534 results about "Dosing regimen" patented technology

The invention relates to the technical field of tumor treatment, in particular to an intelligent decision-making system for tumor precise targeted medication based on individual mutation information, which comprises a data processing layer, a variation annotation and function prediction layer, a knowledge base integration layer and a scheme decision-making engine and report visualization module. According to the intelligent decision-making system for tumor precise targeted medication based on individual mutation information, a rule engine and a prediction model are combined, dynamic priority ranking is output, multi-model fusion decision making is achieved, and clinical scene deep adaptation is achieved by predicting primary and secondary drug resistance, calculating liver and kidney function adjusting dosage and generating a combined medication time sequence scheme; through an individualized drug delivery scheme, combination drug use optimization is achieved, a visual clinical report is generated, clinical executable operation is further strengthened, and through algorithm quantification, a dynamic knowledge graph, AI auxiliary decision making and a clinical operation closed loop, the next-generation technical research direction of a tumor precise drug use system can be represented.

The present invention provides a method for increasing glycemic control in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. The present invention provides a method for improving weight management in a patient in need thereof, by administering tirzepatide, or a pharmaceutically acceptable salt thereof. Further providing a method for treating a condition selected from atherosclerosis, chronic kidney disease, NAFLD, and NASH. Further provided is a method to prevent or induce remission of diabetes comprising administration of tirzepatide, or a pharmaceutically acceptable salt thereof. Further provided is a dosing regimen for increasing glycemic control, improving weight management, and / or treating dyslipidemia.

The present disclosure provides methods and dosing regimens for the treatment of depression (e.g., treatment resistant depression) with a mucoadhesive composition comprising N, N-dimethyltryptamine (DMT) or a pharmaceutically acceptable salt thereof.

The invention provides a drug screening and curative effect evaluation method and system based on a glioma organ-like model, and relates to the technical field of biological material analys.The method includes the steps that a three-dimensional fluorescence image of the glioma organ-like model is collected, signal intensity analysis and compensation processing are carried out, a growth feature mapping model is constructed, and the three-dimensional fluorescence image of the glioma organ-like model is obtained; and phenotypic characteristics for representing the glioma organoid heterogeneity are obtained. Inputting the phenotypic characteristics into a drug response evaluation network, and calculating a drug sensitivity score; the drug molecular feature library and the drug collaborative analysis model are combined, the synergistic interaction index of different drug combinations is calculated, the optimal drug combination is screened, the drug administration dosage and the drug administration time sequence are determined in combination with phenotypic features, and finally an individualized treatment scheme is generated. According to the invention, the curative effect of the drug on the glioma organs can be effectively evaluated, and the optimal drug combination and administration scheme can be screened out, so that the accuracy and effectiveness of glioma treatment are improved.

Provided herein is, among other things, is a method of treating cancer using an improved intermittent dosing regimen for Azenosertib, or a pharmaceutically acceptable salt thereof, administration to achieve a highly efficacious, safe and tolerable dosing regimen to treat many different types of cancers. In one aspect, the method of treating cancer comprises administering a daily dose of Azenosertib, or a pharmaceutically acceptable salt thereof, (e.g., greater than about 350 mg) in accordance with an improved intermittent dosing cycle, wherein the intermittent dosing cycle comprises one or more dosing weeks with each dosing week comprising between about 2-7 consecutive dosing days and between about 1-7 days without dosing. In some embodiments, the intermittent dosing cycle is repeated wherein the dosing weeks are separated by a break of one, two or more weeks. In some aspects, Azenosertib, or a pharmaceutically acceptable salt thereof, is administered as a combination therapy.

Methods of expanding tumor infiltrating lymphocytes (TILs) using a tumor necrosis factor receptor superfamily (TNFRSF) agonist, such as a 4-1BB agonist, a CD27 agonist, a glucocorticoid-induced TNF receptor-related agonist, an OX40 agonist, a HVEM agonist, or a CD95 agonist, and uses of such expanded TILs in the treatment of diseases such as cancer are disclosed herein. In addition, in some embodiments, therapeutic combinations of TILs and TNFRSF agonists useful in the treatment of diseases such as cancer, including compositions, uses, and dosing regimens thereof, are disclosed herein.

The invention discloses an anesthesia depth accurate prediction system and method based on time sequence alignment. The method comprises the steps that a cross-modal joint time sequence characteristic data matrix is acquired and generated; outputting a time sequence alignment feature sample; outputting a future advanced prediction label set; obtaining a first-stage anesthesia depth prediction model; in the first anesthesia depth prediction model training stage, a logic auditing link is introduced, and a self-adaptive online updating model is formed; starting an anti-fact dose simulation module, and outputting a candidate anti-fact administration scheme set; and inputting the candidate anti-factual administration scheme set into a dynamic security constraint optimizer, rejecting non-compliant schemes by the dynamic security constraint optimizer according to single maximum dose limitation, single additional dose and administration times in a minimum administration interval, and outputting an optimal administration suggestion. According to the method, combined classification judgment is carried out on the anesthesia state grade and the change trend of each prediction step, and the sensitivity of clinical risk identification and abnormal situation early warning is effectively improved.

Antibody formulations are described comprising a mixture of a non-reducing sugar, an anti-α4β7 antibody and at least one amino acid. The disclosed formulations have improved stability, reduced aggregate formation, and may retard degradation of the anti-α4β7 antibody therein or exhibit any combinations thereof. The present invention further provides a safe dosing regimen of these antibody formulations that is easy to follow, and which results in a therapeutically effective amount of the anti-α4β7 antibody in vivo.

The present invention relates to the treatment of subjects having CD20-positive cell proliferative disorders (e.g., B cell proliferative disorders, such as non-Hodgkin's lymphomas). More specifically, the invention pertains to the treatment of subjects having a B cell proliferative disorder by intravenous administration of an anti-CD20 / anti-CD3 bispecific antibody (e.g., mosunetuzumab).

Antibody formulations are described comprising a mixture of a non-reducing sugar, an anti-α4β7 antibody and at least one amino acid. The disclosed formulations have improved stability, reduced aggregate formation, and may retard degradation of the anti-α4β7 antibody therein or exhibit any combinations thereof. The present invention further provides a safe dosing regimen of these antibody formulations that is easy to follow, and which results in a therapeutically effective amount of the anti-α4β7 antibody in vivo.

A conversational AI platform for managing remote and hybrid clinical trials for investigational medical interventions. Embodiments of the present disclosure comprise a conversational AI model and an algorithmic logic engine configured to define and implement protocol parameters for dosing schemas, visit schedules, safety thresholds, and eligibility criteria for a clinical trial. An AI agent is configured to deliver mapped voice prompts to participant devices, captures audio responses, transcribe and extract symptom, adherence, or adverse-event data, and pair response data with physiological-sensor or laboratory input data. The logic engine continuously evaluates the combined data to adaptively select dose-escalation or titration instructions and issue follow-up queries while enforcing safety thresholds. All prompts, audio, transcriptions, decisions, and metadata may be immutably timestamped in an electronic record repository accessible via role-based, encrypted connections. Embodiments of the present disclosure provide for real-time, audit-ready trial communications, automated personalized dosing, and enhanced participant safety monitoring.

Provided herein is the use of certain biomarkers, such as tryptophan and metabolites thereof for use in certain treatment methods. Suitable tryptophan metabolites that may serve as useful biomarkers include, for example, kynurenine (Kyn), kynurenic acid (KynA), and quinolinic acid. Such biomarkers may be used in identifying a subject who may benefit from treatment, predicting the responsiveness or monitoring the response of the subject to the treatment, or determining or adjusting the dosing or dosing regimen of the treatment to the subject.

The present invention provides dosing regimens of bispecific antibodies that target both CD3 and CD20 when used in the treatment of lymphoma, such as B cell non-Hodgkin lymphoma (B-NHL).

The invention includes dry powder nintedanib formulation for dispersion and inhalation administration including salts thereof, indolinone derivative or salts thereof and in fixed dose combinations with carrier agents and other active ingredients. The aerosol delivery combination formulation may be administered as an inhaled aerosol over a few actuations or by two or more actuations. Each dose may be administered one or more times daily on a regular or interval daily dosing regimen. The special formulation parameters of the invention include the selection of the salt for complexation with the form of nintedanib used for an isolated dry powder along with particle size distributions and combination with a force control agent for improved aerosol delivery. Methods of the invention include therapeutically effective doses of the described invention used to treat interstitial lung disease.

The invention relates to dosage forms for daily administration of compounds of formula (A) and formula (I):or a salt thereof, wherein R1, R2, R10, R11, R12, R13, R14, R15, R16, q and p are as described herein. Compounds of formula (A), formula (I), and pharmaceutical compositions thereof are αvβ6 integrin inhibitors that are useful for treating fibrosis such as idiopathic pulmonary fibrosis (IPF) and nonspecific interstitial pneumonia (NSIP).

The invention is a method for treating levodopa naïve patients with Parkinson's disease by orally administering a controlled release levodopa formulation twice a day to the levodopa naïve patient and the method provides an improvement of a patient's motor state as determined by patient's Parkinson's disease diary, provides a reduction of from about 10%-40% in the patient's tremor, dyskinesia, and / or mobility and / or provides a reduction in the patient's Movement Disorders Society version of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) scores by at least 3 points.

Provided is a method of treating malignant tumor by an azabicyclic compound, particularly, with eye disorder reduced. The present invention provides a method for treating malignant tumor, comprising administering an effective amount of 3-ethyl-4-[3-(1-methylethyl)-4-[4-(1-methyl-1H-pyrazol-4-yl)-1H-imidazol-1-yl]-1H-pyrazolo[3,4-b]pyridin-1-yl]benzamide (compound 1) or a salt thereof to a patient in need thereof according to a dosing regimen, wherein the dosing regimen comprises administering the compound 1 or the salt thereof at a dose from 40 mg / body / day to 240 mg / body / day in terms of the amount of the compound 1 for consecutive days, and then providing a withdrawal period of at least 2 days.

Methods, systems and apparatus are described for classifying one or more candidate molecule drugs in relation to one or more desired target conditions for use in downstream processing of drug optimization. A candidate molecule drug inference dataset is received for one or more molecule drugs, the candidate molecule drug dataset comprising data representative of a set of physiochemical values for each candidate molecule drug and a set of pharmacokinetic (PK) values associated with a dosage regimen and target in relation to each candidate molecule drug, and where each candidate molecule drug of the candidate molecule drug dataset is classified as a large molecule drug. For each candidate molecule drug of the candidate molecule drug inference dataset, the corresponding set of physiochemical values and set of PK values for the dosage regimen and target are applied to a machine learning (ML) model configured for classifying whether each candidate molecule drug meets one or more desired conditions associated with pharmacological or pharmacodynamic effects. The ML model is trained using an ML algorithm to train model parameters defining the ML model for classifying whether each candidate molecule drug meets the one or more desired conditions based on a training dataset comprising data representative of a plurality of molecule drugs, each molecule drug represented by a corresponding set of physiochemical values and a set of PK values associated with the dosage regimen and the target, and annotated in relation to corresponding pharmacological or pharmacodynamic effects, responses and / or values in relation to the desired conditions. A set of candidate molecule drugs satisfying the desired conditions is output for downstream processing of drug optimization.

The invention discloses an immunosuppressor administration recommendation system based on deep reinforcement learning, and relates to the technical field of medical medication management, and the system comprises a model construction module, an information acquisition module and a scheme recommendation module. The model construction module comprises a strategy sub-module, an environment sub-module, a reward sub-module and a training sub-module; the strategy sub-module constructs a drug administration recommendation model, and the drug administration recommendation model is used for receiving patient characteristics and then outputting a drug administration recommendation scheme; the environment sub-module predicts the blood concentration of the patient after medication according to the patient characteristics and the medication recommendation scheme; the reward sub-module evaluates the blood concentration of the patient after medication to obtain a reward and punishment value; the training sub-module trains a drug administration recommendation model based on the reward and punishment values, and sends the drug administration recommendation model to the scheme recommendation module when a training termination condition is met; and the scheme recommendation module inputs the target characteristics of the target patient sent by the information acquisition module into a drug administration recommendation model to obtain a target drug administration scheme so as to reduce the decision-making difficulty of the immunosuppressor drug administration scheme.

The invention is a method for treating patients with Parkinson's disease by orally administering a controlled release levodopa formulation and the method provides an improvement of a patient's total post-dose “Off” time, total post dose “On” time and total post dose “Good On” time compared to post-dose of treatment regimens with oral immediate release levodopa tablets.

Disclosed are formulations and dosage forms of avermectins, and particularly of ivermectin. The disclosed compositions may be used in methods for the treatment and prevention of pain in humans.

Provided herein are dosing regimens and methods for treating conditions and diseases characterized by a reduced expression or function of NaV1.1 protein by modulating splicing of a pre-mRNA encoded by an SCN1A gene. The dosing regimens and methods can be used to treat Dravet Syndrome or other conditions and diseases.

The invention is a method for treating patients with Parkinson's disease by orally administering a controlled release levodopa formulation and the method provides an improvement of a patient's total post-dose “Off” time, total post dose “On” time and total post dose “Good On” time compared to post-dose of treatment regimens with oral immediate release levodopa tablets.

The invention provides an optimal administration method for promoting cervical maturation by misoprostol based on a PopPK model, and belongs to the technical field of drug administration scheme optimization, the method comprises the following steps: constructing the PopPK model for oral administration of misoprostol by a pregnant woman in late pregnancy, the PopPK model is a model structure containing absorption lag time zero-order-first-order absorption parallel, one-atrioventricular distribution and first-order elimination, and the PopPK model is a model structure containing absorption lag time zero-order-first-order absorption parallel, one-atrioventricular distribution and first-order elimination; the PopPK model comprises two absorption chambers and one central chamber; and based on the PopPK model, determining a staged administration scheme through simulation optimization. The limitation of a traditional fixing scheme is effectively overcome, and the safety, effectiveness and clinical practicability of drug administration are considered.

Therapeutic use and dosing regimen of anti-ICOS antibodies or antigen-binding fragments thereof for modulating the ratio between regulatory T cells and effector T cells, stimulating the immune system of patients, and / or treating tumours or cancers, as monotherapy or combination therapy, e.g., with anti-PD-L1 antibodies or antigen-binding fragments thereof.

The invention is a method for treating patients with Parkinson's disease by orally administering a controlled release levodopa formulation and the method provides an improvement of a patient's total post-dose “Off” time, total post dose “On” time and total post dose “Good On” time compared to post-dose of treatment regimens with oral immediate release levodopa tablets.

The present invention relates to compounds, pharmaceutical compositions, combined preparations, and dosage regimens for treating, inhibiting the progression, and preventing cardiovascular calcification, and in particular, coronary calcification, aortic artery calcification, and aortic valve calcification comprising inositol phosphates. In a particular aspect the disclosure provides a dosage regimen for treating, inhibiting the progression, or preventing cardiovascular calcification comprising the administration of about 200 mg to about 700 mg of myo-inositol hexaphosphate per administration.

Formulations and dosage regimens of anti-Blood Dendritic Cell Antigen 2 (BDCA2) antibodies are provided. These formulations and dosage regimens find use in the treatment of BDCA2-associated disorders such as systematic lupus erythematosus, cutaneous lupus erythematosus, and discoid lupus erythematosus, and cytokine release syndrome.

The present disclosure features methods, e.g., dosing regimens, of treating cancer with SMARCA4 / SMARCA2 ATPase inhibitors.