We present the first clinical application of the Schättler mathematical framework for metronomic chemotherapy using data from 30 patients with metastatic gastrointestinal cancer from the COMET trial. The model, comprising three coupled ODEs with 12 parameters representing tumour growth, angiogenesis, and immune response, was successfully fitted to individual patient data through AI-assisted optimization, achieving low fitting errors (median squared error: 0.003 for stable disease, 0.007 for progressive disease) at day 56. The growth control parameter \(\xi\) emerged as a potential biomarker, with distinct ranges between stable disease (0.066–0.153) and progressive disease (0.093–0.177), suggesting a critical threshold around \(\xi = 0.115\) . Model parameters showed expected interdependencies reflecting the coupled nature of tumour-microenvironment interactions. While the model demonstrated strong fitting capabilities, prediction of progression-free survival showed moderate correlation ( \(r = -0.71\) ), highlighting the complexity of long-term outcome prediction in metastatic disease. Drug effect parameters were consistently low (0.003–0.09), aligning with the modest clinical benefits observed in recent metronomic chemotherapy trials for metastatic gastrointestinal cancer. This proof-of-concept study establishes the feasibility of applying the Schättler framework to clinical data, with parameter estimates representing exploratory values requiring external validation before clinical implementation. Future studies with larger cohorts and multiple time points will be essential to validate these findings and refine the model for prospective clinical application.
