In its third season, the Longevity & Aging Series is a video series that features esteemed researchers discussing the latest in aging research.
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Below is a transcript of the Season 3 premiere of the Longevity & Aging Series with Dr. Yu-Xuan Lyu from Southern University of Science and Technology (Shenzhen, China). Here, Dr. Lyu joins host Dr. Evgeniy Galimov to discuss his co-authored research paper, featured as the cover for Aging (Aging-US) Volume 16, Issue 20, titled “Longevity biotechnology: bridging AI, biomarkers, geroscience, and clinical applications for healthy longevity.”
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Welcome to Longevity & Aging Series. Today I would like to introduce to you Dr. Yu-Xuan Lyu. Yu-Xuan is a research assistant professor in Southern University of Science and Technology in China, and he focuses his research on mTOR signaling and autophagy. Yu-Xuan is a co-author of a recently published review titled Longevity Biotechnology: bridging AI, biomarkers, geroscience and clinical applications for healthy longevity. This review summarizes the latest developments in longevity biotechnology presented and discussed at the aging research and drug discovery meeting in 2023. So Yu-Xuan over to you. Maybe you will give a more detailed introduction of yourself and your research focuses.
Thanks a lot! It is really amazing to have this opportunity. So as you already introduced myself, I am currently a research assistant professor at the Institute of Advanced Biotechnology at Southern University of Science and Technology. It’s very hard to pronounce it, but basically it’s the SUSTech in China. So the place is in Shenzhen, a city very close to Hong Kong and now you might also have heard about DJI or Huawei. So those companies actually come from Shenzhen. So that’s just to give you where I am and why I’m working on that. But beyond that I also serve as a lecturer at the Geneva College of Longevity Science in Switzerland. So that is one of the reasons why I take this position is because I think there’s two main reasons. So the first reason is I was formerly working as a researcher at the Max Planck Institute for Biology of Aging in Germany. So that’s I think one of the most advanced basic fundamental research institutes on aging and longevity,
And the second is that I’m very keen to push the longevity education because I believe that the longevity if we are going to, in the future, if we can use aging research and also the longevity medicine to apply to the human or translational applications, so technology is something very important we’re going to talk about more in detail today. But also education. I think it’s very important, especially we need to create a dialogue between our researchers and as well as the people who actually would like to understand what longevity research or longevity medicine means and what actually they can benefit from that. So that is one of the reasons I take these positions.
And beyond that, I think as you already gave me a very nice introduction, so I’m focused on the mTOR autophagy signaling cascade. And especially on the sex differences of aging and pharmacological interventions. My former work in the Max Planck is mainly focused on rapamycin, it is one of those that we call geroprotective drugs, we hope that they actually can also apply to humans in the near future. But now that I move back to China, we’re also trying to find nicer, no matter whether it’s supplements or drugs or even fancy other ones, technology can actually try to extend the health span as well as the lifespan in humans. Yeah. So that’s my short introduction. Thank you.
Great. So this paper, this review recently published is basically summarizing the state of the field in our longevity biotechnology. So can you please give some brief overview of this and maybe the main technologies which are driving the field?
Yeah, thanks a lot. I was very glad to share these reviews. Basically if we look into the title, I think we can already see that this paper is mainly trying to get the current or the much modern advance of AI. So that’s one of the very important things in the field at the moment. As well as geroscience and also some technology as well as, how to say, this longevity medicine, so mainly the clinical application. So we’re trying to combine AI, geroscience and biomarkers as well as this life medicine. Sorry, not life medicine but longevity medicine, trying to combine together and see how actually we can create an ecosystem for longevity (bio)technology. Because I think the most important thing at the moment is that we already have quite a lot of advantages and knowledge in different categories.
Like AI, now we have the ChatGPT and as well as we can actually use AI to do the drug discovery, which we might talk about later. But how AI can actually benefit healthcare and also find out drugs which can benefit age-related disease. So that is something actually we need to not only look into AI but also the general science because general science basically provides you with the basic mechanistic of aging, So what aging is and how actually we get old and how actually we can actually extend our health span. So all these mechanistic things, the biological mechanisms, I think that is something actually we need to understand before we can combine with AI.
And as well as the longevity medicine nowadays we call it this more like a prevention medicine because we do believe that if we are going to slow down or even compress the age-the related disease, we cannot only use the current model of a medicine which is we first have the disease and then we use the drug to treat that, We know that if we can actually find out the best time window early on, then actually we can apply some of the interventions. So somehow we can actually prevent age-related disease and also extend our health span. So this paper is trying to combine or try to harmonize or everything which is I think important for longevity in humans. Thank you.
Definitely. And you also mentioned the omics, comprehensive omics and innovative agent clocks. So which also include some AI technologies. So if you start talking about AI as a main driver of biotechnology in longevity, when it’s applied to drug discovery, can you give some overview of that? How is it used in drug discovery and what are the most important parts in the pipeline which could be solved using AI?
Okay, thanks a lot. When we talk about AI, it is huge, So I’m trying to pick up some of the things which I believe are most important for extending our healthy longevity, So one of the key things we find out at the moment is we can apply AI to accelerate drug discovery. So that is something we cannot achieve maybe 10 or 20 years ago. So that is something which is important. So one of the things we found out is that AI can accelerate, especially the early stage of drug discovery at the moment. So in the past decades when we look into this drug pipeline, we might need to spend two to three years for the early stage drug discovery, from finding the target and then to validate the target and also find the lead and then we find the lead and then now we start and do this preclinical animal test and so on.
But now the AI actually can help us to compress this stage from two to three years and then maybe two to three months. So that’s very impressive because I think there’s a few examples including one of our last authors, Alex’s company Insilico. So actually he published, I think his company published at least two very important papers this year, sorry, last year basically, in 2024.
So they find out that the AI can actually really empower the early stage drug discovery to shorten the time. And then also maybe this shortened time can actually cure a lot of things because this is one of the challenges in drug discovery that is we take too much time at the early stage before actually we can get into the clinic. So that is one of the examples. And then the second example, I think I can also tell you that it is something, actually you can combine the AI with the omics. So the omics is one thing I think is very powerful because the omics can tell us not only one point, right, it’s multiple information that can systematically describe our bodies or maybe there’s some kind of disease or somehow the aging information.
But the omics also have a problem because our brain, at least my brain, is not able to handle too much information at the same time. So AI gets in, the AI can help us to digest the information from the omics and then show us the most important information. So that is much easier for not only the researcher but also for the physician who actually in the future can actually apply, use the AI to understand the omics and use some of the omics data to identify the most important biomarkers of aging and also can show how can use this thing to apply the most probable anti-aging or maybe geroprotective therapy or interventions. So I think that is a spiel of the case. I can tell you what AI actually can do. But I believe that AI can do much more. So nowadays I also use AI time data on a daily basis to help me to understand, to trace, to follow the most recent scientific findings as well as to help me to also polish some writing. I think that’s something actually AI is incredible. That’s what I would say. Thank you.
And do you use AI at your lab too? You said you’re looking for geroprotectors, or more to other substances which could extend lifespan. Do you use AI in your lab and if you use, how do you do this?
Yes, thank you. I think that’s a very good question. So we are at the very early stage because I just started my labs earlier this year, sorry, early last year. So basically I’m going to have my one year’s lab establishment anniversary next week. But yeah, I actually started using the AI, so basically this deep learning algorithm to try to understand the differences between the compounds as well as trying to analyze the image. Because one of our current projects, so one of our projects at the moment, we’re trying to build up a high throughput animal in my lab. So we are using AI at the moment mainly for two reasons.
So first is trying to screen the drug library because I think that somehow that we do have a lot of compounds but we cannot do all the screening to do the aging related experiments. So we’re trying to use AI to give the hints that, okay, can you just give us some of the drugs that have potential targets, maybe this signaling like the mTOR or autophagy? So AI does a very good job because they basically just do the screening and also try to find out the literature behind that. So that is the one thing.
The second thing is that because our lab also starting to establish a high throughput animal based drug screening platform, so something similar to the Wormbot, I think Matt Kaeberlein and I think Ora Biomedical and also a couple of companies using start to establish those things in C. elegans. So we do it in fruit flies. So because we believe fruit fly can provide something unique compared to the C. elegans, but nevertheless all those high throughput things, animal base, is basically you have to connect a lot of image and video , And because it’s behavior based. So this AI is very powerful and can help us to identify what the behavior and all the response would have the potential to indicate can be used as a potential indicator to show that those interventions, for instance like a drug A or drug B can have some beneficial effect to the animals.
So that’s the second thing and I think this will be very powerful because when we look back maybe 10 or five years ago, we don’t see any small animal can be used for drug screening because basically usually we just use the cell base and then we jump into the mice. Because the cell base is much easier to analyze then. But nowadays because we have AI so we can actually see a lot of company or also researchers start to use that small animal because we see that some advantage to using small animals, especially the animals which live relatively short because then we can actually test the compounds to see if they can extend the health span but also the lifespan in several weeks or maybe several months, which I think in the future actually we can also accelerate the drugs which can use for age to against aging or against age-related disease much quicker than before.
And you mentioned that you’re doing some screens on drosophila, which is quite interesting. And to be honest, personally I never heard of any screens on drosophila in automated way. Are you aware of any other competitors in this field? And the other question is what kind of diseases or what kind of drugs do you think drosophila would fit better?
Okay, that’s a very good question. So, thank you. So first I think there are not many competitors. I think the reason for that is because drosophila is, even though it’s a very, very well known animal model, the animal model in the research field, but there’s not many people using them to do the drug screening specific for anti-aging or maybe aging research. And we do this because, first of all I work with flies, I think more than seven years. So I do understand flies. And I also have a chance to work with C. elegans. So I do know that they do have a different advantage in that sense. So for drosophila, there’s something I think is a bit out performance through the C. elegans, it’s because they do have two sexes, Natural. So they have males and females and we also see that there’s a lot of intervention including the rapamycin and spermidine in which I perform. And they show significant sex differences.
This is somehow actually to mimic what the mice show that at least in mice, including the light ITP experiment, we do see that rapamycin will have a greater impact on the lifespan of females compared to males. So that is something we also see. So I think that’s the first thing because they do have a natural two sexes. And the second thing is that, drosophila, they do have the adult stem cells. So we know that if you look into the hallmark of aging, so one of the hallmark is a stem cell exhaustion and that is something actually drosophila can actually do much greater jobs if we want to look into how the stem cell renewal and how the stem cell can somehow be connected to each other.
And the only drawback I have to say is that, or maybe two drawbacks let’s say compared to C. elegans. First, the adult of drosophila is not transparent. So if we want to do fluorescence, you need to find a way to do that. But we are already trying to establish fluorescence space experiments. So far it looks really nice. We were actually able to catch up. So that is also somehow beneficial to the AI because the AI actually can do a very good job to remove the noise and capture the real signal. So that’s the first thing.
And the second thing is that I think drosophila live a little bit longer than the C. elegans. And if we’re going to just do the lifespan screening, so that is of course, I think C. elegans is far better. But on the other hand, nowadays, I think the people are more keen to look into the health span rather than lifespan because we know that living healthier is much more important than only living longer,
And drosophila, because they’re more comprehensive in the sense they have legs, they have brains, they also have gut and also they have a heart. So then you can actually create more behavior-based measurement including sleep. So I think drosophila also has a very nice sleep curve similar to mice. So I think that’s something we can actually achieve. We can get more information when we do drosophila. Yeah, so I think that is one of reason I think I will use drosophila, but I think that’s also nice that we get a lot of very nice support from the people using C. elegans to tell us that, okay, these directions should be very promising and we should just keep going. So, thank you.
Well you mentioned that in C. elegans you also can potentially study diseases because they actually have age-related diseases too.
Exactly. Sure, of course. I think that is one thing we also need to appreciate that those small tiny animals can do a lot of things. And also one thing I would like to add because we already have a startup project together with some of my former colleagues in the Max Planck society. So we got support from the Max Planck innovation and we hopefully can establish our company. And later this year that’s what, I need to check with our CEOs, but we already get some kind of financial support to move these projects to the real world applications. And we also started to collaborate with one of the biggest CIOs in Europe and I think the current preliminary data using drosophila to screen drugs or let’s say to measure the toxicity response to the drugs, I think it’s very nice. So I hope that we actually can use drosophila to do more things, not only the drugs toxicity but also the age-related diseases. Thank you.
Amazing. Back to the paper, I remember you mentioned one of the papers from Alex and he has a paper, this so-called dual approach when they simultaneously target particular disease but also some age-related pathways. So do you think this approach would help to establish aging as a disease and help to get some regulatory approvals?
Yeah, I think it’s a very smart way to deal with this. Because one of the burdens, one the biggest burden to define a drug or find a therapeutic way to target aging is because aging is not a disease. So no one’s there to actually push this forward to invest the drugs to target aging, only target aging because they might not be able to get approval and then lose lots of billions of dollars. And I think the dual approach is very nice because no matter how aging might be defined as a disease or not, I hope that will happen in the future, but at the moment we need to follow the current regulatory path. So I think finding a way to find a specific target which is called maybe cancer or dementia or whatever related to this age-related disease I think would be a very nice way to at least find the drugs we can target this.
And at the same time we’re also trying to find out whether this drug can actually also have other potential beneficials like anti-aging. So I think nowadays we also see a lot of very powerful drugs, right, that can actually do multiple functions. Not only one thing but multiple things. I think the point is because for the regulatory agents, I think they’re mainly focused on not the mechanisms behind the disease, they’re more focused on the response for the human. If the drug gets in, no matter how they go, as long as you can relieve the disease symptoms and also have a relatively safe profile and then you get approval.
But for the researcher we are more focused on the mechanism, the mechanism of things. So nowadays we know that aging and the age-related disease have a lot of overlaps including cancer. And if you look closely, I forgot the name of the paper, but basically you also find the mega hallmarks of aging and cancer, something like that. So we actually found out there’s a lot of overlapping between aging and cancer and maybe also dementia. So I think we designed drugs to target one of those hallmarks and potentially we can actually hit two birds. So I think that’s a very nice approach for this dual purpose. Thank you.
Yeah. Let’s move to biomarkers area maybe. So can you share some reflections from the conference about biomarkers?
Yeah. So yeah, thank you. The biomarker is always I think one of the hottest topics in the field since 2013 or whatever, like Steven Horvath, they launched the first, the DNA Methylation clock and also the biomarker is something also related to that. And nowadays, we see a lot of different biomarkers as well as a lot of clocks. So from the DNA Methylations and to maybe a cytokines or almost like a metabolite.
So I think the field is going very well, but we still face a lot of burden because most of the biomarker at the moment we collect is more like this, how to say, the cross-sectional collection, we were not able to collect it longitudinal, at least for most of the studies. So we can build a correlation. But whether these are causations, we don’t know yet. At least for most of us we cannot say that okay, this marker change is something that can actually reflect your body’s change. And I hope maybe in the next five years we can actually do more longitudinal study and also powerful with the AI because one of the important things like all this new biomarker, we might need to cross check with the old generation or the traditional biomarkers like the glucose in the blood, And maybe also the heartbeat and something like that.
We need to actually have a validation between the new generation of biomarkers with the old whether it is outperforming the old generation. If not, then we also have trouble, okay? The people will say, physicians will say, okay, we spend a lot of money more than before. And then you just tell me, okay, then those biomarkers, the traditional one and the new one are basically all the same. That is also very hard too. We need to have a very nice study and maybe not only one study but multiple studies to prove that the biomarker, which is something linked to the… Can actually indicate your health perspective but as well as maybe it also outperforming compared to the traditional one. So I think it’s very promising at the moment, but we still need some time to actually use that omic base or whatever biomarkers in the clinic settings. Thank you.
So basically we need to relate some agent biomarkers to some clinical outcomes to prove that they’re actually showing something meaningful.
Yeah. So I think that nowadays if you’re going to this… There’s several settings I think it’s promising. One of things like the TAME trial. So I have to mention the TAME trial because we all know that the TAME trial is very important. And because it also includes the biomarker. And as long as we can see that, one kind of promising geroprotective interventions can not only extend your health span, decrease your age-related disease potentials, sorry, age-related disease chance, as well as to change your biomarkers. And I think that is something actually you can start to tell that, okay, maybe that is some correlation between the biomarkers and the geroprotective intervention and as well as your biology of aging. So we do need such a clinical setting or clinical trial to prove that.
And talking about clinical trials. What would be the main challenge for them? Do we have the right idea about the targeted population? Should it be younger people or older people or sick people, people who already pass an optimal treatment window? So is there any proper discussion on that in the field?
Okay, thanks. I think at the moment I don’t think we have… We do have a lot of discussions. I have said that, but I don’t think we have an agreement to say which setting would be the best because aging, we still don’t have the clear definition of when the aging started. I think recently there’s a paper published that collects, they did surveys in one of them, I think it’s in the Golden Conference in 2022 if I remember correctly.
So they show that even in the aging field, different researchers will have different ideas when the aging starts. So some people believe it starts when you arrive in the world, So start very early. And some people believe after 20 or 25 years old. So I think if there’s no definition of when the aging starts, I don’t think we will have a very clear definition or the groups to find out how we can try to start an aging intervention to a specific group. But we do see that in different countries or different regions, they started to use intervention to help the people. So that’s including dietary supplements, including some of the small molecule drugs. As well some people actually use the stem cell or maybe the cells, this gene therapy.
So even though there’s a very small cohort, we do see that people are trying to take, I don’t know whether to take the risk, but as some people are trying biohackers and trying to use those approaches to prove themselves. And we do see that mainly of these people around maybe after 35 years or after 40 years old and then something between 35 to 60 or 65. So that is some middle aged people.
I think the people are there too, because I think in those regions that during this age range, the people usually they’re already knowledgeable, they can take their own responsibility. And they are also relatively healthy and they would like to take some very improved interventions, let’s say like that. So I think that might be the target group for the most advanced aging interventions, maybe for the middle aged people. But that’s just my conception and that’s what I see. But I do have a survey which I’m going to share maybe next time and next week at this NUS Healthy Longevity Webinar. So we did a survey in China and we found that the age groups who are most interested in anti-aging or let’s say the age related or aging interventions are middle age groups from 35 to 55, something like that.
Great. Yu-Xuan, part of your review was about longevity medicine. Can you just summarize and give some introduction to this new field?
Yeah, so thanks a lot. And so a longevity medicine as just my opinion, I think it’s a very nice way to… It’s redefined the prevention medicine as well as the personalized medicines because longevity medicine is mainly focused on healthy aging. So I think that’s the first thing. And the longevity medicine doesn’t like the current medicines in the hospital because most of the medicine at the moment, if you go to the hospital and then one of the medicine or one of the physicians will take you to do the exam and give you the treatments.
So the current medicine is basically if you have a disease, if you are sick and then you go to the hospital or whatever clinic and then the medicine can help you or treat you and cure your disease. So that’s the current medicine. But longevity medicine is more like a prevention as well as the personalized medicines, because a longevity medicine is something more advanced in terms of before you get the disease, as long as you are getting old or maybe have some age-related disease or disorder and in the future the longevity medicine kicks in. They help you to change, maybe not only your lifestyle but also maybe use some intervention including supplements, drugs as well as maybe some other possible way to actually to help you to maintain your health.
The longevity medicine is not the medicine that gives you a pill or maybe to cure your disease but rather trying to prevent your age-related disease. And also I think that is the first thing. The second thing is longevity medicine is very personalized medicine. So that is one of the reasons longevity medicine somehow is very endorsed or empowered by the AI because AI actually can help us do a lot of things including the personalized approach. And these two things are very important aspects for longevity medicine. The prevention and personalized. Thank you.
Well obviously this creates some challenges because at the moment in current responsive medicine is quite expensive, so becoming more complex. So if you include a more preventative approach, but we’ll use aging clocks and various diagnostic tests combined with AI, it might create some danger that it will be available for only rich people. So yeah, do you think it could be possible to make longevity medicine available to a wider population?
Yeah, I think that’s a very good question. I think that’s always a hot topic of debate in the field that not only longevity medicine but also apply to the other more advanced approach. So I think you might be right at the moment because if we combine this Omic, the AI and also all these advanced things, the cost is unacceptable for the ordinary people, But if you look into the cell phone revolution or even the computer revolution, at the very beginning only the rich people could use the cell phone despite that at that moment it’s very huge cell phone. We don’t even call the cell phone at that moment. But just after a few years, the prices, the rates dropped because people see that it is very useful and actually can help the people. So I don’t think it will be an issue in the near future because you can see the AI revolution is crazy.
Maybe two years ago we couldn’t even talk about it, maybe we cannot even believe that, okay, there’s a ChatGPT comes in and now we actually we only need to pay a couple bucks and then we already can use the rare most advanced ChatGPT can help us to do a lot of jobs. So maybe at that very beginning or actually at that moment, at this moment, a longevity medicine is still relatively expensive, I have to admit. But after maybe two or three or even five years I think they will be dropped crazily and most of the people actually should be able to afford it. So that’s my perception. Thank you.
Thank you. Great. So what do you think the main challenges for longevity medicine exist at the moment? Or bias. Maybe you see them in China at least?
Yeah, I think that, so one of the things for longevity medicine, the challenge, I think the first challenge is somehow the perceptions. Because it’s called medicine, but actually it’s not the traditional medicine. So as I mentioned, that’s more preventive. So all the people, at least for most of the people in the public, believe that we already have a concept when the medicine is going to cure a disease. But aging is not a disease or a prevention is something we cannot cure before we have them. So I think that is one of the challenges you need to let the people understand. Okay, longevity is something that can actually help you to prevent some risk, some age-related risk in the future. So we might need to take a different approach compared to the current medicine to educate people and also try to talk to them to let them believe, okay, I’m not going to trick you because the people think that okay, I don’t have anything, why I should buy, why has to do the longevity medicine? So I think this concept, the mindset needs to change.
And the second thing, as you mentioned, because it’s prevention medicines. And for most of the longevity or health related indicators are very hard to catch at the very early stage. At the late stage like this current medicine, we only know that we have all the biomarkers to show that, okay, you have a disease because we have those indicators. But for longevity medicine, because we do not very understand what aging is and we don’t at the moment, we don’t have very powerful or let’s say the biomarker actually can already apply in the clinic settings. So that creates a lot of trouble. That’s how we can define whether you are at a health stage or maybe you might have a risk in the near future. Maybe after a couple of years you might have some risk. So now you need to start with longevity medicine. So I think that there are a lot of things we still need to solve before we can actually convince the ordinary people or lay public to use a longevity medicine. Thank you.
Great. And for this conference, can you share any main breakthroughs or do you believe there are any technologies or interventions which are closer to translation in clinical practice?
So there are quite a lot of wow technology breakthroughs. So I cannot name all of them so I have to admit that. But in my opinion, I think one of the cool things I believe can be used in the clinic relatively quickly is this inflammation, the anti-inflammatory treatment. No matter like this IL-11 way to try to inhibit… Sorry. Anyway, trying to modulate this chronic inflammation can actually do a lot of benefit, to create a lot of benefit to extend your health span but also decrease lots of risk in terms of like the autoimmune disease as well as the other disease, something that will happen when you get old. So I think that is something that should be relatively easy because the inflammation is something that is relative, well established in the clinic setting.
So we know that if we look into cytokines, like the IL-6 or IL-10, the change is something we do know that is something related to your health status. So nowadays, if we are actually trying to find a drug or compounds, let’s say, like trying to balance those changes, especially when you’re getting old, I think that will be very useful and very powerful to apply into that setting. Thank you.
And another question what I would like to ask you is do you have any particular main challenges with regulatory approvals at the moment for these interventions? Because as I understand there are no biomarkers or intervention which is approved. What will be the shortest path to this?
Okay, very good question. Very good point. So I have to tell you that initially when I moved back to China, initially I wanted to start to work on this drug intervention similar to rapamycin, right, in China. And then I found there’s no investor interested in that because it’s a very long path, I’m not going to do that. Maybe because it’s China, it is not the United States. In the United States maybe they have a much better understanding of how to invest in drugs to fight against aging. So that is a different story. So if I particularly talk about something that happened in China or maybe in the rest of the world, we found that actually the people are more keen to go into the no regulatory territory to find the compounds that can fight aging. So at the moment we are trying to put more weight on the supplement. Despite that, we do know that supplements are not really nice in the field that they do not believe supplements can be useful because they do have regulations.
But we do know that at the moment if we talk about some general protective compounds, at least in pre-clinical animal testing, we do know that including the NL and N, they somehow they show some benefits, not all, but at least they show some benefit for some age related disorders as well as the AKG and spermidine and also a lot of the new things. And we also see that some companies including Nestle and also the other, these supplements or nutrition companies, put a lot of effort to find a new compound to go this way. So that is also one of my focuses at the moment trying to collaborate with a nutracellular company to try to find out if we can actually find the compounds that’s not going to treat the disease or treat age related disease, let’s say like that. But we are just trying to improve and also slow down your age related disorders and then we found a compound, which we call supplements, that can do something. I know that is not the perfect way, but at least I think that’s a shortcut at the moment.
First step at least.
Yeah.
Okay. And maybe the last question is about governmental institutional steps or initiatives. Maybe you know about any of them in the field.
You mean the government-oriented initiative,
On the population level, because governments operate on the population level. Do they have any initiatives? For example, I know that in the UK they establish trusted research environments to keep the records, medical records for the whole population. And I think there is an idea to use them for longevity. Maybe you are aware of anything like that in China?
Yeah, I think we do have something happening in China, but I think as well as the other countries like this longitudinal aging cohort, I think our government started, at least in China, we started to put a lot of money on to run this longitudinal research collecting these blood samples. And from time to time to describe actually to find out what biomarker can be useful for indicating the aging process or age-related disease process, let’s say like that.
And we do know that the UK Biobank, for instance, is actually very powerful for aging study as well as some disease studies. And in China, I think also in the rest of Europe and also in other countries, we also started to collect those things, particularly like the blood sample and also some people were collecting the stool, the pool sample for the gut microbiome analysis. So those things I think would be very powerful and useful. But of course because it’s a longitudinal study and we were not able to have all the data in those days, we still need to wait for several years until we can actually find this out. But yeah, I think we are actually moving in a very good direction to collect those data. So I think that’s something we should appreciate.
Cool. Well the last question is, you mentioned in the review, something about decentralized science and some new approaches for funding. Can you just elaborate on that?
Yeah, sure. I think that’s very important. And we see that a lot. We see some of the decentralized science funders, like the VitaDAO for instance, and also a lot of the DAOs as well as some cloud funds to support the clinical research, including the rapamycin I think, and as well as the metformin. And also the other things. Because at the moment, as I said, because aging is not a disease, using a drug to treat aging is something, there’s no investor willing to pay for that. And also the government setting, maybe they believe that this is more clinical study and so they usually only fund the fundamental study, They’re not funded clinical studies. So they create a huge gap to move the clinical translation of research forward. So I think this cloud fund and also all the other decentralized science, I think it’s very useful to actually move this field forward.
And I think somehow I also watched a YouTube video and some of that research might also be trying to say that okay, we start another cloud fund and also trying to hold, we can collect enough money from the people who are willing to contribute to their aging research and trying to move things forward. And also I also have to mention that for instance, this adult aging project, I think it’s a very nice approach that nowadays I think because they lack the funding from the government. So they’re also trying to find a way to get some cloud funding to support their research.
And we are also going to start this in China, hopefully this year or maybe next year, so that we can also do some things together with the people. So yeah. But we also need to look into the regulations because different countries have different regulations in terms of this, but we think, yeah, that would be a very nice way to move this field forward. Thank you.
Great. Thank you for your expertise. And yeah, I hope our efforts will bring more people to the longevity field. And all the best with your research and hopefully I’ll see new talks from you soon and maybe see you at the next ARDD meeting in 2025.
Sure, of course. Looking forward to seeing you in Denmark this year.
Cheers. All the best.
Bye.
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