Evaluation of Microbiological Cleanliness of Machines/Equipment through Rinse Technique Using Statistical Process Control

Abstract

To guarantee that patients receive safe therapy with predictable and acceptable medicinal properties, monitoring the quality standards in the healthcare sector and the pharmaceutical business, in particular, is essential. Medicinal products are no exception from these crucial characteristics and hence mitigation of the sources of microbial contamination is a mandatory strategy to avoid harming already-ill populations. Machines, equipment and tools that are used in the industry must be appropriately cleaned to ensure that they will not contaminate the product under processing. The study herein aimed to establish an evaluation system for cleaning efficiency through the rinse technique using Statistical Process Control (SPC) methodologies. A database was established and created for the recorded cleaning process over 20 months of the monitoring period. The control charts were constructed and evaluated from processed data using SPC software. A rare event control chart was used to track the cleaning process intervals with event probability estimated to be 0.080. Concerning the monitoring of the bioburden of rinse samples, the most appropriate fitting attribute chart is U type with Laney modification of over-dispersion to correct for tight control limits that increase alarming false points. Understanding the inspection property is inevitable for the right interpretation of trends.

Keywords

• Laney correction
• U chart
• over-dispersion
• control limits
• SPC
• event probability

References

1. Eissa ME (2018). Microbiological quality of purified water assessment using two different trending approaches: A case study. SJSR 1(3):75-9.
2. Eissa ME, Rashed ER, Eissa DE (2021). Implementation of Modified Q-Control Chart in Monitoring of Inspection Characteristics with Finite Quantification Sensitivity Limits: A Case Study of Bioburden Enumeration in Capsule Shell. El-Cezeri 8(3): 1093-107.
3. Eissa M, Rashed ER, Eissa DE (2022). Principal component analysis in long term assessment of total viable plate count of municipal water distribution network system in healthcare facility. Environ Sci Technol 5(2): 165 - 171.
4. JMP Statistical Discovery (2022). Control Charts, https://www.jmp.com/support/help/zh/15.2/index.shtml#page/jmp/control-charts.shtml Accessed 19.10.2022
5. Kanji GK, Malek A, Tambi BA (1999). Total quality management in UK higher education institutions. TQM 10(1): 129-53.
6. Laney DB (2002). Improved control charts for attributes. Qual. Eng. 14(4):531-7.
7. Marucheck A, Greis N, Mena C, Cai L (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. JOM 29(7-8): 707-20.
8. Mehra S, Ranganathan S (2008). Implementing total quality management with a focus on enhancing customer satisfaction. Int J Qual Reliab 25(9): 913-927.

9. Minitab® 20 Support (2022). Interpret the key results for Laney U' Chart, https://support.minitab.com/en-us/minitab/20/help-and-how-to/quality-and-process-improvement/control-charts/how-to/attributes-charts/laney-u-chart/interpret-the-results/key-results/ Accessed 17.10.2022.
10. MINITAB STATISTICAL SOFTWARE (2022). The Assistant, https://www.minitab.com/en-us/products/minitab/assistant/ Accessed 13.10.2022.
11. Moharram AM, Ismail MA, Shoreit AM, Hassan MH (2014). Biodiversity of microbiota in cephalosporin-manufacturing environments at T3A factory, Assiut, Egypt. JBAM 5:1-3.
12. Park C, Wang M (2022). A study on the g and h control charts. Commun Stat Theory Methods 19:1-6.
13. Pharma Focus Asia (FPA): Knowledge Bank: Pharam Articles (2022). Pharmaceutical Component Kinetics: Inventory dynamic control is crucial, https://www.pharmafocusasia.com/articles/pharmaceutical-component-kinetics-inventory-dynamic-control-is-crucial Accessed 15.10.2022
14. Rinaman WC (2018). Minitab. In Revival: The Handbook of Software for Engineers and Scientists p. 1028-1046. CRC Press USA.
15. Roesti D (2019). Calculating Alert Levels and Trending of Microbiological Data. In Roesti D and Goverde M (eds). Pharmaceutical Microbiological Quality Assurance and Control: Practical Guide for Non‐Sterile Manufacturing p.329-69. John Wiley & Sons, Inc USA.
16. Ryan BF, Joiner BL, Cryer JD (2013). MINITAB handbook: update for release. Cengage Learning USA.
17. Schmitt R, Moerman F (2016). Validating cleaning systems. In Lelieveld H, Holah J, Gabrić D (eds). Handbook of Hygiene Control in the Food Industry p.587-601. Woodhead Publishing UK.
18. Steyaert D (2021). Cleaning validation of biologicals: Determination of a worst-case product for RTH 258 Ghent University Belgium.
19. Walters A (2008). A performance evaluation of the lifestraw: a personal point of use water purifier for the developing world (Doctoral dissertation, The University of North Carolina at Chapel Hill).
20. Vargas DA, Rodríguez KM, Betancourt-Barszcz GK, Ajcet-Reyes MI, Dogan OB, Randazzo E, Sánchez-Plata MX, Brashears MM, Miller MF (2022). Bio-Mapping of Microbial Indicators to Establish Statistical Process Control Parameters in a Commercial Beef Processing Facility. Foods 11(8):1133.
21. Zakuan N, Muniandy S, Saman MZ, Ariff MS, Sulaiman S, Abd Jalil R (2012). Critical success factors of total quality management implementation in higher education institution: a review. Int J Acad Res 2(12): 19.