Your next trial’s biggest recruitment competitor may already be in your own development portfolio. When two study teams build forecasts around the same investigators, referral networks, and patient populations, each plan can look credible while their combined expectations exceed what those sites can deliver.
Portfolio-level clinical trial feasibility assesses whether studies remain workable when their demands overlap. It brings patient availability, site workload, and study timing into the same conversation, giving teams a chance to address internal competition before it becomes an enrollment problem.
Find where recruitment assumptions overlap
An experienced site with access to the right population is an attractive choice for multiple studies. The difficulty arises when separate forecasts each assume that its recruitment potential will be available during the same period.
Sharing an indication does not necessarily mean two trials compete directly. Eligibility criteria, treatment history, disease stage, biomarkers, and patient preferences may lead them toward different populations. Conversely, studies with different eligibility profiles may depend on the same referral pathway or screening team.
A useful portfolio review therefore goes beyond identifying repeated site names. It examines whether recruitment assumptions depend on the same patients becoming available through the same channels at the same time.
That distinction matters when choosing a response. Adding sites may broaden access, but adding another institution drawing from an overlapping referral network may contribute less recruitment capacity than expected.
Look beyond enrollment to the work already committed
Sites also face competing demands after recruitment ends. Participants in follow-up still need appointments, assessments, and support, while amendments, monitoring activities, and data queries continue to occupy research staff.
A site’s ability to identify eligible patients and its capacity to manage another study are related but separate questions. A promising patient population does not establish that coordinators, pharmacy staff, or specialist services have room for the protocol’s requirements.
Consider two studies with different populations but intensive visits scheduled during the same launch period. They may compete for the same staff and facilities even without competing for a single participant. Looking only at enrollment targets would miss that constraint.
Earlier conversations with site operational teams can reveal where these demands converge. Investigators provide essential clinical insight, while coordinators and other delivery staff clarify what accepting another trial would require in practice.
Give sites a view of the combined ask
Separate feasibility questionnaires can leave sites assessing each opportunity without a clear picture of what the sponsor intends to bring next. Where information can appropriately be shared, a coordinated discussion about upcoming studies gives sites a better basis for estimating capacity.
The conversation should establish:
Where demand overlaps: patient populations, referral sources, staff, facilities, and visit schedules.
When pressure is likely to peak: activation, screening, intensive treatment visits, or continuing follow-up.
What would change the estimate: additional support, different timing, revised procedures, or changes in existing commitments.
Sites will also have obligations to other sponsors, and they may be unable to share confidential details. Teams can still ask about available capacity and expected constraints without requesting another organization’s study plans.
The aim is a realistic combined commitment. A series of individually reasonable estimates may need adjustment once everyone can see the full workload.
Resolve trade-offs before every study becomes urgent
Identifying overlap is useful only if someone can act across study boundaries. Individual teams may have little room to revise milestones or site plans when they are accountable for delivering their own trial.
A portfolio discussion creates space to compare alternatives: sequencing activation differently, broadening the investigator pool, adjusting geographic coverage, or supporting a specific resource gap. Each option should be assessed against the actual constraint. Additional coordinator support may address workload, for example, but it cannot create a larger eligible population.
These decisions also need to respect clinical judgment and patient choice. Portfolio planning should improve access and operational readiness while preserving appropriate consideration of each patient’s options.
Revisit capacity as studies change
A delayed launch can create an overlap that did not exist in the original plan. An amendment can increase visit intensity, and slower recruitment can extend a study’s demands into the next program’s expected start.
Portfolio feasibility should therefore be revisited when those assumptions change. A shared view of recruitment windows, major workload commitments, and site feedback helps teams recognize when one study’s revised timeline affects another.
The practical goal is to stop committing the same capacity more than once. When study teams plan against a realistic picture of what patients and sites can support, their individual forecasts become more useful and their combined delivery plans more credible.
Continue the conversation at SCOPE Summit, March 1–4, 2027, in Orlando, Florida. Join colleagues across clinical research to explore feasibility, site strategy, recruitment, and operational planning. Explore the program and register.