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Clinical Trial Matching

The Efficacy of AI in Matching Patients to Clinical Trials

A Trial Navigator Case Study




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Webinar Focus:

Improving Access to Early Phase Trials

Delays in candidate identification and the absence of real-time visibility of open studies can impinge on equity of care as patients potentially miss out on trials for which they could have ultimately proved eligible. 

Drawing on new research undertaken by Guy's and St Thomas' NHS Foundation Trust, King's Health Partners ECMC and Inspirata, this webinar explored the efficacy and impact of deploying artificial intelligence-based automation as a means of eliminating common bottlenecks in the identification and matching of patients to relevant early phase clinical trials.  

Webinar Topics

  • Challenges with existing approaches to clinical trial matching.
  • Natural language processing (NLP) AI in an oncology context.
  • Research team drivers and expectations.
  • Public and patient involvement in research design and execution.
  • Project results and recommendations.
  • The case for NLP in improving patient outcomes and equity of care.

View the Replay


debashis sarker

Dr. Debashis Sarker
Reader in Experimental Oncology
King’s College London

Aoife Regan

Dr. Aoife Regan
BSc, PhD
Head of Programme Office
Experimental Cancer Medical Centre (ECMC)

Danny Ruta

Dr. Danny Ruta
Clinical Artificial Intelligence Lead
Guy's and St Thomas NHSFT

Alan Quarterman (1)-modified

Alan Quarterman
PPI Representative
Guy's and St Thomas' Biomedical Research Centre

Phil Brierley

Phil Brierley
Commercial Director
Inspirata Europe Ltd

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