Qualitative threshold method validation and uncertainty evaluation: a theoretical framework and application to a 40 analytes LC-MS/MS method.

Qualitative methods have an important place in drug testing, filling central needs in, amongst others, screening and analyses linked to per se legislation. Nevertheless, bioanalytical method validation guidelines either do not discuss this type of method, or describe method validation procedures ill adapted to qualitative methods. The output of qualitative methods are typically categorical, binary results such as "presence"/"absence" or "above cut-off"/"below cut-off". Since the goal of any method validation is to demonstrate fitness for use under production conditions, qualitative validation guidelines should evaluate performance by relying on the discrete, binary results, instead of the continuous measurements obtained from the instrument (e.g., area). A tentative validation guideline for threshold qualitative methods was developed by in silico modeling of measurements and derived binary results. This preliminary guideline was applied to an LC-MS/MS method for 40 analytes, each with a defined threshold concentration. Validation parameters calculated from the analysis of 30 samples spiked above and below threshold (false negative rate, false positive rate, selectivity rate, sensitivity rate and reliability rate) showed a surprisingly high failure rate. Overall, 13 out of the 40 analytes were not considered validated. Subsequent examination found that this was attributable to an appreciable shift in the standard deviation of the area ratio on a day-to-day basis, a previously undescribed and unaccounted for behaviour in qualitative threshold method validation literature. The developed guideline was modified consequently and used to validate a qualitative threshold method, relying on binary results for performance evaluation and taking into account measurement uncertainty.