Pharmacovigilance Event Extraction

Pharmacovigilance event extraction aims to automatically identify and extract adverse drug events (ADEs) from various text sources like medical literature and social media, improving drug safety monitoring. Current research heavily utilizes large language models (LLMs), often within retrieval-augmented generation (RAG) frameworks, to process and analyze textual data, with a focus on mitigating issues like "hallucinations" and improving accuracy through techniques like incorporating contextual information and multimodal data (text and images). This automated approach promises to significantly enhance the efficiency and accuracy of pharmacovigilance, enabling faster detection of safety signals and ultimately improving patient safety.