Poly(β-amino ester) (PBAE)-based nanoparticles have emerged as promising carriers for RNA delivery, yet clear design rules linking formulation parameters to performance are still lacking. In this study, a Quality by Design (QbD)-guided and Design of Experiments (DoE)-driven approach was combined with high-throughput microfluidics to rapidly identify formulations with favorable physicochemical properties and consistent critical quality attributes (CQAs). Response Surface Modeling revealed that high total flow rates (TFR ≥ 10), nitrogen to phosphorus (N/P) ratios ≥10, and a Flow Rate Ratio (FRR) of 1 : 3 (buffer : ethanol) led to the formation of smaller, more stable particles. Among the polymers tested, a polymer candidate with a balanced composition of hydrophobic and hydrophilic side chains demonstrated optimal intraparticle stability and gene silencing performance. Notably, transfection efficiency depended strongly on formulation parameters beyond polymer type and N/P ratio, with flow rate ratio emerging as a key driver of gene knockdown kinetics. The lead formulation achieved ∼95% gene knockdown even after two weeks of storage at 4 °C. Scale-up production of the lead candidate confirmed the transferability of optimized Critical Process Parameters (CPPs) and preserved CQA profiles, validating the robustness of the design space. This study establishes a robust and scalable QbD-guided workflow for the development of microfluidically manufactured siRNA nanoparticles, enabling rapid optimization, reliable scale-up, and clinically relevant performance.

Effective pulmonary messenger RNA (mRNA) vaccination requires delivery systems capable of overcoming the airway barrier and efficiently transfecting pulmonary antigen-presenting cells. Here, we developed a hybrid polymeric system incorporating poly(lactic-co-glycolic) acid (PLGA) and poly(β-amino esters) (PBAEs) to enhance pulmonary mRNA delivery. The components acted through a spatiotemporally coordinated cascade: early PLGA hydrolysis acidified endosomes, boosting PBAE protonation and tightening mRNA condensation for protection; increased buffering, driven by accelerated protonation, strengthened proton-sponge-mediated escape; and weakened electrostatic interactions in the cytosol enabled rapid mRNA release and translation in dendritic cells, supporting immune activation. These findings highlight the need to balance endosomal escape with timely mRNA release for functional expression. The system also overcame the mucus barrier and enabled mRNA transfection in human lung tissue samples. After vibrating-mesh nebulization, it retained superior activity compared with lipid nanoparticles. These results support the PLGA/PBAE system as a viable platform for pulmonary mRNA vaccine delivery.

Biodegradable poly(β-amino) esters (PBAEs) have been a focus of interest for delivering therapeutic siRNA for several years. While no approved therapies are on the market yet, our study aims to advance PBAE-based treatments for currently "undruggable" diseases. The PBAEs used in this study are based on a recently reported step-growth copolymerization, which results in polymers with a unique balance of lipophilicity and positive charge, thereby showcasing diverse properties. Upon incubation with siRNA, these PBAEs form a unique structure and topology, which we classify as a subtype of classical polyplex, termed "micelle-embedded polyplexes" (mPolyplexes). The impact of different nebulizers on the physicochemical performance of these nanoparticles was investigated, and it was found that various mPolyplexes can be nebulized using vibrating-mesh nebulizers without the loss of gene silencing activity nor a change in physicochemical properties, setting them apart from other nanoparticles such as marketed LNPs. Finally, their therapeutic application was tested in human precision-cut lung slices from patients with lung fibrosis. mPolyplexes mediated 52% gene silencing of matrix metalloprotease 7 (MMP7) and a downstream effect on collagen I (Col I) with 33% downregulation as determined via qPCR.

The implementation of high-throughput methods for fuelling the design of effective nanocarriers for RNA delivery remains challenging. Traditional experimental screening is resource-intensive, while purely computational approaches face limitations, such as data scarcity for machine learning models and the high computational cost of molecular dynamics simulations. This work introduces a high-throughput virtual screening platform, ″Bits2Bonds,″ integrating coarse-grained molecular dynamics simulations with machine learning-driven optimization to design novel poly(β-amino ester) (PBAE) carriers for therapeutic siRNA delivery. The platform evaluates virtual polymers using MD-based ″challenges″ that simulate key hurdles in nucleic acid delivery, such as membrane and siRNA interaction (association/dissociation). The computational framework was calibrated and validated against experimental data, including synthesis and characterization of four distinct PBAEs, log measurements, siRNA encapsulation assays, and cell culture knockdown experiments. This integrated approach provides a powerful tool for the design and rapid virtual screening of optimized polymeric siRNA delivery systems.