The Mass Spectrometry society of Japan - The 68th Annual Conference on Mass Spectrometry, Japan
Japanese

Abstract

Table of contents

Timetable

Plenary Lectures

Award Lecture

Oral Sessions (Day1, Day2, Day3)

Poster Presentations (Day1, Day2, Day3)

Panel Discussion

Luncheon Seminars (Day1, Day2, Day3)

Corporate Program

Oral Sessions

Day 1, June 22（Wed.）　17:50-18:10　Room A (Main Hall)

1A-O1-1750　　PDF

Data-driven drug target discovery for idiopathic pulmonary fibrosis using proteome data linked to medical information

(1NIBIOHN, 2Osaka National Hospital, 3Osaka Univ., 4Osaka Univ., 5RIKEN AIP, 6NTT CSL)
oYayoi Natsume-Kitatani1, Mari N Itoh1, Yasushi Matsumura2, Yoshito Takeda3, Jun Adachi1, Atsushi Kumanogoh3, Kenji Mizuguchi1,4, Naonori Ueda5,6

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.