Ghafghazi Shiva, Moini Zanjani Taraneh, Vosough Maryam, Sabetkasaei Masoumeh
Department of Pharmacology, Neuroscience Research center, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Evin, Tehran, Iran.
Chemistry and Chemical Engineering Research Center of Iran, P.O. Box 14335-186 Tehran, Iran.
Iran J Pharm Res. 2017 Winter;16(1):120-131.
In the present study, a comprehensive and systematic strategy was described to evaluate the performance of several three-way calibration methods on a bio-analytical problem. Parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), self-weighted alternating trilinear decomposition (SWATLD), alternating penalty trilinear decomposition (APTLD), and unfolded partial least squares combined with the residual bilinearization procedure (U-PLS/RBL) were applied on high performance liquid chromatography with photodiode-array detection (HPLC-DAD) data to quantify carbamazepine (CBZ) in different serum samples. Using the proposed approach, successfully quantification of CBZ in human plasma, even in the presence of diverse uncalibrated serious interfering components was achieved. Moreover, the accuracy and precision of each algorithm for analyzing CBZ in serum samples were compared using root mean square error of prediction (RMSEP), the recovery values and figures of merits and reproducibility of the analysis. Satisfying recovery values for the analyte of interest were obtained by HPLC-DAD on a Bonus-RP column using an isocratic mode of elution with acetonitrile/K2HPO4 (pH = 7.5) buffer solution (45:55) coupled with second-order calibrations. Decreas of the analysis time and less solvent consumption are some of the pluses of this method. The analysis of real samples showed that the modeling of complex chromatographic profiles containing CBZ as the target drug using any of the mentioned algorithms can be potentially benefit drug monitoring in therapeutic research.
在本研究中,描述了一种全面系统的策略,以评估几种三向校准方法在一个生物分析问题上的性能。平行因子分析(PARAFAC)、交替三线性分解(ATLD)、自加权交替三线性分解(SWATLD)、交替惩罚三线性分解(APTLD)以及结合残差双线性化程序的展开偏最小二乘法(U-PLS/RBL)被应用于高效液相色谱-光电二极管阵列检测(HPLC-DAD)数据,以定量不同血清样品中的卡马西平(CBZ)。使用所提出的方法,即使在存在各种未校准的严重干扰成分的情况下,也成功实现了人血浆中CBZ的定量。此外,使用预测均方根误差(RMSEP)、回收率值以及分析的品质因数和重现性,比较了每种算法分析血清样品中CBZ的准确性和精密度。在Bonus-RP柱上,采用乙腈/K2HPO4(pH = 7.5)缓冲溶液(45:55)的等度洗脱模式结合二阶校准,通过HPLC-DAD获得了目标分析物令人满意的回收率值。减少分析时间和降低溶剂消耗是该方法的一些优点。实际样品分析表明,使用上述任何一种算法对以CBZ为目标药物的复杂色谱图进行建模,在治疗研究中可能有助于药物监测。