# Validation of analytical methods as an evaluation tool for research data reliability. Functional Ecology

Anne Jaulin, Elodie Ollivier, Nathalie Cheviron, Virginie Grondin, Amelie Trouve

## ► To cite this version:

Anne Jaulin, Elodie Ollivier, Nathalie Cheviron, Virginie Grondin, Amelie Trouve. Validation of analytical methods as an evaluation tool for research data reliability. Functional Ecology. Functional Ecology Conference - JEF AnaEE France, Dec 2018, Nancy, France. 2018. hal-02786058

HAL Id: hal-02786058

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Submitted on 4 Jun 2020

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# VALIDATION OF ANALYTICAL METHODS AS AN EVALUATION TOOL FOR RESEARCH DATA RELIABILITY

Anne JAULIN*, Elodie OLLIVIER, Nathalie CHEVIRON, Virginie GRONDIN, Amélie TROUVE

UMR ECOSYS INRA, AgroParisTech, Université Paris-Saclay, plateforme Biochem-Env, 78026, Versailles, France

* anne.jaulin@inra.fr

contact-biochemenv@inra.fr

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## Context

The platform Biochem-Env:

* Was created in 2012 by INRA (French National Institute for Agricultural Research) with the support of the ANR program "Investissements d'avenir" as a service of the infrastructure ANAEE-France,

* For the **biochemical characterization of natural environments** (soils and sediments) and **associated macrofauna** in research projects,

* By developing and validating methods in order to **provide traceable analytical data with high level of confidence**.

For intra-laboratory validation of quantitative analytical methods, the INRA's Quality Guidelines for research and experimental units (2013) recommends **"the accuracy profile" method** according to the NF V03-110:2010 standard.

Could we use a same internally developed method to quantify proteins in various biological models ?

## Validation of analytical methods by the accuracy profile approach

### Purpose:

* To provide guarantees on analytical results, for the analyst and the end-user

* To demonstrate analytical method fitting with the scientific objectives

* To allow laboratory recognition

* To improve analysts working practices

### Benefits of the accuracy profile approach:

* An overall statistical method combining trueness and precision

* A standardized approach: NF V03-110:2010

* A simple and graphic interpretation for a rapid decision

* The determination of the scope of the method

* The determination of quantification limits

* An estimation of measurement uncertainty

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## Material and methods

Protein determination method by the Bicinchoninic acid
(Ref. QPBCA-1KT, QuantiPro™ BCA Assay Kit, Sigma-Aldrich)

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Validation method according to the « accuracy profile » approach (NF V03-110:2010 standard):

* Selection of validation samples:

- Spiked reference material: Bovine Serum Albumine

- 7 levels (0.5 ; 1 ; 2 ; 5 ; 10 ; 20 ; 30 mg.mL⁻¹)

- 3 replicates (repeatability)

- 6 days of analysis (intermediate precision)

- 2 analysts (intermediate precision)

* Calibration (indirect quantitative analysis):

- 6 levels (0 ; 2 ; 4 ; 8 ; 16 ; 20 ; 30 ; 40 mg.mL⁻¹)

- Regression model: polynomial

## Results

Biological model effect

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Matrix effect

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1 analyst

2 analysts

### Performance of the method

Fixed criteria:
B = ±80% (expectation tolerance limits)

λ = ±20% (acceptability limits)

Limit of Quantification LQ:
2,7 mg/mL

Scope of the method:
2,7 to 30 mg/mL

Measurement uncertainty range
(U₉₅%) : 10 to 30%

## Conclusions

### Accuracy profile approach:

* Global statistical combination of trueness and precision and pragmatic

* Simple graphic interpretation, allowing a clear and easy comparison between method performance and intended use and, a rapid decision

* No limit in the choice of the calibration model => large scope range

* Methods with very low variability can be validated (not rejected by a H0)

* Diagnostic tool, matrix effect taken into account

* Risks and guarantees managed for both end-users and laboratories

* Estimation of measurement uncertainty

### The validation of this analytical method helped us to:

* Determine the performance of the method

* Improve the steps for sample preparation and analysis

* Assess the matrix effect

* Pointed out the importance of an experimented analyst

* Analytical method for protein quantification in 4 biological models was validated with a good accuracy considering scientific specification and needs.

Decision on the
fitness for
purpose

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## Perspectives :

* Adapt λ-acceptability values according to the concentration range

* Extend the method to other biological models and biomarkers (Lipid, glycogen...)

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## References

[1] Validation des méthodes d'analyse quantitative par le profil d'exactitude. Numéro spécial du Cahier des Techniques de l'INRA, 2010.

[2] Labo-Stat: Guide de validation des méthodes d'analyse, Feinberg M. Retirage 2012.

[3] Jaulin A. et Deschamps M. La validation de méthodes d'analyse quantitative, c'est l'affaire de tous ! La démarche Qualité au service des activités de recherche. Journées de la mesure et de la métrologie J2M 2012 du 8-11/10/2012, Le Croisic.

[4] Feinberg M. et Laurentie M. A global approach to method validation and measurement uncertainty. 2006. Accred. Qual. Assu. 11, 3-9.

[5] Feinberg M. et al. New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data. 2004. Anal. Bioanal. Chem. 380: 502-514.