Complementing Observational Signals with Literature-Derived Distributed Representations for Post-Marketing Drug Surveillance.

ABSTRACT:

Introduction

As a result of the well documented limitations of data collected by spontaneous reporting systems (SRS), such as bias and under-reporting, a number of authors have evaluated the utility of other data sources for the purpose of pharmacovigilance, including the biomedical literature. Previous work has demonstrated the utility of literature-derived distributed representations (concept embeddings) with machine learning for the purpose of drug side-effect prediction. In terms of data sources, these methods are complementary, observing drug safety from two different perspectives (knowledge extracted from the literature and statistics from SRS data). However, the combined utility of these pharmacovigilance methods has yet to be evaluated.

Objective

This research invest

SUBMITTER: Mower J 

PROVIDER: S-EPMC7243821 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature