Artificial Intelligence in Pharmacovigilance: Improving Drug Safety

Year : 2025 | Volume : 14 | Issue : 01 | Page : 1 16
    By

    Mohd. Wasiullah,

  • Piyush Yadav,

  • Satish Kumar Yadav,

  • Rishabh Chauhan,

  1. Principal, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  2. Academic Head, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  3. Associate Professor, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India
  4. Scholar, Department of Pharmacy, Prasad Institute of Technology, Jaunpur, Uttar Pradesh, India

Abstract

Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event detection, and predicting potential risks, allowing for proactive risk management. Despite challenges in data quality, model interpretability, and regulatory compliance, AI’s role in PV is advancing rapidly, promising more efficient and accurate drug safety monitoring. A concise summary of the article touches on how artificial intelligence (AI) is transforming pharmacovigilance (PV) by enhancing the detection, analysis, and prediction of drug-related adverse events. This review highlights the advancements AI brings to drug safety, such as enhancing efficiency, minimizing human error, and enabling real-time analysis of massive datasets from diverse sources

Keywords: Artificial intelligence (AI), pharmacovigilance (PV), signal detection, predictive analytics, natural language processing (NLP)

[This article belongs to Research and Reviews : Journal of Computational Biology ]

How to cite this article:
Mohd. Wasiullah, Piyush Yadav, Satish Kumar Yadav, Rishabh Chauhan. Artificial Intelligence in Pharmacovigilance: Improving Drug Safety. Research and Reviews : Journal of Computational Biology. 2025; 14(01):1-16.
How to cite this URL:
Mohd. Wasiullah, Piyush Yadav, Satish Kumar Yadav, Rishabh Chauhan. Artificial Intelligence in Pharmacovigilance: Improving Drug Safety. Research and Reviews : Journal of Computational Biology. 2025; 14(01):1-16. Available from: https://journals.stmjournals.com/rrjocb/article=2025/view=194674


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Regular Issue Subscription Review Article
Volume 14
Issue 01
Received 14/12/2024
Accepted 07/01/2025
Published 20/01/2025
Publication Time 37 Days
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