Artificial intelligence-enabled safety monitoring in Alzheimer's disease clinical trials.

ABSTRACT:

Background

Investigators conducting clinical trials have an ethical, scientific, and regulatory obligation to protect the safety of trial participants. Traditionally, safety monitoring includes manual review and coding of adverse event data by expert clinicians.

Objectives

Our study explores the use of natural language processing (NLP) and artificial intelligence (AI) methods to streamline and standardize clinician coding of adverse event data in Alzheimer's disease (AD) clinical trials.

Design

Our quantitative retrospective study aimed to develop a gold standard AD adverse event data set, evaluate the predictive performance of NLP-based models to classify adverse events, and determine whether automated coding is more efficient, accurate, reliable, and consistent than

SUBMITTER: Jimenez-Maggiora GA 

PROVIDER: S-EPMC12184043 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature