Robotics, Agents, and World (RAW) Models to Target Cancer
Data Science Seminar Series
February 18, 2026 | 11:00 AM – 12:00 PM
Online
Register/Join
Discover how artificial intelligence (AI), robotics, and predictive models could transform cancer drug development. During this Data Science Seminar, Dr. Arvind Ramanathan will present an approach that uses automated systems to generate and test hypotheses to design new cancer therapies.
Join us 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.
Dr. Ramanathan’s approach combines three cutting-edge technologies: AI agents that reason through different design strategies, predictive models that forecast which experiments will succeed , and robotic labs that conduct experiments autonomously. This integrated system creates a continuous loop of hypothesis generation, prediction, and validation, setting a foundation that could accelerate the pace of discovery for cancer therapeutics.
Register now to secure your spot for this Data Science Seminar Series session.
About the Speaker
Arvind Ramanathan, Ph.D.
Dr. Ramanathan is a computational science leader at Argonne National Laboratory with joint appointments at the University of Chicago and Northwestern University. His research group integrates robotic laboratories, generative AI techniques, and multiscale simulation methods to understand and design complex biological systems for cancer therapeutic development.
About the Data Science Seminar Series
CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI’s Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:
- How can AI be used for diagnosis, treatment, or omics research?
- What are the related laws and ethical considerations for AI?
- How can we empower an AI-ready cancer research community through workforce development, collaborations, and funding?
To view upcoming speakers or recordings of past presentations, visit the Data Science Seminar Series page.