office of the texas state chemist texas feed and fertilizer control service agriculture analytical...

OFFICE OF THE TEXAS STATE CHEMIST Texas Feed and Fertilizer Control Service Agriculture Analytical Service

OTSC Statistically Derived Risk-Based Plan-of-Work

Susie DaiAssistant Research Professor

Mary SasserManager Field Operations

K.M LeeAssociate Scientist

Tim HerrmanProfessor, State Chemist and Director

OFFICE OF THE TEXAS STATE CHEMIST

Outline

Who are we? Sampling: Risk Management What ? Why ? How?

Regulatory Science

OFFICE OF THE TEXAS STATE CHEMIST

OFFICE OF THE TEXAS STATE CHEMIST

Where do We Receive the Authority

Texas Commercial Feed Control Act

Texas Agricultural Code

Chapter 141

Agricultural Analytical Service Three teams

Feed and Fertilizer Control Service Field investigators Registration Compliance

OFFICE OF THE TEXAS STATE CHEMIST

Office of the Texas State Chemist, Texas Agricultural Experiment Station, Texas A&M University System

Sample Chain of Custody

Sample Received

Sample Information Stored

Official Sample

Official Feed Seal Placed on Sample

Information Entered

Sample Shipped

Sample Prepared for Analysis

Reports Mailed to Manufacturer

Analytical Results to FFCS Each analytical result

must be surrounded by sample integrity. Without proof of the sample chain of custody, an analytical result is just a number.

Texas Commercial Feed Control Act

Texas Agriculture Code

Chapter 141

OFFICE OF THE TEXAS STATE CHEMIST

Risk = Probability x Consequence

Risk Probability Consequence

= X

Risk: A characteristic of a situation or action wherein two or more outcomes are possible, the particular outcome that will occur is unknown, and at least one of the possibilities is undesired.

OFFICE OF THE TEXAS STATE CHEMIST

What is Our Sampling Plan

Codex Alimentarius Animal Feed Taskforce: "Guidelines on application of risk assessment for feed" and a “list of hazards in feed”

OFFICE OF THE TEXAS STATE CHEMIST

What is Our Sampling Plan

Biological Bacterial

(Salmonella, Brucella)

Endoparasites (Toxoplasma and Taenia spp.)

Prions

Chemical Mycotoxin (aflatoxin,

fumonisin, ochratoxin, DON, T-2)

Industrial contaminants (Dioxin and PCB)

Heavy metals Drug residue Pesticide residue

OFFICE OF THE TEXAS STATE CHEMIST

Communication for Plan-of-Work

January: administrative planning

April: development & implementation

October: mid-year review

OFFICE OF THE TEXAS STATE CHEMIST

Why: AFRPS Standard 8 Planning and Resources

Requirement Summary Documented work

plan to support its inspection and sample collection

Conduct an evaluation of resource needs to complete inspection and sample collection projections

Evaluate resources to fully implement AFRPS

Program Elements Work plan to include:

inspection projections, sample, timeframe

Resources including adequate staff, equipment and funding

Conduct a review of resources required to implement the AFRPS including IT, funding, staff, equipment and other.

OFFICE OF THE TEXAS STATE CHEMIST

Why OTSCPlan of Work

FDA Plan-of-Work Inspection-based

Facility inventory Risk ranking Samples to support

inspection as evidence Rely upon states to

conduct the majority of inspection (60-70%)

OTSC Plan-of-Work Sample-driven

Targets coverage of all establishments in state

Directs inspections based on violation history

Builds into the POW FDA inspections

OFFICE OF THE TEXAS STATE CHEMIST

How ?

Plan of Work Attributes: Scalable including the ability to adjust sample numbers based

on state-wide tonnage, shifts in the use of different ingredients, and weighted by establishments risk factor and tonnage.

Adaptable including continuous updating subject to quarterly review.

Assessable such that conformance to the plan is possible real time.

Automated using project management software. Differentiates between investigational, surveillance and

monitoring sample collection. Transitional to facilitate process-control regulatory oversight

including one-sample-strategy and HACCP adoption. Portable to enable field investigators to perform work at any

point in the state and avoid duplication.

OFFICE OF THE TEXAS STATE CHEMIST

What: Three Components Economic Sampling Plan of

Work Feed Hazard Sampling Plan of

Work Investigational Plan of Work

OFFICE OF THE TEXAS STATE CHEMIST

Component 1Economic Sampling Plan of Work: Why?

Goal: GMP compliance of firms

OFFICE OF THE TEXAS STATE CHEMIST

Different Firms

What and How:

OFFICE OF THE TEXAS STATE CHEMIST

What and How Different Firms

Different

Inspection

Frequencies

OFFICE OF THE TEXAS STATE CHEMIST

How: Violation History as a Determinant for Inspectional Frequency

OFFICE OF THE TEXAS STATE CHEMIST

Results

2008 2009 2010 2011 2012 20135%

10%

15%

20%

25%

30%

25%21%

24%20%

17%13%

Sample Violation History for TexasFeed Industry

Fiscal Year

Sam

ple

Viol

ation

Hist

ory

(%)

Source: Office fo the Texas State ChemistFY 13: 9/1/2012-4/25/2013

2008 2009 2010 2011 2012 20135%

10%

15%

20%

25%

30%

21% 20% 20%17% 16%

14%

Sample Violation History for TexasFertilizer Industry

Fiscal Year

Sam

ple

Viol

ation

Hist

ory

(%)

Source: Office fo the Texas State ChemistFY 13: 9/1/2012-4/25/2013

OFFICE OF THE TEXAS STATE CHEMIST

Component 2:Feed Hazard Sampling Plan of Work

OFFICE OF THE TEXAS STATE CHEMIST

Component 2:What: Feed Hazard Sampling Plan of

Work

OFFICE OF THE TEXAS STATE CHEMIST

nppzp /)ˆ1(ˆˆ 2/

n

zn

z

n

ppz

n

zp

22/

2

22/

2/

22/

1

4

)ˆ1(ˆ

2ˆ

)/()~1(~~ 22/2/ znppzp

• Wald interval

• Wilson interval

• Agresti-Coull interval

where, n : sample size; Z/2 : (1 - /2) 100th percentile of the standard normal distribution

p : observed sample portion;

22/

22/ 2/

:

zn

zT

~𝒑 (T : observed sample frequency)

Why: Binomial Probability Statistics

OFFICE OF THE TEXAS STATE CHEMIST

Sample size (n)

where, N : population (a total number of feed products)

e : acceptable error

Z/2 √ 𝑝 (1−𝑝)𝑛

(n: average sample size of the past 3 years)

)1()1(

)1(2

2/2

22/

ppzeN

Nppzn

Sample Population

Sample Distribution

Violation Rate (Contamination)

SamplingSample size (n)

Presentation of the Population

Why: How Many Samples We Need to Take for this Sample Category?

OFFICE OF THE TEXAS STATE CHEMIST

• p (violation rate) : 0.297

• Product: corn products (aflatoxins)

Lower limit Upper limit

Wilson interval 0.2766 0.3189

• 95% confidence intervals

• N (population) : 50,000 • Z/2 : 1.96

• Estimated sample sizes

675 (minimum) 732 (maximum)

• e (acceptable error) : 0.034

How: Representative Sample Numbers to Estimate the Whole Population

Conclusion from Statistics: Taking ~700 corn samples can estimate the aflatoxin contamination in the whole corn industry in TX

OFFICE OF THE TEXAS STATE CHEMIST

How : POW Total Work Load

Work Plan Summary

Complete list of investigator’s feed & fertilizer facilities

Newly registered firms

Economic feed & fertilizer projections

Economic mycotoxin projections

Funded project projections

Regulatory inspections

One Sample Strategy

Equipment list

Contact lists

OFFICE OF THE TEXAS STATE CHEMISTComponent 3

Inspections Work Plan

OFFICE OF THE TEXAS STATE CHEMIST

Alignment of OTSC POW with AFRPS

OFFICE OF THE TEXAS STATE CHEMIST

Alignment of OTSC POW with AFRPS

OFFICE OF THE TEXAS STATE CHEMIST

National View of POWWhat, Why and How

USDA FSIS

OFFICE OF THE TEXAS STATE CHEMIST

Global View of POW: What, Why and How

New Zealand

EU

France CODEX

Regulatory Science Graduate Curriculum

Advancing the

science

of creating tools,

standards,

and practices to

improve the

protection and

compliance

of food systemsregsci .tamu.edu

SCSC 635Comparative Global

Standardsin Food Systems

SCSC 634Regulatory Science:

Principles & Practices in Food Systems

Globalization and standards Principles of standards development Regional food laws and regulations Impact of food law and regulations on

trade, food security and food protection

Emerging field of regulatory science

Food law and policy

Risk analysis

Conducting a risk assessment

Current issues and problems

Fall

regsci .tamu.edu

AGEC 638Special Topics in

Managerial Economics forRegulatory Science

SCSC 636Regulatory Science

Methodologyin Food Systems

Economic impact of regulations

Financial principles and practice for investments in compliance and oversight

Cost-benefit analysis of regulations governing the food industry

Statistically derived risk-based POW

Compliance Strategies

Inspectional Techniques for food systems

Crisis response & incident command

Spring

regsci .tamu.edu

SCSC 629/VTMI 629Laboratory Quality Systems

Validity & reliability of laboratory data

Laboratory process control

Quality assurance procedures, tools and methods

Laboratory management

Summer

regsci .tamu.edu

OFFICE OF THE TEXAS STATE CHEMIST

OFFICE OF THE TEXAS STATE CHEMIST Texas Feed and Fertilizer Control Service Agriculture Analytical Service

END

Acknowledgements:

APHL – Feed and Food Subcommittee

FDA – Texas Feed Safety and Inspection CAPS

Texas A&M AgriLife Research