Clinical Researcher—December 2022 (Volume 36, Issue 6)

DATA-TECH CONNECT

Pelin Thorogood, MEng, MBA; Dr. Jeff Chen, MD, MBA

 

The convergence of four trends—some of which have accelerated since the pandemic—is transforming the clinical research industry. First and second, virtualization and disintermediation are changing access to research and the dissemination of its findings. Third, thanks to rapid growth in digital health and the Internet of Medical Things, we now have more data than ever about our health. Fourth, and perhaps most importantly, with the maturation of big data–driven technology and artificial intelligence (AI), we can now make sense of these massive datasets to drive better decisions, whether on personal health, policies, and/or business. Here is a look at how each trend impacts the health and wellness industry.

Trend #1: Virtualization

As a trend which has been accelerated during the pandemic, virtualization democratizes participant access to trials. During the pandemic, researchers were forced to move clinical trials online, asking participants questions and sending products to their homes so they could self-dose. This was a rapid change from the traditional, physical trial, which was leveraging the existing infrastructure of universities, hospitals, and contract research organizations—and all the associated costs, including staff.

Virtualization allows companies of any size to conduct clinical research, due to the significantly reduced cost of clinical trials. It also brings diversity to where it really counts—to healthcare. Many groups have been traditionally left out of clinical trials, which have typically been focused on white males in metropolitan areas. Virtualization allows for women, different ethnic groups, and rural populations to be part of clinical trials. A poll taken in  2017 by Research!America found that 30% of adults surveyed said they’d like to participate in clinical trials if they were more convenient and less time consuming.

With virtualization, we can open up access to all demographics, improving the heterogeneity of the sample population and therefore the generalizability of the research findings. Further, with sufficient numbers, each of these demographic variations starts becoming meaningful and begins to be representative of the population at large.

Large-scale and intentional heterogeneous studies enable inclusion of diverse ethnicities, genders, age groups, behavioral habits, and pre-existing health conditions, which in turn moves us closer to making personalized medicine a reality for more patients.

Trend #2: Disintermediation

In order to examine data from trials of pharmaceutical drugs, the U.S. Food and Drug Administration (FDA) needs tremendous amounts of infrastructure in terms of personnel, businesses, and other involved government agencies. That bureaucracy will not change anytime soon, since U.S. pharmaceutical companies are subject to FDA regulations and need explicit FDA approval before they can start selling their patented formulas.

However, a whole new world of health interventions is opening up, including exercise, functional foods, herbs, cannabis, meditation, breath work, acupuncture, or aromatherapy. These interventions don’t need FDA approval or a doctor’s prescription. They aren’t so expensive that they need insurance coverage. They’re already being sold today. They’re democratized. They simply need access to fast, affordable clinical trials to demonstrate effectiveness to minimize risk of Federal Trade Commission action against false or misleading claims.

Virtualization and disintermediation eliminate the need for a mediator to share or communicate research findings. Typically, new medical research is published in esoteric medical journals that require paid subscriptions. It may take many years before healthcare professionals adopt that information into clinical practice and share it with their patients. In our opinion, such journals shouldn’t be the gatekeepers of information, especially on interventions that can be acquired without a prescription. Data on the safety and effectiveness of nonprescription health interventions can—and we believe should—be disseminated directly to consumers. The explosion of digital channels to serve direct-to-consumer content in a variety of engaging formats offers an unprecedented opportunity to disseminate valuable data nearly instantaneously, instead of through a lengthy trickle-down effect. Imagine how many lives can be saved and impacted.

Trend #3: Digital Health and the Internet of Medical Things

The 21st Century CARES Act, passed under the Obama Administration, requires interoperability of healthcare data among payers, providers, and technology vendors. It also means patients can effortlessly share their data with whomever they choose, including researchers gathering large-scale data on the outcomes of health interventions.

Patients are now hyper-connected, and the Internet of Medical Things (IoMT) grants us access to levels and types of data that were previously uncaptured or untouchable by researchers. From smartphones and consumer wearables to medical-grade devices like wireless blood pressure cuffs, glucose meters, and electrocardiograms, we have the technology to capture data on how individuals are in their real, day-to-day lives, instead of from readings taken only in the hospital or clinic.

We also now have interoperability; when patients have easy access to their data across electronic health records, insurance claims, and laboratory results, they’re empowered. They can use that information to switch to a new healthcare provider, or a new insurance carrier. Providers are also empowered to do things like switch to a new electronic health record system.

Trend #4: Big Data and AI

This last trend is especially exciting, as it perfectly builds on the first three trends in several ways:

• Through democratization of access for more formulations and a much higher diversity of participant population, enabled by virtualization and disintermediation.
• Through the vast quantity of high dimensionality of data on individuals, thanks to digital health and the IoMT.

We have access to an unprecedented and rapidly growing quantity of both retrospective and prospective data on more people than we’ve ever had in our history. Further, with the growing maturity of AI, we now have the opportunity to make good use of these data in many ways for better decision making.

We will experience a gradual shift in the coming years toward more trust and acceptance of AI and machine learning, new digital health capabilities, and more surveillance-type monitoring of patient populations. For example, the power of larger datasets and our ability to manage the holistic picture of our patients’ data in the digital domain enable us to be far more predictive regarding individual health outcomes, based on demographic, behavioral, and preexisting conditions of patients. We can be far more proactive in how we diagnose and treat so that we can focus more on the root of human wellness, rather than simply reacting to symptoms.

The large datasets also give us the opportunity to not just research the questions we thought to ask, but to explore hidden correlations in the data to see how demographics, behaviors (e.g., coffee/alcohol intake), other prescription medications, and pre-existing conditions may play a role in the efficacy or side effects of the therapeutic studies.

These signals—even though they may not yet be conclusive—are the perfect hypothesis to drive further targeted research. The kind where we can anticipate patient health outcomes, explore hidden correlations for potential “signals,” accelerate and iterate research, enable precision targeting, and drive data-driven decision making.

A Future of Pharma and Farma

The future is both pharma and farma, not either/or. We’re predicting a world of abundance where pharmaceuticals and plant medicines live side-by-side and support health and wellness for populations—with transparency on the safety and efficacy of pharma, as well as of ancient remedies.

We predict a future where we are using these products in combination not just to combat ailments, but to enhance human function, whether it’s in terms of focus, creativity, physical strength, libido, or other desirable areas. We expect to see more affordable treatments offering better outcomes and fewer side effects to their target population.

We anticipate precision marketing with health and wellness products. Think digital marketing—but based on massive quantities of human health data. With this, AI-driven recommendation engines will match the right people with the products for their specific condition. We expect easily accessibly clinical proof of effectiveness to empower consumers, healthcare professionals, and the entire supply chain in between.

 

Pelin Thorogood, MEng, MBA, is Co-Founder and Executive Chair of Radicle Science, an AI-driven Proof-as-a-Service company offering the first easy path for non-pharmaceutical products to clinically prove their true effects beyond placebo by leveraging a crowdsourced, virtual, and direct-to-consumer approach, enabling research across diverse populations and conditions.

Dr. Jeff Chen, MD, MBA, is CEO and Co-Founder of Radicle Science.