(M1030-09-52) Overcoming Quantitative Challenges in Bioanalysis of Small Molecules Using the MRM³ and Q0 Dissociation Approaches on the SCIEX 7500 System

Purpose: A complex sample matrix can often lead to quantitative challenges in the form of interferences in MRM methods. Using a second-generation product ion for target analytes can improve the selectivity and reduce the interferences in the assay. QTRAP systems from SCIEX have been used for this purpose in a workflow named MRM³. The latest SCIEX 7500 system introduced a new feature, Q0 dissociation enhanced (Q0DE), that produces fragmentation upstream of the first quadrupole, enabling a brand-new way to achieve the MRM³ goal. This study compared the two strategies—Q0DE vs. QTRAP system-based MRM³—using an example pharmaceutical compound, clenbuterol. The metrics used to compare the data were quantitative analysis parameters, including signal, sensitivity and linear response in a calibration curve.

Methods: A standard calibration curve with clenbuterol spiked in artificial urine matrix was analyzed using MRM³ and Q0DE MRM³. In MRM³, the effects of trap fill time with Q0 trapping both on and off were assessed to develop the best-performing MRM³ method. For the Q0DE MRM³ method, only the Q0DE parameter and collision energy (CE) needed to be optimized beyond the normal parameters for clenbuterol (source conditions, etc.). A typical MRM workflow was also included as a baseline for comparing the two MRM³ datasets. Two fragment ions and their sum were used in the quantification. The performance of different methods was assessed using LLOQ, ULOQ, %CV and linearity.

Results: The MRM quantification results—including LLOQ, ULOQ, %CV and linearity—set a baseline in this study. The Q0DE MRM³ method has only one more parameter than the MRM method, which is Q0DE voltage. The setup is similar to the MRM method setup with a table of transitions with CE/CXP and the additional Q0DE parameter. The Q0DE MRM³ results also showed data quality that was comparable to the quality of the MRM results: that is, it showed the same LLOQ at 3 pg/mL, ULQ at 100 ng/mL, a linearity range of 4.5 orders of magnitude and similar %CV in the sub-1% to mid-teen percentage. Traditional MRM³ using QTRAP system functionality, on the other hand, has quite a few more parameters to optimize, including AF2 and trap fill time, with or without Q0 trapping. The results showed that with different fill times, the LLOQ, ULQ and linear dynamic range vary. Q0 trapping also affects those end points. Overall, with Q0 trapping on and sufficient fill time, MRM³ can match the LLOQ from MRM, but with higher variability (%CV). ULOQ was also dramatically reduced, making the linear dynamic range narrower. Fill time would help improve the low-end method sensitivity, but at the same time compromise on signal integrity with saturation at the high end. All these considerations made developing a suitable MRM³ method more involved than an MRM or Q0DE MRM³ method. By comparing Q0DE MRM³ with traditional MRM³, as well as regular MRM, one can see that Q0DE MRM³ is easy to develop and has results that are comparable to MRM results. Therefore, Q0DE MRM³ should be considered a valid alternative to regular MRM that provides additional selectivity where needed, especially when there are interferences in MRM transitions.

Conclusion: Q0DE MRM³ is an easy-to-use tool for developing more selective quantitative methods that is comparable to MRM and outperforms MRM³.