Simulating Multisystem Flares Across Phenotypes

Abstract Background: Multisystem presentations involving hypermobility, pain, fatigue, mediator-related symptoms and orthostatic intolerance are often examined within separate biological domains, limiting the ability to test cross-domain flare hypotheses. Objective: To present an executable in silico scaffold for simulating multisystem flares across neuroimmune, autonomic and connective-tissue phenotypes as a cautious precursor to future digital-twin development. Methods: Mechanistic literature was translated into a dimensionless ordinary differential equation framework using conservative evidence-to-model rules. Candidate nodes were retained only where they represented measurable biological processes, plausible causal intermediates, explicit state variables or future empirical tests. Trait vulnerability, dynamic activation, external drivers and computational perturbation terms were separated. Supplementary File 1 provides the mathematical specification, parameter-derivation workflow, safeguards, scenario-boundary notes, sensitivity, and reproducibility audit. This is then used to build the Python code, which dynamically generates the products to allow inspection and validation/falsification scenarios to be modelled. Supplementary File 2 provides the executable Python source, and Supplementary File 3 provides the GraphViz network representation. PRISMA and TRIPOD+AI were used only as reporting boundaries, not as claims of systematic review conduct or clinical prediction model development. Supplementary File 3 provides the directed systems graph with network topology 'atlas'. This is a ZIP file of 3 files: the source DOA, SVG viewable model and PNG image (artefact). (Tip: Open Source GraphViz is best used to generate the imagery from the source .dot file. Then use InkScape to generate updated images if needed, due to the resolution and scale of the SVGs from GraphViz.) Supplementary 4 is an HTML5 application implementing the mathematics and models the graph for real-time, user-led manipulation of the subject, life-course event impacts, and a range of interventions. (NB: This is not a pre-digital twin, as it is NOT calibrated.) Results: The framework defines a 16-state model spanning extracellular matrix remodelling, MMP/TIMP-related protease balance, damage-associated signalling, mast-cell and mediator activation, cytokine and oxidative burden, endothelial permeability, glycocalyx/barrier function, venous pooling, autonomic regulation, interoceptive load, pain amplification, neuroimmune sensitisation and a dimensionless Composite Presentation Index. The CPI is a comparative simulation output, not a validated clinical score, diagnostic measure, patient-reported outcome, or healthcare utilisation index. Conclusion: The scaffold converts a complex cross-domain hypothesis into inspectable topology, equations, simulations and falsifiable future data requirements. It is a pre-calibration computational scaffold, not a diagnostic, prognostic, therapeutic, or patient-specific digital twin instrument.