Validation procedures for quantitative gluten ELISA methods: AOAC allergen community guidance and best practices.

The food allergen analytical community is endeavoring to create harmonized guidelines for the validation of food allergen ELISA methodologies to help protect food-sensitive individuals and promote consumer confidence. This document provides additional guidance to existing method validation publications for quantitative food allergen ELISA methods. The gluten-specific criterion provided in this document is divided into sections for information required by the method developer about the assay and information for the implementation of the multilaboratory validation study. Many of these recommendations and guidance are built upon the widely accepted Codex Alimentarius definitions and recommendations for gluten-free foods. The information in this document can be used as the basis of a harmonized validation protocol for any ELISA method for gluten, whether proprietary or nonproprietary, that will be submitted to AOAC andlor regulatory authorities or other bodies for status recognition. Future work is planned for the implementation of this guidance document for the validation of gluten methods and the creation of gluten reference materials.

Beta-Binomial Statistical Model for Validation Studies of Analytes with a Binary Response.

BACKGROUND: The probability of detection (POD) model has had widespread application for statistically analyzing single and multiple collaborator validations studies with binary outcome data for a wide range of analytes over the last decade. OBJECTIVE: The POD model is placed on a firm theoretical foundation, and extended to a more generalized beta-binomial model. METHODS: The POD model is revisited and embedded in the beta-binomial model. This generalization includes collaborator reproducibility as a specific parameter. The new model includes only two distributional parameters: the overall across-collaborator probability of detection (LPOD) and the intraclass correlation of collaborators (ICC), measuring irreproducibility. Differences between methods are measured by the difference in LPOD values, denoted dLPOD. RESULTS: Accurate statistical estimators and confidence intervals are provided with validation by simulation. This new beta-binomial model will be applicable to a full range of candidate methods giving binary qualitative results, including microbiological, toxin, allergen, biothreat, and botanical analytes. CONCLUSIONS: The new beta-binomial model provides easy equivalence tests to show the study clearly demonstrates (with 95% confidence) that the method differences and collaborator reproducibility are acceptable. HIGHLIGHTS: The validation system for qualitative binary methods using probability of detection (POD) of an analyte as the parameter of interest has been modified and further validated.

Determination of Ethanol in Food by Enzymatic Method Enzytec™ Liquid Ethanol, Collaborative Study: Final Action 2017.07.

BACKGROUND: Enzytec™ Liquid Ethanol was approved as AOAC Official MethodSM2017.07 First Action in September 2017 and is now further characterized by a collaborative study using the manual and automated version of the test. METHOD: It is applicable to quantify ethanol in diluted or undiluted kombucha, fruit juices, vegetable juices, and alcohol-free beer samples around 0.5% ABV within 20 min using two ready-to-use reagents and measurement of absorbance at 340 nm. RESULTS: The overall relative reproducibility standard deviation across a wide concentration range for kombucha was calculated to be 6.99% by modeling the reproducibility standard deviation by the mean concentration for each of the six kombucha pairs by a linear regression. Analysis of juices and beer showed an overall higher variation with an estimated overall RSD(R) value by regression of 10.1%. Mean recovery of aqueous ethanol reference solutions tested by each participant was between 100 and 103%. CONCLUSIONS: The data obtained by this collaborative study show that the EnzytecTMLiquid Ethanol is suitable to quantify ethanol from matrices representing important alcohol-free liquid food categories. HIGHLIGHTS: The EnzytecTMLiquid Ethanol was approved as AOAC Method 2017.07 Final Action.

On the use of the Horwitz Ratio (HorRat) as an acceptance criterion for dietary fiber collaborative studies.

The quest for optimum methodology for any analyte often includes a study of the method in multiple independent laboratories. Evaluation of the results of these studies is typically subjective; however, various attempts have been made to increase the objectivity of the evaluation. Among the objective propositions is the use of the Horwitz Ratio (HorRat) as applied to collaborative study statistics. A historical review of fiber method validation studies performed since 1940 shows that the Horwitz curve does not effectively predict the results of dietary fiber collaborative studies, either retrospectively or prospectively. Consequently, use of the HorRat as a criterion for accepting or rejecting dietary fiber methods is contraindicated. An alternative, objective statistical approach is proposed that may also apply to collaborative studies of other empirical analytical methods in general.

Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.

Validation procedures for quantitative food allergen ELISA methods: community guidance and best practices.

This document provides supplemental guidance on specifications for the development and implementation of studies to validate the performance characteristics of quantitative ELISA methods for the determination of food allergens. It is intended as a companion document to other existing publications on method validation. The guidance is divided into two sections: information to be provided by the method developer on various characteristics of the method, and implementation of a multilaboratory validation study. Certain criteria included in the guidance are allergen-specific. Two food allergens, egg and milk, are used to demonstrate the criteria guidance. These recommendations will be the basis of the harmonized validation protocol for any food allergen ELISA method, whether proprietary or nonproprietary, that will be submitted to AOAC and/or regulatory authorities or other bodies for status recognition. Regulatory authorities may have their own particular requirements for data packages in addition to the guidance in this document. Future work planned for the implementation and validation of this guidance will include guidance specific to other priority allergens.

Preparation of Validation Materials for Estimating Gluten Recovery by ELISA According to SMPR 2017.021.

BACKGROUND: In September 2017, the AOAC INTERNATIONAL Stakeholder Panel for Alternative Methods adopted Standard Method Performance Requirement (SMPR®) 2017.021, "Quantitation of Wheat, Rye, and Barley Gluten in Oats," as guidance for the validation of methods for measuring gluten in oat products. The SMPR requires prospective methods to demonstrate adequate recovery (50-200%) based on the analysis of a set of reference samples. OBJECTIVE: This document provides specific methods and data on the preparation of such validation materials and their analysis by an R5 ELISA kit to demonstrate the SMPR recovery estimation procedure. METHODS: Seven reference samples were made by spiking wheat, rye, and barley into gluten-free oat flour at two levels, 10 and 20 mg/kg. The levels of gluten were determined by a wet chemical method based on the Codex Alimentarius definition of gluten. RESULTS: The recoveries for wheat, rye, and barley were 122, 425, and 349%, respectively, for the R5 ELISA kit. The wet chemical method for estimating gluten in a sample of pure grain demonstrated repeatability relative SDs ranging from 1.40 to 2.75%. CONCLUSIONS: The reference materials are suitable to estimate ELISA kit responses to wheat, rye, and barley and calculate recoveries. HIGHLIGHTS: A series of oat flours spiked with wheat, rye, and barley flours were developed to be used as reference materials. A wet chemical method was established to estimate gluten contents based on the Codex definition. The reference materials are available for purchase to support further method development and validation.

Quantification of Wheat, Rye, and Barley Gluten in Oat and Oat Products by ELISA RIDASCREEN® Total Gluten: Collaborative Study, First Action 2018.15.

Background: Since its introduction to the analytical community, the R5 method to quantify gluten led to a strong improvement of the situation for the food industry and celiac patients. During recent years, some questions arose on the use of the Codex Alimentarius factor of two to convert from prolamins to gluten, an overestimation of rye and barley, inadequate detection of glutelins, and the inhomogeneous distribution of gluten in oats. These limitations of the R5 method, especially when measuring oat samples, led to AOAC Standard Method Performance Requirement (SMPR®) 2017.021, which was approved by stakeholders in 2017. Objective: We present a collaborative study of a method for the quantitative analysis of wheat, rye, and barley gluten in oat and oat products using a sandwich ELISA that is based on four different monoclonal antibodies including the R5 monoclonal anitbody. Methods: The sandwich ELISA detects intact gliadins and related prolamins from rye and barley, high-molecular-weight (HMW) glutenin subunits (GS) from wheat, HMW secalins from rye, and low-molecular-weight (LMW) GS from wheat. It does not detect D-hordeins from barley. Samples are extracted by Cocktail solution, subsequently followed by 80% ethanol, and analyzed within 50 min. Results: The measurement range is between 5 and 80 mg/kg gluten using a calibrator made out of a gluten extract from four different wheat cultivars. The results of the collaborative test with 19 participating laboratories showed recoveries ranging from 99 to 137% for all three grain sources. Relative reproducibility SDs for samples >10 mg/kg gluten ranged from 10 to 53%. Conclusions: The collaborative study results confirmed that the method is accurate and suitable to measure gluten from all three grain sources and has demonstrated performance on oat matrices, which meets the criteria as specified in SMPR 2017.021. Data from in-house validation experiments are available as Annex B to this publication.

Detection and Antigenic Profiling of Undeclared Peanut in Imported Garlic Using an xMAP Multiplex Immunoassay for Food Allergens.

A shipment of imported garlic powder was suspected of containing peanut. Samples (subs) collected from the shipment displayed considerable variability in peanut antigenicity when analyzed by enzyme-linked immunosorbent assay (ELISA). This raised questions regarding whether peanut was actually present, the amount present, and the basis for the variability in antigenic content. Analyses that used an xMAP multiplex assay for the detection of peanut and additional food allergens generated responses that were characteristic of peanut. Specifically, the relative intensities of two different peanut-specific antibodies coupled to beads (peanut-37 and -38) and the antigen profiles were identical to garlic controls spiked with peanut. In addition, the xMAP data did not indicate the presence of other allergens. Quantitative analyses indicated an approximately fivefold variation in peanut concentration among different subs. In contrast, within a sub, the apparent peanut concentration appeared constant. Particle size analyses of the garlic powder subs indicated a single distribution profile, with a peak at 380 µm. ELISA analysis of sieve-fractionated garlic powder from one of the subs indicated that slightly less than half of the detectable peanut was smaller than 212 µm, with the remainder almost evenly split between 212 and 300 µm and >300 µm. Modeling to predict possible oral exposure levels of peanut other than those directly measured requires additional research on the physicochemical properties of peanut and garlic, along with information on the production of the garlic powder.

Characterization of near-infrared spectral variance in the authentication of skim and nonfat dry milk powder collection using ANOVA-PCA, pooled-ANOVA, and partial least-squares regression.

Forty-one samples of skim milk powder (SMP) and nonfat dry milk (NFDM) from 8 suppliers, 13 production sites, and 3 processing temperatures were analyzed by NIR diffuse reflectance spectrometry over a period of 3 days. NIR reflectance spectra (1700-2500 nm) were converted to pseudoabsorbance and examined using (a) analysis of variance-principal component analysis (ANOVA-PCA), (b) pooled-ANOVA based on data submatrices, and (c) partial least-squares regression (PLSR) coupled with pooled-ANOVA. ANOVA-PCA score plots showed clear separation of the samples with respect to milk class (SMP or NFDM), day of analysis, production site, processing temperature, and individual samples. Pooled-ANOVA provided statistical levels of significance for the separation of the averages, some of which were many orders of magnitude below 10⁻³. PLSR showed that the correlation with Certificate of Analysis (COA) concentrations varied from a weak coefficient of determination (R²) of 0.32 for moisture to moderate R² values of 0.61 for fat and 0.78 for protein for this multinational study. In this study, pooled-ANOVA was applied for the first time to PLS modeling and demonstrated that even though the calibration models may not be precise, the contribution of the protein peaks in the NIR spectra accounted for the largest proportion of the variation despite the inherent imprecision of the COA values.

Exploring authentic skim and nonfat dry milk powder variance for the development of nontargeted adulterant detection methods using near-infrared spectroscopy and chemometrics.

A multinational collaborative team led by the U.S. Pharmacopeial Convention is currently investigating the potential of near-infrared (NIR) spectroscopy for nontargeted detection of adulterants in skim and nonfat dry milk powder. The development of a compendial method is challenged by the range of authentic or nonadulterated milk powders available worldwide. This paper investigates the sources of variance in 41 authentic bovine skim and nonfat milk powders as detected by NIR diffuse reflectance spectroscopy and chemometrics. Exploratory analysis by principal component analysis and varimax factor rotation revealed significant variance in authentic samples and highlighted outliers from a single manufacturer. Spectral preprocessing and outlier removal methods reduced ambient and measurement sources of variance, most likely linked to changes in moisture together with sampling, preparation, and presentation factors. Results indicate that significant chemical variance exists in different skim and nonfat milk powders that will likely affect the performance of adulterant detection methods by NIR spectroscopy.