The Measurement Challenge in Longevity: Can Aging Biomarkers and Clocks Close the Gap?

Targeting and measuring biological aging 

A growing number of longevity-focused biotech companies are testing interventions that aim to modify aging biology, from senolytics and immune-function enhancement to metabolic interventions, cellular reprogramming, and tissue engineering. Yet robust measurement of aging itself in humans remains a central bottleneck, complicating the testing of preventive and therapeutic strategies.

In the absence of a clear framework for measuring the process of aging beyond chronological age, most longevity drug development has focused on age-related proxy diseases. At the same time, a growing biomarker industry is trying to address this measurement gap. Academic groups and biotech companies are developing and validating markers linked to “biological age”, a concept intended to capture the physiological state of an organism, organ, tissue, or cell. Biological age can be distinct from an individual’s chronological age and differ for different organs and body systems. 

A particularly active field of aging biomarker research is that of so-called aging clocks. For such aging clocks biomarkers or biomarker profiles are translated into predictive biological age scores using computational models. While hundreds of aging clocks have been developed, noisy data, a lack of standardized validation, and missing causal links to aging biology currently still limit their use in clinical research and their value as interpretable, consumer-facing tools. However, trials that validate and benchmark these markers are underway to establish reliable aging biomarker profiles and support their integration into regulatory frameworks. Predictive biomarker profiles, whether expressed as aging clocks or in other formats, could become important tools for aging research, longitudinal monitoring and treatment-response assessment in clinical development, routine clinical monitoring, and consumer health tracking.

The drug-development bottleneck – why aging is hard to measure