By Allan Marinelli, Quality Validation 360 Inc.
Due to globalization, restructuring of organizations, and the emergence of fast-paced technologies, companies need efficient and effective methods for validation, especially when establishing a defendable environmental sampling plan (the performance qualification [PQ] phase). This is especially true because there is a higher probability for regulatory agencies to scrutinize the documentation process during inspection when companies attempt to obtain licensure of their facility for the manufacturing of their products.1
As far as establishing a defendable environmental monitoring (EM) sampling plan within the PQ phase, six phases can be proposed to increase the likelihood of success during inspection for licensure of the facility. However, the extent of assimilating the suggested information is commensurate with the risk of the manufacturing process applications controlled under the relevant regulatory agencies and intended uses. I have provided a generic example of the elements suggested to attain successful inspection, but some companies may need less planning while others may need more.
The previous two EM articles — “3 Prerequisites To Establishing An Environmental Monitoring Sampling Plan” and “Sampling Preparation & Execution Best Practices For Environmental Monitoring” — covered phases1 through 3. This article will focus on the remaining phases (4 to 6).
Figure 1: The six phases of an environmental monitoring sampling plan
After taking the samples from the specified locations and transporting them to the laboratory, the following steps are recommended:
1. Prepare the samples for incubation by scanning the labels on them provided the company has scanning capabilities or simply incubate.
a. Set the samples for incubation.
i. At the end of each day, verify that the collected microbe samples were sent for incubation in accordance with the EM program or validation EM plan.
ii. The incubator should be set in the stabilization temperature range of 30 to 35 degrees Celsius. Per manufacturers’ recommendations, some Agar plates (typically 9 cm and 14 cm) must be incubated upside-down while other Agar plates (typically 5.5 cm) are to be incubated in the normal orientation (lid facing upward).
2. Prior to the next sampling session, clean and sanitize the instruments, including the sampling trolley.
3. Analyze the samples in accordance with the company’s standard operating procedures and ensure the acceptance criteria is met. See Table 1 for test conducted versus acceptance criteria requirement based on room area classification with respect to the drawings in Part 2 of this article series.
Table 1: Example of PQ Environmental Monitoring Guidelines2
Phase 5: Sampling Analysis
In this phase, you need to establish appropriate alert limits for microorganisms and nonviable particles relative to classified and controlled areas in manufacturing. These limits are determined using historical data, which is typically taken by combining baseline geometric/four corners of the room data points and predictive personnel/material flow direction within the rooms as a function of room classifications. The limits should be re-evaluated regularly and coupled with previous validations, so a routine EM program can be subsequently implemented post-validation.
EM data is not normally distributed, but the data profile represents a skewed distribution, with many zeros and low or high values. Sample points within a classification area may be treated as individual groups or grouped by functionality and criticality (e.g., floor, airlocks, and other sample points).
The following sequences is suggested:
1. Establish alert and action limits.
When calculating 95 percent quantiles, either the empirical or parametrical method can be used to establish the calculation of limits for classified areas.
Various approaches can be used to calculate the 95th percentile on a data set:
However, in the pharmaceutical and biopharmaceutical industries, typically upon historical analysis of observed data/received, the data falls within a logarithmic normal distribution fitted to data scenario.
For grades A and B, the empirical method is recommended, whereas for grades C and D the parametrical method is recommended. Using a parametric method, 95 percent quantiles are obtained from a distribution (logarithmic normal — a continuous probability distribution of random variable whose logarithm is normally distributed3 — distribution fitted to data, which represents data) that requires a small amount of data set, typically at least 20 observations. In contrast, the empirical method would require at least 50 percent of the observations that result in being typically zero.
The process of deciphering the alert and action limits is indicated below as a reference:
2. EM Data Trending Analysis
Various trending parameters can be factored in as identified in Table 2. But it is not an exhaustive or restrictive list, as this is dependent on the company’s user requirement specifications, standard operating procedures, and/or validation outcome:
Table 2: Example of a Monitoring Trending Analysis Table
The process in this section entails the following suggestions:
Phase 6: Sampling Conclusion
In this phase, write an EM report using the company’s report template that encompasses all results in either tabular method (tables, Excel spreadsheets) or other relevant methods (graphical, pictorial figures, flowcharts) while factoring in all encountered excursions or deviations and how the resolutions were derived toward closure or completion of the EM validation project.
Note: A version of this article will appear in an upcoming revision of the book Environmental Monitoring: A Comprehensive Handbook, to be published by the PDA/DHI (Parenteral Drug Association/Davis Healthcare International).
About The Author:
Allan Marinelli acquired over 25 years of worldwide cGMP experience in Belgium, France, South Korea, China, India, Canada, and the U.S. under the FDA, EMA, SFDA, KFDA, WHO, and other regulators. He is currently the president/CEO of Quality Validation 360 Inc., providing consultation services to the (bio)pharmaceutical, medical device, vaccine, and food/beverage industries. Marinelli has authored peer-reviewed papers (Institute of Validation Technology) and chapters on validation, risk analysis, and environmental monitoring in PDA/DHI books, and chapters on cleaning validation in PDA/DHI books. In addition, Marinelli published peer-reviewed articles on Pharmaceutical Online, Bioprocess Online, and Outsourced Pharma in 2016, 2017, and 2018. He is an associate member of ASQ (American Society for Quality) and published an article in ASQ titled “Against the Grain, Standing your ground when senior majority rules” in Quality Digest (Aug. 2014). You can contact him at firstname.lastname@example.org