Analytical methods based on ultrahigh-performance liquid chromatography – tandem mass spectrometry (UHPLC – MS/MS) nowadays allow the simultaneous determination of hundreds of target analytes. The traditional approach to quantitative method validation has three major drawbacks, namely (i) it is extremely laborious, repetitive and rigid; (ii) it does not allow the introduction of new analytes without starting the validation from the very beginning and (iii) it is performed on spiked blank matrices, whose very nature is considerably modified by the addition of a large number of candidate analytes standard solutions. Predictive chemometric models were developed from closed sets of analytes for the estimation of validation parameters on molecules of the same class, but not included in the training set. Retention time, matrix effect, recovery effect, identification (LOD) and quantification (LOQ) limits were predicted with Principal Components Analysis (PCA) and Partial Least Squares (PLS) methods. These procedures were initially applied to data previously reported in validated UHPLC-MS/MS multi-residue methods for human whole blood [1], oral fluid [2] and urine [3] samples, proving effective and in accordance with the recommendations of SOFT/AAFS guidelines. Secondly, a new validation procedure was developed for UHPLC-MS/MS multi-residue methods based on the concept of robustness, allowing a rapid and complete evaluation of the validation parameters required by international guidelines. Our protocol suggests to examine samples prepared with coeluting and non-coeluting analytes, in order to verify electrospray (ESI) signal suppressions phenomena and interferences in realistic situations, in opposition to fully spiked blank samples at concentrations comprised by standard validation practices. Lastly, chemometrically-driven validation processes are proposed for new analytes to be included into existing validated methods, together during typical validation practices.
Chemometric approach to open validation protocols. prediction of validation parameters in uhplc-ms/ms methods for large sets of analytes
ALLADIO, EUGENIO;A. Salomone;PIRRO, VALENTINA;VINCENTI, Marco
2013-01-01
Abstract
Analytical methods based on ultrahigh-performance liquid chromatography – tandem mass spectrometry (UHPLC – MS/MS) nowadays allow the simultaneous determination of hundreds of target analytes. The traditional approach to quantitative method validation has three major drawbacks, namely (i) it is extremely laborious, repetitive and rigid; (ii) it does not allow the introduction of new analytes without starting the validation from the very beginning and (iii) it is performed on spiked blank matrices, whose very nature is considerably modified by the addition of a large number of candidate analytes standard solutions. Predictive chemometric models were developed from closed sets of analytes for the estimation of validation parameters on molecules of the same class, but not included in the training set. Retention time, matrix effect, recovery effect, identification (LOD) and quantification (LOQ) limits were predicted with Principal Components Analysis (PCA) and Partial Least Squares (PLS) methods. These procedures were initially applied to data previously reported in validated UHPLC-MS/MS multi-residue methods for human whole blood [1], oral fluid [2] and urine [3] samples, proving effective and in accordance with the recommendations of SOFT/AAFS guidelines. Secondly, a new validation procedure was developed for UHPLC-MS/MS multi-residue methods based on the concept of robustness, allowing a rapid and complete evaluation of the validation parameters required by international guidelines. Our protocol suggests to examine samples prepared with coeluting and non-coeluting analytes, in order to verify electrospray (ESI) signal suppressions phenomena and interferences in realistic situations, in opposition to fully spiked blank samples at concentrations comprised by standard validation practices. Lastly, chemometrically-driven validation processes are proposed for new analytes to be included into existing validated methods, together during typical validation practices.
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