SCOPE Orlando 2026 Recap: How Data-Driven Sites Can Prove Patient Access to Win Trials and Accelerate Enrollment

Everyone is talking about how sponsors are using AI. At SCOPE Orlando, Inato turned the spotlight to research sites. We sat down with three sites to learn how they are using real patient data and AI-enabled workflows to prove patient access, win trials, and accelerate enrollment. The panel, moderated by Liz Beatty, Co-founder and Chief Strategy Officer at Inato, featured:

• Mari Livermore, Site Director and CEO at Pantheon Clinical Research
• Lily Palladino, Business Development Manager at Discovery Clinical Trials
• Aneesh Vaze, Managing Director at Clinical Research Philadelphia, LLC

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Let’s recap their discussion.

Sponsors Expect Faster, Data-Driven Feasibility

‍Feasibility has become more demanding for sites. Sponsors are looking for hard data over tentative estimates, asking more in-depth questions, and often working on tighter timelines. Sites need to quickly make sense of their data and go after the trials that are right for them; AI makes it easier for them to do this.

AI can dramatically reduce the time spent on feasibility and help sites quickly determine whether a study is even worth pursuing. This level of efficiency can help any site reduce burden, but it’s especially critical for sites working across multiple EMR systems, like networks. “Being a multi-site network, we have so much data across our sites from different locations. AI can really help us streamline that process. We’re getting feasibility questionnaires done in record time due to using AI, where before it would take us hours. Now, we notice at least a decrease of 80% in enrollment time,” said Palladino.

AI Enables Sites to Identify Patients at Scale

AI enables sites to identify the right patients at a scale that simply was not possible before. “We were not seeing success with advertising or manually looking at databases and charts,” said Vaze, describing how his team would spend all day reviewing patient records, identify only a handful of potential participants, and then get turned down by most of them.

Using AI, now his team can instantly search across multiple EMRs—encompassing over 300,000 patients—and identify all of the eligible patients with confidence, ensuring no one slips through the cracks. As Vaze described, “Using AI, we’re able to look at thousands of participants, get a list that we feel confident enough that we can provide to each of the provider partners so that we can almost guarantee that we can get the right participants in.” What was once a slow, manual process with unpredictable results has become a scalable workflow that allows his team to identify the needle-in-a-haystack patients amid hundreds of thousands of records.

Deeper Pre-Screening Improves Patient Experience and Sponsor Confidence

Using AI to evaluate patients against the full set of inclusion and exclusion criteria before the screening visit can significantly improve the patient experience. Livermore noted that when her team brings patients in after assessing them against the full inclusion and exclusion criteria, they’re about 90 percent sure those patients will enroll. This approach benefits both patients and sites. Screen failures are costly and time-consuming for research teams, but they are also frustrating for patients who may travel long distances only to learn they don’t qualify. Identifying exclusions earlier helps avoid unnecessary visits and fosters a more respectful, positive patient experience from the very first interaction.

Livermore also shared how reducing screen fail rates and boosting enrollment has improved sponsor confidence in her site, strengthened those relationships, and set her up for future trial opportunities. In one obesity study with a tight enrollment window, Pantheon Clinical Research screened 40 patients and enrolled 38, an outcome that shocked the sponsor. Livermore explained, “It’s been remarkable for us—we are a fairly new site and after the sponsor visit we actually were awarded four more studies because they saw how we pre-screen these patients.”

Final Thoughts

There’s a clear shift underway at the site level. AI enables these leaders to accelerate workflows, improve enrollment outcomes, and build credibility with sponsors to bring more trials to their communities, freeing them to spend more time on what matters: patients.

As for a final word of advice for other sites, Palladino said, “Who doesn’t want to work more efficiently? It is quick, it is efficient, it’s working smarter, not harder.”

Interested in implementing AI to prove patient access, win trials, and accelerate enrollment? Click here.