Recently, researchers at the company Deep Longevity proposed a method of applying AI algorithms and techniques to longevity extension technologies. The methods were proposed in an article published in the journal Nature Aging, called “Artificial Intelligence in Longevity Medicine”.
As reported by EurekaAlert, the authors of the study layout a framework for the application of AI in the development of human longevity extension technologies. They argue for the creation of a new discipline that combines elements of medicine, traditional biology, and artificial intelligence, dubbing the new field “Longevity Medicine”. Longevity Medicine can also be defined as the creation of restorative and preventative medicine enabled by aging research and artificial intelligence.
Traditional approaches to extending the average length of human life revolve around the treatment of disease. Yet at a certain point, there are diminishing returns on advances in this form of life extension, with researchers estimating that even the complete elimination of cancer would only add approximately 2.3 years to average life expectancy in the US at birth and just 1.3 years at 65 years of age. Similarly, even the elimination of common diseases like pneumonia and influenza would only increase the average lifespan by approximately 0.2 years and 0.5 years respectively.
The reason that there aren’t larger gains in overall lifespan when these diseases are eliminated is that they are merely manifestations of a larger problem, aging. Aging is associated with all manners of disease, the ultimate cause rather than the proximate cause. It’s possible that advances in forestalling the effects of aging could be brought about by AI. AI systems can ascertain a person’s age with a high degree of accuracy when trained on longitudinal data including features based on physiological and biological processes.
The authors of the article layout a framework to guide the application of deep learning and other AI techniques to longevity research, and the opportunities that may result from this research. Starting with biological age prediction and monitoring, scientists can develop biomarkers, using these biomarkers to guide the creation of biological targets involved in aging. From there, proteins and molecules can be synthesized to tackle the biological processes involved in aging, undergoing clinical trials. Data analytics is employed to discern the best way to use any promising therapies, leading to the creation of precision medicine that improves people’s physical and mental health. This cycle repeats as more data is gathered to improve biological models.
Underpinning the cycle described above is a deep generative reinforcement learning network. The network is fed data originating from a variety of different disciplines, including aging research, biology, chemistry, medicine, and psychology.
According to Evelyne Yehudit Bischof, physician of Human Longevity and professor at Shanghai University explained via EurekaAlert that AI has enabled the creation of an entirely new field of medicine.
“Artificial intelligence holds great potential for medicine in general; however, the ability to track and learn the minute changes that transpire in the human body every second over the patient's lifetime and in large number of patients enables the development of a new field of medicine – longevity medicine”, said Bischof.
The article was created by Bischof and other researchers. Also contributing to the article were Alex Zhavoronkov, chief longevity officer of Deep Longevity, and AI expert and computer scientist Kai-Fu Lee.