DRUG REPURPOSING SYSTEM AND METHOD BASED ON HETEROGENEOUS ASSOCIATION NETWORK DEEP LEARNING

Title:

DRUG REPURPOSING SYSTEM AND METHOD BASED ON HETEROGENEOUS ASSOCIATION NETWORK DEEP LEARNING

Document Type and Number:

WIPO Patent Application WO/2023/077854

Kind Code:

A1

Abstract:

The present invention belongs to the technical field of biological medicine. Disclosed are a drug repurposing system and method based on heterogeneous association network deep learning. The system comprises a prediction tool module, an experiment verification module and an external service module. In the prediction tool core module of the provided deep learning drug repurposing system, electronic medical record data is used for updating a "drug-disease" incidence matrix; drug information such as electronic medical records, chemical structures, target protein sequences, side effects, and protein interactions are merged with disease information such as electronic medical records, ontology and phenotype, and a drug similarity matrix and a disease similarity matrix are generated; finally, said three matrixes are combined to generate a "drug-disease" heterogeneous association network.

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Inventors:

YU QI (CN)
HE PEIFENG (CN)
ZHANG SHENXIAO (CN)
LIU GELIANG (CN)
SHI GAOXIANG (CN)
WANG QI (CN)
GAO QICHAO (CN)

Application Number:

PCT/CN2022/104668

Publication Date:

May 11, 2023

Filing Date:

July 08, 2022

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Assignee:

UNIV SHANXI MEDICAL (CN)

International Classes:

G16H70/00

Foreign References:

CN114038574A	2022-02-11
CN110021360A	2019-07-16
CN113053468A	2021-06-29
CN110021341A	2019-07-16
CN110176271A	2019-08-27
US20210142173A1	2021-05-13

Other References:

"Master's Thesis", 18 April 2021, HEILONGJIANG UNIVERSITY, CN, article SONG, YINGYING: "Research on a Drug Relocation Method Based on Network Representation Learning and Deep Learning", pages: 1 - 74, XP009545529, DOI: 10.27123/d.cnki.ghlju.2021.001133

Attorney, Agent or Firm:

TAIYUAN SHENLIDE INTELLECTUAL PROPERTY AGENCY (SPECIAL ORDINARY PARTNERSHIP) (CN)

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