The research and development （R＆D） process of Chinese medicine, with one notable feature, clinical application based, is significantly different from which of chemical and biological medicine, from laboratory resea...The research and development （R＆D） process of Chinese medicine, with one notable feature, clinical application based, is significantly different from which of chemical and biological medicine, from laboratory research to clinics. Besides, compound prescription is another character. Therefore, according to different R＆D theories between Chinese and Western medicine, we put forward a new strategy in drug design of Chinese medicine, which focuses on ＂combination- activity relationship （CAR）＂, taking prescription discovery, component identification and formula optimization as three key points to identify the drugs of high efficacy and low toxicity. The method of drug design of Chinese medicine includes： new prescription discovery based on clinical data and literature information, component identification based on computing and experimental research, as well as formula optimization based on system modeling. This paper puts forward the concept,research framework and techniques of drug design of Chinese medicine, which embodies the R＆D model of Chinese medicine, hoping to support the drug design of Chinese medicine theoretically and technologically.展开更多
Objective:To analyze the component law of Chinese patent medicines for anti-influenza and develop new prescriptions for anti-influenza by unsupervised data mining methods. Methods: Chinese patent medicine recipes for ...Objective:To analyze the component law of Chinese patent medicines for anti-influenza and develop new prescriptions for anti-influenza by unsupervised data mining methods. Methods: Chinese patent medicine recipes for anti-influenza were collected and recorded in the database, and then the correlation coefficient between herbs, core combinations of herbs and new prescriptions were analyzed by using modified mutual information, complex system entropy cluster and unsupervised hierarchical clustering, respectively. Results: Based on analysis of 126 Chinese patent medicine recipes, the frequency of each herb occurrence in these recipes, 54 frequently-used herb pairs, 34 core combinations were determined, and 4 new recipes for influenza were developed. Conclusion: Unsupervised data mining methods are able to mine the component law quickly and develop new prescriptions.展开更多
文摘The research and development （R＆D） process of Chinese medicine, with one notable feature, clinical application based, is significantly different from which of chemical and biological medicine, from laboratory research to clinics. Besides, compound prescription is another character. Therefore, according to different R＆D theories between Chinese and Western medicine, we put forward a new strategy in drug design of Chinese medicine, which focuses on ＂combination- activity relationship （CAR）＂, taking prescription discovery, component identification and formula optimization as three key points to identify the drugs of high efficacy and low toxicity. The method of drug design of Chinese medicine includes： new prescription discovery based on clinical data and literature information, component identification based on computing and experimental research, as well as formula optimization based on system modeling. This paper puts forward the concept,research framework and techniques of drug design of Chinese medicine, which embodies the R＆D model of Chinese medicine, hoping to support the drug design of Chinese medicine theoretically and technologically.
基金supported by Scientific Research Special Project of TCM Profession (200907001E)Science and Technology Special Major Project for "Significant New Drugs Formulation" (2009ZX09301-005-02)
文摘Objective:To analyze the component law of Chinese patent medicines for anti-influenza and develop new prescriptions for anti-influenza by unsupervised data mining methods. Methods: Chinese patent medicine recipes for anti-influenza were collected and recorded in the database, and then the correlation coefficient between herbs, core combinations of herbs and new prescriptions were analyzed by using modified mutual information, complex system entropy cluster and unsupervised hierarchical clustering, respectively. Results: Based on analysis of 126 Chinese patent medicine recipes, the frequency of each herb occurrence in these recipes, 54 frequently-used herb pairs, 34 core combinations were determined, and 4 new recipes for influenza were developed. Conclusion: Unsupervised data mining methods are able to mine the component law quickly and develop new prescriptions.
