Opentrons × NVIDIA: Extending Lab Automation into the Era of Physical AI

AI is rapidly reshaping biology, but progress is increasingly constrained not by models but by physical execution in the lab.

In this session, James Atwood (CEO, Opentrons) and Stacie Calad-Thomson (North America Business Development Lead, Healthcare and Life Sciences, NVIDIA) explore how laboratory automation is evolving in the age of Physical AI, where digital intelligence must reliably plan, execute, observe, and adapt in the real world.

While much of today’s AI ecosystem focuses on models, simulation, and prediction, the next frontier requires programmable, end-to-end execution of experiments, translating scientific intent into repeatable physical workflows and generating the execution data AI systems need to learn and improve.

Together, Opentrons and NVIDIA will discuss how open, software-defined lab automation enables this shift, connecting AI planning, perception, and robotics into closed-loop experimental systems. The session will highlight emerging approaches, such as multi-modal training with digital twins, that dissolve the boundary between intent and execution, and explore what this means for scalable, AI-native biology in drug discovery and beyond.

Attendees will also have the opportunity to sign up to participate in future Physical AI initiatives, contributing their expertise through hands-on demonstrations that help inform the next generation of intelligent laboratory systems.

This session offers a practical view into how Physical AI is moving from theory into the lab and why execution is becoming the critical leverage point for scientific breakthroughs.