Yield and productivity are critical for the economics and viability of a bioprocess. In metabolic engineering, the main objective is the increase of a target metabolite production through genetic engineering. However, genetic manipulations usually result in lower productivity due to growth impairment. Previously, it has been shown that the dynamic control of metabolic fluxes can increase the amount of product formed in an anaerobic batch fermentation of Escherichia coli. In order to apply this control strategy, the genetic toggle switch is used to manipulate key fluxes of the metabolic network. We have designed and analyzed an integrated computational model for the dynamic control of gene expression. This controller, when coupled to the metabolism of E. coli, resulted in increased bioprocess productivity.