In my previous post, I discussed medical DX and digitalization, focusing on next-generation AI technologies known as “generative AI” and “foundation models” and how they can create value when combined with “medical and health data.” I explained three key terms of next-generation digital healthcare.
This time, I will explain what new values humanity can create by acquiring this new technology and combining it with medical and health data.
Innovative Services and Businesses Created
What Digital Can Do for Health: Digital Medicine and Digital Therapeutics
Lifestyle diseases are caused by daily habits such as unhealthy eating, lack of exercise, smoking, and excessive drinking. Examples include hypertension, diabetes, heart disease, and dyslipidemia (high cholesterol). Since lifestyle habits are the cause, improving them, i.e., behavioral change, is the fundamental key to preventing and treating lifestyle diseases.
While digital technology cannot directly remove cancer or pharmacologically eliminate viruses from the body, it cannot make one quit smoking through surgery or make one eat vegetables and exercise more through medication. Our higher brain functions, cognitive functions, are responsible for our choices and actions. Therefore, supporting or influencing our cognitive functions and promoting behavioral change is crucial for the fundamental prevention and treatment of lifestyle diseases. Digital medicine and digital therapeutics support this.
Medical Device Programs to Promote Behavioral Change
Medical device programs to promote behavioral change (also known as Software as a Medical Device (SaMD)) aim to improve health by precisely understanding an individual’s health status and providing optimized interventions.
Specifically, AI analyzes data collected from smartphones and wearable devices and provides personalized advice and reminders to users. This makes it easier for users to continue healthy behaviors, effectively managing preventive medicine and chronic diseases.
Policy Trends
The Japanese government is actively promoting the development and dissemination of medical device programs to promote behavioral change in the healthcare field. For example, the Ministry of Health, Labour and Welfare and the Ministry of Economy, Trade and Industry announced the “DX(Digital Transformation) Action Strategies in Healthcare for SaMD (Software as a Medical Device) 2”, or “DASH for SaMD2”, in September 2023. The primary goals are to enhance the predictability of regulatory approval and insurance coverage, and to promote development and market introduction both domestically and internationally. This includes concepts such as two-stage approval, guidance for home-use SaMD, trial priority reviews, strengthening PMDA systems, and supporting international expansion. This aims to achieve the early practical application and market acquisition of innovative SaMD (Ministry of Health, Labour and Welfare & Ministry of Economy, Trade and Industry, 2023).
Additionally, in the 2024 medical fee revision, the “Medical Device Instruction and Management Fee” has been introduced to evaluate the use of SaMD, ensuring that treatments using medical devices are appropriately evaluated and compensated as medical fees (Ministry of Health, Labour and Welfare, 2024).
Furthermore, the Ministry of Economy, Trade and Industry has formulated the “Guidelines for the Development of Medical Device Programs to Promote Behavioral Change in the Healthcare Field.” These guidelines support developers in efficiently developing products that comply with regulations, detailing processes from product design and development to market launch (Ministry of Economy, Trade and Industry, 2023).
With such support from the public sector, it is our role as healthcare providers and entrepreneurs to create and deliver new value to patients!
Examples of SaMD for Promoting Behavioral Change
Next, let’s look at specific examples of how SaMD can be useful in promoting behavioral change.
The figure below shows how personalized AI uses individual data from A, B, and C to send optimal messages. For example, personalized AI understands A’s preference and cognitive tendencies, suggesting a salad by saying, “You will look even cooler if you lose weight!” It suggests a hot pot to B, knowing their dietary trends, saying, “A hot pot is warming this season,” and encourages C to eat vegetables by saying, “Your next blood test will be worrying if you continue this diet.”
Personalized AI uses individual lifestyle and medical information to promote optimal behavioral change. By understanding individual cognitive characteristics, it can promote behavioral change through personalized advice and nudges, supporting optimal actions based on personal risk preferences and time discounting, helping maintain a healthy lifestyle.
Digital Technology for Personalized Medicine
As I mentioned before, digitalization, especially next-generation AI technologies like “generative AI” and “foundation models” combined with “medical and health data (especially time-series data),” enables more detailed personalized medicine.
Precision medicine provides optimal treatment by considering individual genetic, environmental, and lifestyle differences. Unlike conventional “one-size-fits-all” treatments, it emphasizes personalized medicine perspectives.
At the core of precision medicine is genome analysis. Additionally, the use of big data and AI allows the development of algorithms to analyze vast amounts of medical data and find the best treatment for each patient. This enables more accurate diagnoses and treatments. By designing tailor-made treatment plans based on each patient’s characteristics, it is expected to improve treatment effects and reduce side effects.
Advances in medical DX also support precision medicine. With the spread of electronic health records (EHR), doctors can quickly access patient medical data, monitor health status in real-time through wearable devices and smartphone apps, and create individual treatment plans. The use of telemedicine and online medical services is also expanding, providing specialized medical care beyond geographical constraints.
The benefits of precision medicine and personalized medicine include improved treatment effects, reduced side effects, and early detection and prevention of diseases. Of course, there are challenges such as cost, data privacy, and technology dissemination.
Precision medicine is gaining attention as an innovative approach to the future of healthcare, realizing more effective and efficient healthcare delivery and contributing to improving patients’ quality of life (QOL) with the advancement of digital technology. By incorporating personalized medical perspectives, more personalized treatment becomes possible, providing optimal care for each patient.
Passing on the Healthcare We Enjoy to the Next Generation: Open Innovation
Previously, I introduced “Formula of Life” technology, which models the overall picture of individuals by utilizing vast personal data ranging from wearable devices and behavioral economics-based cognitive tendencies to time-series data and genomic-level molecular data.
Wilhelm Röntgen, the discoverer of X-rays, believed his technology should contribute to the advancement of science for all. Today, next-generation AI technologies such as foundation models, represented by large-scale language models like ChatGPT, are considered essential technologies that humanity should share. OpenAI, which developed ChatGPT, has a mission statement: “Our mission is to ensure that artificial general intelligence benefits all of humanity.”
I aim to use ” Formula of Life” as a foundation for AI technology in the health and medical field, as an essential technology that humanity should share, to contribute to the sustainability and development of healthcare through open innovation.
In economics and information technology, there is a term “network effects.” Network effects refer to the phenomenon where the value of a product or service increases as the number of users grows. For example, the attractiveness of social media platforms increases as more friends participate, creating a virtuous cycle that attracts new users.
Similarly, in large-scale learning models, the more data input, the more accuracy improves, and more value can be provided. Network effects become an important factor in increasing overall value as the number of users grows.
In the future, it will be more important to integrate various data related to health and healthcare and to combine interdisciplinary expertise and technology for co-creation and open innovation.
Healthcare Business Development and Startup Support Program: TrueNorth Innovation
My company, Decades Inc., offers the TrueNorth Innovation program, aimed at healthcare professionals, researchers, and business companies passionate about turning innovative ideas into reality.
TrueNorth Innovation supports business development for healthcare professionals, researchers, and business companies through the TrueNorth Meet program. It helps healthcare professionals solve challenges in clinical practice, researchers bring innovative technologies and ideas to market, and business companies develop new businesses in the health and medical field step-by-step.
If you are interested in creating innovative digital products using medical AI and data science as introduced in my previous and this post, please contact us for TrueNorth Meet Phase 1 (Free).
References
– Ministry of Health, Labour and Welfare & Ministry of Economy, Trade and Industry. (2023). ‘Strategy Package to Promote the Practical Application of Program Medical Devices 2’. Available at: [PMDA Website](https://www.pmda.go.jp/review-services/drug-reviews/review-information/devices/0018.html) (Accessed: 21 May 2024).
– Ministry of Health, Labour and Welfare. (2024). Medical Fee Revision 2024. Available at: [MHLW Website](https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/0000067910.html) (Accessed: 20 May 2024).
– Ministry of Economy, Trade and Industry. (2023). Guidelines for the Development of Medical Device Programs to Promote Behavioral Change in the Healthcare Field. Available at: [METI Website](https://www.meti.go.jp/policy/mono_info_service/healthcare/202303.55.pdf) (Accessed: 20 May 2024).
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