Science Corner 66 | Expert Interview: Belinda Tan - The People Behind the Proof
You have probably seen the phrase "clinically validated" on a supplement label. Maybe you have wondered what that actually means, who ran the study, and whether it holds up. The answer depends heavily on the people behind the research, the questions they agreed to ask, and how rigorously they designed the study to answer those questions.
Belinda Tan knows this world from every angle. A physician scientist board certified in dermatology and dermatopathology, she co-founded Science 37, one of the first companies to pioneer decentralized clinical trials, and helped launch a telehealth platform before founding People Science, a public benefit corporation that runs clinical research for supplement brands and ingredient suppliers. She has watched what good science in this industry looks like, and what it doesn't.
I sat down with Belinda to talk about the real state of supplement science: why trust remains the industry's biggest problem, how brands and scientists negotiate what to actually study, and why the N=1 era might finally deliver on the promise of personalized nutrition.
The question is not whether supplements are regulated. They are. The question is whether the research being done is designed to answer the right questions, rigorously, in people who actually look like your customers.
The trust problem is bigger than you think
When I asked Belinda for her overall view of supplement science today, she landed on three words: trust, data, and artificial intelligence. Not in a buzzword way. In a structural way.
The trust problem stems from a fundamental mismatch. Dietary supplements are regulated differently than pharmaceuticals. The burden of proof is lower, which means a lot of products have made it to market with weaker evidence than consumers assume. "How do you know when you're the consumer going to the market, buying the product, that what it says is really what it does?" she said. "That uncertainty exists because this industry is regulated in a very different way than drug development."
What has changed is AI. Belinda sees it reshaping how consumers access evidence, in the same way search optimization once determined what information reached people. "If you don't have high quality, credible data behind what you're talking about, AI is going to pull that up," she told me. Consumers are now closer than ever to being able to evaluate claims for themselves. Which means brands that cut corners on research are running out of places to hide.
Brands want claims. Scientists want truth. Here is how a CRO handles both
People Science is a CRO, which stands for contract research organization. These companies are the behind-the-scenes infrastructure of clinical research: brands and ingredient suppliers hire them to design and run studies, collect and analyze data, and help translate findings into defensible claims. Most consumers have never heard of them, even though CRO work often sits behind the "clinically validated" language on labels they read every day.
The tension at the center of this work is real. Brands come to Belinda's team with a marketing claim already in mind. Scientists want to design studies that answer questions without predetermined answers. "We think in a science-forward sort of way," she told me.
"We need to build studies that are scientifically rigorous, that make sense, and at the same time honor the end goals of the brands to actually be able to sell what they want to sell with the appropriate scientific questions and hypothesis."
The bridge is relationship building. Before any study is designed, Belinda's team works to understand how much regulatory fluency a brand actually has, whether they have legal and compliance teams pushing back on marketing, and whether the claim they want is even achievable given budget and timeline. Most of the real negotiation happens early, before anyone opens a protocol template.
Supplements are regulated. Just not the way you think
One of the most persistent myths in the supplement space is that it operates in a complete regulatory vacuum. Belinda is direct about this: that framing is wrong, and it matters. The relevant players include the FDA's Office of Dietary Supplement Programs and the National Advertising Division, which oversees claim substantiation. The specific language on a label, the endpoint a study is designed to measure, even the protocol title itself, all of these have regulatory implications that a rigorous CRO builds into study design from the beginning.
Regulations also shift with administrations and with industry momentum. For brands doing research, this is not just a compliance concern. It is a strategic one: you want the data you generate to still be usable in the regulatory environment that exists when the product actually launches.
The hardest design question: what are you actually measuring?
Randomized, placebo-controlled, double-blind. These words signal rigor. But rigor in the design means nothing if the study is asking a fuzzy question.
This is where Belinda sees brands make their most common mistake.
"They want to do everything," she told me. "They want to ask all the questions." The instinct is understandable. Brands are excited about their products, and studies are expensive. Why not get as much data as possible? The problem is that diffuse studies produce diffuse results.
When a sponsor comes to People Science, every study requires decisions across the same set of variables:
Endpoint specificity. "Improve sleep" is not a study endpoint. "Reduce sleep latency by X minutes" is. The more precise the question, the more usable the result.
Subjective vs. objective measures. Self-reported outcomes are valid, but pairing them with wearable data raises the bar for peer-reviewed publication and makes findings harder to dismiss.
Compliance design. Enrollment speed is not the same as data quality. Completion rate, how many participants actually finish all study tasks, is what determines whether the data is usable.
Budget and timeline. These constrain everything else. Ignoring them produces studies that never get finished, or never get used.
Belinda's team pushes brands toward a primary endpoint with a clear biological rationale. When brands also want publication in a peer-reviewed journal, the bar gets higher: subjective data alone rarely clears review. That is where wearable data becomes valuable, as an objective anchor for what participants report feeling.
How decentralized trials changed everything
The logistics of recruiting participants used to quietly kill supplement research before it started. Asking people to drive to a site repeatedly, fill out paper forms, and maintain a controlled protocol was a reliable way to get small, unrepresentative samples with high dropout rates.
Decentralized or remote trials changed this. By running studies through participants' smartphones, People Science can recruit faster, pull from a more demographically diverse pool, and maintain much higher completion rates. "Recruitment is probably one of the holy grails of clinical research studies," Belinda told me, and virtualizing the process has addressed more of that problem than almost any other methodological shift in the last decade.
But speed of recruitment is not the same as data quality. Belinda draws a sharp distinction between enrollment rate and compliance. Her team tracks both, and treats completion rate as a marker of platform quality, not just participant motivation.
N=1 is not a gimmick. It might be the future
The most forward-looking part of our conversation was about N=1 research: tracking an individual's response to a supplement over time, using that person's own baseline as the control rather than a separate placebo group. This is not a new concept. What is new is the tooling to actually do it at scale.
For SuppCo, this hits close to home. We have hundreds of thousands of users sharing their individual supplement experiences. Every one of those journeys is different, shaped by the rest of their stack, their sleep, their diet, the life circumstances they are managing. Traditional RCTs average across all of that variation and produce findings that are statistically powerful but often hard to apply to any single individual.
N=1 designs, run with the right technology, can capture the crossover effect: periods on, periods off, washout timing, ramp-up windows. That data structure gives researchers something traditional studies struggle to provide, which is insight into when a supplement starts working, in whom, and under what conditions. "The power of how that allows for both personalization and understanding the biology of what's happening," Belinda said, "is where we are today."
This is the direction the industry needs to move. Not away from controlled research, but toward a more complete picture that includes individual variation rather than explaining it away.
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Personal note from Jordan
I think about the credibility problem in supplement science a lot. Partly because it is my job, but mostly because I have seen it from both sides. Before SuppCo I spent years in regulated healthcare, where the evidentiary bar for any clinical claim is high, fiercely contested, and tied to real accountability. When looking at the supplement space… the contrast is jarring.
What struck me most in talking with Belinda is how clearly she sees the commercial reality without letting it corrupt the scientific one. Brands need to sell products. That is not a dirty truth. But it means the people doing the research have to hold the line on what "validated" actually means. CROs like People Science are often the only thing standing between a marketing team's wishful thinking and a study designed to produce a real answer.
The N=1 piece felt personal. I track my own stack carefully… and publicly (check the link above if you want to see it). My response to certain supplements is almost certainly different from what any RCT would predict for me, because I am not the average participant in those trials. The idea that we could someday have research designs that account for that individual context, rather than wave it away as noise, is genuinely exciting. We are not there yet. But conversations like this one are what move the field in that direction.