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A statistical approach to optimizing paper spray mass spectrometry parameters.

Christine Skaggs1, Lindsey Kirkpatrick2, William R A Wichert1

  • 1Department of Chemistry and Chemical Biology, Indiana University-Purdue University Indianapolis, Indianapolis, IN, 46202, USA.

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Optimizing paper spray mass spectrometry (PS-MS) for ampicillin analysis significantly improved signal intensity. This method enhances the detection of hydrophilic antibiotics like ampicillin.

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Area of Science:

  • Analytical Chemistry
  • Mass Spectrometry
  • Pharmaceutical Analysis

Background:

  • Paper spray mass spectrometry (PS-MS) is challenging for hydrophilic compounds like ampicillin due to substrate binding and low ionization.
  • Ampicillin, a widely used antibiotic, presents analytical difficulties with traditional PS-MS.

Purpose of the Study:

  • To optimize paper spray mass spectrometry (PS-MS) for the analysis and quantification of ampicillin.
  • To overcome the limitations of analyzing hydrophilic compounds using PS-MS.

Main Methods:

  • Optimization of solvent and paper parameters for ampicillin extraction.
  • Utilized a Resolution IV 1/16 fractional factorial design to screen eight parameters.
  • Statistical screening and optimization experiments were performed.

Main Results:

  • Pore size, sample volume, and solvent volume were identified as critical factors influencing peak area and signal-to-blank ratio.
  • Achieved a linear calibration curve (R² = 0.98) from 0.2 to 100 μg/mL.
  • Determined limit of detection (LOD) at 0.07 μg/mL and lower limit of quantification (LLOQ) at 0.25 μg/mL.

Conclusions:

  • The statistical optimization significantly enhanced mass spectral signal intensity by over 40-fold.
  • This statistical approach proved more efficient and effective than traditional one-factor-at-a-time methods.
  • Demonstrated a robust PS-MS method for hydrophilic antibiotic analysis.