Study on dichloromethane content measurement of the preparation process of microspheres based on in-line Raman spectroscopy.

Microsphere formulations are extensively investigated as innovative drug delivery systems. Given their intricate formulation mechanism and process parameters, it is essential to evaluate and control their critical quality attributes (CQAs). During the microsphere preparation process, the concentration of dichloromethane (DCM) in the aqueous phase significantly influences performance of microsphere. Currently, traditional detection methods for DCM in the aqueous phase are mainly offline, which has several weaknesses such as requiring destructive sampling and being time-consuming and results in delaying product analysis. In this study, in-situ Raman spectroscopy was successfully applied to real-time monitor content of DCM in the aqueous phase during the microsphere preparation process and Rotigotine was used as the model drug. Additionally, the DCM concentration during preparation was determined off-line using headspace gas chromatography (HS-GC), then the spectral data were correlated through partial least squares regression (PLS) to build a quantitative analysis model. To eliminate external environment interfering in Raman spectroscopy, 10 preprocessing methods were employed to evaluate the accuracy of the model. The results revealed that the spectra based on standard normal variate transformation (SNV), first derivative (FD), savitzky-golay (S-G) and mean center (MC) significantly enhanced the predictive capacity of the model. The optimized model exhibited the following parameters: root mean square error of calibration (RMSEC) is 0.5857 mg/mL, root mean square error of cross validation (RMSECV) is 0.7436 mg/mL, root mean square error of prediction (RMSEP) is 0.4223 mg/mL, determination coefficient of calibration (R2C) is 0.9878, determination coefficient of cross-validation (R2CV) is 0.9804, and determination coefficient of validation (R2P) is 0.9918. This research successfully realized accurate online measurement and quality control of DCM content during microsphere preparation, which effectively improved the detection efficiency and avoided the influence of sample preparation on the measurement accuracy compared with the previous offline detection methods.