Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
AAPS PharmSciTech. 2013 Jun;14(2):802-10. doi: 10.1208/s12249-013-9966-9. Epub 2013 May 2.
Botanical drug products have batch-to-batch quality variability due to botanical raw materials and the current manufacturing process. The rational evaluation and control of product quality consistency are essential to ensure the efficacy and safety. Chromatographic fingerprinting is an important and widely used tool to characterize the chemical composition of botanical drug products. Multivariate statistical analysis has showed its efficacy and applicability in the quality evaluation of many kinds of industrial products. In this paper, the combined use of multivariate statistical analysis and chromatographic fingerprinting is presented here to evaluate batch-to-batch quality consistency of botanical drug products. A typical botanical drug product in China, Shenmai injection, was selected as the example to demonstrate the feasibility of this approach. The high-performance liquid chromatographic fingerprint data of historical batches were collected from a traditional Chinese medicine manufacturing factory. Characteristic peaks were weighted by their variability among production batches. A principal component analysis model was established after outliers were modified or removed. Multivariate (Hotelling T(2) and DModX) control charts were finally successfully applied to evaluate the quality consistency. The results suggest useful applications for a combination of multivariate statistical analysis with chromatographic fingerprinting in batch-to-batch quality consistency evaluation for the manufacture of botanical drug products.
由于植物原料和当前的制造工艺，植物药产品批次间存在质量变异性。合理评估和控制产品质量一致性对于确保疗效和安全性至关重要。色谱指纹图谱是表征植物药产品化学成分的重要且广泛使用的工具。多元统计分析已显示出其在许多工业产品质量评估中的功效和适用性。本文提出了将多元统计分析和色谱指纹图谱相结合，用于评估植物药产品的批次间质量一致性。选择中国的一种典型植物药产品参麦注射液作为实例，验证了该方法的可行性。从一家中药制造厂收集历史批次的高效液相色谱指纹图谱数据。通过对生产批次之间的变化性进行加权，确定特征峰。修改或去除离群值后，建立主成分分析模型。最后成功应用多元（Hotelling T(2) 和 DModX）控制图来评估质量一致性。结果表明，多元统计分析与色谱指纹图谱相结合，可用于评估植物药产品制造过程中的批次间质量一致性，具有很好的应用前景。
