Top Challenges in Clinical Trial Site Selection — and How to Overcome Them

Summary

  • Many sites fail to enroll patients — 40% enroll zero participants, often due to outdated selection processes.
  • Sponsors still rely on limited internal lists or manual feasibility, which slows startup and increases risk.
  • Global sites are underutilized, even though many have strong capabilities and untapped patient access.
  • Poor sponsor-site fit leads to communication issues and missed milestones, even at “qualified” sites.
  • Startup delays are common due to slow contracting, IRB reviews, or unclear expectations.
  • Solution: Use performance-driven platforms like Intune to match with verified sites, automate feasibility, and streamline global site selection.
  • For sites: Build visibility through transparent, data-rich profiles to get selected for better-fit trials faster.

What sponsors and sites can do today to reduce risk, delays, and costs

If you’re involved in clinical operations — whether as a sponsor, CRO, or site — you already know this: site selection is one of the most critical and time-sensitive parts of launching a successful trial.

And yet, even in 2025, site selection continues to be one of the least predictable, most frustrating, and most costly parts of the process.

Let’s break down the most common site selection challenges — and how your team can overcome them using smarter tools, better data, and stronger collaboration.

1. Too Much Guesswork, Not Enough Data

Many sponsors still rely on internal lists, personal networks, or one-off referrals to find clinical trial sites. It’s a method based more on habit than performance. And it leads to real risk.

🔍 What happens when your “go-to” site has staff turnover or is running three other studies at once?

According to the Tufts Center for the Study of Drug Development, 40% of sites fail to enroll a single patient [1]. That’s not a staffing issue — it’s a selection issue.

How to overcome it:

Use a clinical trial site database that includes verified past performance, therapeutic expertise, and startup timelines — not just contact info. At Intune, we built our platform to give sponsors access to real-world metrics, not guesswork.

2. Slow, Manual Feasibility Processes

It’s not just about who you choose — it’s about how long it takes to get there.

Traditional feasibility involves emailing sites, collecting PDFs, chasing responses, and manually comparing answers. It’s time-consuming, inconsistent, and often based on self-reported estimates.

⏱️ How many weeks have you lost waiting for a feasibility form to come back?

How to overcome it:

Automate and standardize clinical trial site feasibility using platforms that centralize outreach, track responses, and allow apples-to-apples comparisons. Better yet, pre-qualify sites based on performance and capability before you ever hit send.

3. Limited Access to Global Sites

Sponsors want global reach — but most still pull from a narrow, regional pool of sites. This creates:

  • Redundancy in overused high-volume centers
  • Missed opportunities with capable sites in emerging markets
  • Enrollment imbalances that stall recruitment

What if your ideal site is halfway across the world — and you never knew they existed?

How to overcome it:

Tap into a global clinical trial network that connects you to high-performing sites across diverse geographies. With Intune, you can expand your reach without expanding your timeline — using tools that surface sites based on performance, not geography alone.

4. Poor Sponsor-Site Fit

A site might look perfect on paper — right therapeutic area, good facilities, strong PI — but fail in practice due to poor communication or unclear expectations.

Have you ever had a site that technically “qualified” but missed milestone after milestone?

This disconnect is often caused by:

  • Lack of clarity in protocol expectations
  • Underestimated startup timelines
  • Mismatched technology platforms

How to overcome it:

Match sponsors and sites based on operational compatibility, not just enrollment potential. Consider responsiveness, staff structure, past collaboration feedback, and regulatory experience. That’s what Intune’s clinical trial site matching engine is built to do.

5. Unpredictable Startup Delays

Even after selection, delays in contract negotiations, IRB approvals, or budget alignment can slow everything down.

Have you ever had a site take 60+ days to fully activate after being “ready”?

How to overcome it:

Use platforms that provide visibility into site startup timelines, documentation readiness, and contract history. Sponsors can use this data to forecast bottlenecks — and sites can use it to flag areas where they need support or clarification.

Bonus Tip for Sites: Flip the Script

If you’re a clinical research site, the same challenges apply in reverse:

  • Are you waiting months to hear back after a feasibility submission?
  • Are you losing out because sponsors don’t know your capabilities?
  • Are you ready to grow but stuck in a reactive model?

Sites can stand out by building detailed, transparent profiles on platforms like Intune — showcasing past performance, therapeutic specialties, infrastructure, and patient reach.

The goal: get selected faster, for the right studies, with better alignment.

Final Thought: Site Selection Should Be a Strategic Strength — Not a Liability

Whether you’re a sponsor managing 30 trials or a site juggling 6 studies, the tools you use — and the data you trust — will determine how successful your partnerships are.

At Intune, we’re building a better way to connect sponsors and sites through:

  • A dynamic clinical research site finder
  • Performance-based clinical trial recruitment platform tools
  • Streamlined workflows for clinical trials platforms for CROs and sponsors

Ready to leave spreadsheets behind and build smarter, faster site partnerships?

Get in touch or explore our platform to see how you can modernize your approach to site selection.

Sources:

[1] Tufts CSDD. Investigative Site Landscape and Performance Trends. https://csdd.tufts.edu