Novel Data Mining Methodologies for Adverse Drug Event Discovery and Analysis

By R. Harpaz, William DuMouchel, Nigam H. Shah, David Madigan, Patrick B. Ryan, Carol Friedman. Clinical pharmacology and therapy, 2012

395 citations recorded by the source corpus.

An important goal of the health system is to identify new adverse drug events (ADEs) in the postapproval period. Data‐mining methods that can transform data into meaningful knowledge to inform patient safety have proven essential for this purpose. New opportunities have emerged to harness data sources that have not been used within the traditional framework. This article provides an overview of recent methodological innovations and data sources used to support ADE discovery and analysis.

Subfields: Computational Theory and Mathematics, Statistics and Probability, Toxicology

View Paper: https://www.semanticscholar.org/paper/81719e267980178e410b4bb9bbd92fcfebb0f828

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Statistics and Probability

In Toxicology

Citations in the corpus

Portable Automatic Text Classification for Adverse Drug Reaction Detection via Multi-corpus Training (2014, background): “These are passive systems populated by reports of suspected ADRs collected from healthcare professionals, pharmaceutical companies, and maintained largely by regulatory and health agencies [2].”
Computational Drug Repositioning: From Data to Therapeutics (2013, background): “57 A landmark study (using spontaneous reporting data from the Food and Drug Administration’s Adverse Event Reporting System) systematically predicted associations between adverse events and drugs and then verified some of the predictions using EHR data.”
Pharmacovigilance from social media: mining adverse drug reaction mentions using sequence labeling with word embedding cluster features (2015, background): “…studied for extraction of postmar-keting drug safety information, including electronic health records, 18,19 biomedical literature, 20–22 and SRSs. 23,24 However, the surfeit of user-posted online health information has recently encouraged researchers to explore other resources for drug-safety…”
Utilizing Social Media Data for Pharmacovigilance: A Review (2015, background): “Recent research has exposed the various inadequacies of spontaneous reporting systems, prompting researchers to explore additional sources for ADR monitoring [9,2,10].”