154 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 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 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 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 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.

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.

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.

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 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.

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.

Provided are methods of treating subjects in need of an anti-fibroblast growth factor receptor 4 (anti-FGFR4) therapy. The methods comprise administering to the subjects a therapeutically effective amount of a peroxisome proliferator-activated receptor (PPAR) alpha agonist in combination with the anti-FGFR4 therapy. The methods can comprise administering to the subject a therapeutically effective amount of PPAR alpha agonist and a bile acid sequestrant. Also provided are compositions comprising an FGFR4 inhibitor, a PPAR alpha agonist, and, optionally, a bile acid sequestrant. The methods attenuate the dysregulation of bile acid biosynthesis caused by FGFR4 inhibition with anti-FGFR4 therapies. The methods reduce the severity and / or incidence of adverse events associated with anti-FGFR4 therapies.

A device may establish communication between the plurality of intelligent injection devices and an artificial intelligence-powered clinical research platform configured to manage a clinical trial or research program. A device may analyze, via the artificial intelligence platform, clinical trial protocol requirements including study design parameters, randomization schemes, blinding protocols, and adverse event monitoring requirements to generate coordinated medication administration strategies across the plurality of intelligent injection devices. A device may apply research protocol constraints to restrict medication selection, dosage calculations, administration timing, and patient assignment across the plurality of intelligent injection devices. A device may generate real-time coordination instructions through the artificial intelligence platform including synchronized administration timing across multiple sites, dosage verification protocols for different treatment arms, and compliance monitoring procedures tailored to specific research protocol requirements.

The invention relates to the technical field of biology, and provides a predictive biomarker for treating adverse reactions of tumor patients by using CCL5 as an immune checkpoint inhibitor and application of the predictive biomarker, and the predictive biomarker is the dynamic change of the CCL5 relative to a baseline proportion. The detection kit is used for detecting the proportion of CCL5. The dynamic change refers to the change of the CCL5 proportion before and after the immune checkpoint inhibitor is used; if the dynamic change is greater than or equal to 50% or continuously increased, the immune checkpoint inhibitor causes adverse reaction when treating the tumor patient. According to the method, high-risk patients can be identified through peripheral blood detection before irAEs have obvious clinical manifestations, so that a basis for advanced intervention is provided for clinicians, and the occurrence probability of serious adverse events is reduced.

A treatment for patients having cancer expressing Prostate Cancer Specific Membrane Antigen (PSMA) is disclosed. Said treatment involves the use of an 225Ac-radioconjugate, in particular 225Ac-PSMA-I&T. A dosage regimen that entails more frequent administration of the 225Ac-radioconjugate at lower dose level may be employed. This involves the use of a dosage of 50-75 kBq / kg of body weight on a dosing schedule of every 4-6 weeks. A flat dosing may also be employed where the dose does not depend on the body weight of the subject. Such dosing improve the benefit / risk profile with fewer adverse events and less discontinuations, dosing interruptions and reductions in dose. Of particular importance is a reduction in salivary gland toxicity and xerostomia.

This invention discloses a dynamic prediction system for long-term adverse cardiovascular event risk after stent implantation, belonging to the field of personal health risk assessment technology. It includes: a cardiovascular assessment module for determining the target cardiovascular adverse event presentation coefficient based on the target patient's first chest pain rating and real-time heart rate after stent implantation; a cardiac function assessment module for determining the emphasis of cardiac function analysis at each stage based on the target patient's physical examination data after stent implantation; a probability determination module for determining the probability of the first adverse event based on the target cardiovascular adverse event presentation coefficient and the emphasis of each cardiac function analysis; and an indicator determination module for comparing the target patient's first adverse event probability with the second adverse event probability of each monitored patient to obtain the target cardiovascular risk warning indicator for the target patient. This invention can improve the accuracy of long-term risk prediction for adverse cardiovascular events.

The invention belongs to the technical field of chemical drugs, and particularly relates to application of a traditional Chinese medicine composition in preparation of drugs for treating recurrent clostridium difficile infection.The traditional Chinese medicine composition is prepared from 10-50 g of fresh ginger, 3-20 g of honey-fried licorice roots, 5-30 g of ginseng, 3-20 g of dried ginger, 3-30 g of scutellaria baicalensis, 3-30 g of pinellia ternate, 3-15 g of coptis chinensis and 10-30 g of Chinese dates. The traditional Chinese medicine composition is excellent in clinical effect, and in sample research on high-risk crowds such as old people and immunosuppression CDI relapse patients, the treatment scheme of the vancomycin combined with the ginger heart-fire purging decoction is remarkably superior to vancomycin single-drug treatment in the aspect of continuous clinical response rate at the main curative effect end point. This benefit is achieved mainly by reducing the recurrence rate of CDI by more than 60%. The combined scheme shows a robust curative effect in key subgroups such as the elderly and immunosuppressive subgroups, is good in safety, does not increase extra adverse event risks, and particularly does not observe renal function impairment.

The present invention relates to oral compositions comprising cabozantinib salts and at least one pharmaceutically acceptable excipient and methods of using the oral compositions to increase the oral bioavailability of the cabozantinib and reduce the adverse events associate with the oral administration of cabozantinib. The invention also relates to methods for preparing cabozantinib lauryl sulfate salts.

The invention discloses an evaluation method for predicting the safety of EGFR TKIs (epidermal growth factor receptor TKIs) single-drug treatment on NSCLC (non-small cell carcinoma). The method comprises the following steps: acquiring data of a plurality of patients receiving EGFR TKIs treatment; the method comprises the following steps of: constructing a safety assessment final model by taking MDRAE (Maximum Grade Of Related Adverse Event) as a safety index, the final model is an ordered logic regression model, and the covariables of the final model comprise normalized steady-state valley concentration, EGFR TKIs treatment history, gender, baseline glutamyltransferase, baseline uric acid, baseline creatine kinase, baseline platelet and baseline lymphocyte; obtaining target patient data, and inputting each covariable value in the target patient data into the final model; and according to the final model, determining a first probability that the MDRAE of the target patient is at a level 3 or above, a second probability that the MDRAE is at a level 2, and a third probability that the MDRAE is at a level 1 or below, and taking a level corresponding to a maximum probability value in the three probabilities as an MDRAE prediction level of the target patient. According to the invention, the accuracy of predicting the safety of EGFR TKIs single-drug treatment on NSCLC is improved.

The present invention relates to methods of reducing occurrence or severity of dermatologic adverse events (DAEs) in a subject treated with an anti-epidermal growth factor receptor (EGFR) / hepatocyte growth factor receptor (c-Met) antibody and EGFR tyrosine kinase inhibitor, comprising (a) administering an antibiotic(s); (b) administering an antiseptic(s); and (c) administering a non-comedogenic moisturizer to the subject.

Described herein are techniques for predicting whether a subject will experience an immune-related adverse event (irAE) in response to administration of an immune checkpoint inhibitor (ICI) therapy. In some embodiments, the techniques include: determining a likelihood that the subject will experience the irAE in response to administration of the ICI therapy, the determining comprising: performing: (a) processing clinical data using a first machine learning (ML) model to output a first likelihood that the subject will experience the irAE, (b) processing RNA sequencing data using a second ML model to output a second likelihood that the subject will experience the irAE, and / or (c) processing immune receptor data using a third ML model to output a third likelihood that the subject will experience the irAE; and processing the first, second, and / or third likelihoods using a fourth ML model trained to predict the likelihood that the subject will experience the irAE.

The embodiment of the invention provides a clinical test data management system and method, and the system comprises an adverse event confirmation unit which is suitable for obtaining clinical test data, and when it is determined that an event corresponding to the clinical test data is consistent with a preset adverse event, determining that the event is consistent with the preset adverse event; taking events corresponding to the clinical test data as adverse events; the adverse event classification unit is suitable for classifying the adverse events corresponding to the clinical test data according to the types of the adverse events; the adverse event evaluation unit is suitable for evaluating each adverse event according to a preset evaluation standard and determining the priority of each adverse event; an adverse event recording unit; an adverse event generation unit; an adverse event analysis unit; an adverse event association unit; and an adverse event management unit. By the adoption of the technical scheme, adverse events occurring in the clinical test process can be monitored and managed, the adverse events are processed, and the safety of the clinical test is improved.

The disclosure is based, at least in part, on the discovery that if you treat recurrent or metastatic adenoid cystic carcinoma “RIM ACC”, in a subject who has one or more measurable ACC tumors / lesions that have increased in number and / or have increased in a dimension and / or volume by 20% or more prior to treatment, and / or who has an appearance of one or more new ACC tumors / lesions prior to treatment (also referred to herein as “severe RIM ACC”), by administering a high starting daily dosage (i.e., greater than 500 mg and up to about 1 000 mg), e.g., a starting dosage of about 700 mg, of rivoceranib or a pharmaceutically acceptable salt thereof, the severe RIM ACC in the subject improves with acceptable adverse events.