Thorough characterization of a Self-Emulsifying Drug Delivery System with Raman hyperspectral imaging: a case study.

Newly developed drugs often have poor bioavailability due to their poor water solubility (BCS class 2 drugs). It is therefore necessary to develop new strategies to enhance their solubility and their activity, among which, Self-Emulsifying Drug Delivery System (SEDDS). The efficacy of the drugs contained in these preparations is mainly affected by the solid state and the particle size of the active pharmaceutical ingredient (API). However, it is quite complex, long and expensive to characterize these parameters with classical techniques such as X-ray powder diffraction, differential scanning calorimetry or hot stage microscopy. The present article presents, through a case study, the advantages of the Raman hyperspectral imaging in the characterization of such formulations. Indeed, Raman chemical imaging may fully characterize SEDDS with single equipment and operator in a non-destructive way allowing the follow-up of the formulation during stability studies. Raman imaging is therefore a tool of choice in the PAT framework since it increases the knowledge of the formulation and the process. A quantitative multivariate method using Raman hyperspectral imaging to assay the API in the lipid based formulation has been developed and fully validated following the "total error" approach.

A new criterion to assess distributional homogeneity in hyperspectral images of solid pharmaceutical dosage forms.

During galenic formulation development, homogeneity of distribution is a critical parameter to check since it may influence activity and safety of the drug. Raman hyperspectral imaging is a technique of choice for assessing the distributional homogeneity of compounds of interest. Indeed, the combination of both spectroscopic and spatial information provides a detailed knowledge of chemical composition and component distribution. Actually, most authors assess homogeneity using parameters of the histogram of intensities (e.g. mean, skewness and kurtosis). However, this approach does not take into account spatial information and loses the main advantage of imaging. To overcome this limitation, we propose a new criterion: Distributional Homogeneity Index (DHI). DHI has been tested on simulated maps and formulation development samples. The distribution maps of the samples were obtained without validated calibration model since different formulations were under investigation. The results obtained showed a linear relationship between content uniformity values and DHI values of distribution maps. Therefore, DHI methodology appears to be a suitable tool for the analysis of homogeneity of distribution maps even without calibration during formulation development.

Building the quality into pellet manufacturing environment--feasibility study and validation of an in-line quantitative near infrared (NIR) method.

The present study focuses on the implementation of an in-line quantitative near infrared (NIR) spectroscopic method for determining the active content of pharmaceutical pellets. The first aim was to non-invasively interface a dispersive NIR spectrometer with four realistic particle streams existing in the pellets manufacturing environment. Regardless of the particle stream characteristics investigated, NIR together with Principal Component Analysis (PCA) was able to classify the samples according to their active content. Further, one of these particle stream interfaces was non-invasively investigated with a FT-NIR spectrometer. A predictive model based on Partial Least Squares (PLS) regression was able to determine the active content of pharmaceutical pellets. The NIR method was finally validated with an external validation set for an API concentration range from 80 to 120% of the targeted active content. The prediction error of 0.9% (root mean standard error of prediction, RMSEP) was low, indicating the accuracy of the NIR method. The accuracy profile on the validation results, an innovative approach based on tolerance intervals, demonstrated the actual and future performance of the in-line NIR method. Accordingly, the present approach paves the way for real-time release-based quality system.