Sena Marcelo M, Poppi Ronei J
Departamento de Química Analítica, Instituto de Química, Universidade Estadual de Campinas, PO Box 6154, CEP 13083-862, Campinas SP, Brazil.
J Pharm Biomed Anal. 2004 Jan 27;34(1):27-34. doi: 10.1016/j.japna.2003.08.011.
In this work, a simple and rapid analytical procedure was proposed for simultaneous determination of acetylsalicylic acid (ASA), paracetamol (PRC, also known as acetaminophen) and caffeine (CAF) in pharmaceutical formulations based on multivariate calibration and UV spectrophotometric measurements (210-300 nm). The calibration set was constructed with nine solutions in the concentration ranges from 10.0 to 15.0 microg x ml(-1) for ASA and PRC and from 2.0 to 6.0 microg x ml(-1) for CAF, according to an experimental design. The procedure was repeated at four different pH values: 2.0, 3.0, 4.0 and 5.0. Partial least squares (PLS) models were built at each pH and used to determinate a set of synthetic mixtures. The best model was obtained at pH 5.0. An N-way PLS model was applied to a three-way array constructed using all the pH data sets and enabled better results. This calibration model provided root mean squares errors of prediction (RMSEP) from 11.5 to 35% lower than those obtained with PLS at pH 5.0, depending on the analyte. The results achieved for the determination of these drugs in commercial tablets were in agreement to the values specified by the manufactures and the recovery was between 94.7 and 104.5%.
在本研究中，基于多元校准和紫外分光光度法测量（210 - 300 nm），提出了一种简单快速的分析方法，用于同时测定药物制剂中的乙酰水杨酸（ASA）、对乙酰氨基酚（PRC，也称为扑热息痛）和咖啡因（CAF）。根据实验设计，构建了校准集，其中包含九种溶液，ASA和PRC的浓度范围为10.0至15.0 μg x ml⁻¹，CAF的浓度范围为2.0至6.0 μg x ml⁻¹。该过程在四个不同的pH值（2.0、3.0、4.0和5.0）下重复进行。在每个pH值下建立偏最小二乘法（PLS）模型，并用于测定一组合成混合物。在pH 5.0时获得了最佳模型。将N - 路PLS模型应用于使用所有pH数据集构建的三维阵列，可得到更好的结果。该校准模型提供的预测均方根误差（RMSEP）比在pH 5.0时使用PLS获得的误差低11.5%至35%，具体取决于分析物。在市售片剂中测定这些药物所获得的结果与制造商规定的值一致，回收率在94.7%至104.5%之间。
