# Presentation: 197222

## Risk Assessment, the AFSS Model and Introduction to Exposure Scoring 

- 		Barry Hooberman, MPH, Ph.D.
- 		Center for Veterinary Medicine/FDA
- 					AFSS Public Meeting
- 					May 22, 2007

## Overview

- Risk Recap
- Approach
- Hazard Characterization
- Exposure
- Relative Risk Ranking
- Today’s Topics

## The Purpose of the AFSS

- To develop and implement a comprehensive, risk-based, preventive animal feed safety system that minimizes, reduces or eliminates the risks to animal and human health that can arise from animal feed

## Why a Risk-Based Approach?

- Risk assessment is a logical process for collecting, organizing and analyzing information to inform a risk decision (*“science-based decision making”*).
- Risk assessment approach is also a forecasting process for the prevention of illnesses/adverse health risks.
- Eases the interactions between decision makers, stakeholders, and the public

## What is Risk Ranking?

- Risk *assessments* provide the “facts” for risk analysis.

- Risk

- Risk

- Risk

- Risk

- Risk

- Risk

- Risk

## Risk Ranking

- The risk *management* decisions about which risks to manage first are _value_-laden decisions.

**Risk Management**

- Risk

- Risk

- Risk

- Risk

- Risk

- Risk

- Risk

***Worst risks *********

***Management order *********

## How Will Ranked Risks  Be Used?

- Decide how risks from contaminants can best be prevented or controlled:
- Do limits for higher-risk contaminants need to be identified?  If yes, which contaminants?
- Do analytical methods for higher-risk contaminants need to be developed?
- What process changes can feed manufacturers  make to reduce risks from contaminants?
- What surveillance/sampling programs are needed to ensure compliance with contaminant limits?
- For internal use only

## Risk Assessment Poses FourSimple Questions:

- What can go wrong?
- Hazard Identification
- What are the consequences?
- Consequence Assessment
**How can it happen?**
**Exposure**** ****Assessment**
- What is the likelihood it would go wrong?
- Risk Estimation

## Roadmap

## Exposure Assessment - Source

- Identify source of each hazard entering the feed process.
- Feed ingredients will be linked to each hazard they may contain, resulting in a set of _Ingredient:Hazard_ pairs for each ingredient, such as _Corn:Aflatoxin_ and _Clay:Dioxin_.
- Initial level of a hazard in a feed ingredient or feed will depend on:
- Environmental conditions
- Human activities
- Source and type of contaminant
- Source and type of feed ingredient

## Exposure Assessment - Ei

- Initial Exposure Score
- For each pair, a quantitative or semi-quantitative Exposure Score will be calculated or estimated.  (Exposure is the amount of the hazard in the feed ingredient.)
- Score based on:
- Measured data (when available)
- Salmonella contamination data
- Expert opinion

## Exposure Assessment - MF

- Manufacturing Process(es) Modifying Factors
- Feed manufacturing process(es) will either increase, decrease or not affect the level of a particular hazard in the ingredient and feed
- Manufacturing processes include transportation, storage, steps in feed manufacturing, and on-farm processes

## Exposure Assessment - Ef

- Final Exposure Score
- Initial Exposure Score will be modified based on manufacturing processes used in the production of the specific feed ingredient.
- For example, a process may involve sufficient heat to eliminate the possible exposure to a bacterial hazard.

## Roadmap

**Cont.**** ****A**

**Mill: Mix, Heat, etc.**

**Cont. B**

**Cont. C**

**Ingredient 1**

**Ingredient 2**

**Ingredient 3**

**Finished Feed**

**Humans**

**Animals**

**E****i**

**MF**

**E****f**

- = Ei x MF

**E****A**

**E****H**

## Source Materials

**Plant Origin**

**Animal Origin**

**Mineral Origin**

**Microbial****Origin**

**Misc. Origin**

**Grains****A, B, D**

**Oilseeds**
**A, B, D**

**Molasses**
**B, D**

**Roots &**** tubers**
**A, B, D**

**Forages**
**A, B, C, D**

**Roughages**
**A, B, C**

**Fats & oils**
**B**

**Mammalian ****protein meals**
**B, C, D, E, F**

**Poultry meals**
**B, C, D, E**

**Aquatic**** animal meals****B, C, D**

**Fats & oils****B**

**P, Ca, Na**
**D**

**Trace****element premixes**
**D**

**Non-nutritive****adsorbents**
**D**

**Yeast &****single cell protein**
**C, D**

**Human****food waste**
**A, C**

**Animal manure**
**B, C, D**

**A = Mycotoxins**
**B = Agricultural chemicals**
**C = Microbial pathogens**
**D = Metals**
**E = Drug residues**
**F = TSEs**

## Limitations

- DATA!
- Primarily an issue in exposure
- Limited measured data for many hazards
- Strong reliance on expert opinion (not that there is anything wrong with that!)

## Data?!?

- Why build a risk model when we know there are data constraints?
- To organize existing data and maximize its use
- To identify the types of data that are needed
- To facilitate the acquisition of that data by demonstrating how it will be used
- Should relevant data not be available to allow the drawing of conclusions with sufficient certainty, what is usefullness of the model?
- Inform decision-makers about what can be said and what cannot be said with reasonable certainty
- Identify data gaps
- Inform the Center about the state of regulation for animal feeds
- Demonstrate ways in which the Center may implement a risk-based approach
- Inform stakeholders that FDA is willing to adopt new tools and techniques to ensure that the food supply is safe

## Goals for Today

- Concepts
- Hazard Ranking vs. Risk Ranking
- The difference is exposure
- Types of data available to CVM
- Chemical contaminants
- Microbial contaminants
- How data can be assembled to estimate exposure

- Data are to be considered DRAFT

## Exposure to Contaminants in Feeds and Feed Ingredients – Factors

- Levels in raw and processed feed ingredients
- 		 – *Karen Ekelman*
- Level changes during processing of feed ingredients
- 		– *Linda Benjamin*
- Levels in finished feeds
- 		– *Phares Okelo*
- Level changes during storage, transportation and feeding
- 		– *Phares Okelo*
- Amount consumed by swine
- 		– *Barry Hooberman*
- Amount consumed by humans
- 		– *Barry Hooberman*