Based on the data analysis of single prescription of traditional Chinese medicine regularity and new drug combination mining
LIU Xinya
HAN Xiangkun
PIAO Huilian
LI Yongcheng
WANG Yuzhi
ZHANG Xue
Abstract：Objective To carry out the concept of"simplifying drug use",explore the drug use rules of single flavor prescriptions in the Dictionary of Traditional Chinese Medicine Prescriptions through data mining,explore its medication rules and provide a basis for the development of new drugs.Methods Based on the single-flavor prescriptions recorded in the Dictionary of Traditional Chinese Medicine Prescriptions,frequency statistics,association rules(Apriori algorithm),and cluster analysis(IBM SPSS Modeler 18.0,IBM SPSS Statistics,Cytoscape 3.9.1)were used to identify high-frequency drugs,core symptoms,and potential drug combinations.Results A total of 2 903 single-flavor prescriptions were included,involving 736 Chinese medicines.Alum and Coptis are used most frequently,and among the high-frequency drugs,heat-clearing drugs are the most common;Covering 614 conditions,the core conditions are acne,bloody stool,ulce;Twelve associated drug groups and two new prescriptions were found.Conclusion Single-component medication highlights the characteristics of"simplicity and efficiency",and has more advantages for liver diseases.There is great potential for the development of single-component preparations and new drug research and development.The core drug also has the potential to reduce toxicity and enhance efficacy.This study provides data support for the modernization development of single-component preparations and the innovation of new traditional Chinese medicine drugs,and has important guiding significance for clinical application.
Keywords：Single prescription of traditional Chinese medicineDictionary of Traditional Chinese Medicine PrescriptionsData miningPrescription regularityApriori algorithmInnovative drug of traditional Chinese medicine
Publication Date：2025-08-30
Online Publishing Date：2025-09-30(First online date of this platform, not the publication date of the document)
Pages：8( 743-749,818 )