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公开(公告)号:US11842793B2
公开(公告)日:2023-12-12
申请号:US17166952
申请日:2021-02-03
Applicant: NEUMORA THERAPEUTICS, INC. , Yale University
Inventor: John D. Murray , Alan Anticevic , William J. Martin
Abstract: The present tools and methods for detecting, diagnosing, predicting, prognosticating, or treating a neurobehavioral phenotype in a subject. These tools and methods relates to a genotype and neurophenotype topography-based approach for analyzing brain neuroimaging and gene expression maps to identify drug targets associated with neurobehavioral phenotypes and, conversely, neurobehavioral phenotypes associated with potential drug targets, to develop rational design and application of pharmacological therapeutics for brain disorders, and to provide methods and tools for treatment of subjects in need of neurological therapy.
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公开(公告)号:US20230343461A1
公开(公告)日:2023-10-26
申请号:US18209866
申请日:2023-06-14
Applicant: NEUMORA THERAPEUTICS, INC.
Inventor: Monika Sharma MELLEM , Yuelu Liu , Parvez Ahammad , Humberto Andres Gonzalez Cabezas , William J. Martin , Pablo Christian Gersberg
Abstract: Systems and methods for utilizing machine learning to generate a trans-diagnostic classifier that is operative to concurrently diagnose a plurality of different mental health disorders using a single trans-diagnostic questionnaire that includes a plurality of questions (e.g., 17 questions). Machine learning techniques are used to process labeled training data to build statistical models that include trans-diagnostic item-level questions as features to create a screen to classify groups of subjects as either healthy or as possibly having a mental health disorder. A subset of questions are selected from the multiple self-administered mental health questionnaires and used to autonomously screen subjects across multiple mental health disorders without physician involvement, optionally remotely and repeatedly, in a short amount of time.
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公开(公告)号:US12232848B2
公开(公告)日:2025-02-25
申请号:US17603779
申请日:2020-04-29
Applicant: Neumora Therapeutics, Inc.
Inventor: John Chan , Sandeep R. Datta , Alexander B. Wiltschko
Abstract: A system for facial analysis includes a camera, a data storage device and a data processing system. The camera takes video of a subject's face, and the data storage device receives and stores the video. The data processing system extracts a pose of the subject's face, and a representation of the subject's facial gesture state. The pose includes the angle and position of the subject's face. The representation includes facial keypoints that are a collection of points on the subject's face. The system then concatenates each data stream to align the data streams in time, extracts a plurality of facial syllables from the aligned data streams, and compiles the facial syllables into a series of state sequences. Based on the series of state sequences, the system extracts a behavioral fingerprint for the subject that provides a summary of the subject's state over a given period of time.
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公开(公告)号:US12152038B2
公开(公告)日:2024-11-26
申请号:US17194069
申请日:2021-03-05
Applicant: Neumora Therapeutics, Inc.
Inventor: Robert M. Jones , Mariangela Urbano , Gary Brandt , Mark Chambers , David Hardick , Chris Knight , Jason Tierney , Chris Lock
IPC: C07D487/10 , A61P9/00 , A61P25/00 , A61P25/18 , A61P25/20 , A61P25/22 , A61P25/24 , C07D519/00
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 Q1, Q2, Q3, R2a, R2b, R3 and X are as defined herein.
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公开(公告)号:US12087446B2
公开(公告)日:2024-09-10
申请号:US17740713
申请日:2022-05-10
Applicant: NEUMORA THERAPEUTICS, INC.
Inventor: Matthew Kollada , Tathagata Banerjee
CPC classification number: G16H50/20 , A61B5/0205 , A61B5/165 , A61B5/7264 , G06N20/00 , G16H10/20
Abstract: Methods and systems are provided for diagnosing mental health conditions using multiple data modalities. In particular, a trained machine learning model is used for mental health diagnosis, wherein the trained model utilizes a dynamic fusion approach for capturing and preserving interactions as well as timing information between the multiple data modalities.
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公开(公告)号:US20240294492A1
公开(公告)日:2024-09-05
申请号:US18628594
申请日:2024-04-05
Applicant: NEUMORA THERAPEUTICS, INC.
Inventor: Paul Dransfield , Dilinie Fernando , James Harvey , Brian Sparling , John Stellwagen , Zhihua Ma , Anne-Marie Beausoleil , Ryan Hudson
IPC: C07D401/04
CPC classification number: C07D401/04
Abstract: The present disclosure relates to compounds of Formula (I).
and pharmaceutically acceptable salts thereof, wherein the variable are as described herein, and compositions and uses of same for treating neurological disorders.-
公开(公告)号:US20240197220A1
公开(公告)日:2024-06-20
申请号:US18511409
申请日:2023-11-16
Applicant: NEUMORA THERAPEUTICS, INC.
Inventor: Qingzhu GAO , Humberto Andres GONZALEZ CABEZAS , Parvez AHAMMAD , Yuelu LIU
Abstract: A system includes a display device, a user interface, a memory, and a control system. The memory contains machine readable medium including machine 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 display, on the display device, a series of questions from mental health questionnaires. The series of questions includes text and answers for each question. From the user interface, a selection of answers of each of the displayed series of questions is received from a patient. Using a Bayesian Decision List, the received selection of answers is processed to output an indication of mental health of the patient. The indication of mental health identifies a kappa opioid receptor antagonist to which the patient would likely be a higher responder.
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公开(公告)号:US11993580B1
公开(公告)日:2024-05-28
申请号:US18526960
申请日:2023-12-01
Applicant: NEUMORA THERAPEUTICS, INC.
Inventor: Paul Dransfield , Dilinie Fernando , James Harvey , Brian Sparling , John Stellwagen , Zhihua Ma , Anne-Marie Beausoleil , Ryan Hudson
IPC: C07D401/04
CPC classification number: C07D401/04
Abstract: The present disclosure relates to compounds of Formula (I),
and pharmaceutically acceptable salts thereof, wherein the variable are as described herein, and compositions and uses of same for treating neurological disorders.-
29.
公开(公告)号:US20240062847A1
公开(公告)日:2024-02-22
申请号:US18487839
申请日:2023-10-16
Applicant: NEUMORA THERAPEUTICS, INC. , YALE UNIVERSITY
Inventor: John D. MURRAY , Alan ANTICEVIC , William J. MARTIN
Abstract: The present disclosure relates to computer generated topographies from computer correlations of neurobehavioral phenotype mapping data and gene expression mapping data. Neurobehavioral phenotype mapping data is obtained for a selected phenotype and correlated with gene expression mapping data for one or more genes to define a phenotype-gene pair topography for each phenotype-gene pair. A score for each phenotype-gene pair is determined based on the correlation. The scores are used to identify genes, or drug targets, associated with the respective gene of the respective phenotype-gene pair. Conversely, gene expression mapping data is obtained for a selected gene and correlated with neurobehavioral phenotype mapping data for one or more phenotypes to define a gene-phenotype topography for each gene-phenotype pair. A score for each gene-phenotype pair is determined based on the correlation. The scores are used to identify a phenotype associated with the respective phenotype-gene pair.
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公开(公告)号:US11791016B2
公开(公告)日:2023-10-17
申请号:US16150137
申请日:2018-10-02
Applicant: NEUMORA THERAPEUTICS, INC. , Yale University
Inventor: John D. Murray , Alan Anticevic , William J. Martin
Abstract: The present disclosure relates to computer generated topographies from computer correlations of neurobehavioral phenotype mapping data and gene expression mapping data. Neurobehavioral phenotype mapping data is obtained for a selected phenotype and correlated with gene expression mapping data for one or more genes to define a phenotype-gene pair topography for each phenotype-gene pair. A score for each phenotype-gene pair is determined based on the correlation. The scores are used to identify genes, or drug targets, associated with the respective gene of the respective phenotype-gene pair. Conversely, gene expression mapping data is obtained for a selected gene and correlated with neurobehavioral phenotype mapping data for one or more phenotypes to define a gene-phenotype topography for each gene-phenotype pair. A score for each gene-phenotype pair is determined based on the correlation. The scores are used to identify a phenotype associated with the respective phenotype-gene pair.
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