There is no shortage of theorizing on the nature of aging: its biochemical causes; its evolutionary origins; how it progresses; how to measure it. In any era in which thinking is cheap and life science research is expensive, there will be a lot more theorizing than data. While the tools of biotechnology cost less than ever, and the price continues to fall even as capabilities increase radically, I think it arguably the case that we are still in the era of relatively cheap thought and relatively expensive research.
One area in which theory and modeling has over the years found its way to practical use in clinical medicine is in the construction of measures of aging based on a straightforward combination of measures, such as grip strength, markers of inflammation, and so forth. Geriatric medicine has and continues to make widespread use of these assessments of frailty. A great deal of work on measures of aging still takes place, as illustrated by the growth of epigenetic clocks on the one hand and more complex algorithmic combinations of simple health metrics on the other. The work here is an example of the latter, with the choice of metrics and their