Advances in artificial intelligence were found to help shed light on deep biological clocks, said researchers.

‘Deep biomarkers of aging developed utilizing a variety of data types of aging are rapidly advancing the longevity biotechnology industry. ’

Since 2016 the use of deep learning techniques to find predictors of chronological and biological age has been gaining popularity in the aging research community. Advances in artificial intelligence, combined with the availability of large datasets, have led to a boom in the field, increasing the variety of biomarkers that could be considered candidates as potential age predictors. One promising development that considers multiple combinations of these different predictors could shed light on the aging process and provide further understanding of what contributes to healthy aging. 




In the paper titled "Deep Aging Clocks: The Emergence of AI-Based Biomarkers of Aging and Longevity" in Cell Trends in Pharmacological Sciences, Polina Mamoshina, Senior Scientist at Insilico Medicine, and Alex Zhavoronkov, the Founder of Insilico Medicine, summarise current findings on the main types of deep aging clocks and their broad range of applications in pharmaceutical industry.
"Humans are very good at guessing each other's age using images, videos, voice, and even smell. Deep neural networks can do it better and we can now interpret what factors are most important. Very often when someone looks older than their chronological age, they are sick. A trained doctor can guess the health status of a patient just by looking at him or her. At Insilico we developed a broad range of deep biomarkers of aging that can be used by the pharmaceutical and insurance companies, as well as by the longevity biotechnology community. In this paper we describe the recent progress in this emerging field and outline a range of non-obvious applications," said Alex Zhavoronkov, Ph.D, Founder and CEO of Insilico Medicine.
"Using biomarkers of aging to improve human health, prevent age-associated diseases and extend healthy life span is now facilitated by the fast-growing capacity of data acquisition, and recent advances in AI. They hold a great potential for changing not only aging research, but healthcare in general," said Polina Mamoshina, Senior Scientist at Insilico Medicine.
Source-Eurekalert