA) was used as a blind source separation method on a Raman image of a pharmaceutical tablet. Calculations were performed without a priori knowledge concerning the formulation. The aim was to extract the pure signals from the initial data set in order to examine the distribution of actives and major excipients within the tablet. As a method based on the decomposition of a matrix of mixtures of several components, the number of independent component to choose is a critical step of the analysis. The ICA_by_blocks method, based on the calculation of several models using an increasing number of independent components on initial matrix blocks, was used. The calculated ICA signals were compared with the pure spectra of the formulation compounds. High correlations between the two active principal ingredient spectra and their corresponding calculated signals were observed giving a good overview of the distributions of these compounds within the tablet. Information from the major excipients (lactose and avicel) was found in several independent components but the ICA approach provides high level of information concerning their distribution within the tablet. However, the results could vary considerably by changing the number of independent components or the preprocessing method. Indeed, it was shown that under-decomposition of the matrix could lead to better signal quality (compared to the pure spectra) but in that case the contributions due to minor components or effects were not correctly identified and extracted. On the contrary, over-decomposition of the original dataset could provide information about low concentration compounds at the expense of some loss of signal interpretability for the other compounds.
authors: Technologie Servier, 27 rue Eugène Vignat, 45000 Orléans, France. Electronic address: mathieu.boiret@fr.netgrs.com.
authors: Mathieu
authors: M
authors: Boiret
authors: AgroParisTech, UMR 1145 Ingénierie Procédés Aliments, rue Claude Bernard, F-75005 Paris, France.
authors: Douglas N
authors: DN
authors: Rutledge
authors: Irstea, UMR ITAP 361, Avenue Jean-François Breton, 34033 Montpellier, France.
authors: Nathalie
authors: N
authors: Gorretta
authors: Technologie Servier, 27 rue Eugène Vignat, 45000 Orléans, France.
authors: Yves-Michel
authors: YM
authors: Ginot
authors: Irstea, UMR ITAP 361, Avenue Jean-François Breton, 34033 Montpellier, France.
authors: Jean-Michel
authors: JM
authors: Roger
mesh_terms: D000465:Algorithms; D002482:Cellulose / Q000737:chemistry; D002626:Chemistry, Pharmaceutical / Q000379:methods; D005079:Excipients / Q000737:chemistry*; D007190:Indapamide / Q000008:administration & dosage / Q000737:chemistry*; D007785:Lactose / Q000737:chemistry; D020913:Perindopril / Q000008:administration & dosage / Q000737:chemistry*; D025341:Principal Component Analysis / Q000379:methods; D013059:Spectrum Analysis, Raman / Q000379:methods*; D013607:Tablets
chemical_list: D005079:Excipients; D013607:Tablets; D002482:Cellulose; D007190:Indapamide; D007785:Lactose; D020913:Perindopril
keywords: Chemical imaging; Chemometrics; Hyperspectral imaging; Independent component analysis; Raman