PhaseV, a prominent AI firm in clinical development, has introduced its Enrollment Lab solution at the SCOPE Summit. This innovative platform leverages artificial intelligence and real-world data to transform how clinical trial enrollment is planned. By providing sponsors with evidence-based insights before a protocol is finalized, the tool aims to mitigate common recruitment challenges and enhance study feasibility from the earliest stages.
A Paradigm Shift in Clinical Trial Planning
The Enrollment Lab marks a significant departure from traditional, often theoretical, feasibility assessments that rely heavily on site-level surveys. It champions a "population-first" approach, using extensive real-world electronic health record (EHR) data to model enrollment dynamics. This proactive strategy provides a more accurate and comprehensive view of the accessible patient population before site identification even begins.
Leveraging AI for Evidence-Based Protocol Design
At its core, the platform analyzes the complex interplay between patient eligibility criteria and the competitive trial landscape. Its AI-powered engine allows study teams to simulate how modifying inclusion or exclusion criteria directly affects the available patient pool. This capability enables sponsors to effectively "stress-test" their protocol designs against real-world constraints and opportunities.
This advanced modeling empowers sponsors to identify potential recruitment bottlenecks and explore alternative protocol designs with confidence. By quantifying the impact of specific trade-offs, teams can make informed decisions to optimize their study for success. The result is a final protocol grounded in a verified and accessible patient population, reducing downstream risks and financial commitments.
Gaining a Competitive and Geographic Edge
A key innovation of the Enrollment Lab is its ability to translate competitive pressure into a clear signal for patient access. The system maps where eligible patients are located and quantifies the level of competition from other trials in those areas. This intelligence uncovers underutilized geographic regions and lightly contested patient segments ripe for recruitment.
According to CEO Raviv Pryluk, this approach replaces theoretical planning with evidence-based certainty early in the development lifecycle. CTO Elad Berkman added that this provides a clear view of patient access, enabling more accurate trial execution. This foundational analysis ensures that subsequent site identification efforts are targeted and effective, based on a realistic enrollment plan.
Integrating Upstream for Downstream Success
Strategically positioned early in the study planning workflow, the Enrollment Lab establishes what is realistically achievable before major resources are committed. By revealing where eligible patients exist after accounting for all constraints, the tool informs both protocol design and geographic focus. This creates a solid foundation for PhaseV's other site identification tools to build upon.
This integration within the broader PhaseV ClinOps platform creates a seamless transition from high-level strategy to tactical execution. The insights generated by the Enrollment Lab directly feed into the site selection process, prioritizing investigators with proven access to the target patient population. This ensures alignment between the study's design and its operational execution from day one.
The launch of PhaseV's Enrollment Lab represents a significant advancement in applying AI to solve persistent challenges in clinical operations. By embedding data-driven, evidence-based analysis at the very start of the planning process, the solution promises to enhance the predictability and efficiency of clinical trials. Ultimately, this innovation aims to accelerate the delivery of new therapies to patients by ensuring studies are designed for success from their inception.