Development and validation of a high-performance liquid chromatography coupled to charged-aerosol detection method for the quantification of lipids in COVID-19 nanoparticle formulations

Introduction: Lipid nanoparticles (LNPs) are complex formulations of phospholipids and other lipids, used in RNA transfection, including COVID-19 vaccines.These formulations contain key components such as positively charged or ionizable lipids, along with uncharged helper lipids.The varying charges of these lipids pose challenges for their simultaneous detection and quantification.Objectives: This study aimed to develop a reliable method for analyzing lipids in COVID-19 LNPs using high-performance liquid chromatography coupled with a charged aerosol detector (RP-HPLC-CAD).Methodology: A C-18 column was used for the analysis of four key lipids in the vaccine formulation.The experimental design involved varying concentrations of trifluoroacetic acid (TFA) in acetonitrile (ACN), methanol, or water as mobile phases A and B, with some experiments omitting a mobile phase C. Lipid mixtures and individual lipids were prepared at 0.5 mg/mL concentration in methanol or ethanol, and samples included a 9-point calibration curve for the ionizable lipid and two LNP samples.Various mobile phases, nebulization temperatures, and gradient profiles were tested, with run times between 20 to 29 minutes.Most experiments were conducted at 70C nebulization temperature, while others were done at 50C.Each sample was injected once with 8 L volume.The CAD detection rate was set at 10 Hz, and the column temperature was maintained at 50C.Data analysis was performed using Chromeleon 7.3.2software. Results:Results showed that mobile phases with methanol and water and TFA concentrations of 0.1% and 0.15%, respectively, provided optimal lipid separation.A gradient was successfully developed to separate the four lipids in the formulation.The ionizable lipid calibration curve exhibited linearity with an R value above 0.99.Quantification of the ionizable lipid in all tested samples showed efficiencies of 56% and 97% for the LNPs. Conclusion:The study concludes that the HPLC-CAD method effectively analyzed lipids in COVID-19 LNPs, establishing a linear calibration curve for the ionizable lipid and enabling its quantification.Future work will focus on developing a calibration method for all lipids per ICH-Q2 (R2) guidelines, ensuring accuracy, precision, specificity, and a defined working range, including determining the limit of detection (LOD), limit of quantification (LOQ), and calibration range.