A method of computationally modeling a bioreactor which accounts for spatial inhomogeneity, wherein the method comprises: receiving a plurality of current values of process variables, the process variables describing first virtual contents of a first portion of the modeled bioreactor and one or more additional virtual contents of corresponding one or more additional portions of the modeled bioreactor, and the virtual contents including virtual cellular biomass in a virtual extracellular solution; computing, by processing hardware of a computing system, new values of the process variables during a simulated time period, at least in part by generating a plurality of constraints on flux rates of metabolic fluxes describing the virtual cellular biomass by modeling one or more effects of at least some of the current values of the process variables on metabolic reaction kinetics, computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective and the generated plurality of the constraints on the flux rates, computing rates of change of at least some of the process variables based at least in part on the computed flux rates, and updating one or more of the current values of the process variables at least in part by integrating one or more of the computed rates of change for a virtual time step within the simulated time period; computing, by the processing hardware, a metric of the computationally modeled bioreactor based at least in part on the computed new values of the process variables; and generating, by the processing hardware, and based on the metric of the modeled bioreactor one or more of i) information displayed to a user via a user interface, ii) a control setting for a real-world bioreactor, or iii) a training set for an artificial intelligence model of a bioreactor. receiving a plurality of current values of process variables, the process variables describing first virtual contents of a first portion of the modeled bioreactor and one or more additional virtual contents of corresponding one or more additional portions of the modeled bioreactor, and the virtual contents including virtual cellular biomass in a virtual extracellular solution; computing, by processing hardware of a computing system, new values of the process variables during a simulated time period, at least in part by generating a plurality of constraints on flux rates of metabolic fluxes describing the virtual cellular biomass by modeling one or more effects of at least some of the current values of the process variables on metabolic reaction kinetics, computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective and the generated plurality of the constraints on the flux rates, computing rates of change of at least some of the process variables based at least in part on the computed flux rates, and updating one or more of the current values of the process variables at least in part by integrating one or more of the computed rates of change for a virtual time step within the simulated time period; generating a plurality of constraints on flux rates of metabolic fluxes describing the virtual cellular biomass by modeling one or more effects of at least some of the current values of the process variables on metabolic reaction kinetics, computing the flux rates of the metabolic fluxes by performing flux balance analysis subject to a metabolic objective and the generated plurality of the constraints on the flux rates, computing rates of change of at least some of the process variables based at least in part on the computed flux rates, and updating one or more of the current values of the process variables at least in part by integrating one or more of the computed rates of change for a virtual time step within the simulated time period; computing, by the processing hardware, a metric of the computationally modeled bioreactor based at least in part on the computed new values of the process variables; and generating, by the processing hardware, and based on the metric of the modeled bioreactor one or more of i) information displayed to a user via a user interface, ii) a control setting for a real-world bioreactor, or iii) a training set for an artificial intelligence model of a bioreactor.