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Artificial Intelligence in Pharmacovigilance: Global Health Authorities Updates

Introduction

Global health authorities are actively shaping the future of artificial intelligence (AI) in pharmacovigilance, with new guidelines and frameworks emerging across regions. This article explores how regulators in the United States, Canada, Europe, United Kingdom, Brazil, Mexico, and Australia are responding to AI’s growing role in drug safety. From signal detection to case processing, AI is transforming traditional PV workflows. Authorities are now focused on balancing innovation with risk management, transparency, and compliance.


Discussion

Today, AI tools are reshaping each of these activities. Case processing can be streamlined with natural language processing (NLP) and automated intake systems that classify and prioritize reports. Narrative writing benefits from AI‑driven text generation that produces medically coherent drafts, reducing reviewer workload. AE coding is accelerated by machine learning models trained on MedDRA, improving consistency and reducing human error. Case submissions can be automated through intelligent workflow systems that ensure compliance with ICH E2B(R3) standards. Aggregate reporting is enhanced by AI‑powered analytics that synthesize large volumes of safety data into structured outputs. Signal detection has been revolutionized by machine learning algorithms capable of scanning real‑world data, electronic health records, and social media to identify emerging safety concerns faster than traditional disproportionality analyses. Finally, quality and compliance monitoring can leverage AI dashboards that flag anomalies, track metrics, and support continuous inspection readiness.


Below is a snapshot of regulatory developments and strategic approaches worldwide.


Regulatory Updates by Region

  • U.S. FDA: Issued draft guidance in January 2025 titled Considerations for the Use of Artificial Intelligence to Support Regulatory Decision-Making, outlining a risk-based framework for evaluating AI tools used in drug development and safety.

  • Canada (Health Canada): AI/ML guidance for medical devices is imminent, with discussions around pre-determined change control plans (PCCPs) and digital health oversight. PV-specific AI guidance is still evolving.

  • Europe (EMA): Published a reflection paper and launched initiatives under the EU AI Act to guide AI use across the drug lifecycle, including PV. EMA emphasizes transparency, validation, and ethical use of AI in safety monitoring.

  • UK (MHRA): Released its AI regulatory strategy in April 2024, focusing on safety, transparency, and governance. MHRA is integrating AI into both its internal processes and external regulatory frameworks for PV and medical products.

  • Brazil (ANVISA): While no specific regulations for AI systems yet exist, the agency implemented AI tools to streamline post-registration safety evaluations. Although not PV-specific, these innovations support broader drug safety modernization. The agency is also actively using AI to improve processes and accelerate drug and medical device evaluations.

  • Mexico (COFEPRIS): Continues to rely on VigiFlow for AE reporting. While no formal AI guidance exists, COFEPRIS has emphasized international harmonization and digital transformation in its PV framework.

  • Australia (TGA): Released a 2025 compliance update clarifying that AI tools with diagnostic or safety functions may be regulated as medical devices. TGA is revising PV standards to align with global benchmarks.


Conclusion

Artificial intelligence is no longer a future concept in pharmacovigilance, it’s a present reality. As global health authorities begin to formalize their positions, the regulatory landscape is shifting toward structured oversight, ethical use, and validated integration of AI tools. While harmonization is still evolving, the momentum is clear: AI will be central to the next generation of drug safety, risk management, and regulatory compliance. For PV professionals, staying informed and adaptive is no longer optional, it’s essential.


References


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