
AI-Powered Drug Combination Predictions
Bridging preclinical data to clinical outcomes with multimodal AI
MADRIGAL is a breakthrough multimodal AI model that predicts clinical outcomes of drug combinations by integrating diverse preclinical data types, addressing a critical gap in drug development.
- Leverages structural, pathway, cell viability, and transcriptomic data to make accurate clinical predictions
- Identifies safe and effective drug combinations for conditions including type II diabetes, MASH, and acute myeloid leukemia
- Significantly improves upon existing models that rely on limited data types
- Potential to accelerate drug development by reducing failed clinical trials
This innovation represents a major advancement for pharmaceutical research, enabling more efficient identification of promising drug combinations while reducing development costs and timelines for bringing new treatments to patients.
Multimodal AI predicts clinical outcomes of drug combinations from preclinical data