Infrared spectral band screening based on partial least squares is used for the quantitative analysis of mannitol-calcium chloride cocrystal
10.16438/j.0513-4870.2022-1079
- VernacularTitle:基于偏最小二乘回归的红外光谱波段筛选用于甘露醇-氯化钙共晶的定量分析
- Author:
Zu-di LI
1
;
Ke ZHANG
2
;
Ze-fei ZHANG
2
;
Shuai QIAN
1
;
Yuan-feng WEI
1
;
Jian-jun ZHANG
2
;
Yuan GAO
1
Author Information
1. School of Traditional Chinese Pharmacy, China Pharmaceutical University, Nanjing 211198, China
2. School of Pharmacy, China Pharmaceutical University, Nanjing 211198, China
- Publication Type:Research Article
- Keywords:
Fourier transform infrared spectroscopy;
partial least squares regression;
mannitol-calcium chloride cocrystal;
variable selection;
quantitative analysis
- From:
Acta Pharmaceutica Sinica
2023;58(4):1041-1048
- CountryChina
- Language:Chinese
-
Abstract:
Mannitol-calcium chloride metal organic framework (MOF) cocrystal significantly improved the tabletability of β-mannitol and could be developed as a new tablet filler. However, mannitol monomer was found in the product during the scale-up production of the excipient, which significantly affected the functional properties of the excipient. In this study, we intend to quantify the multi-component eutectic system of mannitol-calcium chloride. In this experiment, the MOF cocrystal excipient mannitol-calcium chloride cocrystal was used as the model compound, and infrared spectrum was collected. Based on partial least squares regression (PLSR) method, the abnormal bands were removed and the spectrum was preprocessed by normalization. The quantitative correction model of mannitol-calcium chloride MOF cocrystal content in cocrystal excipients was established and compared by two different variable screening methods, genetic algorithm (GA) and competitive adaptive reweighting algorithm (CARS). Two different variable screening methods, GA method and CARS method, were used to screen out 160 and 14 variables, respectively. The mannitol-calcium chloride cocrystal model established by CARS-PLSR method had the best performance, and the average relative error (MRE) and corrected root mean square error (RMSEC) of the model were 0.008 8 and 0.892 5, respectively, the determination coefficient (R2) of the model was increased from 0.978 3 to 0.994 4. The quantitative method of eutectic system established in this study has high prediction accuracy, fast detection speed and good stability, which is of great significance for optimizing the preparation process conditions and quality control methods of such eutectic excipients.
