Modern oncology is shifting from static, tumor-centric paradigms toward integrative, adaptive models that account for both cancer and host biology. Liquid biopsies and multiomics now offer real-time insights into tumor evolution, but integrating systemic, host-derived biomarkers, such as immune, metabolic, and physiological indicators, can further enhance precision. This evolving framework supports the development of a Global Biomarker and Vulnerability Score (GBVS), synthesizing multi-scale tumor-host data to guide dynamic, AI-assisted treatment strategies. Cancer is approached not as a fixed entity, but as a dynamic, evolving system embedded within the organism’s internal climate. Expert AIs architectures like AlphaZero may continuously assimilate these inputs to predict resistance, tailor therapy sequences, compute and adapt interventions based on the GBVS computed continuously in real time, from longitudinal data obtained from the patient. Process Oncology treatment designs incorporate both targeted oncologic therapies and host-modulating interventions, ranging from circadian-aligned drug delivery to microbiome modulation. Systems-level Process Oncology is based on the proposition that managing metastatic disease may be more effective when guided by both feedback-informed, cancer-directed and organism-level strategies. Rather than eradicating every malignant cell, the goal becomes restoring balance-transforming cancer into a controllable condition through intelligent, responsive, and individualized care.