Buck Institute builds a data platform to measure what actually keeps people healthy longer

Buck Institute for Research on Aging, March 5, 2026

People are living longer, but the additional years are not always good ones. The gap between lifespan and healthspan, the years spent in genuinely good health, continues to widen. A growing body of evidence suggests that many aspects of healthy aging are modifiable, but the infrastructure to measure healthspan coherently, analyze it at scale, and act on the findings has not existed.

The Buck Institute for Research on Aging is attempting to build that infrastructure. Its new initiative, Healthspan Horizons, is a federated data platform designed to link real-world health data from wearables, sleep trackers, nutrition logs, and lab results with periodic deep biological measurements led by Buck researchers. The goal is to create longitudinal datasets dense enough to reveal what actually drives healthy aging over time.

Why dense, longitudinal data matters

The value of this approach lies in density. When many different signals are measured on the same person over time, the data becomes exponentially more informative than cross-sectional snapshots. Patterns emerge that would be invisible in a single blood draw or a one-time survey. Subtle shifts in sleep quality, activity levels, or metabolic markers could signal the early stages of decline well before a clinical diagnosis.

Nathan Price, a professor at the Buck Institute and co-founder of Healthspan Horizons, described the core problem: what has been missing is a way to bring together deep, long-term health data and apply rigorous AI to understand what truly drives healthy aging, at scale and responsibly.

The platform invites participation from wellness companies, health systems, and individuals, who contribute longitudinal data under clear permissions. In return, participants gain access to insights that emerge only when diverse data streams are linked over time.

A federated, not centralized, model

Healthspan Horizons is deliberately not a centralized data warehouse. Instead, it uses a federated, privacy-preserving approach. Approved analyses can run across partner environments without requiring any single entity to take ownership of individuals' health data. Data stewardship stays where it belongs: with the people and organizations who collected it.

This design choice addresses a real concern. Health data platforms have historically struggled with trust. People worry about their data being commercialized or accessed without their knowledge. The federated model is intended to sidestep those concerns by keeping data in place while still enabling analysis across datasets.

The advisory team and institutional backing

The initiative is led by Price and Yi Sherry Zhang, with an advisory group that spans academic medicine, systems biology, precision health, and public health. Advisors include Lee Hood, the pioneer of systems biology and CEO of Phenome Health, who described the platform as helping build the computational and ethical foundation needed to make healthspan measurable and actionable.

Eric Verdin, president and CEO of the Buck Institute, framed the platform as the infrastructure needed to organize and apply the science of aging responsibly.

What the platform does not yet deliver

Healthspan Horizons is, at this stage, an infrastructure project with a white paper and a set of partnerships. The platform has not yet produced the healthspan trajectories or early-warning signals it describes. The AI-driven insights are prospective, not demonstrated.

Federated data platforms also face practical challenges. Harmonizing data across different wearable devices, lab systems, and clinical workflows is technically difficult. Different devices measure the same things in different ways, and standardization across partners will be an ongoing challenge.

There is also the question of who participates. Health data platforms tend to attract people who are already health-conscious and relatively well-off, which can skew the populations represented and limit the generalizability of findings. Whether Healthspan Horizons can achieve the diversity it needs to produce broadly applicable insights remains to be seen.

The initiative's ambition is clear: to make healthspan computable, trustworthy, and accessible. Whether it can deliver on that promise will depend on execution, adoption, and whether the federated model can produce the kind of dense, longitudinal datasets that the science requires.