Control of Pathogens in the Food Industry: A Global Food Company

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Control of Pathogens in the Food Industry A
Global Food Companys PerspectiveControle de
Patógenos na Industria de Alimentos A
Perspectiva de una Empresa Multinacional de
Alimentos
III Simpósio Internacional de Inocuidade de
Alimentos (ABRAPA) VIII Simpósio
Brasileiro de Microbiologia de Alimentos
(SBM)
Dr. Paul A. Hall Sr. Director Microbiology and
Food Safety Glenview, IL
October 26, 2004 Sao Paulo, Brasil
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Kraft Foods Company Facts

• 2003 net revenues of more than 31 billion.
• Largest food and beverage company in North
  America and second largest in the world.
• Brands marketed in over 150 countries globally.
• More than 100,000 employees operating in more
  than 68 countries.
• 197 manufacturing facilities worldwide at the end
  of 2003.

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Kraft Foods Company Facts

• The Kraft brand portfolio is one of the
  strongest in the world.
• Number one share position in 11 global
  categories, 22 of the top 25 categories in the
  U.S., and 18 of the top 25 categories
  internationally.

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Producing Safe Food is our First Priority

• Consumer Protection Trust
• Consumer trust
• Food Safety is critical to that trust
• Business Survival
• Our brands are most important assets
• Industry Responsibility
• Committed to food safety across thefood chain

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Methods to Reduce the Risk from Pathogens in Food

• Prevent inadvertent contamination
• Inhibit growth
• Remove contamination

Adapted from Sofos, et al., 1998
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Top Line Summary

• Public health is best protected by control of
  Pathogens via
• Aggressive environmental monitoring
• Effective corrective actions
• Proper equipment design
• Adherence to GMPs and SSOPs
• Proper handling practice
• Refrigerate perishable RTE products at lt40 F
  (lt4.40º C)
• Consume perishable RTE products quickly
• Appropriate intervention strategies
• Formulation (e.g. lactate salts/sodium diacetate)
  
• Post-packaging treatments

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Pathogen Control Approaches/ Interventions

• HACCP and Prerequisite Programs
• Sanitation and GMPs
• Environmental Monitoring Program
• Ingredient Specifications
• Product Formulation
• Vendor Qualification Quality Expectations
• Auditing and Certification Programs
• New Processing Technologies
• Improved Detection Methods
• Good agricultural Practices/On-Farm Controls

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Pathogen Control - Listeria monocytogenes as an
Example

• Certain foods pose an increased risk of being
  associated with listeriosis
• These foods have the following properties
• Have the potential for contamination with LM
• Support the growth of LM to high numbers
• Are ready-to-eat foods
• Require refrigeration
• Stored for extended periods of time

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Pathogen Control - Listeria monocytogenes as an
Example

• Foods can be classified according to their risk
  based on their properties and history of known
  illness

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US FDA Listeria Risk Assessment
Decreased Risk per Annum
Clusters A and B Clusters C and D Cluster E
Very High Risk Deli Meats Frankfurters (not reheated) High Risk Pâté and Meat Spreads Unpasteurized Fluid Milk Smoked Seafood Moderate Risk No food categories Cluster 1
High Risk High Fat and Other Dairy Products Pasteurized Fluid Milk Soft Unripened Cheese Moderate Risk Cooked RTE Crustaceans Moderate Risk No food categories Cluster 2
Moderate Risk No food categories Moderate Risk Deli-type Salads Dry/Semi-dry Fermented Sausages Frankfurters (reheated) Fresh Soft Cheese Fruits Semi-soft Cheese Soft Ripened Cheese Vegetables Low Risk Preserved Fish Raw Seafood Cluster 3
Moderate Risk No food categories Low Risk No food categories Very Low Risk Cultured Milk Products Hard Cheese Ice Cream and Other Frozen Dairy Products Processed Cheese Cluster 4
Decreased Risk per Serving
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Differentiating Risk in Processed Meats

• Reheated versus unheated hot dogs
• Dried and semi-dried meats
• Pate
• A significant portion (gt70, hot dogs andgt50
  deli meats) of RTE processed meats have been
  formulated with growth inhibitors
• Deli meats really are four product categories
• With and without inhibitors
• In store sliced and packaged
• Commercially prepackaged

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Industry actions to reduce the risk L.
monocytogenes in RTE products

• Training of industry through comprehensive
  Listeria control workshops.
• Review of Listeria control workshop materials
  with USDA staff
• The use of a thermal treatment after a product
  has been packaged to destroy Listeria
  monocytogenes.
• Use of new ingredients to inhibit the growth of
  Listeria monocytogenes on ready-to-eat meat and
  poultry. Many products now contain these
  ingredients.
• Development of new principles for processing
  equipment design that facilitate sanitation and
  reduce the possibility of bacteria being
  "harbored" in tiny spaces like the thread of an
  exposed screw or a hollow roller on a conveyer
  belt.

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Industry actions to reduce the risk L.
monocytogenes in RTE products

• Sophisticated new environmental sampling programs
  that work to target Listeria in the plant
  environment so it can be destroyed before it is
  transferred to products.
• Research to discover new technologies.
• Declaration by the meat and poultry industry that
  food safety is a "non-competitive issue," which
  resulted in the free exchange of food safety
  information among competitors.

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Prevalence of Listeria monocytogenes in Sliced
Lunchmeats and Franks
FSIS Results of ready-to-eat products analyzed
for Listeria monocytogenes
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Incidence of Foodborne Illness 1996-2002
Listeria
National Health Objective .25
Preliminary FoodNet Data on the Incidence of
Foodborne Illnesses --- Selected Sites, United
States, 2002
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Pathogen Control - Listeria monocytogenes as an
Example

• Product reformulation can be a powerful tool for
  reducing consumer risk
• Microbial models can be used to optimize product
  quality and product safety

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Modeling Approaches

• Kinetic Models
• Fit growth curves, derive rate constants.
• Develop multiple regression model for growth rate
  constants as a function of predictor variables.
• Predict amount of growth after time.
• Boundary model
• Define growth threshold ? measure time to growth.
• Develop generalized regression model for time to
  growth as a function of predictor variables.
• Predict time before growth occurs.

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Intro to Boundary Models

• Predict time-to-event (e.g., failure, spoilage,
  growth) as a function of predictor variables.
• Commonly used in
• Engineering time-to-failure of a new design
• Medicine efficacy of different drugs and doses
  on mortality
• Social sciences prisoner recidivism by treatment
  program
• Use generalized regression to get predictive
  model and develop contour maps to show boundary
  between growth and no-growth.
• Handles censored observations.
• Uses maximum likelihood estimation (get log
  likelihood, not R2.)

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Define Growth Threshold
An increase of 1 log10 or more in L.
monocytogenes count, determined by expert review
of growth curves

• Smallest change distinguishable from noise.
• IFT expert panel 2001 a 1 log increase is an
  appropriate level of control for L.
  monocytogenes.
• Evaluation and definition of potentially
  hazardous foods. December 31, 2001. IFT/FDA
  contract no. 223-98-2333 task order no.4.
  Chapter 6 section 9 pass/fail criteria.
•    http//www.foodprotect.org/pdf/hazard_foods/cha
  pter6.pdf

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Experimental Design Processed Meats

• Central composite design for four continuous
  variables
• NaCl 0.8 1.5 2.2 2.9 3.6
• Moisture 45.5 55.0 64.5 74.0 83.5
• Na diacetate 0.0 0.05 0.10 0.15 0.20
• K lactate syrup 0.25 2.5 4.75 7.0 9.25
• Repeated for uncured products, ? 5th variable
  (cured/uncured).
• Model products were made, inoculated, stored at 4
  C, and assessed every 2 weeks for LM count.
• Seman, D.L., et al. (2002) J. Food Protection,
  65, 651-658.

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Model Performance Summary
Model gives good description of the data used to
create it.
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Contours of weeks to 1 log growth of L.
monocytogenes in cured products calculated using
the boundary model with growth and no-growth
modeling and validation observations
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Potential Graphical Output from Boundary Model
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Application

• Simple spreadsheet
• Calculate time to growth from formula
• Calculate lactate from shelf-life
• Plot growth boundary
• Available from Purac America on free CD

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Listeria Growth InhibitionEstimated Benefit to
Public Health
Predicted Log Counts/gm
1/7,500 risk
1/75 MM risk
1/750 MM risk
Based on Growth Model and median mortality risk
for neonates published in FDA/USDA risk analysis
Figure IV-5
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Estimated 95th Percentile Mortality Risk
- 50 g serving of product- Lm growth from an
initial level of 1CFU/g
Intermediate- Age Neonatal Elderly
Initial 1 CFU/g 5 x 10-12 1 x 10-9 4 x 10-11
After 3 log Growth 2 x 10-9 5 x 10-7 2 x 10-8
After 6 log Growth 1 x 10-6 3 x 10-4 1 x 10-5
After 8 log Growth 8 x 10-5 2 x 10-2 9 x 10-4
Source Interpolation from FDA Fall 2003 Listeria
monocytogenes Risk Table IV-12
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• Project Forward controls Listeria in the
  environment
• Using environmental sampling we systematically
  seek out and find sources and take corrective
  action

• Goal - Identify possible technology solutions to
  achieve zero pathogen risk in RTE meat products
• Through formulation, we can further reduce risk
  resulting in greater public health protection

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Concurrent Approach to AddressPublic Health
PROJECT FORWARD Preventative Corrective
Actions
PROJECT ZERO Potential Technical Solutions

• Formulation
• Product/Process Handling
• Post Packaging Pasteurization

• Internal Plants
• External Network

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Project Forward - Listeria Control Program
3-Stage Approach to Address Preventative
Corrective Actions
Sanitation / Environmental Practices
PersonnelTraining
Facility / Equipment Design

• Intensive Environmental swabbing
• Footwear / clothing
• Traffic patterns
• Sanitation
• Maintenance

• Facility layout
• Floors
• Design for Sanitation

• GMPs
• Maintenance
• Sanitation
• Behavior based food safety

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Logic Behind Environmental Control Program

• Listeria Control Equation based on premise that
  intensive environmental monitoring is effective
  in understanding the plant environment to control
  Listeria

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Listeria Equation
Dry,Uncracked,CleanFloors
TrafficPatterns
Sanitation Procedures
SanitaryDesign




GMPs
Listeria Control
Mismanagement of any of the components may
increase the risk of cross contamination.
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Logic Behind Environmental Control Program

• Listeria Control Equation based on premise that
  intensive environmental monitoring is effective
  in understanding the plant environment to control
  Listeria
• Systematic, disciplined approach to seek out,
  find and eliminate the undesirable conditions
  which could support harborage or transference of
  indicator organisms

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Sanitary Zones
Zone 4 Locker rooms cafeteria halls
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Environmental Monitoring Approach

• Timely assessment of control of RTE environment
• Biased intensive sampling during production to
  validate all components
• Large surface areas sampled for Listeria genus
• Sampling is randomized (by the day of the week
  and shift)
• Every RTE processing line must be sampled weekly
• Sampling plans need to be flexible and tailored
  to each specific line and facility

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Logic Behind Environmental Control Program

• Listeria Control Equation is based on premise
  that environmental monitoring is effective in
  understanding the plant environment to control
  Listeria
• Systematic, disciplined approach to seek out,
  find and eliminate the undesirable conditions
  which could support harborage or transference of
  indicator organisms
• Focus improvement efforts (capital and resources)
  as directed by resultsfollow the data

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Logic Behind Environmental Control Program
Finished product testing has significant
limitations.
Probability of Missing Contamination
Contamination in Lot
Number ofSamples Tested
10
2
1
0.5
3 73 94 97 99 10 35 82 90 95 60 lt0.5 3
0 55 74 120 lt0.5 8.5 30 55 180 lt0.5 2.6
16 41 240 lt0.5 0.8 9 30
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Logic Behind Environmental Control Program

• Statistics demonstrate that finished product
  testing has severe limitations
• Finished product sampling is not preventative and
  does not help identify root cause of
  contamination
• Disciplined approach to monitoring promotes
  knowledge and awareness of the environmental
  conditions that could result in product
  contamination
• If there is an effective kill step in the
  process, and if there is no Listeria in the
  environment, there will be no Listeria in the
  finished product
• Public health protection is better served with
  an aggressive environmental program

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Logic Behind Environmental Control Program

• To verify effectiveness of the program, we
  monitor all components in the Listeria equation
• Of 100 RTE meat production lines
• 50 no positive contact surfaces
• 84 single occurrence
• These results indicate the level of Listeria is
  very low in our environment
• Low levels in the environment are not likely to
  result in product contamination

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Low Levels in the EnvironmentEnumeration Data

• Counts of gt10 per area swabbed only seen on floor
  after 2 shifts, or in niches
• Environmental samples of product contact surfaces
  tested for Listeria have been enumerated.
  Positive samples that were enumerated contained
  less than the detection limit of the methods (MOX
  and MPN)
• Data supports concept that random positive
  product contact surfaces contain few Listeria
  (lt10) that can be transferred to product

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Corrective Actions
In the event of a positive Listeria species
environmental sample, Kraft requires follow
up/corrective actions. Typical corrective actions
include

• Review of cleaning records
• Review of environmental data of the area as well
  as adjacent areas

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Corrective Actions (contd)

• Review of line records, for mechanical downtime
• Audit and interview employees concerning
  practices during sanitation, set-up, and
  production
• Inspections of the area and equipment for
  potential harborage points
• Complete a targeted clean

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Benefits of Aggressive Environmental Monitoring
/ Corrective Actions
Percent Positive
Zone 1 Positive Percent Listeria spp. Positive
Annual
Year
Graph 1 values calculated with the formula (total
zone 1 composite total follow up positive) /
(total zone 1 composite samples 5) (total
follow up samples)
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Project Forward Validation Program

• To measure monitoring program effectiveness, a
  validation program is in place to assure that the
  samples taken represent the actual conditions of
  the entire environment at a given time.
• Includes multiple sampling points during
• Pre-op
• Operation
• 2nd shift operation
• One day for two consecutive weeks
• Completed once every six months

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Regulatory Goal

• Protect public health
• Success depends upon locating Listeria--finding
  positive results--and taking proper action
• Even with effective control, environment will not
  be completely Listeria negative
• Utilize appropriate interventions to reduce
  public health risk

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Summary

• Public Health is best protected by
• Implementation of a validated Listeria control
  program
• Aggressive environmental monitoring
• Effective corrective actions
• Incorporation of appropriate intervention
  technologies
• Proper handling practices
• No Listeria monocytogenes exceeding regulatory
  limit in food in commerce

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Obrigado pela atenção! Perguntas?