Features
Polygenic risk score (PRS) modeling
Disease risk prediction and detection
Population genetics analysis
Reduce sequencing costs by 50-90%
Eliminate bespoke software pipelines
Accelerate research timelines
Secure genetics data processing
Machine learning integration
Collaborative research platform
SaaS-based workflow (no local install)
Autonomous hypothesis generation with agentic AI
Multimodal patient data integration (spatial, multi-omics, clinical)
Clinical trial design and patient stratification
Patient and population analytics
Early portfolio decision insights
Patient validation through wet lab infrastructure
Target ID engine distinguishing novel from rediscovery
Collaborative network of 30+ academic centers
Multi-year partnership with Sanofi for custom AI agents
NVIDIA collaboration for biological benchmark testing
Narrows search space in aging research
K Pro connected to front-end user feedback
Support for antibody-drug conjugate development via spatial biology
