We all know how differently people age. Some centenarian shepherds in the Caucasus or the Alps remain perfectly active at 100 years old. Their organs and systems function decades younger than their passport age. Such people are called “super-agers.” In contrast, many middle-aged “couch potatoes” take multiple pills daily and rarely leave the house. The average American over 60 takes 4–6 prescription drugs daily, often followed by supplements and vitamins. Aging is a deeply personal path, and each of us follows our own trajectory.
The quality of our aging can be measured by healthspan—the portion of life lived disease-free and without significant disability. The average lifespan in the U.S. is about 77.5 years, while the average healthspan is only 66. This means that, for the last 11 years of life, most people live with partial disability, chronic pain, or persistent conditions, almost always on medications. Science cannot yet change our overall lifespan, as the limit of human life is tightly wired into our biology. But to a large extent, we can influence how we age—how we look, feel, and function—and we can extend our healthspan by years. One way to monitor this process is by regularly measuring our biological age. Although imperfect, biological age provides a single, intuitive measure of the true physiological state of our cells, organs, and systems.
For over forty years, gerontologists have been searching for measurable biological indicators of aging, beginning with the first NIH/NIA conference on aging biomarkers in 1981. However, for decades, aging research remained an obscure niche with little funding. This changed with the rise of AI methodologies in biomedicine about ten years ago, when several groups developed large-scale predictive models for biological age based on hundreds of thousands of blood tests. Some bioage calculators became publicly available, such as AgingAI by In Silico Medicine (Zhavoronkov, 2016). Doctors and patients could estimate biological age simply by uploading 20–30 standard blood parameters and then measure the effect of health programs or interventions (such as geroprotector protocols) by comparing “before” and “after” results. For example, a two-week stay at the Kivach Health Center reduced biological age by an average of three years (Moscalev, 2023).
Today, estimation of biological age has become mainstream. More and more diagnostic companies and clinics routinely provide patients with bioage scores alongside standard biochemical and hematological data. Many “aging clocks” have been developed, based on telomere length (which shortens with age), epigenetic DNA methylation, metabolomic panels reflecting nutrient sensing, mitochondrial DNA integrity, and cellular senescence markers. More precise aging biomarkers have also been established for individual organs—brain, heart, liver, lungs, and immune system—and are increasingly used for health evaluation and drug discovery.
Biological age can thus be viewed as a simple, intuitive measurement of healthspan—the number of years one lives without chronic diseases, pain, or medication dependency. These health outcomes can be quantified in economic terms, as they determine doctor visits, hospital stays, lost productivity, sick days, and medication costs. Health economists have developed several relevant measures. One is the Quality-Adjusted Life Year (QALY), valued at approximately $100,000 ± 50%. Another is the Value of a Statistical Life Year (VSLY), used by insurers and policymakers to evaluate medical innovations, typically valued at $200,000–$500,000 per year. In this framework, a one-year reduction in biological age—corresponding to a proportional reduction in mortality risk—is worth roughly $200,000–$400,000.
At Santa Maria, we consider biological age reduction a key indicator of our programs’ effectiveness. Recently, we applied the Aging 3.0 model (In Silico Medicine) to “before” and “after” data from fifty randomly selected patients. The results were very encouraging: a two-week cleansing program produced, on average, a six-year decrease in biological age.