Modeling and Optimization of Continuous Viral Vaccine Production

Abstract

A model that captures realistic viral growth dynamics has been developed based on a continuous and semi-continuous production model of an influenza A virus. This model considers viral growth parameters such as viral latency. It also captures the lag observed during the early production of viruses in a culture and explains later-phase growth dynamics. Furthermore, a sensitivity analysis was performed to investigate the effects of each input on each output. This revealed that production of defective interfering particles (DIPs) highly depends on the number of cells introduced to the viral reactor. The rationale for this is, as per the model, that a reduction in number of cells to be infected causes a reduction in DIPs formed as rate of viral infection decreases. Finally, a flowsheet model was created to optimize the continuous platform, including number of cells supplied to the viral reactor. From this, it was observed that the peak number of DIPs formed could be reduced by one-third. Finally, this model is tailorable to different viral particles using parameter estimation. Therefore, the proposed mathematical model provides a versatile, comprehensive platform that can be tailored to various viral cultures with or without a latent phase.