Investigating alternative delivery systems for self-Amplifying RNA vaccines

  • Giulia Anderluzzi

Student thesis: Doctoral Thesis


The rabies virus is an enveloped, single stranded, negative-sense RNA virus of the Lyssavirus genus, zoonotic pathogens within the family Rhabdoviridae. Although extensive effort has been made in the last decades to develop efficacious vaccines to prevent rabies spread, the virus is still responsible for the mortality of about 24,000 to 90,000 people per year especially in developing countries and it has been classified as one of the major causes of death from infectious diseases in humans.;Commercially available rabies vaccines for humans are considered effective, however the production costs are very high and multiple injections are required to achieve protection. Therefore, the development of new vaccines to reduce the toll of rabies disease in the developing world would be highly desirable. Within this project a nucleic acid based vaccine strategy - in particular self-amplifying RNA vaccine (SAM)- has been investigated since this platform was previously reported to elicit protective immune responses, particularly in the case of cell-mediated responses in a safe manner and for a variety of virus disease.;To enhance biological stability and cell internalisation, SAM was combined with four cationic delivery systems. Oil-in-water cationic nano emulsions (CNE), polymeric nanoparticles (NPs), lipid nanoparticles (SLNs) and liposomes were formulated in the absence of or in combination with a specific SAM vaccine. Despite the differences in formulation composition, all samples contained the same concentration of cationic lipid - 1, 2-dioleoyl-3-trimethylammonium-propane (DOTAP), or dimethyldioctadecylammonium (DDA) - known as immunostimulants.;In the preliminary studies, two different manufacturing processes such as Microfluidics and Microfluidisation were applied. As a proof of concept, anionic liposomes and solid lipid nanoparticles were formulated and ovalbumin was encapsulated within the delivery systems as model protein antigen. Resulting carriers were compared in terms of their physico-chemical properties. The purpose was to obtain homogeneous formulations with a diameter in the nanometres range with a given manufacturing method. Furthermore, dialysis, tangential flow filtration (TFF) and size exclusion chromatography (SEC) have been tested as purification methods and compared in terms of the ability to remove both residual organic solvent and unloaded protein from samples without altering physico-chemical attributes.;These process parameters and purification method optimisations were then applied to produce cationic CNE, NPs, SLNs and liposomes in combination with a specific SAM vaccine. In the preliminary studies and during formulations development optimisation, SAM encoding for green fluorescent protein (SAM-GFP) was used as a model SAM with a reporter function,given the ease of detection in in-vitro cell cultures. However, SAM encoding for rabies glycoprotein (SAM-Rabies) represented the actual antigen of interest, employed in this project for further in vivo analysis. Cationic SLNs, NPs and liposomes were produced using microfluidics, since this method required smaller volumes compared to the Microfluidisation, thus avoiding waste of reagents.;However, the Microfluidizer was used to reduce CNE size,due to incompatibility between CNE component and microfluidics chip. Moreover, particles were formulated with SAM encoding the antigen of interest and loaded into or adsorbed onto cationic carriers. All delivery systems were evaluated according to their physico-chemical properties: hydrodynamic radius, sample homogeneity (polydispersity index - PDI) and surface charge. Furthermore, in vitro activity was investigated using three different cell lines:bone marrow derived macrophages (BMDM), bone marrow derived dendritic cells (BMDC) and baby hamster kidney cells
Date of Award5 Mar 2020
Original languageEnglish
Awarding Institution
  • University Of Strathclyde
SponsorsUniversity of Strathclyde
SupervisorYvonne Perrie (Supervisor) & Craig Roberts (Supervisor)

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