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    Substituted benzopyrazolo[1,5-a][1,4]diazepines as GABA positive allosteric modulators
    24.
    发明授权
    Substituted benzopyrazolo[1,5-a][1,4]diazepines as GABA positive allosteric modulators 有权

    公开(公告)号：US12049467B2

    公开(公告)日：2024-07-30

    申请号：US17590404

    申请日：2022-02-01

    申请人： The Johns Hopkins University ,  Lieber Institute, Inc.

    发明人： Yifang Huang ,  Pankaj Jay Pasricha ,  James C. Barrow ,  Ingrid Buchler ,  Michael Poslusney

    IPC分类号： A61K31/5517 ,  A61P1/12 ,  C07D487/04 ,  C07D487/14

    CPC分类号： C07D487/04 ,  A61P1/12

    摘要： This disclosure features chemical entities (e.g., a compound or a pharmaceutically acceptable salt thereof, or an N-oxide thereof) of formula (I), which are positive allosteric modulators of one or more GABA-A receptors, e.g., which are peripherally restricted, positive allosteric modulators of one or more GABA-A receptors; e.g., which are positive allosteric modulators of one or more GABA-A receptors and which selectively target the peripheral nervous system and organs of the body, and which do not substantially pass through the blood-brain barrier. Said compounds are useful e.g., for the treatment of systemic diseases of the body, e.g., diseases in which modulation of one or more peripherally restricted GABA-A receptors is beneficial (e.g., diseases or disorders which are mediated by GABA-A neuronal activity. This disclosure also features pharmaceutical compositions containing the chemical entities described herein as well as methods of using same for the treatment of systemic diseases of the body.

    PROCESSING EVENT DATA BASED ON MACHINE LEARNING
    28.
    发明公开
    PROCESSING EVENT DATA BASED ON MACHINE LEARNING 审中-公开

    公开(公告)号：US20240211800A1

    公开(公告)日：2024-06-27

    申请号：US18088074

    申请日：2022-12-23

    申请人： The Johns Hopkins University

    发明人： Eileen Kasda ,  Christine Robson ,  Asa Adadey ,  David Gillen ,  Mario Koym-Garza

    IPC分类号： G06N20/00 ,  G06F18/23213

    CPC分类号： G06N20/00 ,  G06F18/23213

    摘要： A computer-implemented method includes receiving, by a data processing system, event data representing a medical safety event. The method includes processing the event data, including: parsing, the event data to identify a structure of the event data; and identifying one or more fields from the structure of the event data. The method includes inputting, to a machine learning engine, contents of the one or more fields. The method includes generating, by the machine learning engine and from contents of the one or more fields, one or more feature vectors. The method includes accessing a plurality of indicator candidates. The method includes determining, by the machine learning engine and based on the one or more feature vectors, one or more indicators from the indicator candidates. The method includes tagging the event data with the one or more indicators. The method includes storing the tagged event data in a hardware storage device.