基于线性方程组数学分离模型建立在线过程检测复方缬沙坦氢氯噻嗪片溶出度方法。 分别扫描缬沙坦和氢氯噻嗪的紫外吸收光谱, 两组分在最大吸收波长处完全重叠。 根据朗伯比尔定律吸光度加和性原理, 分别测定两组分在最大吸收波长处的吸光系数, 建立线性方程组数学分离模型, 采用光纤传感过程分析技术(FODT)检测缬沙坦氢氯噻嗪片的溶出度, 并与HPLC法相比较。 在规定的溶出介质中, 两种成分同时实时测定, 并且FODT累积溶出度与HPLC法相比较结果无显著性差异(p>0.05)。 不同批次药物的溶出行为一致, 说明制剂工艺稳定, 均匀度好。 溶出曲线显示缬沙坦溶出快于并高于氢氯噻嗪, 且30 min时两组分的溶出度均大于80%符合美国药典规定。 结果表明, 应用线性方程组数学分离模型结合FODT法可实现复方缬沙坦氢氯噻嗪片中双组分溶出度的同时检测, 并可提供双组分的溶出过程曲线和全部溶出数据, 直观反映各组分在各溶出时段的快慢, 为此药建立标准提供依据。 与HPLC法单点数据相比优势明显, 更有利于药品评价和抽验质量分析。

A method for on-line monitoring the dissolution of Valsartan and hydrochlorothiazide tablets assisted by mathematical separation model of linear equations was established. UV spectrums of valsartan and hydrochlorothiazide were overlapping completely at the maximum absorption wavelength respectively. According to the Beer-Lambert principle of absorbance additivity, the absorptivity of Valsartan and hydrochlorothiazide was determined at the maximum absorption wavelength, and the dissolubility of Valsartan and hydrochlorothiazide tablets was detected by fiber-optic dissolution test (FODT) assisted by the mathematical separation model of linear equations and compared with the HPLC method. Results show that two ingredients were real-time determined simultaneously in given medium. There was no significant difference for FODT compared with HPLC (p>0.05). Due to the dissolution behavior consistency, the preparation process of different batches was stable and with good uniformity. The dissolution curves of valsartan were faster and higher than hydrochlorothiazide. The dissolutions at 30 min of Valsartan and hydrochlorothiazide were concordant with US Pharmacopoeia. It was concluded that fiber-optic dissolution test system assisted by the mathematical separation model of linear equations that can detect the dissolubility of Valsartan and hydrochlorothiazide simultaneously, and get dissolution profiles and overall data, which can directly reflect the dissolution speed at each time. It can provide the basis for establishing standards of the drug. Compared to HPLC method with one-point data, there are obvious advantages to evaluate and analyze quality of sampling drug by FODT.