Abstract: A computer implemented method for determining a dosage of edoxaban for administering to a patient, the method comprising: receiving patient data relating to a patient, wherein the patient data includes a kidney function metric; processing the patient data with a dosage calculator to determine the dosage of edoxaban for administering to the patient, wherein the dosage calculator is derived from a plasma level prediction model; and indicating the dosage.

Abstract: A computer implemented method for determining a dosage of rivaroxaban for administering to a patient, the method comprising: receiving patient data relating to a patient, wherein the patient data includes a kidney function metric; processing the patient data with a dosage calculator to determine the dosage of rivaroxaban for administering to the patient, wherein the dosage calculator is derived from a plasma level prediction model; and indicating the dosage.

Abstract: A method for administering a dosage of Apixaban to a patient for the treatment or prevention of thrombosis, the method comprising: administering a dosage of Apixaban to the patient, wherein the dosage of apixaban is determined by: receiving patient data relating to a patient, wherein the patient data includes a kidney function metric of the patient; and processing, using one or more processors, the patient data with a dosage calculator to determine the dosage of Apixaban for the patient, wherein the dosage calculator is derived from a plasma level prediction model that predicts Apixaban drug plasma levels, and the dosage calculator determines the dosage for the patient based in part on the kidney function metric of the patient.

Abstract: A method for administering a dosage of Apixaban to a patient for the treatment or prevention of thrombosis, the method comprising: administering a dosage of Apixaban to the patient, wherein the dosage of apixaban is determined by: receiving patient data relating to a patient, wherein the patient data includes a kidney function metric of the patient; and processing, using one or more processors, the patient data with a dosage calculator to determine the dosage of Apixaban for the patient, wherein the dosage calculator is derived from a plasma level prediction model that predicts Apixaban drug plasma levels, and the dosage calculator determines the dosage for the patient based in part on the kidney function metric of the patient.

Abstract: A method for administering a dosage of Cagrisema to a patient for the treatment of obesity, the method comprising: administering a dosage of Cagrisema to the patient, wherein the dosage of Cagrisema is determined by: receiving patient data relating to a patient, wherein the patient data includes patient weight data; and processing the patient data including the patient weight data with a dosage calculator to determine the dosage of Cagrisema for administering to the patient wherein the dosage calculator is derived from a pharmacokinetic, PK, model.

Abstract: A computer implemented method for determining a dosage of semaglutide for administering to a patient for the treatment of obesity includes receiving patient data relating to a patient, wherein the patient data includes patient weight data; processing the patient data with a dosage calculator to determine the dosage of semaglutide for administering to the patient; and administering the dosage.

Abstract: A series of substituted imidazo[1,2-b][1,2,4]triazine derivatives of formula (I), being potent modulators of human IL-17 activity, are accordingly of benefit in the treatment and/or prevention of various human ailments, including inflammatory and autoimmune disorders.

Abstract: A method of generating a dosage calculator for determining a dosage of a drug for administering to a patient, the method comprising: receiving population data comprising real population data, and/or simulated population data calculated using a pharmacokinetic-pharmacodynamic, PKPD, model for the drug; and training a machine learning dosage calculator using the population data.

Abstract: The present Invention relates to a pellet comprising melatonin and methods of treating insomnia.

Abstract: The present Invention relates to a pellet comprising melatonin and methods of treating insomnia.

Abstract: A computer implemented method for supporting the treatment of insomnia with melatonin. The method includes receiving sleep data relating to a patient; determining a dosage time for the patient to take a dose of the melatonin based on the sleep data; and indicating the dosage time.

Abstract: A method for treating obesity in a patient, the method comprising administering a dose of a GLP1 agonist to the patient in a treatment regimen effective to manage the patient's satiety and thereby effect a reduction in the patient's weight; and, in conjunction with the administration of the dose of GLP1 agonist, engaging in a directed digital therapeutic program that manages patient weight loss and the treatment regimen for the GLP1 agonist with the objective of achieving a predetermined target weight for the patient, wherein the patient achieves the target weight.

Abstract: A compact, low-power, high image rejection sideband separation receiver is provided. The receiver observes an input radio frequency (RF) signal of multiple spectral lines (spectral observation), then downconverts the signals to intermediate frequency (IF), and then separates the signals to be observed simultaneously in multiple channels. An embodiment is used to observe a signal (G-band) with two spectral lines and utilizes a two stage Weaver architecture to downconvert the signal's frequency, including a combination of mixers in the second stage that achieves the separation of two different channels.

Abstract: The present disclosure relates to methods and systems suitable for use in identifying and providing personalised medicine to a patient. In some aspects, systems and method generate a co-therapy regimen for a patient suffering from a disease or condition. An identification of a co-therapy suitable to treat the disease or condition is received. A desired patient endpoint and a patient position are received, wherein the patient position is defined relative to the desired patient endpoint. A dataset relating to the patient is stored. The dataset comprises one or more patient data based on patient-related measurements. The dataset, the patient position and the desired patient endpoint are processed to generate a regimen for the co-therapy. The regimen is stored in a database.

Abstract: There is a dosage regimen for amlodipine for use in the treatment of hypertension.

Abstract: A compact, low-power, high image rejection sideband separation receiver is provided. The receiver observes an input radio frequency (RF) signal of multiple spectral lines (spectral observation), then downconverts the signals to intermediate frequency (IF), and then separates the signals to be observed simultaneously in multiple channels. An embodiment is used to observe a signal (G-band) with two spectral lines and utilizes a two stage Weaver architecture to downconvert the signal's frequency, including a combination of mixers in the second stage that achieves the separation of two different channels.

Abstract: A method of producing an intermediate program representation for an executable personalised medicine treatment program, comprising: providing a domain specific language environment comprising a personalised-medicine programming language syntax and a user interface; selecting a medical knowledge database for a medical condition; receiving user input to build, using the personalised-medicine programming language syntax and the medical knowledge database, a treatment package for implementing one or more treatment modalities for the medical condition, the treatment package including: treatment objectives defining terminating conditions of the one or more treatment modalities; safety guardrails for ensuring patient safety; and treatment titration definitions for modulating the one or more treatment modalities; and validating the treatment package to demonstrate that the treatment objectives, safety guardrails and treatment titration definitions will be satisfied during execution of the personalised medicine treatm

Abstract: The present disclosure relates to methods and systems suitable for use in identifying and providing personalised medicine to a patient. In some aspects, systems and method generate a co-therapy regimen for a patient suffering from a disease or condition. An identification of a co-therapy suitable to treat the disease or condition is received. A desired patient endpoint and a patient position are received, wherein the patient position is defined relative to the desired patient endpoint. A dataset relating to the patient is stored. The dataset comprises one or more patient data based on patient-related measurements. The dataset, the patient position and the desired patient endpoint are processed to generate a regimen for the co-therapy. The regimen is stored in a database.

Abstract: The present disclosure relates to monitoring patient compliance with a dosage regimen. In some aspects, a patient unique identifier, which enables a patient to be uniquely identified and associated with a patient record, is received. A message is received. The message includes a package unique identifier that enables a package that a drug administered to the patient was stored within to be uniquely identified. The message includes at least one pair of values, wherein each pair of values corresponds to an administration event and indicates an amount of the drug administered to the patient and a time of administration of the amount of the drug to the patient. The drug administered to the patient using the package unique identifier is identified. The identity of the drug and the at least one pair of values are stored against the patient record, which includes a dosage regimen associated with the patient.

Abstract: The present disclosure relates to methods and systems suitable for use in identifying and providing personalised medicine to a patient. In some aspects, systems and method generate a co-therapy regimen for a patient suffering from a disease or condition. An identification of a co-therapy suitable to treat the disease or condition is received. A desired patient endpoint and a patient position are received, wherein the patient position is defined relative to the desired patient endpoint. A dataset relating to the patient is stored. The dataset comprises one or more patient data based on patient-related measurements. The dataset, the patient position and the desired patient endpoint are processed to generate a regimen for the co-therapy. The regimen is stored in a database.