Ye Ji, Zhang Xi, Dai Weixing, Yan Shikai, Huang Haiqiang, Liang Xu, Li Yushan, Zhang Weidong
School of Pharmacy, Second Military Medical University, Shanghai 200433, PR China.
J Pharm Biomed Anal. 2009 Apr 5;49(3):638-45. doi: 10.1016/j.jpba.2008.12.009. Epub 2008 Dec 24.
For quality control purpose, an approach of chemical fingerprinting of Liuwei Dihuang Pill (LDP) and simultaneous determination of its multiple bioactive components were established by using high performance liquid chromatograph (HPLC) coupled with multiple detection techniques. HPLC with ultraviolet detection (HPLC-UV) was used to acquire its fingerprint, and HPLC with combined detections of diode array detector and evaporative light scattering detector (HPLC-DAD-ELSD) was performed to simultaneously determine eight bioactive constituents: including gallic acid, 5-hydroxymethyl furfural, morroniside, sweroside, loganin, paeoniflorin, paeonol and alisol B-23 acetate. The detection limits and quantification limits ranged in 0.11-1.93mug/mL and 0.38-3.85mug/mL, respectively. The validation of the proposed approach was acceptable, with 93.47-104.62% accuracy in recovery test. The intra- and inter-day precisions of the method were evaluated and were less than 3.87%, with accuracy from 95.3% to 103.4%. In addition, the mass spectrometry of the investigated major constituents was also studied. Based on the chromatographic fingerprint data, partial least square (PLS) and discriminate analysis were utilized to visualize the quality information of 60 batches of LDP, and a partial least square-discriminate analysis (PLS-DA) model was constructed with acceptable predictive performance for the discrimination of various products. The proposed approach was expected to be developed as a powerful tool for the quality control of LDP.
为了进行质量控制,采用高效液相色谱仪(HPLC)结合多种检测技术,建立了六味地黄丸(LDP)的化学指纹图谱及同时测定其多种生物活性成分的方法。采用带紫外检测的HPLC(HPLC-UV)获取其指纹图谱,采用二极管阵列检测器和蒸发光散射检测器联用的HPLC(HPLC-DAD-ELSD)同时测定8种生物活性成分,包括没食子酸、5-羟甲基糠醛、莫诺苷、獐牙菜苷、马钱苷、芍药苷、丹皮酚和泽泻醇B-23-乙酸酯。检测限和定量限分别为0.11-1.93μg/mL和0.38-3.85μg/mL。所提方法的验证结果可接受,回收率试验的准确度为93.47%-104.62%。对该方法的日内和日间精密度进行了评估,精密度均小于3.87%,准确度为95.3%-103.4%。此外,还对所研究的主要成分进行了质谱分析。基于色谱指纹图谱数据,利用偏最小二乘法(PLS)和判别分析对60批LDP的质量信息进行可视化,构建了具有可接受预测性能的偏最小二乘判别分析(PLS-DA)模型,用于区分不同产品。所提方法有望发展成为LDP质量控制的有力工具。