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Across the world, there has been an explosion of scientific discovery. Fueling this progress is a convergence of breakthroughs in biological sciences, automation, data harnessing, computing power, and software infrastructure. These are already driving changes in laboratory architecture, bringing automation and digitization to the fore to connect the physical and cultural attributes of laboratory space and scientific practice.

The physical layout and organization of laboratories have experienced great change across centuries of scientific experimentation.

Despite 50 years of major advances in instrumentation and computer modeling, laboratory design has failed to evolve and adapt to the changing needs of researchers. Emergent technologies are increasingly transforming collaboration between scientific disciplines. The challenge is to create a fully functional and integrated laboratory that optimizes technology while also providing grounds for innovation and creativity.

This paper highlights the evolution of the laboratory space in the life sciences research industry and demonstrates how revolutionary changes will influence laboratory architecture, operation and maintenance.

Laboratories from the mid-20th century witnessed increased integration of transitional and experimental spaces, but a space fostering interaction and community remained an unfulfilled goal. The design of older buildings is simply sub-optimal for collaborative science practices.

Figure 1: Evolution of scientific space


Source: CBRE 2022 Occupancy Benchmarking Program.

The evolution of scientific space can be divided into four historical phases: individual exploration, professional research, centralized research and integrated interdisciplinary research. The era of professional scientific research laboratories increasingly shifted from individual to cooperative research. Centralized organization arose and space topology changed, with greater integration of experimental and transitional spaces.

Laboratory configurations of today

Currently, the complexity of scientific research and the necessity of multidisciplinary, face-to-face interaction among teams positions scientific enterprise as an increasingly social activity. Stimulating innovation and promoting communication are the focal considerations in laboratory design. Functional space is no longer adequate to meet research needs.

Configurations of today’s laboratory space:1


Traditional Laboratory

Centered around a broad range of desktop experimentation and organized as repetitive workstations designated for specific utilities


Open Laboratory

Available for use by a range of disciplines for diverse experimentation and research. Such labs leverage investment into key instrumentation, and because of such high use they require accessibility, high instrument setup and uptime, tear down, cleaning and calibration


Flex/modular Laboratory

Designed to be adaptable and reconfigurable to accommodate a variety of research needs. Modular furniture, utilities and equipment facilitate rearrangement and modification to meet the specific requirements of a project


Collaborative Laboratory

Brings together a variety of disciplines to realize the goal of producing innovative solutions from all personnel involved in the delivery and impact of laboratory output

Looking ahead: integrated interdisciplinary research

Occupancy evaluation has paved the way to understanding how patterns of use contribute to the success—and indeed, failure—of laboratory building design. Today's standards prioritize designs that consider functional needs and safety concerns, along with ergonomics, indoor air quality, flexibility, thermal/visual/acoustical comfort and existence of collaborative spaces. Such transitional spaces have expanded, ranging from break rooms and lounges to other places where researchers can both relax and collaborate outside the laboratory proper.

Scientific workspaces in the next three decades are set to incorporate:


Cloud technology2

The direction of laboratory design and architecture is becoming increasingly built around the rise of the robot researcher. Cloud labs present a means by which anybody, anywhere can conduct experiments via remote control, facilitated by remote access. Experiments are programmed through a subscription-based online interface. Using software, automated scientific instruments and robots are coordinated to perform experiments and process data. The allure of cloud labs is productivity—conducting several experiments at once, accelerating the speed to result. Moreover, remote-operated labs address the “reproducibility crisis”—the inability to replicate research using the published methods when attempted by a different group.


Laboratory automation3

Increasingly, laboratory equipment is moving away from batch to continuous-flow instrumentation. Search lab automation paves the way for methodical and standardized processes, with miniaturization and parallelization empowering laboratories to screen several experimental conditions. Together they enable fast and accurate process development in a fraction of the space, cost and time.


Digital twin technology4

A digital twin provides a replicated virtual model of the physical system. In the life sciences, the use of digital twin technology is in its infancy. However, as digitalization coincides with the increasing automation of testing, researchers can rapidly recreate and reproduce experimental scenarios, across locations and personnel, in highly controlled environments. Incorporating digital twin technology into scientific experimentation can bolster the volume of fit-for-use data generated.

Figure 2: Laboratory Roadmap Evolution

Source: Paul Janssenswillen, Head of Scientific Projects, CBRE.

Driven by the need to accelerate and improve the success of research and drug discovery, life science laboratories are increasingly looking to technology to plug the gaps between physical labor in the laboratory and complex data analytics.

1 Gregory Weddle, Vice President Specialty & Regulated Solutions, CBRE.
2 The Guardian. Cloud labs and remote research aren’t the future of science – they’re here. Last accessed January 2023.
3 Technology Networks Informatics. Automation in the Lab of the Future. Last accessed January 2023.
4 Lei Z, Zhou H, Hu W, Liu G. Web-based digital twin online laboratories: Methodologies and implementation. digitaltwin; 2022. DOI: 10.12688/digitaltwin.17563.1.

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