Charting and Evaluation of Environmental Microbial Monitoring Data

Abstract

Statistical tools are required to organize and present microbial environmental monitoring data for the purpose of evaluating it against regulatory action limits and of determining if the microbial monitoring process is in a state of control. This paper applies a known methodology of a simple and straightforward construction of control XmR (X data and moving range) charts of individual microbial counts as they are or of contamination rates derived from them, irrespective of the type of the parent data distribution and without the need to transform the data into a normal distribution. Plotting of monthly and cumulative sample contamination rates, as newly suggested by USP <1116>, is also shown. Both types of the control charts and plots allow an evaluation of the behavior of the microbial monitoring process. After addressing the magnitude of microbial counts expected in environmental monitoring samples, this paper presents the rationale behind the use of XmR charts. Employing data taken from environmental monitoring programs of pharmaceuticals manufacturing facilities, this paper analyzes examples of (1) microbial counts from passive or active air sampling in area Grade D or B or Class 100,000 in XmR charts, (2) contamination recovery rates as suggested by USP <1116> from active air samples in area Grade B and contact plates in area Grade C, and (3) instantaneous contamination rates with calculations illustrated on microbial counts of contact plates in area Grade D.

LAY ABSTRACT: Pharmaceutical companies conduct environmental monitoring programs, and samples of air (active and passive sampling) and of surfaces (contact plates) are routinely tested for microbiological quality. Thus, hundreds of microbial counts of tested environmental monitoring samples are routinely generated and recorded. Statistical tools are required to organize and present this abundant data for the purpose of evaluating it against regulatory action limits and determining if the microbial monitoring process is a state of control. This paper has a two-fold purpose. The first purpose is to provide microbiologists and quality assurance personnel simple and straightforward tools of statistical process control for evaluating the behavior of the microbial monitoring process: individual XmR (X data and moving range) control charts of microbial counts as they are or of rates derived from them are constructed irrespective of the type of the parent data distribution and without the need to transform the data into a normal distribution. Plotting of monthly and cumulative sample contamination rates, as newly suggested by USP <1116>, is also shown. The second purpose is to present examples of the charting of (1) microbial counts, (2) contamination recovery rates as suggested by USP <1116>, and (3) instantaneous contamination rates using data taken from environmental monitoring programs of pharmaceuticals manufacturing facilities.