公开(公告)号：US12171758B1

公开(公告)日：2024-12-24

申请号：US18764004

申请日：2024-07-03

Applicant: Neumora Therapeutics, Inc.

Inventor： Brian Van Dyke ,  Yawei Shi ,  Mengya Ma ,  Lori Jean Van Orden

IPC: A61K31/4709 ,  C07D413/14

Abstract: Disclosed herein is a solid Form A of 1-(6-ethyl-8-fluoro-4-methyl-3-(3-methyl-1,2,4-oxadiazol-5-yl)quinolin-2-yl)-N-(tetrahydro-2H-pyran-4-yl)piperidin-4-amine hydrochloride exhibiting at least X-ray lines (in degrees 2θ±0.2) at 4.30, 8.59, 12.88, 18.82 and 21.34 in a powder diffraction pattern when measured using Cu Kα radiation. The solid Form A is an antagonist of the kappa-opioid receptor (KOR) and is useful for treating conditions that benefit from the same. Compositions comprising the solid Form A, as well as related methods of use are also disclosed.

公开(公告)号：US20240355480A1

公开(公告)日：2024-10-24

申请号：US18587367

申请日：2024-02-26

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Yuelu LIU ,  Monika Sharma MELLEM ,  Parvez AHAMMAD ,  Humberto Andres GONZALEZ CABEZAS ,  Matthew KOLLADA

IPC: G16H50/30 ,  A61B5/00 ,  A61B5/055 ,  A61B5/16 ,  G06F18/21 ,  G06F18/214 ,  G06N20/00 ,  G16H10/20 ,  G16H20/70 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70

CPC classification number: G16H50/30 ,  A61B5/0042 ,  A61B5/055 ,  A61B5/16 ,  A61B5/7267 ,  G06F18/2148 ,  G06F18/2178 ,  G06F18/2193 ,  G06N20/00 ,  G16H10/20 ,  G16H30/20 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  A61B2576/026 ,  G06V2201/031 ,  G16H20/70

Abstract: A system for evaluating mental health of patients includes a memory and a control system. The memory contains executable code storing instructions for performing a method. The control system is coupled to the memory and includes one or more processors. The control system is configured to execute the machine executable code to cause the control system to perform the method: A selection of answers associated with a patient is received. The selection of answers corresponds to each question in a series of questions from mental health questionnaires. Unprocessed MRI data are received. The unprocessed MRI data correspond to a set of MRI images of a biological structure associated with the patient. The unprocessed MRI data is processed to output a set of MRI features. Using a machine learning model, the selection of answers and the set of MRI features are processed to output a mental health indication of the patient.

公开(公告)号：US11742076B2

公开(公告)日：2023-08-29

申请号：US17960755

申请日：2022-10-05

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Matthew Edward Kollada

IPC: G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G16H30/40 ,  G06V10/77 ,  G06V10/82 ,  G06V10/774 ,  G06T7/00 ,  G06N20/00

CPC classification number: G16H40/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0016 ,  G06V10/774 ,  G06V10/7715 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N20/00 ,  G06T2207/10088 ,  G06T2207/10104 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016 ,  G06T2207/30104 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating multi-modal data archetypes. In one aspect, a method comprises obtaining a plurality of training examples, wherein each training example corresponds to a respective patient and includes multi-modal data, having a plurality of feature dimensions, that characterizes the patient; jointly training an encoder neural network and a decoder neural network on the plurality of training examples; and generating a plurality of multi-modal data archetypes that each correspond to a respective dimension of a latent space, comprising, for each multi-modal data archetype: processing a predefined embedding that represents the corresponding dimension of the latent space using the decoder neural network to generate multi-modal data, having the plurality of feature dimensions, that defines the multi-modal data archetype.

公开(公告)号：US20230260634A1

公开(公告)日：2023-08-17

申请号：US18136832

申请日：2023-04-19

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Matthew Edward Kollada

IPC: G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G16H30/40 ,  G06V10/77 ,  G06V10/82 ,  G06V10/774 ,  G06T7/00

CPC classification number: G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G16H30/40 ,  G06V10/7715 ,  G06V10/82 ,  G06V10/774 ,  G06T7/0016 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying a patient. In one aspect, a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using an encoder neural network to generate an embedding of the multi-modal data characterizing the patient; determining a respective classification score for each patient category in a set of patient categories based on the embedding of the multi-modal data characterizing the patient; and classifying the patient as being included in a corresponding patient category from the set of patient categories based on the classification scores.

公开(公告)号：US20240415433A1

公开(公告)日：2024-12-19

申请号：US18724083

申请日：2022-12-30

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tanya WALLACE

IPC: A61B5/16 ,  A61B5/00 ,  A61B5/374 ,  A61K45/06

Abstract: Methods and systems are provided for evaluating mental health conditions based on a EEG data. According to one implementation, a system for evaluating mental health in a subject includes: a set of EEG sensors configured to output brain wave data collected from the subject. The system also includes a processor, and logic that is integrated with and/or executable by the processor. Moreover, the logic is configured to: receive, by the processor, brain wave data from the set of EEG sensors, the brain wave data corresponding to a treatment administered to the subject, and evaluate, by the processor, the brain wave data to determine an EEG profile over a period of time. The logic is also configured to: determine, by the processor, a mental health condition of the subject using the EEG profile, and output, by the processor via a user interface, an indication of the mental health condition.

公开(公告)号：US20240021298A1

公开(公告)日：2024-01-18

申请号：US18370818

申请日：2023-09-20

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Matthew Edward Kollada

IPC: G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G16H30/40 ,  G06V10/77 ,  G06V10/82 ,  G06V10/774 ,  G06T7/00

CPC classification number: G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G16H30/40 ,  G06V10/7715 ,  G06V10/82 ,  G06V10/774 ,  G06T7/0016 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for jointly training an encoder neural network and a decoder neural network. In one aspect, a method comprises: updating current values of a set of encoder parameters and current values of a set of decoder parameters using gradients of a reconstruction loss function that measures an error in a reconstruction of multi-modal data from a training example, wherein: the reconstruction loss function comprises a plurality of scaling factors that each scale a respective term in the reconstruction loss function that measures an error in the reconstruction of a corresponding proper subset of feature dimensions of the multi-modal data from the training example.

公开(公告)号：US20230343446A1

公开(公告)日：2023-10-26

申请号：US18212690

申请日：2023-06-21

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Peter Crocker

IPC: G16H30/40 ,  G06N3/02 ,  G06N3/08 ,  G06V10/82 ,  G16H50/70 ,  G06N3/045 ,  G06V10/77 ,  G06T7/00 ,  G16H40/20 ,  G16H50/20 ,  G06V10/774

CPC classification number: G16H40/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0016 ,  G06V10/7715 ,  G06V10/774 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N20/00

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a respective response score for each of a plurality of patient categories. In one aspect, a method comprises: generating a drug signature for a drug; generating an embedding of the drug signature in a latent space; and processing: (i) the embedding of the drug signature in the latent space, and (ii) data defining a plurality of patient categories, to generate a plurality of response scores, wherein each response score corresponds to a respective patient category and characterizes a predicted response of patients included in the patient category to the drug.

公开(公告)号：US11670417B2

公开(公告)日：2023-06-06

申请号：US17960705

申请日：2022-10-05

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Matthew Edward Kollada

IPC: G16H50/30 ,  G06N3/08 ,  G16H20/60 ,  G16H40/20 ,  G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06N3/045 ,  G16H30/40 ,  G06V10/77 ,  G06V10/82 ,  G06V10/774 ,  G06T7/00 ,  G06N20/00

CPC classification number: G16H40/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0016 ,  G06V10/774 ,  G06V10/7715 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N20/00 ,  G06T2207/10088 ,  G06T2207/10104 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016 ,  G06T2207/30104 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for classifying a patient. In one aspect, a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using an encoder neural network to generate an embedding of the multi-modal data characterizing the patient; determining a respective classification score for each patient category in a set of patient categories based on the embedding of the multi-modal data characterizing the patient; and classifying the patient as being included in a corresponding patient category from the set of patient categories based on the classification scores.

公开(公告)号：US11887724B2

公开(公告)日：2024-01-30

申请号：US17960759

申请日：2022-10-05

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Tathagata Banerjee ,  Matthew Edward Kollada ,  Amirsina Torfi ,  Peter Crocker

IPC: G16H50/70 ,  G16H50/20 ,  G06N3/02 ,  G06V10/82 ,  G06V10/774 ,  G06N3/08 ,  G16H30/40 ,  G16H40/20 ,  G06N3/045 ,  G06V10/77 ,  G06T7/00 ,  G06N20/00

CPC classification number: G16H40/20 ,  G06N3/02 ,  G06N3/045 ,  G06N3/08 ,  G06T7/0016 ,  G06V10/774 ,  G06V10/7715 ,  G06V10/82 ,  G16H30/40 ,  G16H50/20 ,  G16H50/70 ,  G06N20/00 ,  G06T2207/10088 ,  G06T2207/10104 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30016 ,  G06T2207/30104 ,  G06V2201/03

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a clinical recommendation for medical treatment of a patient. In one aspect a method comprises: receiving multi-modal data characterizing a patient, wherein the multi-modal data comprises a respective feature representation for each of a plurality of modalities; processing the multi-modal data characterizing the patient using a machine learning model, in accordance with values of a set of machine learning model parameters, to generate a patient classification that classifies the patient as being included in a patient category from a set of patient categories; determining an uncertainty measure that characterizes an uncertainty of the patient classification generated by the machine learning model; and generating a clinical recommendation for medical treatment of the patient based on: (i) the patient classification, and (ii) the uncertainty measure that characterizes the uncertainty of the patient classification.

公开(公告)号：US11858943B2

公开(公告)日：2024-01-02

申请号：US17500780

申请日：2021-10-13

Applicant: Neumora Therapeutics, Inc.

Inventor： Robert M. Jones ,  Mariangela Urbano ,  Gary Brandt ,  David Hardick ,  Chris Knight ,  Jason Tierney

IPC: C07D487/04 ,  A61P15/08 ,  A61P15/10 ,  A61P25/20 ,  C07D498/04 ,  A61P9/06 ,  A61P25/18 ,  A61P25/22 ,  C07D491/04 ,  A61P25/24

CPC classification number: C07D487/04 ,  A61P9/06 ,  A61P15/08 ,  A61P15/10 ,  A61P25/18 ,  A61P25/20 ,  A61P25/22 ,  A61P25/24 ,  C07D491/04 ,  C07D498/04

Abstract: Compounds are provided that antagonize vasopressin receptors, particularly the V1a receptor products containing such compounds, as well as to methods of their use and synthesis. Such compounds have the structure of Formula (I), or a pharmaceutically acceptable isomer, racemate, hydrate, solvate, isotope, or salt thereof:




wherein A, B, G, R1, R1b, R1c, R2 and X are as defined herein.