April 2026 — Walk the floor at any Lab of the Future event this year and you hear the same story. Most big pharma companies have AI models in production. Predictions are getting better. Budgets are getting signed. And yet, behind all of it, there’s a quiet problem almost nobody is naming: the layer that connects what the AI decides to what the lab actually does is still, in most organizations, a person with a spreadsheet.
That gap is what newLab®, the lab operations infrastructure orchestration layer built natively on ServiceNow, was built to close.
“The lab is automated, but the orchestration is still human. The AI model says: run this experiment. And then someone, usually still a person, figures out what’s available, checks maintenance, books the time. We want to close that gap.” — Pierre Merea, CEO, newLab®
The Dry Lab Has Outpaced the Wet Lab
For the last five years, R&D organizations have poured investment into the dry lab: the computational side, where models predict molecular behavior and suggest the next experiment. Those investments are paying off. The wet lab has not kept up. Equipment still has to be found, booked, and maintained by people before any prediction turns into a result.
The handoff is where time disappears. A model can propose a thousand experiments in an afternoon. A scientist then spends the next week finding out which instruments are free, which are down, and who owns what across which site. In most R&D organizations, that coordination still happens in calendars and email threads.
newLab® fills in the missing piece in the lab in the loop model: the operational layer, driven by AI, that keeps the wet lab synchronized with whatever the dry lab is producing. It is not a LIMS and it is not an ELN. It sits underneath both and manages the resources, services, and workflows that make experiments actually happen.
Built Natively on ServiceNow
newLab® runs directly on ServiceNow, the enterprise infrastructure platform most large R&D organizations already use for IT and operations. The choice is deliberate. Rather than asking labs to adopt another standalone system, newLab® extends the workflow engine pharma, biotech, cosmetics, food and beverage, chemicals, and higher-education research institutions have already standardized on.
The result is one platform where lab equipment, scientific services, shared resources, and workflow orchestration live alongside the rest of the enterprise. And where the AI layer finally has something to talk to on the other side.
Why Now
Merea’s point from the field is simple: the appetite for AI in research is no longer what’s holding labs back. The models work. The data strategies are in place. Executive sponsorship is there. What’s missing is the operational layer that turns a prediction into a scheduled, resourced, executed experiment.
“Every R&D leader I talk to is past the question of whether AI belongs in the lab,” Merea said. “The real question is what has to be true operationally for AI to work. That’s the conversation newLab® was built for.”
The labs that solve the orchestration problem first are the ones that will actually compress discovery timelines. For everyone else, the AI will keep running and the experiments will keep waiting.
newLab® is working with R&D and IT leaders across pharma, biotech, and adjacent industries to build that layer. More on the dry lab to wet lab integration approach is available at newlabcloud.com.
About newLab®
newLab® is the operational infrastructure layer for R&D labs, built natively on ServiceNow. It manages the resources, services, and workflows that connect computational research to physical lab execution, giving research teams and the AI systems guiding them a single platform for lab orchestration. newLab® works with pharma, biotech, cosmetics, food and beverage, higher education and research, and chemical and materials science organizations.
For more information, visit newlabcloud.com or book a demo at newlabcloud.com/bd









