Chromatographic study of nucleoside-lipids by RP-UHPLC-DAD/CAD

A rapid and quantitative reversed-phase HPLC-DAD/ELSD method for lipids involved in nanoparticle formulations

Lipid nanoparticles (LNPs) have shown great success as drug delivery systems, especially for mRNA vaccines, as those developed during the Covid-19 pandemics. Lipid analysis is critical to monitor the formulation process and control the quality of LNPs. The present study is focused on the development and validation of a high-performance liquid chromatography – diode array detector –evaporative light scattering detector (HPLC-DAD/ELSD) based method for the simultaneous quantification of 7 lipids, illustrating the main components of LNPs: ionizable lipids, the neutral co-lipid cholesterol, phospholipids, hydrophilic polymer-lipids for colloidal stability (e.g., a PEGylated lipid). In particular, this study focuses on two innovative synthetic lipids: a switchable cationic lipid (CSL3) which has demonstrated in vitro and in vivo siRNA transfection abilities, and the palmitic acid-grafted-poly(ethyloxazoline)₅₀₀₀ (PolyEtOx), used as an alternative polymer to address allergic reactions attributed to PEGylated lipids. The HPLC separation was achieved on a Poroshell C18 column at 50 °C using a step gradient of a mobile phase composed of water/methanol mixtures with 0.1% (v/v) trifluoroacetic acid (TFA). This method was validated following ICH Q2(R1) & (R2) guidelines in terms of linearity (R² ≥ 0.997), precision (relative standard deviation on peak areas < 5% for intermediate repeatability), accuracy (recoveries between 92.9% and 108.5%), and sensitivity. Indeed, low detection and quantitation limits were determined (between 0.02 and 0.04 µg and between 0.04 and 0.10 µg, respectively). Due to its high selectivity, this method allowed the analysis of lipid degradation products produced through degradation studies in basic, acidic, and oxidative conditions. Moreover, the method was successfully applied to the analysis of several liposome formulations at two key steps of the development process. Consequently, the reported HPLC method offers fast, versatile, selective and quantitative analysis of lipids, essential for development optimization, chemical characterization, and stability testing of LNP formulations.

Oligonucleotide Solid Nucleolipid Nanoparticles against Antibiotic Resistance of ESBL-Producing Bacteria

Antibiotic resistance has become a major issue in the global healthcare system, notably in the case of Gram-negative bacteria. Recent advances in technology with oligonucleotides have an enormous potential for tackling this problem, providing their efficient intrabacterial delivery. The current work aimed to apply this strategy by using a novel nanoformulation consisting of DOTAU, a nucleolipid carrier, in an attempt to simultaneously deliver antibiotic and anti-resistance oligonucleotides. Ceftriaxone, a third-generation cephalosporin, was formulated with DOTAU to form an ion pair, and was then nanoprecipitated. The obtained solid nanocapsules were characterized using FT-IR, XRD, HPLC, TEM and DLS techniques and further functionalized by the anti-resistance ONα sequence. To obtain an optimal anti-resistance activity and encapsulation yield, both the formulation protocol and the concentration of ONα were optimized. As a result, monodispersed negatively charged nanoparticles of CFX-DOTAU-ONα with a molar ratio of 10:24:1 were obtained. The minimum inhibitory concentration of these nanoparticles on the resistant Escherichia coli strain was significantly reduced (by 75%) in comparison with that of non-vectorized ONα. All aforementioned results reveal that our nanoformulation can be considered as an efficient and relevant strategy for oligonucleotide intrabacterial delivery in the fight against antibiotic resistance.

Charged aerosol detection in early and late-stage pharmaceutical development: selection of regressionmodels at optimum power function value

In recent years, the use of quantitative liquid chromatography (LC) coupled charged aerosol detection (CAD) for poor UV absorbing analytes in multicomponent mixtures has grown exponentially across academic and industrial sectors. The ballpark of previous LC-CAD reports is focused on practical applications, as well as optimization of critical parameters such as: response dependencies on temperature, nebulization process, analyte volatility, and mobile-phase composition. However, straightforward approaches to deal with the characteristic nonlinear response of CAD still scarce. A highly overlooked parameter is the power function value (PFV), whose optimization enables a detection signal that is more linear with higher signal-to-noise ratio (S/N) and lower relative standard deviation (RSD) of area counts. Herein, a systematic investigation of different regression models (log-log, first-and second-degree polynomial) by both interpolation and extrapolation process in conjunction with PFV optimization throughout the development of LC-CAD assays is reported. The accuracy of the results via interpolation is always good (< 5%) when operating in the vicinity of the optimum PFV regardless the regression model choice. On the contrary, extrapolation process only worked when applying log-log regression at the optimum PFV (accuracy <5%). This outcome indicates that a first-order regression via interpolation can be a safe and simple choice for quantitative LC-CAD in highly regulated laboratories (GLP, GMP, etc.). Whereas a straightforward extrapolation combined with log-log regression can enable the deployment of high-throughput LC-CAD assays, especially but not limited to laboratories where the synthetic process route is undergoing rapid change and optimization (medicinal chemistry, discovery, biocatalysis, process chemistry, etc.). This approach is crucial in developing quantitative LC-CAD assays for poor UV absorbing pharmaceuticals that are sensitive, precise, accurate and robust across early and late-stage pharmaceutical development.