Current medicine deploys an outdated “find it, and then fix it” approach, in which the disease is diagnosed only after clinical symptoms onset, through treatments that reduce symptoms rather than address the root cause. This raises the question: What if we could extend our health status and prevent our disease before it begins? How do we leverage emerging technologies, especially AI, to help us achieve this?
Although many pioneer AI hope to create infinitely abundant commitments for the future of mankind, the most valuable abundance we can provide is healthy in itself, far beyond the scope of disease management. By shifting focus to the consumer focus in care continuity, AI has the potential to play a transformative role in preventive and personalized health solutions that affect the health of hundreds of millions of people around the world.
This is where “scientific health” comes into play – an accurate, data-driven approach that creates custom health plans by tracking human biology over time. In this promising field, AI is ready to play an increasingly powerful role.
The impact of consequences on individual health is not only an individual, but also a great economic impact. The 2016 Health Affairs Analysis estimates that health care has saved $71 trillion in 2 years from the health range in 2 years. A 2021 study published in Natural Aging focused on a year-long delay, based on a staggering $38 trillion in “willing to pay” measures.
Beyond Disease Management: The Hope of Scientific Health and Prevention
Our healthcare system excels in acute care but struggles with complex chronic diseases such as cardiovascular disease and Alzheimer’s disease, such as the interaction between genetics, lifestyle, environment and aging biology.
Alzheimer’s disease provides a compelling example of the importance of prevention. Despite billions of dollars in investment, drug treatment for advanced Alzheimer’s disease shows minimal benefits, weakly addressing symptoms rather than changing the disease trajectory. However, studies such as fingers and pointers have shown that multidomain lifestyle interventions combining nutrition, physical exercise, cognitive training and vascular risk monitoring can significantly reduce cognitive decline in high-risk populations. Preventing neurons from dying is easier to carry than replacing them after they disappear. The difference here is the way to intervene in an individual’s health journey – the earlier the better.
The CDC reports that 80% of heart disease, stroke and type 2 diabetes can be prevented by lifestyle changes. challenge? Our healthcare system is primarily waiting for clinical symptoms to emerge before the show, and people cannot get personalized insights that can guide effective prevention, even if they want them more now than ever.
In a decade-long study involving thousands of participants, we found that genetic variation significantly influences individual responses to lifestyle interventions, where the microbiome can predict weight loss success and can alter the trajectory of biological aging through targeted interventions. These insights underscore the power of AI-driven personalization, transforming healthcare from a level of all models to truly tailor-made models for individuals.
AI: A promoter of personalized prevention and safety interventions
When focusing on extending health status, our interventions must be different from those used to treat the disease. Since we are working with people in general, any intervention must have an excellent safety profile while still being effective.
Natural products (such as targeted supplements) are a source that can cleverly drive biological systems to healthier functions, often without the side effects of drug intervention. However, the effectiveness of these approaches can depend heavily on personalization, as the right combination is often key – only one change is often not enough to achieve the desired health benefits.
AI now enables real biological personalization by analyzing individuals’ unique genetic variation, microbiome composition and blood markers to create traditional lifestyle and nutritional advice that is suitable for all methods that cannot match. Where traditional ideas offer standardized solutions, your biology needs to be precise.
Real-world examples illustrate why this kind of personalization is important. For example, if you have any genetic variation that blocks vitamin D absorption, following standard dosing guidelines may deficit you, albeit “do it right.” Similarly, your specific gut bacteria may transform phosphatidylcholine with molecules with liver and brain benefits, which can increase trimethylamine-N-oxide (TMAO), thereby increasing your cardiovascular risk – there is no general recommendation for interactions.
The complexity of large numbers of biological interactions creates an impossible problem for individual independent tracking. This is exactly where AI is good at – processing a lot of personalized data to determine which natural product portfolios can work with your unique biological system.
AI can be personalized at scale, providing cost-effectiveness and analysis depth. This approach can: identify potential nutritional needs based on thorough biological analysis rather than general recommendations; detect subtle changes in health trajectories and resolve them as early as possible, and stay healthy before disease progression; and guide specific lifestyle modifications tailored to individual biology.
The result turns the vast majority of complexity into simple, actionable advice tailored to your body’s specific needs, limitations and opportunities.
These insights help to optimize personal health by eliminating guesswork and ensuring that the recommendations are tailored to the biological of the individual, thus helping to optimize personal health – providing the right nutrition at the right dose for improved absorption and effectiveness.
Vision for the Future – A New Era of Personalized Healthcare
Looking ahead, AI will provide increasingly personalized health insights. By being able to train large language models and proxy AIS on select, evidence-based information, users can get more accurate answers to their unique health questions. Continuous monitoring of wearable devices and home diagnosis will provide real-time data, and AI systems can analyze to detect subtle changes that indicate potential health problems before they appear as disease.
When health care prioritizes preventive measures, a real shift will occur – intervening at a biological level before symptoms appear. The Healthcare Service Center will be moved from the clinic to the home and will provide remote monitoring and personalized guidance.
For consumers, this means more transparent about their health and more informed, scientifically supported decisions. This is an important step to lower costs for the healthcare system, focusing on increasing health conditions rather than treating them after the development of chronic diseases.
By leveraging AI for prevention rather than just treatment, we have unprecedented opportunities to transform health care and expand the scope of human health to future generations.
Photos: metorworks, Getty Images
Dr. Nathan Price is Chief Science Officer of Thorne, a leader in science-backed health and wellness solutions. He is also a professor and co-director of the Human Health Range Center at the Buck Institute for Aging. Previously, he was the CEO of AI health intelligence company OneGevity, which merged with Thorne in 2021 and served as professor and associate director of the Seattle Institute of Systems Biology.
He is a biotech pioneer in the 2023 bestseller, Lee Hood, published by Harvard University Press. In 2019, he was named one of the 10 emerging leaders of the School of Health and Medicine by the National Academy of National Academy of Medicine and was appointed to the National School of Science, Engineering, and Medicine Life Sciences Committee in 2021. He is also a member of the American Institute of Medical and Bioengineering and is also the 2023 Alexander and Mildred Seliger Science Award from the American Nutrition Association.
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