Richard Miller
Description: Richard Miller is a Professor of Pathology at the University of Michigan and the Co-Director of the Paul F. Glenn Center for Biology of Aging Research. His research focuses on the key biological processes of aging and discovering interventions that can slow those processes. In this episode, we dive into Professor Miller's work with the Interventions Testing Program (ITP), which has identified over a dozen drugs and gene mutations that can significantly extend the healthy lifespan of mice. He explains why there is no single "mechanism of aging," and how his lab is pioneering the use of "aging rate indicators" to accelerate drug testing in humans. Professor Miller also discusses the most successful anti-aging drugs they've tested, like rapamycin, and addresses common misconceptions in aging science, including why he views the focus on cellular senescence and telomeres as "zombie ideas."
Websites:
Publications:
Aging Rate Indicators: Speedometers for Aging Research in Mice
Mentions:
Interventions Testing Program (ITP) at the National Institute of Aging
Adam Salmon (Aging in non-human primates)
Rusty Gage & George Murphy (collaborators testing drugs on neurons derived from skin stem cells)
Sriram Chandrasekharan (in silico modeling / AI drug discovery)
Other Podcasts:
Peter Attia’s The Drive - #333: Longevity Roundtable (2025)
Peter Attia’s The Drive - #148: Testing Longevity Drugs (2021)
Other:
Show Notes:
[0:07] Introduction
[1:27] Understanding Aging Mechanisms
[3:45] Measuring Aging Processes
[5:25] Caloric Restriction Effects
[7:45] Drug Testing and Aging
[9:47] Misconceptions in Aging Science
[11:57] Key Processes in Aging
[12:57] Anti-Aging Drug Candidates
[14:43] The Role of AI in Aging Research
[19:23] Aging Rate Indicators Explained
[25:40] Drug Testing Criteria
[31:48] The Intervention Testing Program
[44:33] Future Directions in Aging Research
[1:08:57] Funding and Aging Research Insights
[1:13:32] The Importance of Aging Research
Unedited AI Generated Transcript:
Brent Valentine (00:00)
Welcome back to Discovering Academia. We're two college students who travel the world talking with academics about their research passions and current events. Today we talk with Richard Miller, a professor of pathology at the University of Michigan and the co-director of the Paul F. Glenn Center for Biology of Aging Research.
Keller Kramer (00:18)
His research focuses on the key biological processes of aging and discovering interventions that can slow them down. In this episode, Professor Miller describes why there is no single mechanism of aging and how his lab is pioneering the use of aging rate indicators to accelerate drug testing in humans.
He also discusses the most successful anti-aging drugs they've tested, like rapamycin, and addresses common misconceptions in aging science, including why he views the focus on cellular senescence and telomeres as zombie ideas, meaning that they are not able to stay dead. We hope you enjoy.
Brent Valentine (00:48)
Welcome Professor Rich Miller. Thank you for coming on today.
Rich Miller (00:52)
Well, thank you for inviting me.
Keller Kramer (00:54)
start off, we'd love to hear, has anyone ever died strictly from old age?
Rich Miller (01:01)
Yeah, so ⁓ the problem is that people don't die of one thing as a general unless you're like hit by a bust or have a massive stroke or something. It's much more typical that aging will impair your ability to respond to all sorts of bad things. So if someone has bad eyesight and they slip on a patch of ice, it might break a bone because their bones are weak and they go to the hospital.
while they're waiting for their bone to be patched up, they might get an infection because their immune system is weak. And then when they get the infection, they might die of pneumonia because they have problems with breathing. So that person quote died of old age or something like that. But that's not really the best way to think about it. The best way to think about it is to say, what are the many, many, many different ways in which the aging process weakens your ability to.
recover quickly from diseases and to avoid diseases and make your risk of death much higher.
Brent Valentine (02:04)
Yeah, that makes sense. And then in order to understand what aging is, could you walk us through some of the key biological processes of aging?
Rich Miller (02:15)
Yeah, well, what aging is, is very familiar to everybody. It's the process that turns graduate students into emeritus professors. As you get older and older, there are obvious things that change in how strong you are, what you look like, and whether your hair is gray and how thick your bones are and that sort of stuff. And there are less obvious, but just as important changes in your body that make it harder for you to respond to an influenza vaccine and...
Sometimes for some people, harder to think straight and more likely to get cancer. Everybody differs in what aging does to them. Not every old person is exactly the same thing. But by the time you're in your 40s and 50s, you already know that you can't quite do the mile in six minutes the way you used to. And if you need to pick up giant bags of cement and move them to the basement from the trunk of your car, you get your 20-year-old son to do it for you.
So all of those are aspects of aging. Then by the time you're 60 and 70 and 80, 90, in addition to those hassles, you're more likely to get a disease that's going to kill you. Either something like cancer or stroke or heart attack or diabetes or something, or some cumulative set of difficulties which taken together mean that the next time you get COVID, it's going to kill you instead of letting you go home and...
you know, relax for a week or two as you get your strength back.
Keller Kramer (03:46)
And are there specific biological ⁓ ways of measuring aging that we use?
Rich Miller (03:53)
Well, there are attempts and I think they're misguided to sort of try to come up with a single number that tells you how old someone is. And you can see on the face of it, this is not a terrifically useful idea. There is no single number that represents how good you are at all sorts of cognitive things. Some people have lots of emotional intelligence. Some people are really good at doing the cognitive tasks necessary to ⁓
play chess or to do crossword puzzles. Some people are really good with language and others are really good with math. There is no number that in a useful way smushes all that together. The same is true for health. Some people have wonderful cardiovascular fitness, ⁓ but they have problems with their muscle strength or they have problems thinking or they've lost their sense of smell or something like that. People have attempted, I think misguidedly to
collapse all of those different aspects of aging into a single number, I think it's not very useful. it has the obvious disadvantage that once you feel that you've accomplished something by giving someone a number for biological age, you've more or less blinded yourself to all the details that are actually interesting and worth thinking about.
Brent Valentine (05:15)
And then in order to understand all the details, is it useful to think about aging at a cellular level and an organ level and an entire organism level?
Rich Miller (05:25)
Yeah,
that's really important because let me give you an example. If you take a mouse and you put it on a special diet, calorie restriction diet, basically you find out how much would the mouse want to eat and you give it 40 % less than that. They live 30 or 40 or 50 % longer. And it's not just that they live longer, but all of the different aspects of aging are slowed together. the aging of some of the cellular changes that happen in aging, those go slower. The changes in
how tissues look and how likely they are to have ⁓ pre-cancerous nodules in them, that all slows down, changes in the function of cells that divide, like in your bone marrow, that remains useful for longer, but also changes in extracellular tissues, like the lens of your eye and your tendons, things that don't have cells in them, all that is slowed together. The tricky part, the thing that really counts, where
a few labs are working, but it really needs a lot more attention. What causes all of those to slow down at the same time? It's a very familiar phenomenon, so familiar that people tend to ignore it. If you get a miniature schnauzer or a tiny dog like that, that dog's going to be alive and healthy for 10 to 12 years. But if you get a Great Dane or a Mastiff or some mammoth huge dog,
That dog will only be alive and healthy for six or seven or eight years. So everybody knows that small dogs age more slowly, but it's such a common phenomenon that no one, unfortunately, till recently, began to think about, now, why is that? What does that teach us about aging? Everybody's also familiar with this across species. You know that if you've got a pet mouse,
And you're lucky, it might last two years, but if you get a pet dog and you're lucky, it might last 10 years or a chimp, maybe 30 years or a pet whale 200 years or something like that. it's very well known to everybody, even by the time they're sort of in elementary school, ⁓ members of different species age in very similar ways, but at very different rates. So that's the phenomenon we want to study.
How does the changes in the cells, the changes in tissues, the changes in organs and the changes in multi, ⁓ you know, systems that involve feedback loops between the brain and your heart or between the brain and your GI tract, all of that changes with aging in ways that can be slowed down. I mentioned the colorectal restriction, but the thing that my lab specializes in is drugs that can do that as well. I'm sure we'll get to that eventually. And it's true across species.
The problem is what pushes back what postpones so many different kinds of changes in things that are slowing aging.
Brent Valentine (08:26)
Yeah, and is that where the Unitarian thesis of aging comes in that all of these changes kind of occur or start to occur at the same time?
Rich Miller (08:36)
Well, not exactly. mean, the Unitarian theory you got from a paper of mine, it was kind of a joke on the Unitarian religion. But at the time I was trying to set up a contrast, which I think is still, unfortunately, still an active controversy though, it shouldn't be. There are lots of people who say, well, you can never study aging because aging of the brain is one thing, and aging of the eyes means something else, and aging of the liver means something else.
skin aging and hair aging. it's, any one of those is complicated. So you're really kidding yourself, these people say, by thinking you can study the whole thing together. And the reason I think they're wrong, and I think it's important to think of aging as a unitary process, is that you can slow all of these things down. Nature does it all the time when she's making a long-lived species. We can do it in many breeds of slow aging dogs and slow aging horses.
And now we have diets, at least three diets, least 13 drugs, ⁓ and at least half a dozen single gene mutations. That's all the aging process. And so all of those things down. So the notion that you can't study aging because it's so heterogeneous and what it affects, I can see why that mistake is popular one, but it's time to admit it was a mistake and move on.
Keller Kramer (09:59)
you
And like we talked about a little bit earlier, I think everyone would agree that the recognition of aging as a clear factor of life is, I would say, understood across the board. But is there a similar understanding among the science community about the mechanisms of aging?
Rich Miller (10:23)
So there are two interesting things to say about that. mean, I hope they're interesting. One is that there are no mechanisms. There is no such thing as the mechanism of aging. For 50 years now, most of my distinguished colleagues thought what they really needed to learn about was the mechanism of aging. Was it DNA damage? Was it mitochondrial badness? Was it cross-linking of collagen? Was it autoimmune attack? And if you worked on T cells, you were sure T cells were the mechanism of aging.
And the reason this is mistaken and a waste of everybody's time is that there is no mechanism of aging. The things that cause some of your brain cells to die are different from the things that cause your tendon proteins to get cross-linked. And they are different from the ones that cause shifts in your stem cell population in the pancreas or in the bone marrow. There is no single mechanism of aging. The car metaphor is useful. There is no single thing that causes you decide to
go and buy a new car. Sometimes it's that the steering wheel isn't working or you've paid for three transmission repairs or there's rust in the undercoating and the car doesn't work anymore. So there is no cause of the aging of a car. And similarly, there is no cause of aging in animals. What is much more important though is what is it that causes all of these things to get slower?
when you evolve or use a drug or have a genetic mutation that extends lifespan and slows the entire aging process. The second part of your question was, do scientists understand this? No, they're scientists are not that good at thinking about aging, virtually, even the ones that have made a career in doing it. So the notion that if you're trying to study what is the cause of aging, the notion that you're wasting your time.
Keller Kramer (12:05)
Ha ha.
Rich Miller (12:17)
hasn't yet to catch on. There are an awful lot of people who are convinced that the thing they study is the cause of aging. They're interested in cellular senescence or bone marrow stem cell shifts or DNA damage. And they'll argue once they've had a couple of drinks in them that their thing is the cause of aging. And it's a shame because what they really ought to be doing is considering different ideas on the
much more interesting question, what times the process of aging, what is responsible for differences in the rate of aging, not the alleged hypothetical non-existent cause of aging.
Brent Valentine (12:57)
Yeah. And then are there some key processes in the body that like speed up aging across all these different systems? I'm thinking of this because like different drugs target different pathways, whether it's like mTOR pathway or glucose, like regulation and those types of things.
Rich Miller (13:15)
You said speed up aging and that's the first one is to rethink it. Nothing speeds up aging. ⁓ You can make animals sick and they die young. Yeah, that's not hard at all. Dozens of ways to do that. But the notion that what you've done is made them die because you've sped up aging though, it's popular among people who do that to get grants. It's just nonsense. It doesn't make any sense at all. However, if you rephrase your question, you get an interesting one.
What are the targets of proteins or enzymes or pathways that slow down aging? Very different thing. And there, yes, there are a dozen really good candidates that people should be studying and are studying. And there are probably another dozen or so that make equal sense that we haven't thought of yet. You mentioned mTOR, which is the target of rapamycin. That's become very popular. We published a paper in 2009 showing if we gave rapamycin to mice, they live 30%, well, 25%.
Now we have it up to 30 % with combinations of drugs. So learning how that happens, that's very fruitful investigation. How is it the mice treat with rapamycin? Why is it they get less cancer? Why is it that their kidneys last longer? Why is it their brains last longer? Why is it they don't get specific kinds of autoimmune disease? All that's important. And rapamycin, that is the target of rapamycin, which is an enzyme.
That's a really good candidate, but there are a couple of dozen that at present also look good and people should be studying them and a lot of them are being studied.
Keller Kramer (14:53)
In sense that with ophthalmitis it led to less cancer in the rats and also less autoimmune disease. How is slowing of aging different from just delaying the onset of these diseases?
Rich Miller (15:07)
Yeah, that's a good question. I mean, first of all, most of work was done in mice rather than in rats. There are a few studies in rats, most of it's in mice. So what you've put your finger on, a really important question, how is it that when you treat a mouse with rapamycin or a calories-rigged diet or a dozen other drugs, that all of these different aspects of aging slow down to the same extent and in the same way? Maybe not all of them, we're still working that out, but certainly sort of a lot of them.
use cancer. don't know why the animals given rapamycin or acarbose or canagoflozin or 17-alpester-dial, the other drugs that we've discovered. We don't know why they don't get cancer. I mean, they do get it, but they get it 30 or 40 % later than their untreated controls. You can make up some interesting stories and test them. might be, this is my own favorite guess, though it's just a guess.
It might be that aging causes the immune system, which helps protect your cancer to get worse. And in these animals that are aging more slowly, maybe the immune system stays good for longer. And when the immune system stays good, cancers get started and the immune system finds them and knocks them out. There are molecules in the brain, for instance, double cortin is a famous example.
which means that your brain is making new neurons to replace neurons that have died. Well, all of the, all four of the anti-aging drugs that we've tested, they make double-cortin go up in the brain of young adult and in one case, ⁓ older adult animal. So we suspect that if these drugs help mice retain their cognitive powers for longer, maybe it's because they've preserved the ability to make new neurons because the double-cortin has stayed up. So you can,
come up with pretty good specific molecular and cellular hypotheses. Why is it that they don't get obesity so much or they don't get metabolic syndrome or they don't lose immune defenses so much? You can come up with good specific molecular hypotheses and then going about testing them. Now that we have at least 10, probably more than that, but at least 10 different ways of slowing aging in mice, we can start for the first time ever
to ask the key question, what do these have in common? If there are common things that are always flipped or switched in an animal that's slow aging, regardless of how you make it slow aging, you see them all the time, then those are most likely, we call those aging rate indicators, then those are the ones that probably explain all the good stuff you're getting disease by disease by disease, what it gives us a challenge. What's upstream? What's actually controlling?
all of those aging rate indicators when you give a drug A or drug B or drug C or diet one.
Brent Valentine (18:04)
Yeah, and then could you expand a bit more on what the aging rate indicators are? Like I like the example I've heard you say with the car and that's speedometer odometer and also just do we have examples of some of these indicators?
Rich Miller (18:20)
The idea of aging rate indicators is kind of new. Our first papers on this were published three or four years ago, and they have not yet fully permeated into the community's discussion of aging and how to measure it. The basic idea is pretty simple. The basic framework idea is that you've got normal mice or normal people or normal dogs or whatever, and you can make slow aging people and slow aging dogs and slow aging mice, maybe buy a drug, maybe they had
good genes, maybe you put them on a caloric diet. So the idea is what happens more or less immediately after you flip them into the slow aging state by giving them rapamysin or giving them kinagoflozin or putting them on a low calorie or low methionine diet. We would consider those aging rate indicators because the people are the dogs of the mice that are in the slow aging state.
They are aging slowly and we want to know what's different about them. We don't have to wait for them to get old. We know when they get old, they'll be more useful. Somebody else proved that five or 10 or 15 years ago. We know they will age slowly, live longer and look younger when their driver's license says they're old. We don't at present want to know anything about that. All we want to know is what is the difference between normal young adults and those that we know are aging slowly because we gave them a drug that makes them age.
slowly. That's what the age rate indicators are doing. The picture is not complete. So far, all we've done, it's a step, but it's not the last step, is we've measured a dozen or so aging rate indicators that are shared in common by at least 11 different kinds of slow aging mice. In each case, the contrast is between a normal mouse and a slow aging mouse population.
That's why we think the things on our list really are aging rate indicators. The step we need to take now, which we've gotten a grant to do it if the government doesn't cancel all of health grants, we will in the next five years discover whether this applies in normal mice as well. That is, we'll take a batch of normal, healthy young mice. We'll test their level of aging rate indicators once when they are young adults.
Keller Kramer (20:28)
you
Rich Miller (20:44)
And then we'll wait. And our prediction will be that the ones that have the best, the most youthful aging, the slow aging indicators, our prediction is that when they get to be middle aged and older, they will be stronger, they'll be smarter, and they'll be not dead. So, and by the way, they'll be not dead of cancer and they'll be not dead of the other things that kill mice. We're hoping to postpone all or nearly all aspects of aging that are
that are bad for you, the reason why you'd rather be 20 than 95. So that would be the proof that this battery of aging rate indicators discriminates in youth, those individuals who are aging more slowly and those individuals who are aging at a more normal rate. It may be that some of the aging rate indicators we've discovered by looking at slow aging populations of mice won't pan out. And it may be that we'll discover other things that
don't work in these mutants but do work in normal mice. Any of that would be good. We're not saying that our list is the final definitive official list. It's a starting place for refinement. If we get this to work, then we are in terrific shape for taking the step everybody always wants to know about. How do we get the drugs to work in people? So the traditional way, the FDA approved, very sensible way of testing a drug
is you give it to a lot of people, just say you think it prevents measles or something. So you give it to a lot of people, you see who gets measles or you give it to a lot of people and you see who gets a stroke or who gets a heart attack. That's how you test it with a placebo controlled trial. The problem is doing this for aging, have to wait 20 or 30 or 40 years to see if the people died or got aged or something. No one wants to do that, it's too expensive and there lots of reasons why people don't want to do it. However,
If you had some things you could measure in people's blood that told you whether your drug had made them into a slow aging person, then you can begin to get useful insights in a year or something like that. If you give them, let's say you have 10 drugs and you think for a variety of reasons, some of these 10 drugs might slow aging in people and they're safe. You've proven that they're safe. They don't hurt people. You could take some volunteers, give each volunteer one of these drugs and come back a year later.
If three of the drugs had major volunteers have these aging rate indicators in the good direction and the other seven had not done that, you would want to focus the rest of your experiment on the three drugs that work. You want to see what else the three drugs did. Did they preserve your mental health? Did they preserve your physical strength? Did they help you get a better vaccine response? The next time you had a COVID or a flu vaccine, it would be a way of quickly filtering
drugs to see which ones were most promising for human studies. It wouldn't prove that they slow aging. That takes more work and more time and more money, but it does give you a powerful tool in helping you decide where you want to spend that money and spend your time whittling down a better list of candidate anti-aging drugs.
Keller Kramer (24:01)
And with the indicators, and this might be a crude comparison, but would they function similar to biomarkers or of the 12 assuming they hold true in the next study? Would those be things that you could then target the pathways of those indicators to create drugs from?
Rich Miller (24:17)
a wonderful,
instructive question. And the first thing to point out is that they are very, very, very different from biomarkers. I have an edge in my voice because the first four papers we sent in on aging rate indicators went to reviewers who said, yeah, these are just biomarkers. Who cares? Everybody knows about biomarkers. So they're not biomarkers in the same way. And you mentioned this metaphor before, that an odometer is not useful as a speedometer.
In your car, an odometer tells you how many miles the car has been driven. That's what a biomarker of aging does. It tells you how many biological years, crudely speaking, that body has been driven. You've got an 80-year-old, the odometer on that person will read something very different from what the odometer said when he or she was 20. They've been alive longer, aging has had far longer to act on them. So that's what a biomarker of aging is. Critically,
And we'll come back to the aging rate indicator in a moment, the speedometer in this metaphor. Critically, if you want to see if a drug slows aging and all you have, unfortunately, is biomarkers, you give the drug and then you wait and wait and wait and wait. You wait long enough to see aging do something to make your biomarker go down or up a lot in normal people, but less so in the treated people. since a lot of things do not change very much between
a 72 year old and a 73 year old, or between a 72 year old and a 74 year old, you may have to wait five or 10 or 15 years before your biomarker starts to give you a signal to see whether the drug is working. So the aging rate indicator in this metaphor is like a speedometer. If you want to know how fast your car is moving, you do not look at your odometer every 30 years to see what's happened. You look at the speedometer because you want to know how fast it's moving now. Your speedometer doesn't tell you anything about how old you are.
old your car is. You can have an old car going at 50 or an old car going at 20 etc. The speedometer just tells you at the moment you glance at it how rapidly the car is moving and in our mice we think these aging rate indicators tells us how rapidly the mouse is aging whether it's aging ⁓ at a normal pace or at a slower than normal pace. It's easy to see once you understand it, once you explain it.
people say, yeah, so it's like a biomarker of how fast you're going. And the key point here is that it's not a measure of how old you are, it's a measure of how rapidly you are changing. And you only have to measure it once, you don't have to measure it twice to see what the speedometer says. If you've ever had any physics, it's like the difference between your position and your velocity.
Brent Valentine (27:02)
Yeah. Do you have an example of what one of them might be?
Rich Miller (27:06)
Sure,
we have published 10 such examples. Let me talk about two of them. One of them I've already mentioned, the double-cortin, the thing in your brain that tells you whether you've got dividing cells in the brain, basically. All 10 of the slow-aging mice we evaluated, that's five mutants, four drugs, and the caloric-strict diet, they all make double-cortin go up. It's not a matter of reversing aging, because we've looked at young mice. All of these are young adult mice, all except one of the mutants with the young adult.
and double cordon goes up. So that's a candidate aging rate indicator. Another would be to look at the fat. ⁓ There are ⁓ two kinds of cells in your white fat. There are ⁓ fat cells that accumulate lots and lots and lots of fat lipid inside. That's why you have giant blobs of fat all over you. But there are others that are smaller and take the fuel and they turn into heat.
These are like brown fat. They're called beige fat cells. So all 10 of these slow aging mice have less of the bad fat, the kind that is responsible for fat storage, and they have more of the good fat, the kind that's responsible for thermogenesis for heat generation. The molecule that we use to measure this is called UCP1. It stands for uncoupling protein one. It is the thing that distinguishes the good fat.
from the bad fat and UCP-1 goes up in your fat whenever you're on one of these anti-aging drugs or have an anti-aging gene or are on a politically-stricken diet. So I gave you one for fat, I gave you one for brain. We also have some in the muscle, we have some in the plasma, we have some in the liver, and we have some in the macrophages, which have to do with inflammation versus anti-inflammatory protection. So we've got a 10 or 12.
Brent Valentine (29:04)
Yeah. And then when you say they have less of the bad fat, is that converting the white fat into like beige or brown fat? Or is it like removing them?
Rich Miller (29:13)
That's a good question and no
one knows. there two obvious possibilities. One is that the white fat cells turn into brown fat. Might be true. The other thing is that there could be precursor cells in the fat, pre-adipocytes that have a choice. They can either become a white fat cell or become a brown fat cell. And maybe these slow aging drug, anti-aging drugs tip the balance so that more of the ⁓
precursor cells turn into these beige adipocytes that are high in UCP-1, small, not so great at fat storage, but pretty good at helping burn calories.
Keller Kramer (29:58)
And then looking at the testing of anti-aging drugs like right now, what are some of the measures or metrics that you use to evaluate the success of a drug? Because assuming the rate indicators are still being developed. ⁓
Rich Miller (30:09)
You know, that's good.
Yeah.
Well, the way ⁓ I don't think I've mentioned the term ITP yet, but we're going to have to. That's the Interventions Testing Program, the ITP. It was started 21 years ago by the National Aging Institute. It supports studies at three labs, my lab at Michigan, plus Randy Strong's lab at the University of Texas in San Antonio and Ron Kostanj's lab at the Jackson Labs. Each year, ⁓ the international scientific community
gives us 20 or 30 suggestions for drugs they think will work. find that our committee of experts thinks are worth testing and we give them to mice. ⁓ The first time through, the first time we try a new drug, we only have one ⁓ criterion. Did the mouse die? We just count live and dead mice and we simply look for ⁓ things that postpone death and improve survival in the mice. ⁓
If we get some winners and we now have 14 winners, 11 published and three that will be in our next paper, ⁓ when we have a winner, we then go back and we do it again. And this time we are trying to answer the questions you just posed. it improve their, does it preserve strength? Does it preserve immune function? Does it preserve psychological function? Does it block the development of diseases in multiple tissues?
⁓ We're hoping to start cognitive tests. We're going to add those to our test batteries soon. So the way our program is structured, when we have a winner, of course we publish it. And we know that the world has experts on immunity and experts on bones and experts on eyes and hearing and skin. We're hoping that whenever we publish a paper saying, hey, look, this drug slows aging, somebody who knows what he or she is doing in those areas will say, hey, I want to give that to some of my mice and does it slow?
The liver disease, it slow? The kidney disease, does it slow? ⁓ Cataract development or whatever. We do some of that, but we're just three labs and we're not experts on every single aspect of age-associated change. So the real goal of the program is to stimulate and help guide detailed tissue by tissue, cell by cell studies.
Brent Valentine (32:30)
Yeah. And then could you also like give a little bit more detail on the IDP process? Cause I found it pretty interesting how like it's all three labs are concurrently running the same ⁓ studies, right?
Rich Miller (32:42)
Yeah,
we worked it out. ⁓ The literature is up until 20 years ago, was filled with papers where one lab said, hey, I tried this drug, worked. But then no one ever wants to spend the next four years checking it out. Because if it doesn't work, you get to publish a paper saying, sorry, it didn't work. And if it did work, you get to publish a paper saying, yeah, we agree. But there's no thrill or fame in that, even though it's important replicative science.
So what the ITP does is we have two committees actually, an access committee and then our executive committee that picks the drugs. And then every one of these three labs uses the same drugs at the same concentration or the same kind of mice, the same bedding ⁓ that you cannot change. I cannot change the protocol for the Michigan mice without permission of the other ⁓ two leaders plus the NIA staff representative. ⁓
physician science a researcher named Jennifer Fox unless all four of us agree we can't change the protocol at all we like to maintain stability so that the protocol we're using now in year 21 is the same as the one we were using five and ten and fifteen to twenty years ago so that that protocol standardizes on a particular kind of mice genetically heterogeneous mice so that no two of our mice are the same but they're all brothers and sisters basically
and we have the same bedding, the same food, in the same base diet, at the same concentrations. ⁓ That allows us, if a drug works at all three sites, even though every site differs a little bit in how warm the room is and how humid the air is, what the water, local water tastes like, you know, if it worked at all three sites, we and more importantly, the scientific community can view that finding as quite robust and likely to be believable.
and reproducible. We sometimes find, however, that a drug gives a really great effect at one of the three sites and either no effect or a middling good effect at the other two sites. And we publish that and we have to be honest, not every scientific experiment gives a completely compelling, consistent finding. That's just how life is. If it turns out that the drug works great at one site and fairly well at the second site and the third site,
We publish that and people can decide for themselves whether they want to spend time working on the drug. We typically test each drug at only one dose and we do our best to guess what the right dose is, but that's only a guess. And it could be if we pick a dose of 30 parts per million in food, maybe the real dose that works best is 100 or maybe it's 10.
⁓ So if we get a response that's kind of wishy-washy or a little inconsistent at 30, a smart move if our budget allows would be to go back the next year and test it at 10 and test it at 100. It is sometimes often the case that a drug that worked somewhat or inconsistently at the first guess will work better at a higher dose or occasionally even at a low.
Keller Kramer (35:59)
Are there criteria for fully rejecting a drug you mentioned? If it kind of works at one and it works well at the other, then ideally there will be another round of testing at a different dose. Is there a scenario when...
Rich Miller (36:10)
we cannot
definitively state this drug will never work because it might work at a different dose or it might work if the diet had more fat in it or something like that. we would never say we have definitively proven that resveratrol cannot extend mouse lifespan at all. However, if a drug produces
no benefit or actually a harmful effect which we've now seen four times for specific four different drugs. We have to ration our money. We don't have a great budget. We have a decent budget but it's not nearly what we need to actually make rapid progress on these drugs. So each year we have enough money to try five or maybe if we stretch six or even seven drugs. So we don't want to quote waste.
our limited resources on retrying a drug that seemed not to work at all when we tried it the first time. ⁓ We want to reserve our limited capacity either for multiple doses of drugs that look kind of maybe okay and more importantly trying out new drugs that no one has ever tested but which have some either scientific promise or occasionally because they're being sold by hypesters and fraudsters and con artists.
There a lot of people that say try my special kind of resveratrol or my special kind of nicotinamide riboside or my special brand of fish oil or curcumin or whatever. There's enough popular interest in this and who knows, they might be right. Some of these drugs, despite the absolute lack of evidence in most cases, some of these drugs just might work. And so we will sometimes pick a drug because it has
achieved certain amount of popular fame or interest and tested. They've never worked, but at least we're making that contribution to the literature.
Brent Valentine (38:13)
Now, and with some of those drugs that don't work, why are they so popular? Why do people think they work?
Rich Miller (38:20)
There are two reasons. People want to make money. I'm sure you've noticed that. And if they can look you straight in the eye and wearing a white coat and say, I won a science prize once and by God, I take this stuff. Trust me, it's really great. You're tempted to believe that the people they sell to are not the sort of five or 10 % of the population that says, prove it. What papers have shown that the stuff works?
They instead say, wow, you're a famous scientist at MIT or Harvard or wherever, and you wouldn't lie to me because you'd get a reputation for not being completely truthful. You don't want to do that. So I believe you. And yes, here's $90 for a month supply of whatever it is you're hawking. People really don't want to get old. It's an extremely unpleasant thing to happen. And I don't want it to happen to me or my friends either. And that makes them very gullible. People say to themselves,
Maybe it'll work, maybe it won't hurt me. Let me just give it a try. Let me give it a whirl. Not everybody is particularly skeptical or enthusiastic enough to look up the papers on their own. And in many cases, there are no papers. It's mostly just...
Keller Kramer (39:36)
You mentioned that there were 14 winners that have come out of ITP. What are of those, what are some of the most successful findings and I guess like what constitutes success in your eyes for these findings?
Rich Miller (39:48)
The drug that had the biggest effect when used on its own was rapamycin. For females, the highest dose we ever tried, maybe it would work even better at higher doses, but the highest dose we ever tried, it extended female lifespan by 26 % and male lifespan by 23%. To give you a sense of whether that's a big or a small number, ⁓ it turns out if you had a cure for cancer, nobody over the age of 50 ever, ever gets cancer again.
you have increased human lifespan in the United States by 3%. It's actually about 2.7%. So the rapamycin by itself does 10 times better than you'd get from a complete cure for cancer. And if you ask people, would it be good to have a cure for cancer? The answer is almost always yes. I would like to have a cure for cancer myself. However, the drugs we have which work on aging do 10 times better in a mouse situation.
If they worked in the humans in the same way, the amount of active, healthy, productive lifespan one would get would go up by 10 times better than a complete cure for cancer. the second drug that we have that worked almost as well as Acarbose, ⁓ Acarbose and the third drug, Canagliflozin,
They work on lowering blood glucose. They don't put you into hypoglycemia, which could make you faint. They don't do that. But what they do is they prevent you from having a glucose spike. So if I have six donuts for my breakfast, trust me, my glucose will go way up. It'll then come down pretty quickly. But there'll be a peak, a surge of glucose in my blood, which is probably not good for me. So what these drugs do is they blunt that peak in different way. One of them works in the...
GI tract is slow starch digestion, the other works in your kidneys to help you get rid of excess glucose in the urine. But they both work by limiting spikes in blood glucose. So they extend mouse lifespan too. ⁓ If I were a cancer biologist, and I've been ignored by dozens to hundreds of cancer biologists in the last 10 years when I say this statement, I would really, really like to know why you can postpone cancer dramatically in mice.
by blocking peaks of blood glucose. The combination of two of those drugs, rapamycin plus a carbose is the best we've ever gotten. If you give it to male mice, you get 29 % lifespan increase, which is the best single effect we've had. The first time we had a combination that worked better than either drug used on itself. So that's our current record breaker.
And then the three or four others that give you a 12 or 15 % increase in lifespan. There's a puzzle which we are unhappy with and don't understand. Probably three quarters of the drugs that work, work either only in males or better in males. We have two or three that work equally well or even one that works only in females. So it's a tiny effect. We don't know why that is. And we would love to know why.
⁓ So, obviously we're
Brent Valentine (43:20)
Yeah. And then do you think like years in the future, the best anti-aging treatment will be some combination of multiple different mechanisms?
Rich Miller (43:31)
Yeah, that's a good question. And the answer is maybe. We really don't know. That's the sort of question we would like to know the answer to. ⁓ It's possible that some drugs will specifically improve your immune system and others will specifically improve your cognitive powers and a third set will modify the stem cell compartment.
The odd thing, it's really important, but is for many people surprising, is that the drugs that are slowing aging are doing all of that together, right? How they do that, we don't know. But dissecting out the specific mechanisms by which all of those age-associated changes are postponed in common, that will help us come up with a, first a theoretical answer to your question, and then teach us how to test.
specific combinations that may be rationally chosen.
Keller Kramer (44:34)
Are there particular newer or less popular biological processes that you would like to see investigated as potential drug targets?
Rich Miller (44:48)
Well, there are a couple of dozen pretty good ideas. It may well be that the nicotinamide pathway is important. It may well be that changes in bone marrow, stem cell preservation is important. It could well be that what really counts is blocking inflammatory changes in the brain. Our drugs do block inflammatory changes in parts of the brain, the ones we've looked at.
and it may be that we would have good luck looking at anti-inflammatories, particularly ones that are brain specific. I've mentioned two drugs that seem to work by limiting blood glucose. it could be that learning more about how high glucose is really bad for aging in multiple tissues and cell types, maybe that will pay off. ⁓ these are my personal favorites, but other scientists have their personal favorites which deserve attention.
There are some that are currently very popular, ⁓ cellular senescence, instance, and telomeres and sirtuins. These are things that are still, there's sort of zombie ideas. They're dead, but they won't stay dead. They should be dead, but we're gonna have to cut their heads off and then shoot them and then burn them before they die. are people laboring away.
Brent Valentine (46:04)
Hahaha
Rich Miller (46:08)
They support one another's grants. Everybody who's working on cellular senescence thinks it's really cool. So they give good scores to cellular senescence, despite the ⁓ very strong arguments against that being a key element in the biology of aging. So there are some ideas out there that ought to be dead but aren't. But there are lots of great ideas that are still understudied and deserve to be carefully evaluated.
Brent Valentine (46:34)
Yeah. And then have you guys looked at the comparison of like a ketogenic diet and the drugs that do like that block glucose spice?
Rich Miller (46:45)
We have not looked at a ketogenic diet. There are practical reasons for making that hard to do in mice. A baseline diet that we use for the mice has a certain percentage of fat, a certain percentage of protein, and a certain percentage of carbohydrates. To turn that into a ketogenic diet means you have to change the carb storage, radically increase the amount of lipid, change the protein source, et cetera, et cetera. So it's making many changes together.
That means you really can't compare it to the controls. The closest we got, ⁓ some people who are experts on this, recommended that we try adding a compound of butane diol to the chow. They said that butane diol would turn the mouse into a ketogenic state. And we tried butane diol, which they are also trying in human clinical trials. So we tried it in mice. And it had no effect. ⁓
but we have not actually tested the sort of classical ketogenic diets.
Brent Valentine (47:50)
Yeah, that makes sense.
Keller Kramer (47:53)
And stepping out a little bit of kind of the current research. Is there a path for the IDP to testing on other model organisms outside of mice and rats and
Rich Miller (48:05)
So you
won't do anything except in mice. That's our sort of charter. We don't want to waste our limited amount of attention and money. However, we certainly hope to inspire studies in other organisms. The two that are most advanced and most interesting, ⁓ one is in dogs. It's the dog aging project. Daniel Promislow, now at Tufts, is the leader there. And one of his close friends and colleagues, their name Matthew Kaberline, they both used to be washed in Seattle. They've both left. Matthew is
⁓ a part of the dog aging project that he's gotten the grant of his own to study rapamycin in dogs. I think a lot more needs to be done. I would really like to see someone do a study of kinagliflozin in dogs or a study of the 17-alpha estradiol in dogs or even maybe acarbos. ⁓ I think those are good vets too and there's just not enough money available for that kind of study.
The other organism that I think is going to pay off pretty quickly, there's work being done at the University of Texas by a guy named Adam Salmon, one of my alums. I'm proud of what Adam has done now that he's out on his own. Adam has been studying the marmoset. Marmosets are primates, which makes them really interesting because we're primates too. But it's a short-lived primate. I'm not fully up to date. I think the average lifespan is about eight or 10 years, something like that. So he's done a rapamycin study in marmosets.
and all the results are not finished and they're not published, initial look at the evidence suggests that the stuff might be working. So that's good news. ⁓ I think ⁓ common marmosets live longer than you'd like to do this sort of study, but the evidence that a drug is worth testing in humans, marmoset data is gonna be kind of persuasive, In part because
You can test them to see how strong they are, not just how long they live, which is important, but did it slow down cancer? Did it slow down diabetes in the marmosets? Did it slow down liver failure? Did it preserve their ability to solve mazes or to solve puzzles? All of that can be done in marmosets using tests that are pretty much analogous to tests that you would do on aging people if they were in the study of the same general nature.
Brent Valentine (50:29)
And then have you seen like the organ on chip technology and the idea?
Rich Miller (50:33)
Before we get to organ on a chip, ⁓ the problem has been talking to people who work on humans. There is a group of people who are very proud of their ability to test drugs in humans. And in my view, they're not doing a very good job. They don't want to 20 years to understand that, to see if their drug worked. And so they try to do things that they think might be sort of like aging. They look at methylation clock.
or something, things that haven't been actually vetted and documented to be good biomarkers. They think of them as biomarkers for aging, and they don't know that to look at an age-associated change in a biomarker, you have to wait five or 10 years for a lot of aging to happen so these biomarkers will change. And these people, so far at least, the ones I've come in contact with, are not that interested in discussing the obvious point.
If you have aging rate indicators, not biomarkers, they could help you find drugs that might work in people. That would be a good filtration step. As far as I know, no one has really been interested yet in ⁓ refining, I would say improving their human anti-aging drug studies by incorporating aging rate indicators into the protocol. Then you asked a question about aging on a chip.
That's nonsense. That's sci-fi, it's high tech, aging doesn't happen on chips. It happens when people collapse, right? You can work on a microchip or a biological reactor and try to talk yourself and your funders into thinking it's sort of a little like aging maybe, isn't it? But I think it's a very tough sell, except for those who come in with predisposed
Keller Kramer (52:08)
You
Brent Valentine (52:10)
Yeah, the idea is.
Rich Miller (52:29)
to think it would be ⁓ likely to work. I don't, I'm not one of that.
Brent Valentine (52:34)
The idea I had on that was more if you have like brain cells, the ones that would be making the proteins or the agent rate indicators in the brain, if you gave the drug and that increased that, that could be the.
Rich Miller (52:46)
That's
actually really a good idea. the way we're actually working on this in collaboration with George Murphy and ⁓ Rusty Gage and some other people. What George and Rusty have are two different methods for taking a bit of skin, putting in tissue culture, and then making it into neurons. They have two different ways of doing it and both ways work pretty well. So if you were asking, I have a thousand drugs. I want to see what which of these drugs
do something good to a neuron, you can do it now because they have cells that are happy, including human cells, that are happy, growing in culture. They're not in the brain anymore and they're still neuro-like. I mean, they'll conduct neural impulses and make synapses and things like that. That's a major technological triumph and sets the stage for the kind of work you want to do. The hassle, which I skipped over,
to be tricky is what does doing good mean? ⁓ If what you want is, let's say that you think the way to help your brain is to your brain cells to turn on molecule like BDNF, brain derived neurotrophic factor. That's another aging rate indicator. All the slow aging mice have a lot of it. a exercise turns it on in your brain. So it's probably a good thing. So you could screen drugs using these cultured human
neuron-like cells to say, which of these drugs turn on BDNF? That's a great idea. It's not my idea, but we're doing it. We're working with Rusty and George and their colleagues to try to do just that. The catch, and it's not a fatal flaw, it's a great idea to do it that way. But the possible weakness is that the things that are bad that happen in your brain might involve interactions between two or more cells. So it's possible.
that what goes wrong in your brain is that the glial cells, not the neurons, but the cells that are around the neurons in the brain, they get more inflammatory and they start to make one or more bad cytokines and the cytokines go to the neurons and cause the neurons to die or get sick or something. That's much harder to model in a single cell culture. It's not absolutely impossible, but you really have to have very strong
molecular ideas about which glial cells go into what state, what do they produce, what aspects of neurobiology are then being changed before you use it as a platform for drug screening. There could well be, there almost certainly are some drugs that are good for you because they're cell intrinsic, that is they go to the cell, they do their good thing, end of story. But many others are not cell intrinsic. They might
go to the brain, cause some tiny number of cells in the brain to make a different hormone. That hormone might go to the liver, cause the liver to do something good, which might go to the skin and cause the skin immune cells to help protect you. There might be two or three or more steps in direct. Modeling that in a single cell culture, I think is ⁓ really tough or not doable. That, the only way I think you're ever gonna...
get inroads into that is in the whole animal of which the mice are the obvious animals to work.
Brent Valentine (56:13)
Yeah, that makes sense.
Keller Kramer (56:14)
Yeah.
And then looking at some other, I guess, high tech ⁓ solutions or aids to drug discovery, how are you guys using AI at the IDP? if you're not using it, how do you envision that it could be used in drug discovery?
Rich Miller (56:30)
It's wonderful to ⁓ play chess. you want to cool down after a long hard day at the lab, playing chess against an AI is really recommended. If you want to have fun pretending to be talking with a psychiatrist, AI is really great for that. And it's a wonderful toy. I can see why people want to play around with it. I'm not aware yet of any important discovery in aging that came about because of AI. ⁓
And there are people who say, yes, I'm going to sprinkle some AI juice on my system and that will help you. And that's cool. But I would love to ask them exactly what questions they think a specific AI algorithm can solve.
that that and prove it, you know, that they need to solve and then they think they can't solve it unless they apply a specific AI approach to that. Now, there there are things related to AI and specifically machine learning algorithms for say nonlinear regression. It actually do work. Those are really important. ⁓ We've just published or submitted a paper in which we a student of mine, a guy named Bretton Badenoch ⁓
used a machine learning method for looking at the kinds of changes in your blood chemistry that occur with drug one, drug two, drug three, drug four. What he programmed his statistical routine to do is to say, what are the common factors? That is, what factors in the blood are best at discriminating the slow aging mice from the regular old mice? That was a hard problem that one couldn't solve just by sort of
looking down the spreadsheet yourself. And the machine learning algorithm did a great job of that and is now ⁓ very good, five out of five, at picking drugs that work in mice. It also has the great advantage, it tells us which metabolites, which of these blood chemicals are the influential ones, the things we want to look at when we're developing ideas for new drugs. So complex
statistical programs are already playing and will continue to play an important role in all sorts of science. But the things what people are thinking about is AI so far are ⁓ some of them are very successful at working on protein folding, for instance, that it's made major strides on that. ⁓ But the things that have gotten a lot of funding and attention are things that produce natural language speech. Not often, not always right.
One of my colleagues is developing a drug screen in mice. So he took one of the more popular AI thingies and said, which drug will work better, rapamycin or resveratrol? Now we know the answer is rapamycin. We wanted to see if the chat thingy could do that. And it solemnly said, there's good answers on both sides of that equation. Here.
why you might think rapamycin and here's why you might think resveratrol. And my friend said to it, yes, no, I know that stuff. Which is the better argument? And the thing couldn't get off that, well, you know, there are good arguments on both sides. You've seen our government, the economic geniuses who are running our government, a program called ROC, a program that Elon Musk has developed, to ask it what is the best formula for deciding on what tariffs should apply to each country.
Keller Kramer (1:00:00)
haha
Rich Miller (1:00:11)
And it came up with absolute nonsense, complete, ⁓ ignoramus, but it was confident. And if you believe that AI can solve that problem, you would use that to ruin the world's economy as has been done. If you find something AI can do for aging research, let me know. I would love to hear about it.
Brent Valentine (1:00:31)
Yeah, I think it's probably still too early. Yeah, because I think the stuff that I've been hearing about the most would be if let's say the aging rate indicators come about and then it's like, okay, those are the targets now based on like training a very specific model, really what chemical compounds would match these or like speed that up. That could work.
Rich Miller (1:00:35)
You too.
Yes,
that's very good. One of my collaborators, a guy in Michigan named Sriram Chandrasekharan, is an expert in what he calls in silico cell modeling. He'll put together a complex model with hundreds of components. This enzyme modifies this chemical, which then modifies this enzyme. And when these two enzymes go up, the cell will turn on more of this messenger RNA. That's what he's really good at.
look at a model that he made of a cancer cell and say, here are a thousand drugs that modify these enzymes, which drugs will kill the cancer cell? That has become very accomplished at that. So we're working with him now. We haven't gotten anywhere yet, but we're just starting to say, okay, here are the things that the good drugs do to the liver cells. All of the liver cells from all 10 kinds of our slow aging mice.
Here are the metabolites that go up, here are metabolites that go down. Can you please construct an in silico computerized model for what a liver, a normal liver cell looks like and what the liver cell of these slow aging mice looks like and then put a circle around the elements that are changed. So we can use that then to say, oh wow, I wonder if there might be drugs that change those four enzymes together. I think
Keller Kramer (1:02:07)
you
Rich Miller (1:02:20)
These computer-dependent ⁓ model systems are in their infancy and are highly promising. So far, not much has been accomplished with them, but I think five years from now, it would be entirely plausible that they become important elements of our drug search.
Brent Valentine (1:02:44)
Yeah,
that makes sense.
Keller Kramer (1:02:48)
And then you mentioned it briefly before, but are there any common misconceptions in aging science that you would like to comment on? Particularly mentioning that telomere length is something that you felt strongly about.
Rich Miller (1:03:03)
Yeah, the world, including aging conferences, is filled with common misconceptions. The most important is that throughout the informed public, that is people who go to universities, people who run for a seat in Congress, and people who run major research institutions, they haven't quite gotten into their heads yet that you can slow aging, right?
And that slow aging is kind of a good thing to do because then people stay healthy longer instead of being sick and then dead. They can stay healthy longer. And the right way to actually help people stay healthy and productive and active longer is to slow aging. The general feeling in people who aren't thinking very much about it and unfortunately even among a lot of scientists is that no, you can't slow aging. You're wasting your life.
looking for slow aging drugs because you can't slow aging and they're wrong, but they haven't figured that out yet. One of the reasons it's hard to figure that out is that most of the people on TV and in the Las Vegas conventions of the American Anti-Aging Association, they have something to sell and they don't mind lying or concealing the truth in order to get you to buy their stuff. So those of us who are actually interested in serious science and developing anti-aging drugs are sort of lumped in the connect
collective consciousness with those charlatans and and hucksters, which is not good for the field at all. It gives it a sort of a yucky, icky kind of aura about it and it makes it harder for people to take us seriously and harder for scientists to decide they really...
Those are the sort of community ⁓ vibes in a sense, or community assumptions, latent assumptions, unexamined wrong assumptions that are most importantly getting in the way of making progress. If a president goes on TV and he or she says, we will devote the resources of my administration to conquering cancer, everybody applauds and the popularity goes up. Everybody's in favor of
conquering cancer or in the last decade conquering Alzheimer's, all that's good stuff. If a president goes on TV and he or she says, I'm going to devote the resources of my administration to slowing the aging process, you say, hey, this fellow's gone off the deep end, you can't slow aging. And that's the problem because it is possible to slow aging. We've proven it in mice over and over and over again. And it is not.
Keller Kramer (1:05:31)
You
Rich Miller (1:05:43)
currently possible to stop or even slow Alzheimer's or to stop or even slow cancer except by slowing the aging process. So the community understanding of success and promise of anti-aging research is currently the major barrier to making rapid, more rapid progress. Of every hundred bucks that goes into the National Institutes of Health, six cents gets spent on the kind of aging research we've been talking on.
And that's insane. I'd settle for 1%, which is a 16 times increase in the amount of money going into the science. 10%, which would be 160 fold increase. That would be about right, I think. no one is interested in my opinion about this. Then there are specific misunderstandings about which lines of investigation are most likely to be productive.
Keller Kramer (1:06:18)
Hahaha.
Rich Miller (1:06:43)
There are historical reasons for thinking telomeres or senescent cells might be the key. It's now in retrospect obvious that people were misled, not by fraud, but by a misunderstanding of how to interpret strong, reproducible, but misinterpreted sets of data. And once you have a critical mass of people patting one another on the back and making awards to one another, it's very hard to sort of scrub that out of the system there.
sort of a hundred labs now, which are firmly committed to the notion that senescence happens to a cell, that you can make a cell be young or a cell be old, and that getting rid of the old cells is all you need to do. There are a dozen companies with massive capitalization from venture capitalists who have money to burn and don't want to talk to people who disagree with them. They'll throw $100 million with this idea.
throwing things on cells to make the cells younger without stopping to ask whether the bad things that happen in aging are because you're filled up with old cells or
this complex community of people who all buy the same interlocking sets of hype, they make awards to one another, review one another's grants and give them all good scores, they get into the best journals because they tend not to want to, the editors and the people who are venture capitalists tend not to want to talk to people who are skeptical about this line of research which seems really, really exciting and they've seen.
mentioned in the New York Times and in the Economist, so it's got to be good, right? There's a lot of that. I you mentioned telomeres. I would have included telomeres, that's for sure. Senescent cells, which comes from that same sort of general area of science, and there are sort of a dozen others.
Brent Valentine (1:08:39)
Yeah. And then just to be like clear, I'm thinking you're saying like, if we were to give more funding for aging, we would actually increase the like efficacy outcomes of all the other individual diseases that kind of fall downstream of aging.
Rich Miller (1:08:54)
That's the hypothesis and I think there's pretty good evidence for it. For instance, the oldest discovered effective treatment is this caloric to diet. The mice on the caloric to diet, they have slower development of cataracts. Their immune system stays better for longer. Their bone aging is more slow. Muscle aging is more slow. They live longer. They get fewer cancers. works in 95 % of the different genetic backgrounds.
More recently, ⁓ two or three of the genes like the Snell dwarf mouse, the Ames dwarf mouse, growth hormone receptor knockout mouse, and a couple of the drugs like kinagliflozin and rapamycin, people have begun to accumulate data of this general sort. And although it's probably not true that 100 % of the things that go wrong with aging are slowed by every single drug, when you look, 80 or 90 % of the things that happen with aging are slowed by drug one and
to drop by drug free. So it's a...
supported ⁓ conclusion that many aspects of aging are slowed by these anti-aging drugs. Therefore, if you gave them to people, and they work in people, something we don't know yet, but if they worked in people, the expected outcome is that an awful lot of age-sensitive diseases would occur, but they would occur later.
Brent Valentine (1:10:20)
Yeah, that makes sense.
Keller Kramer (1:10:23)
Then wrapping up, do you have any advice to researchers in the field or any last words you want to part about the need for attention in biogerontology in general?
Rich Miller (1:10:37)
Well, we've touched on that important question many, many times during today's ⁓ discussion. I would ask, if I had to make one pitch, I would ask people who are not trained in aging research but are trained in say, heart attacks or vascular disease or bone disease or cancer biology in particular, ⁓ to try to peek over the silo that protects them from being contaminated by the results of aging researchers. ⁓
The cancer biologists, at least at Michigan and I think nationally, they think that cancer biologists have perfectly proven ways of discovering anti-cancer drugs. That's what they do. They're the world's experts at it. They're really good at it. The drug companies pay them for their consulting services. The notion that someone who's not a cancer biologist has a new idea, a way of, and it actually works. It actually slows cancer over and over again, many kinds of cancers. They sort of...
understand the basis for that, but not enough for them to actually change anything they do. ⁓ And I think that's a terrible loss of opportunity. I haven't had equally ⁓ frustrating sets of conversations with the brain biologists and with the muscle biologists and with the heart biologists, but it's only because I have a limited capacity for frustration. I was on a radio show, this was before podcasts were invented, believe it or not.
It was an actual live radio broadcast with a guy named John Trotsinowski, who was head of Alzheimer's research at PAN. He and I were in good terms. He a really great researcher. died a few years ago. And the radio interviewer asked me what I would do if I were in charge of Alzheimer's research. And I said, it's obvious. Of all that tons and tons and tons of money being poured into Alzheimer's research, both by the government and by private foundations.
take 5 % of it and use it to study aging because so far the only thing we've got that is slowing neurological degeneration is anti-aging drugs. So wouldn't it be good for the Alzheimer's crowd to allow 5 % of their vast financial resources? They can't spend it fast enough. They can't find people to spend the money on fast enough. Why don't they give 5 % of it to study
of the effect of anti-aging drugs on neurodegeneration. And Trojanowski, the Alzheimer's guru, said, no, you're trying to take our money. You can't do that. This is important. Don't you understand how important Alzheimer's is? We need every single dime of it. And he viewed my suggestion as an attempt to steal. And he's not alone, unfortunately, in that understanding.
terrible shame and is retarding progress in the preventive medicine and our understanding of multiple disease, nearly every disease that people get, the main risk factors how old you are, if you're 80, chance of getting diseases one, two, three, four, five is enormously greater than when you're in your 30s. That's because of aging and people outside the rather narrow field of aging biology.
They kind of know that, but they don't understand that that's what they should be focusing on. People want to focus on how does cholesterol cause heart attacks? That's important, but far more important than cholesterol is how old you are. And they just don't ever work on that. It's somebody else's problem. It's the problem of the aging biologist. That's the message that I hope not just younger scientists, but even older scientists would open their minds to. Somebody, ⁓
in the early 20th century was asked, what is it going to take before quantum physics and the Einsteinian revolution became the dominant mode of discussion, replacing Newtonian mechanics? And this fellow said, well, eventually all the current physicists will die and then we replace them before we learn this growing up. Unfortunately, it's kind of a cynical but alas, potentially accurate way. I think the notion that aging is the
aging research as the key to understanding the pathobiology and prevention of multiple diseases is going to be hard to accomplish while the decisions are being made by people who grew up without that tradition.
Keller Kramer (1:15:08)
Cool.
Brent Valentine (1:15:08)
That makes sense. Well, thank you so much for a great conversation today.
Rich Miller (1:15:12)
Yeah, thanks for inviting me.
Keller Kramer (1:15:15)
Thank you.