Challenges in Developing a Risk Ranking Model for Feed Contaminants Dolores A. Beblo, Ph.D.
U.S. Food and Drug Administration Prepared for presentation at CVM
Animal Feed Safety System (AFSS)
Rockville, MD Public Meeting
September 12, 2006 |  |
Slide 2 For improving public health, which feed hazards should receive the most surveillance or regulatory attention? |  |
Slide 3 Risk Ranking Tool Framework for organizing information on feed contaminants, feed production, processing and consumption Uses: - Compare and evaluate different exposure
- scenarios Identify what data gaps exist for estimating and optimizing mitigating interventions
|  |
Slide 4 Risk Ranking Model Components Hazard Identification Hazard Characterization/
Health Consequence Scoring Exposure Assessment Relative
Risk Ranking |  |
Slide 5 Hazard Identification Data Sources Evidence of animal feed contamination - FDA Feed Contaminants Program investigational sample data
- FDA surveys of feed ingredients and feed
- USDA Food Safety and Inspection Service (FSIS) National Residue Program (NRP) sampling for pesticides and environmental contaminants where investigation indicated a feed source
|  |
Slide 6 Hazard Identification (cont.) Data Sources Evidence that contaminated animal feed results in animal health consequence - Infection outbreak and feed contamination incident reports
|  |
Slide 7 Hazard Identification (cont.) Evidence that contaminated animal feed results in human health consequence Data Sources - Epidemiological studies of bovine spongiform encephalopathy (BSE)
Data Needs - Only limited data for Salmonella
|  |
Slide 8 Hazard Characterization of Contaminant Factors that influence the outcome of exposure to contaminant - Potency and severity (Health Consequence Scoring)
- Contaminant physical and chemical properties
- Strain virulence
- Feed composition
- Factors related to conditions of ingestion
- Animal and human host factors
- Sensitivities of populations
|  |
Slide 9 Health Consequence Scoring Probability of consequence from ingestion of a given amount of contaminant - Chemical hazards: various reported reference levels for acceptable exposure (NOAEL, RfD, ADI, AEL)
- Microbial hazards: limited data; infective doses reported, but one unit might cause infection
|  |
Slide 10 Chemical vs. Microorganism Hazard Characterization - Different factors for contaminant classes: chemical or biological
- Relative weighting across and within class
|  |
Slide 11 Animal and Human Host Factors - Age
- Human immune status
- Others beyond AFSS scope initially
|  |
Slide 12 Hazard Characterization Data Sources - Scientific literature
- Battery of chemical toxicity studies
Data Needs - Limited pathogen dose-response data in animals and humans
- Incomplete epidemiological information
- Difficulty in extrapolating from animal data to humans or other animals
- Lack of mechanistic models
|  |
Slide 13 Exposure Assessment - What is the probability of consumption of contaminated feed?
- What are the likely numbers of microorganisms or amounts of physical or chemical contaminants in the feed at the time of consumption?
|  |
Slide 14 Exposure Assessment - Levels in raw feed ingredients
- Processing and production
- Levels in feed
- Distribution and storage
- Feed handling practices
- Feed consumption
- Animal vs. human
|  |
Slide 15 Exposure Assessment Data Sources - FDA Feed Contaminants Program investigational sampling – exposure estimate from residue prevalence, reference level of detection, and consumption survey data
Data Needs - FDA Feed Contaminants Program investigational sampling - No quantitative microorganism count data
- Not all feed contaminants of concern are included in current sampling programs
- Opportunities for industry contribution
|  |
Slide 16 Model Development is an Iterative Process Surveillance Data (Time N) Surveillance Data (Time 2)
Scientific Literature &
Surveillance Data (Time 1)
Model Iteration 1
Model Iteration 2
Model Iteration N
|  |
Slide 17 Model Quality/Adequacy - Are the essentials for safeguarding animal feed captured?
- Too much or little detail?
- Validity of assumptions?
- Is data variability reflected?
- How is uncertainty handled?
- Transparent development process?
|  |
Slide 18 Promoting and Protecting Public Health Thanks for your attention |  |
