Radicle Science Co-founders, Jeff Chen MD/MBA and Pelin Thorogood, MBA (both Cornell University Alums) gave the keynote talk for the Cornell West Coast Predictions event on March 2, 2022.

How many of us use over-the-counter (OTC) wellness products? How do we decide what to buy? How much to use? Let’s be honest, how many of us ever wondered if it actually is snake oil?

The issue behind consumer distrust in OTC health and wellness products is lack of rigorous, effective data. Traditional research trials cost $25 to $50 million, which prohibits most companies from validating their products. Large pharma companies with patent-based monetization models can afford to invest the time and money into clinical trials despite the cost, speed and scale limitations.

Health and wellness CPG manufacturers don’t have a patent-based business model, since natural products can’t be patented. They can’t justify a multi-million dollar investment into valuable research data about their products. This hinders market growth, and, most importantly, impedes the potential global health impact of these widely accessible and affordable products.

We need to reimagine clinical research in order to provide people with precision solutions for their health need states. This two-part series will first explain why and second explain how, based on trends we’ve see happening in our industry.

The evolution of clinical research

The creation of the Food and Drug Administration (FDA) occurred in 1938 with the passage of the Food Drug & Cosmetic Act under the Roosevelt administration. It required that all new drugs go through safety review with the FDA before going to market and prohibited unproven claims. This precipitated modern clinical trials, where unapproved drugs go through a series of tests in humans to prove they’re safe and effective beyond placebo.

Fast forward to today, and clinical trials haven’t fundamentally changed at all in more than 80 years! These trials still follow a slow, expensive, and antiquated process. New drugs can take 5-10 years and a billion dollars to get FDA approved.

In spite of the hold-up, the world has made tremendous progress in healthcare over the past several decades, whether through pharmaceutical drugs, vaccines, or other health improvements that have increased the average global lifespan by 22.4 years for men and 22.7 years for women since 1950.

Consumer mistrust in health and wellness products

4000 years later and natural medicine hasn't changed

Because clinical research hasn’t changed, the world of OTC medicines hasn’t changed much over the past decades, either. Trials are conducted explicitly to submit data to the FDA for review, which means they must be in strict compliance with painstakingly cumbersome FDA regulations. All OTC drugs must be isolated and synthesized in labs and manufactured for purity, potency and batch-to-batch consistency.

Today, a growing number of consumers are attracted to supplements over OTC drugs, with the belief that natural is better. Here’s the catch: because natural products aren’t regulated by the FDA, consumers can’t be sure of their safety (including purity and potency) and efficacy.

What is needed is rigorous clinical trial data proving the consistency, efficacy and safety of these products.

Clinical research data needs to be reimagined because…

It isn’t applicable to real world usage.

Western medicine often focuses on outcomes that can be detected in lab work or by a healthcare provider. FDA trials entail a litany of blood tests or imaging scans or physician assessments to focus on quantitative outcomes as opposed to qualitative outcomes as reported by the patient. It’s no surprise that many drugs, when used in the real world, don’t perform the same as in their FDA clinical trials.

It doesn’t represent the total population.

The high cost of trials precipitates as few participants as possible that still hits a minimum statistical power threshold. However, a smaller trial means a greater noise-to-signal ratio. To minimize statistical noise and increase odds of success, trials must recruit very specific types of individuals who are most likely to benefit from the drug and least likely to have a bad side effect. The problem is these individuals are needles in a haystack and don’t have enough in common with anyone in the real world. A majority of clinical trials fail to enroll enough people, since they are looking for people who don’t really exist.

It’s siloed and can’t be aggregated.

Have you ever wondered why there have been so many trials on things like fish oil, yet we still aren’t sure what it does? Or why do we have a multitude of FDA approved antidepressants, with data showing they are better than placebo, but little to no data on how they compare against one another?

One reason for this uncertainty is bespoke trials that result in siloed study data. One study’s data sits on a professor’s hard drive, another sits with a pharma company. Since we can’t access the source data underlying these studies, researchers who want to do a meta-analysis are forced to take the written topline findings of all the studies and then attempt to derive a more confident conclusion.

Even if researchers could access all the source data and analyze the entire aggregate dataset directly, they would run into a second problem: The data won’t aggregate. That’s because each study was conducted uniquely, with different methods, populations, outcome measures, and time points. The end result: siloed data composed of small datasets with low confidence, which cannot be compared, instead of a single large aggregate dataset with a strong confidence and high predictive power. The current model doesn’t serve the healthcare providers who need to know what type of individual should use which specific product in what manner to achieve a targeted effect or the consumer who is often at a loss as to which health and wellness products to trust.

In Part 2 of this post, we explore four exciting data trends that are upending the research industry….


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