Clustering analysis of Keishibukuryogan formulas by use of self-organizing maps

フォーマット:

論文

責任表示:

Satomi, Hisanori ; Mori, Yoshikazu ; Makino, Bunsho ; Nakai, Youichiro ; Takeda, Shuichi ; Aburada, Masaki ; Miyamoto, Kenichi

言語:

英語

出版情報:

Pharmaceutical Society of Japan = 日本薬学会, 2010-11-01

著者名:

Satomi, Hisanori

Mori, Yoshikazu

Makino, Bunsho

Nakai, Youichiro

Takeda, Shuichi

Aburada, Masaki

Miyamoto, Kenichi

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掲載情報:

Chemical and Pharmaceutical Bulletin

ISSN:

0009-2363      

巻:

58

通号:

11

開始ページ:

1497

終了ページ:

1501

バージョン:

publisher

概要:

金沢大学附属病院薬剤部<br />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 medi … cines 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. © 2010 Pharmaceutical Society of Japan. 続きを見る

URL:

http://hdl.handle.net/2297/25780