Engineering challenges in personalised cell therapies: applying fundamental engineering, ultra scale-down design and experimental flow dynamics approa

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

Abstract

This proposal will establish a rigorous fundamental engineering understanding of the impact of fluid dynamics on multiple process steps towards safer and more robust personalised medicine manufacture and will enable the design of ultra-scale down devices that will speed the development of the next generation processing while improving yields and reducing cost of therapies. The engineering understanding will be used to design a portfolio of novel ultra scaledown tools to evaluate and model the effect of 3D shear environment of T-cells expansion and subsequent process steps. The project will be guided by an iterative design thought process, from the establishment of objectives and specification criteria, through to synthesis, analysis, fabrication, testing and end-user evaluation. A portfolio of USD tools mimicking critical process interactions would be invaluable to optimise the process at a small scale, targeting key cost drivers, thus establishing a more robust process from the start and allowing for savings at later stages of development. Engineering characterisation experiments will be based on the use of laser-based techniques, high speed camera imaging and automated image analysis. A Particle Image Velocimetry (PIV) system will be used to obtain information on flow pattern, presence of stagnant areas, mean and turbulent velocity characteristics and extent of laminar/transitional flow at specific locations. Macromixing information, obtained under a range of industrially relevant operating conditions, will constitute a basis for developing scale translation models and provide a thorough and complete insight of the mechanism of operation from the engineering/fluid dynamics viewpoint. The engineering insight will inform the design of the subsequent T-cells cultivation experiments.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509577/1 01/10/2016 30/09/2021
2268438 Studentship EP/N509577/1 23/09/2019 22/09/2023 Gergana Georgieva Atanasova