ADE Eval: An Evaluation of Text Processing Systems for Adverse Event Extraction from Drug Labels for Pharmacovigilance.

ABSTRACT:

Introduction

The US FDA is interested in a tool that would enable pharmacovigilance safety evaluators to automate the identification of adverse drug events (ADEs) mentioned in FDA prescribing information. The MITRE Corporation (MITRE) and the FDA organized a shared task-Adverse Drug Event Evaluation (ADE Eval)-to determine whether the performance of algorithms currently used for natural language processing (NLP) might be good enough for real-world use.

Objective

ADE Eval was conducted to evaluate a range of NLP techniques for identifying ADEs mentioned in publicly available FDA-approved drug labels (package inserts). It was designed specifically to reflect pharmacovigilance practices within the FDA and model possible pharmacovigilance use cases.

Methods

Pharmacovigila

SUBMITTER: Bayer S 

PROVIDER: S-EPMC7813736 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature