A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying

Area of Science:

• Computational biology
• Physiological modeling
• Systems biology

Background:

• In-silico models of biological organisms are complex and time-consuming to develop.
• Model development is iterative, relying on literature and experimental data.
• Existing methods require significant programming effort and lack flexibility.

Purpose of the Study:

• To introduce a flexible and user-friendly plug-and-play scheme for biological systems modeling.
• To reduce programming effort in creating and adapting physiological models.
• To facilitate dynamic model building and simulation.

Main Methods:

• The scheme requires users to provide component structures and experimental data in tabular format.
• Component behavior is described mathematically and linked externally during simulation.
• Biological systems are abstracted into a network of smaller, independently behaving sub-systems.

Main Results:

• The scheme was demonstrated by modeling human gastric emptying dynamics.
• The model successfully predicted gastric emptying under varied intestinal nutrient infusion.
• Predictions showed less than 6% error in estimating half-emptying time, verified by a human study.

Conclusions:

• A new plug-and-play scheme for biological modeling has been developed.
• The scheme reduces programming effort by abstracting systems into sub-systems.
• Modeling and simulation are automated, becoming machine-readable and executable tasks.