Multiscale Modeling in Systems Biology

Multiscale modeling in systems biology is a methodological approach designed to represent, integrate, and simulate complex biological phenomena occurring across various organizational levels, from the molecular to the tissue scale. In contrast to reductionist perspectives, this holistic framework acknowledges that biological processes emerge from dynamic interactions among components operating simultaneously in multiple spatial and temporal scales. Its development has been facilitated by the growing availability of omics data and the evolution of advanced computational tools, enabling the creation of realistic and predictive simulations. This article reviews theoretical foundations and current applications of multiscale modeling in key fields such as personalized medicine, computational pharmacology, tissue engineering, and clinical simulation. It covers integration strategies such as hierarchical and concurrent coupling, and highlights the use of specialized platforms like GROMACS, NAMD, SimBiology, and PhysiCell. The advantages of this modeling approach include the design of individualized treatments, virtual testing of biomaterials, and the optimization of clinical trials through simulated cohorts. Multiscale models allow not only a more accurate representation of biological systems but also enable the anticipation of pathophysiological dynamics, reduce drug development timelines, and enhance clinical decision-making. Their future effectiveness will depend on data interoperability, algorithmic refinement, and integration with artificial intelligence. Ultimately, multiscale modeling is a foundational tool for advancing toward a more predictive, contextual, and adaptive biology suited to the evolving challenges of contemporary medicine.