Feasibility Without Guesswork: Unlocking Genomic and Real-World Data for Faster Study Execution

Clinical trial feasibility has long been constrained by the same fundamental problem: the data used to estimate patient availability rarely reflects the patients who will actually enroll. Site surveys capture what investigators think they have seen. Historical enrollment figures describe what happened in prior studies under different protocols. Neither answers the question that matters: do the right patients, with the right biology, exist at the right sites today?

This webinar introduces a new feasibility standard — one grounded in connected real-world evidence that spans structured clinical data, genomic and biomarker profiles, and unstructured clinical notes. Together, these data layers allow sponsors and clinical operations teams to test protocol feasibility before sites are selected, not after activation has already committed resources to the wrong locations.

Samantha Eells, Solutions and Market Lead for Clinical Operations at TriNetX, and Mark Hughes, Genomics Solution Engineer at TriNetX, will walk attendees through how deeper, more connected data transforms each stage of the feasibility process. Attendees will learn how to translate complex protocol eligibility criteria — including molecularly defined inclusion requirements — into queryable variables across real-world patient populations, how to identify sites where both the patient population and the operational evidence support successful enrollment, and why combining structured EHR data with genomic profiles and clinical notes produces fundamentally more reliable feasibility estimates than any single data type alone.

For precision medicine studies, oncology trials, and rare disease programs in particular, ICD and CPT codes alone cannot define the eligible population. A patient with the right diagnosis may lack the required biomarker. A site with high volume may have no genomic data coverage. This webinar addresses both gaps — and demonstrates how connecting these evidence layers earlier in study design reduces the risk of missed enrollment targets, delayed timelines, and costly protocol amendments.

Attendees will leave with a practical framework for evidence-driven feasibility and a clearer picture of what it means to select sites based on confidence, not assumption.

Speakers

Samantha Eells, Solutions and Market Lead, Pharma Clinical Development & Clinical Operations, TriNetX

Samantha Eells is an Epidemiologist and Strategic Leader with over twenty years of experience spanning clinical research, technology product development and biopharma innovation. At TriNetX, Samantha applies a data-driven lens to solving some of the industry’s most pressing clinical challenges. Samantha’s career includes senior leadership roles at Science 37 and Lightship, where she built and guided solutioning teams to develop transformative offerings for sponsors, clinical sites and study participants. Sam’s foundation in rigorous scientific research was established over a decade at UCLA and the Lundquist Institute, where she led federally funded epidemiologic studies and industry-sponsored clinical trials.

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Mark Hughes, Genomics Solution Engineer, TriNetX

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