Cairnes agrees, saying that for developers and landlords looking for ROI, the capital expenditure on contrasting technical elements makes it more difficult to set up dry labs on demand, as tenants have very specific requirements.
“While the physical construction costs may not be significantly different than traditional labs, it is the more complex AI, automation and robotics equipment that is driving costs up,” he says. “It is likely that providing flexible laboratory space that meets the needs of end-user scientists and their specific scientific plans will continue to be critical to the future of the laboratory.”
Digitalization supports faster innovation
Project management professionals are now leveraging digital tools and AI to create time and quality efficiencies for more strategic and cost-effective construction of life science projects.
AI's ability to collect, organize and interpret large amounts of information to produce useful insights can help with everything from procurement planning and program planning to monitoring site safety or improving sustainability.
Cairnes explains how Building Information Modeling (BIM) helps create digital twins for visualization and better planning. “For example, it can detect potential collisions between pipes, wiring or electrical systems and structural elements such as beams, which could lead to expensive problems later,” he says.
For Dusi, what’s most exciting is AI’s potential to improve the overall experience and well-being of people working in life sciences laboratories. She sees great potential for AI to simulate different scenarios and create evidence-based design for greater productivity and efficiency.
“By looking at the path of access for scientists, how many steps are required between different pieces of equipment, how they interact with their colleagues in wet and dry labs, as well as things like air quality, daylight, we can design and build labs that support researchers help achieve important breakthroughs more quickly,” she says.