Up and Down Stream Bioprocessing for viral vector production
Properly skilled and trained research professionals are paramount to stimulate ongoing innovations in viral vector-based gene therapy development, and to ensure their effective implementation in industrial and clinical settings. As explained below, each Doctoral Candidate (DC) has a specific assignment with a dedicated focus.
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In WP1 we will develop highly innovative advances in the field of viral vector technology and production. We aim to identify and subsequently modulate key cellular pathways of producer cell lines to increase the basic production efficiency. In parallel, we will optimize the manufacturing process through digital twin simulations, application of 3D printing and development of new, rapid methods for quality control of the produced viral vectors.
DC1 will study cellular pathways in producer cells to improve vector production efficiency. DC1 will also optimize the manufacturing environment to facilitate large-scale production, with a lower footprint, at a better cost and, in a closed system. Finally, DC1 will evaluate high-density custom designed 3D printed fixed beds for adherent cell culture and viral vector production.
The development of new techniques is required to ensure reliability in the large-scale manufacture of rAAV gene therapies. Key critical quality attributes (CQAs) such as viral genome titre, number of viral particles and capsid content need to be assessed during and after production to monitor the manufacturing process and define the potency, purity and safety of the final gene therapy product. However, the analytical methods used to assess these CQAs are slow or low-throughput. DC3 will generate standard materials to develop and validate new analytical techniques that will feed back into the production process to expedite process development and to adapt the assays to pharma standards.
rAAV manufacturing is still heavily reliant on heuristic optimisation methods. Variability in raw material and lack of automation translates in significant process variation, complicating industrial translation of the manufacturing process. DC8 will develop a digital twin that will enable the use of sophisticated Process Systems Engineering methodologies for model-based optimization of upstream unit operations in rAAV manufacturing. In addition, a set of computational decision tools based on a ‘whole-process’ model will be developed for the design and economic assessment of cost-effective and scalable rAAV manufacturing processes in collaboration with SPSE (DC7). While the focus will be on rAAV production, the same process systems engineering methodologies can help navigate the complex multi-parametric optimization of VLP production (DC5, DC6, DC9).