[Challenges in Understanding the Biological and Pharmacological Responses Based on Emergent Complexity in Biological Systems: From Bone Metabolism to General Physiology].

Biological systems are complex, and although researchers strive to understand them, the accumulated knowledge often complicates integrative comprehension. Consolidating this knowledge can provide insights into the landscape of specific biological events. Our study on bone metabolism, focusing on the behavior of the receptor activator of nuclear factor kappa B (RANK) and its ligand (RANKL) highlighted the challenges in understanding its role across different cell types. At the same time, the study underscores the importance of exploring interactions between various players (cell types and genes/proteins) in complex systems, which is a core focus of systems biology. Analysis by mathematical models is a potentially powerful tool for describing the dynamic behavior of components in the interaction networks. However, such model-based analyses are limited by parameter availability and reliability. To address this, we proposed two approaches, i.e., sequential simulation and system-wide behavior constraints. Sequential simulation of small dynamic models offers potential in reproducing behavior in larger networks, as seen in toxicity analysis of sunitinib-related adverse effects. System-wide constraints derived from "homeostasis" help reduce the parameter search space in large-scale models, as demonstrated in model-based analysis of the effects of non-steroidal anti-inflammatory drugs (NSAIDs) on the arachidonic acid pathway. These analytical approaches offer insights into biological system dynamics and can enhance our understanding of pharmacological effects that result from perturbations in complexities of biological systems.