Limitations of Risk Assessment Based on Non Fit-For Purpose/Invalidated Laboratory Methods

Transcription

1 Limitations of Risk Assessment Based on Non Fit-For Purpose/Invalidated Laboratory Methods Robert L. Buchanan Center for Food Safety and Security Systems College of Agriculture and Natural Resources University of Maryland

2 IOM Report on Food Safety A 2010 report responding to a Congressional request for a comprehensive review of the gaps in the ability of the U.S. FDA to ensure food safety A major thrust of the report was the approaches and infrastructure needed for FDA to become risk-based

3 IOM Report on Food Safety To become a risk-based system, FDA need systematic sources of Behavioral data Economic data Food production data Surveillance data The data should be acquired based on clearly defined data standards

4 Presentation Discuss where risk assessors get their data What can go wrong? What can happen if they get bad data? What can happen if they get incomplete information? How to fix the problem? Concluding remarks?

5 Where Do Risk Assessors Get Their Data???

6 Data for Risk Assessment It is generally well understood that quantitative risk assessments are data driven and work best when there are sufficient quantities of data available Need data: Hazard prevalence Dose-response relations Food intake Host status Food composition Hazard/food interactions Hazard/food/host interactions

7 Data for Risk Assessment What is less appreciated is that almost all data used in food safety risk assessments are derived for other purposes Data typically involves multiple studies and multiple investigators Data may cover decades of studies These data need to be normalized to take into account differences in methodologies, sampling techniques, and sensitivities

8 Sources of Risk Assessment Data Hazard Prevalence Data Research by academics Government surveys Industry quality assurance data Dose-Response Relationships Toxicology studies Infectious doses trials Vaccine trials Epidemiologic investigations

9 Sources of Risk Assessment Data Host Status Medical research Epidemiologic investigations Toxicological research Food Composition Food and nutrition research Industry QA data Government surveys

10 Sources of Risk Assessment Data Food Intake Nutrition databases (NHANES, CFSII, WWEIA, EFSA/ECFCD Food commodity economic data Food/Hazard Interactions Food toxicology research Hazard kinetics studies Predictive microbiology studies

11 Data Challenge In the absence of data specifically developed for a risk assessment, one must find effective means for maximizing the utility of current data in regard to three parameters Accuracy Variability Uncertainty Ideal would be to find ways of using all data and be able to correct for methodological differences

12 What Can Go Wrong???

13 Example 1: Inappropriate Method Scenario: Need to assess the risk of infection by enterohemorrhagic Escherichia coli O157:H7 on uncooked beef slices that are treated with acetic acid marinate (ph 3.0) for 7 hours for pathogen control Determined effectiveness of control measure by observing declined using MacConkey s Agar Results indicated that achieve greater than 4-log reduction in E. coli levels

14 Example 1: Laboratory Results Log(cfu/ml) Time (h) BHIA MC E. coli O157:H7 exposed to ph 3.0 environment

15 Impact of Method Error Using the Beta-Poisson dose-response model (Hass et al, 2000) with the α and β values of Teunis et al (2004), the predicted probability of infection from 100g serving originally containing 1 CFU/g is: MA results: 0.06% BHIA results: 30.16%

16 Example 2: Insufficient Information Scenario: Have only two studies on the frequency of contamination of foods by Listeria monocytogenes which have reported very different results Study 1: 2% of food tested contained the pathogen Study 2: 20% of the food tested contained the pathogen Minimal information provided on the methods of sampling analysis

17 Example 2: Insufficient Information How should the risk assessor handle the information? Average the frequencies? Reject one of the frequencies? Assume the frequency has a rectangular distribution?

18 Example 2: Insufficient Information How should the risk assessor handle the information? Average the frequencies? Reject one of the frequencies? Assume the frequency has a rectangular distribution? First questions to ask are how were the samples taken and analyzed What if I told you that one survey was based on 10 g samples and the other on 25 g samples

19 Example 2: Insufficient Information g Probability density g Log (CFU/g)

20 How Do We Fix It???

21 Data Challenge The task of the risk assessor would be greatly simplified if all researchers used the same validated methods Helps reduce two of the three key attributes Accuracy Uncertainty

22 Data Challenge In the absence of such a risk assessment utopia, the goal is to maximize the use of available data by appropriate adjustment, correction, or weighting of data Key to this is the inclusion of key attribute data and sufficient experimental details In addition there is supplemental information that are often used by risk assessors that might not be included in reporting the results of a standard method

23 Supplemental Data Food Water activity, ph, origin, sample storage conditions, processing conditions, methods of sampling, etc Host or Test Animal Age, genetics, diet, chronic diseases, immune status, medications, etc Hazard Purity, source, contaminants, method of delivery, etc Specific supplemental data needed will vary depending on the specific food-hazard-host combination and purpose of the risk assessment Quantitative data is better!!! Often risk assessors need access to raw data

24 Data Challenge A major challenge is the limited space in most journals for non-essential information Take advantage of supplemental data files that are increasingly available with many journals Take advantage of different organizations that serve as repositories for food safety data (e.g. FoodRisk.org)

25 Decisions on Data Adequacy An integral part of any good risk assessment is the use of data inclusion/exclusion rules Should be articulated before the risk assessment is initiated and then followed Process benefits greatly by having access to subject matters experts in Developing the decision criteria Reviewing the studies and data sets that are identified

26 Concluding Remarks

27 Key Points Ideally, all data used for food safety risk assessment would be based on validated, fitfor-purpose methods In the absence of such data, available data will be used while increasing the level of uncertainty In the absence of specific data, assumptions will be made based on best science Both the risk assessments and the risk management decision based on them need the involvement of the people who generated the data Risk assessments have life spans and should be re-run when significant new data or findings warrant a reexamination

28 FAO/WHO JECFA Resources Principles and Methods for the Risk Assessment of Chemicals in Food Combined Compendium of Food Additive Specifications

29 FAO/WHO JEMRI Resources Exposure Assessment of Microbiological Hazards in Food: Guidelines Hazard Characterization in Food and Water: Guidelines