- 13 October, 9:40 AM | Barcelona
Rank sites by enrollment potential before startup decisions are made
Industry data shows that 37% of clinical trial sites under-enroll and 11% enroll no patients at all – a persistent drag on timelines that conventional feasibility methods have not solved.
In this session, Emily McInturf, Director, Feasibility, and Andrei Seryi, Director, Knowledge Management & Process Improvement at PSI CRO, will demonstrate how PSI’s AI-enabled semantic knowledge platform applies natural language processing, knowledge graphs, and predictive analytics to reveal enrollment risks before they materialize.
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What you can expect to learn
Attendees will learn how semantic AI and knowledge graph technology can help:
Generate ranked site options rapidly to identify high-potential sites earlier in planning
Improve protocol-to-site fit visibility and identify enrollment risks before startup
Replace fragmented, assumption-heavy feasibility with structured AI reasoning over operational knowledge
The people in the room
Emily McInturf,
Director, Feasibility
PSI CRO
Andrei Seryi
Director, Knowledge Management & Process Improvement
PSI CRO
Connect with PSI in Barcelona
PSI’s feasibility team has applied this platform across complex global programs, consistently improving site selection accuracy and supporting on-time enrollment across multiple therapeutic areas.
