Danaher Corporation on October 14, 2026 announced a collaboration with NVIDIA to advance autonomous science and help accelerate the pace of scientific discovery.
The collaboration pairs Danaher’s scientific instrumentation, automation technologies, laboratory workflow software and domain expertise with NVIDIA accelerated computing and AI technologies. Danaher described the work as part of its broader effort to shape the future of AI-enabled science, and said the goal is to speed researchers’ progress from prediction to experimental evidence, producing a continuous learning cycle in which experimental results feed back into models and models help shape the next round of experiments.
AI Integration Into Scientific Instruments and Laboratory Workflows
Danaher and NVIDIA are working to integrate AI into scientific instruments. The work spans edge computing through NVIDIA DGX Spark, accelerated analytics and data processing through RAPIDS, and real-time inference, scientific reasoning and foundation model technologies including BioNeMo Open Models. Initial efforts focus on a select group of priority instruments, with the potential to expand across a broader portfolio over time.
The companies are also exploring how scientific and physical AI, including NVIDIA Cosmos world models and Omniverse Digital Twins, can support more intelligent instruments and laboratory workflows. Danaher said the work is intended to keep experimental evidence at the center of scientific decision-making.
Danaher said the collaboration seeks to advance its commitment to connected science by bringing AI, accelerated computing, instruments, workflows and experimental data together to produce experimental evidence. The company said it aims to help researchers shorten and simplify the path from an AI-generated prediction to the experimental evidence needed to act on it, while keeping customers free to choose their models, standards and technology providers.
Executive Statements
“AI is reshaping how science is conducted, and Danaher is at the forefront of that transformation,” said Julie Sawyer Montgomery, President and Chief Executive Officer of Danaher. She said the collaboration rests on a shared vision of more connected, adaptive and accessible innovation, and she framed its purpose as helping researchers take on consequential challenges and turn scientific discovery into human impact.
“The next era of scientific discovery will be driven by a continuous loop between AI and experimentation,” said Kimberly Powell, Vice President of Healthcare at NVIDIA. She said the companies are bringing accelerated computing and physical AI into the lab, linking models with instruments and real experimental data so that experiments improve models and models guide the design of better experiments, with the goal of helping researchers shorten discovery timelines from years to months.
Danaher’s Planned AI-Powered Autonomous Lab
On October 7, 2026, Danaher announced plans to launch its first AI-powered autonomous lab, designed to help researchers develop custom antibodies and other molecular tools. Based at Abcam, a Danaher company, the lab combines technologies from Danaher operating companies Beckman Coulter Life Sciences, Cytiva, Genedata, Integrated DNA Technologies and Molecular Devices in one connected workflow, with device orchestration and robotic automation from collaborative work with Automata. The October 7 release also disclosed that Automata received an investment from Danaher in January 2026.
In that announcement, Danaher said the lab applies AI to create new affinity reagents, including antibodies, then builds and tests each candidate, with every result returned to the model to improve the next design. The company said the lab is designed to deliver up to 8x faster discovery of affinity reagents and up to a tenfold increase in annual reagent generation, from tens to hundreds of reagents per year as the lab scales.
Danaher also said each design built in the lab is verified, tested and fed back to improve the next, with scientific rigor maintained alongside speed, and that the approach is expected over time to complement traditional immunization-based methods used to discover antibodies and other research tools.
Danaher described the autonomous lab as the first step in a broader initiative to create smart instruments, integrated workflows and autonomous labs. Under that program, the company said, instruments are being designed to be easier to integrate and control programmatically, to produce AI-ready data and to include expert-level agentic systems designed to simplify operation, improve data quality and generate deeper insights.
The company said these devices can then be connected into integrated workflows and autonomous labs that execute design-make-test-learn cycles, supporting a shift toward more predictive and standardized research workflows in which models prioritize the most promising designs before they are built and robotics support more consistent experimentation. The autonomous lab is expected to operate at scale in early 2027.
