Systematic Assessment of Matrix Effect, Recovery, and Process Efficiency Using Three Complementary Approaches: Implications for LC-MS/MS Bioanalysis Applied to Glucosylceramides in Human Cerebrospinal Fluid

Abstract

The evaluation of matrix effect, recovery, and process efficiency is essential in the validation of LC-MS/MS bioanalytical methods, as they impact assay accuracy, precision, and sensitivity. However, guidelines on bioanalytical method evaluation are not harmonized and can occasionally be ambiguous. To address this need, the study presents an integration of three different approaches to assess these parameters within a single experiment. The first approach examined the variability of peak areas and standard-to-internal standard (IS) ratios between different matrix lots to assess the influence of the analytical system, relative matrix effects, and recovery on method precision. The second strategy evaluates the influence of the overall process on analyte quantification. The third approach calculates both the absolute and relative values of matrix effect, recovery, and process efficiency, as well as their respective IS-normalized factors, to determine the extent to which the IS compensates for the variability introduced by the matrix and recovery fraction. Applying these strategies to an LC-MS/MS method for quantifying glucosylceramides in cerebrospinal fluid addresses the challenges posed by limited sample volume and endogenous analytes, while providing a comprehensive understanding of the factors that influence method performance and promoting adherence to different guideline recommendations. This study supports the importance of a systematic evaluation of matrix effect, recovery, and process efficiency during method validation. Standardized evaluation methodologies would improve data interpretation, enhance method reliability, and contribute to harmonization in in-house bioanalysis.

1

Schematic protocol for the preparation of the three sets of samples and the information that can be obtained from each set. The data obtained in set 1 assess the variability of the entire analytic system (including sample preparation, chromatographic system, and detector performance). Since the main difference between sets 2 and 1 is the sample matrix, the data obtained from set 2 provide information on the combined effect of the analytical system and ionization efficiency. Set 3 evaluates the combined effects of the analytical system, sample matrix, and analyte recoveries on the method performance, as this set includes the addition of the compounds in the matrix prior to extraction. Created in BioRender. Castillo, L. (2025) https://BioRender.com/ur17de8.

2

Flowchart containing the three different strategies and the link between the different descriptors. The first strategy involved the evaluation of the factors that influence the overall precision of the method, as well as the impact of IS in compensating for this variation. In set 1, CVs of peak areas reflected overall system variability, including sample preparation, chromatography, and MS performance. Set 2 incorporated relative matrix effect, representing variability in response when the same compound amount is added to each extract. Set 3 included recovery variability between lots and served as an indicator of overall precision. Each set integrated its own contributing sources of variation of the previous one. CVs of standard-to-IS area ratios assessed IS compensatory effect at each stage of the process. The variability between lots of the slopes calculated from the area ratios at each concentration were considered another indicator of the compensating effect of the IS for each factor. The second strategy examined the influence of overall process efficiency on analyte quantification. The third strategy involved the evaluation of the absolute matrix effect (ME), recovery fraction (RE) and overall process efficiency (PE), and their corresponding IS-normalized factors (MEF, REF, and PEF). ME, RE, and PE values represented the effect of the sample matrix on the ionization efficiency of the target compounds, the recovered fraction of the target compounds after various processing and extraction steps of the method, and the combined effect of both on the overall efficiency of the method, respectively. MEF, REF, and PEF indicated the extent to which each process impacts the standard compared to the IS. The variation of these parameters between lots (rME, rRE, and rPE) and the corresponding compensatory performance of the IS (rMEF, rREF, and rPEF) were also estimated.

3

Graphical representation of the ME, RE, and PE values (a) and their normalized-factor by IS (MEF, REF, and PEF) (b) from the third approach. The boxplots (mean + SD) indicate the variability between matrix lots (n = 3). The orange dashed line represents the ideal value (100% for absolute values and 1 for normalized factors). The lower ME, RE, and PE of the IS compared to the standards are reflected in the MEF, REF, and PEF >1 for all isoforms and concentrations.