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Defining and Presenting Overkill Cycle Validation
When sterilization validation comes up in an audit of a moist steam-sterilization autoclave, the quality assurance manager will be asked to explain how autoclave loads were validated. The conventional, easy answer is the term “overkill,” which is understood to mean that all items were steamed beyond all hope of anything surviving a grossly exaggerated load cycle--and that would be the end of it. This “overkill cycle” entails increasing the temperature or lengthening the time of the sterilization cycle with little understanding of what is occurring within the load items. All bioindicators (BIs) are inactivated at some undetermined but early point in the validation cycle, and temperature profiles are presented separately. In this approach to overkill sterilization cycle validation, no attempt is made at correlation of the biologic and physical data. Temperatures recorded by thermocouples are used to calculate the accumulated lethality at various load points. Bioindicators are placed beside each of these thermocouples to comply with well-established sterilization methods. In this scenario, BIs are considered as mere binary factors, either alive or dead. The data would be presented as just that: all BIs were inactivated.
A key component when presenting any autoclave validation package, however, is to be able to clearly defend how the requirement to correlate biologic and physical lethality data from the validation reports is satisfied (1). Fulfilling this requirement can provide sound justification for autoclave critical process parameters (CPPs) and how they were validated, no matter what type of production cycle is run.
The data demonstrated by the inactivation of the BIs have a numeric value, because the D-value (i.e., the decimal reduction time or time required to kill 90% of the BIs) and population are known through compendial testing. Because the F0 number (i.e., lethality level) represented by the physical data is derived by an equation of probable microbial death rates, actual kill must be demonstrated as well. Although less precise by nature than data generated by calibrated thermocouples, the BI data can be enumerated and are relevant when compared to the physical data to demonstrate a real versus theoretical kill. It is this one-two punch that makes the validation an assurance of the routine sterilization process.
An overkill cycle addresses the worst possible routine manufacturing conditions, which should be challenged by the validation load conditions (2). The validation represents a known, worst-case demonstration of a successful cycle; hence the most resistant organisms (e.g., Geobacillus stearothermophilus) with a high population count are placed in the most difficult locations for steam penetration within a given load.
An overkill production cycle may be an appropriate choice to satisfy the numerous and sometimes conflicting regulatory requirements for delivered leathality to assure sterilization by claiming a CPP for F0 of greater than a certain value, but the choice does not absolve a manufacturer from applying appropriate validation principles in demonstrating CPPs are met. If one of these methods of demonstration is biological data, these data should be relevant to the test being conducted.
For example, inactivating a BI with a D value of 1.5 and a population of 106 should take an F0 of 18 min. When the adjacent thermocouple accumulates 40 F0s, a margin of error greater than 100% has been built into the biological portion of the test. This is an example of a bad test, not of “overkill sterilization validation.” If, however, the BI has a D value of 36, the maximum allowable for a compendial indicator, then an Fphy of 40 would seem appropriate.
Justifying load parameters
It is crucial to determine appropriate cycle parameters. This author has repeatedly found autoclave cycles programed by the autoclave manufacturer and accepted by the plant owner without running development studies prior to operational and performance qualification. The program parameters were assumed to provide a predetermined sterility assurance level within all load items without any testing prior to the validation runs of an overkill cycle. It is necessary to compare theoretical F0s with the actual F0s delivered in an actual cycle. This real development testing will give a good idea of performance and capability of the autoclave and allow for realistic program-parameter settings.
It may be appropriate to add some time or temperature as a safety factor to account for all of the variables inherent to autoclaving items needed in a manufacturing process. Unknown incoming bioburden load is a reasonable driver to choose an overkill sterilization cycle. However, gross overage indicates a lack of control of the process and a lack of understanding of the appropriate lethality being delivered to load items. Delivered lethality should be well understood from development runs and applied judiciously, even in overkill cycles, in order for validation to be a credible assurance of process functionality.
Fractional cycles as a method of validating overkill cycles
By defining a fractional (i.e., partial) cycle time and temperature for validation loads based on an understanding of the autoclave capabilities in conjunction with particular load limitations, an excellent rationale can be made, and manufacturing cycles can be programed as overkill cycles. The overkill compensates for deviations in time or temperature caused by calibration faults in controlling thermocouples, chamber leaks, variability in packaging and assembling components, or other production events.
Any autoclave validation, for either overkill or product-specific load cycles, must demonstrate the delivered lethality to the most difficult locations using biological and physical data. More than being just a “dead or alive” reading, the BI does enumerate delivered lethality when assessed appropriately. By knowing the D value of the BIs used and setting the fractional validation cycle to accommodate this value, inactivation can be achieved in the BIs and correlated to the thermocouple readouts. This validated cycle can then be appropriately increased to account for minor process variations to support a robust, validated process. This validation method, firmly based in the accepted tenets of sterilization science and a rational scientific approach, will provide a sound basis for an autoclave sterilization program.
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