595 results about "Drug candidate" patented technology

The invention relates to the technical field of electronic prescriptions, in particular to a dynamic electronic prescription generation method and system based on artificial intelligence. The method comprises the following steps: collecting the latest physiological state parameter flow of a patient, carrying out real-time health state evaluation, and generating a personalized patient state map; historical medical records of a patient are extracted, time sequence pathological evolution tracking is carried out, and a pathological evolution trajectory is generated; performing multi-parameter time sequence difference comparison calculation and drug curative effect quantitative evaluation based on the personalized patient state map and the pathological evolution trajectory to obtain a curative effect evaluation report; performing allergic drug identification on the patient based on the historical medical record of the patient, and performing secondary drug screening to obtain a drug candidate set; and performing intelligent matching calculation on the drug candidate set according to the curative effect evaluation report, and performing combinatorial optimization analysis to generate a final effective electronic prescription. The electronic prescription is automatically updated and adjusted based on the state change of the patient, the risk of allergic prescriptions is reduced, and the safety of the prescriptions is improved.

The invention discloses a tumor personalized drug recommendation method and system based on fusion of multiple clinical guidelines, and belongs to the technical field of bioinformatics and precision medicine. The method comprises the following steps: acquiring gene variation data and clinical feature information of a patient; generating a preliminary drug candidate list based on drug recommendation rules of a plurality of clinical guidelines; calculating the weight of each guide by adopting a dynamic weight distribution algorithm; obtaining drug-gene-disease associated information through multi-hop reasoning of the knowledge graph; calculating a drug evidence score by adopting a multi-dimensional scoring algorithm; carrying out personalized score adjustment in combination with individual features of the patient; and outputting a personalized drug recommendation result. According to the method, through multi-guide dynamic fusion, multi-dimensional evidence scoring, knowledge graph reasoning and personalized adjustment, the problems of incomplete guide coverage, lack of personalization, low response speed and the like in the prior art are solved, the method has the advantages of high accuracy, high clinical applicability, quick response and the like, and the clinical real-time decision-making requirement can be met.

A method is disclosed for using an artificial intelligence engine to generate candidate drug compounds, wherein the method comprises: generating candidate drug compounds comprising sequences via a creator module of the artificial intelligence engine. The method includes generating, via a descriptor module, a respective description for each of the candidate drug compounds at nodes in a knowledge graph, wherein the knowledge graph comprises a multi-dimensional representation of the candidate drug compounds and the respective description comprises drug compound structural information, drug compound activity information, and drug compound semantic information. The method includes determining a shape of the multi-dimensional representation of the candidate drug compounds; determining, based on the shape, a slice configured to be obtained from the representation; determining, using a decoder, which dimensions are included in the slice; and based on the dimensions, determining an effectiveness of a biomedical feature of the slice.

The invention relates to the technical field of drug research and development, in particular to a target AKT1 drug molecule discovery and delivery integrated system and method based on deep learning. Aiming at the problems of molecular design, optimization and delivery link separation and low research and development efficiency of drugs in the prior art, the system constructs a multi-module collaborative framework, and comprises a target analysis module for analyzing a target structure and formulating a generation strategy; the molecule generation and optimization module is used for generating and optimizing candidate molecules in combination with the generation model and reinforcement learning; the delivery scheme design module is used for matching a delivery carrier based on molecular physicochemical properties; and a verification module that predicts and evaluates the molecule-deliverer combination using molecular docking and ADMET. An evaluation result of the verification module is fed back to the molecule generation and optimization module to form a closed-loop optimization mechanism, so that an automatic process from target analysis to output of candidate drug molecules and matched delivery schemes thereof is realized. Compared with the prior art, the efficiency and success rate of early drug discovery can be improved.

The invention discloses an application of cryptotanshinone in preparation of an anti-mycobacterium tuberculosis drug, and relates to the technical field of bioengineering. The molecular formula of the valerianin disclosed by the invention is C19H20O3. The mycobacterium tuberculosis is a mycobacterium tuberculosis H37Rv strain. Cryptotanshinone is disclosed as a natural-source compound for the first time, has the dual advantages of high efficiency and low toxicity, has an obvious effect of resisting mycobacterium tuberculosis, provides a brand new candidate drug scheme with development potential for solving the difficulty of tuberculosis treatment, and has great scientific value and application prospect.

The invention relates to the field of biomedical application of inorganic materials, in particular to application of lanthanum carbonate in preparation of drugs for resisting liver cirrhosis and inhibiting liver inflammations, the drugs comprise lanthanum carbonate and pharmaceutically acceptable auxiliary materials, the drugs are ground and then mixed with food to prepare a drug mixture, and the drug mixture is prepared into the drug for resisting liver cirrhosis and inhibiting liver inflammations. The mass ratio of the lanthanum carbonate in the medicine mixture is 1-10%, and the mechanism of the lanthanum carbonate for treating the liver cirrhosis is as follows: interference or blocking of activation and proliferation of hepatic stellate cells, inhibition of extracellular matrix generation and promotion of extracellular matrix degradation. According to the invention, a rat liver cirrhosis model is constructed through chemical induction, and the effects of reversing liver cirrhosis and inhibiting liver inflammation are found when a rat is treated by taking lanthanum carbonate orally, so that a new candidate drug is provided for clinical treatment of liver cirrhosis.

The invention relates to the technical field of image analysis, in particular to a targeted drug curative effect prediction method based on image recognition, which comprises the following steps: acquiring tissue images and nuclear morphological parameters by a microscope, establishing a database in combination with transcripts, extracting an injury area, recognizing image features through a convolutional neural network, and constructing a prediction model; and inputting candidate drug molecular structures for molecular docking, calculating a repair progress by combining animal verification to establish a curative effect model, predicting drug scores and response time based on the curative effect model to generate a ranking list, screening high-score drug cells, verifying monitored survival, comparing, predicting and outputting a result. The method comprises the following steps: extracting a cell nucleus form, revealing a relation between damage and molecular abnormality in combination with a transcriptome, identifying a target spot corresponding to an abnormal mode and pathological change through deep learning, performing affinity prediction and animal verification on a drug structure, quantifying the repair progress by adopting image difference, and evaluating the curative effect with two dimensions of structure and function. And curative effect scores and response prediction are output to realize system sequencing, so that drug screening is more accurate and practical.

The invention belongs to the field of new application of medicines, and particularly relates to application of SIRT4-IN-1 in preparation of medicines for treating autoimmune diseases. It is found for the first time that SIRT4-IN-1 reduces the activation degree of immune response induced by HSV-1 virus infection by up-regulating acetylation modification of cGAS, inhibits abnormal activation of immune response in Trex1 deficient mouse cells and peripheral blood mononuclear cells of systemic lupus erythematosus patients, and improves abnormal activation of autoimmune response. The invention provides a new candidate drug for clinical treatment of systemic lupus erythematosus.

The invention provides a diversity maintenance and deduplication screening method and system for drug candidate molecules of a drug-loaded corneal contact lens, and relates to the technical field of artificial intelligence and candidate molecule generation and screening. The method comprises the steps that after density perception screening, evolutionary memory comparison, gradient sensitivity evaluation and non-dominated sorting screening are sequentially carried out on a pre-obtained original candidate molecular solution set, candidate molecular solutions are reserved as an optimized candidate subset of a current iteration period and used for participating in subsequent fitness reevaluation and updating of next-generation generator parameters; and repeating the above process until a preset number of loop iterations is reached, and then stopping. According to the method, a quadruple cooperation mechanism of density perception, evolutionary memory, gradient sensitivity and non-dominated sorting is constructed, so that adaptive screening and diversity maintenance of a candidate molecular solution set in an iteration process are realized, and the problems of insufficient exploration and local optimum caused by candidate convergence in the prior art are effectively solved.

A device may include a data acquisition layer comprising a patient information collector and a drug information collector, each operable to ingest patient-specific clinical data and drug-specific data, respectively. A device may include an analysis engine comprising a multi-criteria ranking engine configured to compute composite suitability score for candidate medications by weighting one or more of medication efficacy, medication safety, medication resistance, medication cost, or patient-specific coverage factors. A device may include a presentation layer comprising a summary dashboard configured to display a ranked medication recommendation set produced by the analysis engine.

The invention belongs to the technical field of biological medicines, and particularly discloses an alkynyl pyrimidine derivative as well as a preparation method and application thereof. The structure of the alkynyl pyrimidine derivative is shown as a formula I. The novel alkynyl pyrimidine derivative capable of efficiently inhibiting the LSD1 activity is provided, the preparation process is simple and easy to implement, the good effect of resisting colorectal cancer cell proliferation is shown on the animal level, and safe and effective candidate drug molecules are provided for targeted therapy of colorectal cancer.

The invention discloses an application of an RUNX2 inhibitor in preparation of a medicine for treating vascular calcification related diseases, and the RUNX2 inhibitor comprises an ester compound which is selected from at least one of Corilagin, 1, 2, 3, 6-tetragalloylglucose, NADP (Nicotinamide Adenine Dinucleotide Phosphate), Stafib-2 and uridine triphosphate sodium salt. The ester compound provided by the invention is used as a drug for inhibiting vascular calcification and progression of the RUNX2 inhibitor, and provides a new thought, a target spot and a small molecule drug for treatment of vascular calcification. The five small molecule compounds have good drug safety and a strong vascular calcification inhibition effect, and can be used as candidate drugs for inhibiting vascular calcification.

The invention relates to a molecular property prediction method and system based on multi-task pre-training and multi-modal fusion. The method comprises the following steps: collecting a data set and performing molecular conversion; performing multi-task pre-training, which comprises the following steps: generating a heterogeneous enhanced view; constructing a pseudo label; performing comparative learning according to the structure enhanced view and the heterogeneous enhanced view, and constructing a maximum similar task; capturing semantic differences among molecules according to the pseudo labels; carrying out multi-modal fusion, namely introducing functional group structure information, and extracting molecular sequence characteristics based on Transform and Mamba2 to obtain fused molecular multi-modal representation; and analyzing and predicting the classification or regression task. A heterogeneous enhanced view is established in a multi-task pre-training stage, multi-task self-supervision is performed in combination with multi-granularity features of molecular fingerprints, and functional group structure information is introduced in a multi-modal fusion stage, so that deep cross-modal interaction is realized, downstream prediction performance is improved, and candidate drug screening and molecular property evaluation processes are accelerated.

The invention relates to the technical field of anti-enterovirus medicines, in particular to application of Enractevir in preparation of an anti-enterovirus medicine. According to the invention, efficient screening of candidate drugs is realized through a multi-channel virus reporting system based on a TAT trans-activation effect, and a small molecule compound drug Enractevir with a specific antiviral effect on enterovirus group A 71 and enterovirus group D 68 is obtained. Enractevir improves the interferon secretion level of host cells by inhibiting the activity of enterovirus 2A / 3C protease, thereby inhibiting virus replication and proliferation. Enractevir plays a role through double-target 2A / 3C protease, and the risk of virus drug resistance can be reduced. According to the technical scheme, the technical problem that in the prior art, specific drugs for the two kinds of enteroviruses are lacked can be solved, a standardized treatment scheme is provided for prevention and control of enterovirus related diseases in the global range, and the medicine has remarkable public health significance and wide application and popularization value.

The invention discloses a preparation method of a cochlear organ chip integrated with a blood labyrinth barrier, and belongs to the field of biomedical engineering. The preparation method of the simulated blood labyrinth barrier comprises the following steps: constructing an endothelial cell culture cavity and a pericyte culture cavity, and separating the endothelial cell culture cavity and the pericyte culture cavity through a simulated basement membrane; and respectively inoculating percutaneous cells and endothelial cells into a percutaneous cell culture cavity and an endothelial cell culture cavity, and culturing to obtain the simulated blood lost barrier. The chip can effectively simulate the structure and the function of the BLB, and the barrier integrity of the BLB is evaluated through TEER (trans-epithelial electrical resistance) measurement and an apparent permeability coefficient. The invention also relates to application of the chip in NIHL drug screening, in particular to drug evaluation for oxidative stress induced inner ear organ injury. Through the platform, the protection effect of the candidate drugs on the TBHP-induced oxidative stress injury of the inner ear organs can be evaluated, and a new tool and thought are provided for developing novel NIHL treatment drugs.

The invention belongs to the technical field of biological medicines, and particularly discloses a quinazoline derivative as well as a preparation method and application thereof. The structure of the quinazoline derivative is shown as a formula I. The invention provides a novel quinazoline derivative capable of efficiently inhibiting LSD1 activity, the preparation process is simple and easy to implement, a good effect of resisting colorectal cancer cell proliferation is shown on the animal level, and safe and effective candidate drug molecules are provided for targeted therapy of colorectal cancer.

The invention belongs to the technical field of biological medicines, and particularly discloses a pyrimidine derivative as well as a preparation method and application thereof. The structure of the pyrimidine derivative is as shown in formula I in the specification. The novel pyrimidine derivative capable of efficiently inhibiting the LSD1 activity is provided, the preparation process is simple and easy to implement, the good effect of resisting colorectal cancer cell proliferation is shown on the animal level, and safe and effective candidate drug molecules are provided for targeted therapy of colorectal cancer.

The invention relates to the technical field of medical artificial intelligence, and discloses a drug recommendation system and method based on multi-agent cooperation. The system comprises the steps that a retrieval agent conducts structured processing and retrieval enhancement generation on extracted multi-source heterogeneous data, and a first drug candidate set related to a target disease is obtained; the pharmacological agent performs hierarchical quantitative scoring and reflection-driven rearrangement on the first drug candidate set to obtain a second drug candidate set; the clinical intelligent agent performs clinical quantitative scoring and diagnosis and treatment adaptive weight ranking on the first drug candidate set to obtain a third drug candidate set; and the coordination agent carries out dynamic weighted fusion on the first drug candidate set, the second drug candidate set and the third drug candidate set to obtain a drug comprehensive evaluation score matrix, and carries out conflict resolution and fine arrangement output on the drug comprehensive score matrix to obtain a drug recommendation result related to the target disease. The accuracy, interpretability and reliability of drug recommendation are remarkably improved.

The invention discloses application of a compound with a benzo-aza structure in preparation of a medicine for inhibiting osteoclast formation, the structure of the compound is shown as a formula (1), and R substituent is one of H, OCH3, Br, F and i-Pr. Cell experiments prove that the compound with the benzo-aza structure has a remarkable inhibiting effect on RANKL-induced osteoclast differentiation and marker gene expression, can be used as a candidate medicine which is novel in structure and is used for inhibiting osteoclast formation, and is used for targeting osteoclast to treat osteoporosis related diseases.

The invention discloses a novel immunologic adjuvant, a composition containing the immunologic adjuvant and a pharmaceutical composition. The immunologic adjuvant is picrasidine S. The immunologic adjuvant composition comprises picrasidine S and optionally one or more other types of immunologic adjuvants, such as an aluminum adjuvant. The pharmaceutical composition comprises an antigen and the immunologic adjuvant composition. Experiments prove that the picrasidine S can effectively stimulate dendritic cells to generate cell factors IFN-beta and IL-6, and has PS dose dependence; picrasidine S plays an important role in enhancing specific humoral immune response of different types of antigens, and has a stronger effect than an aluminum adjuvant; the picrasidine S immunity can enhance the anti-tumor immune response in different tumor models. According to the invention, a new candidate drug is provided for research and development of a new generation of vaccine adjuvants, and meanwhile, the medical application of the picrasidine S is also widened.

The invention discloses a pseudomonas aeruginosa InA protein and application thereof, and relates to the technical field of biological detection, the InA protein is InAS2, InAAP41 or InAS8, the amino acid sequences of the InA protein are respectively shown as SEQ ID NO.1-3, and the nucleotide sequences for coding the InAS2, the InAAP41 and the InAS8 are shown as SEQ ID NO.4-6. Compared with the prior art, the InA protein can improve the solubility of target protein, in addition, the InA protein and pseudomonas aeruginosa immune protein also have ultrahigh affinity, a biosensing chip with regeneration reversibility is developed based on the InA protein, the chip can capture fusion protein with the InA protein, and the biosensing chip has the advantages that the biosensing chip can be used as a biosensing chip with regeneration reversibility, so that the biosensing chip can be applied to biosensing of pseudomonas aeruginosa. The chip can be used for detecting the affinity between the fusion protein with the InA tag and a candidate drug, drug screening is realized, and meanwhile, the protein-drug affinity kinetics detected by the chip can also be used for pharmacological research of drugs.

The invention discloses a drug activity prediction method and system based on multi-modal medical big data, and relates to the technical field of artificial intelligence. The method comprises the steps of obtaining multi-modal medical big data, and performing multi-modal coverage collection based on the multi-modal medical big data to obtain a multi-modal data set; carrying out biological feature recognition based on the multi-modal data set and carrying out clustering analysis to determine a plurality of biological feature classes; performing drug activity influence analysis according to the biological characteristic classes, and constructing a characteristic-activity mapping list to screen target candidate drugs; and extracting biological characteristic data prediction activity based on the target candidate drugs, and generating drug activity report feedback optimization data. The technical problems of inaccurate prediction result and poor generalization ability caused by dependence on single-modal data and lack of correlation analysis on complex biological characteristics of a traditional drug activity prediction method are solved, and high-precision prediction of drug activity is realized by utilizing multi-modal fusion and biological characteristic clustering analysis, so that the method is suitable for large-scale popularization and application. And the medicine screening efficiency and the intelligent level are improved.

The invention relates to the field of biomedical application of inorganic materials, in particular to application of lanthanum carbonate in preparation of a medicine for treating hepatic encephalopathy. According to the application of lanthanum carbonate in preparation of the medicine for treating hepatic encephalopathy, the medicine comprises lanthanum carbonate and pharmaceutically acceptable auxiliary materials, the lanthanum carbonate comprises any one or more of lanthanum carbonate hydrate and basic lanthanum carbonate, the medicine is ground and then mixed with food to prepare a medicine mixture, and the medicine mixture is prepared into the medicine for treating hepatic encephalopathy. The mass ratio of the lanthanum carbonate in the medicine mixture is 1-10%. According to the application, the blood ammonia is reduced based on the glutaminase, the hepatic encephalopathy is reversed by reducing the blood ammonia and systemic inflammation, and the liver function is recovered by regulating the inflammation, so that the hepatic encephalopathy is favorably cured, a good treatment effect is shown, and a new candidate medicine is provided for clinically treating the hepatic encephalopathy.

The embodiment of the invention provides a drug optimization method and system based on the overall effect of a protein network. The method comprises the following steps: constructing a protein interaction network related to a target disease, and dividing each protein target into a risk protein set and a protection protein set; respectively calculating first binding affinity data of the candidate drugs and each protein target in the risk protein set, and generating a first network comprehensive score based on the first binding affinity data; respectively calculating second binding affinity data of the candidate drugs and each protein target in the protection protein set, and generating a second network comprehensive score based on the second binding affinity data; calculating network confrontation scores of the candidate drugs according to the first network comprehensive score and the second network comprehensive score; and determining whether the candidate drug is a preferred drug based on the network adversarial score. The method can overcome the defect that a single-target drug is insufficient in curative effect due to a network compensation effect, so that safer and more effective candidate drugs are screened out.

The application discloses a candidate drug ranking method and system based on topological coding supervision reconstruction, and belongs to the field of bioinformatics. The method comprises the following steps: step S1, obtaining drug design data; step S2, constructing a drug-biological entity association matrix; step S3, calculating a drug side topological matrix for describing the connection relationship between drugs and a biological entity side topological matrix for describing the connection relationship between biological entities according to the association matrix; step S4, constructing a finite-order topological filter and a spectral stable topological filter to form a bidirectional topological evidence field; step S5, obtaining a reconstruction supervision matrix through a supervised reconstruction objective function; and step S6, obtaining candidate drug ranking based on the reconstruction supervision matrix. The application can improve the high-order mechanism recognition ability, robustness and interpretability in drug-target prediction, drug repositioning, candidate molecule screening and molecular generation result ranking.

The invention discloses application of pedunculoside in preparation of a medicine for treating psoriasis, and relates to the technical field of medicines. The invention provides a natural candidate drug which is clear in structure and has both effectiveness and safety for clinical treatment of psoriasis.

The invention relates to a radionuclide labeled trimer probe 68Ga-TRAP-(FAPI) 3 targeting FAP and a preparation method thereof, Trap is used as a trivalent chelating platform, and three FAPI targeting units are covalently connected by clicking a chemical linking arm to form a trimer structure; the invention further relates to application of the 68Ga-TRAP-(FAPI) 3 probe in preparation of imaging agents or therapeutic drugs for diagnosing FAP positive diseases, experiments prove that the trimer probe is good in affinity and high in stability, and in cell experiments and animal experiments, the uptake rate of FAP positive cells is kept at a high level within 240 minutes; preclinical and preliminary clinical applications show that the tumor detection rate of the < 68 > Ga-TRAP-FAPI 3 in various cancer models is superior to that of < 18 > F-FDG, and compared with < 68 > Ga-FAPI-04, the < 68 > Ga-TRAP-FAPI 3 is clearer to display focuses (particularly tiny metastases), higher in uptake intensity and particularly outstanding in delayed imaging, and the < 68 > Ga-TRAP-FAPI 3 can be used for preparing a medicine for treating cancer. And a novel drug candidate with better performance is provided for precise diagnosis and staging of tumors and subsequent radionuclide targeted therapy.

The invention discloses application of eugenin in preparation of a medicine for treating cerebral arterial thrombosis, and belongs to the technical field of medicines. An in-vivo middle cerebral artery occlusion model is adopted, after reperfusion is conducted for 24 h, the cerebral infarction volume and movement coordination function defect of a mouse are detected to evaluate the treatment effect of eugenin, and activation of microglial cells and survival of neuronal cells are observed through immunofluorescence to clarify the action way of eugenin. Pharmacological activity shows that eugenin can obviously reduce the cerebral infarction volume of a model mouse, improve pathological damage of cells and promote recovery of a motion coordination function, and the action way of eugenin is to promote survival of neuronal cells and inhibit activation of microglial cells. Research results indicate that eugenin has the effect of resisting cerebral arterial thrombosis and can be used as a candidate medicine for developing the cerebral arterial thrombosis resisting medicine.

The application discloses an active polypeptide and application thereof in treating diabetic peripheral neuropathy, and belongs to the technical field of biological polypeptide drugs. An amino acid sequence of the active polypeptide is QVWPDGFVGLAKLWI, which is obtained by step-by-step enzymatic extraction and purification from Morus alba L. which is a homology of medicine and food. The polypeptide can significantly inhibit oxidative stress, inflammatory infiltration and cell apoptosis of Schwann cells induced by a high-sugar environment, and repair the function of damaged nerve cells. Meanwhile, the polypeptide can effectively improve abnormal sciatic nerve conduction function of a diabetic model mouse. The active polypeptide can be used for preparing a drug for treating diabetic peripheral neuropathy, and provides a new candidate drug and research and development direction for the targeted treatment of diabetic peripheral neuropathy.

The invention discloses application of 4-isopropyltoluene to improvement of depression-like behaviors of mice. An experiment adopts a chronic constraint stress method to construct a depression model, through behavioral detection such as a sucrose preference test, a tail suspension test and a novel inhibition ingestion test, and in combination with molecular biology means such as immunofluorescent staining and Western blot, the anti-depression effect and potential mechanism of 4-isopropyltoluene are systematically evaluated, and the anti-depression effect and potential mechanism of 4-isopropyltoluene are evaluated. Results show that 4-isopropyltoluene plays a significant anti-depression role by inhibiting neuroinflammation, enhancing glial cell support function and activating AKT signal pathway, and has the potential of being developed into a novel anti-depression candidate drug.