Analytical and Bioanalytical Chemistry

, Volume 380, Issue 3, pp 502–514 | Cite as

New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data

  • Max Feinberg
  • Bruno Boulanger
  • Walthère Dewé
  • Philippe Hubert
Original Paper


The implementation of quality systems in analytical laboratories has now, in general, been achieved. While this requirement significantly modified the way that the laboratories were run, it has also improved the quality of the results. The key idea is to use analytical procedures which produce results that fulfil the users’ needs and actually help when making decisions. This paper presents the implications of quality systems on the conception and development of an analytical procedure. It introduces the concept of the lifecycle of a method as a model that can be used to organize the selection, development, validation and routine application of a method. It underlines the importance of method validation, and presents a recent approach based on the accuracy profile to illustrate how validation must be fully integrated into the basic design of the method. Thanks to the β-expectation tolerance interval introduced by Mee (Technometrics (1984) 26(3):251–253), it is possible to unambiguously demonstrate the fitness for purpose of a new method. Remembering that it is also a requirement for accredited laboratories to express the measurement uncertainty, the authors show that uncertainty can be easily related to the trueness and precision of the data collected when building the method accuracy profile.


Data quality Method validation β-Expectation tolerance interval Uncertainty 


  1. 1.
    ISO/IEC 17025 (2000) General requirements for the competence of testing and calibration laboratories. ISO, GenevaGoogle Scholar
  2. 2.
    UK Department of Trade and Industry (1998) Manager’s guide to VAM, valid analytical measurement programme. LGC, Teddington, UK
  3. 3.
    EURACHEM (1998) The fitness for purpose of analytical methods: a laboratory guide to method validation and related topics, 1st edn. EURACHEM, Budapest
  4. 4.
    Food and Drug Administration (1995) International conference on harmonization, definitions and terminology, Q2A. Federal Register 60:11260–11262Google Scholar
  5. 5.
    Caporal-Gautier J, Nivet JM, Algranti P, Guilloteau M, Histe M, Lallier M, N’guyen-Huu JJ, Russoto R (1992) Guide de validation analytique SFSTP. STP Pharma Prat 2:205–226Google Scholar
  6. 6.
    Chapuzet E, Mercier N, Bervoas-Martin S, Boulanger B, Chevalier P, Chiap P, Grandjean D, Hubert P, Lagorce P, Lallier M, Laparra MC, Laurentie M, Nivet JC (1997) Méthodes chromatographiques de dosage dans les milieux biologiques: stratégie de validation. STP Pharma Prat 7:169–194Google Scholar
  7. 7.
    Chapuzet E, Mercier N, Bervoas-Martin S, Boulanger B, Chevalier P, Chiap P, Grandjean D, Hubert P, Lagorce P, Lallier M, Laparra MC, Laurentie M, Nivet JC (1997) Méthodes chromatographiques de dosage dans les milieux biologiques: stratégie de validation, exemple d’application de la stratégie de validation. STP Pharma Prat 8:81–107Google Scholar
  8. 8.
    Boulanger B, Dewe W, Hubert P (2000) Objectives of pre-study validation and decision rules, AAPS conference. APQ Open Forum, Indianapolis, INGoogle Scholar
  9. 9.
    Hubert P, Nguyen-Huu JJ, Boulanger B, Chapuzet E, Chiap P, Cohen N, Compagnon PA, Dewe W, Feinberg M, Lallier M, Laurentie M, Mercier N, Muzard G, Nivet C, Valat L (2003) Validation of quantitative analytical procedure, Harmonization of approaches. STP Pharma Prat 13:101–138Google Scholar
  10. 10.
    Shah VP, Midha KK, Dighe S, McGilveray I, Skelly JP, Yacobi A, Layloff T, Viswanathan CT, Cook CE, McDowall RD, Pittman KA (1992) J Pharm Sci 81:309–312Google Scholar
  11. 11.
    Food and Drug Administration (2001) Guidance for industry, bioanalytical methods validation. US Food and Drug Administration, Washington, DC,
  12. 12.
    Mee RW (1984) Technometrics 26(3):251–253Google Scholar
  13. 13.
    Satterthwaite FE (1946) Biometrics Bull 2:110–114Google Scholar
  14. 14.
    Hubert Ph, Chiap P, Crommen J, Boulanger B, Chapuzet E, Mercier N, Bervoas-Martin S, Chevalier P, Grandjean D, Lagorce P, Lallier M, Laparra MC, Laurentie M, Nivet JC (1999) Anal Chim Acta 391:135–148CrossRefGoogle Scholar
  15. 15.
    Chiap P, Ceccato A, Miralles Buraglia B, Boulanger B, Hubert Ph, Crommen J (2001) J Pharm Biomed Anal 24:801–814CrossRefPubMedGoogle Scholar
  16. 16.
    EURACHEM/CITAC (2000) Guide: quantifying uncertainty in analytical measurement, 2nd edn. EURACHEM/CITAC, Budapest,
  17. 17.
    Ranson C (2001) Workshop on the experience with the implementation of ISO/IEC 17025, Eurachem-Eurolab, Paris, 4 October 2001Google Scholar
  18. 18.
    Feinberg M, Montamat M, Rivier C, Lalère B, Labarraque G (2002) Accred Qual Assur 7:409–411CrossRefGoogle Scholar
  19. 19.
    ISO/DTS 21748 (2003) Guide to the use of repeatability, reproducibility and trueness estimates in measurement uncertainty estimation. ISO, GenevaGoogle Scholar

Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • Max Feinberg
    • 1
  • Bruno Boulanger
    • 2
  • Walthère Dewé
    • 2
  • Philippe Hubert
    • 3
  1. 1.Institut National de la Recherche AgronomiqueParis cedex 05France
  2. 2.Lilly Development CentreStatistical and Mathematical SciencesMont-Saint-GuilbertBelgium
  3. 3.Department of Analytical and Pharmaceutical Chemistry, Institute of PharmacyUniversity of Liège, CHULiège 1Belgium

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