Analyzing design and planning trends in medical research laboratories and workplace environments: A benchmarking study

Abstract

Architects and planners typically rely on past experiences and exclusive methods to determine the allocation of space and planning costs. However, the actual space allocations and physical attributes of laboratory and workplace environments require further exploration, highlighting the need for more research. To address this knowledge gap, this study compared three medical research facilities' architectural, casework, and module properties to identify essential space allocations, physical attributes, and future research directions. The study utilized REVIT models to collect floor plans of three medical research facilities within the last twelve years, with variables of interest including room classification size, Building Gross Footage (BGSF), Departmental Gross Footage (DGSF), laboratory module size, and module quantity per laboratory. Space Syntax analysis was used to compare connectivity measures across the three buildings. The findings demonstrated a trend towards laboratory spaces that maximize collaboration, flexibility, and efficiency while balancing open and private workspaces. Laboratory support spaces per laboratory room increased, potentially due to a demand for greater flexibility and spatial needs. Lab workstations were relocated outside laboratory areas to enhance safety and reduce costs. The analysis also revealed a shift towards smaller lab modules with larger widths to reduce redundancy, support safer distances, reduce travel distances, and increase the number of modules per lab. Furthermore, contemporary lab workspaces had higher connectivity values, indicating a trend towards more connected, collaborative spaces that encourage meetings and spontaneous interactions. This study highlights the importance of continuously evaluating and optimizing laboratory space allocation and design to promote productivity, efficiency, and collaboration in medical research facilities. Future research should conduct longitudinal studies using empirical data to address the limitations of current research.