Robotics, Agents, and World (RAW) Models to Target Cancer
To Know
About this Class
Join us for the latest Data Science Seminar Series to explore how AI, robotics, and predictive models could transform drug development. Dr. Arvind Ramanathan, a computational science leader at Argonne National Laboratory, will share an approach his lab is developing that uses automated systems to generate and test hypotheses to design cancer therapies. |
Join the webinar to explore how:
• autonomous AI agents can compete to generate and test hypotheses for cancer drug design.
• real world models can predict experimental outcomes and guide which experiments to run next in robotic laboratories.
• applications of this approach can target intrinsically disordered proteins (IDP) to design therapies for the oncogenic driver WHSC1 and metabolic regulator NMNAT2.