Charged Aerosol Detectors: Superior Lipid Component Analysis During Lipid Nanoparticle Development and Quality Control

Lipid nanoparticles (LNPs) have been in the spotlight since their use in COVID-19 vaccines. These LNPs successfully encapsulate and deliver nucleic acid, with its cargo of SARS-CoV-2 spike protein determinants, into target cells. Now, many researchers are focusing their efforts on determining how else LNP-encapsulated nucleic acids can be used.

The expansive reach of the COVID-19 mRNA vaccines has brought with it stringent regulatory measures. Assessment reports issued in 2021 made it mandatory for vaccine developers to use robust analytical methods to test the quality and safety of every component in a vaccine’s formulation, ranging from lipid subtypes to pH buffer ingredients. Consequently, all emerging mRNA vaccines in the pipeline must meet these requirements to receive regulatory approval.

Analytical methods used by LNP vaccine developers must be sensitive enough to reliably detect and quantify all LNP components. High-performance liquid chromatography (HPLC), coupled with UV detection, is widely used in pharmaceutical characterization. However, most LNP components go undetected by UV because they lack chromophores.

To thoroughly characterize LNP components, laboratories require an alternative detection technique, that can capture all analytes and impurities in a single run.

Characterizing LNP formulation components

LNP formulations contain a number of excipient compounds, each contributing to the stability and structural integrity of the vaccine. Their components include:

• Buffers to maintain pH balance
• Tonicity agents to prevent osmotic shock and reduce local irritation
• Lipids, especially in mRNA vaccines, to protect the mRNA and facilitate its delivery to the cells

Individual ingredients present in the final formulation require quality control (QC) and purity checks. Analytical methods are therefore used to monitor degradation, capture and assess potential impurities and track lot-to-lot variability. However, at this stage, research teams often face a common challenge – the need to optimize multiple methods and use different instruments to analyze individual LNP components due to their chemical diversity. Piecing together data from several methods and instruments can quickly become time- and resource-intensive. The chances of inadvertent errors and unintentional oversight also increase, risking a vaccine’s regulatory status in the long run.

Laboratories benefit from using one reliable “go-to” analytical technique that can measure as many components as possible in a single run. The use of universal detectors as a catch-all approach for LNP component characterization is on the rise, with several regulatory bodies also recommending a more streamlined method.

UV detectors fall short – here’s why

HPLC has long been an essential method for separating individual LNP components. However, UV detectors have an inherent limitation that means key LNP components are not detected: they can only detect UV-active compounds that contain a chromophore. Most excipients used in LNPs, unfortunately, lack double bonds and aromatic rings. As a result, they can easily get missed during component characterization using HPLC-UV.

Additionally, one of the most integral components of LNPs – the lipids – also lack chromophores, and therefore, remain undetected using UV methods. In bypassing all lipids, the delineation of lipid subtypes that maintain the mRNA’s structure, function and stability, is also left out.

To put this into context, the LNPs used in the mRNA vaccines for SARS-CoV-2 require four types of lipids (Figure 1). For each of these lipid subtypes, reliable identification, purity assessment and ratio quantification are mandatory regulatory requirements – and beyond the scope of UV detectors.

Figure 1: Different lipid components are used in LNP-based mRNA vaccines. Here, the four types of lipids used in the COVID-19 mRNA vaccines are highlighted. Credit: Thermo Fisher Scientific.

To measure all critical quality attributes in LNP vaccines, a detector, such as an evaporative aerosol, that can identify a wide range of compounds, lipids included, as well as provide higher levels of sensitivities to catch impurities, is better suited.

Destructive detectors: Improved LNP characterization

Destructive detectors, used in conjunction with HPLC, accurately detect LNP attributes that elude UV, including lipid components. Two types of destructive detectors are common: evaporative light scattering detectors (ELSDs), and charged aerosol detectors (CADs).

Although both detectors use evaporative aerosol technology to spray dry eluents into dried particles, the method for downstream aerosol residue detection varies. ELSD uses scattered light, and a photosensitive multiplier, for analyte detection. In CAD, particles are charged by a stream of ionized nitrogen gas and detected by a sensitive electrometer. These detection methods lead to different performances – but which is better for LNP analysis?

Laboratories may turn to ELSD as an alternative to detect and quantify lipids, along with other non-chromophoric analytes. It’s worth noting, though, that the sensitivity offered by ELSD, often a point of concern for chromatographers, isn’t high enough to reliably quantify trace impurities.

CAD is a superior choice for robust LNP characterization, owing to its high sensitivity and precision. It offers improved performance in a range of applications, including the analysis of active pharmaceutical ingredients, impurities and excipients.¹ And lipid analysis is no exception. CADs offer improved dynamic range, sensitivity, linearity, accuracy and precision over ELSD.² It comes as no surprise, therefore, that many laboratories have already adopted HPLC-CAD as the method of choice for lipid analysis in mRNA-LNP vaccines and related LNP formulations.³

Evaluating CAD for lipid analysis

To evaluate whether CAD and LC can detect lipids and differentiate between its subtypes, we injected several lipid components typically used in LNP formulations into an HPLC column and passed them through a CAD detector. Within 10 minutes, the HPLC-CAD system separated – and detected – the different lipids as high-resolution peaks, along with trace impurities, demonstrating the high sensitivity of this method (Figure 2).

All four lipids could be quantified with a lower limit of detection of 10 μg/mL and over a range of more than two orders of magnitude. Achieving this level of sensitivity is necessary to monitor and control impurity levels in LNP formulations, which, in turn, determines the safety and efficacy of the vaccine.

Overall, CAD demonstrated excellent results in characterizing lipid components, making it a perfect choice to detect low-level impurities.

Figure 2: Separation of LNP formulation using the HPLC-CAD system. Using HPLC-CAD, we achieved high-resolution separation and detection of four lipids, along with trace impurities. Calibration curves for individual lipid components showed linearity and a large dynamic range. Credit: Thermo Fisher Scientific.

Reasons to switch to HPLC-CAD

To reliably capture all LNP components without concerns about analyte omissions, vaccine developers and formulation scientists benefit from coupling HPLC to CAD detectors.

Switching to CAD enables:

• Near-universal detection: CAD detects semi- and non-volatile analytes from a wide variety of chemical structures and compositions (e.g., proteins, small molecules, lipids, polymers), making it a “one-stop shop” for multi-analyte detection.
• Estimating quantity of unknown impurities without individual standards: No matter the type of analyte, if it’s non-volatile, CAD delivers a uniform response. When assessing unknown impurities, it’s possible to quantify the analyte without available standards by simply extrapolating the calibration curve of another known compound.
• “All-in-one” LNP component characterization: Streamlining LNP components characterization and impurity detection on a single system speeds up internal timelines and provides efficiency gains for the team. Oversight and omissions are also minimized, thereby boosting confidence in the characterization results.
• Regulatory compliance: Product specifications for the two COVID-19 mRNA vaccines provided by the European Medicines Agency (EMA) required lipid components to be identified and quantified using HPLC-CAD. It is likely that future vaccines or drugs employing LNPs will also require HPLC-CAD-based lipid analyses.

Drug development teams tasked with vaccine development typically demonstrate two distinctive traits: they act fast and pivot quickly. Just as prompt action and meticulous fine-tuning are encouraged in designing drug delivery systems, the same also holds for the analytical methods used to characterize them. Laboratories engaged in LNP component characterization should consider stepping away from familiar-looking detection protocols and upgrade to CAD detectors so they never miss a key component or inadvertently breach regulatory requirements.

References:

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