AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review

Year : 2025 | Volume : 15 | 03 | Page : –
    By

    Muchukota Sushma,

  • Isbha S,

  • Varshita Pattar,

  • Bharathi B.V,

  • G. Jyoteshwari,

  1. Associate Professor, Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education & Research (AB), IPER Bangalore, Karnataka, India
  2. Student, Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education & Research (AB), IPER Bangalore, Karnataka, India
  3. Assistant Professor, Department of Pharmacy Practice, Vidya Siri College of Pharmacy, Bengaluru, Karnataka, India
  4. Student, Department of Pharmacy Practice, Aditya Bangalore Institute of Pharmacy Education & Research (AB), IPER Bangalore, Karnataka, India
  5. Student, Department of Pharmacy, Gautham College of Pharmacy, Bangalore, Karnataka, India

Abstract

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Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is being done by for example allowing real-time analysis of data, process automation for dealing with cases, and early signal detection even from large data sets (such as electronic health records, social media, and literature databases). This review discusses the state-of-the-art in AI-powered pharmacovigilance, assessing its efficiency and implementation difficulties, as well as legal aspects. In addition, it describes future perspectives (i.e. personalized pharmacovigilance and AI enabled predictive modelling for proactive risk management). Through the increased speed, precision and breadth of ADR monitoring, AI presents an unlimited potential to promote patients’ safety and effective regulatory structures in the changing field of drug safety surveillance.

Keywords: Pharmacovigilance; Adverse Drug Reactions; Artificial Intelligence; Machine Learning; Drug Safety

How to cite this article:
Muchukota Sushma, Isbha S, Varshita Pattar, Bharathi B.V, G. Jyoteshwari. AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review. Research and Reviews: A Journal of Pharmacology. 2025; 15(03):-.
How to cite this URL:
Muchukota Sushma, Isbha S, Varshita Pattar, Bharathi B.V, G. Jyoteshwari. AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review. Research and Reviews: A Journal of Pharmacology. 2025; 15(03):-. Available from: https://journals.stmjournals.com/rrjop/article=2025/view=0


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Ahead of Print Subscription Review Article
Volume 15
03
Received 17/05/2025
Accepted 19/07/2025
Published 21/07/2025
Publication Time 65 Days
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