DrugRAG: Enhancing Pharmacy LLM Performance Through A Novel Retrieval-Augmented Generation Pipeline
Researchers have developed DrugRAG, a novel retrieval-augmented generation pipeline designed to enhance the performance of large language models (LLMs) on pharmacy-related question-answering tasks. In their study, they evaluated ten LLMs, finding that GPT-5 and o3 performed best on a 141-question dataset. DrugRAG, which integrates structured drug information without altering model architecture, significantly improved accuracy across several models, particularly smaller open-source ones, by up to 21 percentage points. AI
IMPACT Provides a practical method to enhance LLM accuracy for specialized knowledge domains like pharmacy.