Pharmacovigilance (PV) is increasingly crucial yet operationally overloaded, as traditional manual processes for adverse event (AE) reporting become unsustainable. In 2023, the FDA reported over 2.1 million safety signals, a significant rise from 2011. With adverse drug events ranked as the third leading cause of death in the U.S., there’s a pressing need for PV automation to manage this complexity effectively.
The market for automated PV solutions is projected to grow from $3.03 billion in 2026 to $5.68 billion by 2031, driven by the integration of AI technologies like Natural Language Processing (NLP) and machine learning, which enhance data processing efficiency and accuracy. Key pillars for successful implementation include a clear strategy, transformation of operational models, and robust stakeholder communication and training.
As AI adoption accelerates, regulatory frameworks are evolving to ensure transparency and human oversight in automated systems. The future of drug safety appears to hinge on these advancements, promising to shift PV from reactive to predictive capabilities, thus improving patient safety.
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Link to original article source: https://www.pharmaceuticalcommerce.com/view/how-automation-and-ai-can-transform-pharmacovigilance
