Disease target discovery method and system based on multi-agent architecture

By employing a disease target discovery method based on a multi-agent architecture, which combines the collaborative work of a central agent, multi-omics agents, and structural agents, this approach addresses the issues of long cycles, high costs, and high technical barriers to data fusion in traditional target discovery methods. It achieves efficient and accurate target discovery, supporting new drug development.

CN122201415BActive Publication Date: 2026-07-24CHINA RESOURCES PHARM RES INST (SHENZHEN) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA RESOURCES PHARM RES INST (SHENZHEN) CO LTD
Filing Date
2026-05-14
Publication Date
2026-07-24

AI Technical Summary

Technical Problem

Traditional target discovery methods are time-consuming and costly. Multi-omics and structural computation methods have limitations in target discovery, such as insufficient drugability assessment, high dependence on structural information, and high technical barriers to data fusion, making it difficult to achieve efficient collaboration and large-scale application.

Method used

A disease target discovery method based on a multi-agent architecture is adopted, including a central agent, a multi-omics agent, and a structural agent, which achieve target discovery through division of labor and cooperation. The central agent is responsible for task decomposition, result integration, and arbitration, while the multi-omics agent and the structural agent perform autonomous reasoning and verification, respectively. The system identifies targets through multiple rounds of autonomous exploration.

Benefits of technology

It lowers the threshold for analyzing complex multimodal data, improves the accuracy and comprehensiveness of target discovery, achieves more comprehensive coverage and accurate identification of disease targets, and significantly improves the efficiency and reliability of new drug development.

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Abstract

The present application relates to a disease target discovery method and system based on a multi-agent architecture. The multi-agent architecture comprises a multi-omics agent, a structure agent and a central agent. The disease target discovery method comprises: obtaining a task description in natural language and multi-modal data of a user by the central agent; analyzing multi-omics data by the multi-omics agent to generate a first initial target recommendation report, and analyzing structure data by the structure agent to generate a second initial target recommendation report; performing consensus analysis on the first initial target recommendation report and the second initial target recommendation report by the central agent, identifying consensus targets and unique targets, and feeding back the unique targets to the multi-omics agent and the structure agent respectively; verifying the unique targets by the multi-omics agent and the structure agent respectively to generate a first supplementary target recommendation report and a second supplementary target recommendation report; and generating a final target recommendation report by the central agent.
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