An exhaustive review of the state of laboratory design will reveal some exciting solutions toward creative environments, flexibility and sustainability. These are the three constants that end up in almost every article written on the subject. 

Have you noticed that, because they are so ubiquitous in design literature, they are beginning to sound like solutions looking for applications? Maybe it is because they have been such good concepts in the past that we take them for granted and use them now without thinking. We repeat the catchphrases without thought, using words that are not our own. We dress new challenges with comfortable clothes, sometimes re-tailoring them to fit no matter the situation. 

In this article, let’s detour through a different threshold. Let’s open our eyes again and see things the way they are now, today, in our current geopolitical, economical, and socially inter-netted, tribally isolated, interlocked and collision-prone world. 

We first need to remember that, for laboratory design, our client is not a company, a government agency or an institution; it is science, and science knows no borders. If life sciences are our client, health is the primary driver.

In December 2017, the Centers for Disease Control indicated in a commentary “Global Health Security—An Unfinished Journey” that a tidal wave of communicable diseases threatening global health has been growing since 1980. As a result, we are experiencing an unprecedented growth in global health threats that need new proven drugs, vaccines and therapies. 

What is the life science research, development and production industry doing to address this need? 

According to “A new future for R&D? Measuring the return from pharmaceutical innovation 2017,” published by Deloitte Centre for Health Solutions, there has been a 67 percent cost increase of R&D that is driving a 22-percent decrease in the number of new drugs and therapies that have reached the market during the past seven years. So not only are we not keeping up, but we are actually going backward in terms of producing new proven therapies. This is not to say that the things we are producing are not phenomenal; it just means we are not keeping pace with the current challenges. 

These two facts are pre-functional data, the drivers of challenges we face today in laboratory design. Companies are combatting these pressures by what is now being termed as the industrialization of R&D. The universe is not limited by gravity; it is driven by it. And so for the life science industry, if it isn’t all about the money, it is mostly about the money. On the operational side of R&D, firms are leaning more on technology, standardization and collaboration. The following summarizes the largest components making up these operational priorities.


In clinical processing laboratories throughout our healthcare system, we are seeing the complete re-design of laboratories to allow for expandable automation systems to process and analyze patient samples. The more patients, the more samples; the more samples, the more risk for mistakes; the more risks for mistakes, the more emphasis on verifiable repetitive procedures—hence the marriage of risk adverse hospital administrators and automation. 

Automation is completely changing how we plan what used to be technician workspace. We will find that repetitive tasks for centrifuging, pipetting, plating, incubation, sample analysis and other functions will now be strung along a conveyor line and will have a mixture of hand and automated manipulation stations. Effects will be felt by reducing staff counts and adjusting staffs of system managers. 


With the increase in the amount of data being produced by automated systems and genomic research, another area of repetitive task simplification is the growing reliance on cognitive automation for data analysis, pattern and anomaly identification and data processing. 

The prospect of increases in staff for the data analysis required by this surge in information is being offset by the use of artificial intelligence (AI). Interpretation is still in the realm of human necessity, but some of the more tedious tasks are being delegated to AI systems. 


Real World Evidence is another term for global collaboration across multiple fields of study. With the surge in quantified science and analysis extracted from automation, AI and the information developed from animal and human studies throughout the globe, there is the potential to assist in identifying where the best values exist to expend the most needed efforts. 

Online framework development for digital sharing of global health and science information is a growing endeavor. These frameworks can assist in the research being done so we can reduce redundancy and utilize validated information to focus efforts on those areas left uncovered, undiscovered and untested. 


In the mass production of proven products identified through research, there is a growing use of single-use technologies that assist in the change out of different product production areas. As a result, manufacturers can essentially use a single space to produce multiple product batches by quick change-out procedures using single-use technologies and techniques. This allows them to utilize space more efficiently. 

By reducing the use of permanent equipment and infrastructure installations and using plastic bag and tubing runs in movable tank containers, manufacturers can set up for specific batch runs and reset the production areas for the next product run. This reduces capital costs and allows for a scheduled run of product that aligns with accurate, “just-in-time” product demands. 

The efficiency effects of this technology could be tracked to everything from incoming ingredient supplies to outgoing product packaging, storage and warehousing. 


One of the major costs in production facilities in addition to the infrastructure utilized in the manufacturing process addressed by single use technology is the advancement of closed process system technology. These advancements house critical product isolation and clean environments within the equipment itself. This relieves the cost and the need to produce large critical environment rooms that house pre-production, production and post-production activities. 

By isolating the environment within the specific production equipment, you reduce the need for full room classification because the product never touched the room environment. To paraphrase a renowned mentor in the industry, it is like controlling the environment inside a quart of milk so it does not need to be placed in a refrigerator. 

These are just five components of the current science industry that are changing the needs for science facility design. It is all pre-functional information that generates different metrics for facility programming and planning. 

We need to watch these trends that affect the needs of the facilities we plan today. If you were to say today that the current staff counts and space we currently use to research, develop and produce products for the future will be cut by 30 percent but be expected to produce 30 percent more results, you would think one to be mad. 

Let’s see in 10 years where we are. 

As the Science & Technology Practice Leader for RS&H, Michael P. Vascellaro, AIA, NCARB, is responsible for the vision, thought leadership, and business development of facility design services related to the science industry. His 30-year background as a specialty architect includes experience in programming, planning, and design of science and technology applications within research, education, and production environments.