In January 2021 a paper entitled Artificial Intelligence in Longevity Medicine was published in Nature Aging. This paper is now the most active Nature aging paper. It is in the 98th percentile and ranked 3,327th of the 306,891 tracked articles of a similar age in all journals and is in the 95th percentile and ranked 2nd of the 21 tracked articles of a similar age in Nature Aging. The authors, Alex Zhavoronkov, PhD, Evelyne Bischof MD, and Kai-Fu Lee, PhD, propose a framework for the application of next-generation AI to extend human longevity, and explore how recent applications of AI to aging research are leading to the emergence a whole new discipline called Longevity Medicine.
Although advances in medicine have reduced mortality and extended lifespan, these advances have not increased healthspan. Since aging is the highest risk factor in many diseases, people are spending years living with chronic conditions as a consequence of living longer. The authors suggest that using specific preventive measures to treat aging at the organismal level would provide a much more substantial benefit to humans than simply targeting a single disease such as cancer. Curing a single disease would not lead to a significant increase in healthspan, whereas adding a geroscience based approach to routine clinical care would make a huge impact in healthspan.
“To an AI scientist like myself, the application of AI for longevity is very exciting, because rarely do we have an area so rich with data, so new, and so monumental for AI algorithms to make a big impact.”
Kai-Fu Lee, PhD, Chairman and CEO, Sinovation Ventures
Longevity medicine is emerging as an essential medical discipline combining the most advanced diagnostic and interventional approaches. The authors define longevity medicine as a branch of precision medicine that is specifically focused on promoting healthspan and lifespan, and is powered by AI technology. Longevity medicine will use innovative technologies to exploit the potential of the human genome, deep quantitative phenotyping, omics (e.g., epigenomics, metabolomics, proteomics), microbiome, and precision medical imaging. As technology advances longevity medicine will evolve.
The authors anticipate that AI-powered longevity medicine will:
1) facilitate the discovery of drug targets for specific individuals
2) facilitate the identification of tailored geroprotective interventions
3) facilitate the identification of biomarkers to enhance the study of aging
4) facilitate the identification of interventions that may help slow down or reverse aging
5) result in big improvements in healthcare for people of all ages
“Deep learning has enabled us to take a very holistic approach to measuring, analyzing, and interpreting the minute changes that transpire during aging. We are now tracking these changes, reinventing experimental functional medicine, and cultivating a new generation of AI-enabled physicians specializing in a new and exciting discipline – Longevity Medicine”.
Alex Zhavoronkov, PhD, Chief Longevity Officer at Deep Longevity and CEO at Insilico Medicine
The aging process requires longitudinal monitoring of millions of parameters in many different types of data sets that change over the course of a lifetime. Finding complex patterns in large volumes of longitudinal data is where AI demonstrates spectacular performance. Over the past few years, AI systems have increasingly outperformed human experts in many areas including drug discovery, analyzing medical images, clinical trials, and personalized medicine. The image above illustrates deep generative reinforcement learning for many areas of healthcare. Several deep learning applications in the clinical practice are represented.
Deep learning was instrumental in establishing deep aging clocks that generate estimates of an individual’s biological age based on data extracted from routine blood tests. Using AI-powered tools such as deep aging clocks, clinicians should be able to more precisely assess and monitor individual health risks and tailor appropriate interventions or changes in lifestyle for a specific person. The authors suggest that deep aging clocks should become an essential part of the doctor’s tool kit, enabling AI-supported recommendations to promote long and healthy lives. The image above illustrates how deep neural networks trained on longitudinal data of healthy subjects and patients with diseases learn the difference between aging and disease. Deep Neural Networks could be used to help predict risk and help position individuals in their optimal-performance biological age range.
“Seeing my patients changing their lives, optimizing their biological and behavioral health, receiving their subjective feedback on the improvement of their performance and quality of life, while being able to quantify these outcomes with AI-based tools, is the ultimate satisfaction for me as longevity physician.”
Evelyne Bischof, MD, longevity physician at Human Longevity Inc., associate professor at Shanghai University of Medicine and Health Sciences, internal medicine specialist at Renji Hospital and University Hospital of Basel.
In order for longevity medicine to be accepted as a legitimate area of medicine, aging must be recognized as a medical condition instead of a natural process. There are many AI-based tools that can already be used by doctors to assess health and aging status and new technologies are evolving rapidly. The authors conclude that “given the rapid progression of AI-based experimental longevity medicine, now is the time to catalyze its translation to common clinical practice. This transition will bring new solutions to patients and healthy individuals. Longevity medicine is also an opportunity for multidisciplinary collaborative work of thus far often distinctive players to transform public health into public healthy longevity.”
Zhavoronkov, A., Bischof, E. & Lee, KF. Artificial intelligence in longevity medicine. Nature Aging 1, 5-7 (2021). https://doi.org/10.1038/s43587-020-00020-4
Alex Zhavoronkov, PhD is the founder and CEO of Insilico Medicine and the Chief Longevity Officer at Deep Longevity. He is an expert in AI for drug discovery and aging research and has published 321 peer-reviewed papers. He is also the author of “The Ageless Generation: How Advances in Biotechnology Will Impact the Global Economy”.
Kai-Fu Lee, PhD is Chairman and CEO of Sinovation Ventures and is the former president of Google China. He is one of the most followed micro-bloggers in China with over 50 million followers and has published 81 peer-reviewed papers. He is the author of New York Times bestseller AI Superpowers: China, Silicon Valley, and the New World Order.
Evelyne Bischof MD is a specialist in internal medicine, with research focus on AI in oncology, precision medicine, biogerontology, and geronto-oncology. She has published over 50 peer-reviewed papers. She is a longevity physician at Human Longevity Inc., associate professor at Shanghai University of Medicine and Health Sciences, and an internal medicine specialist at Renji Hospital and University Hospital of Basel in Switzerland.