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01.12.2018 | Research | Ausgabe 1/2018 Open Access

Journal of Translational Medicine 1/2018

Enhanced clinical-scale manufacturing of TCR transduced T-cells using closed culture system modules

Journal of Translational Medicine > Ausgabe 1/2018
Jianjian Jin, Nikolaos Gkitsas, Vicki S. Fellowes, Jiaqiang Ren, Steven A. Feldman, Christian S. Hinrichs, David F. Stroncek, Steven L. Highfill



Genetic engineering of T-cells to express specific T cell receptors (TCR) has emerged as a novel strategy to treat various malignancies. More widespread utilization of these types of therapies has been somewhat constrained by the lack of closed culture processes capable of expanding sufficient numbers of T-cells for clinical application. Here, we evaluate a process for robust clinical grade manufacturing of TCR gene engineered T-cells.


TCRs that target human papillomavirus E6 and E7 were independently tested. A 21 day process was divided into a transduction phase (7 days) and a rapid expansion phase (14 days). This process was evaluated using two healthy donor samples and four samples obtained from patients with epithelial cancers.


The process resulted in ~ 2000-fold increase in viable nucleated cells and high transduction efficiencies (64–92%). At the end of culture, functional assays demonstrated that these cells were potent and specific in their ability to kill tumor cells bearing target and secrete large quantities of interferon and tumor necrosis factor. Both phases of culture were contained within closed or semi-closed modules, which include automated density gradient separation and cell culture bags for the first phase and closed GREX culture devices and wash/concentrate systems for the second phase.


Large-scale manufacturing using modular systems and semi-automated devices resulted in highly functional clinical-grade TCR transduced T-cells. This process is now in use in actively accruing clinical trials and the NIH Clinical Center and can be utilized at other cell therapy manufacturing sites that wish to scale-up and optimize their processing using closed systems.
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