Unraveling DCT Misconceptions

Kristin Mauri

One of the widespread notions about decentralized clinical trials (DCTs) is that Big Pharma has an advantage because DCTs require more bandwidth and greater financial resources than “traditional” trials. That may discourage small-to-midsize biopharmaceutical and biotechnology innovators, but it's not true.

While small-to-midsize pharmaceutical and biotech companies may feel they lack the expertise to conduct DCTs, and that these trials are too expensive, DCTs can be easier to recruit for. DCTs can also deliver long-term cost savings that may offset any additional up-front investment.

DCT savings result from efficiencies realized through telemedicine's time-saving and burden-reducing conveniences, electronic consent (eConsent), electronic patient-reported outcomes (ePRO), electronic clinical outcome assessments, and use of wearable/sensor technologies. DCTs can also enable the recruitment of a broader base of patients, thereby shortening enrollment timelines. Such advantages can reduce trial durations by one to three months, yielding further savings.

Unraveling DCT misconceptions

DCTs have become a vital component of the current research landscape more than a whim. Although now fixed in the future of clinical development, DCTs are still referred to variously as “remote,” “virtual,” “site-less,” “direct-to-patient,” or “hub-and-spoke” trials. DCTs have become increasingly common in the wake of the COVID-19 pandemic and are expected to gain market share in the post-COVID era.

DCTs have achieved buzzword status in the industry, generating confusion over what they are. The Association of Clinical Research Organizations (ARCO) defines a DCT as a trial that "brings the trial to the patient by utilizing local healthcare providers, optimizing digital health technologies. Enabling the patient's voice to accelerate medical product development, speed delivery of therapies to patients, and create efficiencies across clinical research processes."¹

The focus on patient-centricity, with its advantages of convenience and flexibility, makes DCTs especially appealing to patients, contributing to high rates of participant satisfaction. DCTs are also increasingly attractive to small-to-mid-size biopharma and biotech companies, though the perceived challenges of conducting these trials may make some sponsors apprehensive. However, in our experience, those perceptions are often driven by common misconceptions about the DCT model.

One misperception is that DCTs are 100 percent remote. In actuality, DCTs more typically adopt a hybrid model representing varying degrees of decentralization, with some activities conducted on-site and others happening remotely. For example, after the initial visit to the principal investigator's site, the remaining visits may be conducted via telehealth. That can be a compelling inducement for patients to participate, particularly those living with rare diseases and who live hundreds of miles from a trial site.

DCTs also offer geographic and population flexibility, enabling recruitment across regions, ethnicities, and socio-economic groups, often leading to faster enrollment, fewer screening failures, and greater retention. Moreover, with fewer sites, DCTs come with fewer review boards, potentially lower regulatory costs, and potentially less-complicated protocol amendments.

Nevertheless, DCTs require extensive planning and steps to ensure patient safety, regulatory adherence, and clean, robust data production. Therefore, small-to-midsize companies entering the DCT space need to consider the factors cited in the following sections.

Trial design, budget, and vendor management

Regardless of company size, mastering trial design, budget, and vendor selection for DCTs is critical. To a great extent, these three factors are inter-related in that the first factor can influence the other two. Unlike in a traditional trial, in which investigators enter data from patients who visit the site, participants in a DCT may enter data themselves or use remote data-gathering devices. The DCT sponsor must therefore use trial design to determine how to integrate, manage, and analyze the data and which technologies and personnel to deploy for these tasks.

Managing vendors can be a considerable hurdle for small and midsize sponsors, particularly when integrating discrete data collection, analysis, and reporting methods. That's because collecting data across multiple third-party systems can make the process exceedingly complicated—and expensive. Yet even as costs pile up for staffing, partnerships, shipping, call centers, and visiting nurses, small-to-midsize sponsors need to remember that DCTs can deliver cost savings and should account for those savings in their budget calculations.

Choosing the right partner

Remote data collection in a DCT raises a number of questions regarding the format in which the data are collected and delivered and how to secure the data from the vendor. Partnering with a technology vendor that employs a "source-agnostic" data management system can answer those questions, making a DCT more cost-effective. Such a system can readily aggregate data from multiple data feeds, including the remote, wearable, and leave-behind technologies that can facilitate provision of eConsent, direct-to-patient supply of investigational product (IP), investigator-participant interactions, home health visits, collection of ePRO, and connectivity in general.

Figure. Mapping a decentralized clinical trial²

Source: Used with permission, ACRO DCT Data Flow Map

Working within a single operating system across many platforms can still seem challenging to small-to-mid-size innovators who lack the large staffing resources of Big Pharma. However, the solution isn't necessarily to hire a big CRO with a large staff and related bureaucracies. Instead, sponsors should identify a technology partner with a centralized operating platform that aggregates all the data and facilitates risk management, incorporating the kind of automation on which DCTs thrive.

Utilizing dashboards 

Incomplete or less-than-robust data can doom even the best-designed trial. The risks of suboptimal data may feel heightened in a DCT, in which data are largely patient-reported or uploaded from a wearable or other remote device, raising concerns that patients may overlook their reporting requirements or that a technology glitch may create a device malfunction.

Anticipating and minimizing such risks is especially important for small-to-midsize sponsors. Unlike their large pharma competitors, they often rely on reaching key milestones to satisfy investors and maintain adequate funding for continued operations. A key risk-mitigation strategy is to use a platform with dashboards that can instantly identify patterns of missing or anomalous data. The ability to view reports and status on dashes that continually centralize, analyze, and track data and risks in real time can level the playing field. The sponsor's size and resources become far less of a factor in a DCT’s success. Therefore, small-to-midsize sponsors should perform due diligence to find a tech provider that can deliver a comprehensive data view in a consistent format regardless of source and across multiple platforms.

Centralization through automation

For sponsors, one of the most appealing features of DCTs is their use of high-touch technology to automate data collection, interpretation, and reporting processes. That is especially important for maintaining centralized safety and efficacy databases, which are essential for monitoring and assessing the status of a DCT. Bringing all the data into one central location helps the sponsor see the complete picture of a trial cost-effectively. Centralization also places the data within easy reach of investigators and other DCT stakeholders, particularly patients; accessibility is at the heart of DCTs' patient-centric promise and appeal.

Workflow optimization

One of the drawbacks of traditional clinical trials is that they employ time- and labor-intensive analytical processes to detect data inconsistencies or worrisome patterns. In a DCT, an integrated data management system alleviates that drawback by providing workflow oversight and insights. Today, machine-learning algorithms perform those processes in real time—with greater speed, accuracy, and consistency. Moreover, DCT sponsors can establish pre-determined alerts that signal data anomalies requiring a closer look. An integrated, algorithm-driven system can thus address potential risk factors by significantly strengthening data certainty.

Seizing the advantage

For some sponsors and trial personnel, DCTs call for new and different skill sets than those required for traditional clinical trials; they also require the deployment and management of new technologies. Large pharma companies would seem to have the edge here in that they were already heavily investing in data management processes and systems well before the advent of DCTs.

In reality, small and midsize sponsors can seize a significant logistical advantage. Unburdened by established (and potentially outdated) data management processes and systems, these companies can adopt new source-agnostic systems, amalgamate best practices, and coordinate a roster of best-in-class vendors to optimize DCT results.

Moreover, the freedom to select and customize various technologies according to their individual needs allows small-to-midsize companies to minimize staffing requirements and streamline workflows while tracking safety, clinical, and operational risks in real time. Such benefits can also facilitate the protection of patient safety, regulatory compliance, and delivery of clean, conclusive data—thus assuaging any concerns about navigating the evolving DCT landscape.

Kristin Mauri, Solutions Services Director, Remarque Systems

References

1. QbD Manual for Decentralized Clinical Trials: The Quick Reference Guide. Association of Clinical Research Organizations (ARCO). 2021. Available at: https://www.acrohealth.org/qbdguide/.
2. ACRO Decentralized Clinical Trials Complete Map. ACRO Decentralized Clinical Trials Working Party, Association of Clinical Research Organizations (ACRO). 2021. Available at: https://www.acrohealth.org/dctdataflow/.