Laboratories are fascinating collections of equipment, technology and resources. As lab planners, we are familiar with the combinations of technologies required for various kinds of science – imaging systems and electrophysiology rigs are essential to neurobiology, for example. These combinations are so common that we maintain benchmarks for various types of labs whose spatial thumbprints are relatively predictable. These characteristics are not, however, static. They change as technologies evolve and routine tasks become automated or even outsourced.
Of many influences driving biomedical research, I want to highlight two that will have spatial impacts in the years to come. The first is AI, an exciting collaboration between data science, software engineering and the life sciences – which everyone is talking about with some degree of bluster, uncertainty and anticipation. The second is the FDA modernization act signed by President Biden in 2022.
AI will, among other things, enable scientists to compare, merge and iterate faster with massive data sets like transcriptome data, which is generated and manipulated both manually and through software techniques. The promises of this research are therapies that target specific cancer tissues, for example. In order for something like transcriptomics, that is, research reliant on large, sophisticated datasets, to mature, become routine and produce breakthroughs, significant collaborations must occur between computational experts with AI expertise.
Robert Benson Photography
Harvard’s Kempner Institute, designed by PAYETTE, studies natural and artificial intelligence.
Virtually every biomedical discipline is poised to explode with data streams – from behavioral research that uses cameras to track animal movements to electron microscopy that reveals molecular pathways for drug delivery. Lab planners should question the need for lab space and understand potential shifts – will each member of the lab group need a bench or can bench space be devoted to tasks and shared equipment? Will AI make common lab routines faster and change the need for lab support spaces – for example, tissue dissection could become faster by using AI to isolate tissue types instead of separating tissue types by hand, which could result in a larger volume of samples to test. Even small changes to common lab tasks can result in new setups and new lab space needs.
The second trend is inspired by Dr. Mehdi Nikkhah’s recent keynote at the Lab Design 2024 conference on Innovative Lab Space to Build Better Model Systems for Studying Human Disease Progression. His research approach is possible due to the FDA modernization act, which began as H.R. 7667, a Senate bill that enables alternatives to animal models when there are scientifically valid alternatives.
Dr. Nikkhah’s research draws on an alchemy of expertise in micro/nanoengineering, biomaterials and biology/medicine resulting in the creation of microchips engineered as tissue platforms (Biochips). Biochips have advantages over mice because they can grow human tissue, have shorter iteration cycles, and superior imaging potential. The lab setup is straightforward as well:
- Access to cleanroom for fabrication of chips
- Biochip micro fab
- Bench space and 3d printers for printing tissue
- Cell culture lab
- Imaging lab with fluorescence microscopy setup
- No mouse colony, no procedure room
Image Source: U.S. Department of Energy
This ingenuity is at the heart of the creative scientific process. Lab planners should be asking how alternatives to animal models might impact the amount and types of spaces needed in the future. As Dr. Nikkhah’s research grows, his ability to incubate new samples, compare images and develop therapies will undoubtedly be impacted by AI. Institutes at the NIH are incentivizing AI workforce development and coordinating foundational datasets, methodologies and best practices across the institutes.
Trends are exciting and full of promise. Collaborations between medicine and engineering have a remarkably successful history from the invention of Dacron and the Starr-Edwards heart valve, which extended life for hundreds of thousands, to the nano engineering of proteins and pathways that now hold so much promise for solving the most vexing diseases. As lab planners, we must constantly question benchmarks by developing forward-looking research spaces that are more versatile and hybrid by design.
