Satomi Hisanori, Mori Yoshikazu, Makino Bunsho, Nakai Youichiro, Takeda Shuichi, Aburada Masaki, Miyamoto Ken-ichi
Department of Clinical Pharmacy, Kanazawa University, Ishikawa, Japan.
Chem Pharm Bull (Tokyo). 2010 Nov;58(11):1497-501. doi: 10.1248/cpb.58.1497.
Kampo medicines, traditional herbal medicines in Japan, are comprised of multiple botanical raw materials that contain a number of pharmacologically active substances. Conventionally, the quality control of kampo medicines has been performed by analyzing the contents of two or three representative components. However, it is not sufficient to check quality only with a limited number of specific components. We performed HPLC of 287 lots of keishibukuryogan formulas, calculated the areas of 11 components on chromatograms as feature values and made a cluster analysis using self-organizing maps (SOMs). We verified the precision (repeatability and intermediate precision) of clustering results when using the same samples and successfully established an clustering method using SOMs that is capable of precisely clustering differences in HPLC-fingerprints among pharmaceutical manufacturers, differences in HPLC-fingerprints due to the combination ratios of botanical raw materials, and differences in HPLC-fingerprints due to changes in component contents caused by time-course deterioration. Consequently, we could confirm that this method is useful for controlling the quality of multiple component drugs and analyzing quality differences.
汉方药，即日本的传统草药，由多种植物原料组成，这些原料含有多种药理活性物质。传统上，汉方药的质量控制是通过分析两三种代表性成分的含量来进行的。然而，仅通过有限数量的特定成分来检查质量是不够的。我们对287批桂枝茯苓丸配方进行了高效液相色谱分析，计算了色谱图上11种成分的面积作为特征值，并使用自组织映射（SOM）进行了聚类分析。我们验证了使用相同样品时聚类结果的精密度（重复性和中间精密度），并成功建立了一种使用SOM的聚类方法，该方法能够精确地对不同制药商的高效液相色谱指纹图谱差异、由于植物原料组合比例导致的高效液相色谱指纹图谱差异以及由于随时间推移变质引起的成分含量变化导致的高效液相色谱指纹图谱差异进行聚类。因此，我们可以确认该方法对于多成分药物的质量控制和质量差异分析是有用的。
