12 results about "Drug reaction" patented technology

The invention relates to CD1a-reactive T-cell receptors (TCRs), and their use in treating or preventing an inflammatory skin or mucosal disorder or disease or one or more associated systemic disease or disorder, one or more inflammatory drug reaction which manifests systemically, a CD1a-expressing malignancy or a malignancy wherein CD1a is altered in expression or function.

A biological function estimation device includes a processor configured to predict a drug reaction in a patient based on an evaluation value obtained by evaluating a biological function of the patient from a test result before drug administration and data on a drug to be administered to the patient, and configured to correct the evaluation value according to a comparison result between an obtained prediction value and a measurement value obtained by measuring the drug reaction after the drug administration.

This invention discloses a rapid phenotypic drug susceptibility detection method for Mycobacterium tuberculosis infected samples. The method utilizes the incorporation of deuterium into biomolecules synthesized by metabolically active Mycobacterium tuberculosis in a heavy water (D2O) environment, thereby generating C-D characteristic peaks in single-cell Raman spectroscopy. The inhibition of metabolic activity by anti-tuberculosis drugs leads to a decrease in the C-D signal. By calculating the metabolic change rate between drug-treated and untreated samples, the bacterial drug response can be quantified, and susceptibility / resistance determination and MIC value can be established. This invention provides a rapid phenotypic drug susceptibility detection method for Mycobacterium tuberculosis based on single-cell Raman spectroscopy and heavy water labeling technology (Raman-DIP). This method detects the metabolic changes of individual bacteria under the action of anti-tuberculosis drugs to determine drug susceptibility and minimum inhibitory concentration (MIC), enabling a rapid detection process from sample to result.

The invention provides an intelligent intravenous drug regulation and control system and method, and the system comprises a data collection module which is used for collecting basic parameters and life parameters of a patient; the intelligent decision-making module is used for predicting the medication response of the patient and recommending the medication dosage of the patient based on the basic parameters and the life parameters of the patient; and the execution interaction module is used for automatically generating a doctor's advice based on the patient medication response prediction result and the patient medication dosage recommendation, being linked with a hospital information system and sending an operation prompt to a medical staff terminal. And the aim of improving the individual difference coping ability is fulfilled.

1. The name of the design product: colorimetric box. 2. The use of the design product: for drug reaction and result comparison. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: design 1 perspective view. 5. Design 1 is designated as the basic design.

The invention provides a model for predicting the risk of allergic reaction of a Wilson disease patient during copper expelling treatment, and belongs to the crossing field of clinical medicine and biological information technology. The risk prediction model comprises: an input module receiving patient parameter indexes composed of a sodium dimercaptopropanesulfonate injection dosage, a severe adverse drug reaction, a drug allergy history, a neutrophil count, a lymphocyte count, a ratio of neutrophil to lymphocyte, a ratio of platelets to lymphocyte, a leukocyte count, a urine copper level and a platelet count; the processing module is connected with the input module and is used for calculating the score and prediction probability of the allergic reaction during copper expelling treatment based on the parameter indexes of the patient; and the output module is connected with the processing module, and outputs the allergic reaction risk probability obtained by the risk prediction model during the copper expelling treatment of the Wilson disease patient. The risk prediction model can be conveniently used for early recognition and risk prediction of anaphylaxis of a Wilson disease patient during copper expelling treatment.

The invention discloses a turbid traditional Chinese medicine antibacterial MIC detection method based on a TTC indicator and a detection kit thereof, and belongs to the technical field of microbiological detection. The method comprises the following steps: screening a TTC optimal working concentration culture medium and an adaptive pore plate which have no bacteriostatic action on target bacteria and can make pore bottom bacteria precipitate and develop clearly; selecting an adaptive pore plate, setting a blank control, a drug-TTC reaction control and a positive control, adding a turbid traditional Chinese medicine liquid, a bacterial liquid of a to-be-detected strain and a TTC optimal working concentration culture medium, and constructing an experiment and control system; culturing at constant temperature; and based on a pore plate precipitation focusing effect, observing the color and precipitation state of an experimental pore in combination with a contrast pore result, and judging an MIC value. The method solves the problem that MIC determination is interfered by turbid traditional Chinese medicine color development, is simple and convenient to operate and accurate in result, can quickly realize accurate detection of turbid traditional Chinese medicine antibacterial MIC, and is suitable for evaluating the antibacterial activity of traditional Chinese medicine.

The present application relates to a kind of drug reaction prediction methods based on multi-source heterogeneous network, comprising: extracting the structural features of drug, constructs drug structure similarity matrix, introduces drug physical and chemical property information and constructs drug physical and chemical property similarity matrix, drug structure similarity, physical and chemical property similarity matrix and synergistic drug matrix are fused to obtain drug similarity fusion matrix, constructs three cell line similarity matrix and adopts nuclear fusion strategy and is fused to obtain cell line similarity fusion matrix;Based on drug similarity fusion matrix, cell line similarity fusion matrix and drug-cell line association matrix, construct heterogeneous network, and extract drug embedding features and cell line embedding features from it, reconstruct drug-cell line association matrix, realize prediction.The present application introduces drug physical and chemical property information and drug synergistic information, enriches the features of drug, solves the problem of highly sparse chemical descriptor and molecular fingerprint feature vector.

The present disclosure in one aspect, relates to compounds, compositions, and methods for degrading pregnane X receptor (PXR) protein. The invention further relates to the use of the disclosed compounds in decreasing adverse drug reactions such as, for example, adverse drug reactions associated with administration of an anticancer agent, an antibacterial agent, a non-steroidal anti-inflammatory agent, or an anticonvulsant agent. The invention, in one aspect, further relates to compounds, compositions, and methods for identifying PXR ligands. This abstract is intended as a scanning tool for purposes of searching in the particular art and is not intended to be limiting of the present disclosure.

The invention provides a protein mutation drug resistance prediction method and system based on multi-task deep learning, and the method comprises the steps: obtaining evidence entries from a CIViC / PharmGKB library, carrying out the preprocessing, and supplementing pathogenicity tags to build a double-tag corpus; the protein is characterized by using a mutation site neighborhood local one-bit code and an evolutionary comparison site specific scoring matrix PSSM dual path, the length is standardized, and the drug is mapped and spliced by using a PubChem881-dimensional fingerprint; constructing a Transform cascade model, firstly transfusing the pathogenicity probability, then splicing with the intermediate characterization to transfuse the drug resistance probability, and carrying out combined loss training; and dividing data set evaluation, and analyzing multiple mutations in combination with attention. The performance of the method is superior to or not lower than that of an existing tool, a high-resolution three-dimensional structure is not needed, accurate prediction can be achieved only through a small amount of input features, meanwhile, whether drug reaction is driven by mutation pathogenicity or not can be determined, differentiated medication strategies are formulated for different types of patients, and the method has good cross-center migration potential and is suitable for clinical application. The method can be widely applied to scenes such as accurate medication decision making, drug resistance early warning and drug redesign.

The application discloses an anti-inflammatory effect evaluation method based on SAMC regulation of M1 polarization of macrophages, relates to the technical field of biological medicine, and comprises the following steps: surface modification is performed on a nano-carrier complex, a molecule specifically combined with a M1 type macrophage marker is added, and a targeted modified nanoparticle is generated; the targeted modified nanoparticle is added into RAW264.7 macrophages, a flow cytometry is used to detect the binding condition of the targeted modified nanoparticle and the RAW264.7 macrophages, and targeted binding data is generated; a macrophage culture system is constructed according to the RAW264.7 macrophages, and a drug is treated through the targeted modified nanoparticle, real-time monitoring of the change of cell survival condition, inflammatory factor level and cell polarization state is performed, and drug reaction data is generated. The application reduces side effects and adverse reactions of a traditional drug administration mode.

The present invention relates to antibodies or antigen-binding fragments thereof capable of binding to CD1a. The antibodies or antigen-binding fragments thereof may be chimeric or humanized and may be used to treat one or more inflammatory skin or mucosal disorders or diseases, or one or more related systemic diseases or disorders, or one or more inflammatory drug reactions manifesting systemically, or CD1a-expressing malignancies.