Project objectives:
One of the challenges for the biopharmaceutical industry today is maximizing the production throughput to keep up with the increasing demand while keeping facility footprint and cost of goods manufactured (COGm) low. AstraZeneca has been developing a Next Generation Manufacturing (NGM) process to overcome this challenge. The cell culture part of the NGM process utilizes a perfusion-based process intensification strategy along with an adaptive continuous feed strategy which enables adjustment of the feed composition on demand to deliver optimal recipe/components that are required for cell growth and recombinant protein production. This effort has led to a significant increase in productivity while keeping the product quality attributes similar to those observed in the previous platform process. However, the process development work thus far has been with clones that are selected by a fed-batch based screening method due to a lack of high throughput clone selection methods that are representative of the NGM process. High throughput scale down screening models representative of the final production process are essential as the cell line development process delivers clones with diverse growth and productivity characteristics. Cells are exposed to a very different environment in the NGM process as compared to a fed-batch process, so the current high throughput screening method is not adequate for selecting the best clones that are most suitable for NGM process.
The purpose of this research is to elucidate the effect of process intensification on cellular properties and apply the findings to the development of a high throughput clone screening method suitable to screen hundreds of clones based on their predicted performance in the next generation manufacturing (NGM). The doctoral candidate will contribute to the project with focus on the following objectives:
· Identify key cell culture process elements required in the high throughput screening method to ensure its predictiveness of each clone’s performance in NGM process. Experimental studies will be conducted using existing small scale systems and verification at 3L bioreactor scale
· Develop a mechanistic understanding of interactions between process parameters and cellular properties that are relevant to NGM process performance
· Identify cellular properties and process outputs that are indicative of each clone’s performance in bioreactors
· Optimize existing high throughput screening methods and relevant process parameters based on the findings above
Significance & Background:
This project will be part of the UCL-AstraZeneca Centre of Excellence (CoE) that is a joint collaboration between University College London (UCL) and AstraZeneca. The centre’s aim is to generate a set of predictive decisional tools for both upstream and downstream biopharmaceutical processing activities. This involves the application of micro-scale and high-throughput cell culture studies involving correlation development, multivariate data analysis (MVDA), process economics and discrete-event optimisation. The candidate will join a team of PhD and postdoctoral researchers working in the CoE across upstream and downstream processing as well as modelling tools. The project will be hosted by the department of Biochemical Engineering at University College London in collaboration with AstraZeneca sites across Cambridge (UK) and Gaithersburg (US).
Sponsor background: AstraZeneca focuses on process development and manufacture of novel biotherapeutics for clinical trials and the market. AstraZeneca has an initiative focusing on development and implementation of next generation manufacturing process with the aim to increase the productivity by more than 5-fold as compared to the current platform process through process intensification. Such a process change will require a different clone selection environment which is capable of selecting the clone best suited for the intensified process. AstraZeneca has identified the need for tools that enable predictions of cell culture performance for each clone in the cell line development stage of the development cycle. The doctoral candidate will collaborate closely with a team of scientists in the Cell Line Development team at AstraZeneca to evaluate various existing technologies that are both novel and commercially available and propose the best platform strategy to be implemented as a part of this project.
UCL BE Background: The department of Biochemical Engineering at UCL is well-placed to address this challenge as it has pioneered (a) decisional tools including modelling software for whole bioprocess economics and optimisation, capacity planning and portfolio management as well as advanced multivariate data analysis algorithms tailored to bioprocessing applications, (b) ultra-scale down mimic methodology and equipment for scale-up or scale-out of processes with small volumes of material and (c) particle imaging velocimetry algorithms for bioprocess fluid dynamics applications.
Candidate requirements:
- Bachelor’s or Master’s degree in Biochemical Engineering / Chemical Engineering / Bioprocessing / Biology / Biochemistry or relevant subject area with an interest in cell culture device development and process automation
- Excellent written, verbal communication and presentation skills in English
- Interpersonal skills and ability to work effectively in a team
- Travel between UCL and AstraZeneca (mainly UK site) for experimental and research activities
- Willingness to travel to AstraZeneca US sites, depending on training or project requirements
- This project will require the candidate to possess basic engineering and computing skills and a desire to understand the challenges of dealing with complex biological materials in real environments.
Skills gained
- cell culture and purification techniques
- cell culture process technologies including bench scale bioreactors
- cell based assays
- upstream / downstream scale-down experimental work in a company environment
- statistical modelling of cell culture process parameters
- laboratory automation, experimental design and database management
Deadline and Application Process
The deadline for submission is 23:59 on Wednesday, 16 June 2021.
Please send a CV (max 2 pages) and covering letter outlining motivations for undertaking this EngD studentship and relevant experience and expertise. Please send this directly to Professor Micheletti ([Email Address Removed]) quoting ‘AZ EngD’ in the subject of the email.
Candidates will be contacted via email for interview. Interviews will take place via Microsoft Teams.
In addition to this you must submit your formal application to the EngD in Bioprocess Engineering Leadership course (DDNBENSBIL01) through UCL’s application portal by the above deadline of 16 June 2021. More information about the course and application process is available here: https://www.ucl.ac.uk/biochemical-engineering/study/postgraduate-research/biochemical-engineering-and-bioprocess-leadership-engd
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