Design and characterisation of a scale-down perfusion platform for mammalian cell process development

Lead Research Organisation: University College London
Department Name: Biochemical Engineering


This project seeks to optimise perfusion processes via addressing two related challenges, namely:
- Scale-down and process verification of novel cell retention methodologies (AWS)
- Understanding steady state and maximise process performance and productivity

- Design and build a small scale version of the AWS system, able to work with and fully connected to a 250mL perfusion bioreactor.
- Understand the limits of and characterize the "operating window" for AWS perfusion processes. Benchmark against other cell retention technologies.
- Understand steady state with respect to: cell size distribution, cell cycle distribution, primary metabolism, specific productivity. Model based process optimisation (perfused media, perfusion rate, target VCD at steady state).

Project Description
The Acoustic Wave Separator (AWS) technology developed by Pall offers a number of promising benefits such as: (a) not being susceptible to fouling, (b) being tuneable to allow for cell fractionation and conditional bleeding and (c) causing less stress to the cells. However, a scale down version amenable to high-throughput process development in small volume automated bioreactors does not exist. The aim is to develop, in collaboration with Pall, a scale down version of the AWS as a cell retention device in small volume bioreactors and to understand the limits of and characterize the "operating window" for continuous processes using the AWS technology.
Experimental investigations will be based on a fully controlled scale-down perfusion bioreactor recently developed at UCL. This novel 250ml bioreactor, specifically designed for mammalian cell cultivation under perfusion mode, is equipped with a Levitronix pump and TFF filter, used for cell retention. Perfusion runs at 1VVD have been successfully run and showed good reproducibility over 10 days. Expertise from Pall on the AWS and its operation will be key to select suitable scaling criteria.
Mathematical analysis and characterisation of the steady state will be based on a series of metabolic modelling and Systems Biology techniques recently developed at UCL. Process variables that will be studied both mathematically and experimentally at steady state include: cell size distribution, cell cycle analysis, primary metabolic uptake & secretion rates, amino acid uptake & secretion rates, cell viability and viable cell density.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S021868/1 01/10/2019 31/03/2028
2417299 Studentship EP/S021868/1 28/09/2020 27/09/2024 Ciara Lucas