Operator-derived particles and falling bacteria in biosafety cabinets

Abstract

IntroductionTo ensure the sterility of cell products that cannot undergo conventional sterilization processes, it is imperative to establish and maintain a clean room environment, regulated through environmental monitoring, including particle counts. Nevertheless, the impact of particles generated by operators as potential contaminants remains uncertain. Thus, in this study, we conducted an accelerated test to assess the correlation between particles generated by operators and airborne bacteria, utilizing biosafety cabinets within a typical laboratory setting. These biosafety cabinets create a controlled environment with air conditioning and high-efficiency particulate air (HEPA) filters, offering fundamental data relevant to cell production. Materials and methodsWe conducted a simulation followed by real-time experiments involving human operations to explore the quantity of particles, particle sizes, and the percentage of bacteria within these particles. This investigation focused on conditions with heightened particle generation from operators within a biosafety cabinet. The experiment was conducted on operators wearing textile and non-woven dustless clothing within biosafety cabinets. It entailed tapping the upper arms for a duration of 2 min. ResultsObservations under biosafety cabinet-off conditions revealed the presence of various particles and falling bacteria in textile clothing. In contrast, no particles or falling bacteria were detected in operators wearing dustless clothing within biosafety cabinets. Notably, a correlation between 5 μm particles and colony-forming units in textile clothing was identified through this analysis. The ratio of falling bacteria to the total number of particles within the biosafety cabinet was 0.8 ± 0.5 % for textile clothing, while it was significantly lower at 0.04 ± 0.2 % for dustless clothing. ConclusionThis study demonstrated that the number of particles and falling bacteria varied depending on the type of clothing and that quantitative data could be used to identify risks and provide basic data for operator education and evidence-based control methods in aseptic manufacturing areas. Although, this study aims to serve as an accelerated test operating under worst-case conditions, the results need to make sure the study range in general research.