Clinical trials in a COVID-19 pandemic: Shared infrastructure for continuous learning in a rapidly changing landscape

Abstract

Background: Clinical trials, conducted efficiently and with the utmost integrity, are a key component in identifying effective vaccines, therapies, and other interventions urgently needed to solve the COVID-19 crisis. Yet launching and implementing trials with the rigor necessary to produce convincing results is a complicated and time-consuming process. Balancing rigor and efficiency involves relying on designs that employ flexible features to respond to a fast-changing landscape, measuring valid endpoints that result in translational actions and disseminating findings in a timely manner. We describe the challenges involved in creating infrastructure with potential utility for shared learning.

Methods: We have established a shared infrastructure that borrows strength across multiple trials. The infrastructure includes an endpoint registry to aid in selecting appropriate endpoints, a registry to facilitate establishing a Data & Safety Monitoring Board, common data collection instruments, a COVID-19 dedicated design and analysis team, and a pragmatic platform protocol, among other elements.

Results: The authors have relied on the shared infrastructure for six clinical trials for which they serve as the Data Coordinating Center and have a design and analysis team comprising 15 members who are dedicated to COVID-19. The authors established a pragmatic platform to simultaneously investigate multiple treatments for the outpatient with adaptive features to add or drop treatment arms.

Conclusion: The shared infrastructure provides appealing opportunities to evaluate disease in a more robust manner with fewer resources and is especially valued during a pandemic where efficiency in time and resources is crucial. The most important element of the shared infrastructure is the pragmatic platform. While it may be the most challenging of the elements to establish, it may provide the greatest benefit to both patients and researchers.

Keywords: COVID-19; Data & Safety Monitoring Board; Data Coordinating Center; Platform protocol; core protocol; efficient infrastructure; master protocol; pandemic.

Figure 1.

Endpoint landscape over time.

Figure 2.

Endpoint class over time. The bars correspond to the total number of endpoint families on a given date. Each color corresponds to a specific endpoint class.

Figure 3.

Endpoint class by study population. The size of the box corresponds to the number of primary endpoints for a specific population. Each box can be expanded to see additional details on the primary endpoints linked to it.

Figure 4.

Possible governance structure for a platform protocol.

Figure 5.

Schematic of adaptive platform trial for COVID-19 outpatients.