Modular dynamics paradigm in biosystems multilevel modeling: Software design and PBPK/PD validation.

OBJECTIVE

The development of mechanistic-based modeling and simulation (M&S) tools is essential for advancing our understanding of biological systems. This study presents a novel M&S software tool, Cyborgs Simulator (CybSim), which employs a novel modular modeling paradigm on top of an acausal object-oriented modeling language (OOML)-defined architecture. This paradigm avoids the imposition of hard links between biosystem components and the mechanisms that drive their dynamics, thus facilitating the evolution of the biological model with newly discovered mechanisms.

METHODS

Following an examination of the fundamental principles underlying the formal definition of mechanistic models in the field of biosciences, which provides the rationale for the modular dynamics paradigm, a conceptual framework and subsequent computational design of CybSim that supports it are presented. In addition, the description includes pertinent features of CybSim, such as the multi-modeling approach, the separation of biosystems from artificial (machine) components, and their connection to algorithmic blocks. The reliability and accuracy of CybSim are evaluated through the construction and comparison of the predictions of two physiologically based pharmacokinetics (PBPK) models with their published references, in other M&S tools.

RESULTS

The logarithmic absolute errors of bacterial count predictions were below 2 % in almost all scenarios of the aditoprim model in pigs (reference model in Berkeley Madonna 8.3.23), while the mean absolute prediction errors calculated as a function of time were similar to the numerical precision of the integrators (10-10 in all scenarios of the caffeine model in humans (reference model in mrgsolve 1.5.1). PBPK/PD models in CybSim required only one flow-limited tissue for all mechanistic configurations, demonstrating the reliability of the modular modeling paradigm. The validation of CybSim included other essential features such as the incorporation of a module for accessing and predicting of biological-physiological data, an algorithmic system that includes metric blocks and pharmacodynamics, and an artificial systems module.

CONCLUSION

The study confirms that the modular dynamics paradigm can be implemented under modern acausal OOML M&S tools to facilitate the discovery and addition of new mechanistic knowledge in biosystems models. CybSim is a novel graphical modular modeling tool for biosystems that incorporates this paradigm and has been validated under several scenarios for the PBPK modeling approach.