(471g) Engineering-Driven Application of Quality By Design to the Gmma Platform: Enabling the Production of Affordable and Effective Vaccines for Low and Middle Income Countries

Gram-negative bacteria naturally shed outer membrane vesicles (OMV) during growth. GMMA (Generalized Modules for Membrane Antigens) derive from bacteria engineered to enhance native OMV formation and to reduce GMMA reactogenicity. The GMMA surface is a representation of the outside of the bacteria, with multiple membrane antigens presented to the immune system in their native conformation and correct orientation (1,2). Large body of preclinical data shows that GMMA are highly immunogenic and elicit substantially higher antibody responses against key vaccine candidate antigens, whether these are polysaccharide or protein moieties, compared with corresponding purified antigens delivered as glycoconjugate vaccines or recombinant formulations (3).

GMMA is produced by bacterial fermentation with simple filtration-based downstream processing. Such process has been already scaled-up for producing GMP-quality GMMA at large scale for Shigella sonnei and nontyphoidal Salmonella, pathogens of particular relevance for LMIC. The most advanced GMMA-based vaccine is S. sonnei, already tested in clinical trials showing to be safe and immunogenic in adults (4,5).

In this work we present a techno-economic analysis of the GMMA production process, using SuperPro Designer. We investigate different operating scenarios and scales and monitor their impact on operational and capital costs of the facility. Current efforts are focused on a systematic and quantitative identification of quality attribute-process parameter relationships based on first-principles and data-driven modelling. We will present an illustrative example for such an implementation of Quality by Design principles to the separation unit of tangential flow filtration. The latter is based on independent experimental runs under varying conditions that indicate critical process parameters and allow for a thorough risk assessment. Lastly, we demonstrate a science-driven framework to assist with: (a) identification of the critical quality attributes & critical process parameters and (b) quantification of the impact of the critical processes parameters on the monitored attributes.

Deep process understanding combined to a robust analytical control strategy will support sustainable manufacturing of safe and efficacious GMMA based vaccines, focusing on both product quality and process performance.

1. Gerke C, et al. PLoS One. 2015 Aug 6;10(8):e0134478.
2. De Benedetto G, et al. Vaccine. 2017 Jan 11;35(3):419-426.
3. Micoli F, et al. Proc Natl Acad Sci U S A. 2018 Oct 9;115(41):10428-10433.
4. Launay O, et al. EBioMedicine. 2017 Aug;22:164-172.
5. Obiero CW, et al. Front Immunol. 2017 Dec 22;8:1884.