公开(公告)号：US12002590B2

公开(公告)日：2024-06-04

申请号：US18311087

申请日：2023-05-02

Applicant: NEUMORA THERAPEUTICS, INC.

Inventor： Monika Sharma Mellem ,  Yuelu Liu ,  Parvez Ahammad ,  Humberto Andres Gonzalez Cabezas ,  William J. Martin ,  Pablo Christian Gersberg

IPC: G16H50/30 ,  G16H10/60 ,  G16H50/20

CPC classification number: G16H50/30 ,  G16H10/60 ,  G16H50/20

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 is 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.

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

IPC: G16B20/00 ,  G16H20/10 ,  G16B40/00 ,  G16H30/20 ,  G16H50/20 ,  G16B25/10

CPC classification number: G16B20/00 ,  G16B25/10 ,  G16B40/00 ,  G16H20/10 ,  G16H50/20 ,  G16H30/20

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.

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

IPC: G16H50/30 ,  G16H50/20 ,  G16H10/60

CPC classification number: G16H50/30 ,  G16H50/20 ,  G16H10/60

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.

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

IPC: G16B20/00 ,  G16H50/20 ,  G16H20/10 ,  G16B25/10 ,  G16B40/00 ,  G16H30/20

CPC classification number: G16B20/00 ,  G16B25/10 ,  G16B40/00 ,  G16H20/10 ,  G16H50/20 ,  G16H30/20

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.