ゲノム解析 × AI ×個別化医療ー次世代バイオマーカーと医療応用ー

	Prof. Ludmil B. Alexandrov, Ph.D. Professor, Department of Cellular and Molecular Medicine and Shu Chien-Gene Lay Department of Bioengineering, UC San Diego Ludmil B. Alexandrov, PhD, is a Professor of Bioengineering and Cellular & Molecular Medicine at the University of California San Diego. He is internationally recognized for founding the field of mutational signatures and establishing a quantitative framework to decode the biological, environmental, and endogenous processes that shape cancer genomes. His work transformed cancer genomics from descriptive cataloging into a mechanistic science capable of identifying the causes of cancer directly from DNA. Dr. Alexandrov’s research has uncovered major environmental and microbial drivers of human cancer, including demonstrating the mutagenic role of air pollution in lung cancer among never-smokers and identifying colibactin as a likely contributor to the global rise in early-onset colorectal cancer. More broadly, his work bridges genomics and artificial intelligence to enable cancer risk stratification, early detection, and precision treatment strategies. He has authored over 160 peer-reviewed publications, including over 30 papers in Nature, Science, and Cell, and has been recognized annually since 2019 as a Clarivate Highly Cited Researcher. He is an elected Fellow of the American Institute for Medical and Biological Engineering (AIMBE).
	中川 英刀 先生 国立研究開発法人理化学研究所 チームリーダー 1991年　大阪大学医学部医学科卒業 1991年　大阪大学医学部第２外科 1992年　大阪大学医学部付属病院 ICU 1993年　国立大阪病院外科 1996年　大阪大学医学部第２外科　 1999年　The Ohio State University, USA 2003年　東京大学医科学研究所　ヒトゲノム解析センター　 2008年～　理化学研究所　チームリーダー       2015年～　AMED　バイオバンク/ゲノム関係　PO  　 資格: 日本外科学会認定医、日本消化器外科学会認定医、日本がん治療認定医、臨床遺伝専門医                  現在の研究テーマ： ①がんゲノム解析 ②腫瘍免疫、single-cell解析、ST解析 ③がんの遺伝的リスク、遺伝性腫瘍 ④ゲノム医療
	Dr. Woong-Yang Park, MD, PhD Chair, GxD IntelliMed is an AI-powered drug discovery platform designed to help pharmaceutical companies identify high-value therapeutic targets, discover predictive biomarkers, and optimize clinical development strategies. By integrating clinically annotated genomics, single-cell and spatial omics, pathology, and treatment-response data, IntelliMed provides a comprehensive framework to understand disease biology in real clinical contexts. The platform is particularly powerful for revealing tumor–microenvironment interactions, target expression patterns, resistance mechanisms, and patient subgroups most likely to benefit from specific therapies. Built for translational and clinical applications, IntelliMed supports target prioritization, biomarker hypothesis generation, patient stratification, and indication expansion across oncology programs, including targeted therapies, immuno-oncology, and ADC development. Its AI-driven analytics enable pharma partners to move beyond descriptive data analysis toward actionable decision-making grounded in human clinical samples. By combining advanced multi-omics interpretation with scalable computational models, IntelliMed aims to reduce development risk, improve trial success rates, and accelerate the delivery of precision medicines to patients.
	Dr. Alan Moazzam, MD, MBA, FACP Health Sciences Assistant Clinical Professor, Division of Hospital Medicine  & Advisor to the Institute for the Global Entrepreneur (IGE), UC San Diego Alan Moazzam MD MBA FACP is a board-certified internal medicine physician who specializes in caring for hospitalized patients. Dr. Moazzam completed his residency in internal medicine at USC Los Angeles County Hospital. He earned his medical degree at Saint Louis University, in St. Louis, MO and his Bachelor’s degree in Biochemistry from UCSD. He currently serves as a Health Sciences Assistant Clinical Professor with the Division of Hospital Medicine at UCSD. He is Chair of the Physician Steering Committee for the Institute of Healthcare Engineering at Jacobs School of Engineering. He is a clinical mentor and advisor to the Institute for the Global Entrepreneur (IGE) at UCSD, where he advises teams wanting to commercialize their medical technology inventions. He is a Physician Affiliate to the Jacobs Center for Healthcare Innovation, where he works with researchers to develop AI-based clinical support tools and GenAI innovations for UCSD healthcare ecosystem. His research interests include anti-circadian night shift work and its effects on human physiology. He is a member of UCSD's Center for Circadian Biology. Dr. Moazzam is a Fellow of the American College of Physicians and a member of the Society of Hospital Medicine.

講演要旨

Prof. Alexandrov
The integration of genomics and artificial intelligence is transforming how we understand, prevent, and diagnose cancer. In this talk, I will present a unified framework combining large-scale data and machine learning to address both public health and clinical challenges.
     First, I will describe our work applying machine learning to large-scale cancer genomics to investigate the rise of early-onset colorectal cancer. Analyses of whole-genome data across 11 countries reveal geographic and age-related mutational patterns, including evidence for early-life exposures such as colibactin, informing risk stratification and opportunities for early intervention at the population level, including in Japan.
     Second, I will show how AI can predict treatment response directly from routine histopathology images, enabling AI-based diagnostics that can complement or, in some cases, replace molecular testing in a more cost-effective and scalable manner, while guiding therapy selection.
     Together, these examples illustrate how genomics and AI can bridge discovery and clinical implementation in precision oncology.

Dr. Park
IntelliMed is an AI-powered drug discovery platform designed to help pharmaceutical companies identify high-value therapeutic targets, discover predictive biomarkers, and optimize clinical development strategies. By integrating clinically annotated genomics, single-cell and spatial omics, pathology, and treatment-response data, IntelliMed provides a comprehensive framework to understand disease biology in real clinical contexts. The platform is particularly powerful for revealing tumor–microenvironment interactions, target expression patterns, resistance mechanisms, and patient subgroups most likely to benefit from specific therapies. Built for translational and clinical applications, IntelliMed supports target prioritization, biomarker hypothesis generation, patient stratification, and indication expansion across oncology programs, including targeted therapies, immuno-oncology, and ADC development. Its AI-driven analytics enable pharma partners to move beyond descriptive data analysis toward actionable decision-making grounded in human clinical samples. By combining advanced multi-omics interpretation with scalable computational models, IntelliMed aims to reduce development risk, improve trial success rates, and accelerate the delivery of precision medicines to patients.

Dr. Moazzam
Bringing a new therapy, diagnostic, or digital health technology to patients in the United States is rarely limited by the science itself - it is shaped by a uniquely complex financial and regulatory architecture. In this lecture, Dr. Moazzam offers Japanese stakeholders a pragmatic map of the American healthcare system: the fragmented mix of public and private payers, how hospitals and physicians are actually paid, the coding and reimbursement pathways that determine whether an innovation reaches patients at scale, and the rising influence of value-based care. He will discuss how a clear understanding of this ecosystem equips companies to enter the US market with informed, realistic go-to-market strategies, setting the stage for the panel discussion on shortening the distance between scientific breakthrough and clinical impact.