Detection of low dose of piroxicam polymorph in pharmaceutical tablets by surface-enhanced Raman chemical imaging (SER-CI) and multivariate analysis.

This study demonstrates, for the first time, the ability of surface-enhanced Raman chemical imaging (SER-CI) combined with multivariate analysis to detect low levels (0.1% (w/w)) of a polymorphic form in a pharmaceutical mixture. In the studied formulation, piroxicam was used as a model molecule to develop this approach.

Towards a spray-coating method for the detection of low-dose compounds in pharmaceutical tablets using surface-enhanced Raman chemical imaging (SER-CI).

Surface-enhanced Raman chemical imaging (SER-CI) is a highly sensitive analytical tool recently used in the pharmaceutical field owing to the possibility to obtain high sensitivity along with spatial information. However, the covering method of the pharmaceutical samples such as tablets with metallic nanoparticles is a major issue for SER-CI analyses due to the difficulty to obtain a homogeneous covering of tablet surface with the SERS substrates. In this context, a spray-coating method was proposed in order to fully exploit the potential of SER-CI.

An iterative approach for compound detection in an unknown pharmaceutical drug product: Application on Raman microscopy.

Raman chemical imaging provides both spectral and spatial information on a pharmaceutical drug product. Even if the main objective of chemical imaging is to obtain distribution maps of each formulation compound, identification of pure signals in a mixture dataset remains of huge interest. In this work, an iterative approach is proposed to identify the compounds in a pharmaceutical drug product, assuming that the chemical composition of the product is not known by the analyst and that a low dose compound can be present in the studied medicine.

Setting local rank constraints by orthogonal projections for image resolution analysis: application to the determination of a low dose pharmaceutical compound.

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.

Application of chemometric algorithms to MALDI mass spectrometry imaging of pharmaceutical tablets.

During drug product development, the nature and distribution of the active substance have to be controlled to ensure the correct activity and the safety of the final medication. Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI), due to its structural and spatial specificities, provides an excellent way to analyze these two critical parameters in the same acquisition. The aim of this work is to demonstrate that MALDI-MSI, coupled with four well known multivariate statistical analysis algorithms (PCA, ICA, MCR-ALS and NMF), is a powerful technique to extract spatial and spectral information about chemical compounds from known or unknown solid drug product formulations.

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

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.

Application of independent component analysis on Raman images of a pharmaceutical drug product: pure spectra determination and spatial distribution of constituents.

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.

Tablet potency of Tianeptine in coated tablets by near infrared spectroscopy: model optimisation, calibration transfer and confidence intervals.

A near infrared (NIR) method was developed for determination of tablet potency of active pharmaceutical ingredient (API) in a complex coated tablet matrix. The calibration set contained samples from laboratory and production scale batches. The reference values were obtained by high performance liquid chromatography (HPLC) and partial least squares (PLS) regression was used to establish a model.

Synthesis and pharmacological evaluation of new 1,2-dithiolane based antioxidants.

Molecules containing a dithiolane moiety are widely investigated due to their antioxidant properties. The archetypal representative of this class of compounds is lipoic acid and indeed the lipoic acid-dihydrolipoic acid couple is part of the antioxidant defence system of the cell. In the course of a program aiming to find improved antioxidants effective in vivo, we designed, synthesised and pharmacologically investigated new lipoic acid analogs.