Abstract
Mass spectrometry coupled with liquid chromatography is a valuable tool for drug development and personalised drug therapy. The matrix effect is caused by enhancing or suppressing the analyte signal intensity by the interfering compounds of biological fluids. The matrix effect may influence the reliability of the quantitative results. Thus, its evaluation is a critical part of bioanalytical method validation. Identified factors affecting the matrix effect are the physicochemical properties of the analyte, type of biological material, analytical conditions, the ion source construction and calculation method. The order of analysis of test samples (pure solutions and post-extraction spiked samples) is another factor possibly affecting quantifying the matrix effect variability between sources. Our primary goal was to find which experimental design – interleaved or set of blocks – is more sensitive to detect matrix effect variability. Additionally, to better understand the reason of variability, we evaluated the influence of chromatographic elution and the type of plasma (normal, lipemic or hemolyzed), co-elution, and carry-over of phospholipids. We used chemometric methods: Principal Component Analysis and Partial Least-Squares Discriminant Analysis. Although a comparable (but statistically different) matrix effect (%RSDMF) is observed using the interleaved and block schemes, for some compounds, the order of the samples strongly influences the results. The interleaved scheme was generally more sensitive in detecting the matrix effect than the block scheme. Thus, reporting the order of samples is needed to ensure the repeatability of experiments. Chemometrics suggests that lipemic samples analyzed in isocratic conditions are most prone to the matrix effect. Different compositions of matrix lots of the same type – especially lipemic – may influence method reliability. Thus, evaluating more than one source of lipemic and hemolyzed plasma is recommended.
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