A statistical approach to optimizing paper spray mass spectrometry parameters.

Rationale: Paper spray mass spectrometry (PS-MS) was used to analyze and quantify ampicillin, a hydrophilic compound and frequently utilized antibiotic. Hydrophilic molecules are difficult to analyze via PS-MS due to their strong binding affinity to paper substrates and low ionization efficiency, among other reasons.

Methods: Solvent and paper parameters were optimized to increase the extraction of ampicillin from the paper substrate. After optimizing these key parameters, a Resolution IV 1/16 fractional factorial design with two center points was employed to screen eight different design parameters simultaneously.

Results: Pore size, sample volume, and solvent volume were the most significant factors affecting average peak area under the curve (AUC) and the signal-to-blank (S/B) ratio for the 1 μg/mL ampicillin calibrant. After optimizing the key parameters, a linear calibration curve with a range of 0.2 μg/mL to 100 μg/mL was generated (R  = 0.98) and the limit of detection (LOD) and lower limit of quantification (LLOQ) were calculated to be 0.07 μg/mL and 0.25 μg/mL, respectively.

Conclusions: The statistical optimization procedure undertaken here increased the mass spectral signal intensity by more than a factor of 40. This statistical method of screening followed by optimization experiments proved faster and more efficient, and produced more drastic improvements than typical one-factor-at-a-time experiments.