With many clinical sites shut down to enforce social distancing and trial staff diverted to duties related to COVID-19, some life sciences companies have begun conducting decentralized clinical trials (DCTs). These studies use new technology and processes to perform many trial functions remotely rather than at the site, and rely on help from the patient, family members and other caregivers instead of healthcare professionals.
The shift to DCTs has also helped address weaknesses in the traditional clinical trial model that predate the pandemic. These include:
- Time-consuming, expensive manual processes for collecting data.
- Excess costs for trial sponsors and inconvenience for patients visiting offices for routine check-ins.
- Lack of communication tools and processes to gather timely data and insights remotely from patients on adherence, progress, adverse events or outcomes.
- Inability to collect data for a broader range of endpoints, or outcomes, of trials.
However, DCT adoption has been limited by many forces, including trial sponsor inertia, uncertainty about regulatory approval and unreliable remote sensing and reporting technology. Adoption has also been hampered by the fact that study protocols are written for clinicians, not patients, making it more difficult for participants to follow treatment regimens, report on their condition and give informed consent to the trials without visiting a professional.
Continued COVID-19 restrictions on face-to-face contact, however, forced rapid adoption of DCTs despite these early issues. At the same time, regulators clarified DCT requirements, and new remote monitoring capabilities such as electrocardiogram sensing in products (i.e., an Apple Watch Series 6) continue to make DCTs more feasible.
This is an opportunity to not only continue lifesaving clinical trials during this and future pandemics, but also to transform the trial experience for study participants. DCTs reduce the need for inconvenient travel for patients, empower participants and caregivers to administer treatment, monitor results and make needed interventions, and facilitate the real-time gathering of clinical information and the delivery of clinical trial supplies.
Most importantly, DCTs can reduce the time, cost and effort of clinical trials and speed the delivery of new treatments to market.
Deciding where and how to begin the journey to DCTs can seem daunting. A clinical trial assessment and prioritization framework can help determine which trials are best suited to decentralization, which technologies and processes are needed to make them successful, and how to create a plan for initiating decentralized trials most quickly.
Where DCTs work best
We suggest following a framework that includes first evaluating the potential patient consequences -- ranging from fatal to severe to major, minor, or none — of discontinuing or delaying each trial. For those trials where the consequences of delay are most fatal or severe or major, the next step is to examine the study protocol to assess test requirements including:
- The type of medication the patient must receive.
- The type of patient monitoring required.
- The skill level required to administer the treatment.
- The amount and type of intervention or advanced diagnostics required.
- Logistical obstacles such as challenges in delivering supplies to the patient’s home or poor internet connectivity that could limit the delivery of test data.
- The need for other physical tools, such as a glucometer, or digital tools such as a smartphone app for cognitive behavior therapy.
The weight assigned to each metric will vary based upon the type of condition involved. For example, complex oncology treatments that require infusions and a routine scan or cardiology treatments that require advanced diagnostics or expert skill may be less suitable for remote trials than a behavioral or respiratory condition that can be monitored without the need for expert help.
Such a framework should then walk the user through a detailed series of questions (see interactive version) to help determine which trials are best to decentralize and how to best to implement them.