Commentary|Videos|June 22, 2026

2026 DIA Global Annual Meeting: What Sites Struggle With and What the Data Will Eventually Tell Us About DCT

In this video interview from the 2026 DIA Global Annual Meeting, Joan Chambers, independent senior consultant at Tufts CSDD, examines the operational challenges sites face when implementing DCT components and makes the case that the industry is still in a learning phase—one the data will ultimately need to guide.

Full interview summary

In a recent video interview with Applied Clinical Trials at the 2026 DIA Global Annual Meeting, Joan Chambers, independent senior consultant at Tufts CSDD, shared her perspectives on decentralized clinical trials following a session she moderated on the topic. She opened by framing DCT as an umbrella concept encompassing a range of modalities—telehealth, mobile apps, in-home nursing visits, mobile vans—each of which can be deployed selectively depending on the needs of a given study. The core value proposition, she argued, is flexibility: by meeting patients where they are, DCT models expand access to populations that have historically been excluded from trials due to geographic or logistical barriers, and that accessibility directly supports both recruitment and retention.

On the operational side, Chambers was candid about the challenges sites face in implementing these models. Sites already manage multiple studies across multiple sponsors, each with its own technology stack. Adding a DCT component introduces yet another layer of complexity—new tools to learn, new workflows for data collection and patient follow-up, and the need to dedicate staff time to managing a fundamentally different type of patient interaction alongside traditional site operations. She identified this technology burden as one of the most common and persistent friction points in DCT implementation at the site level.

Chambers closed with a grounded set of takeaways from the session, cautioning against the assumption that DCT represents a universal solution. The field, she noted, is still defining the term itself, and the evidence base for which specific modalities produce the best outcomes in which contexts is still being built. Her expectation is that as data accumulates over the next several years, it will become clearer which DCT activities are most effective and in which settings—ultimately guiding the industry toward more evidence-based, fit-for-purpose trial designs that bring research to patients who would not otherwise have the opportunity to participate.


Related to this article

What Expanding AI Ecosystems Mean for Sponsor Complexity and Oversight
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, argues that CROs must act as orchestrators rather than aggregators—and that the real test of any AI ecosystem is whether it reduces sponsor coordination burden or just hands it back to them.
Where AI Governance in Clinical Development Falls Short
In this video interview, Rajneesh Patil, global head of AI, digital, and innovation in clinical development at Syneos Health, identifies three recurring failure modes in AI governance frameworks—and explains why responsible AI must be an ongoing operating discipline, not a one-time approval gate.