Analysis of eligibility criteria clusters based on large language models for clinical trial design.

ABSTRACT:

Objectives

Clinical trials (CTs) are essential for improving patient care by evaluating new treatments' safety and efficacy. A key component in CT protocols is the study population defined by the eligibility criteria. This study aims to evaluate the effectiveness of large language models (LLMs) in encoding eligibility criterion information to support CT-protocol design.

Materials and methods

We extracted eligibility criterion sections, phases, conditions, and interventions from CT protocols available in the ClinicalTrials.gov registry. Eligibility sections were split into individual rules using a criterion tokenizer and embedded using LLMs. The obtained representations were clustered. The quality and relevance of the clusters for protocol design was evaluated through 3 exper

SUBMITTER: Bornet A 

PROVIDER: S-EPMC11833473 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature