Unlocking the Capabilities of Large Language Models for Accelerating Drug Development

Wes AndersonIan BraunRoopal BhatnagarKlaus RomeroRamona WallsMarco SchitoJagdeep 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.