Exploring lipid nanoparticle design spaces using self-regulating microfluidic machines and multiplexed in vivo biodistribution

Delivering therapeutic mRNA relies on lipid nanoparticles (LNPs). Finding optimal process parameters for new lipid combinations in LNP formulations remains a challenge. We used an automated, self-regulating microfluidic formulation platform developed for PEG-containing LNPs that actively changes process parameters to meet preset LNP diameters, and now explore how this automated production setup can be expanded to LNPs decorated with poly(2-oxazoline) (POx)-lipids. We also examine how the choice of lipopolymer affects the resulting physicochemical properties and in vivo biodistribution of the resulting LNPs. For that, we tested new LNPs by swapping poly(ethylene glycol) (PEG) lipopolymers for alternatives based on poly(2-methyl-2-oxazoline) (PMeOx) and poly(2-ethyl-2-oxazoline) (PEtOx). For both POx-lipid variants, the platform independently identified optimal production conditions in four or fewer iterative cycles, yielding particles of the preset size and high mRNA encapsulation. Small-angle X-ray scattering revealed that smaller LNPs modified with PEtOx had greater structural surface variety and higher mRNA loading efficiency. When multiplexing these formulations in mice, the PEtOx-containing LNPs accumulated more in bone marrow and liver (and less in spleen and pancreas), compared to those with PEG, indicating trends that the chemistry of the lipopolymer affects the biodistribution of the resulting LNPs. By combining automated formulation and in vivo multiplexed testing, our approach provides a practical way to rapidly plan, formulate, and evaluate large pharmaceutical design spaces to select excipients and process parameters yielding optimal biological performance of LNPs.

Abstract from PubMed (PMID 42977225). This entry was added automatically by our daily literature monitor because it matches the topics we follow; read the full paper at the original source.