Modeling retrovirus production for gene therapy. 1. Determination of optimal bioreaction mode and harvest strategy

Citation
Pe. Cruz et al., Modeling retrovirus production for gene therapy. 1. Determination of optimal bioreaction mode and harvest strategy, BIOTECH PR, 16(2), 2000, pp. 213-221
Citations number
32
Categorie Soggetti
Biotecnology & Applied Microbiology",Microbiology
Journal title
BIOTECHNOLOGY PROGRESS
ISSN journal
87567938 → ACNP
Volume
16
Issue
2
Year of publication
2000
Pages
213 - 221
Database
ISI
SICI code
8756-7938(200003/04)16:2<213:MRPFGT>2.0.ZU;2-9
Abstract
Although retroviruses are a promising tool for gene therapy, there are two major problems limiting the establishment of viable industrial processes: r etrovirus stability and low final yield in the supernatant. This fact empha sizes the need for an effective process optimization, not only at a genetic level but also at a bioprocess engineering level. In part 1 of this paper a mathematical model was developed to optimize the bioreaction yield by det ermining the best retrovirus harvest strategy in perfusion cultures. PA317 cells producing recombinant retroviruses were used to develop and test this model. Cell culture was performed in stirred tanks using porous supports. The parameters of the proposed model were experimentally determined for bat ch and perfusion cultures at 32 and 37 degrees C both with and without addi tives to enhance production; the model was then validated. This model allow ed the determination of the optimal values of all operational variables inc luded: batch and perfusion duration and perfusion rate. The highest product ivity (2682 virus cm(-3) h(-1)) was obtained under the following conditions : batch at 37 degrees C for 53 h followed by perfusion at 32 degrees C for 23 h with a perfusion rate of 0.107 h(-1). This value was 3.5-fold higher t han the best result obtained in batch cultures for the same conditions of t iter and quality. A sensitivity analysis of the parameters showed that the parameters that affect most the final productivity depend on the bioreactio n phase: cell growth in batch culture and production and product degradatio n in perfusion culture. In part 2 of this paper, this model is extended to the first step of downstream processing, and the addition of further steps to the process is discussed in order to achieve global process optimization .