Introduction to FDA-iRISK®

Course Description

Participants will be introduced to FDA-iRISK® , a Web-based, comparative risk assessment tool that has been available for public use since 2012. This peer-reviewed tool has many built-in functions and automated features that allow users to conduct fully probabilistic risk assessments relatively rapidly and efficiently. It enables users to build, view and share scenarios that reflect their real-world or theoretical food safety issues, without requiring extensive risk assessment modeling experience.

This course is paired with Quantitative Risk Assessment and held over one week.  As part of the course we will provide attendees a guided, hands-on opportunity to explore the tool and develop food-safety risk scenarios. The course is conducted in a computer teaching laboratory.

Prerequisite:
It is strongly recommended that this course be taken after you have completed the Risk Management and Qualitative Risk Assessment course. These courses provide contextual information about risk analysis that is not repeated here.  Participants should also have basic knowledge of probability and statistics and intermediate level skills in using Microsoft Excel 2003.

RESOURCES

Excel: There are web-based resources that provide introductory Excel 2003 training. Many such courses are available - some at no cost - like the one found at www.videoprofessor.com.
Basic Statistics: The quantitative methods course does not require in-depth knowledge of statistics, but an understanding of basic terminology is necessary. There are web-based resources that provide information about basic theory in probability and statistics. Some examples include http://www.robertniles.com/stats and http://www.statsoft.com/textbook.

Overview of Topics

Introduction to FDA-iRISK®, Building scenarios in FDA-iRISK®, Guided walk through of working in FDA-iRISK®

Learning Objectives

  • Understand usefulness of models and the important tradeoffs in the design of models
  • Understand the differences between deterministic and stochastic models
  • Gain a strong foundation in basic probability theory and probability distributions
  • Be able to build basic probabilistic models using Excel and @RISK
  • Case studies: Microbial hazard and Chronic chemical hazard
  • Simulation principles and techniques
  • Scenario and Sensitivity analysis

Register now for Summer 2024