Efficient detection of specific pharmaceutical components in compound medications based on Raman spectroscopy

The application of Raman detection technology in drug component analysis is becoming increasingly widespread; however, the complexity of many pharmaceutical formulations poses significant challenges for component analysis. This study proposes an efficient method for detecting specific components in composite medications. Initially, Raman spectroscopy is employed to analyze the target components without sample preparation, thereby conserving detection time. The study also addresses noise and fluorescence interferences that arise during the detection process. The airPLS algorithm is utilized to mitigate noise interference, while a novel approach is proposed that combines the airPLS algorithm with the interpolation peak-valley method to eliminate fluorescence interference from the spectra. Furthermore, the method integrates Density Functional Theory (DFT) with experimental Raman spectral analysis to examine the components of composite medications. The experimental results demonstrate that this approach reduces detection time, resolves both types of interference, and accurately identifies the target components, thereby enhancing the detection success rate. • Use Raman spectroscopy for non-destructive detection of a specific component in a pharmaceutical formulation. • Use the airPLS algorithm to resolve noise and combine it with peak-valley interpolation to reduce fluorescence interference. • Refine the peak-valley method with PCHIP interpolation and detection to address baseline drift from fluorescence interference. • Use Density Functional Theory and Raman spectroscopy to analyze pharmaceutical formulation components.