Virtualizing ADC Development
- Presenting Turbine’s Virtual Lab-powered platform for predictive modeling and automated validation of payload and ADC responses across diverse molecular contexts at scale
- Showcasing how virtual screening enables payload–indication ranking and identification of synergistic dual-payload combinations, including examples with DXd and DM1
- Demonstrating that ADC sensitivity prediction integrates target antigen expression with payload potency, enabling biologically grounded positioning of ADCs across cancer subtypes
- Highlighting how virtual perturbations uncover predictive biomarkers and resistance mechanisms, including TROP2-mediated Dato-DXd sensitivity and SLFN11-driven TOP1i resistance