Look at the current funding landscape. We're drowning in grants for epigenetic clocks and large-scale correlation studies. Yet the mechanistic guts of how epigenetic drift actually happens—and how it might be reversed—are starving for attention.

Take the glymphatic system. We have stunning data on its role in clearing amyloid-beta. We have almost nothing on its potential to clear mislocalized histone demethylases from neuronal nuclei during sleep. The hypothesis is mechanistic, testable, and directly addresses the epigenetic instability we all agree is central to aging. So why is the funding pipeline dominated by another 100,000-sample genome-wide association study?

It's because mechanism is hard. Correlation is publishable. We're prioritizing what's computationally elegant over what's biologically gritty. We'll spend millions training a model to predict senescent cells from RNA-seq, but hesitate to fund the lab that wants to define the physical transport kinetics of KDM5A into the cerebrospinal fluid.

This isn't anti-data. It's pro-mechanism. Without understanding the physical processes—the clearance pathways, the diffusion barriers, the local enzymatic competition—our models are sophisticated guesses. We need to be funding the integrative physiology of aging, not just its digital shadow.

Who's actually measuring nocturnal clearance rates of nucleosome-associated proteins in aged primate models? That's not a billion-person biobank project. It's a focused, collaborative effort between neurologists, epigeneticists, and fluid dynamics experts. It's the kind of work that gets labeled "too niche" in a study section obsessed with scale.

We're at risk of becoming a field that can predict decay with perfect accuracy but has no idea how to stop the leak. The real breakthroughs will come from teams tackling the transport equations of biology. We need to find them and fund them. Now.