Digital Innovation In Pharmacovigilance

The rapid advancements in artificial intelligence (AI) technologies, particularly with the rise of Large Language Models (LLMs) and generative AI over the past two years, have sparked significant excitement in the field of pharmacovigilance (PV). AI applications in PV are showing great potential, with current explorations including the use of Natural Language Processing (NLP) for managing case intake, generative AI for narrative writing, and advanced AI techniques for signal detection and predicting adverse events. This whitepaper delves into the current reality versus the hype surrounding AI in pharmacovigilance, highlighting key business use cases and potential benefits for biopharmaceutical safety teams. It also provides a decision framework to help determine whether AI is the right solution or if more proven approaches, like rules-based automation, are better suited for specific tasks.

Importantly, the paper emphasizes the need for a balanced integration of people, processes, and technology to fully capitalize on AI opportunities. It stresses the importance of critically evaluating the usefulness of disruptive technologies across different functions and stages of the safety lifecycle, ensuring they can deliver tangible benefits, enhance patient safety, and align with the organization’s core strategic goals.