An Agent-based Learning Model Integrating Sex Differences in Renal Cell Carcinoma - Simulation and Analysis Codebase

The project implements an RCC-specific agent-based learning model (ALM) developed as python porting and enhancement of the OncoAgent simulator, designed to simulate tumor-immune interactions in a three-dimensional environment. As its main contributions, the model integrates : Sex hormone-dependent modulation mechanisms, togeather with treatment effects of immune checkpoint inhibitors (ICIs) and tyrosine kinase inhibitors (TKIs); Tumor genetic evolution via a genetic algorithm; Data-driven parameter optimization using clinical outcome data. The archived version includes: Full source code of the enhanced RCC agent-based model; Simulation interface, execution and training scripts; Analysis scripts used to reproduce figures and reported result. The model was developed in Python and can be executed in 3D interface mode using Solara and pythreejs. All dependency specifications for reproducible execution are available in the requirement specification files.