-PDA Technical report n. 1. Validation of Moist Heat Sterilization Processes: Cycle design, –Development, Qualification and Ongoing Control.

-UNI EN 285. Sterilizzazione. Sterilizzatrici a vapore. Grandi Sterilizzatrici.

-UNI CEN ISO 17665-1. Sterilizzazione dei prodotti sanitari. Calore umido. Parte 1. Requisiti per lo sviluppo, la convalida, il controllo di routine di un processo di sterilizzazione per dispositivi medici.

-UNI CEN ISO 17665-2. Sterilizzazione dei prodotti sanitari. Calore umido. Parte 2. Guida alla applicazione della ISO 17665-1.

This book balances theoretical, and sometimes philosophical, discourses about the nature of sterility and the conceptual problems of microbial viability with sound practical guidance on how to validate the sterility test, problematic products as well as solutions on how to control the environment and review manufacturing process parameters, while navigating the regulatory minefield. PDA. 240 $.

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A person might say, “It doesn’t matter what type of biological indicator I place in my load, it will tell me if I reach my SAL (Sterility Assurance Level). If the BI is killed that means I achieved my target SAL and as long as that happens I am happy.” That argument will work great until you have a failure. Then what should be done? Time and time again, a customer will call and say “there is something wrong with your BI”. Once all the details are presented, more often than not it is either improper use of the BI or the wrong BI all together. The reason there are so many different types of BIs out there is because not every BI is appropriate for every situation. Proper selection of BIs for your process is of the utmost importance.

Another customer might state, “I can just cut this BI into smaller pieces or fold it a few times and it will work for my application”. You might think you can reconfigure a standard BI in a way that it will work but if you do that it will most definitely affect the performance of the BI. A biological indicator is a system composed of the inoculated substrate and the primary packaging. Modifying any of the components of that system will affect the performance of the BI. The two most likely characteristics that will be affected by modifying a BI are the population and resistance. This could mean that you are providing too little or too great of a challenge as to what was originally intended and you wouldn’t be adequately monitoring your process. If the modification affected the BI in a way that it reduced the challenge you could completely inactivate the BI and your processed load could potentially be unsterile. If the modification affected the BI in a way that increased the challenge it could result in positive growth of the BI even though the sterilization cycle conditions should have been adequate to sterilize your load and completely inactivate the BI.

By Robert Bradley, M.S.
Director of Laboratory Production
Omaha Manufacturing Facility
Mesa Laboratories, Inc.

 Spore News. MESA Lab. Custom Biological Indicators.

Abstract

Food of non-animal origin (FoNAO) is consumed in a variety of forms, and a major component of almost all meals. These food types have the potential to be associated with large outbreaks as seen in 2011 associated with VTEC O104. A comparison of the incidence of human cases linked to consumption of FoNAO and of food of animal origin (FoAO) was carried out to provide an indication of the proportionality between these two groups of foods. It was concluded that outbreak data reported as part of EU Zoonoses Monitoring is currently the only option for EU-wide comparative estimates. Using this data from 2007 to 2011, FoNAO were associated with 10% of the outbreaks, 26% of the cases, 35% of the hospitalisations and 46% of the deaths. If the data from the 2011VTEC O104 outbreak is excluded, FoNAO was associated with 10% of the outbreaks, 18% of cases, but only 8% of the hospitalisations and 5% of the deaths. From 2008 to 2011 there was an increase in the numbers of reported outbreaks, cases, hospitalisations and deaths associated with food of non-animal origin. In order to identify and rank specific food/pathogen combinations most often linked to human cases originating from FoNAO in the EU, a model was developed using seven criteria: strength of associations between food and pathogen based on the foodborne outbreak data from EU Zoonoses Monitoring (2007-11), incidence of illness, burden of disease, dose-response relationship, consumption, prevalence of contamination and pathogen growth potential during shelf life. Shortcomings in the approach using outbreak data were discussed. The top ranking food/pathogen combination was Salmonellaspp. and leafy greens eaten raw followed by (in equal rank) Salmonellaspp. and bulb and stem vegetables, Salmonellaspp. and tomatoes, Salmonellaspp. and melons, and pathogenic Escherichia coli and fresh pods, legumes or grain.

© European Food Safety Authority, 2013

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