See below
Lead Research Organisation:
University College London
Department Name: Biochemical Engineering
Abstract
Full title: A framework for the development, analysis and validation of mathematical models of upstream unit operations used in the production of recombinant proteins as part of an integrated whole bioprocess modelling platform
Summary: The development of predictive and robust mathematical models enables the application of traditional process systems engineering (PSE) techniques (such as model-based optimization) to cell-based bioprocesses leading to increased productivity and reduced operating costs (Kiparissides et al, 2015). However, despite recent advances in modelling tools in the areas of systems biology and metabolic engineering, several challenges still remain before detailed kinetic models reach the degree of maturity required for conventional use in industrial applications (Almquist et al, 2014). The aim of this project is to bridge this apparent 'information gap' by developing a novel computational approach able to integrate, organize and guide experimental information across multiple scales and unit operations in order to enable 'whole bioprocess' simulation and optimization studies. The developed models will be experimentally validated and will be used to derive optimal fed-batch feeding strategies (through model based optimization) and, subsequently, to implement these strategies at the bioreactor scale (through automated model predictive control). The EngD researcher will utilise the gPROMS family of products for the development of mathematical models and will focus on their 'plug-and-play' integration within PSE's whole bioprocess modelling platform.
Summary: The development of predictive and robust mathematical models enables the application of traditional process systems engineering (PSE) techniques (such as model-based optimization) to cell-based bioprocesses leading to increased productivity and reduced operating costs (Kiparissides et al, 2015). However, despite recent advances in modelling tools in the areas of systems biology and metabolic engineering, several challenges still remain before detailed kinetic models reach the degree of maturity required for conventional use in industrial applications (Almquist et al, 2014). The aim of this project is to bridge this apparent 'information gap' by developing a novel computational approach able to integrate, organize and guide experimental information across multiple scales and unit operations in order to enable 'whole bioprocess' simulation and optimization studies. The developed models will be experimentally validated and will be used to derive optimal fed-batch feeding strategies (through model based optimization) and, subsequently, to implement these strategies at the bioreactor scale (through automated model predictive control). The EngD researcher will utilise the gPROMS family of products for the development of mathematical models and will focus on their 'plug-and-play' integration within PSE's whole bioprocess modelling platform.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| NE/W502716/1 | 01/04/2021 | 31/03/2022 | |||
| 1930924 | Studentship | NE/W502716/1 | 01/10/2017 | 24/03/2022 | Viktoria Gkoutzioupa |