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Creation of a High-Yield AAV Vector Production Platform in Suspension Cells Using a Design-of-Experiment Approach.


ABSTRACT: Recombinant adeno-associated virus (rAAV) vectors are a leading gene delivery platform, but vector manufacturing remains a challenge. New methods are needed to increase rAAV yields and reduce costs. Past efforts to improve rAAV production have focused on optimizing a single variable at a time, but this approach does not account for the interactions of multiple factors that contribute to vector generation. Here, we utilized a design-of-experiment (DOE) methodology to optimize rAAV production in a HEK293T suspension cell system. We simultaneously varied the transgene, packaging, and helper plasmid ratios, the total DNA concentration, and the cell density to systematically evaluate the impact of each variable across 52 conditions. The results revealed a unique set of parameters with a lower concentration of transgene plasmid, a higher concentration of packaging plasmid, and a higher cell density than previously described protocols. Using this DOE-optimized protocol, we achieved unpurified yields approaching 3 × 1014 viral genomes (VGs)/L of cell culture. Additionally, we incorporated polyethylene glycol (PEG)-based virus precipitation, pH-mediated protein removal, and affinity chromatography to our downstream processing, enabling average purified yields of >1 × 1014 VGs/L for rAAV-EGFPs across 13 serotypes and capsid variants.

SUBMITTER: Zhao H 

PROVIDER: S-EPMC7334306 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Creation of a High-Yield AAV Vector Production Platform in Suspension Cells Using a Design-of-Experiment Approach.

Zhao Huiren H   Lee Ki-Jeong KJ   Daris Mark M   Lin Yun Y   Wolfe Thomas T   Sheng Jackie J   Plewa Cherylene C   Wang Songli S   Meisen W Hans WH  

Molecular therapy. Methods & clinical development 20200603


Recombinant adeno-associated virus (rAAV) vectors are a leading gene delivery platform, but vector manufacturing remains a challenge. New methods are needed to increase rAAV yields and reduce costs. Past efforts to improve rAAV production have focused on optimizing a single variable at a time, but this approach does not account for the interactions of multiple factors that contribute to vector generation. Here, we utilized a design-of-experiment (DOE) methodology to optimize rAAV production in a  ...[more]

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