Drug Labeling

Drug labeling research focuses on improving the extraction, analysis, and utilization of information contained within drug labels to enhance various aspects of drug development and use. Current research employs advanced machine learning techniques, including large language models (LLMs) like BERT and novel graph-based deep learning architectures, to automate tasks such as adverse drug event identification, ADME property extraction, and drug repurposing prediction. These advancements aim to accelerate drug discovery, improve pharmacovigilance, and facilitate more efficient regulatory processes, ultimately leading to safer and more effective medications.