Matching Patients With Cell Surface–Targeted Clinical Trials Using Large Language Models

20260 citationsJournal Articlehybrid Open Access

Authors

S. Carson Callahan · University of Wisconsin–Madison

Matthew R. Chrostek · University of Wisconsin–Madison

Nicholas R. Rydzewski · University of Wisconsin–Madison

Matthew L. Bootsma · University of Wisconsin–Madison

Kyle T. Helzer · University of Wisconsin–Madison

Hamza Bakhtiar · University of Wisconsin–Madison

Zachary S. Morris

Abstract

Our LLM-based approach enables real-time, automated matching of patients to CST clinical trials, addressing major barriers to enrollment and expanding trial accessibility. Errors were uncommon, and performance is poised to improve as LLMs evolve. Optimizing patient-trial matching for CSTs can improve both patient benefit and trial success.

Topics & Keywords

Cancer Genomics and Diagnostics Computational Drug Discovery Methods Statistical Methods in Clinical Trials

Publication Details

Published in: JCO Precision Oncology

Volume 10, Issue 3, pp. e2500757-e2500757

DOI: 10.1200/po-25-00757

Field-Weighted Citation Impact: 0.00

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Matching Patients With Cell Surface–Targeted Clinical Trials Using Large Language Models

Authors

Abstract

Topics & Keywords

Publication Details