Quality risk management for microbial control in membrane-based water for injection production using fuzzy-failure mode and effects analysis.

IF 3.5 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE PeerJ Computer Science Pub Date : 2024-12-23 eCollection Date: 2024-01-01 DOI:10.7717/peerj-cs.2565

Luoyin Zhu, Yi Liang

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Abstract

Microbial proliferation presents a significant challenge in membrane-based water for injection (WFI) production, particularly in systems with storage and ambient distribution, commonly refered to as cold WFI production. A comprehensive microbial risk assessment of membrane-based WFI systems was performed by employing Fuzzy-Failure Mode and Effects Analysis (Fuzzy-FMEA) to evaluate the potential microbial risks. Failure modes were identified and prioritized based on the Risk Priority Number (RPN), with appropriate preventive measures recommended to control failure modes that could increase the microbial load and mitigate their impact. Key hazards were identified including fouling of ultrafiltration (UF) membranes, insufficient sealing of heat exchangers, leakage in reverse osmosis (RO) membranes, and ineffective vent filters unable to remove airborn microorganism. Based on Fuzzy-FMEA results, suggestions for optimization were proposed to improve microbial control in membrane-based WFI systems in the pharmaceutical industry.

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来源期刊

PeerJ Computer Science Computer Science-General Computer Science

CiteScore

6.10

自引率

5.30%

发文量

332

审稿时长

10 weeks

期刊介绍： PeerJ Computer Science is the new open access journal covering all subject areas in computer science, with the backing of a prestigious advisory board and more than 300 academic editors.