Validation of calibration models

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Oct 22, 2014 - Contact: [email protected]. Homoscedastic. Heteroscedastic. (More weight on those data points in regression calculation) ...
Validation of calibration models: Development and testing of a practical procedure Brigitte Desharnais, Félix Camirand-Lemyre, Pascal Mireault, Cameron D. Skinner

2014 Annual Meeting of the Society of Forensic Toxicologists Wednesday, October 22nd 2014

http://entre-deux-films.over-blog.com/article-un-peu-de-culture-le-cri-wilhelm-113761242.html (Consulted October 15th 2014)

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Choosing a Calibration Model Order Weighting

Linear

Quadratic

No weight 1/x 1/x2

“Ultimately, the best approach is to use the simplest calibration model that best fits the concentrationresponse relationship.”  Cannot simply use r;  Should be evaluated visually using standardized residual plots;  Other alternatives: ANOVA LOF, significance of second order term, coefficient of determination. 3 Contact: [email protected]

Standardized Residuals Plot Tool

4 Contact: [email protected]

Standardized Residuals Plot Tool

   

Stepwise, systematic method Unbiased Choose model Validate model

5 Contact: [email protected]

Test Data  LC-MS/MS method  50 analytes (benzodiazepines, amphetamines, opioids, cocaine and metabolites)  15 deuterated internal standards

 Nine calibrants (5, 10, 15, 50, 75, 100, 400, 500, 1000 ng/mL)  5 replicates in the same run

6 Contact: [email protected]

Raw Data

7 Contact: [email protected]

Is Weighting Appropriate? Testing Heteroscedasticity with the F-Test Heteroscedastic

Homoscedastic

Error smaller at one concentration

Contact: [email protected]

More confidence to those data points

WEIGHTING (More weight on those data points in regression calculation) 8

Is Weighting Needed? Testing Heteroscedasticity with the F-Test F-TEST

Comparison of Fcalc with the F Distribution Table. p>0.05 : Homoscedastic data No weighting p0.05 or negative Fcalc: linear)

p0.05: calibration model validated) 15 Contact: [email protected]

Food for thought The data used for this process should be:  Intra-day or inter-day?  Intra-batch (extraction) or inter-batch?

To consider:  Production processes  Mathematical theory  Potential to yield an erroneous model  Potential to validate an incorrect model (variability introduced)

16 Contact: [email protected]

Acknowledgements

Félix Camirand-Lemyre University of Sherbrooke

From the LSJML: Gabrielle Daigneault Marc-André Morel Julie Lacquerre Cynthia Côté Martine Lamarche Marie-Pierre Taillon Édith Viel Lucie Vaillancourt

Supervisors: Pascal Mireault Dr. Cameron Skinner From Concordia: Michel Boisvert John Chin

Funding:

17 Contact: [email protected]

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