Lipid nanoparticles (LNPs) have been employed for drug delivery in small molecules, siRNA, mRNA, and pDNA for both therapeutics and vaccines. Characterization of LNPs is challenging because they are heterogeneous mixtures of large complex particles. Many tools for particle size characterization, such as dynamic and static light scattering, have been applied as well as morphology analysis using electron microscopy. CE has been applied for the characterization of many different large particles such as liposomes, polymer, and viruses. However, there have been limited efforts to characterize the surface charge of LNPs and CIEF has not been explored for this type of particle. Typically, LNPs for delivery of oligonucleotides contain at least four different lipids, with at least one being an ionizable cationic lipid. Here, we describe the development of an imaged capillary isoelectric focusing method used to measure the surface charge (i.e., pI) of an LNP‐based mRNA vaccine. This method is capable of distinguishing the pI of LNPs manufactured with one or more different ionizable lipids for the purpose of confirming LNP identity in a manufacturing setting. Additionally, the method is quantitative and stability‐indicating making it suitable for both process and formulation development.

Direct at line monitoring of live virus particles in commercial manufacturing of vaccines is challenging due to their small size. Detection of malformed or damaged virions with reduced potency is rate-limited by release potency assays with long turnaround times. Thus, preempting batch failures caused by out of specification potency results is almost impossible. Much needed are in-process tools that can monitor and detect compromised viral particles in live-virus vaccines (LVVs) manufacturing based on changes in their biophysical properties to provide timely measures to rectify process stresses leading to such damage. Using ERVEBO, MSD’s Ebola virus vaccine as an example, here we describe a flow virometry assay that can quickly detect damaged virus particles and provide mechanistic insight into process parameters contributing to the damage. Furthermore, we describe a 24-h high throughput infectivity assay that can be used to correlate damaged particles directly to loss in viral infectivity (potency) in-process. Collectively, we provide a set of innovative tools to enable rapid process development, process monitoring, and control strategy implementation in large scale LVV manufacturing.

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