One general piece of feedback on both this and the previous post: LEV isn’t necessarily the ideal model for analyzing antiaging research. It’s an attractive idea, especially for those of us with quantitative backgrounds and a strong understanding of economics, but it’s definitely not how most biologists view the problem—and in this case, it’s not just biologists missing the boat in some obvious way.
Here’s (my interpretation of) how biologists see the problem.
There are organisms which do not age—notably the hydra. This means that the hydra’s mortality rate is independent of the hydra’s age: a hundred-year-old hydra is no more or less likely to die in the next year than a one-day-old hydra. An older hydra looks and behaves exactly like a younger hydra (once development is complete). Contrast to humans: humans clearly look and behave differently as we get older. Our mortality rate increases with age.
The main goal of mainstream antiaging research is not LEV, but antiaging in the sense of the hydra: make older humans biologically indistinguishable from younger humans. This does not immediately lead to unbounded life expectancy, as in LEV; it just means that older humans would have the same mortality rates as younger humans. For today’s first world countries, where age-related diseases are the main cause of death, that would mean dramatically longer (but still finite) life expectancies.
One specific way this vision differs from LEV: LEV inherently depends on continuous progress, on new research constantly removing mortality sources. Antiaging, on the other hand, will some day be done: once we’ve nailed down the key mechanisms of human aging, and figured out how to correct them, that’s it. Older humans can be reset to a “younger” biological state, mortality curves will be independent of age, job done and we all go research something else. This makes antiaging mostly a technical problem, whereas LEV is as much economic as technical.
The definition of LEV I used in the previous post is: “Longevity Escape Velocity (LEV) is the minimum rate of medical progress such that individual life expectancy is raised by at least one year per year if medical interventions are used”. So it doesn’t lead to an unbounded life expectancy. In fact, with a simplified calculation, in the first post I calculated life expectancy after LEV to be approximately 1000 years. 1000 years is what comes up using the same idea as your hydra example (risk of death flat at the risk of death of a young person), but in reality it should be slightly less, because in the calculation I left out the part when risk of death starts falling just after hitting LEV. We are not dealing with infinite utilities.
The main measure of impact I gave in the post comes from these three values and some corrections:
1000 QALYs: life expectancy of a person after hitting LEV
36,500,000 deaths/year due to aging
Expected number of years LEV is made closer by (by a given project examined)
Sorry, yes, LEV as you’ve defined it does not immediately lead to unbounded life expectancy. I’m not sure this is the way most people define LEV? I always thought the magic number was expected lifespan based on current mortality rates increasing by 1 yr per yr—that way everything remains well defined even when life-expectancy-accounting-for-medical-advances diverges, and we can meaningfully talk about the critical transition point.
Anyway, that’s kind of beside the point I’m trying to make: increasing rate of medical progress is not necessarily the most useful way to think about the problem, at least for now. Maybe you were already thinking of it the way I had in mind, and I just got confused by the LEV label.
One general piece of feedback on both this and the previous post: LEV isn’t necessarily the ideal model for analyzing antiaging research. It’s an attractive idea, especially for those of us with quantitative backgrounds and a strong understanding of economics, but it’s definitely not how most biologists view the problem—and in this case, it’s not just biologists missing the boat in some obvious way.
Here’s (my interpretation of) how biologists see the problem.
There are organisms which do not age—notably the hydra. This means that the hydra’s mortality rate is independent of the hydra’s age: a hundred-year-old hydra is no more or less likely to die in the next year than a one-day-old hydra. An older hydra looks and behaves exactly like a younger hydra (once development is complete). Contrast to humans: humans clearly look and behave differently as we get older. Our mortality rate increases with age.
The main goal of mainstream antiaging research is not LEV, but antiaging in the sense of the hydra: make older humans biologically indistinguishable from younger humans. This does not immediately lead to unbounded life expectancy, as in LEV; it just means that older humans would have the same mortality rates as younger humans. For today’s first world countries, where age-related diseases are the main cause of death, that would mean dramatically longer (but still finite) life expectancies.
One specific way this vision differs from LEV: LEV inherently depends on continuous progress, on new research constantly removing mortality sources. Antiaging, on the other hand, will some day be done: once we’ve nailed down the key mechanisms of human aging, and figured out how to correct them, that’s it. Older humans can be reset to a “younger” biological state, mortality curves will be independent of age, job done and we all go research something else. This makes antiaging mostly a technical problem, whereas LEV is as much economic as technical.
The definition of LEV I used in the previous post is: “Longevity Escape Velocity (LEV) is the minimum rate of medical progress such that individual life expectancy is raised by at least one year per year if medical interventions are used”. So it doesn’t lead to an unbounded life expectancy. In fact, with a simplified calculation, in the first post I calculated life expectancy after LEV to be approximately 1000 years. 1000 years is what comes up using the same idea as your hydra example (risk of death flat at the risk of death of a young person), but in reality it should be slightly less, because in the calculation I left out the part when risk of death starts falling just after hitting LEV. We are not dealing with infinite utilities.
The main measure of impact I gave in the post comes from these three values and some corrections:
1000 QALYs: life expectancy of a person after hitting LEV
36,500,000 deaths/year due to aging
Expected number of years LEV is made closer by (by a given project examined)
Sorry, yes, LEV as you’ve defined it does not immediately lead to unbounded life expectancy. I’m not sure this is the way most people define LEV? I always thought the magic number was expected lifespan based on current mortality rates increasing by 1 yr per yr—that way everything remains well defined even when life-expectancy-accounting-for-medical-advances diverges, and we can meaningfully talk about the critical transition point.
Anyway, that’s kind of beside the point I’m trying to make: increasing rate of medical progress is not necessarily the most useful way to think about the problem, at least for now. Maybe you were already thinking of it the way I had in mind, and I just got confused by the LEV label.