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Laboratory work for GET-IN doctoral network

Doctoral Candidate 7

Development of a computational platform for cost-effective and scalable rAAV production


Host institution of GET-IN the University of Thessaloniki

Host institution: Aristotle University of Thessaloniki (AUTh), Greece

Supervisory team: Prof. Alexandros Kiparissides (PhD promoter, AUTh), Dr. Jan Schrooten (Antleron), Dr. Sarah Fadda (Siemens Process Systems Engineering)


As the number of commercially available treatments increases so does the demand for synthetic and virus-based gene delivery systems. Adeno-associated viruses (AAV), which are small non-enveloped viruses, have emerged as the leading platform for gene delivery due to their excellent safety profile and efficient transduction to various target tissues. However, in order to meet increasing global demand, several process and technology related bottlenecks need to be resolved. AAV manufacturing still heavily relies on transient transfection production methods using primarily adherent cell lines, both of which are impractical and cost ineffective to scale up, while stable suspension cell lines have not yet been fully optimized. The complex and demanding purification process that follows further exacerbates the problem, resulting in low final yields.

This project aims to develop a ‘whole process’ model of AAV manufacturing that can accurately assess the efficacy of and/or design novel, robust and economically favourable process configurations. 

A successful project will result in: (1) A detailed list of suitable alternative technologies for each unit operation based on data from technology providers and the scientific literature. (2) An information matrix detailing technology incompatibilities, expected/nominal range of input and expected/predicted range of output for each unit operation. (3) Model-assisted decisional tools that evaluate and rank alternative process configurations and technology combinations based on user defined input characteristics and output quality criteria. (Integrated whole process manufacturing model).

Enrolment in Doctoral School: AUTh

Planned secondments:

  • Siemens Process Systems Engineering, UK (Months 9-11): Whole process modelling, model development and parameter estimation

  • KU Leuven, Belgium (Months 18-19): Introduction to upstream bioprocessing

  • KU Leuven, Belgium (Months 29-30): Introduction to downstream bioprocessing


  • You hold a master’s degree in physics, (bio) engineering or a related field.

  • You are ambitious, well organized and have excellent communication skills.

  • You are proficient in English both spoken and written

  • You have the ability to work independently and have a critical mindset.

  • You are an enthusiastic and motivated person, eager to participate in network wide training events, international travel and public awareness activities.

  • Willingness to travel


  • Solid knowledge of mathematical modelling, process modelling, process flowsheets

  • An understanding of bioprocessing, biomanufacturing

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