1. Knowledge Graphs in Pharmacovigilance: A Scoping Review.
- Author
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Hauben M, Rafi M, Abdelaziz I, and Hassanzadeh O
- Subjects
- Humans, Drug Interactions, Pharmacovigilance, Drug-Related Side Effects and Adverse Reactions epidemiology, Adverse Drug Reaction Reporting Systems statistics & numerical data
- Abstract
Purpose: To critically assess the role and added value of knowledge graphs in pharmacovigilance, focusing on their ability to predict adverse drug reactions., Methods: A systematic scoping review was conducted in which detailed information, including objectives, technology, data sources, methodology, and performance metrics, were extracted from a set of peer-reviewed publications reporting the use of knowledge graphs to support pharmacovigilance signal detection., Findings: The review, which included 47 peer-reviewed articles, found knowledge graphs were utilized for detecting/predicting single-drug adverse reactions and drug-drug interactions, with variable reported performance and sparse comparisons to legacy methods., Implications: Research to date suggests that knowledge graphs have the potential to augment predictive signal detection in pharmacovigilance, but further research using more reliable reference sets of adverse drug reactions and comparison with legacy pharmacovigilance methods are needed to more clearly define best practices and to establish their place in holistic pharmacovigilance systems., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: At the time of manuscript submission Manfred Hauben was a full time employee of Pfizer Inc., New York, New York, USA; he has also won stocks in pharmaceutical companies that may manufacture or market drugs mentioned in the article. However, he reports no other conflicts of interest that are directly relevant to the content of this manuscript. Mazin Rafi, a former Summer Associate of Pfizer Incorporated, is currently pursuing an MSc in Data Science through Rutgers University, New Brunswick, USA. He has no other conflicts of interest that are relevant to the content of this manuscript. Ibrahim Abdelaziz is affiliated with IBM Research - Yorktown Heights, Yorktown Heights, NY, USA. He reports no conflicts of interest that are relevant to the content of this manuscript. Oktie Hassanzadeh is also affiliated with IBM Research - Yorktown Heights, Yorktown Heights, NY, USA. He reports no conflicts of interest that are relevant to the content of this manuscript., (Published by Elsevier Inc.)
- Published
- 2024
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