129 results about "Patient population" patented technology

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg of bupropion hydrochloride, or a molar equivalent amount of the free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg of dextromethorphan hydrobromide, or a molar equivalent amount of the free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg of bupropion hydrochloride, or a molar equivalent amount of a free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg of dextromethorphan hydrobromide, or a molar equivalent amount of a free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg of bupropion hydrochloride, or a molar equivalent amount of the free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg of dextromethorphan hydrobromide, or a molar equivalent amount of the free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg of bupropion hydrochloride, or a molar equivalent amount of the free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg of dextromethorphan hydrobromide, or a molar equivalent amount of the free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

The invention discloses a method and a system for evaluating movement of two lower limbs of a stroke patient, and relates to the technical field of movement function evaluation. The invention discloses a stroke patient double-lower-limb movement evaluation system which comprises a task guide module, a movement acquisition module, a movement scoring module, an interference evaluation module, a trend analysis module, a combination analysis module and a result output module. According to the method, the scoring model based on crowd category feature matching is constructed, exercise ability scoring is performed by adopting a machine learning algorithm or a fixed weighted combination, personalized evaluation is realized according to the group features of different patients, and the generalization ability and prediction accuracy of the scoring model are improved; group modeling is carried out by introducing features such as patient age, gender and motion level, and a scoring strategy is automatically switched according to the number of samples, so that the scoring mechanism also has reliability and clinical consistency in a family scene with limited data volume.

A method and algorithm for dosing single and multiple drugs for an individual patient includes the step of collecting data from the individual patient. The data includes drugs to be taken by the patient, the patient's age, medical condition, metabolism, and other factors. The method further includes the steps of analyzing the individual patient data in view of dosing criteria established based on patient population data. Based on the analysis, a dose of the single or multiple drugs is recommended. Alternative treatment options can also be recommended.

A implemented method, computing system and computer-readable medium for stratifying patient cancer risk using molecular data includes receiving molecular data; processing the molecular data using a machine learning model; and generating a matched treatment strategy for the patient based upon the patient's molecular data risk. A computer-implemented method, computing system and computer-readable medium for training a machine learning model to stratify patient cancer risk using molecular data includes receiving a patient training dataset, and a reference training dataset; selecting a cohort of patients; selecting a small subset of genes using univariate selection; generating a corrected reference training dataset; selecting a smaller subset of genes using multivariate selection; training a survival model; and (g) selecting a decision threshold to identify a patient population.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

The disclosed method and system pertain to stratifying a patient population for precision medicine in Inflammatory Bowel Disease (IBD) treatment. The method involves accessing a multi-omic dataset comprising genomic, transcriptomic, and proteomic profiles of patient data. Machine learning algorithms are employed to analyze the dataset and identify biomarkers associated with a response to a drug for treating IBD. The patient population is stratified into phenotypic groups based on the identified biomarkers using unsupervised clustering. A patient population predicted to respond to the drug is defined based on the stratification and further analysis of patient metadata. The system includes a data storage unit and a processor configured to perform the method. The method and system can be used to optimize therapeutic interventions in IBD management.

Disclosed herein are methods of using OX40 as a biomarker for predicting clinical sensitivity and therapeutic response of subjects having cancer to treatment with immunotherapeutic agents, and methods of using OX40 as a biomarker for selecting patient population for cancer treatment with immunotherapeutic agents. Disclosed herein are also methods of treating OX40-expressing cancers using immunotherapeutic agents. Further provided herein are kit for predicting the responsiveness of a subject having cancer to treatment with immunotherapeutic agents.

Systems and methods for non-invasively measuring intracranial in accordance with embodiments of the invention are illustrated. One embodiment includes a method for estimating an intracranial pressure of a patient, including introducing a tracer into the blood of a patient, recording, using an imaging device, the traversal of the tracer through a brain of the patient as a kinetic curve, estimating a mean transit time (MTT) of the tracer through the brain of the patient based on the kinetic curve, measuring a mean arterial pressure (MAP) of the patient, calculating an intracranial pressure index as MAP−Ck / MTT, where C is a constant to scale proportional relationships based on healthy patient population characteristics, and k is a constant in pressure / time, and providing the intracranial pressure index. In various embodiments, regions of the brain unaffected by transient vascular abnormalities are identified and are used for data collection.

The present disclosure relates generally to biomarker discovery and patient stratification, and more specifically to machine learning techniques for discovering relevant biomarkers using data collected as part of the standard-of-care (SoC), which can be used to identify a relevant patient population for a therapeutic with a known mechanism of action (MoA). An exemplary method for predicting activity of a molecular analyte of a patient comprises: training a first module of a machine learning model based on a plurality of medical images of a first cohort; training a second module of the machine learning model based on one or more molecular analyte data sets obtained from a second cohort; receiving a medical image from the patient; and predicting, using the trained first and second modules of the machine learning model, the activity of the molecular analyte from the medical image of the patient.

The present application relates, inter alia, to anti-cMET antibody drug conjugates ("ADC") ("pH-ADC") having lower target-specific binding at lower pH relative to physiological pH; a pharmaceutical composition including the pH-ADC; a method for preparing the pH-ADC; methods of selecting a specific patient population for cancer treatment with an anti-cMET pH-ADC; the present invention relates to pH-ADCs, and methods of using the pH-ADCs in the treatment of cancer, including cMET + / cMET-expressing or overexpressing cancers, in particular non-small cell lung cancer ("NSCLC"), including cMET + / cMET-expressing or overexpressing cMET.

Disclosed is method and system for identifying treatment subpopulations within a patient population of a clinical study, by applying a causal ensemble model configured to output an ensemble Conditional Average Treatment Effect (eCATE).

Provided herein are methods and compositions for the treatment of ALS using chlorite or a pharmaceutical composition comprising sodium chlorite, for a target ALS patient population. Also provided herein are methods for identifying a target ALS patient population likely to be responsive to treatment with chlorite or a pharmaceutical composition comprising sodium chlorite, the methods including identifying ALS patients with elevated plasma C-reactive protein (CRP) levels and / or patients age 40-65, sporadic ALS pathology, or combinations thereof.

The invention belongs to the technical field of biological medicine, and particularly relates to application of actinomycin D in preparation of a ctDNA detection sensitizer. The invention provides a ctDNA release method based on actinomycin D as an enhancer, which can significantly improve the release level of ctDNA in early small-volume tumors and tiny residual lesions, thereby improving the sensitivity and positive detection rate of liquid biopsy in MRD detection. Under an extremely low dosage, the ActD can generally promote a plurality of human tumor cells to release ctDNA under the condition of not causing obvious cell death, and has good biological safety and adaptability. The method is especially suitable for tiny, biological inert or anatomical position hidden focuses which are difficult to identify by iconography, namely blind area patient groups in disease monitoring, and has a wide clinical application prospect.

The invention relates to the technical field of cardiovascular disease health risk assessment and management, and discloses a cardiovascular patient group health assessment system based on diet and individual characteristics, which comprises a data acquisition module, an analysis and prediction module and a health assessment module. According to the cardiovascular patient group health assessment system based on diet and individual characteristics, a data acquisition module acquires a user data set, a data preprocessing unit identifies the user data set, a risk proportion unit calculates a disease risk ratio Hbfx, and a variable prediction unit calculates a disease prediction data set Fbyc; the health assessment module calculates a comprehensive influence data set Zhyx and comprehensively assesses the influence of significant variables of a user on CVD risks, analysis and assessment are more comprehensive and highly targeted, the health assessment module compares a reference data set according to the comprehensive influence data set Zhyx and judges and assesses corresponding scores, and the effect of early intervention and treatment of cardiovascular diseases is better.

Systems and methods for ophthalmic disease detection and risk assessment that combines digitally-augmented examination instruments with neural networks trained to analyze examination imagery across diverse patient populations and variable image qualities, enabling automated analysis and classification of eye conditions during routine clinical examinations.

A cognitive assessment system includes a computing device, a server coupled to the computing device, and an eye tracking device coupled to the computing device. The computing device includes a cognitive assessment program configured to perform at least one cognitive assessment task to assess cognitive function of a user. The server includes a database. The database stores historical performance data of the user, a historical performance model of the user, task performance data of a healthy population, and task performance data of a patient population. The eye tracking device is configured to capture eye movement information of the user.

This application relates to, inter alia, anti-cMET antibody drug conjugates ("ADCs") having lower target-specific binding at low versus physiologic pH ("pH-ADCs"), pharmaceutical compositions including the pH-ADCs, methods of making the pH-ADCs, methods of selecting specific patient populations for cancer treatment with an anti-cMET pH-ADC, and methods of using the pH-ADCs to treat cancers, including cMET+ / cMET-expressing or cMET-overexpressing cancers, particularly including cMET+ / cMET-expressing or cMET-overexpressing non-small cell lung cancers ("NSCLCs").

The application belongs to the field of biological medicine, and particularly relates to a pharmaceutical composition for treating inflammatory bowel disease and application of the pharmaceutical composition. The disclosed pharmaceutical composition comprises anti-TNF monoclonal antibody, phosphoketolase-producing bacteria or a pharmaceutically acceptable viable bacterial preparation or extract thereof. The application comprehensively utilizes multi-dimensional data analysis and experimental verification of'microbe-immune', and finds that the phosphoketolase-producing bacteria can regulate host immune metabolic microenvironment, actively stabilize blood drug concentration of the anti-TNF monoclonal antibody and reduce immunogenicity, so as to achieve the purposes of stabilizing blood drug concentration of the anti-TNF monoclonal antibody and delaying clearance, significantly improve clinical response rate and remission rate, and is particularly suitable for a patient population with primary non-response or secondary non-response to the anti-TNF monoclonal antibody, thereby providing an effective solution for solving this clinical difficulty.

The invention discloses an application of a T cell subset in improving the treatment effect of AK112. The T cell subset is XCL1 + CCL3 + CD8 + T cells. The invention relates to an application of a specific T cell subset in improving the curative effect of AK112, a T cell agonist and AK112 are combined for use, and by synergistically activating the T cell function and reversing the immunosuppression microenvironment, the single drug resistance of AK112 is effectively overcome, the continuous remission time is remarkably prolonged, the treatment response is deepened, the applicable patient group is expanded, and meanwhile, the toxicity risk is reduced. The invention further develops a full-spectrum flow cytometry kit containing 13 antibodies, 13 key markers of the T cell subgroup can be simultaneously detected by one tube, patients sensitive to evoximab treatment (i.e., high expression of the subgroup) can be efficiently screened out, and a convenient tool is provided for accurate medication.

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg of bupropion hydrochloride, or a molar equivalent amount of a free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg of dextromethorphan hydrobromide, or a molar equivalent amount of a free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

The invention relates to the field of immune assessment, in particular to an end-stage nephropathy dialysis patient immune assessment method, which comprises the following steps: preparing a database for storing assessment scores of various parameters; preparing a convolutional neural network, and collecting immune intensity change data before and after dialysis of a patient population as a training library; immune intensity change data before and after dialysis under experimental conditions are obtained under laboratory conditions, the data under the experimental conditions are input into a convolutional neural network, and the convolutional neural network is used for training according to a preset mixing proportion rule and outputting a dialysis cause compensation function; data such as demographic characteristics, basic diseases, representative immune activation state data, representative immune senescence state data and dialysis frequency of a patient are collected, a total score is calculated based on a database and a dialysis cause compensation function, and the immunocompetence of the patient is evaluated. By adopting the method, the immunocompetence fluctuation caused by imperfect biocompatibility of the dialysis membrane can be compensated in immune assessment.

This invention discloses a rapid implantation system for a multi-module integrated surgical kit for daytime breast augmentation, belonging to the field of medical device control and computer-aided surgery technology. The system receives confirmation commands from a patient population identifier via a graphical user interface. Based on this identifier, it matches the corresponding target-specific surgical kit from a pre-set specific surgical kit library. Then, based on the target-specific surgical kit and the patient population identifier, it matches an adaptive implantation strategy from an implantation strategy library. The system further generates a module call sequence containing multiple sub-tasks based on the adaptive implantation strategy. Each sub-task is associated with a functional module identifier and execution parameters. Control commands are sent to the corresponding target device in sequence to drive the device to execute the sub-tasks. This invention achieves rapid and precise implantation control of a multi-module integrated surgical kit through population-characteristic-driven specific surgical kit selection and adaptive implantation strategy configuration, improving the standardization and operational efficiency of daytime breast augmentation surgery.

A method for automatically abstracting and selecting an optimal set of variance-related functions that are an indicator of an individual outcome in healthcare, wherein the method comprises: generating, by one or more processors, an abstracted set of variance-related candidate-patient functions, wherein the abstracted set of variance-related candidate-patient functions are temporally heteroscedastic functions; optimizing, by one or more processors, each patient function from the abstracted set of variance-related candidate-patient functions by identifying a time period in which the variances and heteroscedasticity of each patient function are maximized, wherein this optimization produces an optimal abstracted set of variance-related patient functions from the time period in which the variances and heteroscedasticity of each patient function are maximized;by one or more processors comparing the optimal abstracted set of variance-related patient functions with a historical dataset for a patient population to create a predictive set of variance-related patient functions, wherein the predictive set of variance-related patient functions predicts a health-related target outcome of the patient population; by one or more processors generating a current optimal patient set of variance-related patient functions for a current patient; by one or more processors comparing the optimal set of variance-related patient functions for the patient population with the current optimal patient set of variance-related patient functions for the current patient;In response to the optimal set of variance-related patient functions for the patient population, which matches the current optimal patient set of variance-related patient functions for the current patient within a predefined limit, one or more processors determine whether the health-related target outcome matches a predefined health-related target outcome for the current patient; and in response to the health-related target outcome matching the predefined health-related outcome for the current patient, one or more processors issue an alert regarding the predefined health-related outcome for the current patient.

The present invention generally relates to pharmaceutical compositions, methods, and devices / systems for treating vascular diseases. More particularly, the present invention relates to medical methods, devices, and kits for delivering drugs to peripheral vascular tissue to treat neointimal growth. More specifically, the present invention described herein is intended to overcome the drawbacks of existing treatments for peripheral artery disease (PAD). The devices and methods of the present invention are for reducing one or more pathological conditions; reducing treatment complications in the treated patient population, reducing the target lesion revascularization (TLR) rate; and reducing the patient population that requires any type of leg amputation, particularly for patients with PAD associated with infrapopliteal (tibial) arteries, such as patients with clinical indications for treatment below the knee (e.g., claudication and / or critical limb ischemia (CLI)) for treatment below the knee, and patients with complex pathologies are specifically contemplated.

This disclosure relates to administration of a combination of: 1) about 100-110 mg, about 104-106 mg, or about 105 mg or less of bupropion hydrochloride, or a molar equivalent amount of the free base form or another salt form of bupropion; and 2) about 40-50 mg, about 44-46 mg, or about 45 mg or less of dextromethorphan hydrobromide, or a molar equivalent amount of the free base form or another salt form of dextromethorphan in certain patient populations, such as patients having moderate renal impairment, patients receiving a concomitant strong CYP2D6 inhibitor, patients who are known CYP2D6 poor metabolizers, those in need of an NMDA antagonist that does not cause dissociation, and those at risk of QT prolongation.

Disclosed herein are methods of administering thiostrepton with anti-cancer agents to treat cancers such as mesothelioma, lung cancer and ovarian cancer.