Fast Raman chemical imaging of tablets with non-flat surfaces

Area of Science:

• Analytical Chemistry
• Pharmaceutical Analysis
• Spectroscopy

Background:

• Accurate spatial distribution analysis of multiple active pharmaceutical ingredients (APIs) within a single tablet is crucial for quality control.
• Traditional imaging methods may struggle with complex mixtures and low-concentration components.

Purpose of the Study:

• To evaluate and compare different Raman imaging methods for analyzing the distribution of three APIs in a curved, embossed analgesic tablet.
• To assess the impact of imaging techniques on the accuracy of API quantification and particle size analysis.

Main Methods:

• Micro-Raman spectroscopy with continuous focus adjustment and rapid data acquisition (approx. 60 spectra/sec).
• Application of univariate, self-modelling curve resolution (MCR), and regression analyses to derive pure component spectra and images.
• Image quality assessment, thresholding, and histogram analysis.
• Particle size analysis on thresholded images for the lowest concentration API (caffeine).

Main Results:

• Multivariate methods (MCR and regression) provided superior imaging of all three APIs compared to univariate analysis.
• The univariate image of caffeine was significantly affected by signals from more abundant APIs, a limitation overcome by multivariate approaches.
• Caffeine area coverage varied from 1% (univariate) to 4% (regression) depending on the imaging method.
• Particle size analysis was feasible only for caffeine due to the high abundance of other APIs.

Conclusions:

• Multivariate Raman imaging techniques offer enhanced accuracy for analyzing API distribution in complex pharmaceutical formulations.
• These methods are essential for overcoming signal interference from abundant components, particularly for low-concentration APIs.
• The choice of imaging and analysis method significantly impacts the quantitative results and subsequent particle size analysis.