Our approach to mathematically describing a cell population behaviour has evolved in the past decades. From the use of Monod kinetics, when a limiting nutrient shows to control cell behaviour, we now see modelling approaches based on a genome-wide description of a biosystem, integrating the various “omics” datasets available. However, do we always need that level of complexity to face a problem of bioprocess optimization or to elucidate the mechanisms of a metabolic disease?
Professor Venkatasubramanian will review the different phases of Artificial intelligence (AI) in process systems engineering (PSE) over the past 30 years and argue that the time for AI in PSE, and in other domains, has arrived, finally.
C. Perry Chou, Chemical Engineering
Murray Moo Young, Chemical Engineering