Opentrons Labworks Inc., a leader in laboratory robotics for AI-driven scientific discovery, is advancing the development of physical AI-powered laboratory systems through a strategic integration with NVIDIA. The collaboration combines Opentrons’ global network of over 10,000 deployed robotic systems with NVIDIA’s Isaac and Cosmos platforms to create AI models trained on real-world biological experiments. This partnership enables the creation of physical AI systems that learn directly from laboratory operations, bridging the gap between simulation and real-world experimentation. Opentrons provides a unique combination of assets: a vast, standardized fleet of lab robots used by top research universities and leading biopharma companies, along with deep expertise in executing diverse scientific workflows across both its own platforms and third-party instruments. Until now, AI in drug discovery has largely focused on prediction—suggesting molecules, identifying targets, and analyzing data—while actual experimental execution has remained a major bottleneck. By standardizing physical lab processes and generating high-quality training data from real experiments, Opentrons is enabling AI systems to continuously learn from wet-lab results, accelerating the pace of discovery. “We envision a future where physical AI drives autonomous experimentation across labs worldwide,” said James Atwood, CEO of Opentrons. “AI models propose hypotheses and experimental plans, our robots execute them, and the results are fed back into the system to refine future experiments. When this loop runs continuously across thousands of labs, discovery timelines can shrink from years to weeks.” Stacie Calad-Thomson, North American Business Development Lead for Healthcare and Life Sciences at NVIDIA, emphasized the importance of connecting computation with physical validation. “With NVIDIA AI, Opentrons delivers the standardized, reliable infrastructure needed to turn experimental designs into consistent, reproducible results,” she said. “This is critical for generating the high-quality training data that physical AI models require to operate effectively across diverse lab environments.” Opentrons’ AI-enabled robots automate complex workflows in areas such as antibody discovery, genomics, and proteomics. With deployments at every top-20 U.S. research university and 14 of the world’s top 15 biopharma companies, the company operates the largest standardized network of lab automation globally. The collaboration will be highlighted at the SLAS International Conference and Exhibition, February 9–11, 2026, in Boston. During the joint session, “Opentrons × NVIDIA: Extending Lab Automation into the Era of Physical AI,” the companies will explore how AI-driven planning and robotic execution are converging to create self-improving scientific systems. Following the presentation, NVIDIA representatives will join Opentrons at Booth #917 to engage with scientists and introduce a new program that allows researchers to contribute real experimental data to train AI models for scientific discovery. Opentrons, backed by SoftBank and Khosla Ventures, is headquartered in New York and is building the physical execution layer for autonomous science. The company’s open, API-driven platform standardizes biological experimentation, enabling continuous feedback between AI and laboratory systems. For more information, visit opentrons.com.