Forms Dynamics in Human Pathology: A Gestalt-Inspired Perspective on In Silico Ecophysical Modelling

Understanding pathological processes remains challenging because clinical descriptions primarily rely on phenotypic observations, while the underlying dynamical mechanisms that generate and stabilize disease states often remain implicit. This article introduces forms dynamics as an applied physics framework aimed at interpreting pathology as the dynamical evolution of structured configurations sustained by continuous exchanges of energy, matter and information with the environment. The approach integrates concepts from non-equilibrium thermodynamics, complex systems modelling and Gestalt-inspired structural reasoning. Within this perspective, pathological systems are represented through physically meaningful variables and fluxes whose interactions can be expressed through coupled balance equations or equivalent graphical schematizations. Empirical data, including clinical observations, diagnostic measurements and network-based analyses of biological interactions, inform the identification of relevant variables and pathways. Model calibration constrains parameters using physiological ranges, characteristic timescales and observed trajectories, while validation relies on the consistency of the resulting dynamical regimes with clinical phenotypes and responses to perturbations. Within this framework, physiological conditions correspond to stable attractors in the system’s dynamical landscape, whereas pathological states emerge from altered coupling between variables and fluxes, leading to alternative stable or metastable regimes. By providing a physically grounded representation of pathological dynamics, forms dynamics offers a unifying modelling strategy for complex diseases and may support translational research, physics-informed digital twins and more interpretable computational tools for clinical decision support.