Arthur Combs, MD is a clinician, serial entrepreneur and thought leader in wearable technology and digital biomarkers. He serves as a consultant to numerous companies especially those bringing new noninvasive or digital technology to market.

Arthur Combs, MD

As early as 100 years ago (see photograph of Radio News cover, April 1924) the concept of “decentralized care” seemed just around the corner. Several key elements had to evolve over the past century to make this a reality: the sensors (remote patient monitoring), the telecommunication infrastructure (the Internet), the science, and perhaps most importantly, the buy-in from the medical and patient communities. The COVID-19 pandemic greatly accelerated the latter—to the point where we need to ask: what’s next? What did we learn, and how do we pragmatically move forward?

Depending on how we define them, decentralized clinical trials (DCT) are not new– the concept and early trials with a decentralized design significantly antedated COVID 19. Craig Lipset, clinical research pioneer, cites an internet feasibility study from 2003 and a Boston University patent for “Trials over the Internet” in 2007. But they still are not a singularly defined entity which has led to some confusion around the nomenclature (virtual? hybrid? combinations? site-less?) and execution.

Recently, the Clinical Trials Transformation Initiative (CTTI) 

 defined DCT as trials “in which some or all study assessments or visits are conducted at locations other than the investigator site.” Here, we specifically focus on a 

 of this broad spectrum: how technology can enable participation, leading to lower participant burden and better data. We believe this aligns well with the efforts to provide broader access to a more diverse population, which is encouraged by the latest 

In part, pharmaceutical companies and CROs can conduct viable decentralized drug development trials because of the advent of remote patient monitoring technology, wearable sensors, and electronically gathered data such as ePROs, but also as a result of a more patient centered, real-world data focus. How those trials are established, conducted, and validated evolved significantly under the pressure of the COVID-19 pandemic.The question now is what happens next? What have we learned (both pre- and post-COVID) and how can we put it to practical use? How do the benefits to participant burden and cohort diversity balance with the hard endpoints required to establish safety and efficacy for new drugs? What study design elements, enabling technology, and next generation data management are required for all stakeholders including patients, investigators, sponsors, society to benefit? 

Starting with the positives on the patient side, many aspects of clinical trials can be performed remotely—which, when done right, increases convenience, accessibility, and diversity. Medical grade remote patient monitoring (RPM) devices and digital technology can facilitate obtaining high-quality data—but transforming this data into clinical trial endpoints is a high bar. Most importantly, the foundation needs to be established first, which is required for regulatory approvals, and ultimately for the pharma industry’s buy-in.

As anyone who has spent hours in digital “customer support loops” for their wireless carrier can attest, decentralized processes have to be simple, effective, and efficient in order to ensure patient adherence. We have heard from subjects who are motivated but unable to participate in drug trials due to the travel burden. DCT capabilities such as RPM devices can allow them to participate. These medical devices—mostly wearables—must be designed for patient comfort, reusability, and self-service. Depending on the trial, the participant pool could be tech-savvy millennials, or it could be an older demographic who is much less comfortable with technology and/or relies on a caregiver. Trial participants can represent a broad range of demographics as we seek to expand the diversity of participants for various studies.

The pandemic forced some populations to rapidly adapt to various forms of digital healthcare, including telemedicine. This is a positive development, but it is not enough. There is an opportunity to further capitalize on this adoption by driving participation in decentralized trials and expanding to previously underserved populations. To do so means acknowledging issues and developing solutions to ensure the progress attained thus far is not transient and expedites more patient-centric drug development.

Instead of just throwing technology at the problem, both digital healthcare companies and pharmaceutical companies must seek a more deliberate application of wearable and digital technologies. There is a tension between patient burden and convenience, and the ability to gather the hard, statistically significant endpoints for safety and efficacy that are ultimately needed for regulatory approvals. Effective DCT requires being able to remotely monitor patients and obtain precise data that meets both clinical endpoints and those required for FDA approval.

One key advantage that DCT can deliver using technology is the ability to gather data in the “real world” with a cadence driven by biology. This requires rethinking how we have historically defined endpoints and looking toward more 

l outcomes that are more meaningful than the results of a point-in-time lab or physician assessment. Even the definition of a 

is changing as we better understand individual and circadian variations. Clearly not all endpoints can, or should, be measured at home. As examples, diagnostic imaging or biopsies will not be performed in somebody’s living room. But the key is determining 

 endpoints that can be obtained from a patient performing daily activities that correlate with the scan or biopsy results, and that provide a more granular picture of the disease trend.

Successful DCT trial implementation is not necessarily fully virtual. We believe that hybrid approaches that incorporate remote features, convenient locations, and conventional methods are here to stay for the foreseeable future. Sleep is an illustrative case study. It is said that sleep studies in the clinic are an accurate measure of how nobody sleeps. People tend to sleep better in their own homes, so data derived from a trial conducted with remote technology is less of a burden for the subjects, more representative, and can be performed nightly over time which establishes patterns and derives analyzable data. Having said that, sometimes sleep studies in a local sleep lab can bring valuable insights with technology that is not readily deployable at home. As another example, in considering endpoints for an arthritis study, is the change in range of motion 90 days after the onset of treatment as reflective of efficacy as data on how, and how much, a patient is actually moving—in the real world, when not observed by a physician. That can be the difference between a singular, objective finding and assessing drug efficacy by the subject’s practical function. The ability to record continuous data provides a longitudinal view of a patient instead of snapshots. Researchers can evaluate a patient’s progress wherein each subject is his own control instead of comparing patient A with patient B for real-world analysis of the condition and applicable trends. This new, richer, more objective data will only be beneficial if we have the ability to adequately structure and analyze the various information streams to reap the benefits of a decentralized model.

With a decentralized model, a new approach to trial endpoints is necessary. The recently issued draft 

 regarding digital health technology and RPM for clinical investigations specifically states that novel endpoints should be justified, and the method of assessing a patient’s response should be “well-defined and reliable.” That can present a challenge for RPM and the data streams it produces. Those conducting a study want to ensure the endpoints will meet necessary standards for safety and efficacy, and thus for approvals.

Remote patient monitoring technologies are an important tool in the DCT arsenal. They contribute to the proverbial win-win-win—to have the cake, eat it too, and not put on the extra pounds:

lower burden for patients, which will broaden access,

better and more objective data that links clinical research to the real world; and

faster recruitment, better retention, increased patient diversity, and cheaper trials that allow for more attempts to reach the desired goal.

The pandemic provided a glimpse into what is possible when pharma, (med) tech, CROs, and regulators work together with a sense of urgency against a common threat. To successfully put a dent in the dire unmet medical need, this spirit of cooperation must continue. This is the only way to develop trials that are tailored to the situation, adapt to the patients, and fit into their lives, as opposed to the other way around.

, Lead, Emerging Technology Strategy – Clinical Design, Delivery & Analytics, Eli Lilly and Company

, MD is a clinician, serial entrepreneur and thought leader in wearable technology and digital biomarkers. He serves as a consultant to numerous companies especially those bringing new noninvasive or digital technology to market.

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