[Fundamental technologies for COVID-19] Year Started : 2020

Masanori Arita

Data Platform for Counteracting Virus Infection with Ultrasensitive Measurements

Research Director
Masanori Arita

Professor
National Institute of Genetics
Research Organization of Information and Systems

Collaborator
Takashi Abe Professor
Faculty of Engineering Department of Engineering
Niigata University
Jun Uetake Associate Professor
Field Science Center for Northern Biosphere
Hokkaido University
Ryosuke Omori Associate Professor
International Institute for Zoonosis Control
Hokkaido University
Haruo Suzuki Associate Professor
Faculty of Environment and Information Studies
Keio University
Ryo Honda Professor
College of Science and Engineering
Kanazawa University
Shun-ichi Matsuura Senior Researcher
Research Institute for Chemical Process Technology
National Institute of Advanced Industrial Science and Technology (AIST)
Outline

We detect viruses from various urban environments (sewage, public spaces, medical sites, etc.) by utilizing new ultra-sensitive genome amplification technology, acquire their genome information, and publish data from public databases and portal sites that we cooperate internationally. We will also analyze genome mutations and build a mathematical model for epidemic countermeasures. As a whole, we will build a data infrastructure that can handle various emerging infectious diseases.

Seiya Imoto

Research on Conquering Coronavirus Disease by Advanced Genomic Analysis and Artificial Intelligence

Research Director
Seiya Imoto

Professor
The Institute of Medical Science
The University of Tokyo

Collaborator
Yukinori Okada Professor
Graduate School of Medicine
Osaka University
Seishi Ogawa Professor
Graduate School of Medicine
Kyoto University
Koichi Fukunaga Professor
School of Medicine
Keio University
Satoru Miyano Specially Appointed Professor
M&D Data Science Center
Tokyo Medical and Dental University
Outline

We will construct the world-class COVID-19 database with 5,000 clinical samples and multi-omics data. In this database, we will conduct GWAS considering SNPs, viral genome, and clinical information to clarify the genetic background of COVID-19 severity in Japanese. Furthermore, we will construct an artificial intelligence system that can predict COVID-19 severity and extend it to explainable AI (XAI) to complete the information infrastructure for controlling infectious diseases with big data.

Hiroyuki Katayama

Creative Development for Detection and Removal of Viruses in Environment Using New Materials

Research Director
Hiroyuki Katayama

Professor
Graduate school of Engineering
The University of Tokyo

Collaborator
Takashi Kato Professor
Graduate school of Engineering
The University of Tokyo
Katsuya Teshima Director´╝ĆProfessor
Interdisciplinary Cluster for Cutting Edge Research, Research Initiative for Supra-Materials
Shinshu University
Yuta Nishina Research Professor
Research Core for Interdisciplinary Sciences
Okayama University
Eiji Haramoto Professor
Graduate Faculty of Interdisciplinary Research
University of Yamanashi
Outline

Our team will develop highly sensitive detection methods for the novel coronavirus. New materials will be developed that can control adsorption and desorption of viruses to establish efficient concentration methods. These will be achieved by self-assembled polymers, inorganic crystals and functionalized carbon that have high adsorptivity and/or high water permeability while blocking viruses. Furthermore, in order to efficiently remove viruses, we will develop new materials such as polymer nanostructured films, photocatalytic inorganic crystals, and carbon filters to realize excellent virus removal and inactivation performance.

Eiryo Kawakami

Development of data-driven infection-control strategies based on stratification of preclinical populations

Research Director
Eiryo Kawakami

Team Leader
Advanced Data Science Project
RIKEN

Collaborator
Atsushi Kaneda Professor
Graduate School of Medicine
Chiba University
Kei Sato Professor
The Institute of Medical Science
The University of Tokyo
Shinji Nakaoka Associate Professor
Faculty of Advanced Life Science
Hokkaido University
Outline

COVID-19 is characterized by a diversity of symptoms, with the majority of infected people remaining asymptomatic or mild, while some become severe or fatal. Compared to substantial data collected in hospitals after the onset, data before the onset has not been sufficiently accumulated, and no methodology has been established to assess the risk of developing illness and becoming severe for each individual in advance. In this study, we will collect saliva and nasopharyngeal swab samples from thousands of healthy and asymptomatic individuals by exploiting the large-scale socieal PCR testing system that we have already started to build. We will comprehensively measure human- and microbial-derived DNA and RNA contained in these samples, and develop a method to evaluate the individual risk of developing illness and becoming severe before the onset of disease through an approach that combines machine learning with statistical and mathematical modeling. We will also develop a model for predicting epidemic trends that takes into account the diversity of the disease risk for each individual, with the aim of creating personalized infection-control strategies that determine when, who, and what interventions are most effective.

Makoto Jinno

Research on mass-automated testing systems considering viral mutation

Research Director
Makoto Jinno

Professor
School of Science and Engineering
Kokushikan University

Outline

The spread of the novel coronavirus (SARS-CoV-2) has revealed issues regarding the number of polymerase chain reaction (PCR) tests that can be conducted per day and the testing system and organization in Japan. This research aims to realize a mass-automated testing system by utilizing robotics technology and information management technology to prepare for future virus mutations. We present an innovative concept for constructing a new mass-automated test system with system flexibility and continuity and verify the effectiveness of the proposed concept using a partial model. To realize the mass-automated testing system, first, the requirements and technology trend surveys and issues will be extracted, and a new concept will be created from the results. Second, the element technology development of the sample accumulation (pre-stage processing) process system and the PCR inspection process system, which are the key elements for efficiency improvement and system flexibility in all inspection processes, will be conducted. Finally, an integrated system including inspection information will be constructed, and its effectiveness will be verified using the partial model based on the concept. From the results of this research, it will be possible to realize a safe and secure society that can quickly and accurately grasp the mass occurrence of future coronavirus mutations and the next pandemic.

Toshiya Senda

A novel strategy to inhibit viral replication by controlling GTP metabolism

Research Director
Toshiya Senda

Professor
Institute of Materials Structure Science
High Energy Accelerator Research Organization

Collaborator
Atsushi Kawaguchi Professor
Faculty of Medicine
University of Tsukuba
Atsuo Sasaki Project Professor
Graduate school of Media and Governance
Keio University
Koh Takeuchi Professor
Graduate school of Pharmaceutical Sciences
The Unidersity of Tokyo
So Nakagawa Associate Professor
School of Medicine
Tokai University
Yoshio Hayashi Professor
School of Life Sciences
Tokyo University of Pharmacy and Life Sciences
Outline

The development of drugs against SARS-CoV-2 is underway worldwide, however, there is no specific drug for SARS-CoV-2 yet. This is because it takes time to create a drug for a specific target. To respond rapidly to emerging infectious diseases such as COVID-19, it is necessary to establish general therapeutic strategies applicable to viral infections based on a new concept. Since GTP is a cellular energy molecule used for protein synthesis including viral proteins, we focused on host energy metabolism, on which viruses depend for their replication. We consider that regulating GTP metabolism may inhibit the synthesis of viral proteins and could be a general strategy for antiviral therapy that can apply to any type of virus. In this research, we will develop drugs based on this concept. Furthermore, by combining the development of novel compounds targeting viruses, we aim to the synergistic effects of two different drugs and establish a therapeutic strategy that is widely applicable to viral infections including COVID-19.

Makoto Tsubokura

Development of the Integrated Risk Assessment System for the Viral Droplet Infection on a Supercomputer and its Social Implementation

Research Director
Makoto Tsubokura

Professor
Graduate School of System Informatics
Kobe University

Collaborator
Akiyoshi Iida Professor
Graduate School of Engineering, Department of Mechanical Engineering
Toyohashi University of Technology
Kazuhide Ito Professor
Faculty of Engineering Science
Kyushu University
Naoki Kagi Professor
School of Environment and Society
Tokyo Institute of Technology
Masashi Yamakawa Professor
Faculty of Mechanical Engineering
Kyoto Institute of Technology
Outline

In the era of coexistence with emerging infectious diseases represented by COVID-19, we will develop a system that utilizes a supercomputer, which can be a common social foundation for risk assessment of droplets and droplet nuclei infection. Furthermore, we will propose measures to reduce the risk of infection in the age of living with emerging virus by utilizing the obtained system. In order to control and reduce the risk of infection of residents to COVID-19 in the indoor environment, the transport dynamics of viral droplets and droplet nuclei, which was difficult to directly observe and evaluate in the past, are evaluated by thermal fluid numerical simulation. The accuracy and reliability of the risk assessment will be drastically improved by integrating the simulation system by comprehensively analyzing the pharmacokinetics, immune system response, and physiological response associated with infection. The developed system is implemented on a supercomputer system to reduce the turnaround time for the risk assessment and to increase the number of corresponding test cases compared to conventional experiments and simulations. It will also be possible to create big data for AI learning.

Kouhei Tsumoto

Development of Functional Regulation and Sensing of Viruses based on Antibody-Based Molecular Design

Research Director
Kouhei Tsumoto

Professor
Graduate School of Engineering
The University of Tokyo

Collaborator
Satoshi Takahashi Professor
Institute of Multidisciplinary Research for Advanced Materials
Tohoku University
Takao Hashiguchi Professor
Institute for Life and Medical Sciences
Kyoto University
Hideo Fukuhara Associate Professor
International Institute for Zoonosis Control
Hokkaido University
Outline

To realize Antibody-Based Molecular Design targeting new coronaviruses, we develop the sensing and drug design technologies for creating novel diagnosis and therapeutics through miniaturizing functional antibodies. We will integrate the following research areas; 1. antibody engineering, 2. structural biology, 3. organic chemistry, and 4. single-molecule imaging. This study will enhance our understanding of molecular mechanism of the virus infection and principle of miniaturization of antibodies.

Takeharu Nagai

Development of a technology platform for simple diagnosis of infectious diseases at home

Research Director
Takeharu Nagai

Professor
SANKEN (The Institute of Scientific and Industrial Research)
Osaka University

Collaborator
Kunihiko Nishino Professor
SANKEN (The Institute of Scientific and Industrial Research)
Osaka University
Daisuke Fujiwara Lecturer
Graduate School of Science
Osaka Prefecture University
Outline

In order to prevent the spread of various infectious diseases including the novel coronavirus and to reduce the pressure on medical institutes, there are needs to develop a simple diagnostic procedure and system by which a patient can perform an examination by himself/herself at home. In this project, target peptides that can recognize the molecular characteristic of various pathogens will be systematically selected from a gene library and incorporated into chemiluminescent proteins to construct a platform that will allow rapid development of light emitting molecular sensors that can recognize each pathogen. Furthermore, a smartphone-based diagnostic system will be developed that can easily confirm the infection at home by detecting the luminescence signal. These technologies will build the foundation to support the nation to coexist with the emerging and re-emerging infectious diseases, by the visualization of infection information and construction of infection prediction maps using smartphones.

Takeshi Noda

Development of human organoid-based, respiratory organs-on-a-chip for understanding viral pathogenesis

Research Director
Takeshi Noda

Professor
Institute for Life and Medical Sciences
Kyoto University

Collaborator
Mototsugu Eiraku Professor
Institute for Life and Medical Sciences
Kyoto University
Shimpei Gotoh Professor
Center for iPS Cell Research and Application
Kyoto University
Ryuji Yokokawa Professor
Graduate School of Engineering
Kyoto University
Outline

Understanding the SARS-CoV-2 replication mechanisms in human is necessay to develop specific therapeutics for COVID-19. Currently, several cultured cell lines and primary cultured cells are used as SARS-CoV-2 infection models. However, there is no suitable model that reflects the infection and replication in human body. In this study, to elucidate the SARS-CoV-2 replication in the human respiratory tracts, we aim to develop a “respiratory organs-on-a-chip” equipped with nasal cavity, respiratory tract, and lung organoids that are differentiated from human ES cells and iPS cells. Then, using the respiratory organs-on-a-chip, we will analyze the mechanisms of SARS-CoV-2 replication pathogenesis. Such a human respiratory organs-on-a-chip, which reproduces the human upper and the lower respiratory tracts, will be an innovative tool for researches on various respiratory viral infections.

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