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COPYRIGHT 2017. ALL RIGHTS RESERVED.
Standardization of Non-Targeted Methods for Food Fraud Detection
Jeffrey Moore, Ph.D. Senior Director – Scientific Strategy & Planning US Pharmacopeia [email protected]
Understanding Food Fraud Globally, Quebec City, April 5, 2017
COPYRIGHT 2017. ALL RIGHTS RESERVED.
USP’s Beginnings
USP was founded in 1820 by 11 physicians, in Washington, D.C.
COPYRIGHT 2017. ALL RIGHTS RESERVED.
A global resource for food integrity and safety solutions including science-based standards, tools, and services to improve confidence in
the global food supply chain.
USP’s Food Program
Food Fraud Mitigation Guidance
www.foodfraud.org Training & Advising
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Role of testing in food fraud mitigation
What are non-targeted methods and why are they (and why are they not) they being used?
Overview of draft USP guidance on non-targeted methods
Outline
COPYRIGHT 2017. ALL RIGHTS RESERVED.
5
Food Fraud Mitigation Approach For Ingredients
Prioritization
Controls
Data
Testing
Horizon Scanning
Other Factors
How to use data to make prioritization decisions
Supply Chain
History
COPYRIGHT 2017. ALL RIGHTS RESERVED.
The Challenge of Testing for Food Fraud
Criminal “designs” adulterant to evade existing QA system QA system reacts
by developing new tests
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Instead of looking for what should not be there…
Define very carefully the characteristics of
what should be there
Exclude anything that deviates significantly
from those characteristics
A Way to Get Ahead of Fraud Perpetrators
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Output U
9
Sample (U)
Reference Set (S1 to Sn)
Analytical Procedure Similarity
Assessment Procedure Output S1
Output S2 Output S3…Sn
Significance Level (α)
Is U Typical or Atypical with respect to Sn?
Typical
Atypical
Example Analytical Procedures
Spectral Chemical Wet-chemical
Example Similarity Assessment Procedures
Multivariate model (e.g. SIMCA)
Univariate model (e.g. CI, HQI)
Subjective criteria (e.g. “principle spots”)
Example Output types
Spectra
Quantitative measurements
Chromatograms
Images, e.g. micro-photographs
Hyperspectral images
5.39%
Essential Elements of a Non-Targeted Method
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Slide courtesy of Steve Holroyd, Fonterra
Example of NT Adulterants Detection: Liquid Milk by FTIR (Fonterra)
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Charge to Expert Panel:
To develop and validate a “tool-box” of methods and specifications for skim milk powder that will help protect against economically adulterated materials, including the next melamine
USP Expert Panel on NT Methods
COPYRIGHT 2017. ALL RIGHTS RESERVED.
nanometers
Rapid detection on melamine in Skim Milk Powder (SMP) by NIR
Study That Sparked USP’s Interest
0.012 to 0.39% dry-blended melamine in SMP
Non-adulterated SMP
0.033 to 0.39% Wet-blended melamine in SMP
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Calibration Reference Set 0% Melamine
0.03% WB Melamine 0.09 % WB Melamine 0.30 % WB Melamine 0.33 % WB Melamine 0.39 % WB Melamine
5 10 15 20 25 30
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2 x 10 -4
Hotelling T2 (60.95%)
Q R
esid
uals
(39.
05%
)
SIMCA Model
Wet-Blended Melamine Detectable in NT Model (CFSAN-FDA)
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Take-Aways from Study
Non-targeted methods beneficial even when you know what adulterant you are looking for
RM’s for “genuinely fake” adulterated foods needed to provide confidence in rapid test methods
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Instrumentation and chemometrics advances -> to non-targeted methods.
Used in routine testing as screening methods, followed by more targeted confirmatory methods for “abnormal” samples
Continued significant investments by major food companies, Testing Labs, and European funded R&I projects
Horizon 2020
Market Trends
COPYRIGHT 2017. ALL RIGHTS RESERVED.
17
Year
Cou
nt
Pubmed hits for “untargeted OR non-targeted OR nontargeted”
November 16 2016
Advances in, and maturation of, analytical technologies and data processing allowing rapid broad spectrum analysis
Scientific Trends
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Many companies already have the infrastructure, but may not know how to implement this novel approach.
Lack of solid information about the generation and application of NT methods, and very little support.
Lack of standardization Terminology: What does “non-targeted” mean, how to validate?
In use, but inconsistent development
Organizational risk tolerance is not always taken into account when developing non-targeted methods
Representativeness of reference / calibration model
Challenges to Implement NT Methods
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Name: USP “Guidance On Developing and Validating Non-Targeted Methods For Adulteration Detection”
Aim: Adaptable “framework” for develop. & valid., encourage use of NT methods, reduce confusion
Elaboration: 10 experts since early 2015
Stage: Public comment period closed end March; Anticipated final publication in September
Where to find: http://www.usp.org/guidance-developing-and-validating-non-targeted-methods-adulteration-detection
19
Draft USP Guidance on NT Methods
Send comments to: Dr. Kenny Xie, [email protected]
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Non-Targeted Method = Method that determines the similarity of a sample (U) to a reference standard or set (Sn) with a binary output – Typical or Atypical compared to Sn Sensitivity = Ability to correctly recognize unacceptable samples/material as Atypical Specificity = Ability to correctly recognize acceptable samples/material as Typical
Definitions
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Applicability statement
Method development using reference set
Application of test set to method
Method performance evaluation
Interpret results, monitor and maintain method
Logic flow of USP’s NT Guide
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Applicability statement: NT NMR screening method for detecting economically motivating levels of any adulterants (e.g. melamine at 0.1%) in milk powder with sensitivity of 95%, selectivity of 95% at 95% confidence level
Method development: using reference set of 53 commercial milk powders • DMSO-d6 extraction • 600 Mhz NMR • No pre-processing • Conformity index analysis • Boundary drawn at CI =
6.15
Example: NMR screening method
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Application to test set: • 16 independent milk powders • 61 adulterant spiked samples
Example: NMR screening method
Adulterant Estimated LOD
Melamine <0.005%
Urea <0.05%
DCD 0.05-0.5%
Maltodextrin 0.05-0.5%
Soy protein ND
Specificity = 100%
COPYRIGHT 2017. ALL RIGHTS RESERVED.
Applicability statement: NT NMR screening method for detecting economically motivating levels of any small molecule adulterants (e.g. melamine at 0.1%) in milk powder with sensitivity of 95%, selectivity of 95% at 95% confidence level
Example: NMR screening method
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Method performance evaluation: In-progress
Example: NMR screening method
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Many analytical techniques lend themselves to non-targeted testing
They can be rapid, inexpensive, and powerful tools for mitigating risks in food ingredient supply chains, even for known adulterants (e.g. wet-blended melamine).
Combined with targeted methods they can be more effective than either individually.
USP is helping to address the standardization gap, seeking public comments on its proposed Guidance for Non-Targeted Methods.
Conclusions on Non-Targeted Methods
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USP Expert Panel on Non-Targeted Methods for Milk Ingredients
Kenny Xie (USP)
Steve Holroyd (chair, sub-team on NT guidance)
Anthony Hanlon
Carmen Diaz-Amigo
Acknowledgements