A unified approach to optimize multidrug chemotherapy using a pharmacokinetic (PK)/enhanced pharmacodynamic model was developed using the vascular endothelial growth factor receptor (VEGFR) signaling system. The base VEGFR network model, characterized by ligand-receptor interactions, enzyme recruitment (Grb2-Sos, phospholipase C γ (PLCγ), and phosphoinositide-3 kinase (PI3K)), and downstream mitogen-activated protein kinase and Akt cascade activation, was linked to a sunitinib (VEGFR inhibitor) PK model and underwent Sobol sensitivity analysis that revealed potential sunitinib-enhancing mechanisms. Drugs targeting these mechanisms (a VEGF inhibitor, a PI3K inhibitor, a PLCγ inhibitor, and a mitogen-activated protein kinase inhibitor) and sunitinib were input to optimization-based control analyses to design multidrug regimens that maintained 80% pERK and pAkt inhibition for 28 days while minimizing drug dose. The resultant combination regimens contained both continuous and discontinuous schedules, mostly at low doses, and were altered by oncogenic mutations. This pipeline of computational analyses demonstrates how model-based methods can capture the complexities of drug action, tailor cancer chemotherapy, and empower personalized medicine.