The 37th JPMA Policy Seminar Prospects for Next-Generation Medicine Pioneered by DX: New Challenges for Medical DX that Transcends Industry, Driven by Co-Creation
Demonstrating Value and Becoming a Global Model
The 37th JPMA Policy Seminar was held on March 10, 2026. In recent years, medical DX (Digital Transformation) has played a pivotal role in Japan's social security and industrial competitiveness. At this policy seminar, key persons from various positions discussed how to "quantify" the value of medical DX and accelerate its implementation in society, with a wide range of issues in mind, including AI (artificial intelligence) drug discovery and supply chain stabilization. The following is a transcript of the seminar.
(Titles are current at the time of the seminar)
The venue
Opening Remarks
Realization of sustainable social security
Chairman, Japan Pharmaceutical Manufacturers Association
Asuka Miyabashira
Faced with the challenges of rising healthcare costs and demographic change, Japan needs a system that makes more efficient use of limited resources. Medical DX is the foundation for such a system, and co-creation by diverse stakeholders is essential. Through efforts to quantify the value of Medical DX and to promote public understanding, JPMA hopes to encourage the optimal allocation of limited medical resources, leading to the realization of a sustainable social security system and the dissemination of a Japanese-style medical model.
Special Presentation] The Importance of Quantitatively Demonstrating the Effects, etc. of Improving Operational Efficiency and Management Efficiency through Medical DX and its Social Impact and Effects on the Public
Incentives to promote introduction
Member of the House of Representatives
Mr. Akihisa Shiozaki
The LDP's Joint Project Team (PT) for the Promotion of Health and Medical Information Systems has proposed the promotion of migration to cloud-native systems, hospital DX support, and the establishment of a national medical information platform.
The Ministry of Health, Labour and Welfare (MHLW) conducted a questionnaire survey on the actual status of AI and ICT (Information and Communication Technology) utilization, and found that in some areas, numerical data showed the effects of introduction, such as automation of operations in clinical data aggregation, efficiency of nursing care monitoring, and identification of vital signs. Based on this reality, in the FY2026 revision of medical fees, incentives for operational efficiency were incorporated into the reimbursement system: on the condition that nursing work is made more efficient through the use of ICT, the criteria for the assignment of nursing staff will be made more flexible by up to 10%. In addition, one physician administrative assistant can be included in the number of staff assigned to a maximum of 1.3 physicians through the introduction of a generative AI or voice input system.
The new electronic medical record information sharing service will allow physicians to refer to a wider range of information, such as medical information forms and discharge summaries. However, some in the field say that there is too much information to look through, so a summary function that instantly summarizes and presents the necessary information is expected to be implemented.
Electronic prescriptions are another major pillar of medical DX. Recently, data has quantitatively shown its contribution to improving the quality of medical care, such as the nearly 10 million duplicate medication alerts that have been shown to occur monthly (see graph).
Currently, efforts are underway to connect various medical-related databases. We would like to promote medical DX with you as an important infrastructure that is both offensive and defensive.
Keynote Speech] The Quantitative Impact of AI Drug Discovery: The Scale, Speed, and Knowledge Circulation Expanded by Tokyo-1 and the Transformation of Drug Discovery
Drug discovery research is greatly streamlined.
Zeureka Chief Technology Officer
Daisho Makiguchi
Although the amount of AI-related investment by pharmaceutical companies is increasing every year and AI in drug discovery research is being announced one after another, human and computational resources to validate these technologies are becoming a bottleneck. In addition, while AI demonstrates high accuracy in areas where there is an abundance of training data, there are many cases where there is no data in unexplored areas of new drug research and the utilization of such data is not successful. This is where "Lab-in-the-Loop," in which small amounts of high-quality data are produced, and the AI is made to learn and loop around, becomes important. In order for this loop to take root in research, not only the AI model, but also the computational resources, human resources, and operations will be essential.
In order to respond to these social issues, we are supporting the circulation through a service called "Tokyo-1," which provides high-specification GPU (image processing semiconductor) supercomputers and community management. Two years have passed since its launch, and in addition to the GPU supercomputer, the company is now providing DX solutions and a co-creation and collaborative community to nurture human resources who can use these solutions.
There, multiple companies regularly hold technology introductions and discussions under the rules of "participating, teaching, and helping each other. An executive board that brings together the management level is also held to share the enthusiasm of researchers and changes in the field. The mindset of researchers at each company has also changed significantly, and their efforts have become extremely active, with full docking on a billion scale and other highly accurate simulations and utilization of AI being implemented on a large scale as a matter of course.
Keynote Speech] The Role and Challenges of DX in Stable Supplies: Issues of Supply Chain Transformation
Supply and demand-integrated infrastructure
Director, IBM Japan
Healthcare & Life Sciences Leader
Mr. Shinchi Sasaki
The instability of the pharmaceutical supply is caused by a mechanism that structurally amplifies the gap between supply and demand. At the root of this is the disconnection of data. The cycle of over-ordering by the medical side at the time of an infectious disease outbreak, and then returning the product after the outbreak has subsided when the production is increased, is repeated because prescription data and shipment data are not connected, and the supply-demand balance on a regional basis is not visible. Returned product information is also not shared throughout the supply chain, and it is difficult to grasp data such as actual dosing data.
Visualization from the smallest unit, such as "shipment x region," is the starting point for understanding supply and demand. Furthermore, if sharing can be done across facilities, it is possible to eliminate uneven distribution of inventories by utilizing joint inventories on a regional basis. Such supply DX is not only a means of reducing costs, but also a part of regional healthcare and national security (ensuring a stable supply of pharmaceuticals). It is important to design a structure that is both efficient in normal times and resilient in emergencies.
There are three key elements to the solution: first, standardization and connection of prescribing and supply/demand data; second, establishment of national KPIs (key performance indicators) to measure the value of healthcare and supply stability; and third, design of incentives linked to results. To realize these three goals, a national-level pharmaceutical data linkage infrastructure is required. In 10 years' time, the national healthcare infrastructure will evolve into one that integrates supply and demand, and a crisis-resistant structure will be realized by linking healthcare and supply. In 10 years, a national healthcare infrastructure that integrates supply and demand will be realized, and a crisis-resistant structure will be realized by linking healthcare and supply.
Panel Discussion] Collaboration and policies to visualize the value of medical DX
Value quantification beyond the pharmaceutical industry
Moderator: Jun Ando, Editorial Writer, Nikkei Inc.
Panel discussion
Clarification of benefits
Ando: Why is it so difficult for Japan's medical DX to progress?
Shiozaki: Japan has universal health insurance, and the scale of insured medical care is large, so it takes time to implement medical DX while maintaining fairness and equity. However, now that the infrastructure has finally been established, we are entering the stage of showing the "way out" of what benefits there will be if it is introduced in the future.
Sasaki: Japan's medical data is probably the best in the world in terms of quality and comprehensiveness, but the problem is that they are not sufficiently linked. If data coordination can be promoted in the current medical DX, Japan's medical data infrastructure could quickly become a global model.
Makiguchi: Trying to tackle the issues of medical DX is easily perceived as additional work in the field. Since the current system and operational rules are cautious, it may be necessary to make the consent, anonymization, and review process for research and utilization more convenient.
Miyabashira: It is important to measure the value that medical DX brings as the "exit" mentioned by Dr. Shiozaki. First of all, users must feel the value before progress can be made. We would like to deliver the value to the public and patients through quantitative evaluation, and to use this as an opportunity to get the entire country moving.
Patient outcomes are the axis
Ando: Then, what should be quantified so that the benefits of medical DX can be easily conveyed to the general public?
Miyahashira: The potential of medical DX cannot be clarified by the industry alone. What should be quantified are the values that the public and patients can feel, such as improved efficiency of medical treatment and quality of medical services, in addition to the outcomes of treatment. We would like to work with various stakeholders beyond the pharmaceutical industry to quantify the value and ensure that the results are widely felt.
Sasaki: Ultimately, it is the value of patient health. I believe that DX and AI should be the driver, and that the collaboration of systems, companies, and medical care should be the goal.
Makiguchi: It is also important to show KPI according to the position of patients and healthcare professionals, and have them realize the importance of the system. It is also very important to explain privacy, purpose of use, access logs, etc., so that people understand that DX is the foundation of safety and efficiency.
Shiozaki: Medical DX is difficult because the various stakeholders are facing different directions. It is important to step into the motivation and design policies in detail in line with incentives. Visualization of value is nothing but the correct design of incentives.
(Authored and produced by Nihon Keizai Shimbun, Inc. (2026 Nikkei e-Advertising Special Edition))
