オーラルセッション
- 第1日 6月22日（水） 17:50～18:10 A会場（メインホール）
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1A-O1-1750 PDF
診療情報と紐付けられたプロテオームデータによる特発性肺線維症を対象としたデータ駆動的創薬標的探索
A ministry-to-ministerial research project aimed at “development of artificial intelligence that accelerates the creation of new drugs” based on the framework of the Public/Private R&D Investment Strategic Expansion PrograM (PRISM) aims to address the problem of the current drug discovery and development process, which is the high attrition rate at Phase 2 clinical trials that may have caused by the drug target discovery using experimental animal data in the early development stage. We are developing machine learning algorithms that perform data-driven drug target discovery from human-derived data which include omics data linked to medical information. We have been promoting the project with three goals in mind: (1) collection of omics data linked to medical information and construction of a database, (2) development of machine learning algorithms that present candidate drug targets in a data-driven manner using the constructed database, and (3) development of an infrastructure for sharing the achievements of the project.
In this presentation, we will introduce our results in data-driven drug target discovery for idiopathic pulmonary fibrosis (IPF) using state-of-the-art DIA proteome data linked to medical information.