European Immunology

Computational Immunology, AI Modeling & Immune System Simulation

Computational immunology integrates artificial intelligence, machine learning and predictive modeling to enhance understanding of immune dynamics. By analyzing large-scale genomic, proteomic and cellular datasets, AI models identify disease biomarkers, predict treatment responses and simulate immune interactions at multiple scales. Digital immune twins, agent-based simulations and structural modeling help design vaccines, optimize immunotherapy strategies and evaluate drug–immune interactions before clinical testing. These tools accelerate discovery timelines and reduce development costs. Computational approaches are also improving neoantigen prediction, immune repertoire analysis and personalized therapy design. The fusion of immunology and AI is creating a powerful platform for next-generation precision interventions.