1. Pathogen Reduction Dialogue Panel 3 Microbial Testing for Control Verification Robert L. Buchanan U.S. Food and Drug Administration Center for Food Safety and Applied Nutrition May 7, 2002

2. Microbiological Testing Microbiological testing important food safety tool Technologically- based, statistically-based tool Right tool for the right job

3. Microbiological Testing One of the most apparent, but poorly understood parts of food microbiology Different types of microbiological testing Safety of “batches” * Process control * Investigational sampling Surveillance

4. Microbiological Testing Effective use requires a clear understanding of the goals, assumptions, and characteristics of testing programs

5. Microbiological Testing “Within batch testing” vs. “Between batch testing” Different goals, assumptions, and techniques

6. Microbiological Testing “Within Batch Testing”: Demonstrate the safety of a single lot of food

7. Microbiological Testing Within-batch testing detailed “snapshot” of an operation assumes no prior knowledge of the process focus on establishing safety (or quality) of the batch provides only limited capability to do trend analysis of performance over time can be used nationally to acquire “state of industry”

8. Microbiological Testing Effective within certain ranges of contamination frequency or levels of contamination Above or below those ranges, becomes increasingly ineffective When acceptable defect rate is less than 1%, the number of samples needed becomes a limiting factor

9. Microbiological Testing “Between Batch Testing”: Demonstrate that a food safety system/process is continuing to function as intended

10. Microbiological Testing “Between-batch testing” not designed to assure batch safety which is assumed to be safe if validated process is “in control” assumes intimate knowledge of process requires prior analysis for performance and variation requires sampling over time can also be used nationally to assess “state of industry”

11. Microbiological Testing “Between-batch testing” Much easier to demonstrate that a process is not functioning within a specification than to prove that something (e.g., a pathogen) is not present

12. Sampling for Process Verification Microbiological contamination typically flows with a process A microbiological sample taken within a process provides a measure that integrates all the preceding steps in a process

13. Sampling for Process Verification The status of a multiple step process is the summation the initial level of contamination and all the steps that increase or decrease the level of contamination Microbial Status = Ho +  I +  R

14. Sampling for Process Verification Sampling of end products integrates the effects of the entire food safety system For investigations of cause, benefits to taking samples at multiple locations

15. Process Control Statistics The basis for process control evaluations is the collection of microbiological data over time Typically arrayed graphically as a control chart

16. Process Control Statistics First step is to conduct a process control study (baseline study) An “under control” process is run for a period of time to access its “capabilities” and establish: Central tendency (mean or median performance) Variance Also used to establish limits (control values) Often use 3 

17. Process Control Statistics Loss of process control is then assessed by determining if “defect rate” has become greater than what would be expected by “chance alone” Approach can be used with either “variables” (quantitative data) or “attribute” (+/- or binned quantitative data) sampling plans

18. Example: Moving Window Sum One of simplest for attribute sampling plans + - + - - - - + - - - - - + - -

19. Moving Window Sum Example: Making red marbles Receive Blue Marbles Paint Marbles Red* Package Marbles *Defect rate = 10%

20. Moving Window Sum Based on the probability of finding more than an expected number of “defective” responses within a specified window of samples

21. Moving Window Sum Is this process under control? (Sampling rate = 1 per 1000)

22. Moving Window Sum When is control of this process lost? (Sampling rate = 1 per 1000)

23. Impact of Stringency

24. Juice HACCP

25. Key feature: 5-D (99.999%) performance standard Restricted to juice after it has been expressed Verification of this requirement is via process validation and review of process records Goal: Limit risk to >10 -5 /year

26. Juice HACCP Microbiological testing not required based on ineffectiveness of testing at low defect rates treatment affects all juice processes are validated and reliable

27. Microbiological Testing Simplified example Assume 1 enteric bacteria per ml 5-D treatment reduces to 1 per 10,000 mL To detect survivor, need 1 10-L sample 10 1-L samples 100 100-mL samples 1000 10-mL samples 10,000 1-mL samples

28. Juice HACCP Key exemption: Citrus Juices Processors of citrus juices may count surface treatments of the fruit as partially or totally fulfilling 5-D treatment Based on the underlying assumption that the nature of citrus fruit is such that contamination is restricted to the fruit’s surface

29. Juice HACCP These citrus juice processors have an additional HACCP verification requirement of periodic testing for E. coli Two 10-ml juice samples/1000 gal/day Once per week if produce <1000 gal

30. Juice HACCP Data evaluated using process control statistics using a 7-sample window One positive sample requires process review Two positive samples require diversion to 5-D after extraction until cause identified

31. Juice HACCP Designed to verify that the original assumption is still valid, i.e. pathogens are restricted to the surface of the fruit Internalized pathogens will not be treated Potential for growth at least in some fruit Within range for effective detection Requirement takes into account potential for chance contamination

32. Microbiological Testing Microbiological testing can be an integral part of any integrated program for verifying the effectiveness of food safety control measures