The convergence of four trends — some of which have accelerated due to the pandemic — is transforming the research industry.
Virtualization and disintermediation are changing access to research and its findings. Thanks to digital health and the Internet of Medical Things (IoMT), we now have more data than ever about our health. Perhaps most importantly, with the maturation of big data-driven tech and AI, we can now make sense of these massive data sets to drive better decisions, whether on personal health, policies, and/or business. Here is a look at each.
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 CROS — 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.
Virtualization also brings diversity to where it really counts — to health care. Many groups have been traditionally left out of clinical trials, which have typically been focused on white males in metro areas. Virtualization allows for women, different ethnic groups, and rural populations to participate. 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, generalizability of the research findings. And with sufficient numbers, each of these demographic variations start becoming meaningful and begin 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 personalized medicine for the population at large.
In order to examine data from trials of pharmaceutical drugs, the 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. pharma 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 are opening up, including exercise, functional foods, herbs, cannabis, meditation, breathwork, 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 FTC action against false or misleading claims.
Virtualization and disintermediation also eliminate the need for a mediator to share or communicate the findings. Typically, new medical research is published in esoteric medical journals that require paid subscriptions. It takes an average of 17 years before health care professionals adopt that information into clinical practice and share it with their patients. 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 should — be disseminated directly to consumers. The explosion of digital channels to serve D2C content in a variety of engaging formats offers an unprecedented opportunity to disseminate valuable data nearly instantaneously, instead of a 17-year-trickle-down effect. Imagine how many lives can be saved and impacted.
The 21st Century CARES Act, passed under the Obama Administration, requires interoperability of health care 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.
Now, we have a lot of data at our fingertips.
Patients are now hyperconnected. The IoMT (Internet of Medical Things) gives us the kind of data that was being constantly generated, but uncaptured for eons. From smartphones and consumer wearables, like the Oura ring and Apple Watch, 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 readings 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 health care provider, or a new insurance carrier. Providers are also empowered to do things like switch to a new electronic health record system.
Big data and AI
This last trend is the most exciting, as it builds on the first three trends.
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. And with the growing maturity of AI, we now have the opportunity to make good use of this 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 data sets 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, behavior, 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 data sets also give us the opportunity to not just research the questions we thought to ask but also to explore hidden correlations in the data to see how demographic, behavior (e.g., coffee or 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.
The future is 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 safety and efficacy of pharma, as well as ancient remedies.
We predict a future where we are using these products in combination to combat ailments and also to enhance human function, whether it’s focus, creativity, physical strength, or libido. We see cheaper treatments with better outcomes and fewer side effects.
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. This will empower consumers, health care professionals, and the entire supply chain in between.
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