67 results about "Personalized medicine" patented technology

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.

The present disclosure provides methods, compositions and systems for identifying variant targets of interest, for example, in clinically actionable genes. Disclosed herein are representative assays for identifying gene variants, for example, that are implicated in one or more drug metabolism pathways. The methods, composition and systems disclosed herein enable a highly streamlined and cost-effective workflow for moving forward the emerging field of personalized medicine and related fields of study such as pharmacogenomics.

The invention relates to a double-attention-enhanced drug prediction model MTDADP under a multi-task learning framework, and belongs to the technical field of medical artificial intelligence. According to the method, disease diagnosis detail information can be fully utilized, association between the disease diagnosis detail information and medical history can be deeply mined, and safer and more accurate personalized drug prescription recommendation can be realized. The method comprises the following steps: firstly, performing embedded representation on historical treatment records, current symptoms and test details of a patient by the MTDADP; the state representation of the patient is enhanced through double mechanisms of access level attention and feature dimension attention; then constructing a patient memory bank and carrying out two-channel retrieval, and comprehensively utilizing drug distribution information of similar and dissimilar patients; then, the safety of drug representation is enhanced through a graph convolutional network by using an EHR graph and a DDI graph; and finally, integrating multi-source information to carry out joint prediction, introducing disease diagnosis prediction as an auxiliary task, and carrying out optimization through a multi-objective loss function. Experimental results on a disclosed PIC data set show that the MTDADP is remarkably improved in Jaccard, F1 and PR-AUC indexes compared with an existing advanced baseline model, and the effectiveness of the method in the aspect of improving the drug prediction accuracy is verified.

A genetic prime editing screening platform to identify functional variants related to human health and disease, is configured substantially to annotate genome with nucleotide resolution with actionable disease prediction and treatment for personalized medicine.

Methods and systems are described for a high-level approach to organ generation by self-assembly using bioprinting, overcoming longstanding challenges in replicating the intricate architecture and function of complex organs. In some embodiments, these methods are used to produce lung tissues and microtissues, demonstrating how mini-lung constructs can be produced on a small scale through specialized processes and media. In such embodiments, methods and systems for generating bioprinted lung tissues and microtissues are provided, as are tissues made by such methods. The tissues find use in implantation, drug discovery, personalized medicine, and other applications. Methods for the large-scale manufacturing of lung epithelial stem cells are also provided.

The invention relates to the technical field of biology, and discloses a construction method of a gastric cancer organoid culture system, which comprises the following steps: preparation of a conditioned medium: culturing L-WRN cells and collecting the conditioned medium; preparing a gastric cancer organoid culture medium, and mixing the conditioned culture medium, the basic culture medium, a plurality of growth factors and additives; and extraction and culture of organoid: separating cells from gastric cancer tissues, mixing the cells with matrigel, and culturing by using the prepared culture medium. According to the method, the repeatability and the stability of the organoid model are improved, the response consistency of the organoid in drug screening is improved, and the reliability of the model in disease mechanism research and personalized medical application is guaranteed.

Based on experimental data, observed i n the Personalized Medicine Laboratory of the requesting institute, which reveal an increase in the inorganic polyphosphate (iPolyp) in fecal samples from subjects affected by colorectal cancer compared to samples from individuals not affected by the same disease, inorganic polyphosphate is suggested as a novel non-invasive biomarker to be detected in fecal samples for the early diagnosis of colorectal cancer, to be associated with other screening methods such as fecal occult blood, in order to provide greater predictivity, i.e., the probability that a subject with a positive diagnostic test is actually affected by colorectal cancer.

The field of the invention is in vitro assays for the production of in vitro organ culture systems and the use of such in vitro organ culture systems for screening assays in drug screening, patient selection and personalized medical context. More specifically, the present invention relates to an in vitro method of establishing a tumor organoid from a cancer tissue sample obtained from a subject, an in vitro method of providing immune cells activated by an autologous tumor organoid, a method of preparing an in vitro organ culture system for mimicking interaction of a tumor with an immune system of a subject, and a method of preparing an in vitro organ culture system for mimicking interaction of a tumor with an immune system of a subject. The invention relates to an in vitro organ culture system, and to an in vitro organ culture system produced thereby, to a method for determining the reactivity of a tumor to at least one immunooncology drug therapy using said in vitro organ culture system, and to a kit for preparing an in vitro organ culture system that mimics the interaction of a tumor with the immune system of a subject, as disclosed herein.

An exemplary system comprises a memory that stores instructions and a processor communicatively coupled to the memory and configured to execute the instructions to perform a process. The process may comprise accessing an individual three-dimensional (“3D”) cochlea model of a cochlea of a recipient of a cochlear implant system that includes a stimulating lead inserted into the cochlea during a lead insertion procedure, generating, based on the individual 3D cochlea model and procedure data associated with one or more lead insertion procedures performed with respect to one or more other recipients, an individualized drug delivery profile for the recipient, and transmitting a command to the cochlear implant system to cause release of a drug from the stimulating lead in accordance with the individualized drug delivery profile.

The invention relates to the technical field of data analysis, in particular to a patient medical information intelligent analysis method based on a big data artificial intelligence model, which comprises the following steps: processing large-scale and high-dimensional data according to clinical symptoms and disease degrees in multiple sources such as electronic health records, genome data and the like, extracting key features by utilizing a dimension reduction technology, and analyzing the key features; and information loss is reduced. The non-linear relation in the data can be identified and modeled, the complex mode is disclosed, and the medical data information of the patient can be analyzed more deeply. The refined analysis helps doctors to identify specific requirements of different patient groups, the effectiveness of clinical decisions is improved, and personalized medical treatment and resource optimization are realized.

Provided are methods, systems and computer program product embodiments for analyzing multi-omic data using a tensor regression model for genome-wide association studies in the life sciences. The unique structure of tensor covariates is leveraged to find associations between the omics data and complex diseases. Within this framework, the excessive dimensionality is reduced to a manageable level, leading to efficient estimations and predictions. The method is superior to using classical regression techniques in genome-wide association studies, which are challenged by analyzing multi-dimensional and uniquely structured data from the health and life sciences, in which covariates can take on more intricate forms such as multi-dimensional arrays. Embodiments have multiple uses in genomics, proteomics, metabolomics, multi-omics data integration, drug discovery, personalized medicine and predictive modeling, demonstrating the versatility and importance of tensor regression models to understand the associations between omics data and complex diseases.

The invention discloses a medicine big data sharing platform based on cloud computing, and belongs to the field of data management, and the platform comprises a network construction unit which is used for building a distributed storage network on a cloud computing center; the interface setting unit is used for setting a mechanism access interface and a personal access interface; the database forming unit is used for forming a medicine big database; the mechanism request processing unit is used for screening an initial medicine data set according to the mechanism access request; the mechanism data processing unit is used for generating a target medicine data set and sending the target medicine data set to the requesting mechanism; the personal request processing unit is used for screening an associated medicine data set according to the personal access request; and the individual report generation unit is used for generating a personalized medicine data analysis report and sending the report to the requesting individual. By integrating and storing dispersed medical data and providing data access interfaces and processing services oriented to organizations and individuals, efficient sharing and utilization of the medical data are realized.

The invention provides a lung squamous cell carcinoma organoid culture medium and a culture method. The lung squamous cell carcinoma organoid culture medium is prepared from the following components: R-spondin-1, Noggin, EGF (Epidermal Growth Factor), FGF10 (Fibroblast Growth Factor), FGF7 (Fibroblast Growth Factor), A83-01, Y-27632, Nicotinamide, Insulin, B27 Supplement, N-Acetylcysteine, Alpisib, GlutaMAX, primary cell antibiotics and the like. The lung squamous cell carcinoma organoid culture medium can be used for efficiently culturing lung squamous cell carcinoma tissues and successfully obtaining organoid, the formed organoid is highly similar to primary lung squamous cell carcinoma tissues in cell type, polarity and spatial hierarchical structure, and the micropathologic characteristics of tumors are truly reproduced. And the organoid can be stably passaged for a long time, so that an ideal and reliable preclinical model is provided for pathogenesis research, personalized drug screening and novel therapy development of lung squamous cell carcinoma.

To provide methods and systems for predicting HLA class II specific epitopes and characterizing CD4+ T cells. [Solution] This disclosure provides a method for preparing personalized cancer vaccines. This disclosure also provides a method for training a machine learning HLA-peptide presentation predictive model. The methods and compositions described herein can be used in a wide range of applications. For example, the methods and compositions described herein can be used to identify immunogenic antigen peptides, and can also be used for the development of drugs such as personalized medicines, as well as for the isolation and characterization of antigen-specific T cells.

An exemplary system comprises a memory that stores instructions and a processor communicatively coupled to the memory and configured to execute the instructions to perform a process. The process may comprise accessing an individual three-dimensional (“3D”) cochlea model of a cochlea of a recipient of a cochlear implant system that includes a stimulating lead inserted into the cochlea during a lead insertion procedure, generating, based on the individual 3D cochlea model and procedure data associated with one or more lead insertion procedures performed with respect to one or more other recipients, an individualized drug delivery profile for the recipient, and transmitting a command to the cochlear implant system to cause release of a drug from the stimulating lead in accordance with the individualized drug delivery profile.

System and methods for computer modeling in medicine. A sort of period table of medical models is described for personalized diagnostics, prognostics and therapeutics, including at least 80 major categories of medical models. Generative artificial intelligence and geometric deep learning techniques, and algorithms including 2D and 3D graph machine learning and GenAI algorithms, are described, tailored and applied to diagnostic disease description, prognostic prediction and therapeutic development and management, including generation of novel synthetic drugs. The AI and machine learning techniques and algorithms are applied to understand each individual's genetic, RNA and protein anomalies that represent the source of many unique patient diseases. AI-enabled software agents assist physicians and researchers in building patient medical models. Several personalized medicine applications of individualized medical modeling include cardiovascular

The invention provides a mechanical arm personalized medicine taking method and system based on AI dialogue driving, and relates to the technical field of AI.The method includes the steps that medicine taking appeals are received, dialogue state tracking analysis is conducted, related medicine nodes are positioned in a medicine relation network, user recessive medicine taking preferences are recognized, medicine recommendation vectors are generated, and the selection probability is calculated; and a storage position index of the target medicine is determined, and a mechanical arm pose transformation matrix is calculated to execute the medicine taking action. The personalized degree and accuracy of medicine distribution can be improved, the user experience is enhanced, and the risk of medicine dispensing errors is reduced.

The invention provides an intelligent drug research and development system. According to the intelligent drug research and development system, a three-dimensional conformation generation unit, a target spot specificity recognition unit, a multi-task drug screening unit, a drug attribute prediction unit, a personalized drug design unit and a dynamic feedback learning unit are integrated, and intelligent models of all stages of a drug design process are integrated through a multi-unit cooperation mechanism; and a complete artificial intelligence driving type drug research and development platform capable of realizing closed-loop operation is formed.

The invention relates to the field of microfluidic organ chips, in particular to a laminated organ chip and a use method thereof.The laminated organ chip comprises a sample layer, a blood vessel layer, a matrix layer and an organ-like layer which are laminated from top to bottom, a closed structure is formed through plasma bonding reaction, and five independent fluid channels are arranged in the closed structure; blood circulation, matrix perfusion, cell inoculation and metabolite collection are respectively realized, and cross contamination is reduced. The blood vessel layer is provided with a bionic flow channel for simulating human body blood circulation; the matrix layer realizes selective exchange of small molecules through a porous membrane structure; and the organ-like layer supports a porous membrane by using a strip-shaped microstructure and is used for cell attachment. The laminated organ chip disclosed by the invention can highly simulate physiological hierarchical structures of human organs, blood vessels and matrixes and human microenvironments, can be used for pathological research, drug research and development and testing, personalized medical treatment, toxicity testing and the like, and has wide application value in the fields of biomedical research and the like.

The application relates to the technical field of medical treatment, in particular to an intelligent medicine auxiliary system based on patients with cognitive impairment. The application comprises a terminal interaction layer, a perception decision layer, a cloud service layer and a user management layer; the perception decision layer comprises an intelligent medicine management module and a personalized adaptation module; the intelligent medicine management module is used for performing multiple reminders, medicine identification verification, medicine taking behavior recording and medicine taking record backtracking according to a preset medicine taking scheme; the personalized adaptation module is used for dynamically adjusting a reminding mode and an interaction strategy according to a cognitive impairment degree and a visual impairment grade of a patient. The application aims to provide an intelligent medicine auxiliary system based on patients with cognitive impairment, so as to realize safe, standardized, intelligent and personalized medicine taking management for patients with cognitive impairment.

Provided are a serum-free medium for co-incubation of tumor organoids and immune cells, a tumor organoid immune microenvironment system and a construction method therefor, and a method for evaluating the efficacy of drugs based on tumor organoid immune co-culturing. The used medium for co-incubation of tumor organoids and immune cells can well maintain the growth of tumor organoids and immune cells, and can provide nutritional support for these two different types of cells. In addition, the established method for evaluating the efficacy of drugs in a tumor organoid immune co-culture system can be used for evaluating the efficacy and toxic side effects of an immune drug against a tumor, helping to select potentially effective drugs and optimize a treatment scheme. By means of the organoid immune co-culture system, the response of different patients to drugs can be better understood, providing a basis for personalized medicine and precision treatment.

This invention relates to the field of brain network analysis technology, specifically to a multimodal brain network fusion method based on tensor spectral clustering. The method includes: acquiring multimodal brain network data, including structural magnetic resonance imaging (SMRI) data, functional magnetic resonance imaging (fMRI) data, and diffusion tensor imaging (DTI) data; preprocessing the multimodal brain network data; constructing individual morphological brain networks, functional brain networks, and structural brain networks based on the preprocessed multimodal brain network data, and performing normalization processing; fusing the normalized multimodal brain networks using a tensor spectral clustering algorithm to obtain a fused brain network; acquiring the subject's behavioral data, inputting the behavioral data into the fused brain network, and calculating the subject's behavioral prediction values. This invention not only advances research in neuroscience, cognitive science, and psychology but also provides strong support for related clinical applications and personalized medicine.

An exemplary system comprises a memory that stores instructions and a processor communicatively coupled to the memory and configured to execute the instructions to perform a process. The process may comprise accessing an individual three-dimensional ("3D") cochlea model of a cochlea of a recipient of a cochlear implant system that includes a stimulating lead inserted into the cochlea during a lead insertion procedure, generating, based on the individual 3D cochlea model and procedure data associated with one or more lead insertion procedures performed with respect to one or more other recipients, an individualized drug delivery profile for the recipient, and transmitting a command to the cochlear implant system to cause release of a drug from the stimulating lead in accordance with the individualized drug delivery profile.

The invention belongs to the technical field of intelligent medical treatment, and particularly relates to a personalized drug recommendation method and system fusing adverse drug reactions, and the method comprises the following steps: inputting longitudinal electronic health record multi-source data of a patient, extracting and fusing time sequence features and drug similarity features, and generating comprehensive information representation of the patient. Local drug information representations and drug information representations are generated through a drug molecule bipartite graph and a drug information cassette, respectively, based on the comprehensive information representation of the patient. After external adverse drug reaction information is introduced and processed by an encoder, the comprehensive information of a patient is used for representing weighting, and adverse drug reaction characteristics are obtained. And the local drug information representation, the drug information representation and the adverse drug reaction characteristics are spliced, and final drug combination recommendation is output through prediction scores. According to the method, various kinds of useful information are fully utilized, complementarity and correlation among different medicine information sources are captured, the quality of multi-source data fusion is improved, and the accuracy and safety of medicine recommendation are optimized.

The invention discloses an intelligent medication management system for explaining medication guidance based on AI and digital avatar, and relates to the technical field of deep application and innovation of an artificial intelligence technology in the medical field. Comprising an input and preprocessing module, a private domain knowledge base construction module, a conditional retrieval and learning rearrangement module, a generation and instrumentalization reasoning module, a traceability and medication affiliation module, an output and interface module and a digital avatar explanation generation module. According to the invention, technology fusion innovation is carried out: three fields of a large model, a professional knowledge base and a digital human technology are organically fused in a specific medication guidance, and a smooth cooperation process is designed. According to the invention, application scene innovation is carried out: in the field of medication guidance, a solution for providing a face-to-face video explanation personalized medication guidance for a patient by digital division crossing time and space is provided for the first time, and accurate and effective information transmission between a doctor and the patient is realized.

In general, disclosed herein are methods for simultaneous monitoring the relative sensitivities of different organoids to a therapeutic agent. The method may include obtaining a sample that includes a plurality of barcoded organoid avatars; contacting the sample with a therapy; detecting in the sample at a first point in time the copy number, amount, and / or activity of one or more organoids; repeating the detection step at a subsequent point in time; and comparing the copy number of one or more organoids detected to monitor the progression of the effectiveness of the therapy.

A method for diagnosing a disease in a subject, in particular a hematological malignancy or a solid tumor, comprising the steps of: isolating (21, 61) an extracellular vesicle precipitate (3a, 3b) obtained from a sample (2) of a biological fluid previously taken from the subject; measuring (31, 41, 51-52), from said precipitation, parameters representative of six biomarkers: (I) the size of the extracellular vesicles; (II) the total amount of extracellular vesicles; (III) an amount of extracellular vesicles expressing the first antigen on their own surface and (IV) an amount of extracellular vesicles expressing the first antigen and the second antigen; (V) an average fluorescence intensity for each of the antigens; and (VI) the nucleic acid content of the extracellular vesicles; first comparing a parameter representative of the biomarker with a corresponding critical value; based on the first comparison step, assigning a partial score to each parameter or to the six biomarkers; calculating a final score, namely the score of the subject, as the sum of the partial scores; a second comparison of the final score with at least one predetermined diagnostic threshold, preferably with two diagnostic thresholds, an upper diagnostic threshold and a lower diagnostic threshold; based on the second comparison step, a probabilistic diagnosis of the lesion is estimated. Under the background of personalized medical treatment, the combination of the six biomarkers overcomes the limitation of the prior art method caused by high clinical heterogeneity between subjects, which is specifically embodied in sensitivity to a given lesion; in other words, a certain biomarker, not other biomarkers, selected from the six biomarkers and related parameters of the biomarkers are different.

A method and apparatus enabling additive manufacturing of individualized oral therapeutic capsule forms containing multiple medicinal ingredients, also referred to as a personalized polypill process. A process and supporting apparatus to fulfil the formulated therapy prescribed by a physician to address the medical conditions of an individual patient, furthering the practice of personalized medicine. The methods and apparatus apply to the powder forms of active pharmaceuticals, dietary supplements, and specialized chemicals, such as diagnostic inks and dyes. The methods teach the deposition of computer-controlled amounts of high-potency powder forms of active ingredients deposited in sequential layers into a single delivery form. Each active ingredient layer is sequentially deposited to a programmable dosage accurately controlled with closed-loop gravimetric sensing, enabling sub-milligram mass deposition accuracy. Cumulative doses are compacted into segregated layers of programmable density with the optional addition of an inert barrier film between each chemical entity to minimize interactions.

The system provides customizable diagnostic tools to quantify brain health over the span of a lifetime and to assess the impact of various interventions. The system may be configured to receive information regarding a first user of the system; output, based on the information regarding the first user of the system, a first indication of one or more cognitive tasks for an assessment of the first user; receive data relating to the one or more cognitive tasks performed by the first user; generate at least one of one or more diagnoses or one or more analyses for the first user based on the data relating to the one or more cognitive tasks performed by the first user; and output a second indication of the at least one of the one or more diagnoses or the one or more analyses for the first user.

This invention discloses a novel aggregation-induced luminescent substance targeted delivery method for a triple therapy combining chemotherapy, radiotherapy, and immunotherapy for tumors. This invention relates to the field of biotechnology, specifically to a novel aggregation-induced luminescent substance targeted delivery method for a triple therapy combining chemotherapy, radiotherapy, and immunotherapy for tumors. This invention provides a drug with inhibitory or anti-tumor activity against tumor cells. The active ingredient of the drug contains LNC@AIEgen, which is composed of inactivated cancer cells and Complex 1 loaded onto the inactivated cancer cells. The nanoplatform LNC@AIEgen designed in this invention is used for synergistic chemotherapy-radioimmunotherapy. This system fully utilizes the advantages of the delivery carrier, enhancing the anti-tumor therapeutic effect and acting as an anti-cancer vaccine. This simple yet effective strategy enables large-scale clinical treatment of cancer and contributes to personalized medicine.