Economic Nonlinear Model Predictive Control of Continuous Viral Bioreactors

Abstract

Viral particle systems are integral parts of modern biotechnology, finding use in vaccines, drug delivery platforms, and recombinant protein production. Continuous manufacturing of these systems can offer improved manufacturability and quality control. However, viral systems often have complex kinetics which can introduce undesirable process dynamics and lower product titers in continuous operation. This article explores the use of economic nonlinear dynamic optimization and model predictive control to achieve multiple process objectives such as maximizing productivity and/or purity. Economic nonlinear model predictive control is also demonstrated to robustly control the bioreactor under plant-model mismatch in different scenarios.