Advances in multiregion sequencing have revealed extensive intratumor heterogeneity (ITH) — the presence of genetically distinct subclones within a single tumor. These findings support a branching evolution process (BEP), in which multiple subclonal lineages evolve in parallel from a common ancestor. ITH profoundly influences tumor behavior, including hallmarks of cancer, and growth and invasion phenotypes. It also underlies the emergence of therapeutic resistance, as distinct subpopulations may harbor mutations that confer survival advantages. We have built a 2D, multi-scale, data-driven agent-based model (ABM) for BEP with Hallmark Integration (BEP-HI) that simulates melanoma evolution under the hallmarks of uncontrolled proliferation, resistance to apoptosis, immune evasion, and genetic instability. The model is calibrated for BRAF-associated superficially spreading melanoma with the inclusion of key driver genes. We find three ITH regimes: clonal sweep (single dominant clone), subclonal sweep (multiple subclones cluster together), and fractal (high heterogeneity). We use cross-PCF to quantify spatial relations and find that the most aggressive clone closely clusters with the second most aggressive. Additionally, we observe that immune cell density is higher in hot tumors than in cold tumors, and shows opposing dynamics as base mutation rates increase. By integrating differential equation models for the mechanisms of action of targeted BRAF inhibitors and anti-PD1 immunotherapy, we aim to predict how ITH affects the onset of drug resistance, and to use a virtual patient cohort to optimize combination therapy to overcome this resistance.