A Bioprocess Discovery Tool to Speed Up New Vaccine Development

This project set out to address the need for a more efficient ‘discovery’ of suitably robust routes to manufacture of cell lines for use in whole cell vaccines and whole cell therapies. The goal was to develop a suite of tools to identify impacts of bioprocessing; this included the development of ultra scale-down (USD) platform technology and a panel of biological tests to predict and characterize the cellular response to processing.
The project has established the ultra scale-down platform and analytical strategy to allow new cell lines to be addressed and new processes optimised. The project has examined a number of cell lines and has demonstrated the generality of the approach.
A panel of biological tests ranging from rapid and requiring low cell numbers (membrane integrity, cell size, surface marker analysis) to longer more complex analyses (cell death, cytokine release, biopotency) have been developed and are largely generic meaning that they can be applied to many different cell therapeutics. A novel method for identifying novel biomarkers resulting from cellular stress has been developed for mass spectrometry. An Artificial Neural Network has been employed using data from USD bioprocessing experiments to aid the prediction of cell quality outcomes following bioprocessing, the aim here was to create a predictive tool that identify limits of processing. ANN is shown to be a powerful tool in identifying subtle changes in the data that may be due to parameters not previously considered.
Our findings enable early stage bioprocess development of therapeutics. The data generated from this project has indicated that each cell line studied has a different response to shear stress. This will impact upon new whole cell therapies currently emerging. We have developed the tool set to identify the robustness of cells during bioprocessing and a broad set of parameters. However, ‘fine tuning’ should be carried out on individual cell types before designing the whole bioprocess. In addition, it has become clear that it is not only the engineering parameters that require careful control, cell culture parameters prior bioprocessing are highly important and should be kept in mind by researchers bringing new therapies to clinic.