A novel, Q-PCR based approach to measuring endogenous retroviral clearance by capture protein A chromatography
- PMID: 18988264
- DOI: 10.1002/bit.22172
A novel, Q-PCR based approach to measuring endogenous retroviral clearance by capture protein A chromatography
Abstract
Quantification of virus removal by the purification process during production is required for clinical use of biopharmaceuticals. The current validation approach for virus removal by chromatography steps typically involves time-consuming spiking experiments with expensive model viruses at bench scale. Here we propose a novel, alternative approach that can be applied in at least one instance: evaluating retroviral clearance by protein A chromatography. Our strategy uses a quantitative PCR (Q-PCR) assay that quantifies the endogenous type C retrovirus-like particle genomes directly in production Chinese Hamster Ovary (CHO) cell culture harvests and protein A pools. This eliminates the need to perform spiking with model viruses, and measures the real virus from the process. Using this new approach, clearance values were obtained that was comparable to those from the old model-virus spike/removal approach. We tested the concept of design space for CHO retrovirus removal using samples from a protein A characterization study, where a wide range of chromatographic operating conditions were challenged, including load density, flow rate, wash, pooling, temperature, and resin life cycles. Little impact of these variables on CHO retrovirus clearance was found, arguing for implementation of the design space approach for viral clearance to support operational ranges and manufacturing excursions. The viral clearance results from Q-PCR were confirmed by an orthogonal quantitative product-enhanced reverse transcriptase (Q-PERT) assay that quantifies CHO retrovirus by their reverse transcriptase (RT) enzyme activity. Overall, our results demonstrate that protein A chromatography is a robust retrovirus removal step and CHO retrovirus removal can be directly measured at large scale using Q-PCR assays.
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