Ask Greg McMillan - What are the breakthroughs in dynamic modeling of bioreactors?

Greg's Response:

Several equations enable the user to readily set parameters that provide robust high-fidelity kinetics for the effect of temperature, pH, and concentrations on cell growth rate and product formation rate that is profound for modern day biologics. For temperature and pH, convenient cardinal equations are used where the key parameters for growth and product formation is simply the best temperature and pH set point including any shifts for batch phases. The minimum and maximum temperatures complete the parameter settings. This is a tremendous advancement to the traditional uses of Arrhenius equations for temperature and Villadsen-Nielsen equations for pH that required parameters not readily available set with a precision to the sixth or seventh decimal place. For concentrations, a generalized Michaelis-Menten equation, shown to be useful for modeling intracellular dynamics, can easily model the limitation and inhibition effects of substrate concentrations. The equations provide a link between macroscopic and microscopic kinetic pathways. If the limiting or inhibition effect is negligible or must be temporarily removed, the limitation and inhibition parameter is simply set to 0 g/L and 100 g/L, respectively. The biological significance and ease of setting parameters is particularly important.

These revolutionary equations enable the same generalized kinetic model to be used for all types of cells. Previously, yeast cells (e.g., ethanol production), fungal cells (e.g., antibiotic production), bacterial cells (e.g., simple proteins), and mammalian cells (e.g., complex proteins) had specialized equations developed that did not generally carry over to different cells and products. In the next post, methods, and tools to assist in parameterization will be offered.

Dynamic first-principle models in the literature were primarily created for batch processes without control system dynamics. Controllers and strategies were emulated and consequently disparate from actual capability in a modern control system. The dynamic models along with a digital twin defined and exemplified can operate in the continuous as well as the batch mode. Measurement and final control element dynamics and the exact duplicate of controllers, historian, and operator interfaces in the lab, pilot plant, or production unit are used so that automation and process engineers and operations are working in the same automation system configuration and interface with dynamics representative of what is in the actual plant.

For much more knowledge see 2021 ISA Book New Directions in Bioprocess Modeling and Control – Maximizing Process Analytical Technology Benefits Second Edition.