78332 results about "Pharmaceutical drug" patented technology

A scalable platform for orchestrating networks of specialized AI multi-agent networks that enables secure collaboration through token-based protocols and real-time result streaming with advanced dynamic chain-of-thought pruning. The central orchestration engine manages domain-specific agents, implementing sophisticated multi-branch reasoning with contribution-estimation layers that evaluate each agent's utility using Shapley value-inspired metrics. The system employs information-theoretic and gradient-based surprise metric to guide memory updates and dynamic reasoning expansion, preventing local minima stagnation while preserving valuable insights through adaptive forgetting mechanisms. The platform unifies Monte Carlo tree search with contribution-aware estimation to detect high-synergy expert combinations while maintaining privacy through partial data approaches. It scales across distributed computing environments, enabling complex collaborative tasks like materials discovery, product engineering and manufacturing process design, biomedical research, and drug development. The system supports multi-party economic rewards through systematic contribution effort, cost and importance tracking, while standardized interfaces manage security, privacy, and policy constraints across heterogeneous agents.

The present disclosure provides novel compounds useful as inhibitors of KRAS, in particular KRAS G12D and / or other KRAS G12 mutants, as well as pharmaceutical compositions comprising these compounds and methods of treatment by administration of these compounds or the pharmaceutical compositions.

The invention relates to a drug-disease relationship prediction method and system based on a dual-channel fusion knowledge graph. The method comprises the following steps: S1, constructing a biomedical fusion knowledge graph; s2, constructing a drug-disease sub-graph based on the biomedicine fusion knowledge graph; s3, constructing a dual-channel adaptive fusion feature module, and embedding a drug-disease sub-graph; s4, performing enhanced splicing on the drug-disease sub-graphs in the dual-channel fusion knowledge graph pre-embedded network, importing an edge-node iterative updating learning mechanism, training a spliced sub-graph relation perception learning network, and obtaining enhanced sub-graph feature embedding; and S5, utilizing the trained enhanced subgraph features to embed, calculate and output the prediction probability of the drug-disease relationship. According to the method, the semantic representation capability of the knowledge graph and the topological modeling advantages of the graph neural network are integrated, and efficient and accurate prediction of the drug-disease relationship is realized through multi-modal feature interaction, sub-graph enhancement and a dynamic sub-graph learning mechanism.

Set forth are vascular valves and servovalves and methods of using the same that may be positioned in the circulatory system without interrupting blood flow to facilitate solid organ transplantation so as to reduce graft organ anoxia and degradation before and after harvesting and storage, thereby minimizing late-term cardiac allograft vasculopathy as a major cause of graft failure. Along the urinary tract, bypassing bladder-generated urge sensation by diverting urine directly from the ureters to a neobladder or collection bag alleviates intractable incontinence, nocturia, urethral syndrome, overactive bladder, dysuria, or frequency. Where the lower tract is missing, a prosthesis can thwart disease and preclude the degenerative metaplastic transition to carcinoma risked when gut is used to construct a conduit for urine, a neobladder, and / or high-maintenance stoma. Druglines to valves and servovalves can directly pipeline-target medication to nidi, anastomoses, or any other trouble spots.

Provided are a pyrimidine polycyclic derivative inhibitor, a preparation method therefor and the use thereof. In particular, provided are a compound as shown in the general formula, a preparation method therefor, a pharmaceutical composition comprising the compound, and the use thereof in the treatment of cancers and other related diseases.

Disclosed herein are compositions comprising an NSAID such as meloxicam and / or rizatriptan in combination with a cyclodextrin and / or a carbonate or a bicarbonate. These compositions may be orally administered, for example, to improve the bioavailability or pharmacokinetics of the NSAID for the treatment of pain such as migraine, arthritis, and other conditions. Also disclosed herein are methods of treating pain, such as migraine, comprising administering meloxicam and rizatriptan to a human being suffering from pain, such as migraine. For migraine, these methods may be particularly useful when the meloxicam and rizatriptan are administered while the human being is suffering from an acute attack of migraine pain or migraine aura. In some embodiments, the combination of meloxicam and rizatriptan may be administered in a manner that results in a Tmax of meloxicam of 3 hours or less.

Related to macrocyclic compounds and therapeutic uses thereof. Disclosed a compound of formula (I), or a pharmaceutically acceptable salt thereof, a solvate thereof or a solvate of the pharmaceutically acceptable salt, and their use for the preparation of a medicament of treatment of cancer. Provided herein are useful compounds for the inhibition of RAS mutant and the compound shows good inhibitory activity against RAS.

The present invention is directed to the compounds of Formula (IV) inhibitors of KRAS(G12D). The inhibitors described herein can be useful in the treatment of diseases or disorders associated with KRAS(G12D), such as Lung cancer, Pancreatic cancer, Colorectal cancer et al. In particular, the invention is concerned with compounds and pharmaceutical compositions inhibiting KRAS(G12D), methods of treating diseases or disorders associated with KRAS(G12D), and methods of synthesizing these compounds.

The present invention belongs to the technical field of medicinal chemistry, and particularly relates to a pyrimidine macrocyclic compound. The compound has a good inhibitory effect on KRAS mutations, has a good inhibitory effect on the G12V mutation and other types of mutations of the KRAS gene, can be used as a general KRAS inhibitor, and can be used for the treatment of tumors driven by KRASG12V and other types of gene mutations.

A pharmaceutical composition comprising a protein arginine methyltransferase 5 (PRMT5) inhibitor and a KRASG12C (Kirsten rat sarcoma viral oncogene homolog glycine-to-cysteine) inhibitor. The pharmaceutical composition can be used for treating various cancers, comprising solid tumors. The combined product can be used for treating any number of diseases associated with PRMT5 and / or KRASG12C.

The invention belongs to the technical field of medical resource intelligent management, and relates to a hospital comprehensive monitoring analysis method and platform based on artificial intelligence, and the method comprises the following steps: generating a medicine management basic data set; generating a primary prediction signal; adjusting a prediction weight according to the conflict level and outputting a reliable demand prediction instruction; a quantitative evaluation value reflecting the medicine turnover efficiency, the immediate pressure and the cost loss is calculated, and when the quantitative evaluation value exceeds a preset safety alert threshold value, an inventory abnormity alarm signal is generated; outputting an allocation strategy instruction containing the medicine flow direction, the allocation quantity and the time efficiency; and comparing a deviation value between the reliable demand prediction instruction and the allocation strategy instruction, and when the deviation value continuously exceeds a preset deviation threshold value, triggering an update prompt of the drug safety use limit rule base. The problem that demand prediction and clinical rule verification are separated in a traditional mode is solved.

The invention discloses a liver disease diagnosis and treatment strategy recommendation method based on a knowledge graph, a medium and equipment, and the method comprises the steps: collecting the basic information of a user, constructing a space-time correlated individual liver disease knowledge graph according to the basic information of the user, and enabling the knowledge graph to comprise a disease cause feature node, a pathology grading node, a complication early warning node and a treatment response node which are correlated with each other; inputting the individual hepatopathy knowledge graph into a hierarchical reinforcement learning model for joint reasoning, and outputting multiple groups of strategy options including an antiviral treatment scheme, a liver protection drug combination and a metabolic intervention measure; analyzing a topological propagation path of a complication early warning node through a complication prediction sub-model, and dynamically adjusting an initial candidate diagnosis and treatment strategy set; and updating the individual hepatopathy knowledge graph when obtaining the basic information of the new user. According to the method, multi-dimensional data fusion and dynamic strategy optimization of liver disease diagnosis and treatment are realized, and the accuracy and timeliness of a diagnosis and treatment scheme are remarkably improved.

A recombinant humanized collagen and a preparation method therefor. The recombinant humanized type III collagen can be efficiently and stably expressed in three expression systems of yeast, Escherichia coli, and CHO cells, and has the biological activity superior to that of a commercially available collagen product. The recombinant humanized type III collagen has structural characteristics and functional activity similar to those of a natural collagen, and thus has wide application prospects in biomedical materials, tissue engineering products, cosmetics, foods, health care products or drugs, medical instruments, medical cosmetology and the like.

The present invention relates to a compound as shown in formula (A) having a pan-RAS inhibitory effect, or an isotopic derivative or stereoisomer thereof, or a pharmaceutically acceptable salt thereof, and a pharmaceutical composition containing the compound, and the use of the compound of formula (A) in the prevention and / or treatment of cancers, tumors, inflammatory diseases, autoimmune diseases or immune-mediated diseases.

The present invention relates to the use of a FAK inhibitor in preparing a drug to be jointly used with a KRAS G12C inhibitor to treat a tumor.

Dosage forms, drug delivery systems, and methods related to sustained release of dextromethorphan or improved therapeutic effects are disclosed. Typically, bupropion or a related compound is orally administered to a human being to be treated with, or being treated with, dextromethorphan.

Provided is a compound useful as an active ingredient in a pharmaceutical composition for treating cancer.　The present inventors have examined a compound useful as an active ingredient in a pharmaceutical composition for cancer treatment, and have completed the present invention by finding that: a heterocyclic compound represented by formula (I) and formula (I-I) has excellent an action of inducing degradation of a mutant KRAS protein and a wild-type KRAS protein, and in particular, an action of inducing degradation of a KRAS protein having a G12C mutation, G12D mutation, G12V mutation, or G13D mutation; and said heterocyclic compound has mutant KRAS inhibition and the inhibitory activity of KRAS amplified by a wild-type KRAS gene, and in particular, inhibitory activity of KRAS having a G12C mutation, G12D mutation, G12V mutation, or G13D mutation. The heterocyclic compound according to the present invention or a salt thereof can be used as a therapeutic agent for cancer.

A tricyclic compound as a VHL ligand, a preparation method therefor, and a use of the compound or a pharmaceutical composition thereof for preventing and / or treating a series of diseases, disorders, and conditions.

Dosage forms, drug delivery systems, and methods related to sustained release of dextromethorphan or improved therapeutic effects are disclosed. Typically, bupropion or a related compound is orally administered to a human being to be treated with, or being treated with, dextromethorphan.

The present invention provides macrocyclic compounds, the use thereof for selectively inhibiting the activity of RAS mutants, and pharmaceutical compositions comprising the compounds, e.g., for treatment of various diseases including cancer.

A computer-implemented system for personalized health optimization constructs a confidence-weighted personal health knowledge graph (PHKG) from heterogeneous data, including wearable sensors, medical devices, lab results, medication logs, and conversational inputs. A multi-stage causal-inference stack identifies modifiable drivers of outcomes using layered methods (e.g., MI, GAM, Neural Granger, DAG-GNN), and simulates candidate interventions. A recommendation engine ranks lifestyle or pharmacologic actions using a benefit-to-friction score, selecting a personalized intervention aligned with user readiness and clinical safety constraints. Interventions may include a minimum effective dose (MED), optimal level, adaptive low-dose, or behavioral challenge. Optional modules include reinforcement learning for timing adaptation and privacy-preserving on-device inference. The system operates across domains including metabolic, cardiovascular, renal, sleep, stress, and medication response, enabling cross-condition synergy evaluation. The architecture is modular, supports runtime plug-in targets, and adapts in real time with or without continuous clinical oversight, depending on deployment.

The invention discloses a drug target affinity prediction method and system based on a multi-scale protein attention mechanism, and belongs to the crossing field of bioinformatics and artificial intelligence. The method comprises the following steps: firstly, extracting protein sequence features through an ESM2 pre-training model, predicting that a three-dimensional structure is converted into a two-dimensional contact graph, and extracting spatial topological information in combination with a graph convolutional network; a two-dimensional attention mechanism is innovatively designed, structural features are taken as query vectors, sequence features are taken as key value pairs, and cross-modal feature fusion is realized by dynamically associating sequence semantics and spatial proximity relationships through multiple attention. Drug molecules are characterized by adopting MACCS fingerprints, are spliced with protein multi-modal features and then are optimized through a deep network, and finally an affinity value is output through a regression prediction module. According to the technology, the problem of protein heterogeneous data fusion is effectively solved, the generalization ability to unknown targets is remarkably improved, an efficient calculation tool is provided for new drug research and development and drug relocation, and the drug research and development cost can be reduced.

A spiro compound, and a preparation method therefor and a use thereof. Specifically, the present invention relates to a compound of formula (I) or a pharmaceutically acceptable salt, stereoisomer, tautomer, polymorph, solvate, N-oxide, isotopically labeled compound, metabolite, or prodrug thereof, a pharmaceutical composition comprising the compound, a preparation method therefor, and a use thereof in preparation of a drug for preventing or treating KRAS-mediated related diseases.

A database structure obtained by means of information retrieval, and a reasoning system, which structure and system specifically relate to a gut microbe knowledge graph system, comprising: a gut microbe knowledge graph consisting of a gut microbe knowledge base, a gut microbe and small-molecule drug therapy association knowledge base, and a clinical medicine database; and a multimodal uncertainty reasoning system, using the gut microbe knowledge graph. The gut microbe knowledge graph system predicts potential diseases, drugs, genes, etc., which are associated with gut microbes.

Provided is an antibody-drug conjugate for use in the treatment of cancer in which one or more KRAS mutants, particularly a KRAS G12V mutant, a KRAS G12D mutant, and a KRAS G12C mutant, are expressed. Also provided are a drug and a drug-linker conjugate for use in the antibody-drug conjugate.　The present inventors have produced an antibody-drug conjugate with which a heterocyclic compound represented by formula (II) and having an activity of inducing the decomposition of KRAS mutant proteins can be delivered to cancer in which EGFRs are expressed, the production being achieved by linking the compound to an anti-EGFR antibody. The present inventors have also discovered a drug-linker conjugate for use in the antibody-drug conjugate or a salt thereof. In cancer in which EGFRs are expressed, the antibody-drug conjugate induces the decomposition of one or more KRAS mutants, particularly a KRAS G12V mutant protein, a KRAS G12D mutant protein, and a KRAS G12C mutant protein, thereby inhibiting the KRAS mutants and exhibiting an anti-tumor effect.

The invention discloses a drug and target interaction prediction method based on multi-scale convolution feature fusion, which comprises the following steps: acquiring drug molecule data, target protein data and drug and target interaction data, constructing a drug molecule map according to the drug molecule data, and coding a target protein sequence according to the target protein data; inputting the drug molecular map into a model, and obtaining drug features through a multi-scale map convolutional network and a dynamic gating attention mechanism; inputting a target protein sequence into the model, and obtaining target features through hierarchical cavity convolution and a bidirectional gating cycle unit; through multi-head cross attention, the drug features are aligned with the target features, local and global cross-modal fusion is carried out, and drug target fusion features are obtained; based on the drug target fusion features, outputting a drug and target interaction prediction probability; and training the model according to the drug and target interaction data and the prediction probability, and applying the trained model to drug and target interaction prediction.

Dosage forms, drug delivery systems, and methods related to sustained release of dextromethorphan or improved therapeutic effects are disclosed. Typically, an antidepressant, such as bupropion or a related compound is orally administered to a human being to be treated with, or being treated with, dextromethorphan.

This disclosure relates to a method of treating a neurological disorder, comprising administering a bupropion, or a combination of a bupropion and a dextromethorphan, to a human being in need thereof, monitoring the human being for Brugada pattern / syndrome, drug reaction with eosinophilia and systemic symptoms, or acute generalized exanthematous pustulosis, and reducing or discontinuing use of the bupropion, or the combination of the bupropion and the dextromethorphan, if the human being develops Brugada pattern / syndrome, subcutaneous tissue disorder, drug reaction with eosinophilia and systemic symptoms (DRESS), or acute generalized exanthematous pustulosis.

Disclosed in the present invention are a quinazoline compound, and a pharmaceutical composition thereof and the use thereof. Provided in the present invention is a compound as represented by formula I, a stereoisomer thereof or a pharmaceutically acceptable salt thereof. The compounds of the present invention have a good degradation effect on the KRAS protein with a G12D mutation, have a good inhibitory activity against the proliferation of tumor cells with a KRAS G12D mutation, and exhibit good pharmacokinetic properties.