Quantification of 28 neuroleptics in human plasma by LC-HRAM-MS for clinical research
Applications | 2021 | Thermo Fisher ScientificInstrumentation
Antipsychotic drugs (neuroleptics) are essential for managing psychotic disorders such as schizophrenia. Reliable quantification in plasma at low ng/mL concentrations supports clinical pharmacokinetics, therapeutic drug monitoring, and adverse effect assessment.
This study describes the development and analytical validation of a rapid LC–HRAM–MS method for simultaneous quantification of 28 neuroleptics in human plasma. The approach uses stable isotope internal standards and covers low to mid ng/mL concentration ranges.
Sample preparation:
Chromatography:
Mass spectrometry:
Calibration was linear (1/x weighting) for 27 analytes; norclozapine used a quadratic fit. LLOQs ranged from 0.59 to 37.1 ng/mL. Calibration bias was within ±10%, intra- and inter-assay precision (%CV) < 8%. No significant carryover was observed. Representative chromatograms and calibration plots confirmed selectivity and sensitivity.
Advances may include expansion to larger analyte panels, integration of microflow UHPLC and ion mobility, AI-driven data processing, and full automation for high-throughput therapeutic monitoring and metabolic profiling.
The developed LC–HRAM–MS method is robust, rapid, and validated for 28 neuroleptics in human plasma, meeting clinical research requirements for sensitivity, accuracy, and precision.
LC/HRMS, LC/MS, LC/MS/MS, LC/Orbitrap
IndustriesClinical Research
ManufacturerThermo Fisher Scientific, RECIPE
Summary
Importance of the Topic
Antipsychotic drugs (neuroleptics) are essential for managing psychotic disorders such as schizophrenia. Reliable quantification in plasma at low ng/mL concentrations supports clinical pharmacokinetics, therapeutic drug monitoring, and adverse effect assessment.
Objectives and Overview
This study describes the development and analytical validation of a rapid LC–HRAM–MS method for simultaneous quantification of 28 neuroleptics in human plasma. The approach uses stable isotope internal standards and covers low to mid ng/mL concentration ranges.
Methodology
Sample preparation:
- Aliquot 50 µL plasma.
- Add 100 µL acetonitrile with internal standards for protein precipitation.
- Centrifuge and dilute supernatant 10-fold in aqueous mobile phase.
Chromatography:
- Vanquish Flex Binary UHPLC with Hypersil GOLD 2.1 × 50 mm, 1.9 µm column at 40 °C.
- Gradient elution (0.1% formic acid in water/methanol) over a 5.5 min run at 0.4 mL/min.
Mass spectrometry:
- Orbitrap Exploris 120 with heated electrospray (HESI) positive ionization.
- Full MS–ddMS2 acquisition at 60 000 resolution (m/z 100–500).
- Ion source: 350 °C vaporizer, 300 °C transfer tube, 3 500 V capillary voltage.
Used Instrumentation
- Thermo Scientific Orbitrap Exploris 120 MS.
- Thermo Scientific Vanquish Flex Binary UHPLC.
- Thermo Scientific Hypersil GOLD 2.1 × 50 mm, 1.9 µm column.
- Thermo Scientific TraceFinder 5.1 software.
Main Results and Discussion
Calibration was linear (1/x weighting) for 27 analytes; norclozapine used a quadratic fit. LLOQs ranged from 0.59 to 37.1 ng/mL. Calibration bias was within ±10%, intra- and inter-assay precision (%CV) < 8%. No significant carryover was observed. Representative chromatograms and calibration plots confirmed selectivity and sensitivity.
Benefits and Practical Applications
- Fast analysis: 5.5 min run time.
- Simple, offline protein precipitation sample prep.
- High-resolution accurate-mass detection for improved selectivity.
- Sensitivity suitable for low ng/mL quantitation in clinical research.
Future Trends and Potential Uses
Advances may include expansion to larger analyte panels, integration of microflow UHPLC and ion mobility, AI-driven data processing, and full automation for high-throughput therapeutic monitoring and metabolic profiling.
Conclusion
The developed LC–HRAM–MS method is robust, rapid, and validated for 28 neuroleptics in human plasma, meeting clinical research requirements for sensitivity, accuracy, and precision.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
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