An Updated Review on the in vitro and Computational Approaches for the Simulation of Carbohydrate Digestion

Recent advances in gastrointestinal research have increasingly focused on understanding the digestion of carbohydrates, a major energy source with complex physiological implications. This review summarizes current approaches for investigating carbohydrate digestion, including static, semi-dynamic, dynamic, and advanced computational models. Static models are widely used due to their simplicity and reproducibility. They are particularly valuable for studying how food processing affects carbohydrate digestibility, exploring structure – function relationships, and quantifying glucose release rates in vitro, which supports the screening and optimization of low-GI foods. Semi-dynamic models, by incorporating time-dependent parameters such as gradual pH shifts and gastric emptying, offer improved physiological relevance while maintaining operational feasibility. Dynamic models, by simulating physiological digestive processes and enabling real-time monitoring, have been used to predict glycemic responses, optimize starch-based formulations, investigate macronutrient interactions, and support the development of targeted medical nutrition. Recent computational models provide valuable tools for simulating digestive processes. These models combine theoretical frameworks with experimental data to facilitate mechanism analysis, variable screening, and personalized nutrition planning. Although computational models cannot fully replace laboratory experiments, they enhance research efficiency and offer valuable new approaches for analyzing carbohydrate digestion. However, further research is essential to comprehensively explore the potential of this methodology.