Minisymposium Presentation

Evidence from randomised controlled trials is often reported as aggregate effects, while individual patients may differ from the trial population in many ways. Determining the most applicable evidence for a given patient’s unique characteristics and prior treatments can be challenging. Large Language Models (LLMs) enable large-scale processing of textual information, offering a step change in how we extract and apply trial evidence. This presentation will cover recent advancements in leveraging LLMs to accelerate the translation of evidence into personalised treatments.