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Orchestrating generative AI in pharmacovigilance: predicting and preempting the unpredictable.
Darmendra Ramcharran1, Jeffery L Painter2, Vijay Kara3
1GSK, 1000 Winter Street, Waltham, MA 02451, USA University of Rhode Island, Kingston, RI, USA.
Therapeutic Advances in Drug Safety
|December 23, 2025
Summary
Generative artificial intelligence (GenAI) presents new opportunities and challenges for pharmacovigilance (PV). This review explores GenAI integration in drug and vaccine safety, proposing a framework for responsible implementation.
Area of Science:
- Pharmacovigilance and Artificial Intelligence
Background:
- Generative artificial intelligence (GenAI) is rapidly emerging as a transformative technology.
- Pharmacovigilance (PV) faces evolving challenges in drug and vaccine safety monitoring.
- Integrating advanced AI into high-risk safety domains requires careful consideration.
Purpose of the Study:
- To review emerging trends and practical applications of GenAI in pharmacovigilance.
- To examine the potential benefits and inherent risks of GenAI in drug and vaccine safety.
- To propose a framework for the ethical and effective integration of GenAI into PV systems.
Main Methods:
- This perspective review synthesizes current experimental data and early real-world applications.
- It analyzes conceptual frameworks for GenAI adoption in pharmacovigilance.
- The review emphasizes rigorous testing, human oversight, and ethical considerations.
Main Results:
- GenAI offers significant opportunities for enhancing pharmacovigilance processes.
- Potential risks include data privacy, algorithmic bias, and the need for robust validation.
- A structured framework is proposed to guide GenAI implementation in PV.
Conclusions:
- GenAI can revolutionize pharmacovigilance if implemented thoughtfully.
- Successful integration necessitates a focus on safety, ethics, and human-AI collaboration.
- This work supports PV professionals in navigating the evolving landscape of AI in drug safety.
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