title: Setting local rank constraints by orthogonal projections for image resolution analysis: application to the determination of a low dose pharmaceutical compound.
abstract: Raman chemical imaging provides chemical and spatial information about pharmaceutical drug product. By using resolution methods on acquired spectra, the objective is to calculate pure spectra and distribution maps of image compounds. With multivariate curve resolution-alternating least squares, constraints are used to improve the performance of the resolution and to decrease the ambiguity linked to the final solution. Non negativity and spatial local rank constraints have been identified as the most powerful constraints to be used. In this work, an alternative method to set local rank constraints is proposed. The method is based on orthogonal projections pretreatment. For each drug product compound, raw Raman spectra are orthogonally projected to a basis including all the variability from the formulation compounds other than the product of interest. Presence or absence of the compound of interest is obtained by observing the correlations between the orthogonal projected spectra and a pure spectrum orthogonally projected to the same basis. By selecting an appropriate threshold, maps of presence/absence of compounds can be set up for all the product compounds. This method appears as a powerful approach to identify a low dose compound within a pharmaceutical drug product. The maps of presence/absence of compounds can be used as local rank constraints in resolution methods, such as multivariate curve resolution-alternating least squares process in order to improve the resolution of the system. The method proposed is particularly suited for pharmaceutical systems, where the identity of all compounds in the formulations is known and, therefore, the space of interferences can be well defined.
authors.affiliation: Technologie Servier, Orléans, France. Electronic address: mathieu.boiret@servier.com.
authors.forename: Mathieu
authors.initials: M
authors.lastname: Boiret
authors.affiliation: Grup de Quimiometria, Dept. Química Analítica, Universitat de Barcelona, Spain.
authors.forename: Anna
authors.initials: A
authors.lastname: de Juan
authors.affiliation: IRSTEA, UMR ITAP, 361, Montpellier, France.
authors.forename: Nathalie
authors.initials: N
authors.lastname: Gorretta
authors.affiliation: Technologie Servier, Orléans, France.
authors.forename: Yves-Michel
authors.initials: YM
authors.lastname: Ginot
authors.affiliation: IRSTEA, UMR ITAP, 361, Montpellier, France.
authors.forename: Jean-Michel
authors.initials: JM
authors.lastname: Roger
mesh_terms: D002482:Cellulose / Q000032:analysis; D007190:Indapamide / Q000032:analysis; D007785:Lactose / Q000032:analysis; D016018:Least-Squares Analysis; D008962:Models, Theoretical; D015999:Multivariate Analysis; D004364:Pharmaceutical Preparations / Q000032:analysis*; D025341:Principal Component Analysis; D013059:Spectrum Analysis, Raman; D013229:Stearic Acids / Q000032:analysis; D013607:Tablets / Q000737:chemistry
chemical_list: D004364:Pharmaceutical Preparations; D013229:Stearic Acids; D013607:Tablets; C031183:stearic acid; D002482:Cellulose; D007190:Indapamide; D007785:Lactose
keywords: Low dose compound; Multivariate curve resolution-alternating least squares; Orthogonal projections; Raman microscopy