A center of gravity for biomedical
data science in the world

Tokyo Medical & Dental University
M&D Data Science Center
5th Fl., Building 22, Surugadai Campus,
Tokyo Medical and Dental University,
2-3-10 Kanda Surugadai, Chiyoda-ku, Tokyo
101-0062 Japan
E-mail mddsc.dsc@tmd.ac.jp
URL https://dsc.tmd.ac.jp/en/home/

October 2023

M&D Data Science Center1

M&D Data Science Center

OutlineGreeting

Data Science will open up the innovative
world of medicine and dentistry.

In addition to the University Hospital, Tokyo Medical and Dental University has
a Bioresource Research Center, an intractable diseases treatment cluster, anda large amount of data on clinical practice in medicine and dentistry.
The M&D Data Science Center will serve as a national model for human resource development and research by utilizing the data held by the University
and establishing three facets for basic, applied, and clinical development: theM&D Data Science Platform, M&D Data Science Implementation, and M&D
Data Science Outcome, respectively.
The instructors at the Center are an array of researchers working in areasthat include information science, statistical science, computational science,and ethical, legal, and social issues (ELSI).
Our goal is not only to promote cutting-edge research and clinical implementation, but also to develop human resources who will lead society as entrepreneurs.

2 M&D Data Science Center

The M&D Data Science Center is a university-wide organization under the directcontrol of the President, and consists of 8
divisions containing 5 core departments
and 10 cooperative departments.

Medical and dental research and medical care are entering a new phase in terms of the as part of digitalization and globalization. This particularly applies to biomedical research, in which vast amounts of data can now be obtained in genome information
analysis and one-cell analysis, and the possibility of creating new solutions through integrated analysis of this information isincreasing. In the medical field, the advanced concept of a smart hospital is becoming a reality, with integrated analysis of vast
amounts of medical information and its application in medical treatment, as well as the construction of networks within hospitals and with outside institutions. In addition to spatial expansions such as telemedicine using ICT technology and global publichealth, temporal expansions are also taking place in areas such as preventive medicine and preemptive medicine.
In response to this situation, the M&D Data Science Center was established in April 2020 as a model case for spearheading new
medical and dental research, medical care, and education at the University in the Society 5.0 era from the perspective of data
science.
We have been carrying out research and collaboration based on and driven by data science through the promotion of collaborative research within the University and provisioning of data analysis infrastructure and services including SHIROKANE, a supercomputer installed at the Institute of Medical Science of the University of Tokyo, and SHIRAUME, a storage server running at the
University.
Other than playing an important role in a university-wide effort to build a platform for the accumulation and provision of comprehensive, high-quality medical data owned by the university hospital and Bioresource Research Center, we are also promoting
education in data science and AI for all undergraduate students and upgrading data science education in graduate schools.

M&D Data Science Center

Center Director
Specially Appointed Professor,Tokyo Medical and Dental University

Satoru Miyano

Division of AI and Big Data Research
Division of Multidimensional Biological Data
Division of Health Intelligence
Division of Data Science Algorithm Design and Analysis
Division of Medical Statistical Mathematics Research
Division of Data Science ELSI Research
Division of Smart Hospital
Division of Data Science Strategy

M&D
Division of
Data Science
implementation Smart Hospital
Collaborative

Provision of a practical training
environment
Demands of the medical ﬁeld
Technical support

Educational
Organization(Faculty, etc.)
̶ Industry-academia
co-creative education̶
Internships, Collaborative
research

Division of AI and
Big Data Research

Data sharing
High-precisionmultidimensional medical data

TMDU
big data

Research support andinfrastructure development

Division of HealthIntelligence

Social implementation

Research outcomes, provision of educational materials
Multidimensional biological data

M&D
Data Science
Foundations

Division of
Data Science
Strategy

Entrepreneurs

Industry

Research issues

M&D
Data Science
Practice
Collaborative

Provision of educational
materials

Division of
Data Science Algorithm
Design and Analysis

Division ofMultidimensional
Biological Data

Social implementation anddevelopment support

Division of Medical
Statistical Mathematics
Research

Division of
Data Science
ELSI Research

M&D Data Science Center3

Divisions/Departments
Division of AI and Big Data Research

M&D Data Science Center
Department of
AI Technology
Development (Core)
Specially Appointed Professor(Acting Department Head)

Department ofIntegrated Analytics(Core)
Specially Appointed
Professor

Satoru Miyano

Associate Professor

Takanori Hasegawa

Assistant Professor

Satoshi Ito

Project Researcher

Yoko Tanaka
Technical Assistant

Asako Suzuki
Visiting Professor

Seishi Okamoto(Fujitsu Ltd.)

Visiting Professor

Koji Maruhashi(Fujitsu Ltd.)We develop new mathematical methods using bioinformatics and artificial intelligence
technologies for integrated analysis of multidimensional and ultra-heterogeneous big datain the medical and biological field. Through the analysis using bioinformatics, statisticalscience, and machine learning on advanced information processing technologies such as
supercomputers and GPUs, we aim to elucidate biological and life systems and immune
profiles for cancer, aging, and chronic critical illness for the development of drug discovery
and new therapeutic strategies.

Satoru Miyano

Research Topic

Technical Assistant

1. Knowledge discovery from big data using supercomputers and artificial intelligence
technology
2. Elucidation of biological/life systems and immune profiles of cancer, aging, and chronic
critical illness by mathematical modeling
3. Large-scale data analysis of whole genome/exome, single-cell transcriptome, proteome
data, etc.
4. Systems modeling and simulation of disease states
Development and applicationof mathematical methods forbiological big data
The pathophysiology of thedisease is a situation in which
control abnormalities affecteach other in a complex
manner due to the influenceof multiple genes and theenvironment including theintestine and skin, and in particular, cancer is a state that deviates from integrated control
as a system. We integrate ultra-multidimensional and ultra-heterogeneous biological big
data such as genome and other omics data, pathological conditions, and environmental
data through the development of advanced computational science strategies and information processing technologies such as supercomputers. Our research will elucidate the mechanisms of biological/life system failures, called pathological conditions, and to develop drug
discovery and therapeutics.

Joint Research Coronavirus Task ForceAs a member of the Collaborative Research Coronavirus Task Force, an emergency project toprotect society from novel coronaviruses, we have conducted all preliminary whole genome
and transcriptome analyses. Data from this task force is increasing daily, and by FY2022,
over 1,000 whole genome samples have been completed; another 4,000 samples will be analyzed in FY2023, resulting in 10,000 whole genome data including controls.

4 M&D Data Science Center

Junior Associate
Professor

TakashiKamatani

Momoko Suguyama

Medical big-data analysis and evidence-based personalized medicine are crucial to settle
on social issues that we face, such as the population decline and super-aging challenge.
Our mission of Department of AI Technology Development is to develop the statistical andartificial intelligence methodologies that can be used in biomedical research and to identify
evidence if precision medicine based on biomedical data analysis.
The main research areas of the Department of AI Technology Development include: 1.
Development of the statistical and artificial intelligence methodologies that can be used inbiomedical research; 2. Uncovering complex mechanism of diseases (e.g., cancer) based on
biomedical data analysis.

Develop statistical and artificial methodologies for precision
medicine
To improve efficiency of medical treatment and preventive
care, genomic personalized
medicine has been drawn alarge amount of attention. Oneof our research topics is developing computational strategies
for patient specific analysis andprovide data-driven evidence
to achieve effective precision
medicine.

Network Biology
Gene regulatory network is crucial for understanding complex disease mechanisms because
the molecular mechanisms of diseases involve many genes intricately connected in a molecular network rather than the abnormality of a single gene. We conduct network biology
studies, such as development of computational approaches for gene regulatory network
estimation and network-based marker identification, especially we focus on interpretation ofmultilayer massive networks.

Department of Medical Data Analytics (Cooperative)
Ukihide Tateishi Professor (Department of Diagnostic Radiology and Nuclear Medicine)
Yoshikazu Nakajima Professor (Department of Biomedical Informatics)

Division of Multidimensional Biological Data
Department of Multiomics (Cooperative)
Tetsushi Furukawa Executive Director (Director, Institute of Research)
Jun Nakabayashi Professor (Department of Mathematics)

Construction of integrated analysis platform for
M&D data and promotion of cooperation system

Department of Genomics (Cooperative)

Medical and dental sciences and medical research are entering a new era in terms of both
quality and quantity of information. It is common to acquire and use large amounts ofbiological information, such as genomic information analysis and single cell analysis, which
can be integrated to obtain new knowledge and new findings. We will then promote theconstruction of the necessary information education and infrastructure.

Department of Transcriptomics (Cooperative)

Toshihiro Tanaka Professor (Department of Human Genetics and Disease Diversity)

Itoshi Nikaido Professor (Department of Functional Genome Informatics)

M&D Data Science Center

5

Divisions/Departments

M&D Data Science Center

Division of Health Intelligence

Division of Data Science Algorithm
Design and Analysis

Department of AI
Systems Medicine(Core)

Department of Data
Science Algorithm
Design and Analysis(Core)

Professor

Hideyuki Shimizu

We approach questions from the viewpoint of medical professionals by integrating largescale data acquisition, mathematical modeling, and validation experiments. We are also
investing heavily in science and medicine’s future by emphasizing education inside andoutside our laboratory. Please visit our website (https://shimizuhideyuki-lab.org/) for more
information.

Research Projects

Professor

Hideo Bannai

AI-based stratification for personalized medicine (clinical informatics)
Junior Associate
Professor

Satoshi Ohno

Specially Appointed
Assistant Professor

Hirohumi Aso

Project Researcher

Daisuke Koga

Based on our expertise as physicians, we are developing analytical methods and tools to
address issues unique to healthcare data and conducting research for personalized medicine.
For example, by using AI to learn breast cancer gene expression data, we developed a method
to stratify stages based on only 23 genes, which was broadcasted in NHK news and Nikkei
newspaper.
AI Drug Discovery

Assistant Professor

Diptarama
Hendrian

Our research focuses on developing algorithms and data structures for efficiently processing
and analyzing large scale data.

String Algorithmics
Algorithms are an essential component of data science, especially for handling large data
sets. Our aim is to design algorithms and data structures that are both effective and efficient,to help manage and analyze various types of large-scale medical data such as sequence andsensor data. Our main research topic is on time and space efficient algorithms for patternmatching/search/discovery, data compression, and compressed data processing. We also
study combinatorics on words as a theoretical background for algorithmics on strings.
Pattern matching/search/discovery

We study efficient algorithms and index structures for pattern matching and string information retrieval, used for example in keyword search, as well as finding patterns that characterize the data, based on various appropriate definitions of “occurrence”.

We developed LIGHTHOUSE, an AI drug discovery system that “illuminates” target compounds from a vast chemical space. This study was widely broadcasted in many media.
We are extending LIGHTHOUSE to develop a drug discovery platform that incorporates
the laws of physiochemistry. We have begun to take on the challenge of designing not only
small-molecule drugs but also more complex molecules such as nanobodies.
Data compression and compressed data processing

Technical AssistantThrough data compression, we aim not only to save storage space and communication
bandwidth required for storing and transferring the data, but also to “compress” even thetime required for computation, by processing the data “as is” in compressed form.

Yasunari Wakizaka

Understanding Multifactorial Diseases by Integrating Multi-omic Data

We aim for a comprehensive understanding of diseases as a failure of biological systems
using large-scale data.
We take a systems biology approach with differential equations and other applied mathematical methods to elucidate disease mechanisms and to predict drug targets.

6 M&D Data Science Center

M&D Data Science Center

7

Divisions/Departments

M&D Data Science Center

Division of Medical Statistical Mathematics
Research
Department of
Biostatistics (Core)
Professor

Kunihiko Takahashi

Junior Associate
Professor

Tatsuhiko Anzai

Assistant professor

Yuki NishidaWe aim to contribute to M&D sciences,through developing and practicing
effective statistical methods for data
analysis to solve statistical problems
from a wide spectrum of medical,
dental, and healthcare research.

Development of biostatistical methods for M&D
data science
Our department is carrying out methodological research in biostatistics,
including geographical data analysis
in spatial epidemiology, disease surveillance and monitoring of infectious,
real-world data analysis of complex
and unistructural data in medicine,meta-analysis for integration ofevidence and models, dynamic modeling in health science. We also develop
software and are exploring application
thereof in various fields in healthcare.

Division of Data Science ELSI Research

Practice of Biostatistics
in M&D science

Division of Smart Hospital

Our department are engaged in many
projects in collaboration with medical,
dental, and healthcare professionals and scientists. We are bridging biostatistical design andanalysis to a wide variety of statistical problems in clinical research, clinical trials, observational studies, and laboratory research in medicine, and aims to contribute to health sciences through biostatistics in M&D data science by effective use of data.

Department of Smart Hospital Development (Cooperative)

Department of Data Science ELSI Research (Cooperative)
Masayuki Yoshida Professor (Department of Life Sciences and Bioethics)

Ryuji Koike Professor (Health Science R&D Center)
Masumi Ai Professor (Department of Insured Medical Care Management)

Division of Data Science Strategy
Department of Biostatistics (Cooperative)
Akihiro Hirakawa Professor (Department of Clinical Biostatistics)

Department of Data Science Strategy (Cooperative)
Kaori Iida Professor (Open Innovation Center)
Atsuhiro Kinoshita Professor (Department of Educational Media Development)

Department of Statistical Genetics (Cooperative)
Yuta Kochi Professor (Department of Genomic Function and Diversity)

Visiting Academic Staff

Department of Epidemiology (Cooperative)
Takeo Fujiwara Professor (Department of Global Health Promotion)
Jun Aida Professor (Department of Oral Health Promotion)

8 M&D Data Science Center

Heewon Park Visiting Professor (Sungshin University)

M&D Data Science Center9

M&D Data Science Center

Graduate School Admissions
Each of the M&D Data Science Center’s core departments has established education and research departments in the University’s Graduate School of Medical and Dental Sciences, and accepts graduate and research
students. The Graduate School of Medical and Dental Sciences welcomes students from diverse educational
backgrounds, not limited to medicine and dentistry and students enrolled in the Master’s Program: Health
Sciences and Biomedical Engineering (2 years) can continue their studies to the Doctoral Program: Medical
and Dental Sciences Track (4 years) or Doctoral Program: Biomedical Sciences and Engineering Track (3years).

Campus/Access Map

立体駐車場入口

Entrance of Multi-story Parking Garage

3号館

B棟

Building 3

A棟

Building B

Building A

本郷門

D棟

Hongo Gate

Building D

559

R

M&Dタワー
M&D Tower

湯島地区

5号館

西門

8号館北
8号館南

517

Building 8 South

Building 6

湯島門
（正門）

本
(H Hon 郷通
on go りgo D
St orireet)Building 8 NorthMAX

Yushima Gate

2号館

北門

H

Yushima Campus

6号館

Building 5

West Gate

外堀門①

Sotobori Gate

立体駐車場
神田川 Kandagawa (Kanda River)

TMDU Garden

23号館（看護師宿舎）

Applicants must have graduated or be expected to graduate from the School of Medicine, Schoolof Dentistry, School of Veterinary Medicine (6-year program), or School of Pharmacy (6-year
program), or have completed or be expected to complete a master’s degree (or be recognized ashaving equivalent or higher academic ability). Students can obtain a Doctoral Degree (Medical
Science, Dental Science, Mathematical Medical Science, Philosophy) by submitting a doctoral
thesis within the term.

7号館

Building 23 (Nurses Dormitory)

Building 7

21号館（生体材料工学研究所）
Building 21
Institute of Biomaterials
and Bioengineering

Sotobori 外堀通
Dori り
(So
tob

ori

Stre

et) お茶の水門
Ochanomizu Gate

10号館

聖門

Building 10

Hijiri Gate

東京メトロ丸ノ内線
御茶ノ水駅
Subway Ochanomizu
Station

駿河台地区

お
茶
の
水
橋

Building C

e

22号館

C棟（機能強化棟）

南門

South Gate

ano

miz

uB

ridg

Building 22
交番

Police Box

聖
橋

JR御

茶ノ
水駅

JR O

chan

omiz

u Sta

Hijiribashi (Hijiri
Bridge)Integrated Analysis/Biostatistics/AI Systems Medicine

Sotobori Gate

知と癒しの庭

Surugadai Campus

Doctoral Program: Medical and Dental Sciences Track

Multi-story
Parking
Garage外堀門②Och

Applicants must have graduated or be expected to graduate from a four-year undergraduate program (or be recognized as having equivalent or higher academic ability).
For the Master’s Program: Health Sciences and Biomedical Engineering, students must contact
and receive permission from prospective supervisors in their desired department before applying
to take the entrance examination. Students can obtain a Master’s degree (Medical Science, Dental
Science, Oral Health Care Science, Science, Engineering, Medical Laboratory Science) by submitting a master’s thesis within the term.

Building1 East

1号館西Building1 West

Master’s Program: Health Sciences and Biomedical Engineering
Integrated Analysis/Biostatistics/AI Systems Medicine/AI Technology/Data Science Algorithm
Design and Analysis

1号館東Building 2

North Gate

IIt

tion

Station-Ochanomizu
Subway Shin

新東
御京
茶メ
ノト
水ロ
駅千
代
田
線

Doctoral Program: Biomedical Sciences and Engineering Track
AI Technology/Data Science Algorithm Design and Analysis

Applicants must have completed or be expected to complete a master’s degree (or be recognized
as having equivalent or higher academic ability). Students can obtain a Doctoral degree (Science,
Engineering, Medical Laboratory Science, Oral Health Care Science) by submitting a doctoral
thesis within the term.
Yushima and Surugadai Campuses• JR Line Ochanomizu Sta.
• Subway Marunouchi Line Ochanomizu Sta.
• Subway Chiyoda Line Shin-Ochanomizu Sta.

10 M&D Data Science Center

M&D Data Science Center11