CytoSolve addresses a fundamental limitation in computational systems biology: the difficulty of scaling integrated models of cellular function when traditional methods require merging all component models into a single software program. The authors describe a dynamic integration system that treats each pathway model as a “black box,” allowing independent simulations across distributed computing resources while synchronizing results into a composite global solution. This paradigm avoids the need for source code unification, supports heterogeneous code formats, and accommodates updates or proprietary models without centralized maintenance, enabling scalability and collaborative model development across domains. In a demonstration using the Epidermal Growth Factor Receptor (EGFR) signaling model, CytoSolve successfully partitions a large pathway into four independent submodels distributed on separate machines and recombines their solutions to match the output of a traditional monolithic implementation, proving that its distributed dynamic integration yields equivalent results with manageable computational overhead. By alleviating the maintenance and scalability issues inherent in monolithic models, CytoSolve provides a flexible platform for constructing large-scale, integrative molecular pathway simulations that can evolve as individual models develop, paving the way toward comprehensive, multi-scale biological modeling.
