Revolutionizing Wellness Research with Dr. Jeff Chen: AI, Placebo Effects, and Health Span Strategies

On this episode of Sports Science Dudes, Dr. Chen shares how Radicle Science is using AI to transform clinical trials. This method not only garners authentic data but also reflects a true picture of how wellness products perform in the chaos of daily life.

Timeline:

2:00 The process of how Radicle Science works

4:45 How do research subjects respond if an investigator is not present?

10:19 Adherence in these studies

11:39 The placebo effect

12:33 If you tell someone they are getting a placebo, they’ll still improve if you tell them it will help them

15:44 What’s the latest on CBD? Need a 100 mg dose or higher

20:30 Crowdsourcing as part of running a study

23:46 Who is the PI using the Radicle Science model? The data is owned by the client

26:40 What are the main endpoints that can be done by Radicle Science? Cost is 100k for a trial with a sample of 500

30:12 Radicle Science may serve as a good model for very active adults or elite athletes (e.g., sleep quality)

33:35 Longevity – Dr Chen’s philosophy

40:16 Evolutionary reasons – humans didn’t have many glucose spikes

41:26 Dr Chen’s way of making rice! 

Dr. Jeff Chen, MD, MBA is an impact entrepreneur, executive, physician, and scientist on a mission to transform the health of our bodies and minds using non-pharmaceutical products. He is co-founder/CEO of Radicle Science, an AI-driven healthtech B-Corp providing history's first Proof-as-a-Service solution for wellness products to easily prove their true effects at unprecedented affordability, speed, and scale.  Radicle Science was named by KPMG as one of the Top Ten US “Tech Innovators” of 2022 and by Fast Company as a “World Changing Idea”.  Dr. Jeff gave a MainStage Talk on Radicle Science at TED 2023.  

Previously he was the founder and Executive Director of a UCLA research center where he led clinical trials on natural products.  Dr. Jeff has been interviewed by outlets including CNN, Forbes, Wall Street Journal, TIME, NPR, Entrepreneur, Rolling Stone, NBC News, Financial Times, WebMD, Politico, Business Insider, SF Gate, VICE, Vogue and more for his expertise.  Following a BS at Cornell, Dr. Jeff earned his MD and MBA concurrently at UCLA.

About the Show

We cover all things related to sports science, nutrition, and performance. The Sports Science Dudes represent the opinions of the hosts and guests and are not the official opinions of the International Society of Sports Nutrition (ISSN), the Society for Sports Neuroscience, or Nova Southeastern University. The advice provided on this show should not be construed as medical advice and is purely an educational forum.

Hosted by Jose Antonio, PhD

Dr. Antonio is the co-founder and CEO of the International Society of Sports Nutrition and the co-founder of the Society for Sports Neuroscience, www.issn.net. Dr. Antonio has over 120 peer-reviewed publications and 16 books. He is a Professor at Nova Southeastern University, Davie, Florida in the Department of Health and Human Performance.

Twitter: @JoseAntonioPhD

Instagram: the_issn and supphd

Co-host Anthony Ricci EdD

Dr Ricci is an expert on Fight Sports and is currently an Assistant Professor at Nova Southeastern University in Davie Florida in the Department of Health and Human Performance.

Instagram: sportpsy_sci_doc and fightshape_ricci

Transcript

Speaker 1: 0:02

Welcome to the sports science dudes. I am your host, dr Jose Antonio, with my co-host, dr Tony Ricci. If you're a first-time listener, hit the subscribe button. Like the show. You'll find us on Spotify, apple Podcasts, rumble and, last but not least, youtube, especially yesterday, excuse me is Dr Jeff Chen. He is an impact entrepreneur, executive physician, scientist. He does a whole lot of shit here. He's on a mission to transform the health of our bodies and minds using non-pharmaceutical products. I'm a big fan of that. He is a co-founder, slash CEO, of Radical Science. We'll have some fun conversations about that. It's an AI-driven health tech B-corp providing histories first proof as a service solution for wellness products to easily prove their true effects at unprecedented affordability, speed and scale. Radical Science was named by KPMG as one of the top 10 US tech innovators of 2022 and by Fast Company as a world changing idea. Dr Jeff gave a main stage talk on Radical Science at TED 2023. Previously, he was founder and executive director of UCLA Research Center, where he led clinical trials on natural products. I think that that'll be something fun to talk about.

Speaker 1: 1:22

You've been interviewed by a lot of outlets, including CNN, forbes, wall Street Journal, time, npr. You've appeared on WebMD, politico, Business Insider. You run the gamut. You got your bachelor's degree in Cornell, which is cold as crap in Cornell. That's all I got to say.

Speaker 2: 1:40

Indeed, that's cool, but it is chilly yeah.

Speaker 1: 1:44

You got your MD and MBA concurrently. Boy, you're badass at University of California in Los Angeles. Jeff, welcome to the show Sport Science dudes. Go ahead and go through the process in which let's say I'm a funding source, I'm giving you guys 100 grand to do a study on X, Y and Z, so walk them through.

Speaker 3: 2:09

Got it Okay. In many ways you could think of us as the. We do take on the principal investigator duties, we do take on, say, CRO duties, but what we'll basically do is a narrow range of types of studies. But because we focus on those narrow range of studies, we're able to build these tremendous amount of efficiencies and scalability into these processes. The way it works is you come to me, you pick one of these 10 standardized studies, Master protocols, pre-IRB approved. They're built in our tech stack. We run them before. We know what recruitment looks like, we know what attrition looks like, we know that the power analysis, we know what attrition is, we know what variance looks like, all these things. You pick one of these template studies, send us your product, send us your placebo to our warehouse and then we take it from there and at that point we push play.

Speaker 3: 2:56

Our recruitment campaigns go out. We know how they convert, we know that recruitment, how long it takes. That point, people come in, they are, they automatically go through screening. They're deemed eligible, they consent, they. We verify their address and then they're stratified and randomized and the product starts shipping out.

Speaker 3: 3:14

Some people are getting placebo, Some people are getting the active product and then we're collecting information on side effects, consumption outcome measures, and then in certain studies there's add-on biomarkers, so little kits that we'll send. We'll collect blood or saliva, there's some quantitative biomarker test and that's that's pretty much it and the whole study just runs. And then at the end we do some pretty unique things, such as we promise all participants that as soon as the study finishes they get unblinded and we give them all their data back in a health report and because of that we don't pay any participant incentives. So we actually think this results in more accurate data, because you're not in this to get a $100 Amazon gift card. You're in this because you're curious what your health report's going to look like, and so we actually think you result. This intrinsic motivation that we leverage, we think results in more accurate data in the extrinsic motivation of a gift card or a monetary incentive.

Speaker 1: 4:06

Can you give an example? You don't have to mention the product, but some of the outcome measures that you went through and what the data looks like coming back? Because even when we do a clinical trial, where we are, we are meeting the subject and we have a research team that you know, we're basically with you as we're collecting data. Whether we're doing, let's say, an iPad test, you know psychomotor vigilance or profile of mood states, or you know we're doing a one repetition maximum or VO2. I mean, the investigators are always there. Now there's got to be a change in human behavior when nobody's there, and so what is your what?

Speaker 1: 4:42

happens in that case? What's your experience?

Speaker 3: 4:44

there. It's a great question, and so there's a couple ways to look at this. One is if someone is reporting on their mood or reporting on their psychology or some form of reporting when they are pulled out of their natural environment, put into a lab or a university or a clinic, and then there's someone in like a white coat, staring at them from across the table and you're asking them to fill stuff out. What their experience in that moment is very different than what they might be experiencing in the real world.

Speaker 3: 5:15

So, part of the anonymity in some way cases is good because it's true real world effect data. And then the other aspect is again the fact that we don't we're not paying them, so they really have no incentive to just like make stuff up, for example. But that's why this doesn't, this model doesn't lend itself well to. There's certain studies that need to happen in a physical lab. Again, many of the things you guys are talking about. It'd be very difficult for us to do, although one thing that I'm thinking could be interesting is imagine there was some I'm totally spit balling here. This is just a fun thought exercise you guys are making me think about.

Speaker 3: 5:50

Let's say there was some supplement that specifically the way that it changes their physiology, could result in maybe improved run times. You could do a virtual study where runners don't know if they're on the placebo or the blinded product and all of them are tracking their runs. It could be that simple and any statistical significance you see in a double-blind, random, wise placebo control trial like that. Yes, it wasn't. You didn't have someone monitoring them vigilantly to know that those run times weren't when they were on like a moped or something. Now here's the other benefit of our model Large sample sizes also take out a lot of the variation noise that cripple small studies. So our minimum sample size is 500 people.

Speaker 1: 6:26

That's a lot of people.

Speaker 3: 6:30

So that's one way that we overcome that as well.

Speaker 1: 6:33

Yeah, you know what, tony, I was thinking one of our colleagues, leah Genie she does a lot of, I guess, sex survey as a sexual function type studies and this actually would be perfect because I asked her. I said are you, are you in the room? When they answer these questions? She's like, believe it or not, I have to walk out because they don't want me in the room and otherwise they may just lie on these surveys, and I'm thinking this would actually be a perfect model. So I could see how you know it would work really well there. But Tony and I were talking about how, when we were going to elite athletes, they don't listen to anybody like Tony. Give your experience on that.

Speaker 2: 7:14

Well, yeah, they're easily persuaded, right? I think. To just point what we have here I mean, elite athleticism is a little bit different in a sense, where they're incessantly looking, hearing and, and you know, trying to find a new advantage that maybe somebody else is doing right, and that's really, I think, a completely different mindset and behavioral practice than looking at some of the outcomes you're looking for right as opposed to better sleep, elevated mood, maybe a little bit more energy in in the, in an aerobic capacity. So adherence is very. I wouldn't trust it, certainly in an MMA or boxing world, but then again I don't trust anything. It's not that jazz model wouldn't work in that world, nothing works in that world. But but I think to your point.

Speaker 2: 8:09

I really like the notion that I think about it. On the intrinsic side, you have people who are invested, who are actually curious about what you know outcomes are going to be, and they are doing this because they want to be a, I would say, an active participant and probably adhere to the required practices that are recommended in this study. So that seems to be, you know, a very strong point about it, right, like you said, not just coming in. Hey, you get a gift card. Now, what the hell? I'll go do the study so. And then when you're talking in terms of numbers of 500, you know that weeds out, and very well should what we see on the end points there where, as you noted earlier, if there are non-compliance or exaggeration in any of the claims, so I see this as being pretty viable and I was completely unfamiliar with it, jeff. Pretty neat thought really.

Speaker 3: 9:01

Thank you. Yeah, and you know there's. I think there are just general limitations of any clinical trial approach in general right, and I think we've done our best to improve where we can and other areas. We suffer from the same limitations of any clinical trial Lab studies of athletic performance. It's a little different where they're truly under constant surveillance.

Speaker 3: 9:26

But any sort of trial where you have a take home product, like the trials that I was running at UCLA, we would send people home with medication journals, physical pen and paper medication journals, and kind of the running joke was before each revisit that they would come back and hand us their journal. We give them a new set. We kind of joked that they were sitting in the parking lot scribbling that thing out furiously. Oh shit, did I three weeks ago? Was I taking it? Did I have side effects last week? I don't. Oh man, like you know, these, these docs are going to be mad at me. So at least with when you collect it in a virtual environment, it's just in time. The records that come in are timestamp. They're immutable. You don't have to worry about recall. They can't change their responses. They don't have to remember to respond to me to get notified when it's time to record a side effect, record their consumption.

Speaker 3: 10:14

And, speaking of you, brought an interesting point about adherence, which is that also, in many ways, no one, even in the real world, no one's using these products perfectly.

Speaker 3: 10:25

And I think the one of the conundrums that you have with clinical trials is sometimes when they are so artificial and synthetic they may be executed perfectly, but then the data doesn't translate, and that's why all the time you see these pharma drugs brilliant phase three data hit the market, start being used, they're not improving outcomes, right, and then the doctor stopped prescribing them, insurance companies drop their reimbursement and that drug dies, even though you're like, wait, but the phase three data showed a benefit. Well, it's because the face of data had you had people calling every day, did you use it? A perfect, perfect, perfect adherence. And, let's not forget the same, the sample that was collected, man like 100 exclusion, exclusion criteria, meaning the data sets will generate on people that don't look like anyone else in the world and, no surprise, when it hits the real world it doesn't actually pan out the way that they saw in these kind of synthetic, artificial trials. That's another thing that we always think about as well. It's that generalizability, that relevance of the data sets that we generate.

Speaker 1: 11:25

Let's talk about the idea of a policy, the issue of a placebo effect. I think one of the more interesting clinical trials that was that were done in the exercise science realm was the investigators gave, they had subjects do an exercise test but prior to each exercise test, they gave them three and they actually told the subject that they were three different doses of caffeine. However, all of them are placebos. However, when the subject was realizing, or thought they were realizing, that this, the dose of caffeine, was higher, they actually perform better, even though every, every capsule or pill was a placebo. So talk a little bit about that. And you know, I'm sure you deal with those kinds of issues, particularly when you're when you're dealing with such large sample sizes.

Speaker 3: 12:14

Really. So you know it's. It's so fascinating. I mean the placebo, the thing that you mentioned is really interesting the the. In some ways you're describing a dose response relationship for the placebo effect. I find that fundamentally fascinating.

Speaker 3: 12:28

Here's the other really interesting thing about the placebo effect there have been studies done where if you tell someone, you literally tell someone, I'm going to give you a placebo. But the placebo effects are real thing and it makes you feel better and you give it to them and they still get a slight improvement. So it's like it's kind of meta if you think about that. So in our studies obviously we see a clear placebo effect and it's influenced by several things. Number one the interest in the category of that product in general will increase the placebo effect. So if I say, hey, in this study you could get either placebo or some African bush wheat that you've never heard about, you're going to get a low placebo effect. So as soon as you start talking about like DVD or functional mushrooms and tropics, you see a bump in placebo effect because it's so popular in the zeitgeist that there is this elevated expectancy, biases, elevated belief in it.

Speaker 3: 13:23

So I think it's a combination of you know, what do you believe to be true, about these products. What relationship or association do you have? And I think in terms of inter individual psychology and personality, there's certainly certain types of profiles where people have an elevated perspective. But another benefit of going very large in sample size is that not, do you? Not only do you get that diversity, not only do you are more able to kind of cancel out all the confounding variables because they're evenly distributed between a product and placebo. With a large sample size like that, you only need to be placebo by a little bit to be statistically significant, and so that's also just a better it's like it's just fact the larger the sample size, the better odds you have a beating placebo and so.

Speaker 3: 14:10

But here's the other interesting thing I'll say about. Last thing I'll say about the placebo effect. It's been increasing in power If you go back and you look at all the pharmaceutical drug trials and you look at the placebo response over the last four plus decades the placebo response has been growing and people have tried to create explanations. I think one explanation is that the whole Eastern medicine movement the mind body, like yoga, meditation, you are more than your body. All of that has been kind of pushing people to increasingly maybe experiment with and believe in the power of belief and expectancy and all these things, and I think maybe that was one possible explanation for why placebo effect across all trials has been increasing in magnitude over the last several decades. And it's actually pharma has complained that it's making it harder and harder for them to be placebo in their FDA trials.

Speaker 1: 15:05

That's amazing. Their trials have a sample size is huge. So if you're not getting a difference with the placebo, then whatever the treatment is has got to be God awful. Now you mentioned something that's very popular in our category in sports. You mentioned CBD. Talking to athletes that use it what they describe, and I'm sure they would like a placebo effect but it's all over the place. Some guys say it helps, some guys say it doesn't do anything. I mean, I played around with it. I couldn't find anything, but there's others who swear by it. So how do you sift through all that noise to get some sort of answer about CBD?

Speaker 3: 15:44

I think there's several things there, I think the dramatic variations in the formulations of products.

Speaker 3: 15:51

that's a good point Dramatic variations in the dosages and then dramatic variations in the form factor and more so, the formulation, and so CBD is really poorly absorbed. But as soon as you add certain emulsifiers, as soon as you add certain fats, you can dramatically boost the absorption. And I think all the published clinical data that I've seen on CBD has really only shown efficacy in humans when you're taking like 100 milligrams, and up usually like several hundred milligrams is where you start to see that effectiveness. And so I think there's so many different variables that might result in someone having a product that has efficacy or not.

Speaker 3: 16:36

Another thing we're always trying to tease apart as well, which the large scale diverse sample sizes have, is what are the differences person to person? And so we're always wondering about that. And so, yes, some of the peer-reviewed publications we've had, we're generally talking about averages. On average, this product was statistically significant, had significantly more improvement compared to placebo. But what we really want to get to is a point where we can start to have such diverse and large data sets where we can say, aha, okay, yes, on average it is better than placebo, or maybe on average it's not, but depending on your gender, your age, your ethnicity, which is kind of a reflection of your DNA and then your lifestyle, which is a reflection of environmental exposures and a bunch of things.

Speaker 3: 17:20

At that point it does or it doesn't. So it's that really precision medicine lens that we want to be able to get to at Radical, and so for us that diversity representation was really, really important for us. So right off the bat with our trials, we were able to get gender parity in our studies and on average right now we're hitting about 20, 25% non-white and trying to increase that further, which, as we all know, your average trial tends to skew male, especially historically like white male urban areas right. So we're trying to get rural populations involved in all sorts of diversity around the board so that our data sets can then actually be analyzed further and maybe identify the variables that actually make a product more or less likely to work for someone.

Speaker 1: 18:06

I know in South Florida. Certainly the diversity here racial and ethnic diversity is you can pretty much get whatever sample you want. Now, since you're recruiting virtually, how do you go about doing this? Because I wouldn't know the first thing in terms of, okay, well, I'm in South Florida, but let's say I need people who are more like people in Idaho or whatever. How would you go about recruiting these kinds of subjects?

Speaker 3: 18:33

So it's interesting about a standardized trial right. So I have one sleep study, same master protocol, and I've run it dozens of times. Each time I run that protocol we are getting smarter and better about recruitment Versus. Can you imagine if the three of us created a bespoke study? We get some recruitment flyers that we think look pretty good, we get them IRB approved and we go and release them and we realize like it's not resonating, it's not converting. But we're kind of stuck and we get that one and done chance and the recruitment drags on for a year or whatever. So we've gotten really, really optimized and we're continuously improving.

Speaker 3: 19:08

So it's think we set quotas. So once, like, our enrollment hits a certain quota, other people coming in, our eligibility criteria will no longer necessarily let them come in to that study, for example. And so we have certain quotas that we set. And, more specifically, it's actually the way that we recruit. So it's not that we're actually changing the branching logic and the eligibility criteria, it's that once we know we know that certain channels are good at recruiting men, certain channels are good at recruiting people of color, certain channels are good at recruiting rural communities, and so once we hit certain quotas for them, we'll literally turn off those ads and so, and generally then that quota kind of stays stable and that's how we get this large diverse sample. Yeah, at this point we've had people from all 50 US states. Over 20% of our volunteers are coming from rural communities who never get to be in a clinical trial because they're so far from the nearest academic university center.

Speaker 1: 20:03

That's amazing that you would get certainly the rural subjects from any rural population I don't think I've ever had in any of the exercise science studies we've done, so that actually is a great point. Now tell us a little bit about how the issue of what's the word crowdsourcing, how that works in terms of making clinical trials go by faster, more affordable, things like that.

Speaker 3: 20:28

That's a great question. So I think the second you go virtual, several things start to happen All those facilities, those medical facilities you don't need them anymore and then all the people that have to staff that facility, the person to check people in, the parking attendant, all the way to the principal investigator, the study nurse, like the site manager all these individuals no longer actually are part of that equation as well. So there's tremendous cost savings there in the actual physical personnel, physical infrastructure. The next thing that happens when you go virtual is your eligible pool of volunteers goes from the 50,000 people that live within driving distance of a university or clinic to 200 million American, us adults. So your eligible pool goes up several, you know, 100,000 percent basically in size, and so your cost and speed that it takes to recruit goes down dramatically once you have that larger pool to work with and the diversity goes up tremendously. The other thing is, with a standardized trial, I don't have to spend that fixed cost every time designing the study, getting it powered, getting it out to be approved, building it on the tech platform, debugging it. It's already I do that once and I can optimize, optimize, optimize, optimize. So it gets a difference between when Ford Motors turns out a car. They didn't build the first car, they built the first standardized automated car and you no longer have to do a custom design and spend four years with three guys hand building like some car in a garage and it hits the road and the engine catches on fire and the wheel falls off. It was the first time that car that I've ever been built.

Speaker 3: 22:02

The other benefit of standardization is, once something is really well standardized, you can then build tons of technology automations around it in a way that you couldn't if it was bespoke. But now that standardized, I can automate everything from the side effect tracking to the data collection to the data cleaning. Imagine how much work a biostatistician has to do to manually clean a bespoke study. But once it's standardized, I can build code to automate all the cleaning, automate the analysis, automate the report generation back to the participants, automate all the engagement messaging, the adherence reminders for the participants, tracking the products can be automated. Randomization, stratification, eligibility screening, consent all of that becomes automated.

Speaker 3: 22:42

And so you know between and so, and with the standardization you also have the opportunity to get better and better, kind of like what I described earlier with recruitment every step of the trial we get to get better and better each time we run it, versus with the bespoke study. You're often left guessing every single time, because then, you know, I build this custom car, some of the learnings translate to the next one, but Murphy's law is going to pop up and you know stuff's going to go awry. But with standardized trials you don't have to worry so much about that either. So that's sort of some of the core ways that we've been able to do what we do. And yeah, compared to pharma trials, it's about two to almost three orders of magnitude cheaper to run from what we charge our clients.

Speaker 1: 23:26

Now this is fascinating in that you know when we go through clinical trials. You know we fill out IRB, get consent forms, et cetera, et cetera. So when the trial is done, are you the lead author, when you pen the paper and you submit the manuscript, I mean, who's?

Speaker 3: 23:45

the principal investigator? It's a great question. Yeah, so we are the PI. So the studies are registered to clinicaltrialsgov. They're all IRB approved. We are the PI when the study completes. Our clients, I mean.

Speaker 3: 24:00

So, unlike the university, we don't try to preserve academic freedom. The data is fully confidential. We are here for our client. It's not a client decides what I want to do with this data set. So we give them our own internal report. They review it and at that point they're free to do whatever they want. They go, push them a paper. They could skip the paper and just start marketing claims, or you know, no one has to even know that they ran a study. When we go to register the trial on clinicaltrialsgov, we even protect the identity of our client. So you don't even know that they even did a study with us. We are the study sponsor. We do assume the liability, the responsibilities, the reporting requirements. We're the PI. So then, but then our client gets to review that. And then what?

Speaker 3: 24:38

Generally, what has happened is the clients who want to go on and publish, they are fully free to do it on their own, but generally they'll have us go and do the publication, and that's why we know the protocol.

Speaker 3: 24:50

So well, right, and we've been able to publish other studies in the past with maybe analogous template skeleton protocols as well.

Speaker 3: 24:59

So so, so far, for all the publications coming from trials, they've actually asked us to go and be the authors of it.

Speaker 3: 25:05

And now here's the other thing that's interesting Our master protocols were designed with a variety of input from various academics at universities across the country, from Harvard to Hopkins to UCLA to San Diego UW, et cetera, et cetera, et cetera. And when the manuscript is ready because they were involved in the creation of, effectively, the protocol except it was a master protocol they actually will review the manuscript with us and most of them, depending on how busy they are for certain publications, they will jump on board as co-authors. So we've actually co-authored our studies and peer review publications with, again, harvard Hopkins, ucla, san Diego, university of Washington, washington University, st Louis, upit, you know like kind of some of the top tier medical research universities around the country. So it's a really amazing model where we get to leverage the academic gold standard principles of rigor, we get to involve these brilliant minds and they love it too, because they don't have to deal with all the bureaucracy and the paperwork of running a trial at the university, as well as the multi year timelines that sometimes it can take.

Speaker 1: 26:12

Now, within the exercise science realm, you know, let's say there's typically 20 to 25 assessments that we do, you know, related to whatever we do for that particular sport or athlete. Now, obviously that's done in-house, it's not something that could be done virtually. So for things that are done virtually, what would be sort of a list of your top 10, if there's such a list top 10 clinical endpoints that you would look at, that a company goes to you and say, hey, I have this product here, tonka at Ali. It's supposed to boost testosterone. What can you do for me? So is there the sort of you know I wish companies, you know there would be like a sales sheet like this cost this much, this cost this much, etc. Etc. So what you look like.

Speaker 3: 27:00

Sure so. And speaking of that sales sheet, I mean we're really pretty darn transparent and fixed on pricing. It's again pick any of our 10 standardized trials it's under 100K and you get a 500% double-blind randomized placebo control trial. It's like that's it Nice. We'll get results back to you, you know, within six to nine months. The most popular areas generally that people have been purchasing from us are around sleep, I would say gut health, mood, stress as measured by PROs and by salivary cortisol, as well as energy and cognition. Those are some of the most popular areas as well, and then some of our latest studies that we've rolled out with are ones around libido. A lot of people have been requesting a women's health study, a women's hormonal health, so that'll be arriving shortly, in the coming months one on women who are going through perimenopausal arena and grappling with all the symptoms, and then one for women who are still having their menstrual cycles products that could treat their menstrual symptoms that they might be experiencing. Yeah, I think that was your main question, right?

Speaker 1: 28:13

Yeah, well, it's funny you bring up the stress measuring salivary cortisol. We actually do quite a bit of that here and the assays are done in-house in the Department of Neuroscience. We collaborate with a neuroscientist there and she has grad students that run all these assays for us. So if I'm a subject in one of your studies and I'm assuming I'm spitting into this little tube, that saliva has to be frozen, at least for the assays we do.

Speaker 1: 28:40

So I'm trying to think of the logistics. If I live in Boise, Idaho, and I'm a subject in the study, what do I do with this saliva sample?

Speaker 3: 28:49

Yeah. So here's what's really interesting. I would say 10 years ago a lot of what radical is doing couldn't have happened just because smartphone saturation wasn't there yet, broadband internet wasn't there yet, and then also these D2C kits just weren't that good. But the amount that we've worked with, we've investigated so many different vendors that have these CLIA certified, clinically validated testing kits for blood and saliva and so, yes, some of them, depending on the type of test, they're collecting, some of them in certain instructions where either it's, as soon as you spit into it, drop it in this prepaid USPS envelope and then tomorrow, boom, they're gonna take it and they've done the validation studies to know that that sample will stay consistent even at room temperature, if it's gonna get there over an or two next business day back to the lab. Other things, like a lot of the finger prick dried blood smear tests, those you just drop. It's crazy. It's just a little of quarter card. Drop it in a regular envelope. It can make its way slowly back through snail mail and they can't test it. But there are limitations. Certain types of tests that require large volumes of blood aren't offered via these D2C kits, so we also right now don't offer it. So we are not remotely a replacement for trials or site-based trials of universities. It's in these circumstances the virtual one makes a lot of sense.

Speaker 3: 30:05

Now, one thing that's interesting that you guys brought up. I think for us, the closest arena that we might play to the sports nutrition world might be around subjects that are either elite or just pretty active adults very, very, very active adults, all the way to elite athletes. But instead of necessarily looking at their performance, what does it mean to have an elite athlete take a product and have significantly improved sleep quality? Right, sure. And is that a good enough outcome in and of itself, without knowing how it's changing their muscle reaction time or things like that? Maybe it is.

Speaker 3: 30:46

Or an elite athlete who is, compared to placebo, noticeably less stressed, noticeably less anxious, or even just simple things like pain having noticeably less pain, and so, in a self-reported outcome measure, is that good enough to move the needle and be useful, without knowing how it actually impacts their performance, for example? And so I think there's an opportunity there as well for sports nutrition brands, because right now they're selling you that performance-based product, but that athlete or that active adult is probably going out to all the mainstream brands and buying products for some of these other areas. You know my Ashwagandha for stress and this and that, but maybe sports nutrition brands you already have that customer's attention. Why not sell them the other, more lifestyle, holistic wellness products that maybe also ideally you've studied not just in a general population but in a highly all the way from athletes to very, very active adults who exercise at least, you know, like five times a week or something. I think there's a tremendous opportunity to take that share of the pie because you already are selling something to that customer anyway.

Speaker 2: 31:51

Yeah, that would be particularly true, jeff, at the elite level where you know to be in terms of performance, there are significant sacrifices We've always made to augment performance, and health has been a secondary consideration. So in the aggregate, testing some of the factors that you had mentioned, you can make very, very rational assertions that performance inevitably is going to improve or significantly decline in the absence of right, the proper sleep, the elevated mood, the proper cognition and so forth. So those things have to be in place in order to maximize potential in human performance. So in that capacity, I think there's a lot of room there that you can collaborate and put forth some work that would really advance performance in that capacity.

Speaker 1: 32:41

Jeff, in the interest of time I wanna tackle the issue of longevity and health span. I know this is one of your great interests and it's sort of an ancillary interest for us. I mean, tony and I were always talking about how we're in the fourth quarter of our life and we hope that we have a few over times left, since we've been doing this a long time. So tell us a little bit about your philosophy as it relates to health span and longevity. And in the social media space, I'll tell you what I hear a lot of. Well, peter Atia, he's always talking about doing zone two training, and Tony and I have talked about how, in a way, it's kind of silly to focus just on zone two training. And then you have guys like Huberman talking about doing cold plunges and staring in the sun, and I hate. At the end of the day you gotta work out. If you're not working out, all that other stuff is just kind of a waste of time. So what is your philosophy on that? We're curious to hear.

Speaker 3: 33:33

Great and everything that I'm about to say is really most of it's just my own kind of practices and things that I've personally come across. Obviously, studying longevity in clinical trials is it's tough. You either need a really really really long time span or what's really interesting is for the first time ever we're actually starting to hone in on certain types of diagnostic tests that could kind of give us a quantitative sense of longevity. I know in the past people used like telomere length. That maybe isn't the best. But now, looking at like epigenetic changes that might be associated with longevity, those are starting to get interesting, especially as people are starting to come up with really seems like decently clinically validated consumer grade tests for this. And as soon as you can track something, you can now reliably improve it. But before, if you can't track something, how do you know what's happening? But from my personal standpoint, a lot of the longevity things that I don't think people may be talking as much about I think the muscle mass thing that, jose and Tony, you guys, I'm sure, personally really focus on that if you look at the elderly, that might be the single biggest determinant of longevity and also avoiding mortality is how much muscle mass you have in the elderly, and we all know that once you start hitting your mid 30s, muscle mass peaks and starts to decline and it's really hard to build back up later in life. So if you can just continue to at your peak and maintain that muscle mass, I think that's gonna be a tremendous, tremendous boon to your longevity, and that's not even, I would say, even contested at this point. That's just the muscle mass itself, not to mention the cardiovascular benefits of exercise, as well as the cognition and staving off dementia benefits as well of exercise. I would say that. So I totally agree with everything you guys are saying there.

Speaker 3: 35:20

I think some other areas that people may want to think about is regulating their blood sugar spikes, and not because they're worried about becoming diabetic. That is definitely one consequence. But if you think about it, I don't know how often in the wild our bodies are used to having massive blood sugar spikes. Cause number one it was really hard just to get ahold of raw Hards or glucose. And if you did get ahold of it, man, you were on your feet 13 hours a day. That, like those, you never really spiked. You kind of just went bleer and then, like you're off, headed for the next valley. Yet now look what happens to us today three, four or five meals a day, snacks in between it's just boon, boon, boon, boon, boon, boon, boon. And you're sitting in between and each time your blood sugar spikes, glucose I mean. We all talk about oxygen being a very damaging molecule. Glucose glycosylation it's super damaging.

Speaker 3: 36:12

It's damaging everything it's touching is brutal, yeah, so I think recently one of my key longevity things that I've been doing is really trying to blunt my sugar spikes.

Speaker 3: 36:24

And the way that I do that. There's a few simple ways to do that. One is you don't even have to change what you eat. If you change the sequence of what you eat, you can make dramatic impacts on your blood sugar spikes. So if you are gonna eat sugar or even any sort of carbohydrate or any sort of starch, sequencing that after you've had fiber, fat and protein will have a significant blunting of your sugar spikes. So I always have my little rice or bread at the end of the meal. Or if I'm hungry on an empty stomach and I'm reaching for those crackers or some bread, I'll be like you know what pause I should have a handful of nuts in my mouth, fiber fat, protein and then maybe have some of that.

Speaker 3: 37:05

So there's, and also I think about glycemic load. So the same 100 grams of let's say I eat 100 grams of carbs a day, I could eat along one meal, but man, that's gonna my blood sugar's gonna go through the roof. But that same hundred I could divvy up over three meals, especially if I eat it after the fiber fat, protein. And so, yes, it'll probably reduce your chances of diabetes. And but this whole notion of not causing all of that damage that those from the sugar spikes? I think it is. And also your energy levels will be better too, because the energy crashes you get are due to as I understand it are due to the delta. So the higher peak you have in a glucose spike and then when that comes down, that delta is where your body perceives as that energy spikes. If you never let it peak to begin with, you're not gonna get that delta. The other thing is just a little bit of movement after you eat. So your blood sugars are usually spiking at about an hour after you start eating a meal, after you start eating something with carbs in it. At that point you're just going for a walk, doing some calisthenics. Also, you'll see dramatic blunting.

Speaker 3: 38:12

And then the final thing I'll say on the topic of sugar spikes, and I'm curious to hear what you guys have any experienced or seen on that Little bit of vinegar. Little bit of vinegar can also create a blunting of your sugar spikes, as well as some cinnamon. So if you're eating a sweet snack, having some cinnamon with it on top of everything I just talked about can help, especially if the snack, if the sweet snack's at the end of a meal, also starting each meal a lot with a tablespoon of vinegar could be apple cider, any type of vinegar. You can dilute it in some water so it doesn't burn as much when you drink it. That'll blunt your blood sugar spikes as well. And last thing I'll say, with sorry last thing I'll say, with the blunting of your blood sugar spikes, it means your body releases less insulin. If your body releases less insulin, it also means less fat storage. So if you're also someone who's trying to lose weight, this may be a way to also lose weight without necessarily restricting calories.

Speaker 1: 39:04

You know it's funny in a Filipino. I was born in the Philippines. In a Filipino household. Rice is often served at breakfast, lunch and dinner, so we're literally eating rice all day. So you can in a way say I'm addicted to rice. No, by the way, we probably use vinegar for everything. So it's kind of ironic.

Speaker 2: 39:22

You mentioned vinegar.

Speaker 1: 39:23

You know, but we eat so much rice Rice is probably 20, 25% of total calories for most Filipinos. But Okay so, but no, I want to mention.

Speaker 2: 39:33

Here's the hat. Go ahead, jeff go ahead, jeff.

Speaker 1: 39:35

No, go ahead. Well, I wanted to mention the muscle mass issue is actually important because you know you can predict morbidity and mortality if someone ends up in the hospital and they lose a lot of lean mass. Ironically and you know we joke with Tony a lot that Tony actually hates lifting weight so much because he actually gains muscle too easily, which is strange, because a lot of people want that problem. You know, for me, you know I'm a hard gainer, but Tony, he just puts on muscle.

Speaker 2: 40:00

Like he can walk into a weight room and stare at a weight, Especially now that I started eating protein again so it's really going through the roof.

Speaker 2: 40:08

But that was fascinating, jeff, what you spoke to too, and because I have talked, I've discussed this quickly with my students from an evolutionary biology perspective. Exactly to your point. There was no given situation where glucose is going to spike. I mean, even if you ran into an apple tree a thousand years ago what number of thousand? Let's say, 15,000 years ago 95% of it was eaten by squirrels and worms.

Speaker 3: 40:29

Anyway, so it was like you were knocking down 15 apples in a pot but and it would show up once a season, they're these tiny little sour crab apples. They weren't genetically, you know, weaponized for sugar, you know yeah and, to your point, the pathophysiology of diet and beauty shows.

Speaker 2: 40:48

I've always called it human rusting. Just about every system in the human body rust and, unfortunately slowly breaks down. It would probably be more advantageous if somebody had high blood sugar and just fell to the ground, because then it would be alarmed enough to do something about it.

Speaker 1: 41:04

But over the years, right we're getting.

Speaker 2: 41:06

It's a neuropathy neuropathy and it's just as if we're rusting away like a ship. But it's really interesting that that was one of the things you noted, and it's something I've always tried to blunt, so I'm pretty excited about it. I'm actually gonna try the vinegar too. I've not done that previously.

Speaker 3: 41:23

Yeah, and to your point, Jose, on the rice thing. Okay, so here's another interesting hack. There's cooled carbohydrates exhibit this interesting phenomenon where. So okay, so you take any starch that's in the raw form oats, rice, wheat, bran, whatever A lot of that starch is in the form of resistant starch aka fiber. You're not gonna absorb it as calories, it's not gonna blanch your sugar.

Speaker 3: 41:47

The first time it goes from raw to cooked, almost all of that resistant starch breaks down into regular starch and it's just gonna go straight into sugar after you eat it.

Speaker 3: 41:57

But after that first cooking from raw to cooked, if you let it cool and ideally it looks like if you let it almost freeze all the way, you reform much of that resistant starch and the subsequent heating like heating it up in the microwave to eat doesn't break down as much of that resistant starch. So it's estimated that if you take carbs, you cook them. Once you have free, use them, even keep them up again, it looks like you may be keeping 20 to 30% of that starch in the form of resistant starch aka fiber. So I stopped really eating carbs fresh. I'll cook all my rice ahead of time, I'll freeze it and then, when I want, I'll microwave it and eat it Again, also layering in that sequence. Just as an. And it works for bread, it works for potatoes, rice, anything that's a starch or a carbohydrate can seems to exhibit this phenomenon, where giving it one cooling cycle after the first cooking cycle can maintain that resistant starch even with subsequent heating.

Speaker 1: 42:54

Interesting. Hey, before we sign off, I wanna mention that the 21st Annual IASIS and International Society Sports Nutrition Conference is June 18 to 20. It is in Bonita Springs, florida. Jeff, hopefully, it'd be great if you could come to it. You'll meet all the people who are the leading thinkers in exercise and sports science, specifically sports nutrition. We're actually a very small group because there might be and I might be exaggerating this, tony there might be 100 scientists in the world that do sports nutrition research.

Speaker 2: 43:27

It's significantly less than people would assume based upon the size of the industry.

Speaker 1: 43:31

yeah, yeah, it's just so rare so you literally could probably meet 20% of them at one conference.

Speaker 3: 43:38

That sounds amazing. Yeah, I've heard such good things about the IASIS. I would love to attend Prior to having been able to, but this is great and what a great reminder to go. So, yeah, it's really cool.

Speaker 1: 43:51

Well, dr Chen, this has been a really interesting conversation. I'm gonna tell people more about radical science. I think, no doubt, it's a model that is quite useful for certain things. So I think you're doing something, you're providing a service that is innovative, and I'm a big fan of new, cool, innovative stuff. So I gotta thank you for that, and thank you for being on the Sports Science Dudes. We're glad to have had you on the show.

Speaker 3: 44:18

Honor. Do you guys consider me Again? I have people rave about your show, so it's amazing. And Jose and Tony, thank you so much for the time. It was such a pleasure.

Speaker 2: 44:25

Yeah, thank you, jeff. I really learned a lot, and that's always the good part about this show too, so I appreciate it. Thanks guys, thank you guys. I'll see you guys next time.