c. Proposed SEC 507.45(a)(2)--Validation based on scientific and technical information. Proposed SEC 507.45(a)(2) would require that, except as provided by paragraph (a)(3) of this section, the validation of preventive controls include collecting and evaluating scientific and technical information or, when such information is not available or is insufficient, conducting studies to determine whether the preventive controls, when properly implemented, will effectively control the hazards that are reasonably likely to occur.
The scientific and technical information that would be evaluated to determine whether preventive controls effectively control the hazards that are reasonably likely to occur may include scientific publications, government documents, predictive mathematical models and other risk-based models, and technical information from equipment manufacturers, trade associations, and other sources. If the qualified individual conducting the validation relies on sources such as scientific publications, the qualified individual would need to ensure during validation that the conditions used by the facility are consistent with those described in the publication that is being used to support the adequacy of the preventive control measure to control the hazard. For example, if a study demonstrates adequate inactivation of Salmonella spp. during the manufacturing of dry dog and cat food, conditions such as ingredient matrix, temperature, and heating time, that were critical to achieving inactivation in the study must be the same when the facility manufactures the dry dog and cat food (or any change in the critical parameters must be such that the same or greater lethality is achieved). Documents published by FDA, such as the Food Code (Ref. 76), the Pasteurized Milk Ordinance (Ref. 77), and the Fish and Fisheries Products Hazards and Controls Guidance (Ref. 78) may provide scientific and technical information useful in establishing the validity of a preventive control measure, such as times and temperatures for heating animal food in which bacterial pathogens may be eliminated, or minimum water activities (aw), minimum pH values, and minimum temperatures for the elimination of a variety of pathogens.
Predictive mathematical models that describe the growth, survival, or inactivation of microorganisms in foods may provide scientific and technical information useful in determining whether a process would be adequate to reduce microorganisms of public health concern (Refs. 79 and 80). Other risk-based models may examine the impact of a control measure on a hazard and may be useful if appropriately validated for a specific animal food. If the model is for a different food, it may still provide useful validation information that could be supplemented by additional data. For example, there are many mathematical models for thermal resistance of Salmonella spp. If a model for the thermal resistance of Salmonella spp. is developed for the same type of food as the animal food being produced, and the animal food being produced has the same critical parameters such as pH and aw that were used in developing the thermal resistance model, then heat processes based on the model would generally be considered validated. If the model is for thermal resistance of Salmonella spp. in a type of animal food that is only similar to the animal food being produced, or has different critical parameters than were used in developing the thermal resistance model, it would be necessary to conduct additional thermal resistance studies in the animal food being produced to provide the data needed to show that a heat process adequately reduces Salmonella spp. in that animal food and to establish the critical parameters for the process. For example, a model for thermal resistance of Salmonella spp. on meat and bone meal may not apply to poultry meal, even though the foods are similar in that both are animal by-products. The extent of such studies would, however, be less than the extent of such studies if there were no data on the heat resistance of Salmonella spp. in a similar animal food. For example, if the thermal resistance of Salmonella spp. in initial studies with canola meal is similar to that for soybean meal then a thermal resistance study used to develop data for canola meal could investigate fewer times and temperatures, or use fewer replicates, than would be the case in the absence of the information about the thermal resistance of Salmonella spp. in soybean meal.
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