Toward QbD Process Understanding on DNA Vaccine Purification Using Design of Experiment

Abstract

DNA vaccines, the third generation of vaccines, are a promising therapeutic option for many diseases as they offer the customization of their ability on protection and treatment with high stability. The production of DNA vaccines is considered rapid and less complicated compared to others such as mRNA vaccines, viral vaccines, or subunit protein vaccines. However, the main issue for DNA vaccines is how to produce the active DNA, a supercoiled isoform, to comply with the regulations. Our work therefore focuses on gaining a process understanding of the purification step which processes parameters that have impacts on the critical quality attribute (CQA), supercoiled DNA and performance attribute (PA), and step yield. Herein, pVax1/lacZ was used as a model. The process parameters of interest were sample application flow rates and salt concentration at washing step and at elution step in the hydrophobic interaction chromatography (HIC). Using a Design of Experiment (DoE) with central composite face centered (CCF) approach, 14 experiments plus four additional runs at the center points were created. The response data was used to establish regression predictive models and simulation was conducted in 10,000 runs to provide tolerance intervals of these CQA and PA. The approach of this process understanding can be applied for Quality by Design (QbD) on other DNA vaccines and on a larger production scale as well.

Keywords: DNA vaccine purification; Design of Experiment; QbD; process understanding; tolerance study.

FIGURE 1

Chromatogram of the DEAE capture step (A) and respective agarose electrophoresis (B) where lane 1 is 1 kb plus DNA ladder, lane 2 lysate, lane 3 after RNA precipitation, lane 4 AIEX flow through fraction, lane 5 AIEX washing II fraction, and lane 6 AIEX elution fraction.

FIGURE 2

Prediction plot for %Step yield (A) and for %SC pDNA (B).

FIGURE 3

Response surface prediction for %Step yield with (NH₄)₂SO₄ concentration at washing step and flow rate.

FIGURE 4

Response surface prediction for %SC pDNA with (A) (NH₄)₂SO₄ concentration at washing step and flow rate, (B) (NH₄)₂SO₄ concentration at elution step and flow rate.

FIGURE 5

Prediction profiler of optimized process on HIC purification step. The solid lines are the predicted model. The red dashed lines are the interaction plots and the blue dashed lines are the confidence interval.

FIGURE 6

Simulation runs and distribution charts for HIC purification step. The solid lines are the predicted model. The red dashed lines are the interaction plots and the blue dashed lines are the confidence interval.