Weekly outline
ValidR
F. Marçon (Centre Hospitalier Universitaire d’Amiens–Picardie, Amiens, France)
The validation of assay methods is a critical step in ensuring the reliability of results. It necessitates the application of complex statistical models to evaluate the precision and accuracy of measurements. The use of tolerance intervals (β) and accuracy profiles lends robustness to the validation process[[HUBERT, P. et al. (2004). Harmonization of Strategies for the Validation of Quantitative Analytical Procedures. A Sfstp Proposal--part I. J Pharm Biomed Anal, 36(3), 579-586. http://doi.org/10.1016/j.jpba.2004.07.027]]. These statistical tools define intervals within which a specified percentage of assay results will fall, at a given confidence level. They also assist in determining the limits of quantification, i.e., the minimum and maximum concentrations at which an analyte can be precisely and accurately quantified.
To facilitate these intricate calculations and analyses, an application coded in the R programming language, named ValidR[[MARÇON, F. (2023). marconfr/R_VALIDR: v1.0 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.7706081]], has been developed and validated using the dataset published by Hubert et al. (2004). It is hosted on Rshinyapps servers and is available on the GERPAC website. R, with its advanced statistical capabilities and flexibility in visualization, is particularly well-suited for these tasks. It also allows for the generation of dynamic HTML reports. This application and its source code have been made freely accessible to promote widespread adoption and to streamline the process of scientific manuscript preparation.
[1] HUBERT, P. et al. (2004). Harmonization of Strategies for the Validation of Quantitative Analytical Procedures. A Sfstp Proposal--part I. J Pharm Biomed Anal, 36(3), 579-586. http://doi.org/10.1016/j.jpba.2004.07.027
[2] MARÇON, F. (2023). marconfr/R_VALIDR: v1.0 (v1.0). Zenodo. https://doi.org/10.5281/zenodo.7706081
