Discover Cencora at World Drug Safety Congress Americas 2025
- PV system governance: EU QPPV, PSMF, PV agreement management, quality systems, training, PV audits & inspections
- Local Affiliate PV services: National contact person & all local services
- PV operational support: Literature surveillance, ICSR management, safety reporting
- Benefit-risk management: data-driven insights for decision-making
- AI-enhanced technologies: digitized solutions & intelligent automation
Expert session
Harnessing AI and Advanced Analytics to Revolutionize Pharmacovigilance Signal Management
Pharmacovigilance lies at the heart of patient safety, with signal detection and assessment serving as its cornerstone. However, the growing volume of complex, often unstructured patient data presents significant challenges in identifying, assessing, and acting on safety signals efficiently. Artificial intelligence (AI) and advanced analytics are reshaping the landscape of pharmacovigilance, offering new opportunities to enhance signal management processes.
In this talk, we explore how cutting-edge techniques—such as natural language processing, generative AI, machine learning, and Bayesian statistics—can be applied to unlock the full potential of pharmacovigilance. We will showcase applications that demonstrate how these tools streamline data harmonization, improve signal detection accuracy, and accelerate decision-making. Additionally, we will highlight best practices for ensuring transparency, ethical implementation, and regulatory compliance when adopting these advanced technologies. Finally, we’ll provide insights into the outlook of AI-powered pharmacovigilance, emphasizing its role in creating smarter, more proactive drug safety systems.
Presenters: Lin Li, Head of Clinical Statistics & Computational Biology at Cencora; Stephen Sun, VP, US Pharmacovigilance, Epidemiology, and Risk Management at Cencora
Date: Wednesday, November 5, 2025, 2:00 - 2:20 PM ET
Location: Next Gen Tech & Data |Theater 6 - Room 052A
Connect with us at the booth #313
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