Bio-Innovation Policy Recruiting students for the academic year 2019

Assosiate Professor Shingo KANO
TEL: +81-4-7136-3715
E-mail: kano{at}


【Key Words】Innovation Policy, Intellectual Policy, Technology Standard. Regulation

In our laboratory, we conduct social scientific research on innovation in life science and medicine. All research subjects of the students fall within this category. The theme selection is based on the student’s autonomy. The student, mentors and lab members work together to reconstruct the "vague awareness of the issue" of the student as "Research Questions" to establish the theme as something acceptable as a thesis by thoroughly examining the backgrounds and methods. An introduction of the research areas is as follows (for more detailed examples of themes, please refer to our homepage).

Regarding the efforts to make use of intellectual properties for the development of industries in the field of life science, the key conundrum is the system design; how should we design a value chain of the “National Innovation System” that would connect the various stakeholders in basic research and development of products together? Beyond empirical case studies, a new framework is required for effective IP strategies, technology transfer systems, translational researches, regulatory designs, corporate strategies, and science & technology policies in order to link research outcomes to industries. Based on these perceptions, we realize the importance to readdress the basic question of how innovation itself could or should be measured. Furthermore, in order to plan future innovation policies and corporate strategies, we believe that it is essential to analyze the relationships or interactions between subjects that are responsible for innovation activities; organizations and institutions; innovators and regulators; innovators and users.

Researches in our lab involves the three following areas:
(1) Knowledge Management (KM) in the life science field
Knowledge Management is the basis for discussing intellectual property strategies, corporate strategies, and science & technology policies in the field of life science. To give an example of our research in this area, we have studied the relationship between products and patents (Product-Patent Linkage) in the pharmaceutical field, and an empirical analysis has been conducted on the life cycle management (LCM) of drugs by testing combinations of patent strategies and regulatory strategies. We have also generalized the results by modeling and analyzing the interaction between corporate knowledge managements and science & technology policies by utilizing knowledge cycles in other fields such as genetic engineering. The overall aim in this area is to develop new and workable "knowledge management cycles" for facilitating the utilization of research outcomes.

(2) Measurement of Medical Innovation (MMI)
Measurement of Medical Innovation is a research area aimed at grasping the actual state of innovation in the advanced medical field. As a means of conducting empirical analyses of patent strategies, industry-academia collaborations, and corporate strategies, we use patent-metrics and biblio-metrics utilizing patent data bases and literature data bases) with a focus on specific technologies, products or companies. We aim to empirically analyze innovation activities through developing methods for measuring R&D activities. In the current age of analytics, the need to establish or introduce various data-scientific methods for the acquisition and analysis of data is significant. Our laboratory conducts collaborative researches with data scientists in order to increase the efficiency and validity of our research. The data generated in advanced medicine includes research data on papers, patents, various databases, regulatory documents (e.g. guideline documents and documents generated in the process of reviewing / approving medical products), real world data, et cetera. Although we have experienced great improvement in data access over the years, the development of analytical frameworks and analytical models has been slow to catch up (i.e. we still need a lot of trial-and-errors about what and how we should analyze in order to achieve the intelligence we need). By combining orthodox and unique measurements, we work on data-oriented measurements of innovation.

(3) The National Innovation System (NIS)
We are conducting research on institutions / organizations, industry-academia cooperation, regulation, technical standards, science & technology policies which are all part of the National Innovation System. For example, technical standards and regulations need to be developed timely and efficiently for newly emerging science & technology; if not, they may become obstacles to practical applications, and may bestow direct and negative impacts on industrial competitiveness. In our laboratory, we regard regulatory systems as a critical subject in the NIS. We have redefined regulatory science as policy process of regulation, and have conducted analyses on the interactions between innovation and regulation. We are currently conducting research on the relationship between technology forecasting activities and the establishment of regulatory guidelines / technical standards; the composition process of technical standards / regulatory guidelines; the relationship between technical standards and regulations; the choice of regulatory paths in medical products and services; international comparison of regulations; and boundary organizations responsible for composition of rules.


The University of Tokyo
Graduate School of Frontier Sciences, The University of Tokyo

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