Sterilization of Products Contaminated with Pyronema domesticum

2009 ◽  
Vol 43 (6) ◽  
pp. 489-497
Author(s):  
Carol M. Lampe ◽  
Joyce M. Hansen ◽  
Therese M. Rymer ◽  
Harold Sargent
Keyword(s):  
Health Care ◽  
Ethylene Oxide ◽  
High Resistance ◽  
Product Recalls ◽  
Determination Method ◽  
Dose Determination ◽  
Resistance Model ◽  
Cotton Product ◽  
Multiple References ◽  
Sterilization Dose

Abstract Product recalls due to non-sterility occurred between 1993 and 1994 among manufacturers that were sterilizing cotton products sourced from China using ethylene oxide (EO). The primary contaminant was identified as a pyrophilous mold from the class Discomycetes, Pyronema domesticum. Multiple references suggest this organism has special needs for reproducing and maintaining the two assumed resistant stages of this organism (ascospores and sclerotia). Sterilization resistance studies were performed using a China-sourced cotton product that was naturally contaminated with P. domesticum. These studies showed the organisms to have: 1) a low resistance to moist heat sterilization at 250°F (121°C); 2) a resistance to radiation no greater than that predicted by the bioburden-based resistance model (i.e., Population C) used for dose determination Method 1 described in ANSI/AAMI/ISO 11137-2:2006—Sterilization of health care products—Radiation—Part 2: Establishing the sterilization dose; and 3) a high resistance to EO processing.

scholarly journals Decontamination of N95 masks for re-use employing 7 widely available sterilization methods

PLoS ONE ◽  
2020 ◽  
Vol 15 (12) ◽  
pp. e0243965 ◽  
Author(s):  
Anand Kumar ◽  
Samantha B. Kasloff ◽  
Anders Leung ◽  
Todd Cutts ◽  
James E. Strong ◽  
...  
Keyword(s):  
Health Care ◽  
Hydrogen Peroxide ◽  
Ethylene Oxide ◽  
Woven Fabric ◽  
Treatment Modalities ◽  
Moist Heat ◽  
Gas Plasma ◽  
Fit Testing ◽  
Ultraviolet C ◽  
Hospital Wards

The response to the COVID-19 epidemic is generating severe shortages of personal protective equipment around the world. In particular, the supply of N95 respirator masks has become severely depleted, with supplies having to be rationed and health care workers having to use masks for prolonged periods in many countries. We sought to test the ability of 7 different decontamination methods: autoclave treatment, ethylene oxide gassing (ETO), low temperature hydrogen peroxide gas plasma (LT-HPGP) treatment, vaporous hydrogen peroxide (VHP) exposure, peracetic acid dry fogging (PAF), ultraviolet C irradiation (UVCI) and moist heat (MH) treatment to decontaminate a variety of different N95 masks following experimental contamination with SARS-CoV-2 or vesicular stomatitis virus as a surrogate. In addition, we sought to determine whether masks would tolerate repeated cycles of decontamination while maintaining structural and functional integrity. All methods except for UVCI were effective in total elimination of viable virus from treated masks. We found that all respirator masks tolerated at least one cycle of all treatment modalities without structural or functional deterioration as assessed by fit testing; filtration efficiency testing results were mostly similar except that a single cycle of LT-HPGP was associated with failures in 3 of 6 masks assessed. VHP, PAF, UVCI, and MH were associated with preserved mask integrity to a minimum of 10 cycles by both fit and filtration testing. A similar result was shown with ethylene oxide gassing to the maximum 3 cycles tested. Pleated, layered non-woven fabric N95 masks retained integrity in fit testing for at least 10 cycles of autoclaving but the molded N95 masks failed after 1 cycle; filtration testing however was intact to 5 cycles for all masks. The successful application of autoclaving for layered, pleated masks may be of particular use to institutions globally due to the virtually universal accessibility of autoclaves in health care settings. Given the ability to modify widely available heating cabinets on hospital wards in well-resourced settings, the application of moist heat may allow local processing of N95 masks.

scholarly journals Minimization of Drug Shortages in Pharmaceutical Supply Chains: A Simulation-Based Analysis of Drug Recall Patterns and Inventory Policies

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Rana Azghandi ◽  
Jacqueline Griffin ◽  
Mohammad S. Jalali
Keyword(s):  
Health Care ◽  
Supply Chains ◽  
Performance Measures ◽  
The United States ◽  
Product Recalls ◽  
Inventory Policies ◽  
Inventory Policy ◽  
Drug Shortages ◽  
Pharmaceutical Supply Chains ◽  
Health Care Centers

The drug shortage crisis in the last decade not only increased health care costs but also jeopardized patients’ health across the United States. Ensuring that any drug is available to patients at health care centers is a problem that official health care administrators and other stakeholders of supply chains continue to face. Furthermore, managing pharmaceutical supply chains is very complex, as inevitable disruptions occur in these supply chains (exogenous factors), which are then followed by decisions members make after such disruptions (internal factors). Disruptions may occur due to increased demand, a product recall, or a manufacturer disruption, among which product recalls—which happens frequently in pharmaceutical supply chains—are least studied. We employ a mathematical simulation model to examine the effects of product recalls considering different disruption profiles, e.g., the propagation in time and space, and the interactions of decision makers on drug shortages to ascertain how these shortages can be mitigated by changing inventory policy decisions. We also measure the effects of different policy approaches on supply chain disruptions, using two performance measures: inventory levels and shortages of products at health care centers. We then analyze the results using an approach similar to data envelopment analysis to characterize the efficient frontier (best inventory policies) for varying cost ratios of the two performance measures as they correspond to the different disruption patterns. This analysis provides insights into the consequences of choosing an inappropriate inventory policy when disruptions take place.

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