Predictive chemometrics modelling for enhanced robustness of integrated continuous biomanufacturing processes

UCL Biochemical Engineering has secured an ambitious BBSRC PhD project in collaboration with MedImmune, a leading biopharmaceutical company in Cambridge UK.

This project aims to create experimental and predictive modelling tools to assess and optimise novel ideas for end-to-end continuous bioprocessing of biopharmaceuticals. The potential of continuous processing to maintain and control product quality of biologics will be evaluated. An integrated scale-down platform of perfusion culture linked to continuous capture chromatography will be established. Experimental data will be used to build predictive cause-and-effect models that link critical process parameters (e.g. pH) to critical quality attributes (e.g. glycosylation) using advanced chemometrics techniques. This enhanced process understanding will be used to optimize integrated continuous bioprocesses based on off-line and on-line analytics across the upstream and downstream process. The process models will provide the basis for developing sophisticated control strategies for the integrated processes that will be tested on lab-scale systems at MedImmune. Finally the rewards and risks of implementing continuous processes in an industrial setting will be assessed.

Typical candidate requirements: Biochemical or Chemical Engineering Bachelor’s or Master’s degree desirable. This project will require a candidate who possesses basic engineering and computing skills and a desire to understand the challenges of dealing with complex biological materials in real environments. The candidate will be a competent biochemical engineering graduate. He/she is expected to spend time in both UCL and sponsor facilities.

Skills gained
- mammalian cell culture and purification
- upstream and downstream scale-down experimental work in a company environment
- predictive bioprocess modelling of unit operations and integrated processes
- proficiency in chemometrics
- laboratory automation, experimental design and database management
- pilot plant experience