before you test – know this - aphl
TRANSCRIPT
Before you test –know this
KRISTI MCCALLUM
COLORADO DEPT. OF AGRICULTURE
2019 APHL ANNUAL MEETING
JUNE 4, 2019
Recent events from our testing Raw pet food samples testing positive for
pathogens which led to……Open Record requests, lots of themAngry blogs and film-makers, more angry
people, more angry conference calls, a phony phone call……..
Hearings State Lab data acceptance Regulatory actions
Everything from obtaining the sample to reporting is
This could happen
The Four “C’s” OfQuality Documentation
CORRECTNESS
CONSISTENCY
COMPLETENESS
COMPLIANCE
Attributes Of QualityChain-of-Custody Records
COC RECORD IS COMPLETE, CORRECT, AND CONSISTENT WITH OTHER PROJECT RECORDS
CHAIN OF CUSTODY IS CONTINUOUS
DATES AND TIMES OF TRANSFERS MATCH
COC RECORDS ARE UNIQUELY IDENTIFIED
NUMBER OF CUSTODY TRANSFERS IS MINIMIZED; OR APPROPRIATE FOR THE FACILITY OR ACTIVITY
STORAGE OF SAMPLES IS PER SOPs
What does “data acceptance” mean and why is it important? To produce valid and defensible analytical data that may be used to
take regulatory action or used by other agencies In 2014, APHL created a Data Acceptance Work Group
FDA, USDA, AAFCO, AFDO Used the Partnership for Food Protection (PFP) Laboratory Best Practices
Manual to determine data acceptance criteria Created a Best Practices for Submission of Actionable Food and Feed
Testing Data Generated in State and Local Laboratories – APHL June 2017
Assist laboratories in collection of data, building a defensible data packet and reporting data that can be used by other agencies
Assist laboratories in identifying and developing policies, procedures, and records in order to share human and animal food testing data
What is in a quality data packet?
If someone from the outside or from another agency looked at your data packet, could they find everything that “tells the complete story” of the sample or would they do this?
Sample collection and submission
Defined sampling plan/agreement with customer
COC
Sample collection and transport procedures in place and followed
Sample acceptance criteria are well-defined
Holding times met
Critical for laboratory to have the following: Laboratories submitting data should have the following in place:
Quality Assurance Plan that at a minimum details Handling of samples from receipt, sample prep, sub-sampling, sample
preservation, sample storage and sample disposal
Selection of test methods, technical SOPs
Traceability of reference materials, chemicals, reagents, media, test kits
Equipment calibration, verification and maintenance
Document management and good document control
Records management and control
Type, frequency and evaluation of quality control tests (Blanks, CCV, standard controls)
Non-conforming tests and corrective actions
Training and Demonstration of CompetencyTraining and competency records will need to be made available to anyone who asks for them. This goes for all staff handling customer samples
Methodology
Are your methods going to come into question?
Use of non-official or non-standard methods – must be able to produce validation study data for these methods if asked
If using official or standard methods – be sure your lab has verified that it can meet the performance criteria of the method and that it is suitable for what it’s being used for
Data Packets and Documents
Traceability of all equipment used Traceability of all RM used – QC organisms Traceability of all chemicals, reagents, media, test kits used with
expiration dates Traceability of all critical supplies used Quality criteria defined in SOPs has been met and is documented Analysis steps and sample tracking are well documented with
dates and analyst Results are easy to find and a final result report meets criteria Data was reviewed and released per defined protocols
Important Takeaways Failure to maintain proper COC may constitute a break in sample
custody and may discredit the sample(s) as use of evidence in court proceedings. The sampler and laboratory must assume that all samples collected could be used as evidence in court and treat the sample accordingly.
Remember to have a data packet that tells the complete story of the sample
Before sampling for any program – have a plan and evaluate risk!
