Revolutionizing Drug Safety: The Role of Artificial Intelligence and Machine Learning in Pharmacovigilance

Pharmacovigilance is a crucial process in maintaining drug safety. This article explores the role of artificial intelligence (AI) and machine learning (ML) in advancing pharmacovigilance practices, focusing on their application in adverse drug reaction (ADR) detection and risk management. We examine how AI and ML technologies can streamline real-world data analysis, predict safety signals, and improve decision-making in drug safety monitoring. The paper also discusses the importance of regulatory collaboration, healthcare provider involvement, and patient education in strengthening pharmacovigilance efforts. By integrating these advanced technologies and collaborative frameworks, AI and ML offer significant potential to enhance drug safety, improve patient outcomes, and foster a more efficient pharmacovigilance system.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-12
DOI
https://doi.org/10.5281/zenodo.14858919
Primary Topic
Pharmacovigilance and Adverse Drug Reactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Revolutionizing Drug Safety: The Role of Artificial Intelligence and Machine Learning in Pharmacovigilance

Zenodo (CERN European Organization for Nuclear Research)
Pharmacovigilance and Adverse Drug Reactions
article

Revolutionizing Drug Safety: The Role of Artificial Intelligence and Machine Learning in Pharmacovigilance

article en

Abstract

Pharmacovigilance is a crucial process in maintaining drug safety. This article explores the role of artificial intelligence (AI) and machine learning (ML) in advancing pharmacovigilance practices, focusing on their application in adverse drug reaction (ADR) detection and risk management. We examine how AI and ML technologies can streamline real-world data analysis, predict safety signals, and improve decision-making in drug safety monitoring. The paper also discusses the importance of regulatory collaboration, healthcare provider involvement, and patient education in strengthening pharmacovigilance efforts. By integrating these advanced technologies and collaborative frameworks, AI and ML offer significant potential to enhance drug safety, improve patient outcomes, and foster a more efficient pharmacovigilance system.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 54%
Pharmacovigilance and Adverse Drug Reactions
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