Comparison of different chemometric methods to extract chemical and physical information from Raman images of homogeneous and heterogeneous semi-solid pharmaceutical formulations

Abstract

In formulations of nanostructured lipid carriers, lipid solid dispersions and self-emulsifying drug delivery systems, it is common that a solid or semi-solid lipid excipient is mixed with a liquid solvent or liquid lipid. Even when the excipients are visually miscible upon melting, they might have microscopic non-homogeneities which could lead to instability over time and future phase separation. Raman mapping associated with chemometric methods can be useful to evaluate spatial distribution of compounds, however it has not been extensively applied to the formulations mentioned above. The aim of this work was to compare the outcomes of three different chemometric methods - principal components analysis (PCA), multivariate curve resolution with alternating least squares (MCR-ALS) and independent components analysis (ICA) - to study two systems of very different degrees of microscopic miscibility: cetyl palmitate + Transcutol^© (heterogeneous) and polyethylene glycol 6000 (PEG 6000) + Tween 80^© (homogeneous). These two samples were chosen due to large differences in spatial distribution of the compounds over the pixels which could require different approaches for data treatment. The three methods were compared regarding recovered concentrations (or scores), signals (or loadings) and the need for matrix augmentation to obtain reliable results. Results showed that PCA loadings were the mathematical differences of the spectra of pure compounds for both samples, and therefore only 'contrast images' could be generated. MCR and ICA provided signals that could be related to the chemical components, however MCR presented rotational ambiguities even for the very heterogeneous sample, a situation in which ICA performed better as a blind search method. For the homogeneous sample, both methods showed rank deficiency and therefore the use of a matrix augmentation was necessary. ICA and PCA allowed identifying physical modifications in the homogeneous semi-solid PEG 6000/Tween 80^® sample over the time, probably due to the folding/unfolding of the crystalline chains of PEG 6000. Therefore, this work discusses the ability of the three chemometrics methods to extract information from Raman spectra in order to characterize the chemical, spatial and even physical aspects of semi-solid pharmaceutical formulations, which could be of much use for stability studies of different drug delivery systems.

Keywords: ICA; MCR-ALS; PCA; Raman mapping; Semi-solid pharmaceutical formulations.