Dr. Stephen Goldrick (UCL Biochemical Engineering)
Dr. Chris Spencer (AstraZeneca, Cambridge)
Dr. Michael Thomas (UCL London Centre for Nanotechnology / Biochemical Engineering)
Metabolic profiling of mammalian cultures enables a greater understanding of the physiological state of cells throughout a bioreactor run in addition to monitoring the key metabolite concentrations. This information is invaluable for the development of bespoke amino acid feeds that can be tailored to individual cell lines to enhance productivity and minimise product heterogeneities. However, a major challenge of the metabolic profiling is the cost and challenge of generating the time-course metabolic profiles for a high number of cell cultures.
This project aims to overcome this hurdle by combining the power of a high-throughput Raman (HT) instrument with surface enhanced Raman spectroscopy (SERS). The application of multivariate data analysis (MVDA) and machine learning to the Raman data will enable the prediction of key metabolites for bioreactor control.
This project is multidisciplinary involving two world-leading research centres and a global pharmaceutical company. The project combines the strengths of the London Centre for Nanotechnology (LCN) leveraging their expertise in metallic nanoparticle design, synthesis and modification for label-free surface enhanced Raman spectroscopy. In addition to UCL’s Biochemical Engineering department that is a world leader in bioprocess research creating novel engineering solutions to underpin future biomanufacturing operations and will lead the advanced data analytics and modelling of this project. These two partners will support the ultimate goal of AstraZeneca which is to push the boundaries of science to deliver life-changing medicines.
The work will generate data to train an MVDA model to build the correlations between the Raman spectra and off-line measurements of interest. These measurements can be incorporated into a control strategy enabling at-line control of essential amino acid concentrations and provides the foundation for the development of customised feeds to enhance bioreactor performance for AstraZeneca cell lines.
The candidate will have the opportunity to work at both AZ in Cambridge and at UCL in London, using the facilities available at both organisations will be a great advantage.
Develop models allowing Raman spectroscopy to replace traditional analytical techniques such as metabolite analysers. Ultimately this project will lead to an automated process for the conversion of Raman spectra to actionable bioprocess information.
• Conduct experiments to gather off-line data and spectra, catalogue the parameters that can be measured using the Raman system. The following should be evaluated;
o Amino acids
o Product titer
o Product quality (clipping, tri-sulphide bonds, aggregation etc.)
• Autonomize the analysis of Raman spectra and conversion to bioprocess information
We are looking for a highly motivated, enthusiastic individual, capable of thinking and working independently and willing to learn new skills. Applicants should have or shortly expect to obtain a Degree (or equivalent) in a relevant subject such as biochemical engineering, biochemistry, computer science etc. Experience with bioreactor operation, multivariate data analysis, coding or machine learning would be advantageous. This position is open to UK/EU candidates only. Interviews for the position will take place in March 2020 (link to BBSRC criteria)
Full funding covering the University Composition Fee and Maintenance (currently £17,000 pa), is provided for up to 3 years, with effect from 1 October 2020.