Automatic Quantification workflow using High Resolution Mass Spectrometry

Calibration lines in drug quantification workflows are traditionally determined using QQQ instruments that have high sensitivity and where the ion selectivity is gained by using multiple reaction monitoring. This workflow needs a previously identify transition to be monitored to obtain the needed selectivity for the compound of interest. In this work we demonstrate an automated methodology to perform quantification studies based on high-resolution mass spectra data. We obtain selectivity based on the high resolution, low ppm difference between the observed and the theoretical m/z computed from the compound formula. We gain the needed sensitivity by automatically considering multiple m/z ions, including adducts and fragments, in the computation of the peak areas.

Methods

The methodology has been developed using MSe data acquired on a Waters Xevo G2XS Qtof. A peak analysis is done in the high and low collision energy traces. The m/z of the each of the identified peaks in both MS functions are then compared to the m/z obtained for the parent molecular formula, the multiple charges, the adducts and/or the theoretically generated fragments. The list of experimental peaks that matches any of computed m/z is then submitted to the quality peak analysis (criteria: number of points/peak, ppm, signal/noise ratio, etc.). The area for each of the m/z is computed (isolated or in combination) using an auto-adjusting extraction window and later used in a regression analysis with multiple acceptance criteria.

Preliminary data

The data for the working example is obtained for a compound at 13 different concentration levels: 1, 2, 5, 10, 20, 50,1 00, 200, 500,1000, 2000, 5000, 10000 ng/mL measured in triplicate. The peak quality criteria were based on a minimum of eight scan points per peak, a difference in Retention Time between samples lower than 0.05 min, the ions with a difference between the observed and the computed m/z lower than 15 ppm.  The extraction window was auto-adjustable, the noise evaluation time range (peak units) was set to 6, a the Minimum signal/noise ratio to 3. The maximum variation of nominal concentration of each sample and the average, as well as the maximum CV was set to 25% for a point to be accepted for regression. For a line to be accepted a minimum number of concentration levels was set to 6 with a minimum replication of 2 and a maximum fold change between consecutive points was 10. Three lines can be derived to cover the wider dynamic range, the LLoQ and the ULOQ using different weighting factors. In the example that will be shown the best fragments for quantification are obtained even in absence of the M+H ion due to in-source fragmentation. The regression line obtained covered the dynamic range from 2 to 10000 with all the quality controls fulfilled with a combination of two m/z. It is also observed that due to the different ion intensity and noise evaluation for each ion it was necessary to perform an automatic optimization of parameter for the best peak quality.