As vaccine technologies continue to evolve, from cutting-edge mRNA platforms to viral vectors and protein subunits, so must the strategies used to ensure their safety, efficacy, and consistency.
In this expert Q&A, Dr Arnaud Delobel of Quality Assistance shares insights into the analytical foundations of vaccine quality control. He discusses the tools used to characterize complex formulations, how to validate methods for novel modalities, and where the field is headed next.
What are the most critical analytical methods currently used in vaccine QC, and how do these differ across platforms?
It depends on the type of vaccine. For mRNA vaccines, key QC techniques include capillary electrophoresis (CE), liquid chromatography (LC), and dynamic light scattering (DLS) to assess mRNA integrity, purity, and lipid nanoparticle (LNP) characteristics. Mass spectrometry (MS) is also used for sequence confirmation and detecting degradation products.
In the case of viral vectors, quantitative polymerase chain reaction (qPCR) or droplet digital PCR (ddPCR) is used for genome quantification, and enzyme-linked immunosorbent assay (ELISA) or infectivity assays assess functionality. Mass spectrometry (MS) plays a role in characterizing capsid proteins and identifying residual host cell proteins.
For protein subunit vaccines, reversed-phase, size-exclusion, and ion-exchange chromatography (RPC, SEC, and AEX, respectively) are central to QC workflows. MS supports protein identification, purity checks, and glycan profiling. While there is some overlap in techniques, each platform requires a tailored QC strategy based on its unique analytical priorities.
What role does mass spectrometry play in vaccine QC workflows, and how has its application evolved in recent years?
MS has become a cornerstone of vaccine analysis. In QC, it is widely used for identity confirmation through intact mass or peptide mapping, as well as impurity profiling to detect truncated proteins, enzymes, or degradation products.
MS is also crucial for glycan analysis, including sialic acid profiling, which informs on vaccine efficacy and stability. Recent advances include multi-attribute methods (MAM), where MS is used to monitor several critical quality attributes (CQAs) in a single run. There is also emerging interest in native MS and top-down proteomics.
MS has evolved from a supportive tool to an essential component of comprehensive QC strategies.
What are the key challenges when validating QC methods for regulatory approval, particularly for new modalities?
One major challenge is the lack of established regulatory precedents for novel modalities such as mRNA or gene therapy vectors. Developers must navigate undefined expectations.
These products are often complex, requiring highly sensitive and specific methods that are also robust and reproducible across manufacturing sites and batches. Preparing a complete validation package involves demonstrating consistent method performance under varied conditions and the ability to detect subtle but meaningful changes.
At Quality Assistance, we employ a risk-based approach, focusing on the most critical attributes and design validation plans that are both scientifically sound and practically executable.
How do you approach defining and measuring CQAs for vaccines?
We collaborate closely with sponsors to define CQAs, drawing on their understanding of the product and manufacturing process. Our role is to ensure that these attributes can be reliably measured using appropriate analytical techniques.
We often apply complementary methods to gain a full picture. Some CQAs are particularly difficult to assess. For example, encapsulation efficiency and lipid composition in LNP-based mRNA vaccines, as well as glycosylation and post-translational modifications in protein-based vaccines. Potency assays can also be highly variable and require extensive optimization.
Strong collaboration and a thoughtful, science-driven approach are essential.
What are the analytical considerations when assessing nanoparticle stability and performance?
Lipid nanoparticles are sensitive and dynamic structures, making their analysis technically demanding. Particle size and distribution are typically measured using DLS or nanoparticle tracking analysis (NTA). Encapsulation efficiency, a critical parameter, is often assessed using separation techniques coupled with fluorescence or qPCR.
Additional parameters include zeta potential, which informs on stability, and lipid chemical stability, which is monitored using LC coupled with charged aerosol detection (LC-CAD), LC-MS, or gas chromatography with MS (GC-MS). Because LNP characteristics can shift over time or under different storage conditions, a robust and sensitive analytical toolbox is necessary.
In what contexts are glycan profiling and sialic acid analysis most impactful?
Glycan profiling is crucial for glycoprotein-based vaccines, including protein subunit vaccines and viral vectors with glycosylated capsid proteins. Glycan structure can influence product stability, efficacy, and immune response.
Sialic acid content, in particular, affects circulation half-life and immune clearance. This type of analysis is especially valuable in the following cases:
During comparability studies following a process change
In stability studies, to detect glycosylation shifts
When developing biosimilars that must closely match reference products
LC/MS is the primary tool used for detailed glycan and sialic acid analysis.
Are advanced approaches such as real-time release testing, automation, or machine learning being integrated into QC workflows?
Yes. Real-time release testing (RTRT) is gaining traction, especially in continuous manufacturing environments. It enables faster batch release and better process control.
Automation, particularly in sample preparation, helps reduce variability and increase throughput. Machine learning offers the potential to analyze complex datasets, identify trends, and predict product quality.
However, adoption comes with challenges, including regulatory acceptance, high implementation costs, and the need for historical data to build robust models. Despite these barriers, these technologies are gradually being integrated and are expected to become standard in the coming years.
What advice would you offer to scientists developing QC strategies for next-generation vaccines?
Integrate QC early in development. A strong understanding of the product and its CQAs allows for the development of effective, fit-for-purpose QC methods.
Use orthogonal analytical approaches. They may require more work upfront, but they significantly strengthen validation packages and regulatory submissions.
Where possible, invest early in high-resolution tools, such as MS and CE, to build in-depth product knowledge. Finally, stay informed about evolving regulatory expectations, especially as new modalities continue to emerge.
Conclusion: The Future of Vaccine Quality Control
Vaccine development is evolving at a rapid pace, and so is the science behind vaccine quality control. From ensuring the structural integrity of complex biologics to leveraging cutting-edge tools such as mass spectrometry and real-time analytics, today’s QC workflows are smarter, faster, and more comprehensive than ever.
As these technologies mature, they’re not just keeping up with innovation; they’re helping to drive it, setting the stage for more efficient production and safer, more effective vaccines worldwide.
