光谱学与光谱分析 |
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Simultaneous Quantitative Determination of Multicomponents in Tablets Based on Terahertz Time-Domain Spectroscopy |
CHEN Tao1, LI Zhi1, 2*, MO Wei1, 3, HU Fang-rong2 |
1. School of Mechano-electronic Engineering, Xidian University, Xi’an 710071, China 2. School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin 541004, China 3. China Electronics Standardization Institute, Beijing 100007, China |
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Abstract Terahertz time-domain spectroscopy (THz-TDS) combined with chemometric modeling methods was used to perform quantitative analysis of both active pharmaceutical ingredient (API) and excipient concentrations of multicomponent pharmaceutical mixtures. The THz spectra of ternary mixtures formulated with anhydrous theophylline, lactose monohydrate, magnesium stearate and quaternary mixtures composed of acetaminophen, lactose monohydrate, microcrystalline cellulose and soluble starch were measured using THz-TDS. Two multivariate calibration methods, principal component regression (PCR) and partial least squares (PLS) regression, were employed to correlate THz absorbance spectra with the pharmaceutical tablet concentrations. Both API and excipient concentrations of mixtures were predicted simultaneously, and the PLS method provides better result than PCR method. The correlation coefficients of calibration (Rcal) and validation (Rval) for ternary mixtures’ components, anhydrous theophylline and lactose monohydrate, were all more than 0.98. The Rcal and Rval for quaternary mixtures’ components, acetaminophen, lactose monohydrate, microcrystalline cellulose and soluble starch, were all more than 0. 93, 0.98, 0.63 and 0.86, respectively. Experimental results show that THz-TDS combined with chemometrics is feasible in nondestructive quantitative analysis of multicomponent mixtures, and it can be widely applied in the fields of pharmaceutical analysis and others.
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Received: 2013-01-07
Accepted: 2013-03-04
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Corresponding Authors:
LI Zhi
E-mail: cclizhi@guet.edu.cn
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[1] Li Y, Gao J P, Xu X. Journal of Chinese Pharmaceutical Sciences, 2005, 14(2): 110. [2] LIU Yuan, XIE Meng-xia, CHEN Shi-zhong(刘 媛,谢孟峡,陈世忠). Journal of Beijing Normal University·Natural Science(北京师范大学学报·自然科学版), 2001, 37(2): 217. [3] Suryanarayanan R, Herman C S. International Journal of Pharmaceutics, 1991, 77(2-3): 287. [4] Atef E, Chauhan H, Prasad D, et al. ISRN Chromatography, 2012, 2012: 1. [5] CHEN Rong(陈 荣). Chinese Journal of Pharmaceutical Analysis(药物分析杂志), 2010, 30(9): 1770. [6] Heinza A, Savolainen M, Rades T, et al. European Journal of Pharmaceutical Sciences, 2007, 32(3): 182. [7] Hua Y F, Zhang H J. IEEE Transactions on Microwave Theory and Techniques, 2010, 58(7): 2064. [8] Ueno Y, Rungsawang R, Tomita I, et al. Analytical Chemistry, 2006, 78(15): 5424. [9] Xiong W, Shen J L, Pan R, et al. Proceedings of SPIE, 2009, 7835: 73850I. [10] Wang Y X, Zhao Z R, Chen Z Q, et al. Journal of Applied Physics, 2007, 102(11): 113108. [11] YANG Yu-ping, DONG Rui-lin, ZHANG Zhen-wei(杨玉平, 董睿林, 张振伟). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2012, 32(11): 3035. [12] Shen Y C. International Journal of Pharmaceutics, 2011, 417(1-2): 48. [13] Weakley A T, Warwick P C, Bitterwolf T E, et al. Applied Spectroscopy, 2012, 66(11): 1269. [14] ZHANG Xu, YAO Ming-yin, LIU Mu-hua(张 旭, 姚明印, 刘木华). Acta Physica Sinica(物理学报), 2013, 62(4): 044211. [15] Yu H Y, Niu X Y, Lin H J, et al. Food Chemistry, 2009, 113(1): 291.
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