New AI-enabled study unravels the principles of aging

Nature-published study illuminates the mechanics of aging and disease progression, demonstrating age reversal in an experimental medical intervention.

New work from?Gero, conducted in collaboration with researchers from Roswell Park Comprehensive Cancer Center and Genome Protection Inc. and published in?Nature Communications, demonstrates the power of AI combined with analytical tools borrowed from the physics of complex systems to provide insights into the nature of aging, resilience and future medical interventions for age-related diseases including cancer.

My take on this: Modern AI systems exhibit superhuman-level performance in medical diagnostics applications, such as identifying cancer on MRI scans. This time, the researchers took one step further and used AI to figure out principles that describe how the biological process of aging unfolds in time.

The researchers trained an AI algorithm on a large dataset composed of multiple blood tests taken along the life course of tens of thousands of aging mice to predict the future health state of an animal from its current state. The artificial neural network precisely projected the health condition of an aging mouse with the help of a single variable, which was termed dynamic frailty indicator (dFI) that accurately characterises the damage that an animal accumulates throughout life.

We reached out to Gero’s Peter Fedichev to find out what unique qualities their approach has that enabled this study.

“The approach we adopted in this study is based on the emerging (some say the 5th) paradigm of scientific discovery – when new principles and patterns are identified with the help of AI, modern ML tools and the analysis of Big Data.

“We believe that better explanations for complex biological processes, such as aging, can be found at the intersection of physical and data sciences.”

Read the full article HERE.

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