How does the order of sample analysis influence the matrix effect during LC-MS bioanalysis?

Area of Science:

• Analytical Chemistry
• Pharmacology
• Bioanalysis

Background:

• Liquid chromatography-mass spectrometry is vital for drug development and personalized therapy.
• The matrix effect, caused by interfering biological compounds, can compromise quantitative results in bioanalysis.
• Evaluating the matrix effect is essential for validating bioanalytical methods.

Purpose of the Study:

• To compare the sensitivity of interleaved versus block experimental designs in detecting matrix effect variability.
• To investigate factors influencing matrix effect variability, including chromatographic elution, plasma type, co-elution, and carry-over.

Main Methods:

• Utilized chemometric methods, specifically Principal Component Analysis (PCA) and Partial Least-Squares Discriminant Analysis (PLS-DA).
• Evaluated matrix effect variability using interleaved and block sample analysis schemes.
• Assessed the influence of chromatographic elution, plasma type (normal, lipemic, hemolyzed), and phospholipid carry-over.

Main Results:

• Both interleaved and block schemes showed comparable, yet statistically different, matrix effects.
• The interleaved scheme demonstrated higher sensitivity in detecting matrix effect variability.
• Chemometric analysis indicated that lipemic samples under isocratic conditions are most susceptible to the matrix effect.
• Variability in matrix lots, particularly lipemic plasma, can affect method reliability.

Conclusions:

• The order of sample analysis significantly influences matrix effect quantification and must be reported for experimental repeatability.
• The interleaved experimental design is more effective for detecting matrix effect variability.
• Lipemic plasma and specific chromatographic conditions increase susceptibility to matrix effects, necessitating evaluation of multiple plasma sources.