Features
ExpressionVAE discrete-token encoding for single-cell data
Clinical response prediction from baseline biopsies
Virtual cell models encoding patient biology
Pre-clinical to clinical data integration
Trial design optimization (e.g., power analysis)
Drug rescue identification for failed compounds
Foundation models trained on multi-omics data
Presentation at ICLR '26, CSHL '26, ICML '26
Public research blog with technical deep dives
AI-powered patient identification from EMRs
Natural language processing on unstructured clinical notes
Real-time eligibility screening
Automated patient-trial matching
Integration with clinical trial management systems
Scalable cloud-based platform
HIPAA-compliant data handling
Customizable trial criteria input
Reporting and analytics on recruitment metrics
