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).

Screening of Effective Traditional Chinese Medicine Monomer Compounds for the Treatment of Nonorganic Sleep Disorders Based on Network Pharmacology

[Objectives] To find effective monomer compounds of traditional Chinese medicine targeting nonorganic sleep disorders.[Methods] The reverse thinking of "target-compound" was adopted to search for effective traditional Chinese medicine monomer compounds that intervene in the core targets of nonorganic sleep disorders, and molecular docking technology was used to verify the traditional Chinese medicine monomer compounds that meet the expected goals.[Results] Based on the storm related targets of nonorganic sleep disorders, five monomer compounds of traditional Chinese medicine were screened, namely paeoniflorin, chlorogenic acid, quercetin, baicalin, and ginsenoside Rg1. These monomer compounds of traditional Chinese medicine act on multiple targets such as CASP8, IKBKB, IL1B, IL6, CXCL8, etc. , thereby playing a role in calming the mind and improving sleep.[Conclusions] These monomer compounds of traditional Chinese medicine had potential pharmacological effects on nonorganic sleep disorders and high value in subsequent experiments and clinical applications.

Modern technology-based exploration of mechanism of traditional Chinese medicine in prevention and treatment of gastric cancer

This review comments on the article“To explore the mechanism of Yigong San anti-gastric cancer and immune regulation”.We are interested that the article applied network pharmacology and bioinformatics techniques to elucidate the mechanism of action of Yigong Sang,a traditional Chinese medicine(TCM),in the treatment of gastric cancer(GC).The mechanism of action of Yigong Sang in the treatment of GC has not yet been elucidated because it is composed of multiple Chinese medicines with multiple components and multiple targets.The emergence of network pharmacology and bioinformatics analysis helps explain the mechanism of action of TCM in preventing and treating GC,and provides a possibility for TCM to transform from empirical to evidence-based medicine.This is of great significance for the application of TCM in oncology,new drug development,formula optimization,and the improvement of clinical efficacy.

Use of traditional Chinese medicine bezoars and bezoar-containing preparations in hepatocarcinoma

This manuscript used network pharmacology and experimental verification to analyze the anti-hepatocarcinoma mechanism of action of bezoars in traditional Chinese medicine(TCM),discovering that it can affect the immune cells within the tumor microenvironment and related pathways to produce inhibitory effects in liver cancer.In TCM,bezoars have a unique therapeutic advantage in the prevention and treatment of tumors.They play an anti-tumorigenic role by regulating the immune microenvironment through multi-component,multi-target and multi-pathway mechanisms.With the application of nanotechnology,bezoars and their compound preparations have been developed into anti-cancer drugs with unique therapeutic advantages,providing novel treatment options for tumor patients.

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.

Research Status of Serum Pharmacology and Serum Pharmacochemistry of Traditional Chinese Medicine

Serum pharmacochemistry of traditional Chinese medicine has become a more accurate and rapidly developing reasonable way to analyze the effective material basis of traditional Chinese medicine in recent years. Through this method, we can select very complex Chinese medicine components and clarify the effective substances consistent with the main functions, and then separate and purify effective ingredients in traditional Chinese medicine, so as to explain the material basis of the drug effect and prove the rationality and principle of action of Chinese medicine compounds. It can show the multi-component and multi-target characteristic of traditional Chinese medicine, and after analyzing the migrating components of serum, we can explore the direct effective substances that act on the patient’s body, so as to accelerate and accurately complete the in-depth study of the effective substances of Chinese medicine.

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.

Application of network pharmacology in the prevention and treatment of COVID-19 by traditional Chinese medicine

Network pharmacology is an emerging technology based on systems biology and computer information technology,with the help of databases and related auxiliary software,to carry out new drug development and the screening analysis of drug active ingredients and targets.At present,the network pharmacology has been used widely in the research of prevention and treatment drugs for coronavirus disease 2019(COVID-19).This paper reviews the research methods of network pharmacology in the field of prevention and treatment of COVID-19 by traditional Chinese medicine(TCM)and the development of its specific drugs and further explores the concrete application ideas of this technology.The necessary databases and tools of necessary for screening the active components and targets to molecular docking are summarized.In addition,the practical application of network pharmacology in the study of several potential TCM and active components against COVID-19 is reviewed,mainly including the screening of active components,the discovery of target,and the elucidation of action mechanism.The diversification of research ideas of network pharmacology in the field of TCM was realized,in particular,with two specific ideas in the study of active ingredients of TCM.Finally,the difference of control effect among several TCM and Western medicines on COVID-19 and the limitation and challenge of network pharmacology in TCM,i.e.,the insufficient integrity and accuracy of the database,the uncertain complexity of components analysis,the unclear mechanism of component-target action,and some new challenges due to the characteristics of TCM,are discussed.In view of the importance of TCM in the field of control of COVID-19,the combination of TCM and network pharmacology will continue to play an important role in the development of specific drugs of COVID-19 in the future,in particular,to save time and reduce the workload of drug developers,which is also a direction of TCM development.This study provides theoretical reference and methodological basis for the prevention and treatment of COVID-19 by TCM.

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.

Prediction of the mechanism of prostate prescription Ⅰ in the treatment of chronic prostatitis based on integrative pharmacology of traditional Chinese medicine

Objective:To investigate potential mechanism of Prostate prescriptionⅠin the treatment of chronic prostatitis based on integrated pharmacology.Methods:with the help of TCMIP,the effective compounds of Prostate prescriptionⅠwere screened,and the potential target database of Prostate prescriptionⅠwas established by using the target prediction function of TCMIP.Based on the Human Phenotype Ontology database and protein interaction network(PPI)database,the disease target of CP was identified and the target interaction network was constructed;Through the GO function analysis and KEGG pathway enrichment analysis of the candidate targets,combined with Chinese and foreign literature studies to predict the potential Signaling pathway of Prostate prescriptionⅠin the treatment of CP.Results:79 effective compounds of Prostate prescriptionⅠexerted its effect on 33 targets through 11 pathways.Conclusion:Clinical efficacy of Prostate prescriptionⅠon CP may be reflected in antiinflammation and anti-tumor,cell metabolism,immune regulation,neuroregulation and so on.

Dissecting the underlying pharmaceutical mechanism of traditional Chinese medicine Wenxin Keli acting on atrial fibrillation through network pharmacology

As a well-known Chinese medicine prescription, Wenxin Keli (WXKL) has been widely used in the treatment of many arrhythmias including atrial fibrillation and has achieved significant clinical effects, but the specific mechanism of its treatment of atrial fibrillation remains unclear. This study used a network pharmacology approach to reveal the potential molecular mechanisms of WXKL in the treatment of atrial fibrillation. It involves oral bioavailability screening of ingredients, drug-likeness evaluation, compound target fishing, H-C-T network and C-T-P network construction and analysis. Through the network pharmacology-based research strategy, the complex system of WXKL was analyzed. It was found that 14 representative compounds of WXKL, 30 protein targets and 12 related signaling pathways help us systematically understand the underlying mechanism of WXKL’s anti-atrial fibrillation effects.

Research Progress of Traditional Chinese Medicine in Treating Irritable Bowel Syndrome Based on Network Pharmacology and Molecular Docking Technology

In recent years,using network pharmacology and molecular docking technology to reveal the therapeutic targets of irritable bowel syndrome(IBS)has become a research hotspot.This paper summarizes 31 studies of traditional Chinese medicine for IBS by domestic and foreign scholars,and expounds the action mechanism of single drug,drug pair and compound prescription in the treatment of IBS from the aspects of drug activity,action target,biological process and pathway analysis.It also discusses the shortcomings and prospects of network pharmacology and molecular docking technology in the field of traditional Chinese medicine research,and provides reference for expanding the research ideas of traditional Chinese medicine in treating IBS.

Research Progress in the Application of Network Pharmacology in Traditional Chinese Medicine and Compound Prescriptions

Network pharmacology is a new discipline based on the theory of systems biology,mainly for network analysis of biological systems.It selects specific signal nodes for multi-target drug molecular design.This article summarizes the application of network pharmacology in traditional Chinese medicine and compound prescriptions in recent years from the research progress of network pharmacology,the current research status of single herbs,and the research and application of compound prescriptions.

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.

Mechanism analysis of Traditional Chinese Medicine in treatment of Diabetic Nephropathy based on network pharmacology and Traditional Chinese Medicine inheritance support system

Diabetic nephropathy is one of the most serious complications of diabetes mellitus. In the early stage, edema and proteinuria are the main clinical manifestations. In the later stage, glomerulosclerosis and interstitial fibrosis will occur. And the prognosis is poor. Nowadays, traditional Chinese medicine has a remarkable curative effect in the treatment of diabetic nephropathy. There are more and more studies on the treatment of diabetic nephropathy with traditional Chinese medicine, but most of them focus on the syndromes of diabetic nephropathy, which are short of in-depth research and summary on the mechanism of Chinese herbal prescriptions. In this paper, the traditional Chinese medicine inheritance support system and network pharmacology BATMAN-TCM software were used to collect and analyze the relevant literature. It was found that the core compatibility of Shanzhuyu, Fuling and Shuyu in the treatment of diabetic nephropathy is closely related to the signal transduction pathway and target of diabetic nephropathy, and has a positive effect on the improvement of clinical symptoms such as proteinuria, glycometabolism disorder, edema, etc. This paper explores the core compatibility of Shanzhuyu, Fuling and Shuyu on diabetic nephropathy, in order to provide reference for clinical treatment.

Network pharmacology and data analysis method to explore the traditional Chinese medicine regulates ferroptosis key genes in the occurrence and prognosis of lupus nephritis

Purpose:To explore the traditional Chinese medicine(TCM)regulates ferroptosis key genes in the occurrence and development of lupus nephritis(LN)based on biological information database.Patients and methods:Ferroptosis related genes were identified based on FerrDb database and literature retrieval.Used the OMIM,Gene Cards,Drug Bank to obtain the targets of LN.Cytoscapes 3.8.2 software and STRING database were used to analyze protein-protein interaction(PPI)network.Metacape software and Weishengxin were used to analyze the gene ontology(GO)classification and Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis.UniProt Database and Traditional Chinese Systems Pharmacology Database and Analysis Platform analysis platform were used to obtain the data table of key TCM and related targets.Cytoscapes 3.8.2 software was used to analyze the PPI network.Results:A total of 401 ferroptosis-related genes,361 LN related genes and 21“Ferroptosis-LN”intersection genes were obtained.Ferroptosis in the occurrence and prognosis of LN mainly involved the inflammatory response,cell activation,positive regulation of chemokine production and it was mainly involved in necroptosis,inflammatory bowel disease,ferroptosis and other pathways.A total of 412 TCMs containing key genes of“Ferroptosis-LN”were acquired.The most key genes were contained in Mahuang,Gehua,Baiguo,Chuanniuxi,Jinyinhua.15 key genes of“TCM-LN”were obtained.5 ferroptosis-related key genes in LN regulated by TCM were obtained,which were IL1β,TLR4,IFNG,STAT3 and HMOX1.Conclusion:TCM,such as Mahuang,Gehua,Baiguo,Chuanniuxi,Jinyinhua,may affect the occurrence and development of LN through the key ferroptosis genes,such as IL1B,TLR4,IFNG,STAT3 and HMOX1.