(152a) Mechanistic Modeling Strategies for Lipid Nanoparticle Production

Lipid nanoparticles (LNPs) are a versatile drug delivery platform for a wide range of therapeutic modalities including nucleic acids which have received much attention for their use in the COVID-19 vaccines. Modern manufacturing processes for LNPs for nucleic acids involve rapidly mixing an organic stream containing the lipids with an aqueous stream containing the nucleic acids and are conceptually straightforward. However, detailed understanding of LNP formation and structure is still limited and scale-up can be challenging. Mathematical and computational methods are a promising avenue for deepening scientific understanding of the LNP formation process and facilitating improved process development and control. This presentation describes strategies for the mechanistic modeling of LNP formation, starting with strategies to estimate and predict important physicochemical properties of the various species such as diffusivities and solubilities. Subsequently, a framework for constructing mechanistic models of reactor-scale and particle-scale processes is outlined. Insights gained from the various models are mapped back to product quality attributes and process insights. Lastly, the use of the models to guide development of advanced process control and optimization strategies is discussed.