Cancer Drug Discovery AI Agentic Workflow R&D

Explore an in-depth 57-minute video presentation on the cutting-edge applications of AI agentic workflows in cancer drug discovery research and development. Delve into the latest advancements in Generative AI for drug discovery, focusing on innovative methods to automate and enhance the process of identifying promising drug compound leads. Learn how industry experts are leveraging AI agentic workflows to tackle complex problems in the field. Discover the potential of improved planning and multi-agent collaboration, enabling more productive interactions between large language models (LLMs) and other AI systems. Gain insights into key frameworks such as LangChain, LangGraph, and CrewAI, which facilitate the orchestration of increasingly complex tasks. Examine recent developments shared by experts like Andrew Ng, Harrison Chase, and Arsenii Shatokh, and explore case studies from research groups such as LIAC's 'ChemCrow' and LAMM-MIT's 'MechGPT'. Understand how these chemical AI agentic workflows can be applied to cancer drug discovery, potentially revolutionizing the research process and accelerating the development of new treatments.