326 results about "Drugs sensitivity" patented technology

The invention belongs to the technical field of medicines, and particularly relates to application of sesquiterpenoids and / or pharmaceutically acceptable salts thereof in preparation of medicines for treating or preventing infectious diseases caused by staphylococcus aureus. The invention relates to the field of medicines, in particular to application in preparation of medicines for treating or preventing infectious diseases caused by drug-sensitive staphylococcus aureus or drug-resistant staphylococcus aureus. The structure of the sesquiterpenoids is shown as a formula I in the specification. The sesquiterpenoids applied in the invention are derived from rattan chrysanthemum, the source is wide, and the production cost is low. The sesquiterpenoids shown in the formula I have a very good activity inhibition effect on staphylococcus aureus for the first time, and the sesquiterpenoids have a very good activity inhibition effect on staphylococcus aureus with drug sensitivity, drug medium or drug resistance.

The invention relates to the technical field of knowledge maps, in particular to a multi-task hepatitis B drug screening method and system based on knowledge map assistance, and the method comprises the following steps: based on hepatitis B virus genotype sequence data recorded along with time, patient drug use records and drug sensitivity. According to the method, virus genotype sequence data, patient drug use records, drug sensitivity and other multi-dimensional dynamic time sequence data are integrated, interaction events between entities are marked through timestamps, and virus variation tracks, drug curative effect changes and other dynamic characteristics are embedded into atlas node attributes; and the knowledge representation can reflect the time dependence in a real scene. A hyperedge connection multi-entity set is defined based on biological pathway annotation information and protein interaction data, the limitation that only a binary relation is supported in a traditional knowledge graph is expanded, a drug combination and multi-target synergistic effect mechanism is explicitly modeled, and misjudgment of the combination effect caused by simplification of the interaction relation is avoided.

The invention provides a drug screening and curative effect evaluation method and system based on a glioma organ-like model, and relates to the technical field of biological material analys.The method includes the steps that a three-dimensional fluorescence image of the glioma organ-like model is collected, signal intensity analysis and compensation processing are carried out, a growth feature mapping model is constructed, and the three-dimensional fluorescence image of the glioma organ-like model is obtained; and phenotypic characteristics for representing the glioma organoid heterogeneity are obtained. Inputting the phenotypic characteristics into a drug response evaluation network, and calculating a drug sensitivity score; the drug molecular feature library and the drug collaborative analysis model are combined, the synergistic interaction index of different drug combinations is calculated, the optimal drug combination is screened, the drug administration dosage and the drug administration time sequence are determined in combination with phenotypic features, and finally an individualized treatment scheme is generated. According to the invention, the curative effect of the drug on the glioma organs can be effectively evaluated, and the optimal drug combination and administration scheme can be screened out, so that the accuracy and effectiveness of glioma treatment are improved.

The invention discloses a spatio-temporal trajectory fusion-based closed-loop monitoring method and system for drug-resistant bacteria in a hospital. The method comprises the following steps: collecting and processing strain drug sensitive test results and patient clinical index data in a hospital information system, and screening out key features through an improved genetic algorithm; wherein the clinical index data of the patient comprises original spatio-temporal trajectory data and nursing operation records; analyzing spatio-temporal trajectory data of the patient according to the key features, combining with drug sensitivity spectrum consistency, and constructing a propagation network model by using a graph convolutional network to identify infection source nodes and corresponding topological influence; and generating an early warning signal based on the topological influence of the infection source node, and continuously optimizing prevention and control measures by dynamically adjusting model parameters and a real-time feedback mechanism. By implementing the method provided by the invention, accurate analysis and real-time prevention and control of a drug-resistant bacterium transmission link can be realized.

The invention discloses a circular RNA drug sensitivity correlation identification method based on integrated multi-instance learning. The circular RNA drug sensitivity correlation identification method comprises the following steps: collecting experimental verification circular RNA and drug sensitivity correlation data; establishing a feature representation model based on a heterogeneous network and vertexes; embedding a heterogeneous graph node into the model, and extracting deep feature representation of the node; designing a meta-path instance embedding projector, and generating a plurality of meta-path instances; a circular RNA and drug sensitivity association predictor is constructed and completed; constructing an integrated heterogeneous graph network deep learning model; and outputting the meta-path instance of the circular RNA and drug pair and the attention coefficient, and carrying out interpretable analysis. According to the method, integrated learning and a deep learning model are combined, so that the reliability of the model is improved; according to the invention, interpretable analysis is carried out by utilizing the meta-path and the attention coefficient, the potential action mechanism of the circular RNA associated with the drug sensitivity can be explained, and the guidance of medical research is facilitated.

According to the device and the reagent for extracting the pathogen, the pathogen product separated from the uncultured sample extracted by using the device and the reagent can be subjected to a drug sensitivity test after simple culture and bacteria collection treatment, so that the culture process is shortened compared with pathogen diagnosis and identification of a clinical infected sample, and a drug sensitivity result can be obtained more quickly; and a more timely diagnosis and treatment reference is provided for clinicians.

The invention discloses application of tannic acid combined triazole medicines in preparation of medicines for treating diseases caused by fungi, and belongs to the technical field of antifungal. A series of drug sensitive tests show that tannic acid lower than 3 [mu] g / ml has no influence on the activity of human vaginal epithelial cells, and after the tannic acid is combined with fluconazole, the tannic acid can significantly inhibit the growth activity of drug-resistant candida (including drug-resistant candida albicans and drug-resistant candida glabrata). In view of the natural property, wide source and low toxicity of tannic acid, the invention provides a new antifungal treatment strategy, and the tannic acid has important clinical application value for treating infection (such as vaginal candidiasis) caused by drug-resistant fungi, especially under the condition that the existing antifungal drugs are poor in effect. Therefore, the tannic acid combined triazole medicine can be used for preparing the medicine for treating diseases caused by fungi.

The invention belongs to the technical field of intelligent medical treatment, and provides a drug recommendation method and system based on feature fusion and graph construction, and the method comprises the steps: carrying out the local feature extraction and global feature extraction of a diagnosis sequence, an operation sequence and a drug sequence, fusing the local feature extraction and the global feature extraction, and carrying out the global feature extraction; obtaining a diagnostic representation, a surgical representation and a drug representation; by fusing local feature extraction and global feature extraction, the health condition of the patient can be represented more comprehensively; according to the electronic health record data set, establishing an electronic health record graph, a drug interaction graph and a drug sensitivity graph, obtaining a drug representation by using the established electronic health record graph, drug interaction graph and drug sensitivity graph and a preset graph attention network, and fusing the drug representation with the drug representation obtained by feature extraction to obtain a drug representation; weight contributions of different medical events in recommendation decisions can be displayed, doctors are helped to understand logic behind recommendation, and the model has remarkable result interpretation ability.

The invention discloses a lung squamous cell carcinoma drug discovery method and system based on disturbance response scanning analysis, and belongs to the field of biological medicines.The method comprises the steps that lung squamous cell carcinoma protein expression profile data is downloaded and preprocessed, a robust network module is constructed and multi-scale analysis and evaluation are conducted, and drug genomic data are obtained based on drug genomic data. Predicting the drug sensitivity of the patient by using machine learning, and generating a DRN through difference analysis of the drug sensitivity; predicting drug-target protein binding affinity in combination with deep learning, quantifying node sensitivity through a PRS technology, calculating a DPI disturbance score and ranking drug priorities; high-ranking drugs are screened through comprehensive sensitivity analysis and literature investigation; a drug for a lung squamous carcinoma cell line is screened out through a pre-experiment and is relocated. According to the framework developed by the invention, by integrating proteomics, pharmacogenomics and dynamic network analysis, systematic analysis is provided for relocation drug identification of lung squamous cell carcinoma, and good news is brought to treatment of lung squamous cell carcinoma.

The invention provides a glycolipid metabolism related gene-based endometrial cancer prognosis prediction model construction method, which comprises the following steps of 1, acquiring data containing gene expression and clinical information, and preprocessing the data; 2, differential expression and prognosis gene screening; 3, constructing a prognosis model; 4, analyzing model gene enrichment; 5, evaluating the immunocompetence of the two GLRG related dangerous groups; and step 6, statistical analysis. According to the technical scheme, more accurate and reliable prognosis evaluation is provided for endometrial cancer by comprehensively analyzing multi-dimensional information such as gene expression, immune characteristics, mutation characteristics and drug sensitivity.

The invention discloses a dual-channel fusion cancer drug response prediction method, and belongs to the technical field of biological information. The method aims at solving the problems that an existing prediction method is only limited to intra-modal feature extraction, and a complex nonlinear cooperative relation between a drug and cancer cells is difficult to capture. Multi-omics data, drug molecular structure information and cancer cell line drug reaction data are integrated from databases such as CCLE, GDSC and PubChem, and unified input features are formed through standardization and feature construction. Introducing a hierarchical double-attention conversion network into the first channel to carry out characterization learning on the multi-modal features of the drug and the cell line, and constructing a high-order attention neighbor interaction graph convolutional network in the second channel to capture graph structure information of cancer drug response. And carrying out adaptive weighting on output results of the two channels by using a PPO-based fusion module so as to realize a dynamic optimal decision. And finally, generating a drug sensitivity prediction result of the cancer cell line through a classification predictor.

The invention discloses a high-precision identification method for a culture medium drug sensitive paper sheet based on a mixed model, and the method comprises the steps: S1, image collection and preprocessing: carrying out the standardization processing of a collected culture medium image, including noise removal, illumination correction and contrast enhancement; s2, semantic segmentation model processing: carrying out pixel-level classification on the preprocessed image by adopting a deep learning network architecture, accurately positioning the positions and boundaries of all drug sensitive paper sheets in a culture medium, and generating a segmentation mask; and S3, classification model processing: extracting a paper sheet area based on a result of the step S2, and identifying a drug code and concentration on each paper sheet by using a CNN classification model. And S4, hybrid model fusion: intelligently fusing the data in the steps S2 and S3, and outputting a final drug sensitive paper identification result through confidence weighting and result verification. According to the method, semantic segmentation and classification models are fused, the difficulties of low recognition precision, poor environmental adaptability and the like of a traditional drug sensitive test are overcome, and high-precision automatic recognition of the drug sensitive paper sheets is realized.

The invention, which relates to the technical field of cloud data diagnosis, discloses a cloud data sharing and diagnosis platform for microbial inspection, comprising a data preprocessing module, a federal modeling module, a multi-modal fusion module, a diagnosis scoring module, a block chain evidence storage module, a trusted sharing module and a dynamic optimization module. The data preprocessing module is used for performing format unification and feature extraction on original microbiological inspection data from a plurality of medical institutions by adopting a standardized coding method, the original microbiological inspection data comprises microscopic images, mass spectrum peak maps, drug sensitivity results and clinical information, and a structured inspection feature set is output; and the federated modeling module is used for carrying out cooperative training on locally deployed initial diagnosis models of all mechanisms by adopting a federated learning method based on differential privacy protection, locally calculating gradient information by utilizing the structured test feature set, and uploading gradient parameters subjected to noise disturbance to the central server for aggregation updating.

The invention relates to a model based on multi-modal cross attention and uncertainty integral gradient and application, and relates to the technical field of bioinformatics. The model is obtained based on multi-modal cross attention and uncertainty integral gradient construction, the problems that in an existing drug sensitivity prediction method, multi-modal data fusion is difficult, the model generalization ability is weak, and interpretability is lacked can be solved, the model captures correlation between modals through a cross attention mechanism, and the prediction accuracy of the drug sensitivity is improved. According to the method, uncertainty estimation is realized by combining Monte Carlo Dropout (MC Dropout), feature importance is analyzed by using an integral gradient algorithm, and finally, unification of high-precision prediction and biological interpretability is realized.

The present invention belongs to the technical field of rapid detection of drug sensitivity for bacteria. Disclosed are an enrichment culture medium, and a preparation method therefor and the use thereof. The enrichment culture medium comprises the following raw materials in parts by mass: 15.0-20.0 parts of tryptone, 3.5-5.5 parts of peptone, 1.5-3.5 parts of glucose, 5.0-6.5 parts of yeast extract, 2.0-2.5 parts of dipotassium phosphate, 2.0-3.5 parts of disodium hydrogen phosphate, 1.0-1.5 parts of monopotassium phosphate, 2.5-7.5 parts of sodium chloride, 12.0-18.0 parts of proteose peptone, 15.0-22.0 parts of beef heart infusion powder, 8.0-12.0 parts of soya peptone, 1.0-5.0 parts of 0.1% nicotinamide adenine dinucleotide (NAD), 30-100 parts of newborn calf serum inactivated at 56°C for 30 min, 2.0-4.0 parts of mannitol, 3.0-5.0 parts of sodium pyruvate, 0.23-0.45 parts of cycloheximide, 0.8-2.0 parts of 0.05% bromothymol blue, 2.5-4.5 parts of 0.1% methylene blue, and 1000 parts of distilled water, with the pH value of 6.8-7.5. The enrichment culture medium is used to screen effective therapeutic drugs for bacterial diseases in poultry, and is convenient to use and has a single enrichment effect superior to that of respective selective enrichment broths of target bacteria. Therefore, the culture medium can realize rapid proliferation of common pathogenic bacteria in poultry.

According to the trace pathogen enrichment device and the detection method provided by the invention, pathogen products separated from uncultured samples extracted by using the device can be subjected to drug sensitivity test after simple culture and bacteria collection treatment, so that the culture process is shortened compared with pathogen diagnosis and identification of clinical infected samples, a drug sensitivity result can be obtained more quickly, and the detection efficiency is improved. And a more timely diagnosis and treatment reference is provided for clinicians.

The application discloses a microbial drug sensitivity detection method. The application comprises: loading a microbial database, establishing a corresponding relationship between secondary microbial names and primary categories; loading a drug breakpoint database based on the "antimicrobial drug sensitivity experiment execution standard"; placing a standard culture dish in an image acquisition device to acquire an image, and calibrating an image analysis system with a vernier caliper; inputting sample information to be detected, acquiring and uploading the image; an image analysis system extracts the position of a drug sensitivity paper sheet, identifies the edge of a bacterial inhibition zone and calculates the diameter; the system extracts corresponding drug breakpoint thresholds based on the microbial category, compares the measured diameter and determines the sensitivity classification (S / I / R); and finally, the result is uploaded to a LIS system. The method can realize the automation, standardization and high efficiency of drug sensitivity detection.

This invention provides a data storage method and system for tuberculosis detection, relating to the field of tuberculosis detection technology. The data storage method for tuberculosis detection includes the following steps: S1. Collecting whole-genome sequencing data of Mycobacterium tuberculosis, host serum IgG titer, and drug sensitivity test results; S2. Calculating genetic distance D based on a reverse evolution model to generate four-dimensional spatiotemporal coordinates (t, x, y); S3. Performing data partitioning and storage based on the drug target barrier value β; S4. Generating dynamic metadata using a host-pathogen dynamics model and compressing and storing it. This invention implements a dynamic storage entropy adjustment algorithm at the hardware and software collaborative level, continuously optimizing the matching efficiency of data compression and physical storage. This results in an intelligent data hub that can perceive the evolutionary pulse of pathogens and autonomously optimize resources, providing support for clinical tuberculosis prevention and control decisions with temporal depth, spatial correlation, and risk evolution.

The invention belongs to the technical field of strain identification and drug sensitivity detection, and discloses a strain identification and drug sensitivity detection kit and a preparation method and application thereof, the kit comprises a drug sensitivity disc, a pre-enrichment chromogenic culture medium, a chromogenic culture medium, sterile water and a diluent; the drug sensitive disc body comprises an enterobacteriaceae area, an enterococcus area, a staphylococcus area, a pseudomonas aeruginosa area and an acinetobacter baumannii area; the enterobacteriaceae area is provided with enterobacteriaceae identification culture medium micropores and drug micropores, the enterococcus area is provided with enterococcus identification culture medium micropores and drug micropores, the staphylococcus area is provided with staphylococcus identification culture medium micropores and drug micropores, and the pseudomonas aeruginosa area is provided with pseudomonas aeruginosa identification culture medium micropores and drug micropores. An acinetobacter baumannii identification culture medium micropore and a medicine micropore are matched in the acinetobacter baumannii area; the problems that an existing drug sensitivity test mode is complex in operation, high in cost and low in accuracy of identification and detection results are solved.

The application discloses a kind of full-automatic drug sensitivity equipment, it is related to the field of drug sensitivity equipment, including shell, full-automatic drug sensitivity equipment further includes incubation device, sample adding device and reading device, incubation device, sample adding device, reading device are all arranged in shell, wherein, reading device is arranged at the first side of incubation device, sample adding device is arranged at the second side of incubation device, first side is adjacent with second side;Incubation device is used to place drug sensitivity plate, and incubation device can rotate along its rotation axis, and drug sensitivity plate is provided with bar code information;Reading device is used to read the bar code information of drug sensitivity plate, and is used to reciprocate along the height direction and first direction of incubation device, first direction intersects with the height direction of incubation device;Sample adding device is used to reciprocate along second direction, second direction intersects with first direction, and second direction intersects with the height direction of incubation device.The application has the advantages of reducing floor space, reducing operation difficulty.

The present application relates to the technical field of knowledge graph, in particular to a multi-task hepatitis B drug screening method and system based on knowledge graph assistance, comprising the following steps: based on hepatitis B virus genotype sequence data recorded over time, patient drug use records and drug sensitivity. In the present application, multi-dimensional dynamic time series data such as virus genotype sequence data, patient drug use records and drug sensitivity are integrated, the interaction events between entities are marked by time stamp, the dynamic characteristics such as virus variation track and drug efficacy change are embedded in the graph node attributes, so that the knowledge representation can reflect the time dependence in the real scene. Based on biological pathway annotation information and protein interaction data, the hyperedge connection multi-entity set is defined, the limitation of traditional knowledge graph which only supports binary relationship is expanded, the drug combination and multi-target synergistic mechanism are explicitly modeled, and the misjudgment of combination effect caused by the simplification of interaction relationship is avoided.

The invention belongs to the cross technical field of veterinary medicine and biomedicine, and relates to a construction and evaluation method of a dog spontaneous breast cancer organoid model, which specifically comprises the following steps: (1) obtaining dog spontaneous breast cancer tissues through operation or biopsy, separating tumor tissues under sterile conditions, and carrying out fine enzymolysis digestion treatment to obtain dog spontaneous breast cancer tissues; obtaining a single-cell suspension; and (2) inoculating the single-cell suspension into a three-dimensional culture system, carrying out three-dimensional culture by adopting a culture medium containing EGF, FGF and B27 in combination with a growth factor, promoting the growth and amplification of the breast cancer organs, and carrying out timely passage according to the growth condition so as to maintain the activity of the model. The model constructed by the invention completely retains genetic heterogeneity and pathological microenvironment of primary tumors, does not need gene editing, is simple and convenient to operate and low in cost, is particularly suitable for individual drug sensitivity detection of pet dogs, and provides an efficient and high-simulation experimental platform for dog breast cancer mechanism research and clinical precise medication.

The invention belongs to the technical field of gene engineering, and particularly relates to application of an SSRP1 and / or SUPT16H gene inhibitor in treatment of hepatocellular carcinoma. The invention provides an application of an inhibitor of SSRP1 and / or SUPT16H genes in preparation of a pharmaceutical composition for treating cancers. According to the invention, the high expression of SSRP1 and SUPT16H is obviously related to poor prognosis through pan-cancer analysis of SSRP1 and SUPT16H. In liver cancer, the FACT is preferentially enriched in liver cells, and the expression of the FACT is increased along with the increase of quasi time, which indicates that the FACT participates in tumor evolution and transcriptome reprogramming processes. According to the invention, FK866 and NPK76-II-72-1 are screened as potential inhibitors through drug sensitivity analysis, and FK866 and NPK76-II-72-1 are screened as the potential inhibitors. Therefore, an inhibitor of the SSRP1 and / or SUPT16H gene can be used for prognosis evaluation of the hepatocellular carcinoma patient, and can be used as a treatment target of the hepatocellular carcinoma patient.

The application relates to a clinical microbiological examination drug sensitivity test report automatic generation device, and belongs to the technical field of medical instruments. A fixing assembly is arranged in a box body to fix a culture dish at the center of the bottom of a cavity, so that a cavity top measuring assembly can be used to collect a drug sensitivity type label on the culture dish and measure the diameter of a bacteriostatic circle in the culture dish, the artificial measurement efficiency is improved, and the occurrence of false reports is avoided, the accuracy of drug sensitivity results is improved, and a disinfection and sterilization assembly is arranged in the box body, so that sample cross contamination and laboratory pollution are effectively avoided.

The invention provides a method for treating AR negative TNBC through combination of quercetin and enzalutamide, the quercetin up-regulates the AR expression level by inhibiting a high-expression solute carrier SLC7A5, so that tumor cells which are not sensitive to enzalutamide originally obtain drug sensitivity again; the combined use of an AR antagonist enzalutamide (1-80 [mu] M) can cooperatively block an AR signal channel and significantly inhibit cell proliferation (the inhibition rate of drug combination is 70%, Plt, 0.01 higher than that of a single drug). In-vitro experiments prove that the scheme has a synergistic effect (the effect is optimal when the mass ratio is 1: 1-5: 1) in MDA-MB-231 cells, and an animal model shows that the tumor volume inhibition rate reaches 70% or above. Safety evaluation shows that the drug combination does not cause abnormity of serum biochemical indexes (ALT / AST / BUN / CREA) or damage of main organs and tissues. The invention further provides a preparation method of an oral preparation (tablets / capsules / nanoparticles) containing quercetin (50-500 mg / day) and enzalutamide (40-160 mg / day), and a new strategy is provided for reversing AR-TNBC drug resistance.

The invention provides a cancer subtype classification method, system, equipment and program product based on ferroptosis related miRNA, and belongs to the field of intelligent medical treatment. The breast cancer is divided into four subtypes on the basis of ferroptosis related miRNA, the breast cancer FAP + subtype is identified on the basis of ferroptosis activity, the molecular characteristics of the FAP + subtype of an individual breast cancer patient are measured by establishing FAPscore, and the higher the FAPscore is, the more remarkable the FAP + subtype characteristics of the breast cancer patient are. The invention also finds that FAPscore can be used for predicting response, prognosis and drug sensitivity of individual cancer patients to immunotherapy response, and the discovery has wide cross-cancer species applicability and is not limited to breast cancer. The invention provides a new insight for a more effective and individualized treatment strategy of cancer.

The application discloses a quantum weak measurement real-time detection method and system for studying the drug efficiency of acrolein. The application uses the quantum weak measurement method to realize real-time, label-free and quantitative monitoring of the interaction process between acrolein and organoids, obtains drug efficiency evaluation parameters such as a steady-state response amplitude, an initial response rate, a steady-state time and / or an estimated absorption / binding amount, and can realize in-vitro drug sensitivity stratification and tolerance-related phenotype evaluation in combination with an organoid activity readout. When the sample shows reduced absorption / binding amount and / or reduced kinetic rate, it can be indicated that there is an 'absorption deficiency type tolerance-related phenotype', which is used for further mechanism research and drug strategy optimization. The technology has the advantages of good real-time performance, few sample processing steps, clear application scene and the like.

The invention discloses an application of an ARRB1 inhibitor in preparation of a tumor drug resistance reversal agent or a tumor drug sensitizer. It is found that by reducing ARRB1 expression, the sensitivity of human breast cancer cells to etoposide can be improved, the drug resistance of breast cancer etoposide can be reversed, and an ARRB1 inhibitor can be combined with an anti-tumor drug etoposide for use to improve the treatment effect. The invention provides a new direction for research and development of drugs for overcoming breast cancer treatment drug resistance, and has important clinical application value and development value.

The invention discloses an application of a compound targeting GPR183 in preparation of a medicine for treating acute myelogenous leukemia, the compound is N-{6-[4-(2, 4-dichlorobenzoyl) piperidin-1-yl] pyridin-3-yl}-N '-[4-(trifluorometyl) phenol] urea, a computer virtual screening method is adopted to screen the compound effective to AML, a medicine sensitive experiment shows that the compound has a killing effect on AML, and the compound can be used for preparing a medicine for treating acute myelogenous leukemia. Molecular docking analysis, RT-qPCR and protein imprinting prove that the compound can be directly combined with GPR183, expression of the GPR183 in AML cells is reduced, and proliferation of the AML cells is inhibited, so that the compound serving as the GPR183 targeting compound can be applied to preparation of drugs for treating acute myelogenous leukemia.

The present invention relates to the field of precision medicine technology, specifically a system, method, and storage medium for interpreting precise tumor medication, including: a data acquisition module for collecting genetic data, clinical data, and drug response data of tumor patients from multiple data sources; a data standardization processing module for formatting and standardizing the data to ensure a consistent format and enable effective processing and analysis in subsequent modules; a genetic data analysis module for performing variation analysis based on the patient's genetic data, identifying gene mutation sites, and generating drug sensitivity analysis results; and a drug screening module for screening drugs that match the patient's gene mutation sites from a drug database based on the genetic data analysis results, and providing drug dosage recommendations. By adopting a technical solution that combines quantum optimization technology with genetic data analysis, the technical effect of significantly improving the accuracy of drug screening and dosage recommendations is achieved.