Selectivity (Answer: C)
The validation characteristic that ensures a method can distinguish the analyte from other components in the biological matrix is selectivity (also called specificity). This is a fundamental analytical performance parameter required during method validation to confirm that the assay accurately measures only the target analyte without interference from other matrix components 1.
Definition and Purpose
Selectivity refers to the ability of an analytical method to differentiate and quantify the analyte of interest in the presence of other components that may be present in the biological sample 1. During validation, laboratories must establish that their techniques, procedures, and materials are appropriate to detect the target analyte at the molecular level within the relevant biological matrix 1.
Why Other Options Are Incorrect
- Accuracy measures how close the measured value is to the true value, representing systematic error or bias in the method 1
- Precision evaluates the reproducibility and repeatability of measurements, reflecting random error 1
- Robustness assesses the method's ability to remain unaffected by small, deliberate variations in method parameters 2
Critical Validation Context
Selectivity is particularly crucial in bioanalytical methods because biological matrices contain numerous interfering substances that can compromise accurate quantitation 2, 3. The method must demonstrate it can distinguish the analyte from:
- Endogenous compounds naturally present in the biological fluid 4
- Metabolites of the drug being measured 3
- Co-administered medications 5
- Matrix components like proteins, lipids, and phospholipids 5, 6
Common Pitfalls
Matrix effects represent a major challenge to selectivity, especially in LC-MS/MS methods where co-eluting compounds can suppress or enhance ionization of the target analyte 5, 6. Evaluating selectivity across multiple sources of biological matrix (including lipemic and hemolyzed samples) is essential, as different matrix compositions can significantly influence method reliability 6.