Literature DB >> 25462118

Distribution of a low dose compound within pharmaceutical tablet by using multivariate curve resolution on Raman hyperspectral images.

Mathieu Boiret1, Anna de Juan2, Nathalie Gorretta3, Yves-Michel Ginot4, Jean-Michel Roger3.   

Abstract

In this work, Raman hyperspectral images and multivariate curve resolution-alternating least squares (MCR-ALS) are used to study the distribution of actives and excipients within a pharmaceutical drug product. This article is mainly focused on the distribution of a low dose constituent. Different approaches are compared, using initially filtered or non-filtered data, or using a column-wise augmented dataset before starting the MCR-ALS iterative process including appended information on the low dose component. In the studied formulation, magnesium stearate is used as a lubricant to improve powder flowability. With a theoretical concentration of 0.5% (w/w) in the drug product, the spectral variance contained in the data is weak. By using a principal component analysis (PCA) filtered dataset as a first step of the MCR-ALS approach, the lubricant information is lost in the non-explained variance and its associated distribution in the tablet cannot be highlighted. A sufficient number of components to generate the PCA noise-filtered matrix has to be used in order to keep the lubricant variability within the data set analyzed or, otherwise, work with the raw non-filtered data. Different models are built using an increasing number of components to perform the PCA reduction. It is shown that the magnesium stearate information can be extracted from a PCA model using a minimum of 20 components. In the last part, a column-wise augmented matrix, including a reference spectrum of the lubricant, is used before starting MCR-ALS process. PCA reduction is performed on the augmented matrix, so the magnesium stearate contribution is included within the MCR-ALS calculations. By using an appropriate PCA reduction, with a sufficient number of components, or by using an augmented dataset including appended information on the low dose component, the distribution of the two actives, the two main excipients and the low dose lubricant are correctly recovered.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Active and excipient distributions; Alternating least squares; Low dose compound; Multivariate curve resolution; Raman hyperspectral imaging

Mesh:

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Year:  2014        PMID: 25462118     DOI: 10.1016/j.jpba.2014.10.024

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  2 in total

1.  Fiber-Array-Based Raman Hyperspectral Imaging for Simultaneous, Chemically-Selective Monitoring of Particle Size and Shape of Active Ingredients in Analgesic Tablets.

Authors:  Timea Frosch; Elisabeth Wyrwich; Di Yan; Juergen Popp; Torsten Frosch
Journal:  Molecules       Date:  2019-11-30       Impact factor: 4.411

2.  Multivariate unmixing approaches on Raman images of plant cell walls: new insights or overinterpretation of results?

Authors:  Batirtze Prats-Mateu; Martin Felhofer; Anna de Juan; Notburga Gierlinger
Journal:  Plant Methods       Date:  2018-07-04       Impact factor: 4.993

  2 in total

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