Northwestern University has received $20 million from the National Science Foundation (NSF) to launch the AI-Driven, Rapid, Experimental Automation Machine (DREAM) Cloud Lab, a publicly accessible platform for protein engineering. The initiative, part of a $380 million national network of programmable cloud laboratories, aims to accelerate biotechnology innovation through AI, robotics, and remote experimentation.
Funded by the NSF’s Programmable Cloud Laboratory (PCL) program, the facility will operate within Northwestern’s Center for Synthetic Biology (CSB), leveraging advanced robotics and AI models to streamline protein engineering. This initiative is poised to transform fields ranging from medicine to sustainable materials, with potential applications in drug development, agriculture, and environmental remediation.
The Vision Behind DREAM
The DREAM project, described as the first publicly accessible, AI-powered cloud laboratory for protein engineering,
was highlighted by Mung Chiang of Northwestern University as a strategic milestone. DREAM is an important initiative that will create the platform for our Center for Synthetic Biology to collaborate with researchers across the nation, advancing important breakthroughs in protein engineering and broadly in biotechnology,
Chiang said. The lab’s goal is to overcome the traditional bottlenecks in protein engineering by integrating AI-driven hypothesis generation, robotic experimentation, and iterative data learning.
The NSF’s investment in DREAM is part of a broader $380 million effort to establish a national network of cloud laboratories.
National Network of Cloud Laboratories
The DREAM Cloud Lab is one of 20 inaugural PCL testbeds funded by the NSF. These facilities are designed to create a “virtuous cycle” of automated hypothesis generation, autonomous experimentation, and rapid data analysis, as described by NSF Assistant Director Erwin Gianchandani. The network’s infrastructure will allow scientists to collaborate across disciplines, with DREAM serving as the protein-engineering hub. This integration will enable the sharing of AI models, experimental data, and best practices, fostering a more interconnected scientific ecosystem.
The lab’s physical location within the CSB’s Synthetic Biology Foundry underscores its role as a central node in this network. The Foundry, co-located with the Querrey InQbation Lab—a startup incubator—will facilitate the rapid translation of research into commercial applications. DREAM will positively transform our society, spinning out new companies and creating new jobs by accelerating new technologies for manufacturing, critical mineral mining, healthy aging, agriculture, and advanced materials,
said Julius B. Lucks, principal investigator of the DREAM project.
Leadership and Vision
The DREAM project is led by a team of researchers including co-PIs Danielle Tullman-Ercek, Han Liu, and Michael Jewett, alongside Northwestern’s Julius B. Lucks. Christopher Schuh, dean of Northwestern Engineering, emphasized the university’s longstanding leadership at the intersection of engineering, AI, and biology.
The funding, he added, reflects not only financial support but also strategic recognition of Northwestern’s role in shaping the future of biotechnology.
The project’s leadership also includes Joshua Leonard and Michelle Hoffmann, who will oversee the integration of responsible innovation frameworks. By embedding ethical considerations into the lab’s operations, DREAM aims to address concerns about the societal impact of AI-driven biotechnology. “Building DREAM within the Northwestern Center for Synthetic Biology allows us to integrate our approaches for responsible innovation, boosting our regional biotech ecosystem and serving the entire nation as a hub for transformative science and engineering that benefits everyone,” Lucks said.
Implications for Biotechnology
The DREAM Cloud Lab’s focus on protein engineering aligns with growing interest in AI’s role in life sciences. While tools like DeepMind’s AlphaFold have advanced protein structure prediction, the DREAM initiative addresses the next challenge: experimental validation. By automating the design-build-test-learn cycle, the lab could significantly reduce the time and cost of developing new proteins for medical and industrial applications.
For regions like Canada, where biotechnology ecosystems are rapidly expanding, the DREAM project offers a model for scalable, collaborative research. Canadian institutions such as the Vector Institute and Mila have already pioneered AI-driven approaches to scientific discovery, and access to DREAM’s tools could further accelerate innovation.
Related reading
