Accelerating Oncology R&D via Zero-Shot Prediction & High-Fidelity In Vivo Validation
- Bridging the gap between computational hypothesis and biological reality: Utilizing a zero-shot drug response platform to prioritize therapeutic candidates for novel drugspecimen pairs without the requirement of prior compound-specific training data
- Overcoming Temozolomide (TMZ) resistance in Glioblastoma (GBM): Demonstrating the platform's predictive accuracy in identifying effective novel combination strategies within GBM Patient-Derived Xenograft (PDX) models that exhibit established resistance to standard-of-care
- High-fidelity in vivo validation of AI-generated insights: Presenting comparative data where zero-shot predictions were stress-tested in orthotopic models to confirm accuracy, providing a robust framework for increasing translational confidence and de-risking early-stage development programs