CD Laboratory for Knowledge-based Production of Gene Therapy Vectors

Gene therapy can be used to treat or even cure genetically caused diseases. This CD Laboratory is researching more efficient process development and production to improve the quality and reduce the costs of such therapies.

Gene therapy is a promising way of curing or treating diseases caused by missing or defective genes. Approaches to this have been researched for more than 50 years. In gene therapy, genetic material is introduced into cells to repair defects or replace missing genes. Viruses that do not cause disease in humans have proven to be a very suitable means of transport for introducing DNA into cells. Adenovirus-associated viruses (AAVs) are frequently used for this purpose. However, this modified viral DNA is not incorporated into the human genome, but exists independently in the cells.

The development of a manufacturing process for recombinant AAVs (rAAVs) is currently empirically driven and therefore very cost-intensive and often associated with low yields. This CD Laboratory is researching ways to achieve knowledge- and model-based process development and production of rAAVs for gene therapy. The aim is to make these promising drugs available efficiently and in sufficient quantities in the future.

To achieve this, a profound understanding of interrelationships is required, e.g. how cell lines, therapeutic genes or process conditions interact with each other and influence the quality and quantity of rAAVs. Different cell lines and different therapeutic genes lead to strongly varying ratios between these variants and to high proportions of empty rAAVs, i.e. those that are not loaded with therapeutic DNA. Therefore, analytical methods are needed that enable precise characterisation of rAAVs and impurities and, in particular, can distinguish empty rAAVs from those loaded with therapeutic DNA.

It is currently only possible to check product quality after a process step has been completed. Such analyses are time-consuming and cost-intensive and require downtimes in the process. They only provide retrospective information and cannot be used for process control. For this reason, sensors are being analysed that record important parameters during the process and thus monitor and control them. This approach increases both the safety of the processes and their efficiency.

In order to develop a systematic understanding of important parameters and their interaction, various cell lines are being investigated and a genome-wide analysis of the cell response to virus production is being carried out. In this way, strategies can be developed to improve the rAAV yield and its quality.

Bringing such optimised cell lines to production scale is a multi-stage, time-consuming and cost-intensive process. A process development platform must therefore be developed to enable experiments in miniaturised form. This will include all relevant steps of cell cultivation and further processing (downstream processing). A process optimised in this way will be compared with the current process to compare the results.