Make better immuno-oncology decisions with mechanistic modeling

This poster shows a quantitative systems pharmacology platform that models the full cancer immunity cycle to predict treatment response, optimize combination therapies, and identify predictive biomarkers in immuno-oncology.

See how Certara’s IO Simulator enables:

Prospective prediction of combination therapies using monotherapy-calibrated models
Mechanistic insight into immune response dynamics across tumor, blood, and lymph node compartments
Biomarker identification, including CD8+ infiltration and tumor burden effects
Virtual population simulations to support translational decision-making

Based on a melanoma case study, this work demonstrates how QSP modeling can reproduce clinical outcomes and predict combination efficacy without additional model re-tuning.