Leveraging AI in pharmacovigilance workflows

Artificial intelligence (AI) offers opportunities to increase speed and reduce resource burden across the drug lifecycle, enabling improved patient outcomes. To better support growing case volumes, pharmacovigilance (PV) teams are assessing how this technology can be leveraged to supplement existing efforts, including streamlining case processing and adverse event intake. There are several critical considerations to ensure successful implementation of AI across PV workflows, but with a strategic and compliant approach, AI stands to revolutionize PV functionality.

What Is The Regulatory Climate Like?

The rapid proliferation and relative newness of AI in pharmaceutical processes has resulted in a somewhat uncertain regulatory landscape. However, the FDA and other regulatory agencies around the world have demonstrated a robust effort to provide guidance around how best to leverage this technology. Two recent updates from the FDA should be top of mind for PV teams considering the integration of AI into its current workflows:

The Center for Drug Evaluation and Research’s (CDER) Emerging Drug Safety Technology Program (EDSTP): In 2024, CDER launched EDSTP, an initiative that aims to promote discussion on the use of AI and emerging technologies in PV processes. As part of this program, drug sponsors can request non-binding meetings with the FDA to discuss AI usage in their PV systems and gain regulatory feedback.
Considerations for the Use of AI to Support Regulatory Decision Making for Drug and Biological Products’ draft guidance: Released in January 2025, this draft guidance focuses on AI usage across all stages of the lifecycle, providing insight on how to leverage a risk-based approach to AI to ensure credibility and accuracy.

Though the regulations will likely continue to shift in the coming years, these initiatives reflect the willingness of the FDA to support AI assistance across the drug lifecycle and collaborate with sponsors to enhance its impact.

How Does AI Improve PV Processes?

As PV teams are faced with increasing volumes of structured and unstructured data across a variety of sources, thoughtful inclusion of AI enables more efficient processing and minimal handoffs. These are some of the ways AI might be used to supplement PV efforts:

In-operation data analysis on medical information calls: AI conducts voice and sentiment analysis, transcription, and adverse event intake.
GenAI language processing: Applying AI to scan unstructured data, like social media, for adverse events.
Optical character recognition (OCR): AI pulls data from structured documents and conducts mapping to structured fields.

Drug sponsors exploring where and how to add AI into their existing PV systems should consider working with an experienced provider of AI-driven PV solutions. Given the complexity of AI, establishing a partnership with experts not only helps ensure a return on investment but also brings essential knowledge, skills, and resources to ensure that AI is implemented effectively and safely.

Ready To Learn More?

In a recent webinar, IQVIA experts spoke to the FDA’s latest regulatory guidance around AI and how to strategically implement this technology into existing PV systems to increase efficiency and accuracy. If you are ready to learn more about how to leverage AI in your PV program, download the white paper, The Future of Pharmacovigilance: Integrating AI with Drug Safety Systems.

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What Is The Regulatory Climate Like?

How Does AI Improve PV Processes?

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