AI-Driven Safety Prediction.Confirmed in Human Biology.
Predict toxicity with explainable AI.
Validate in human organ-on-chip systems.
In partnership with Digital Ether Computing
From AI Insight to
Safer Molecules
Translate computational risk into actionable molecular decisions — grounded in human biology.
Predict → Optimize → Validate
AI and biology working as one system — each cycle making the next smarter.
AI Profiling
Score DILI, neurotox & ADMET risk across your library.
Risk Mapping
Pinpoint which substructures are driving safety signals.
Analog Design
Generate safer candidates that preserve bioactivity.
Validation
Confirm risk in human organ-on-chip — closing the loop.
Why Drug Safety Fails Too Late
By the time toxicity surfaces, billions are already spent.
of candidates never reach approval
Most fail on safety or efficacy
of clinical failures are ADMET-related
Caught too late in development
average cost to bring a drug to market
Late failures drive the largest share
What Your Team Gains
Practical advantages at every stage of your safety workflow.
Faster Decision-Making
AI triage compresses weeks of safety analysis into hours. Focus resources on your best candidates.
Human-Relevant Validation
NANOSTACKS liver, brain, and multi-organ models reflect human biology — not rodent physiology.
Explainable AI Insights
Structural risk maps are interpretable and defensible — to your team, collaborators, and regulators.
AI-guided optimization improves compound quality across key drug-like properties, balancing potency, safety, and developability.
Not Just AI. Not Just Wet Lab.
Two specialist teams. One integrated workflow. Both working in your service.
Digital Ether Computing — AI
Graph neural networks trained on safety data
DILI & neurotoxicity risk prediction
Explainable heatmaps per structural feature
Safer analog generation
Revivocell — Biology
NANOSTACKS microphysiological systems
Liver, brain, and multi-organ models
Mechanistic biological readouts
Experimental validation of AI predictions