
Published
At a glance
- AI biological age research at Osaka University explores how patterns in blood steroids might help estimate physiological aging.
- The article describes a model that analyzes 22 steroids and their interactions, rather than treating chronological age as the whole picture.
- Researchers discuss possible future uses in personalized health monitoring; the report also notes that no universally accepted standard for measuring biological age exists.
From the “you have to be kidding me department” comes word that a group of scientists at Osaka University have developed an Artificial Intelligence (AI) model that uses something calling hormone metabolism pathways to estimate a person’s biological age using a mere five drops of blood.
In an article that appeared in the science news site SciTechDaily in late March from the prestigious university stated “by incorporating hormone (steroid) metabolism pathways into an AI-driven model, they have developed a system to estimate a person’s biological age –a measure of how well their body has aged rather than simply counting the years since birth.
“This method requires only five drops of blood to analyze 22 key steroids and their interactions, providing a more precise assessment of overall health. Published in Science Advances, the team’s study represents a major step toward personalized health management, enabling earlier detection of age-related risks and more targeted interventions.”
The scientists Qiuyi Wang, Zi Wang, Kenji Mizuguchi and Toshifumi Takao write in the piece that “aging isn’t just about the number of years we’ve lived – it’s shaped by genetics, lifestyle, and environmental factors. Traditional methods for estimating biological age rely on broad biomarkers, such as DNA methylation or protein levels, but these approaches often overlook the intricate hormonal networks that regulate the body’s internal balance.”
A diagram accompanying the article explains that the scientists measured 22 key steroids by way of a blood sample at which point the data is “fed into an AI systems” in order to calculate biological age.
The article notes that one of the study’s “most striking findings involves cortisol, a steroid hormone commonly associated with stress. The researchers found that when cortisol levels doubled, biological age increased by approximately 1.5 times. This suggests that chronic stress could accelerate aging at a biochemical level, reinforcing the importance of stress management in maintaining long-term health.”
It goes on to say that the four experts in this field “believe this AI-powered biological age model could pave the way for more personalized health monitoring. Future applications may include early disease detection, customized wellness programs, and even lifestyle recommendations tailored to slow down aging.”
In the abstract of the study that appeared In ScienceAdvances, the journal of the American Association for the Advancement of Science’s (AAAS) they wrote that “accurately assessing an individual’s biological age (BA), which reflects their physiological state, is essential for understanding aging and developing effective interventions.
“Unlike chronological age (CA), which simply measures the passage of time, BA provides insights into the biological processes underlying aging. However, determining BA is complex, as it is influenced by both genetic and nongenetic factors, and no universally accepted standards for BA measurement currently exist.”
Meanwhile, in the article they predict that with “ongoing advancements in AI and biomedical research, the dream of accurately measuring – and even slowing – biological aging is becoming increasingly feasible.”
Sources and context
Source: the steroid-metabolism biological-age study in Science Advances (2025).
Research context: The reported model uses steroid measurements and hormone-metabolism information to estimate biological age. The article also draws on a secondary explanation linked in its body.
How to read it: Biological age has no single universally accepted measure. Model-derived estimates and simulated hormone changes are not proof that stress causes a proportional change in lifespan or that a consumer blood test predicts an individual’s future health.









