Before a scientist can run an experiment, somebody has to make the room behave. The air must move in the right direction. Equipment needs to arrive, work, and remain qualified. Materials have to travel through the building without colliding with waste. Safety rules, data systems, vendor schedules, and maintenance plans all need to disappear into the background. Discovery gets the photograph. Infrastructure keeps the photograph from becoming a picture of people waiting.
Brian Taylor has spent nearly three decades close to that unphotogenic machinery. He began at Genentech, focused on large-scale monoclonal antibody production. Later he ran the global Biomanufacturing Solutions business at GE Healthcare Life Sciences, developing systems for other companies to make biologic drugs. At molecular-engineering company Zymergen, he led the healthcare business. The jobs changed, but the underlying question stayed recognizable: how do you turn delicate science into a repeatable operation?
At SmartLabs, where Taylor became interim chief executive in early 2024 and now serves as CEO, the operation is no longer only a manufacturing process. It is the laboratory itself. SmartLabs designs, equips, operates, and supports private research environments that companies can use without first becoming developers, facilities managers, procurement departments, and building engineers. Taylor's proposition is easy to say and difficult to execute: let the scientists own their research, while someone else owns the friction around it.
The room is part of the experiment
The conventional lab is a confident prediction about the future. A company signs a lease, commits capital, specifies a layout, waits through construction, and hopes the scientific program still wants the same things when the doors open. That bargain was awkward when research plans were stable. It is worse when a young biotech might change its target, modality, headcount, or equipment after a single result.
Taylor describes newer drug programs as infrastructure omnivores. They may need one configuration during discovery, another for process development, and specialized support as they move toward manufacturing. His concern is less aesthetic than financial. Every dollar fixed in a room is a dollar unavailable for another scientific attempt. Every month spent waiting for a facility is a month in which the team is not learning.
“For that to work, you've got to be fast - really fast.”Brian Taylor on the pace required in modern life sciences
This is where the phrase “lab-as-a-service” can mislead. A laboratory is not a desk with more outlets. It carries biological-safety obligations, controlled workflows, specialized utilities, and equipment that can cost more than the offices surrounding it. Flexibility cannot mean a room with wheels on the benches and a hopeful shrug. It has to mean a prepared system that can absorb change without handing the risk back to the customer.
Taylor's manufacturing background fits this challenge unusually well. SmartLabs credits him with helping develop turnkey monoclonal-antibody manufacturing solutions on a single-use platform, launching and running regulated cGMP sites, and working with Congress on domestic generic manufacturing. Those are exercises in constraints. A process must be safe, documented, reproducible, and economical at the same time. You cannot charm a bioreactor into compliance.
From making products to making capacity
There is a subtle shift across Taylor's career. At Genentech, he worked on producing a particular class of medicine at scale. At GE, he moved toward platforms that helped many manufacturers build their own processes. At SmartLabs, the product is capacity itself: the ability for a research team to begin, change direction, and grow without rebuilding its physical world at every turn.
He joined SmartLabs in 2020 as executive vice president of Biopharma Solutions. The remit sprawled across technical and site operations, commercial work, lobbying, and the development of new services. It was a role for someone comfortable walking between the mechanical room, the customer meeting, and the policy conversation. In January 2024, founder Amrit Chaudhuri moved into a strategic advisory role and Taylor took responsibility for day-to-day management as interim CEO.
The timing mattered. Biotech's abundant-capital years had ended. A model built around avoiding upfront construction suddenly had to prove more than convenience. It had to show capital discipline. Taylor expanded SmartLabs' Custom Developed Solutions program so the company could design, build, and operate facilities for partners beyond its own research centers. The company was learning to separate its operating system from the real estate it happened to occupy.
An operating system travels
A building does not scale elegantly. A method can. In June 2025, SmartLabs signed a 10-year partnership with International Workplace Group, the operator behind flexible-workspace brands including Regus and Spaces. IWG brought reach across more than 120 countries. SmartLabs brought the specialized playbook: site selection, lab design, construction management, daily operations, and scientific support.
The first international test arrived in May 2026. SmartLabs, IWG, and Australian developer Kurraba Group announced a deployment at ION, a planned life-sciences precinct in Waterloo, Sydney. The project is designed to include more than 27,000 square meters of lab-enabled space, with incubators and cGMP clean rooms. Delivery is scheduled for late 2028. For Taylor, Sydney is evidence that the service can be carried into a market where scientific talent exists but specialized commercial lab capacity is thinner.
Control does not require owning every layer. A biotech can keep its people, data, and intellectual property private while accessing the expensive operational stack around them as a managed service.
There is another layer traveling with it: data. In August 2025, SmartLabs announced a partnership with Sonrai Analytics to make its AI-supported precision-medicine data platform available in SmartLabs centers. The companies also said they would develop applications connecting experimental and infrastructure data. Taylor's line was characteristically broad: “We live in the age of data and AI is what unlocks its true value.” The practical question underneath is narrower and more interesting. If the building knows more about how research is run, can it help the team make better decisions about the research itself?
That idea turns the lab from a passive container into an instrument. Equipment utilization, environmental readings, maintenance records, and experimental data do not have to live in separate worlds. Connect them carefully, and the operating environment can become legible. The value is not a robot scientist. It is fewer blind spots in a system where small delays and mismatched workflows accumulate quietly.
The operator's form of optimism
Taylor was named to the 2024 PharmaVoice 100 in the publication's Biotech Pathfinders group. His reaction redirected the credit toward the SmartLabs team and its member companies. It was consistent with the public version of his leadership: less personality theater, more attention to the system and the people running it. Even his most ambitious statements tend to arrive attached to a list of operational requirements.
That restraint suits the business. Laboratory infrastructure is a promise made in advance. The customer discovers whether the promise was honest only after the experiment changes, a piece of equipment fails, or a program suddenly needs to scale. The real product appears at the inconvenient moment.
“You need somebody who understands the platform but who also understands the science and how to merge those two.”Brian Taylor on the specialized skill behind a flexible lab
The tension in Taylor's strategy is useful. Science requires control, but companies also need flexibility. Labs are local, but the operating model aims to become global. Researchers need specialized environments, but investors want capital efficiency. SmartLabs has to hold both sides without pretending the tradeoff has vanished.
Taylor's bet is that competence can resolve enough of the tension to matter. A well-run platform can give a team privacy without isolation, flexibility without improvisation, and speed without asking scientists to become amateur facility operators. None of that guarantees a successful experiment. It does something more modest and more defensible: it gives the experiment a better place to happen.