Recent breakthroughs in messenger RNA (mRNA) therapeutics have highlighted the importance of lipid nanoparticles (LNPs) as delivery vehicles that protect fragile mRNA and facilitate cellular uptake. While manufacturing technologies that rely on self-assembly through mixing, including microfluidic systems and turbulent jet mixers, have enabled scalable production, a first-principles model explaining the fundamental mechanisms responsible for LNP size and its distribution has remained elusive. This has limited predictive process control and optimization. To address this gap, we present here a model based on crystallization of a lipid during turbulent mixing of water-ethanol, employing population balance equations to predict particle size distributions. The model successfully predicts the influence of key operating parameters including total flow rate, flow rate ratio, and lipid concentration, demonstrating favorable comparison with experimental results and enabling the development of predictive manufacturing processes for consistent critical quality attributes. The mechanistic understanding provides the foundation necessary to optimize manufacturing of LNPs used as delivery agents of mRNA vaccines, which extends beyond the current application to the broader field of nucleic acid therapeutics.
