RP-CAD for Lipid Quantification: Systematic Method Development and Intensified LNP Process Characterization

Lipid nanoparticles (LNPs) and their versatile nucleic acid payloads bear great potential as delivery systems. Despite their complex lipid composition, their quality is primarily judged by particle characteristics and nucleic acid encapsulation. In this study, we present a holistic reversed-phase (RP)-charged aerosol detection (CAD)-based method developed for commonly used LNP formulations, allowing for intensified LNP and process characterization. We used an experimental approach for power function value (PFV) optimization termed exploratory calibration, providing a single PFV (1.3) in an appropriate linearity range for all six lipids. Followed by the procedure of method calibration and validation, linearity (10-400 ng, <i>R</i><sup>2</sup> > 0.996), precision, accuracy, and robustness were effectively proven. To complement the commonly determined LNP attributes and to evaluate the process performance across LNP processing, the developed RP-CAD method was applied in a process parameter study varying the total flow rate (TFR) during microfluidic mixing. The RP-CAD method revealed a constant lipid molar ratio across processing but identified deviations in the theoretical lipid content and general lipid loss, which were both, however, entirely TFR-independent. The deviations in lipid content could be successfully traced back to the lipid stock solution preparation. In contrast, the observed lipid loss was attributable to the small-scale dialysis following microfluidic mixing. Overall, this study establishes a foundation for employing RP-CAD for lipid quantification throughout LNP processing, and it highlights the potential to extend its applicability to other LNPs, process parameter studies, or processes such as cross-flow filtration.

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Publication Details

Journal
Pharmaceuticals
Published
2024-09-16
DOI
https://doi.org/10.3390/ph17091217
Citations
4
Primary Topic
Microfluidic and Bio-sensing Technologies
Type
article
Field-Weighted Citation Impact
0.74

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article

RP-CAD for Lipid Quantification: Systematic Method Development and Intensified LNP Process Characterization

Nicole Beckert, Annabelle Dietrich, Jürgen Hubbuch
4 citations
Pharmaceuticals
Microfluidic and Bio-sensing Technologies
0.74
article

RP-CAD for Lipid Quantification: Systematic Method Development and Intensified LNP Process Characterization

Nicole Beckert, Annabelle Dietrich, Jürgen Hubbuch
article en
4 citations

Abstract

Lipid nanoparticles (LNPs) and their versatile nucleic acid payloads bear great potential as delivery systems. Despite their complex lipid composition, their quality is primarily judged by particle characteristics and nucleic acid encapsulation. In this study, we present a holistic reversed-phase (RP)-charged aerosol detection (CAD)-based method developed for commonly used LNP formulations, allowing for intensified LNP and process characterization. We used an experimental approach for power function value (PFV) optimization termed exploratory calibration, providing a single PFV (1.3) in an appropriate linearity range for all six lipids. Followed by the procedure of method calibration and validation, linearity (10-400 ng, <i>R</i><sup>2</sup> > 0.996), precision, accuracy, and robustness were effectively proven. To complement the commonly determined LNP attributes and to evaluate the process performance across LNP processing, the developed RP-CAD method was applied in a process parameter study varying the total flow rate (TFR) during microfluidic mixing. The RP-CAD method revealed a constant lipid molar ratio across processing but identified deviations in the theoretical lipid content and general lipid loss, which were both, however, entirely TFR-independent. The deviations in lipid content could be successfully traced back to the lipid stock solution preparation. In contrast, the observed lipid loss was attributable to the small-scale dialysis following microfluidic mixing. Overall, this study establishes a foundation for employing RP-CAD for lipid quantification throughout LNP processing, and it highlights the potential to extend its applicability to other LNPs, process parameter studies, or processes such as cross-flow filtration.

PharmaceuticalsVol. 17(9)
Karlsruhe Institute of Technology (DE)
Karlsruhe Institute of Technology, Electronic Components and Systems for European Leadership, Horizon 2020 Framework Programme
Openalex Percentile: Top 32%
Microfluidic and Bio-sensing Technologies
0.74
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