Engineering of Solid Dosage Forms of siRNA-Loaded Lipidoid-Polymer Hybrid Nanoparticles Using a Quality-by-Design...

Therapy based on RNA interference (RNAi), which can be mediated by exogenous small interfering RNA (siRNA), has potential for the management of diseases at the genetic level by silencing gene function(s). In all eukaryotic cells, RNAi is an endogenous regulatory mechanism, where messenger RNA (mRNA) is degraded, preventing its translation into protein. A significant advantage of RNAi therapy is that siRNA is very potent and gene silencing is highly specific, ensuring few off-target effects. However, the delivery of exogenous siRNA to the RNAi pathway in the cytosol is a challenge, and there is a need for development of advanced delivery systems to ensure safe and effective delivery of siRNA to the intracellular target site. Recently, we demonstrated the ability of lipid-polymer hybrid nanoparticles (LPNs) composed of cationic lipidoid 5 (L₅) and the biodegradable polymer poly(DL-lactic-co-glycolic acid) to effectively deliver siRNA directed against tumor necrosis factor alpha (TNF-α) intracellularly to macrophages. L₅ is a novel lipid-like material consisting of a tetraamine backbone linked to five C₁₂ alkyl chains. Here, we describe a systematic quality-by-design (QbD) approach including risk assessment and design of experiments to investigate the influence of critical formulation parameters (i.e., L₅ content and L₅:TNF-α siRNA ratio (w/w)) on the physicochemical properties and the TNF-α gene silencing ability of TNF-α siRNA-loaded LPNs, prepared by using a double emulsion solvent evaporation method. We then detail protocols for the manufacturing of more stable solid dosage forms of LPNs using freeze drying and spray drying processes, respectively. We also provide protocols for characterization of the physicochemical properties of the nanocomposite dry powders, including (1) process yield, (2) aerodynamic particle size, (3) surface morphology, (4) moisture content, and (5) solid state properties. General considerations are provided that emphasize the advantages and disadvantages of applying QbD approaches for optimizing nanoparticulate formulations.