From Data to Enrollment: The Impact of Large Language Models in Clinical Recruitment

Our system introduces a groundbreaking approach in clinical trial recruitment by leveraging Large Language Models (LLMs), including bespoke models and GPT-4. It serves dual functions: aiding Contract Research Organizations (CROs) in matching patient databases to active studies on, and uniquely, enabling pharmacies to identify the most fitting clinical trials for individual patients.

This latter capability, a novel application facilitated solely by our advanced LLM technology, places recruitment downstream in the care process, offering a more personalized and efficient approach to trial enrollment. Remarkably, the system has demonstrated high match rates and significant enrollment rates in a study with pharmacies. This presentation will explore the system’s innovative use of LLMs in patient-trial matching, its transformative impact on the recruitment landscape, and the potential future directions of this technology in clinical research.

About the speaker

Daniel Koppers

Head of R&D at PhlexGlobal
a Cencora Company

Daniel Koppers, the Head of R&D at Phlexglobal, is a luminary in AI and ML, renowned for creating the cune-Distiller platform at Cunesoft, leading to the company’s acquisition. At Phlexglobal, he evolved this into PhlexNeuron, integrating advanced AI technologies like BERT and GPT series, significantly enhancing document processing efficiency and productivity. His work with Cencora in developing AI-based software solutions further cements his status as a pioneer in applying AI and ML in regulatory compliance, showcasing his talent for merging cutting-edge technology with practical business applications.



Sessions: April 2nd – 3rd 2024
Trainings: April 15th – 19th 2024



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