Study on Cefradine Granules Component Analysis and Calibration Transfer Method Based on Near-Infrared Spectroscopy
ZHOU Zi-kun1, 2, LI Chen-xi2 *, WANG Zhe1, 2, LIU Rong1, 2, CHEN Wen-liang1, 2, XU Ke-xin1, 2
1. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, Tianjin 300072, China
2. School of Precision Instrument and Optic Electronic Engineering, Tianjin University, Tianjin 300072, China
Abstract:Near-infrared spectroscopy (NIRS) technology has distinct advantages in component detection for its characteristics of high-speed and low-cost, which is essential for the supervision of drug quality and safety. Studying the method of drug component detection based on NIRS technology is significant for improving the level of drug quality supervision. In fact, owing to differences in performance parameters of different spectroscopic instruments, spectra measured are discrepancy, which brings hardship to the realization for quantitative correction models sharing. Therefore, in order to improve analysis efficiency, the calibration transfer method is discussed. In this paper, the establishment of cephalosporins component correction model and calibration transfer method are studied, and a transformation set selection method based on Markov chain (MC) is proposed. Fifty-six samples of cefradine granules in different batches were used. Spectral data were measured by two Fourier spectrometers. For three components of the sample: cefradine, Cefalexin and water, partial least squares (PLS) method was used to establish a quantitative correction model. MC algorithm is used to construct the probability matrix and select the conversion set, which improves the efficiency of model transformation and the prediction accuracy of spectral data. The experimental results show that the quantitative calibration model transfer between different spectroscopic instruments can be realized by using a small number of sample sets. After the model transfer, the relative error of the quantitative calibration model for the three principal components prediction decreases from 9.67%, 52.14%, 19.25% to 4.37%, 31.12%, 11.67%, respectively. The spectral differences between master and slave instruments can be corrected effectively, and the transfer and sharing of measurement spectra and quantitative analysis models of different instruments can be realized. The modeling analysis and model transfer methods studied in this paper also provide technical support for drug composition and quality detection.
周子堃,李晨曦,王 哲,刘 蓉,陈文亮,徐可欣. 近红外光谱的头孢类药品成分分析与模型传递方法[J]. 光谱学与光谱分析, 2020, 40(11): 3562-3566.
ZHOU Zi-kun, LI Chen-xi, WANG Zhe, LIU Rong, CHEN Wen-liang, XU Ke-xin. Study on Cefradine Granules Component Analysis and Calibration Transfer Method Based on Near-Infrared Spectroscopy. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40(11): 3562-3566.
[1] Roggo Y, Chalus P, Maurer L, et al. Journal of Pharmaceutical and Biomedical Analysis, 2007, 44(3): 683.
[2] Srikar A, Swapna D, Swathi G, et al. International Journal of Pharmacy and Technology, 2010, 2(1): 16.
[3] MA Bo-kai, GOU Xin-lei, ZHAO Xin-ying(马博凯, 勾新磊, 赵新颖). Food Safety and Quality Detection Technology(食品安全质量检测学报), 2016, 7(11): 4295.
[4] Mäntele W. Journal of Biological Physics, 2003, 9(2): 87.
[5] WEI Xue-min, WU Qian, LIU Qiang, et al(魏学敏, 吴 倩, 刘 强, 等). Chinese Journal of Pharmaceutical Analysis(药物分析杂志), 2013, 33(8): 1447.
[6] Boyer C, Gaudin K, Kauss T, et al. Journal of Pharmaceutical and Biomedical Analysis, 2012, 67: 10.
[7] Carvalho L C, Morais C L M, Lima K M G, et al. Food Analytical Methods, 2018, 11(7): 1857.
[8] Abel F F, Raffaele V, Onno E de Noord, et al. Journal of Chemometrics, 2017, 31(3): e2874.
[9] Filzmoser P, Todorov V. Analytica Chimica Acta, 2011, 705(1-2): 2.
[10] Workman J J. Applied Spectroscopy, 2018, 72(3): 340.
[11] CHU Xiao-li, YUAN Hong-fu, LU Wan-zhen(褚小立, 袁洪福, 陆婉珍). Chinese Journal of Analytical Chemistry(分析化学), 2002, 30(1): 114.
[12] Cortés V, Talens P, Barat J M, et al. Postharvest Biology and Technology, 2019, 148: 236.
[13] Chotard A, Auger A, Hansen N. Markov Chain Analysis of Evolution Strategies on a Linear Constraint Optimization Problem. 2014 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2014. 159.
[14] TIAN Gao-you, CHU Xiao-li, YUAN Hong-fu, et al(田高友, 褚小立, 袁洪福, 等). Chinese Journal of Analytical Chemistry(分析化学), 2006,(7): 927.
[15] Harshvardhan S, Ajaya K P, Hare K M. Measurement, 2019, 134: 698.