Resumen de: AU2026200109A1
There is disclosed a cap for an insulin pen comprising: one or more sensors adapted to detect a position of a plunger within an insulin pen; and a user interface comprising one or more user-selectable icons or buttons adapted to announce a meal or an intent to have a meal. have a meal. an a n h a v e a m e a l
Resumen de: EP4685812A2
Systems and methods are provided to provide guidance to a user regarding management of a physiologic condition such as diabetes. The determination may be based upon a patient glucose concentration level. The glucose concentration level may be provided to a stored model to determine a state. The guidance may be determined based at least in part on the determined state.
Resumen de: AU2024335431A1
The present disclosure describes lactate-responsive sensors, sensing systems incorporating a lactate-responsive sensor, and methods of use thereof that would be beneficial for continuously monitoring lactate levels and determining lactate thresholds (both aerobic and anaerobic thresholds). The present disclosure also relates to an analyte sensor for continuously detecting glucose and lactate levels.
Resumen de: AU2024280120A1
Blood glucose level measurement includes a light source configured to irradiate light to a subject; a monochrome part configured to separate wavelength components of the light that is reflected and scattered from the subject; a light receiver configured to receive the light transmitted via the monochrome part and to generate electrical signals based on the received light; and a processor configured to extract information on the blood glucose level of the subject based on a frequency shift of the light due to the Raman effect.
Resumen de: US20260022183A1
The present invention provides pharmaceutical formulations comprising a human antibody that specifically binds to human interleukin-4 receptor (hIL-4R). The formulations may contain, in addition to an anti-hIL-4R antibody, at least one amino acid, at least one sugar, or at least one non-ionic surfactant. The pharmaceutical formulations of the present invention exhibit a substantial degree of antibody stability after storage for several months.
Resumen de: US20260022182A1
The present invention provides pharmaceutical formulations comprising a human antibody that specifically binds to human interleukin-4 receptor (hIL-4R). The formulations may contain, in addition to an anti-hIL-4R antibody, at least one amino acid, at least one sugar, or at least one non-ionic surfactant. The pharmaceutical formulations of the present invention exhibit a substantial degree of antibody stability after storage for several months.
Resumen de: AU2024343861A1
A system includes an analyte measurement system and a software application operatively coupled to the analyte measurement system. The analyte measurement system is configured to measure a ketone level in the bodily fluid of a patient. The application is configured to display at least one of (1) a current ketone level and an indicator of a current ketone trend, (2) a ketone trend graph, and (3) a total amount of time that the ketone levels are above at least one predetermined threshold level. The application is also configured to determine if the current ketone level is above the at least one predetermined threshold level, and in response to determining that the current ketone level is above the at least one predetermined threshold level, output an alarm, wherein the alarm is outputted periodically while the current ketone level is above the at least one predetermined threshold level.
Resumen de: WO2025064417A1
Embodiments can relate to an insulin delivery controller which implements a processor configuration to efficiently attain an insulin delivery target. The insulin delivery controller can include a processor and a memory associated with the processor. The processor can process glucose data received from the memory, including a data representation of glycemic disturbance (d(t)). The processor can determine a glucose rate of change (G'(t)). The processor can generate a command signal to dynamically reshape a glycemic disturbance within a prediction horizon of the insulin delivery controller according to the G'(t). The processor can generate an insulin command signal for an insulin delivery unit to adjust an insulin delivery dosage amount and/or an insulin delivery dosage rate.
Resumen de: US20260021185A1
An improved local anesthetic solution with diminished bitter taste includes an anesthetic agent, an anesthetic solution vehicle, and a bitterness suppressant. The bitterness suppressant includes one or more compounds selected from the group consisting of: a sugar selected from the group consisting of monosaccharide sugars, disaccharide sugars, polysaccharide sugars, and combinations of the any of the foregoing; sweet-tasting compounds; acids; amino acids; salts; miscellaneous suppressant substances; and combinations of any of the foregoing. The improved local anesthetic solution optionally includes one or more additional agents selected from the group consisting of: buffering agents; vasoconstrictors; preservative compounds; stabilizers; contrast media agents; and combinations of any of the foregoing.
Resumen de: WO2026019913A1
In an embodiment, a method includes receiving analyte measurements of a patient for a time period. The method further includes providing, to a user, an interface for supplying contextual data indicative of contextual events for the time period and receiving the contextual data via the provided interface. The method further includes analyzing the analyte measurements and the contextual events to determine a condensed timeline of patient data for the time period, the condensed timeline of patient data including a partial subset of the contextual events. The method further includes presenting information related to the condensed timeline to the patient.
Resumen de: US20260020784A1
Simulating a user's metabolic system and predicting a blood glucose response based on a specified food intake event includes receiving characteristic data representative of specified user characteristics, converting said characteristic data into object data and utilising said object data and a master model to generate a personal digital model representative of said user's metabolic system, receiving food intake data representative of a said specified food intake event, obtaining or generating current glucose data for said user, inputting said food intake data to said personal digital model, and generating, using said personal digital model, a simulation of said user's metabolic system in response to said food intake data and generating a predicted blood glucose response to said specified food intake event, outputting data representative of said predicted blood glucose response, and utilising said data representative of said predicted blood glucose response to retrain said master model and said personal digital model.
Resumen de: US20260020785A1
The present disclosure relates to a continuous blood glucose measurement body attachment unit, and provides a continuous blood glucose measurement body attachment unit, which is manufactured in an assembled state in an applicator so as to minimize separate additional operations, such that the body attachment unit can be attached to the body with only a simple operation of the applicator and, particularly, the body attachment unit has a wireless communication chip so as to be capable of communicating with an external terminal, thereby enabling simple and convenient usage without an additional operation in which a separate transmitter must be connected and enabling maintenance to be more easily performed, and after the body attachment unit is attached to the body, an operation starts by the control of a user, such that an operation start time point can be adjusted to an appropriate time point according to the needs of the user, and an operation can start in a stabilized state, such that blood glucose can be more accurately measured.
Resumen de: US20260021256A1
One or more embodiments of the present disclosure may include an insulin delivery system that includes an insulin delivery device, a user interface that includes multiple user-selectable icons or buttons each representing different meal characteristics, memory to store one or more user-specific dosage parameter, and a processor in communication with the memory and adapted to receive blood glucose data. The processor may also be adapted to determine initial meal characteristics associated with each of the user-selectable icons or buttons based on at least one of the user-specific dosage parameters. The processor may also be adapted to update the meal characteristics associated with each of the user-selectable icons or buttons based upon the blood glucose data.
Resumen de: US20260020779A1
The present disclosure relates to a method for manufacturing an insertion guide needle for a continuous blood glucose monitoring device. The present disclosure provides a method for manufacturing an insertion guide needle for a continuous blood glucose monitoring device, by which: an insertion guide needle can be manufactured through a cutting process and a bending process of a needle raw plate, so that a complicated manufacturing process is unnecessary, and can thus be easily manufactured through a simple process; an enlargement incision part for continuous enlargement and incision, etc. can be conveniently manufactured through such a simple processing process, so that a manufacturing cost thereof can be reduced and also the size accuracy of the insertion guide needle can be improved; and, particularly, in a process of inserting the insertion guide needle into skin, the insertion guide needle can be brought into point contact with the skin to cut the skin, and then can continuously cut the skin in an enlarged manner, so as to minimize pains which may occur in the process of inserting the insertion guide needle into the skin, thereby alleviating the sense of repulsion or tension at the time of using the continuous blood glucose monitoring device.
Resumen de: US20260020780A1
Certain aspects of the present disclosure provide systems and techniques for rapid detection of repetitive metabolic events in a host based on measured analyte data provided by an analyte monitor worn by the host. An example system is configured to obtain measured glucose data of the host. A subset of the measured glucose data is determined, based on performing a filtering operation on the measured glucose data. A respective range of a likelihood of an occurrence of a metabolic is determined for each value within the subset of the measured glucose data. For at least one value within the subset of the measured glucose data, a state of the metabolic event is determined based in part on at least one of an upper bound or a lower bound of the respective range corresponding to the at least one value within the subset of the measured glucose data.
Resumen de: US20260023141A1
The system can include: an array of magnets. In variants, the system can function to generate a homogenous magnetic field within a sample (e.g., in the pulp of a finger). In an example, the system can be used for nuclear magnetic resonance (NMR) imaging and/or magnetic resonance imaging (MRI). In a specific example, the system can be used to measure blood analyte levels (e.g., glucose levels) within a sample.
Resumen de: US20260024646A1
Disclosed herein are techniques related to product consumption recommendations. In some embodiments, the techniques may involve obtaining, for a patient, historical data comprising activity data, food consumption data, and glucose data. The techniques may further involve training a machine learning model to: predict glucose response parameters for the patient using the historical data as a training set; and utilize the predicted glucose response parameters to determine a recommendation associated with consumption of a product by the patient to maintain a glucose level within a target range during an activity.
Resumen de: WO2024192362A1
Embodiments relate to a control module for storing and accessing insulin delivery parameters to accurately set an insulin dosage amount. The control module can include a processor and a memory having instructions stored thereon that when executed by the processor will cause the processor to: receive glucose data including glucose concentration measurements spanning a time period; identify a minimum glucose concentration measurement (Gmin) within the time period; identify a current glucose concentration measurement (Gc); set an upper bound constraint based on the Gmin and the Gc; generate an adapted insulin dosage schedule by imposing a maximum insulin dosage on an insulin dosage schedule based on the upper bound constraint; and either: administer an insulin dosage in accordance with the adapted insulin dosage schedule; or control administration of insulin via an insulin dosage signal based on the adapted insulin dosage schedule.
Resumen de: EP4681641A2
The present invention relates to a sensor applicator assembly for a continuous glucose monitoring system and provides a sensor applicator assembly for a continuous glucose monitoring system, which is manufactured with a sensor module assembled inside an applicator, thereby minimizing additional work by a user for attaching the sensor module to the body and allowing the sensor module to be attached to the body simply by operating the applicator, and thus can be used more conveniently. A battery is built in the sensor module and a separate transmitter is connected to the sensor module so as to receive power supply from the sensor module and be continuously used semi-permanently, thereby making the assembly economical. The sensor module and the applicator are used as disposables, thereby allowing accurate and safe use and convenient maintenance.
Resumen de: AU2025259998A1
Method, device and system for providing consistent and reliable glucose response information to physiological changes and/or activities is provided to improve glycemic control and health management. Method, device and system for providing consistent and reliable glucose response information to physiological changes and/or activities is provided to improve glycemic control and health management. ov o v
Resumen de: US20260018302A1
Present disclosure describes techniques for predicting diabetes risk in patients. The techniques include the step of monitoring a plurality of patient-specific characteristics comprising, at least one physiological parameter, one behavioral indicator, and one visual representation of the patient. The method further comprises extracting, using a first artificial intelligence (AI) model, a stress level of the patient based at least on behavioral indicators, historical lifestyle data, and sensor-derived physiological parameters. The method then include extracting, using a second AI model, a body mass index (BMI) or fat distribution patterns based at least on silhouette images and weight of the patient. The method finally includes predicting, using a third AI model, a blood sugar level or diabetes risk score of the patient based on outputs from the first and second AI models and the monitored characteristics.
Resumen de: US20260018305A1
Detection of anomalous computing environment behavior using glucose is described. An anomaly detection system receives glucose measurements and event records during a first time period. Missing events that are missing from the event records during the first time period are identified by processing the glucose measurements using an event engine simulator. An anomaly detection model is generated based on the missing events during the first time period. Subsequently, the anomaly detection system receives additional glucose measurements and additional event records during a second time period. Missing events that are missing from the additional event records during the second time period are identified by processing the additional glucose measurements using the event engine simulator. Anomalous behavior is detected if the identified missing events that are missing from the event records during the second time period are outside a predicted range of missing events of the anomaly detection model.
Resumen de: US20260014318A1
A processor-implemented method comprises obtaining measured glucose values of a person, fitting a physiological model to a portion of the measured glucose values within a time window after a start of a meal to determine meal-specific values of parameters of the physiological model that characterizes the person's glycemic response to the meal, and predicting a future blood glucose level of the person at a first time after the time window using the physiological model and the meal-specific values of the parameters of the physiological model. In one example, an alert or a notification can be sent to a user or an electronic device based on the predicted future blood glucose level of the person.
Resumen de: US20260013801A1
Methods for predicting glucose values which involve determining a predicction time window using historical data indicative of glucose level influencing events of a person having diabetes and at least one predicted glucose level influencing event. Further disclosed are data processing systems for predicting glucose values, medical servers, user devices, and computer programs.
Nº publicación: US20260013800A1 15/01/2026
Solicitante:
ROCHE DIABETES CARE INC [US]
INT BUSINESS MACHINES CORPORATION [US]
Roche Diabetes Care, Inc,
International Business Machines Corporation
Resumen de: US20260013800A1
A computer-implemented method and system for predicting and displaying glucose values, including receiving CGM data, determining, based on the data, a plurality of first predicted glucose values (33) for a first prediction time window (30), determining, based on the data, that a hypoglycemia event is predicted to occur during a second prediction time window (31) which has a contemporaneous beginning with the first prediction time window (30) but is shorter than the first window (30), and determining a plurality of second predicted glucose values (34) for the second prediction time window (31) and displaying the plurality of second predicted glucose values (34) for the second prediction time window (31) while not displaying predicted glucose values subsequent to the second prediction time window (31).