A new paper cites my N-of-1 as a core feature of next generation longevity science. It explains why my biomarker numbers say less than people think.
I agree.
Aging is a multi-scale physiological process that we can’t actually measure directly. Biomarkers are like the blind men touching the elephant; able to know a piece, but never the whole.
The processes that dictate aging exist at multiple levels of biological complexity. They interact dynamically at different timescales, across different contexts, and along their own trajectories.
Aging manifests differently among people, but in highly nuanced and often invisible ways. The static, cross-sectional measures the field is used to can only get us so far.
N-of-1 initiatives like mine can capture some of this nuance, but ultimately fails at generalizability. The authors also critique N-of-1 as able to show "responsiveness but not durability; optimisation but not causality."
The challenge, so far unmet, is modelling the complexity of aging in such a way that the output is not a forecast of biomarkers, but a simulation of aging system dynamics, i.e. one’s health trajectory into the future.
The most intriguing implication of such a model is an improved ability to predict how our decisions will impact us in the future. A choose your own adventure where we can predict the consequences of both our healthy and unhealthy behaviors.
This is exactly what we are aiming to build. If you're into this as well, hit me up.