Some aspects on the sampling efficiency of microbial impaction air samplers.
Francesco Romano, Jan Gustén, Cesare M. Joppolo Bengt Ljungqvist, Berit Reinmüller.2015
The intent of this article was to assess the sampling efficiency of microbial impaction air samplers and to evaluate the influence of external factors on these measurements.
Air sampling is the process of analysing and detecting varieties and quantities of contaminants in a particular environment. Accurate, reliable and efficient air monitoring is of critical importance for ensuring product quality and human health. Air monitoring requires a specific type of aerosol measurement which monitors the viable airborne particles ranging in size from 0.001 to 100 ?m (1). These viable airborne particles are collected using an air sampler fitted with an appropriate culture media such as Tryptone soya agar which acts as a nutrient source for a wide range of aerobic micro-organisms. This media is incubated for a defined time period and at a defined temperature. Resultant colonies are enumerated and identified to species level. Results are expressed as colony forming units per cubic meter of air sampled expressed (CFU/m3).
Even though air samplers rely on the same basic technology the results from different air samplers are not comparable. Therefore the sampling performance must depend on other external factors such as microbial load, environmental conditions, bioaersol source and specific instrument features (1, 8, and 11). The absence of an industry accepted standard procedure for sampling air monitors is also an influential factor. Considering all these facts it is essential to choose an appropriate air sampler and of equal importance is how to interpret its results.
Ljungqvist & Reinmuller demonstrated that air samples were not equivalent with a tenfold difference in CFU’s between some samplers (6). Air classifications for sterile products by the FDA, WHO and EUGGMP (3, 10 ; 2) state a specified microbiological limit of ; 1 CFU/m3 which translates as zero colonies detected per m3. Consequently with air samplers not being comparable it is possible to have different microbial concentrations from different air samplers that have sampled the same environment (4, 11). Thus an OOS environment may appear in specification.
Over the years it has become apparent that the behaviour of airborne particles is determined by characteristics such as their size, shape and density. The aerodynamic flow around the particle depends on particle size which is measured in terms of the particles aerodynamic diameter. The most commonly used metrics when defining particle size distributions are D values. D-value can be thought of as a “mass division diameter”. It is the diameter which, when all particles in a sample are arranged in order of ascending mass the D value divides the sample’s mass into specified percentages. The percentage mass less than the diameter of interest is the number expressed after the “D”. The D50 is the diameter of the particle that 50% of a sample’s mass is smaller than and 50% of a sample’s mass is larger than. The D50 is also known as the “mass median diameter” as it divides the sample equally by mass (5).
This study aimed to assess the performance of four different microbial air samplers when exposed to different microbial bioburdens generated by human activity. The microbial bioburden will be greatly influenced by cleanroom garments and the behaviour of the operator. In addition, different quality clothing systems reduce air contamination generated by humans to different extents (7, 9). A controlled experiment was set up in a cleanroom environment where three types of cleanroom garments were chosen deemed to be of low, medium and high contamination levels and the operator was instructed to walk in front of the air monitor for a time period of ten minutes. The experiment was repeated in triplicate using a standard operating procedure. The results clearly demonstrated that the quality of clothing had a major effect on contamination levels. A direct correlation between the highest quality cleanroom garment with the lowest level of microbial bioburden of CFU’s/m3 was established.
It was also observed under identical environmental conditions two air samplers with varying D50 values displayed a distinct difference in the accuracy of the result. The sampler with the lower D50 value more accurately monitored variations in microbial concentration. In addition the efficiency of the air sampler to detect small particles is important. It was ascertained that more than half of the viable particles were smaller than 3.64 ?m. This indicates high efficiency samplers with low D50 values should be employed for air monitoring in cleanrooms.
I strongly agree with the outcome of this study which confirms that humans and the quality of cleanroom garments have a major influence on particle counts in the cleanroom environment as people are a huge source of contamination in fact the biggest source of viable and non –viable contamination, this was collaborated by Hu S and A.Shiue study relating to the validation and application of personnel and garments used in cleanrooms (13). Their studies proved that human movement and the aging of cleanroom garments contributed to an increase in microbial load. Each adult loses about 6-14 grams of dead skin material every day. Each person loses a complete layer of skin about every four days equivalent to 10,000,000 particles per day. Ordinary walking movements emit about 10,000 particles per minute. Hence this article proved if the cleanroom garment is of low grade fabric these particles will be more readily released to the air and act as carriers for microorganisms.
In the Pharmaceutical industry and especially in sterile manufacture it is imperative that Quality know if any airborne contaminants put products at risk. It is also important to understand what the contaminants are, and their origin. Critical environmental measurements, like airborne particle measurements, assist with keeping processes in control and with helping to find the root cause of unwanted events. Air samplers are an important tool in the armoury of the microbiologist to monitor cleanrooms for particles and other potential contaminants. Successful air monitoring requires awareness, understanding, and action. Awareness of what the data is saying what counts are present and where and what organisms are present are where. What’s measured must be managed. Knowledge without action is useless. Air monitoring results ultimately need to drive you to take actions if required. Therefore the theory which this article proves that though air samplers rely on the same basic technology the results from different air samplers are not comparable.
It clearly demonstrates the physical parameters of the air monitor such as the d50 as well as the concentration of microorganisms and environmental conditions have a major bearing on the results obtained. This article has led to a better understanding of air sampler performance and the importance of impaction theory.
In summation this study confirms the importance of a standard methodology for microbial air monitoring and that understanding the importance of the dynamics of air sampling in relation to collection of particles is paramount. Results between different air samplers are not equivalent and therefore an air sampler should be assessed and selected on sampling requirements, sampling conditions and the characteristics of the air sampler. The study revealed the microbial load is influenced by operator garments and behavior. The utilization of high quality cleanroom clothing can reduce microbial bioburden. Results also indicated that D50 value of a sampler can aid in predicting its performance and assist in interpreting results.
Air Monitoring programs are integral components of a process to monitor microbial levels in a cleanroom and to ensure the safety, efficacy and quality of bio-susceptible products. Air monitoring can detect changes in the contamination recovery rate that may be indicative of changes in the state-of control within the environment. This is to provide confidence that routine air monitoring will mitigate against microbial proliferation and product contamination. This article contributed to a better understanding of air sampler technology and the external factors that contribute to the microbial bioburden in a sterile cleanroom environment.
Baron, P. A., & Willeke, K. (2001). Aerosol measurement, principles, techniques, and applications (2nd ed.). New York: John Wiley & Sons.
EudraLex. The Rules Governing Medicinal Products in the European Union
Volume 4 EU Guidelines to Good Manufacturing Practice Medicinal Products for Human and Veterinary Use Annex 1 Manufacture of Sterile Medicinal Products: EUGGMP 2008 Recommended Limits for Microbial Contamination.
FDA. Sterile Drug Products, Current Good Manufacturing Practice, Air Classifications by USFDA guideline on Sterile Drug Products
Frankel, M., Timm, M., Hansen, E. W., & Madsen, A. M. (2012). Comparison of samp-ling methods for the assessment of indoor microbial exposure. Indoor Air, 22,405–414. InternationalOrganization for Standardization
ISO 13317-1-2001 Determination of particle size distribution by gravitational liquid sedimentation methods – Part 1: General principles and guidelines).
Ljungqvist, B., & Reinmüller, B. (1998). Active sampling of airborne viable particles in controlled environments: A comparative study of common instruments. European Journal of Parenteral Sciences, 3, 59–62.
.Ljungqvist, B., Reinmüller, B., & Tammelin, A. (2012). Comparison between two measuring methods with active air sampling of airborne viable particles. European Journal of Parenteral Sciences, 17, 56–59.
Seinfeld, J. H. (1986). Atmospheric chemistry and physics of air pollution. New York: John Wiley & Sons.
Tammelin, A., Ljungqvist, B., & Reinmüller, B. (2013). Single use of surgical clothing system for reduction of airborne bacteria in the operating room. Journal of Hospital Infection, 84, 245–247.
WHO 2002: Air Classifications as per WHO 2002
Willke, K. (1976). Temperature dependence of particle slip in a gaseous medium. Journal of Aerosol Science, 7, 381–387.
Zhen, S., Li, K., Yin, L., Yao, M., Zhang, H., Chen, L., et al. (2009). A comparison of the efficiencies of a portable BioStage impactor and Reuter centrifugal sampler (RCS) high flow for measuring airborne bacteria and fungi concentrations. Journal of Aerosol Science, 40, 503–513.
Hu S, Shiue A. Validation and application of the personnel factor for the garment used in cleanrooms. Building and Environment. 2016; 97:88-95.