TCMLLM-PR:evaluation of large language models for prescription recommendation in traditional Chinese medicine

Objective To develop and evaluate a fine-tuned large language model(LLM)for traditional Chinese medicine(TCM)prescription recommendation named TCMLLM-PR.Methods First,we constructed an instruction-tuning dataset containing 68654 samples(ap-proximately 10 million tokens)by integrating data from eight sources,including four TCM textbooks,Pharmacopoeia of the People’s Republic of China 2020(CHP),Chinese Medicine Clinical Cases(CMCC),and hospital clinical records covering lung disease,liver disease,stroke,diabetes,and splenic-stomach disease.Then,we trained TCMLLM-PR using Chat-GLM-6B with P-Tuning v2 technology.The evaluation consisted of three aspects:(i)compari-son with traditional prescription recommendation models(PTM,TCMPR,and PresRecST);(ii)comparison with TCM-specific LLMs(ShenNong,Huatuo,and HuatuoGPT)and general-domain ChatGPT;(iii)assessment of model migration capability across different disease datasets.We employed precision,recall,and F1 score as evaluation metrics.Results The experiments showed that TCMLLM-PR significantly outperformed baseline models on TCM textbooks and CHP datasets,with F1@10 improvements of 31.80%and 59.48%,respectively.In cross-dataset validation,the model performed best when migrating from TCM textbooks to liver disease dataset,achieving an F1@10 of 0.1551.Analysis of real-world cases demonstrated that TCMLLM-PR's prescription recommendations most closely matched actual doctors’prescriptions.Conclusion This study integrated LLMs into TCM prescription recommendations,leverag-ing a tailored instruction-tuning dataset and developing TCMLLM-PR.This study will pub-licly release the best model parameters of TCMLLM-PR to promote the development of the decision-making process in TCM practices(https://github.com/2020MEAI/TCMLLM).

Construction and optimization of traditional Chinese medicine constitution prediction models based on deep learning

Objective To cater to the demands for personalized health services from a deep learning per-spective by investigating the characteristics of traditional Chinese medicine(TCM)constitu-tion data and constructing models to explore new prediction methods.Methods Data from students at Chengdu University of Traditional Chinese Medicine were collected and organized according to the 24 solar terms from January 21,2020,to April 6,2022.The data were used to identify nine TCM constitutions,including balanced constitution,Qi deficiency constitution,Yang deficiency constitution,Yin deficiency constitution,phlegm dampness constitution,damp heat constitution,stagnant blood constitution,Qi stagnation constitution,and specific-inherited predisposition constitution.Deep learning algorithms were employed to construct multi-layer perceptron(MLP),long short-term memory(LSTM),and deep belief network(DBN)models for the prediction of TCM constitutions based on the nine constitution types.To optimize these TCM constitution prediction models,this study in-troduced the attention mechanism(AM),grey wolf optimizer(GWO),and particle swarm op-timization(PSO).The models’performance was evaluated before and after optimization us-ing the F1-score,accuracy,precision,and recall.Results The research analyzed a total of 31655 pieces of data.(i)Before optimization,the MLP model achieved more than 90%prediction accuracy for all constitution types except the balanced and Qi deficiency constitutions.The LSTM model's prediction accuracies exceeded 60%,indicating that their potential in TCM constitutional prediction may not have been fully realized due to the absence of pronounced temporal features in the data.Regarding the DBN model,the binary classification analysis showed that,apart from slightly underperforming in predicting the Qi deficiency constitution and damp heat constitution,with accuracies of 65%and 60%,respectively.The DBN model demonstrated considerable discriminative power for other constitution types,achieving prediction accuracy rates and area under the receiver op-erating characteristic(ROC)curve(AUC)values exceeding 70%and 0.78,respectively.This indicates that while the model possesses a certain level of constitutional differentiation abili-ty,it encounters limitations in processing specific constitutional features,leaving room for further improvement in its performance.For multi-class classification problem,the DBN model’s prediction accuracy rate fell short of 50%.(ii)After optimization,the LSTM model,enhanced with the AM,typically achieved a prediction accuracy rate above 75%,with lower performance for the Qi deficiency constitution,stagnant blood constitution,and Qi stagna-tion constitution.The GWO-optimized DBN model for multi-class classification showed an increased prediction accuracy rate of 56%,while the PSO-optimized model had a decreased accuracy rate to 37%.The GWO-PSO-DBN model,optimized with both algorithms,demon-strated an improved prediction accuracy rate of 54%.Conclusion This study constructed MLP,LSTM,and DBN models for predicting TCM consti-tution and improved them based on different optimisation algorithms.The results showed that the MLP model performs well,the LSTM and DBN models were effective in prediction but with certain limitations.This study also provided a new technology reference for the es-tablishment and optimisation strategies of TCM constitution prediction models,and a novel idea for the treatment of non-disease.

Integrative analysis of bone-formation associated genes and immune cell infiltration in osteoporosis, and the prediction of active ingredients in targeted traditional Chinese medicine

Objective To explore the differential expression and mechanisms of bone formation-related genes in osteoporosis(OP)leveraging bioinformatics and machine learning methodologies;and to predict the active ingredients of targeted traditional Chinese medicine(TCM)herbs.Methods The Gene Expression Omnibus(GEO)and GeneCards databases were employed to conduct a comprehensive screening of genes and disease-associated loci pertinent to the pathogenesis of OP.The R package was utilized as the analytical tool for the identification of differentially expressed genes.Least absolute shrinkage and selection operator(LASSO)logis-tic regression analysis and support vector machine-recursive feature elimination(SVM-RFE)algorithm were employed in defining the genetic signature specific to OP.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analyses for the selected pivotal genes were conducted.The cell-type identification by estimating rela-tive subsets of RNA transcripts(CIBERSORT)algorithm was leveraged to examine the infiltra-tion patterns of immune cells;with Spearman’s rank correlation analysis utilized to assess the relationship between the expression levels of the genes and the presence of immune cells.Coremine Medical Database was used to screen out potential TCM herbs for the treatment of OP.Comparative Toxicogenomics Database(CTD)was employed for forecasting the TCM ac-tive ingredients targeting the key genes.AutoDock Vina 1.2.2 and GROMACS 2020 softwares were employed to conclude analysis results;facilitating the exploration of binding affinity and conformational dynamics between the TCM active ingredients and their biological targets.Results Ten genes were identified by intersecting the results from the GEO and GeneCards databases.Through the application of LASSO regression and SVM-RFE algorithm;four piv-otal genes were selected:coat protein(CP);kallikrein 3(KLK3);polymeraseγ(POLG);and transient receptor potential vanilloid 4(TRPV4).GO and KEGG pathway enrichment analy-ses revealed that these trait genes were predominantly engaged in the regulation of defense response activation;maintenance of cellular metal ion balance;and the production of chemokine ligand 5.These genes were notably associated with signaling pathways such as ferroptosis;porphyrin metabolism;and base excision repair.Immune infiltration analysis showed that key genes were highly correlated with immune cells.Macrophage M0;M1;M2;and resting dendritic cell were significantly different between groups;and there were signifi-cant differences between different groups(P<0.05).The interaction counts of resveratrol;curcumin;and quercetin with KLK3 were 7;3;and 2;respectively.It shows that the interac-tions of resveratrol;curcumin;and quercetin with KLK3 were substantial.Molecular docking and molecular dynamics simulations further confirmed the robust binding affinity of these bioactive compounds to the target genes.Conclusion Pivotal genes including CP;KLK3;POLG;and TRPV4;exhibited commendable significant prognostic value;and played a crucial role in the diagnostic assessment of OP.Resveratrol;curcumin;and quercetin;natural compounds found in TCM;showed promise in their potential to effectively modulate the bone-forming gene KLK3.This study provides a sci-entific basis for the interpretation of the pathogenesis of OP and the development of clinical drugs.

The enlightenment of artificial intelligence large-scale model on the research of intelligent eye diagnosis in traditional Chinese medicine

Eye diagnosis is a method for inspecting systemic diseases and syndromes by observing the eyes.With the development of intelligent diagnosis in traditional Chinese medicine(TCM);artificial intelligence(AI)can improve the accuracy and efficiency of eye diagnosis.However;the research on intelligent eye diagnosis still faces many challenges;including the lack of standardized and precisely labeled data;multi-modal information analysis;and artificial in-telligence models for syndrome differentiation.The widespread application of AI models in medicine provides new insights and opportunities for the research of eye diagnosis intelli-gence.This study elaborates on the three key technologies of AI models in the intelligent ap-plication of TCM eye diagnosis;and explores the implications for the research of eye diagno-sis intelligence.First;a database concerning eye diagnosis was established based on self-su-pervised learning so as to solve the issues related to the lack of standardized and precisely la-beled data.Next;the cross-modal understanding and generation of deep neural network models to address the problem of lacking multi-modal information analysis.Last;the build-ing of data-driven models for eye diagnosis to tackle the issue of the absence of syndrome dif-ferentiation models.In summary;research on intelligent eye diagnosis has great potential to be applied the surge of AI model applications.

An interpretability model for syndrome differentiation of HBV-ACLF in traditional Chinese medicine using small-sample imbalanced data

Objective Clinical medical record data associated with hepatitis B-related acute-on-chronic liver failure(HBV-ACLF)generally have small sample sizes and a class imbalance.However,most machine learning models are designed based on balanced data and lack interpretability.This study aimed to propose a traditional Chinese medicine(TCM)diagnostic model for HBV-ACLF based on the TCM syndrome differentiation and treatment theory,which is clinically interpretable and highly accurate.Methods We collected medical records from 261 patients diagnosed with HBV-ACLF,including three syndromes:Yang jaundice(214 cases),Yang-Yin jaundice(41 cases),and Yin jaundice(6 cases).To avoid overfitting of the machine learning model,we excluded the cases of Yin jaundice.After data standardization and cleaning,we obtained 255 relevant medical records of Yang jaundice and Yang-Yin jaundice.To address the class imbalance issue,we employed the oversampling method and five machine learning methods,including logistic regression(LR),support vector machine(SVM),decision tree(DT),random forest(RF),and extreme gradient boosting(XGBoost)to construct the syndrome diagnosis models.This study used precision,F1 score,the area under the receiver operating characteristic(ROC)curve(AUC),and accuracy as model evaluation metrics.The model with the best classification performance was selected to extract the diagnostic rule,and its clinical significance was thoroughly analyzed.Furthermore,we proposed a novel multiple-round stable rule extraction(MRSRE)method to obtain a stable rule set of features that can exhibit the model’s clinical interpretability.Results The precision of the five machine learning models built using oversampled balanced data exceeded 0.90.Among these models,the accuracy of RF classification of syndrome types was 0.92,and the mean F1 scores of the two categories of Yang jaundice and Yang-Yin jaundice were 0.93 and 0.94,respectively.Additionally,the AUC was 0.98.The extraction rules of the RF syndrome differentiation model based on the MRSRE method revealed that the common features of Yang jaundice and Yang-Yin jaundice were wiry pulse,yellowing of the urine,skin,and eyes,normal tongue body,healthy sublingual vessel,nausea,oil loathing,and poor appetite.The main features of Yang jaundice were a red tongue body and thickened sublingual vessels,whereas those of Yang-Yin jaundice were a dark tongue body,pale white tongue body,white tongue coating,lack of strength,slippery pulse,light red tongue body,slimy tongue coating,and abdominal distension.This is aligned with the classifications made by TCM experts based on TCM syndrome differentiation and treatment theory.Conclusion Our model can be utilized for differentiating HBV-ACLF syndromes,which has the potential to be applied to generate other clinically interpretable models with high accuracy on clinical data characterized by small sample sizes and a class imbalance.

Comparative study on WHO Western Pacific Region and World Federation of Chinese Medicine Societies international standard terminologies on traditional medicine: Diseases in External Medicine (Part 2)

This is a continued study about how to understand and translate the names of diseases in the external medicine of TCM included in the WPRO Standard and the WFCMS Standard according to the discussion made in the book entitled International Standardization of English Translation of Traditional Chinese Medicine： Study of Theory, Summarization of Practice and Exploration of Methodst, the explanation made in A Concise Dictionary of Traditional Chinese Medicine,

Comparative study on WHO Western Pacific Region and World Federation of Chinese Medicine Societies international standard terminologies on traditional medicine: Diseases in External Medicine (Part 1)

External medicine, also frequently described as surgery, has a history as long as that of traditional Chinese medicine （TCM）. There were important doctors in each dynasty who devoted themselves to the study and practice of external medicine. In TCM external medicine, diseases are named either according to their location （such as neck abscess and back carbuncle）, or viscera involved （such as intestinal abscess and lung abscess）, or causes （such as tetanus and chilblain, which are literally known respectively as wind damage of wound and sore caused by cold in TCM）, or shape （such as snake head boil and goose web wind）, or the color （such as erysipelas and vitiligo which are literally known respectively as red toxin and white skin wind）, etc.

Treatment of 140 cerebral palsied children with a combined method based on traditional Chinese medicine(TCM)and western medicine

Objective:To observe and evaluate a method that is effective and practical for treatment of cerebral palsied(CP)children in China.Method:The patient's age and disease type and individual specific conditions were considered in choosingtherapy methods accordingly:Chinese herbs,acupuncture,auricnlar seed pressure,point finger pressing,massage,orthopedichand manipulation,physiotherapy,occupational therapy,language therapy,etc.Meanwhile we created a new CP treatment modelthat combines hospitalized treatment with family therapy.Results:The majority of CP patients improved greatly in motor andsocial adaptation capacities after treatment.Wilcoxon paired rank sum test analysis showed that there were significant differencesbetween the data before and after treatment(P<0.01).Conclusion:This combined therapy method,based on traditional Chinesemedicine and western medicine plus family supplemental therapy,is an effective and practical treatment strategy for CP children inChina.

Analysis on medication rule of traditional Chinese medicine treating chemotherapy-induced diarrhea based on traditional Chinese medicine(TCM) inheritance computing platform system

Objective:To dig deeper into the traditional Chinese medicine treatment rules of chemotherapy-induced diarrhea with traditional Chinese medicine(TCM)inheritance computing platform system.Methods:Taking“traditional Chinese medicine”,“chemotherapy”and“diarrhea”as the theme words,comprehensive search of the database of CNKI,Wanfang and VIP from its inception to November 2020 was conduct-ed.The formulas of external treatment of traditional Chinese medicine for chemotherapy-induced diarrhea were included and the association rule,clustering and factor analysis were carried out.Results:A total of 145 papers,57 prescriptions meeting the inclusion criteria were collected,among which high-frequency drugs including Baizhu(Atractylodis macrocephalae rhizoma),Fuling(Poria),Dangshen(Codonopsisradix),Huanglian(Coptidis rhizoma),Zhigancao(Glycyrrhizae radix et rhizoma praeparata cum melle)were the most commonly used.The confidence level was set as 0.7 and the support level was set as 10,12 core compatibility groups were obtained,and 6 categories were cluster analyzed.Conclusion:The principle of external treatment of chemotherapy-induced diarrhea is mainly“restore deficiency and benefiting qi”,“benefiting water infiltration and dampness”,“clearing heat”and“inducing astringency”.Prescription combination and new prescription combination based on traditional Chinese medicine(TCM)inheritance computing platform system can be used as reference for clinicians and applied in primary hospitals.

Traditional Chinese Medicine and Standardization——Origin and development of TCM

Traditional Chinese Medicine (TCM) is the medical science based on theories and practicing experience of traditional Chinese medicine to study transferring principles of health and sickness,as well as prevention, diagnosis,treatment,rehabilitation and healthcare.TCM is marked with its long history of development,integrated theory system and abundant practicing experience.

Comparative study on WHO Western Pacific Region and World Federation of Chinese Medicine Societies international standard terminologies on traditional medicine: Diseases in External Medicine (Part 3)

rocky mass/cancer： any malignant tumor occurring on body surface that looks and feels like rock In classical Chinese medicine, the character 岩 （literally meaning rock） means the same thing as 癌 （malignant tumor）. That is why it is now usually translated as ＂cancer＂ or ＂carcinoma＂, which is adopted in the WFCMS Standard. To translate it as ＂rocky mass＂ in the WPRO Standard appears quite unique and sounds semantically equivalent to the original term.

Comparative study on WHO Western Pacific Region and World Federation of Chinese Medicine Societies international standard terminologies on traditional medicine:Diseases in External Medicine(Part 4)

The following is a continued discussion about how to understand and translate the names of diseases in external medicine included in the WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region （abbreviated as the WPRO Standard）[1] and the standard compiled by the World Federation of Chinese Medicine Societies （abbreviated as the WFCMSStandard）[2], according to the studies made in the book entitled International Standardization of English Translation of Traditional Chinese Medicine： Study of Theory, Summariza- tion of Practice and Exploration of Methods[3].

Review: The vital role of traditional Chinese medicine (TCM) in the prevention and treatment of COVID-19 and the etiology and pathogenic mechanism of COVID-19 based on TCM theory

"Yi"is defined in traditional Chinese medicine theory as the general pathological conditions of epidemics.Throughout thousands of years of history,TCM has been playing an essential role in preventing and treating epidemics in China.Showing significant efficacy against severe acute respiratory syndrome(SARS)in 2002 and 2003,a medical intervention involving TCM was applied at the beginning of the pandemic of the corona virus disease 2019(COVID-19),and has been found with good preventive and curative value in clinical practice.In this study,the etiology and pathogenic mechanism of COVID-19 was discussed on a TCM theory basis,and the clinically effective prevention and treatment methods/prescriptions were summarized.It is suggested that TCM has been playing a unique and vital role in preventing and treating COVID-19,and thus contributes greatly to public health.

The Great Significance of Establishing Strategic Status of Traditional Chinese Medicine (TCM)

Traditional Chinese Medicine(TCM), based on the philosophic idea of “correlation between man and nature” and “balance of Yin and Yang” and characterized by “integrated concept” and “syndrome identification & treatment determination”, adjusts and activates the self-recuperating ability to rectify its differentiation from normality of human body to meet the goal of preventing and treating diseases mainly by means of traditional Chinese medicinal herbs, acupuncture and moxibustion, etc. The idea of “Human should be in harmony with Nature including bacterium, virus, etc., but not to exterminate microbe in a large scale”, held and promoted by TCM gives, rise to a delicate physiological equilibrium kept between man and microbe and this is just the development trend of medical science in future. For thousands years, TCM has made indelible contribution to the reproduction and prosperity of the Chinese nation, and under the countless attacks of pestilence has never made its people’s death in millions, not such as once occurred in Europe. TCM is also characterized by its “simple, convenient, cheap and effective”method of treatment” and is especially good at preventing and treating chronic diseases, complicate multi-system diseases and new-type virus diseases. Therefore, only when the sanitation and healthcare system is established can the health of 13 billion people in China and the problem of shortage of doctor and medicine for 900 million rural population and large number of poverty-stricken urban population be solved. It is strongly suggested that five promotion projects, namely: TCM policy and statute guarantee, TCM qualified personnel cultivation, TCM scientific research, development of TCM in rural areas and TCM administrative system reform should be carried out in real earnest to make TCM develop in a sustainable way.

Constitution identification model in traditional Chinese medicine based on multiple features

Objective To construct a precise model for identifying traditional Chinese medicine(TCM)constitutions;thereby offering optimized guidance for clinical diagnosis and treatment plan-ning;and ultimately enhancing medical efficiency and treatment outcomes.Methods First;TCM full-body inspection data acquisition equipment was employed to col-lect full-body standing images of healthy people;from which the constitutions were labelled and defined in accordance with the Constitution in Chinese Medicine Questionnaire(CCMQ);and a dataset encompassing labelled constitutions was constructed.Second;heat-suppres-sion valve(HSV)color space and improved local binary patterns(LBP)algorithm were lever-aged for the extraction of features such as facial complexion and body shape.In addition;a dual-branch deep network was employed to collect deep features from the full-body standing images.Last;the random forest(RF)algorithm was utilized to learn the extracted multifea-tures;which were subsequently employed to establish a TCM constitution identification mod-el.Accuracy;precision;and F1 score were the three measures selected to assess the perfor-mance of the model.Results It was found that the accuracy;precision;and F1 score of the proposed model based on multifeatures for identifying TCM constitutions were 0.842;0.868;and 0.790;respectively.In comparison with the identification models that encompass a single feature;either a single facial complexion feature;a body shape feature;or deep features;the accuracy of the model that incorporating all the aforementioned features was elevated by 0.105;0.105;and 0.079;the precision increased by 0.164;0.164;and 0.211;and the F1 score rose by 0.071;0.071;and 0.084;respectively.Conclusion The research findings affirmed the viability of the proposed model;which incor-porated multifeatures;including the facial complexion feature;the body shape feature;and the deep feature.In addition;by employing the proposed model;the objectification and intel-ligence of identifying constitutions in TCM practices could be optimized.

Risk assessment of coronary artery occlusion based on integrated Chinese and western medicine data

Objective To develop an integrated risk model for coronary artery occlusion based on data of both traditional Chinese medicine(TCM)and western medicine data,and to evaluate the contribution of TCM-specific indicators to conventional coronary heart disease(CHD)risk prediction.Methods Data of TCM indicators(tongue,facial,and pulse diagnostics)and clinical parame-ters from patients diagnosed with CHD at the Cardiology Department of Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine,from October 3,2023 to March 15,2024,were collected.Important variables were identified using importance screen-ing and correlation analysis with CHD risk factors and laboratory markers.Six machine learn-ing models including logistic regression(LR),decision tree(DT),support vector machine(SVM),k-nearest neighbors(KNN),random forest(RF),and gradient boosting(GB),were ap-plied to evaluate the risk of coronary artery obstruction by combining clinical and TCM data of CHD.Model performance was assessed using metrics such as accuracy,precision,and re-call,with reliability validated through ten-fold cross-validation.Results A total of 288 patients were included in the study.Fifteen clinical risk factors,includ-ing body mass index(BMI),myoglobin,and alcohol consumption history,were incorporated into the diagnostic models.The KNN model showed good performance when combining clin-ical data with tongue and facial data.The SVM model performed well when clinical data was combined with pulse data.Among all the models,the KNN model with 10-fold cross-valida-tion,which integrates the three types of TCM diagnostic data(tongue,face,and pulse)with clinical data,performs the best(accuracy:0.837,precision:0.814,and recall:0.809).Conclusion Incorporating TCM diagnostic data can enhance the accuracy of coronary artery obstruction risk assessment.The KNN prediction model that integrate tongue,facial,and pulse data performs the best and can be recommended as a clinical decision support tool.

A holistic strategy for quality and safety control of traditional Chinese medicines by the “iVarious” standard system

An effective quality control system is the key to ensuring the quality, safety and efficacy of traditional Chinese medicines(TCMs). However, the current quality standard research lacks top-level design and systematic design,mostly based on specific technologies or evaluation methods. To resolve the challenges and questions of quality control of TCMs, a brand-new quality standard system, named "iVarious", was proposed. The system comprises eight elements in a modular format. Meaning of every element was specifically illustrated via corresponding research instances. Furthermore, frankincense study was taken as an example for demonstrating standards and research process, based on the "i Various" system. This system highlighted a holistic strategy for effectiveness,security, integrity and systematization of quality and safety control standards of TCMs. The establishment of"i Various" integrates multi-disciplinary technologies and progressive methods, basis elements and key points of standard construction. The system provides a novel idea and technological demonstration for regulation establishment of TCMs quality standards.

Applications of HPLC/MS in the analysis of traditional Chinese medicines

In China, traditional Chinese medicines （TCMs） have been used in clinical applications for thousands of years. The successful hyphenation of high-performance liquid chromatography （HPLC） and mass spectrometry （MS） has been applied widely in TCMs and biological samples analysis. Undoubtedly, HPLC/MS technique has facilitated the understanding of the treatment mechanism of TCMs. We reviewed more than 350 published papers within the last 5 years on HPLC/MS in the analysis of TCMs. The present review focused on the applications of HPLC/MS in the component analysis, metabolites analysis, and pharmacokinetics of TCMs etc. 50% of the literature is related to the component analysis of TCMs, which show that this field is the most popular type of research. In the metabolites analysis, HPLC coupled with electrospray ionization quadrupole time-of-flight tandem mass spectrometry has been demonstrated to be the powerful tool for the characterization of structural features and fragmentation behavior patterns. This paper presented a brief overview of the applications of HPLC/MS in the analysis of TCMs. HPLC/MS in the fingerprint analysis is reviewed elsewhere.

Study progress in therapeutic effects of traditional Chinese medicine monomer in severe acute pancreatitis

Severe acute pancreatitis (SAP) is a common acute abdomen clinical problem characterized by high mortality, mul-tiple complications, complicated pathogenesis and difficult treatment. Recent studies found traditional Chinese medicine (TCM) monomers have markedly good effect for treating SAP. Many TCM monomers can inhibit pancreatin, resist inflammation, im-prove microcirculation and immunoloregulation, etc. to block the pathological progress of SAP in multiple ways, reduce com-plications and lower mortality with rapid effects. It is significant for enhancing SAP treatment to deeply understand the current situation in TCM monomers for treating SAP and take precious references therein. This article summarizes the treating effects and mechanisms of TCM monomers for SAP in recent years.