Wes Anderson, Ian Braun, Roopal Bhatnagar, Klaus Romero, Ramona Walls, Marco Schito, Jagdeep T. Podichetty
Recent breakthroughs in natural language processing (NLP), particularly in large language models (LLMs), offer substantial advantages in model-informed drug development (MIDD). With billions of parameters and comprehensive pre-training on diverse data, these models effectively extract information from unstructured and structured data throughout the drug development lifecycle. This perspective envisions LLMs supporting MIDD, enhancing drug development, and emphasizes C-Path’s strategic use of LLM innovations for actionable real-world evidence from real-world data (RWD).
You can read the publication in its entirety on the ASCPT website here.
