Risk stratification of potential drug interactions involving common over-the-counter medications and herbal supplements by a large language model.

ABSTRACT:

Background

As polypharmacy, the use of over-the-counter (OTC) drugs, and herbal supplements becomes increasingly prevalent, the potential for adverse drug-drug interactions (DDIs) poses significant challenges to patient safety and health care outcomes.

Objective

This study evaluates the capacity of Generative Pre-trained Transformer (GPT) models to accurately assess DDIs involving prescription drugs (Rx) with OTC medications and herbal supplements.

Methods

Leveraging a popular subscription-based tool (Lexicomp), we compared the risk ratings assigned by these models to 43 Rx-OTC and 30 Rx-herbal supplement pairs.

Results

Our findings reveal that all models generally underperform, with accuracies below 50% and poor agreement with Lexicomp standards as measured by

SUBMITTER: Kim J 

PROVIDER: S-EPMC12042285 | biostudies-literature | 2025 Jan-Feb

REPOSITORIES: biostudies-literature