The Shift from Study-Centric to Patient-Centric Clinical Trial Recruitment

Introduction

Leading research sites are improving clinical trial recruitment by shifting from a study-centric to a patient-centric approach: instead of asking ‘who fits this study’, the question becomes ‘which study fits this patient’ – matching each patient across multiple trials rather than screening them against one study at a time. This helps investigators and coordinators identify eligible patients more efficiently.

For clinical research coordinators and Principal Investigators (PIs), recruitment remains one of the biggest barriers to successful trial execution. Many research sites struggle to identify and engage enough eligible participants to meet their enrollment goals. Patients and their referring physicians, meanwhile, often have limited visibility into the broader research landscape. As a result, many potentially eligible patients are only assessed against a narrow set of studies, causing relevant trial opportunities to be overlooked. Today’s constraint is no longer only whether a sponsor can design a promising study. It is whether the system can find, qualify, and connect the right patients quickly enough.

The cost of getting this wrong is measurable. In a myTomorrows survey of 100 U.S. clinical trial site professionals, 55% reported delayed trial timelines or missed enrollment targets as a result of recruitment inefficiencies. This challenge is particularly evident in areas such as oncology, rare disease and precision medicine research where eligibility criteria are increasingly complex and patient populations are often highly specific.

As the number and the complexity of clinical trials continues to increase, patient populations are more narrowly defined, and protocols are more complex. This is why leading research sites are adopting a broader, patient-centric approach to trial matching.

The recruitment challenge facing sites today

Coordinators and investigators know the scenario well. A patient expresses interest in a clinical trial. The team reviews the site’s active studies, only to find that the patient doesn’t meet eligibility criteria, or that no relevant trial is currently open. At that point, many sites have limited options. Research staff are already stretched thin, and manually searching external trial databases takes time and rarely fits into routine workflows.

This happens more often than it should. Every week, coordinators invest significant time in reviewing charts, pre-screening candidates, and assessing protocol eligibility – but when screening is limited to a site’s own studies, many potentially eligible patients fall out of the recruitment pathway entirely.

Some may qualify for a trial at a neighboring institution. Others may be a fit for a newly opened study elsewhere, a platform trial with additional treatment arms, or a highly specialized protocol not available locally. Still others may become eligible as inclusion criteria evolve, or new studies begin recruiting.

Without a structured way to evaluate patients beyond a site’s active portfolio, these opportunities can remain undiscovered. Potentially eligible patients drop out of the recruitment funnel, sites lose the value of prior screening efforts, and sponsors continue to face enrollment challenges and delays.

Why a broader screening strategy makes sense

Patient-centric trial matching is the process of evaluating a patient against multiple potential research opportunities, rather than only assessing eligibility for a single study. This may include trials at the local institution, studies at other sites, future trial opportunities, and other appropriate access pathways. Traditionally, sites have evaluated whether a patient fits a specific trial at their own institution, which can unintentionally limit opportunities for patients better suited to a different study, elsewhere or later in their treatment journey.

As research grows more specialized, with adaptive and platform trial designs, biomarker-defined populations, and more personalized therapies, sites need processes that match patients across multiple studies and treatment arms, not just a single protocol.

This captures the value of every patient interaction rather than ending the process at the first non-match, producing a more structured workflow, fewer missed opportunities, and a better patient experience.

Creating a more efficient patient recruitment workflow

The most successful recruitment programs are increasingly focused on efficiency as much as volume. Instead of asking coordinators to manually search multiple databases, modern workflows aim to:

1. Start with internal studies, screening patients against trials currently recruiting at the institution.
2. Quickly assess external opportunities when no suitable local study exists.
3. Support compliant patient referrals once a match is identified.
4. Enable ongoing re-evaluation as eligibility, disease status, and study availability changes over time.

How technology can reduce coordinator burden

Research coordinators already juggle outreach, scheduling, regulatory work, and study management. Asking them to also continuously monitor external studies, new sites, and shifting eligibility criteria isn’t a gap in effort – it’s a gap in workflow design. Existing processes were not built to track constantly emerging opportunities elsewhere.

Sites increasingly see AI as part of the answer: in our Referral Readiness Gap report, 52% of site professionals said AI could support the triaging of incoming referrals to reduce manual review.

Building on published research demonstrating the potential of large language models to support patient pre-screening and trial matching ^{1 2}, the myTomorrows platform automatically screens patient information against eligibility criteria across internal studies, external clinical trials, and appropriate access pathways, for review by the site team, helping reduce manual screening effort and streamline recruitment workflows.

A single workflow that evaluates patients against a broader trial landscape – rather than fragmented databases and manual searches – saves time and lets patients who don’t qualify for one study still be considered for others, even across larger patient populations. The bigger opportunity: turning pre-screening from a one-time check into an ongoing process that runs continuously, so sites keep visibility into new opportunities as studies, sites, and treatment arms open up, instead of losing patients the moment a trial closes or isn’t a fit.

How the myTomorrows platform supports recruitment

The myTomorrows platform helps sites streamline patient identification and referral workflows by making it easier to assess potential eligibility for both internal and external clinical trials. For coordinators and PIs, this means:

Screen patients against internal studies first

Coordinators can review a patient against all active site studies at once, maintaining current workflows while evaluating eligibility for every study running at their own institution. This is already used across high-volume sites in both intake workflows and multidisciplinary meetings, with the ability to add site-specific eligibility criteria.

Identify external opportunities with AI-powered clinical trial matching

When patients don’t qualify for internal trials, coordinators can quickly explore options at other institutions using AI-powered matching, rather than ending the screening process. The platform compares the patient’s case against eligibility criteria, with searches filterable by condition, location, or study phase – reducing the need for manual database searches.

Facilitate compliant referrals

Support efficient and compliant patient referrals to external trial sites, helping ensure patients remain connected to potential research pathways³. Coordinators can monitor referral progress and update recruitment statuses, improving visibility into patient journeys from referral through review, screening, enrollment, or closure.

Reduce administrative burden through clinical trial matching

By bringing trial discovery and referral processes into a single workflow, teams can broaden patient access without creating substantial additional administrative burden.

Conclusion

Recruitment shouldn’t stop when a patient doesn’t qualify for a trial at your institution. As research grows more specialized and patient populations more narrowly defined, sites need to look beyond individual studies toward the right pathway for each patient – combining internal screening with visibility into external opportunities to build a continuous, patient-centered process that reduces manual effort and means fewer patients fall through the cracks.

As AI-powered clinical trial matching becomes an increasingly important component of modern recruitment workflows, organizations that adopt patient-centric matching approaches will be better positioned to improve recruitment efficiency, strengthen research engagement, and expand patient access to clinical research.