
News|Articles|April 20, 2026
Applying Behavioral Science to Improve Clinical Trial Design and Execution
Author(s)Andy Studna, Senior Editor
Behavioral science reveals how recruitment failures, site disengagement, and underrepresentation in clinical trials are rooted in early design decisions, and what sponsors can do to address them before they become costly problems.
Advertisement
Advertisement
Slow recruitment, high dropout, and persistent underrepresentation are among the most costly and enduring challenges in clinical research. Behavioral science offers a framework for addressing them not as isolated operational problems, but as predictable consequences of how trials are designed, sites are selected, and patients are engaged.
Related to this article

The clinical research industry talks about patient-centeredness constantly but embeds it too late, too narrowly, and without clear ownership, and the cost shows up in enrollment failures, protocol deviations, and outcomes that don't reflect what patients actually care about.

Cell and gene therapy access expands into community care settings only when operational coordination, site readiness, and supply chain standardization become first-order priorities equivalent to manufacturing capacity, requiring standardized processes, digital integration, and distributed logistics networks.

Decentralized trial models have demonstrated real gains in enrollment performance and patient access, but operational switching costs, fragmented technology stacks, and unresolved gaps in the patient-site relationship raise a question the industry has been slow to confront directly.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains how AI is shifting trial risk management from reactive to proactive—enabling sponsors to pressure-test protocols and anticipate pivots before a single patient is enrolled.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains why combining analog trial performance data with real-world patient data and site-level recruitment history gives sponsors a far more honest picture of whether their enrollment assumptions are actually achievable.

In this video interview, Claire Riches, VP of clinical solutions at Citeline, explains how AI is expanding endpoint selection beyond the bounded experience of a single sponsor team—and surfacing options that traditional design thinking might never have considered.

In this Q&A, Andrea Valente, CEO of uMotif, discusses what it takes to build genuine trust between patients and sites, why making technology easier to use isn't the same as making patient-site interaction more effective, and where the industry is still falling short in its push toward patient-centered trial design.
Advertisement
Advertisement

