Where an Anti-Aging Theory Goes Right (and Wrong)

“We need more visionaries and integrated fields…because just as the human body is a complex interplay of atomic, molecular, cellular, and systemic processes, so too must be our approach to increasing healthy lifespan.”

While reading Zoltan Istvan’s perspective on what he calls the senescence inference, I found several key points to be insightful, though some aspects could benefit from further clarification. If the goal of his senescence inference is to develop an objective system for calculating or predicting life expectancy, with the aim of attracting more resources, research, and effort toward extending healthy lifespans, then this is undoubtedly a worthwhile and necessary endeavor. However, the current perspective on senescence inference relies on two well-known concepts that, while adaptable, may not be entirely aligned or effective in achieving the optimal outcome for this goal.

These two well-known concepts in question are (1) Moore’s Law, which suggests an exponential increase in computation rates over time as an example of doubling growth, and (2) the applied use of Period Life Expectancy at Birth (Period LEB) as a measure for quantifying life expectancy.

Let us begin with Moore’s Law. While drawing a comparison between senescence inference and Moore’s Law is clever and ambitious, it is fundamentally flawed from the outset. Moore’s Law is an observation developed in 1975 for predicting the doubling of transistors on microchips every two years, applicable to computational machines. This observation was—at one time—considered to be highly effective, but it is less effective today due to the laws of physics and to physical limits, as well as maintaining energy efficiency amid increasing complexity. Briefly put, a tenfold increase in the number of scientists working on the problem of aging paired with a tenfold increase in the amount of money spent on anti-aging does not necessarily mean that there will be 10 times more positive outcomes. Multiplying the number of scientists working on a problem will not produce the same increase in output if, for instance, the additional scientists are less skilled. Multiplying the amount of money will not produce the same increase in output if the promising areas for using that money are shrinking.