Study on quality control of pharmaceutical cocrystal by NIRS
10.7501/j.issn.0253-2670.2013.19.010
- Author:
Shao-Guang LIU
1
Author Information
1. Research Center of TCM Processing Technology
- Publication Type:Journal Article
- Keywords:
NIRS;
Partial least squares regression method;
Quality control of cocrystal;
Rhein-lysine cocrystal;
Stability
- From:
Chinese Traditional and Herbal Drugs
2013;44(19):2683-2687
- CountryChina
- Language:Chinese
-
Abstract:
Objective: To establish a method for the quality control of pharmaceutical cocrystal based on NIRS, using rhein-lysine (lysirein) cocrystal as a case study. Methods: Integrating sphere diffuse reflectance accessory combining partial least squares regression algorithm to establish an analytical method for the content of rhein-lysine cocrystal, and the model was used to study environmental factors, as well as wet mixing and granulating process eutectic degradation conditions. Results: The correlation coefficients (r), root mean square error of calibration (RMSEC), root mean square error of prediction (RMSEP), and root-mean-squares error of cross-validation (RMSECV) of the proposed models were 0.9995, 0.0093, 0.0110, and 0.0120; Under high temperature and light conditions, the content of rhein-lysine cocrystal remained roughly constant (content change < 1%). Under high humidity and wet granulation process, there were some changes in cocrystal concentration, content change < 3%, but it was not significant. Conclusion: The proposed method is fast, non-destructive, simple, and accurate; Rhein-lysine cocrystal in environmental factors and modeling granulation process remains stable.
