The Feasibility Gap: Why Strong Sites Miss Study Opportunities

Clinical trial performance is often framed as an enrollment problem. Timelines slip, targets are missed, and the focus quickly turns to recruitment strategies and patient access.

But in many cases, the real issue starts earlier. Long before the first patient is enrolled, critical decisions are being made about which sites are selected to run the study.

These decisions do not always align with the sites best positioned to execute. Across conversations with investigators, coordinators, and site leaders, a consistent pattern emerges.

Capable, experienced sites are completing feasibility, expressing interest, and then hearing nothing. At the same time, studies move forward with sites that struggle to activate, enroll, or maintain consistency.

This is not a rare occurrence, it is a structural issue in how feasibility and site selection function today. If trial outcomes are going to improve, these early decisions need closer scrutiny.

The Overlooked Constraint in Trial Execution

The industry spends significant time discussing patient recruitment. Yet site selection remains a relatively underexamined factor in trial performance.

As protocols become more complex, the margin for misalignment narrows. Studies now frequently involve biomarker requirements, complex dosing schedules, hybrid or decentralized elements, and increased data collection demands.

At the same time, the site landscape has become more competitive, with continued consolidation, growth of site networks, and the expansion of SMOs. In this environment, selecting the right site is not just about access to patients, it is about operational fit.

When site selection is misaligned, the downstream impact is predictable. Startup slows, enrollment lags, and teams spend more time troubleshooting than executing. These are not isolated operational issues; they are the direct result of upstream decisions.

What Feasibility Has Become

Feasibility is intended to serve as the bridge between study design and site execution. In theory, it should help sponsors and CROs identify sites that are both interested and capable of running the study successfully.

In practice, feasibility often functions as a high-volume, time-constrained process that does not fully capture how a site operates. Sites are asked to complete detailed questionnaires under tight timelines, often across multiple studies at once.

The questions are standardized, designed for scalability rather than nuance. Important aspects of site performance—including workflow efficiency, staff experience, competing study demands, and patient population dynamics—are difficult to represent in a structured format.

At the same time, feasibility is rarely a two-way exchange. Sites provide information but receive limited feedback. There is little visibility into how responses are interpreted or why decisions are made. The result is a process that generates volume, but not always clarity.

Where the Disconnect Happens

The gap between feasibility responses and real-world execution is where many studies begin to drift off course. Protocol expectations are often developed without a clear understanding of how they will translate into site workflows.

A study may look reasonable on paper, but introduce significant operational strain once implemented. Complex visit schedules, specialized testing requirements, and coordination across multiple vendors can quickly overwhelm even experienced teams.

At the same time, feasibility responses may not reflect a site’s true capacity. Sites are balancing staffing limitations, regulatory requirements, and multiple active studies.

A coordinator completing a feasibility questionnaire may not have full visibility into upcoming resource constraints or competing priorities. These are not failures on either side; they are limitations in how the process captures and interprets reality.

The Cost of Misalignment

When feasibility and site selection are misaligned, the consequences extend beyond individual sites. Startup timelines lengthen as sites struggle to meet activation requirements.

Enrollment becomes unpredictable, with some sites underperforming and others overburdened. Protocol deviations increase as teams attempt to manage complexity in real time.

Monitoring and oversight demands grow, adding cost and pressure across the study. Data quality can also be affected.

When workflows are strained, consistency becomes harder to maintain. Small issues accumulate and the overall reliability of the data can be impacted.

These challenges are often addressed downstream, with additional resources, protocol amendments, or site replacements. But by that point, time and budget have already been lost. The issue is not execution alone—it is a misalignment from the start.

What High-Performing Sites Do Differently

Despite these challenges, some sites consistently secure studies and execute them successfully. These sites are not always the largest or the most well-known.

What differentiates them is how they approach feasibility and positioning. High-performing sites tend to treat feasibility as a strategic function rather than an administrative task.

They are clear about the types of studies they can support and the conditions required for success. They communicate their patient access, staff capabilities, and operational strengths in a way that is both accurate and specific.

They also invest in internal alignment. Before responding to feasibility, teams assess current workload, staffing capacity, and competing studies. This allows them to provide responses that reflect real readiness rather than best-case scenarios.

Over time, these practices build trust with sponsors and CROs. Site selection becomes less about interpretation and more about confidence in execution.

Rethinking Feasibility as a Strategic Process

If feasibility is to serve its intended purpose, it needs to evolve from a transactional step into a more collaborative process.

One opportunity is earlier engagement with sites during study planning. Even limited input from site teams can help identify potential operational challenges before protocols are finalized. This does not require broad consensus, but rather targeted insight from sites with relevant experience.

Greater transparency in site selection criteria would also improve alignment. When sites understand what sponsors and CROs are prioritizing, they can respond more effectively and position themselves accordingly.

Communication during feasibility should also be more balanced. Providing feedback to sites, even at a high level, can improve the quality of future responses and strengthen long-term relationships.

Most importantly, the focus should shift from volume to fit. The goal is not to collect as many feasibility responses as possible, but to identify the sites best positioned to execute the study.

Strengthening Alignment Across the Ecosystem

Improving site selection is not the responsibility of one group. It requires alignment across sponsors, CROs, and research sites.

Sponsors and CROs can benefit from incorporating site-level insight earlier and placing greater emphasis on operational fit during selection. Speed is important, but speed without alignment often leads to delays later.

Sites can strengthen their position by approaching feasibility strategically, investing in clear communication, and being realistic about capacity. Overcommitting may secure a study in the short term, but it can create challenges during execution.

At an industry level, there is an opportunity to recognize site capacity as a critical resource. Sites are not interchangeable, as each has unique strengths, limitations, and patient access. Understanding those differences is key to improving trial performance.

Conclusion

Clinical research sites remain central to the success of clinical trials, yet many capable sites continue to be underutilized. The issue is not a lack of experience or infrastructure. It is a lack of alignment in how sites are identified, evaluated, and selected.

By rethinking feasibility as a strategic, collaborative process and improving communication across the ecosystem, the industry can make better use of existing site capacity. The result is more efficient trials, stronger data, and more reliable execution from the start.

About the Authors

Denise McNerney is a Partner at Global Life Sciences Alliance (GLSA), where she works across sponsors, CROs, and research sites to support study feasibility, site selection, and clinical trial execution. Her work focuses on building strategic connections across the clinical research ecosystem to help organizations navigate operational complexity and bring studies forward more effectively.

Chris Matheus is a Partner at Global Life Sciences Alliance (GLSA) and brings over 30 years of experience in the life sciences and clinical research industry. He has worked extensively across research sites, CROs, and industry stakeholders, with a focus on strengthening collaboration, improving feasibility alignment, and supporting more effective trial execution. His work centers on connecting people, processes, and practical strategies to help clinical research programs operate more efficiently.