286 results about "AdverseEvent" patented technology

Disclosed herein are methods and compositions for preventing or reducing adverse events associated with administration of a RAS(ON) inhibitors. Thus, disclosed are compositions and methods for treating or preventing RAS(ON) inhibitor therapy-associated rash or mucositis. The methods involve administering a compound that binds to cyclophilin A (CypA) to compete with a RAS(ON) inhibitor for CypA binding, thereby reducing tri-complex formation in non-tumor tissues. These approaches may improve the tolerability of RAS(ON) inhibitor therapies without compromising efficacy.

The disclosure relates to the use of phosphodiesterase 1 (PDE1) inhibitors for the treatment of cancers and tumors, including for inhibiting tumor recruitment of macrophages and other cells to the tumor or cancer, for complementing and enhancing checkpoint inhibitor therapies, and for mitigating the side effects (i.e., inflammatory-related adverse events) associated with checkpoint inhibitor therapies.

The present invention provides CD40 agonist antibodies having significantly higher CD40 activating activity in the presence of simultaneous tumor associated antigen (TAA) binding than in the absence of such simultaneous binding. Such TAA-dependent CD40 agonism results in a significant increase in therapeutic index, reducing or completely eliminating adverse events that are typically associated with CD40 activation, such as cytokine release syndrome or hepatotoxicity. Also provided are bispecific and multispecific antibodies and polypeptides such as 5T4 / CD40, such as chimeric antigen receptors, which are optionally incorporated into the antibodies with anti-TAA units. Methods of using these antibodies or polypeptides to treat and diagnose diseases, such as cancer, are also provided.

The invention provides a risk detection method and system for adverse events of a drug clinical test. The method comprises the following steps: constructing a clinical biological model according to a body health state, body parameters and a historical examination report of a subject; recording the trial information accepted by the subject, and generating a trial database; according to the physiological monitoring equipment and the health monitoring system, body function parameters and biological indexes of the subject after drug testing are monitored in real time, and drug testing data are obtained; screening and optimizing the drug test data based on a genetic algorithm to obtain drug test reaction characteristics; determining a risk score according to the reagent database and the reagent reaction characteristics; and dividing different risk levels according to the risk scores, and carrying out risk early warning according to the risk levels. According to the method, through screening of the drug reaction characteristics and calculation of the risk score, the monitoring efficiency of adverse events is improved, the data analysis capability is enhanced, and the scientificity and accuracy of the result are ensured.

The invention discloses an application of nitro fatty acid in preparation of a product for predicting, preventing and improving adverse cardiovascular events of patients with acute coronary syndrome. The invention provides application of nitro fatty acid in preparation of products for preventing and improving adverse cardiovascular events of ACS patients. According to the application, for the ACS patient, when the concentration of the 12-nitro conjugated linoleic acid in the body is larger than 0.196 ng / ml and the concentration of the 9-nitro conjugated linoleic acid is larger than 0.296 ng / ml, it is judged that the risk that the ACS patient is re-hospitalized and dead due to non-fatal myocardial infarction / unstable angina pectoris / blood supply reconstruction is low. By detecting the content of nitro fatty acid in a biological sample and supplementing nitro fatty acid, the occurrence rate of adverse events can be greatly reduced. Meanwhile, the invention further provides a detection method of nitro fatty acid, and the accuracy of biological sample detection is improved.

The present disclosure is generally related to methods of reducing the frequency and / or severity of adverse events in subjects undergoing checkpoint inhibitor immunotherapy using natural killer (NK) cells.

The subject matter described here relates to anti-PD-1 x anti-IL-25 bispecific antibodies. In certain embodiments the bispecific antibody is used for the treatment or prevention of cancer. In certain embodiments the bispecific antibody is used for the treatment or prevention of breast cancer. In some embodiments, the bispecific antibody limits immune related adverse events.

A method for determining and indicating expectedness of a first adverse event. The method includes receiving adverse event data associated with the first adverse event. The method further includes receiving request to generate a section of an electronic aggregate report. The request includes an aggregate report type, a reporting period start date, and the reporting period end date. The method includes determining and receiving an electronic reference document including a defined adverse reaction. The defined adverse reaction includes an active start date. The method further includes determining an expectedness cut-off date and the expectedness of the first adverse event. The method further includes generating the section of the electronic aggregate report and indicating the first adverse event is unexpected in the section of the electronic aggregate report.

The invention discloses application of NETs in treatment of postoperative adverse events and prognosis evaluation in an aortic dissection cavity, and belongs to the technical field of biological medicine. The invention finds that the composition protein CitH3 of NETs is closely related to poor aortic remodeling of the aortic dissection, is an independent risk factor of AAEs after intracavitary treatment of a patient with the aortic dissection, and can be used as a key marker for prognosis evaluation of the aortic dissection. Therefore, the invention provides an application of a biomarker such as CitH3 and the like in risk assessment of adverse events occurring after treatment in the aortic dissection cavity. The peripheral circulation NETs marker CitH3 provided by the invention provides an accurate, effective, simple, convenient and easy-to-popularize quantitative index and risk stratification method for the assessment of the overall prognosis of interlayer intracavity treatment.

The invention provides a method and equipment for analyzing adverse event information of a clinical test. The method comprises the following steps: acquiring audio information of a target object; outputting a corresponding pinyin sequence based on the audio information by using a pre-trained speech recognition model; performing text prediction on the pinyin sequence to obtain an output text; in response to the fact that the knowledge-enhanced large language model is utilized to determine that an adverse event exists in the output text, key information in the output text is extracted; performing named entity identification based on the key information to obtain name information, time information and degree information in the key information; and constructing adverse event information based on the name information, the time information and the degree information. By implementing the method and the device, the analysis processing can be automatically performed according to the description of the target object to obtain the corresponding adverse event information, compared with manual processing, the speed is higher, the method and the device are not interfered by clinical environments or other factors, and analysis tasks can be efficiently completed in batches.

The invention discloses a medical quality safety management system, and belongs to the field of medical management. The medical quality safety management system comprises an adverse event management module which is used for front-line medical personnel to input adverse events and a manager to read the beginning and the end of the adverse events in real time; the data summarization and analysis module is used for reading the indexes in the events recorded by the adverse event management module, respectively counting the indexes to form a form, and analyzing and calculating the incentive proportion of the adverse events by using a K-means clustering analysis algorithm; and the data statistics module is used for generating an adverse event analysis report by utilizing a CART model according to an analysis result of the data summarization analysis module. According to the technical scheme, the medical staff can input the adverse events by logging in the account number, the manager can read the beginning and the end of the adverse events in real time by logging in the account number, analysis is carried out through the clustering analysis algorithm and the CART model, the report is generated, and therefore the workload of the medical staff is relieved.

The invention provides a drug adverse event recognition method, system and device based on a large language model and a medium, and relates to the technical field of drug adverse event recognition. Determining a prompt text for performing an adverse event recognition task on the to-be-recognized medical record text based on the background knowledge; inputting the prompt text into the reasoning large language model, and performing structured processing and screening processing on an output result to obtain a plurality of candidate triads and explanation texts; and judging the candidate triple by adopting a fine-tuning large language model, explaining fact consistency between the text and the to-be-identified medical record text, and determining an adverse event identification result. The robustness and consistency of output results are effectively improved by screening a plurality of triples output by the reasoning large language model. And the consistency between the to-be-identified medical record text and the candidate triple is judged by adopting the fine tuning large language model, so that the accuracy, the credibility and the interpretability of the adverse event identification result are improved.

The invention discloses a health care device which is used for transmitting low-frequency waves to a spine or a navel so as to increase the number of endothelial precursor cells (EPC) and reduce the number of circulating endothelial cells (CEC), so that the risk of cardiovascular related adverse events can be reduced. The health care device comprises a box body, and a power supply, a speed controller, a rotating mechanism, a connecting rod mechanism, a knocker and a conical table which are arranged in the box body. The power supply is electrically connected with the speed controller so as to output electric power to the speed controller. The speed controller is electrically connected with the rotating mechanism and controls the rotating mechanism to rotate at a preset speed. The rotating mechanism is connected with the knocker through the connecting rod mechanism so as to drive the knocker to knock a plane of the conical table, and the knocker generates a low-frequency wave with a preset frequency. The invention also provides the health care device which can be used for transmitting low-frequency waves to the spine or navel.

A method for version control of a case dataset includes receiving adverse event data and determining case data based on the adverse event data. The method further includes generating the case dataset including the case data and first version data. The method further includes receiving and classifying first supplemental adverse event data and classifying. The first supplemental adverse event data is classified as at least one of: a first classification or a second classification. The method further includes receiving second supplemental adverse event data and classifying the second supplemental adverse event data. The second supplemental adverse event data is classified as at least one of: the first classification or the second classification. The method further includes determining supplemental case data based on the second supplemental adverse event data. The method further includes generating second version data. The method further includes generating and outputting a supplemental case dataset.

The invention relates to the field of data processing, in particular to a drug safety signal mining method and system based on multi-source data. The method comprises the following steps: firstly, constructing a longitudinal event sequence containing medication and diagnosis events for each patient; calculating a time sequence correlation factor of medication and subsequent adverse events, wherein the time sequence correlation factor is in negative correlation with the time interval of the two events and the number of hybrid diagnosis events in the interval; meanwhile, based on the matching degree of the event time interval and the known incubation period probability distribution, obtaining an incubation period rationality weight; combining the drug dosage, the time sequence correlation factor and the reasonable weight of the incubation period, accumulating the related drug event influence before the occurrence of the adverse event, and calculating the accumulated correlation energy of the specific drug and the adverse event; and finally, carrying out non-proportional analysis on the accumulated associated energy of the patient group, realizing drug safety signal mining, and improving the accuracy and reliability of signal identification.

Methods comprising an integrated, multiscale artificial intelligence-based system that reconstructs drug-specific pharmacogenomic networks and their constituent functional sub-networks are described. The system uses features of the functional topology of the three-dimensional architecture of drug-modulated spatial contacts in chromatin space. Discovery of a drug pharmacogenomic network is made through the selection of candidate SNPs by imputation, determination of the predicted causality of the SNPs using machine learning and deep learning, use of the causal SNPs to probe the spatial genome as determined by chromosome conformation capture analysis, combining targeted genes controlled by the same cell and tissue-specific enhancers, and reconstruction of the pharmacogenomic network using diverse data sources and metrics based on the results of genome-wide association studies. Knowledge-based segmentation methods are used to deconstruct the pharmacogenomic network into its constituent efficacy and adverse event sub-networks for applications in clinical decision support, drug re-purposing, and in silico drug discovery.

The invention discloses an application of an Ackermania muciniphila composition in preparation of a drug for treating Wilson's disease, and relates to the technical field of biological medicines, and the key points of the technical scheme are as follows: Ackermania muciniphila can regulate intestinal flora and micro-ecological environment of WD patients, improve copper expelling and reduce the biological activity and availability of copper absorption drugs, and can be used for preparing a drug for treating Wilson's disease. The drug toxicity is reduced, and adverse events are reduced; therefore, the effects of removing copper, reducing copper absorption medicine and reducing copper accumulation in the body of a WD patient are enhanced. The Ackermania muciniphila can be Ackermania muciniphila viable bacteria, Ackermania muciniphila thermal inactivation thalli or fragments thereof, culture supernatant freeze-dried powder and a composition of the Ackermania muciniphila viable bacteria, the Ackermania muciniphila thermal inactivation thalli or the fragments thereof and the culture supernatant freeze-dried powder. The copper accumulation level in the body of a WD patient is reduced from multiple dimensions, the clinical WD treatment efficiency is improved, meanwhile, the steady-state time of copper in the body of the patient is prolonged, and adverse drug events are reduced.

The invention discloses an intraoperative patient dynamic adverse event real-time early warning system and method, and relates to the technical field of intelligent diagnosis and treatment data processing, and the real-time early warning system comprises an intraoperative data unified preprocessing module which is used for preprocessing clinical variables and outputting structured triples; the variable structure modeling module is used for carrying out feature extraction, and the variable graph feature sequence output time sequence modeling module is used for modeling dynamic information of historical and future contexts at the same time and outputting a context feature sequence H = {ht}; the feature fusion and risk prediction module is used for fusing gt and ht. The risk score sequence prediction interpretability module for outputting continuous time steps is used for carrying out feature attribution analysis on prediction output. The dynamic adverse event real-time early warning system and method are innovative in structure, accurate in prediction, high in interpretability and suitable for deployment, can adapt to complex data characteristics in an operation, and have high real-time performance, high robustness and clinical interpretability.

Described here are methods to utilize genomic and epigenomic detection platforms to provide quantitative metrics, including those representative of molecular phenotypes, in a variety of iimmuno-oncology applications, including those related to the characterization of patient responsiveness, treatment efficacy, adverse events among otheres. In various embodiments, described herein is an example of generating prognostic and t outcomes of a cfDNA-derived promoter methylation score in predicting ICI benefit.

A composition comprising neratinib, or a pharmaceutically acceptable salt thereof, and hydroxypropyl-β-cyclodextrin, a method for preparing same, and use thereof. Study results show that the composition can not only significantly improve the bioavailability of the active ingredient, but also eliminate food effects and adverse event diarrhea.

The application discloses an evaluation method for predicting the safety of EGFR TKIs monotherapy for NSCLC. The method comprises the following steps: obtaining the data of a plurality of patients receiving EGFR TKIs treatment; taking MDRAE (maximum grade of drug-related adverse event) as a safety index, constructing a safety evaluation final model, and the final model is an ordered logistic regression model, the covariates of the final model include normalized steady-state trough concentration, EGFR TKIs treatment history, gender, baseline glutamyltransferase, baseline uric acid, baseline creatine kinase, baseline platelets and baseline lymphocytes; obtaining the data of a target patient, inputting the numerical values of each covariate in the data of the target patient into the final model; determining the first probability of MDRAE of the target patient being grade 3 and above, the second probability of MDRAE being grade 2 and the third probability of MDRAE being grade 1 and below according to the final model, and taking the grade corresponding to the maximum probability in the three probabilities as the predicted grade of MDRAE of the target patient. The application improves the accuracy of predicting the safety of EGFR TKIs monotherapy for NSCLC.

Methods for inducing anti-phosphorylated Tau antibodies without inducing a serious adverse event in humans are described. The methods include administering to the subject an effective amount of a composition containing a Tau phosphopeptide conjugated to an immunogenic carrier.

Provided is a process including: accessing clinical trial data of an ongoing clinical trial that is not yet complete, the clinical trial having a plurality of treatment groups and a plurality of patients in the treatment groups; detecting, with an anomaly detection model, an anomaly in the clinical trial data for a first patient, the anomaly corresponding to a first patient among the plurality of patients; in response to detecting the anomaly classifying the first patient as anomalous in the trial; generating, with the computer system, by an artificial intelligence model, a candidate explanation for the detected anomaly by designating data in a record for the first patient as potentially correlated with the anomaly; and causing the anomaly and the candidate explanation to be presented to a data safety monitoring board (“DSMB”) of the clinical trial.

The present disclosure relates to methods of treating a disease or disorder (e.g., cancer) with an mTOR inhibitor. In particular, the present disclosure relates to methods of treating a subject having cancer by administering specific doses of an mTOR inhibitor. In some embodiments, the present disclosure includes methods for delaying, preventing, or treating acquired resistance to a RAS inhibitor using a dose of an mTOR inhibitor. In some embodiments, the present disclosure relates to methods of using tacrolimus to treat or prevent adverse events associated with the administration of an mTOR inhibitor.

The present disclosure generally relates to compositions and methods for predicting or diagnosing immune-related adverse events (irAE) before, during, or after immune checkpoint inhibitor (ICI) treatment in a subject with cancer. The method includes assessment of immune cell types, cytokines, autoantibodies or any combination thereof.

A method for reducing adverse events associated with administering ecopipam, the method comprising dosing according to a specific weight range and an associated dose escalation regimen, and a further downward dosing regimen for discontinuation of ecopipam.

To provide methods of inducing formation of liver organoids from precursor cells, such as iPSC cells, which can be used for screening for a serious adverse event (SAE), such as liver failure and / or drug induced liver injury (DILI), and / or drug toxicity.SOLUTION: This method comprises the steps of a) contacting definitive endoderm (DE) derived from iPSC cells with a FGF pathway activator and a GSK3 inhibitor, for a period of time sufficient to form posterior foregut spheroids, and b) incubating the posterior foregut spheroids obtained in the step a in the presence of retinoic acid (RA) for a period of time sufficient to form the liver organoid.SELECTED DRAWING: Figure 1

An example system includes an implantable medical device configured to obtain measurement values of one or more patient metrics; and processing circuitry configured to: determine a baseline value for each of the respective one or more patient metrics based on measurement values of the one or more patient metrics over a first period of time; determine a short-term value for each of the one or more patient metrics based on measurement values of the one or more patient metrics over a second period of time, determine a difference between each of the short-term values and the respective baseline value for each of the one or more patient metrics; determine that a risk of an adverse event occurring in the patient is high in response to the determined difference meeting a respective adverse event risk threshold; and generate for output an adverse event high risk alert.

The present invention relates to pharmaceutical compositions and methods for treating ischemic stroke in humans, using a tetrafluorobenzyl derivative of formula (I) or a pharmaceutically acceptable salt thereof conjointly with a thrombolytic drug, endovascular thrombectomy, or both (e.g., endovascular thrombectomy and a thrombolytic drug). Administration of a tetrafluorobenzyl derivative of formula (I) or its pharmaceutically acceptable salt can reduce reperfusion injury and other adverse events in patients conjointly receiving a thrombolytic drug, endovascular thrombectomy, or endovascular thrombectomy with a thrombolytic drug.