Abstract
Understanding the complexity of human digestion is critical for designing models that serve as valuable research tools for process simulation and prediction. Due to the high cost of medical intervention & recent advancements in in vitro digestion protocols, increased demand for inexpensive in silico solutions emerges. This study aims to develop a mathematical model that simulates the in vitro dynamic Food Digestion SIMulator (FooDSIM) functionalities via a digital twin approach. Ordinary Differential Equations (ODEs) simulate the system as a series of Continuously Stirred Tank Reactors (CSTRs) and describe different regions of human organs (stomach, duodenum, ileum, colon) of the human Gastrointestinal Tract (GIT). Various time horizons were used to investigate the effect of periodic feeding on the dynamic stabilisation of the inherently simulated processes (hydraulics, pH, biochemical interactions between enzymes & substrates, and nutrient absorption). A Polynomial Chaos Expansion (PCE)-based Global Sensitivity Analysis (GSA) was performed to explore causal relationships between input & output variables by performing uncertainty quantification. Results indicate that the system self-stabilizes only after 3-4 feeding cycles. Initially, enzyme concentration increases in the duodenum above the input feed threshold, thus significantly affecting the digestion kinetics in the subsequent reactors. Two cardinal models used for the fitting of enzymatic activity data with pH values indicate satisfactory Mean Squared Error (MSE) scores (<0.0114 for Model 1, <0.0134 for Model 2). Overall, this research highlights the potential of mathematical modeling for simulating digestion and predicting experiment outcomes.