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Procedure for the selection and validation of a calibration model: I —Description and Application

Title:

Procedure for the selection and validation of a calibration model: I —Description and Application

Desharnais, Brigitte ORCID: https://orcid.org/0000-0001-7373-656X, Camirand-Lemyre, Félix ORCID: https://orcid.org/0000-0003-3277-2729, Mireault, Pascal and Skinner, Cameron D. (2017) Procedure for the selection and validation of a calibration model: I —Description and Application. Journal of Analytical Toxicology, 41 (4). pp. 261-268. ISSN 0146-4760

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Official URL: https://doi.org/10.1093/jat/bkx001

Abstract

Calibration model selection is required for all quantitative methods in toxicology and more broadly in bioanalysis. This typically involves selecting the equation order (quadratic or linear) and weighting factor correctly modelizing the data. A mis-selection of the calibration model will generate lower quality control (QC) accuracy, with an error up to 154%. Unfortunately, simple tools to perform this selection and tests to validate the resulting model are lacking. We present a stepwise, analyst-independent scheme for selection and validation of calibration models. The success rate of this scheme is on average 40% higher than a traditional “fit and check the QCs accuracy” method of selecting the calibration model. Moreover, the process was completely automated through a script (available in Supplemental Data 3) running in RStudio (free, open-source software). The need for weighting was assessed through an F-test using the variances of the upper limit of quantification and lower limit of quantification replicate measurements. When weighting was required, the choice between 1/x and 1/(x^2) was determined by calculating which option generated the smallest spread of weighted normalized variances. Finally, model order was selected through a partial F-test. The chosen calibration model was validated through Cramer–von Mises or Kolmogorov–Smirnov normality testing of the standardized residuals. Performance of the different tests was assessed using 50 simulated data sets per possible calibration model (e.g., linear-no weight, quadratic-no weight, linear-1/x, etc.). This first of two papers describes the tests, procedures and outcomes of the developed procedure using real LC-MS/MS results for the quantification of cocaine and naltrexone.

Divisions:Concordia University > Faculty of Arts and Science > Chemistry and Biochemistry
Item Type:Article
Refereed:Yes
Authors:Desharnais, Brigitte and Camirand-Lemyre, Félix and Mireault, Pascal and Skinner, Cameron D.
Journal or Publication:Journal of Analytical Toxicology
Date:1 February 2017
Projects:
  • Procedure for the Selection and Validation of a Calibration Model
Funders:
  • National Sciences and Engineering Research Council of Canada
  • Fonds de recherche du Québec – Nature et technologies
Digital Object Identifier (DOI):10.1093/jat/bkx001
Keywords:Calibration, calibration curve, quadratic, linear, weighting, validation, heteroscedastic, standardized residuals, SWGTOX
ID Code:984860
Deposited By: BRIGITTE DESHARNAIS
Deposited On:10 Jan 2019 15:00
Last Modified:10 Jan 2019 15:05
Related URLs:

References:

[1] H. Gu, G. Liu, J. Wang, A.-F. Aubry, M. E. Arnold, Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance, Analytical Chemistry 86 (2014) 8959–8966.

[2] Scientific Working Group for Forensic Toxicology, Scientific Working Group for Forensic Toxicology (SWGTOX) Standard Practices for Method Validation in Forensic Toxicology, Journal of Analytical Toxicology 37 (2013) 452–474.

[3] Davidian, Marie and Haaland, Perry D, Regression and calibration with nonconstant error variance, Chemometrics and Intelligent Laboratory Systems 9 (1990) 231–248.

[4] D.L. Massart, B.G.M. Vandeginste, L.M.C Buydens, S. De Jong, P.J. Lewi, J. Smeyers-Verbeke, Multiple and Polynomial Regression, in: Handbook of Chemometrics and Qualimetrics: Part A, volume 20A of Data Handling in Science and Technology, Elsevier, Amsterdam, Netherlands, 1997, pp. 263–303.

[5] D.L. Massart, B.G.M. Vandeginste, L.M.C Buydens, S. De Jong, P.J. Lewi, J. Smeyers-Verbeke, Straight Line Regression and Calibration, in: Handbook of Chemometrics and Qualimetrics: Part A, volume 20A of Data Handling in Science and Technology, Elsevier, Amsterdam, Netherlands, 1997, pp. 171–230.

[6] Karnes, H Thomas and Shiu, Gerald and Shah, Vinod P, Validation of bioanalytical methods, Pharmaceutical Research 8 (1991) 421–426.

[7] Hubert, Ph and Chiap, Patrice and Crommen, Jacques and Boulanger, Bruno and Chapuzet, E and Mercier, N and Bervoas-Martin, S and Chevalier, P and Grandjean, D and Lagorce, Ph and others, The SFSTP guide on the validation of chromatographic methods for drug bioanalysis: from the Washington Conference to the laboratory, Analytica Chimica Acta 391 (1999) 135–148.

[8] Ingle, James D. and Crouch, Stanley R., Signal-to-Noise Ratio Considerations, in: Spectrochemical Analysis, Prentice Hall, Englewood Cliffs, United States of America, 1988, pp. 135–163.

[9] Food and Drug Administration, Bioanalytical Method Validation – Guidance for Industry, Technical Report, Silver Springs, United States of America, 2001.
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