Overview
ABSTRACT
The process of analytical method validation is well mastered in testing laboratories. It satisfactorily responds to usual concerns of analytical result producers. In this article is demonstrated how measurement uncertainty can better take into account the expectations of laboratory customers. Measurement uncertainty can easily be derived from data collected for validation, without any extra cost. Moreover, it is explained how uncertainty function can be obtained, in order allow for the variation of measurement uncertainty as a function of concentration, that is very specific of chemical measurement.
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Read the articleAUTHORS
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Max FEINBERG: Agricultural engineer, PhD in chemistry Chemometrics consultant, Paris (France)
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Serge RUDAZ: PhD in Pharmaceutical Sciences, Professor in the Pharmaceutical Sciences Section of the Faculty of Sciences at the University of Geneva (Switzerland)
INTRODUCTION
This article provides important additions to
This article presents a recent development, based on the widespread use of measurement uncertainty and uncertainty functions. Measurement uncertainty is a natural methodological development in the field of method validation in analytical chemistry.
Validation is mainly a preoccupation of analysts, yet their role has changed considerably over the last 20 years. In the 1970s, chemometricians proposed defining an analyst as a problem-solver. This highly ambitious definition is now outdated, as many analysts now work in subcontracting laboratories for customers or principals who outsource their testing. Analysts have gradually gone from being genuine problem-solvers to data producers. Of course, not all laboratories are like this. Many university and industrial research facilities still employ analysts to solve problems. However, the setting up of specialized instrumental platforms, to reduce the cost of measurement and federate the use of delicate instruments, tends to specialize them and distance them from the general understanding of the problems to be solved. Yet the demand for analysis results is growing, as they are increasingly taken into account as a basis for decision-making. Paradoxically, in the future, the concept of "decision-making science" could be seen as an implicit objective of the analytical sciences.
Based on a critical presentation of developments in method validation and measurement uncertainty estimation, it is therefore possible to highlight the trends expected over the coming decades.
A glossary at the end of the article (§ 6 ) lists definitions that are important...
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KEYWORDS
measurement uncertainty | experimental design
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Bibliography
Standards and norms
- Exigences générales concernant la compétence des laboratoires d'étalonnages et d'essais - NF EN ISO/IEC 17025 - 2017
- Lignes directrices relatives à l'utilisation d'estimations de la répétabilité, de la reproductibilité et de la justesse dans l'évaluation de l'incertitude de mesure - ISO 21748 - 2017
- Analysis of agricultural and food products – Characterization protocol to validate a quantitative analysis...
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