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In the last five years, our focus has been to develop tools and platform technologies for rapid development and seamless scale-up of nanomedicines for clinical applications. Previously, we presented data showing development of Factor VII siRNA lipid nanoparticles (LNPs) on microfluidic-based NanoAssemblr™ platform. We optimized the formulation at the 2-10 mL scale on the NanoAssemblr™ Benchtop and scaled it up to 100 mL on the NanoAssemblr™ Blaze and then 1000 mL on the 8X Scale-up System. We demonstrated that the NanoAssemblr™ platform provides seamless scale-up and can produce large-scale volumes of lipid nanoparticles with consistent results.
The genetic medicine field is quickly evolving to adopt mRNA-based therapeutics for genetic editing, immunotherapy and gene replacement therapies. In this year’s annual meeting, we will be presenting the development and scale-up of luciferase mRNA LNPs on the NanoAssemblr™ platform. We will optimize the formulation on the NanoAssemblr Benchtop™ at 1-10 mL and scale it up 10X on the NanoAssemblr Blaze and then 100X on 8X Scale-up System. Particle size and polydispersity index will be determined using dynamic light scattering (DLS) technique. RiboGreen Assay will be used to determine encapsulation efficiency. UPLC methods has been developed to analyze mRNA, lipid composition and determine amine to phosphate (N/P) ratio of the formulation. We will also optimize the downstream processing using tangential flow filtration (TFF) for buffer exchange and concentration of mRNA. Finally, the particles will be injected in mice intravenously and gene expression will be determined using luciferase activity (bioluminescence) in a IVIS imaging system.
In agreement to our previous findings with siRNA LNPs, these studies will demonstrate that the NanoAssemblr™ platform provides seamless scale-up and can produce large-scale volumes of mRNA LNPs with consistent results. The 8X Scale-Up system can prepare up to 25 L of product in under 4.5 hours at 96 mL/min and incorporates a disposable fluid path that eliminates the need for costly and time-consuming cleaning validation.