01
INTERACTION PREDICTION
Predict (off)target interactions
Deep-learning models screen candidate structures across a broad protein space to predict potential on-target and off-target interactions.
DRUG SAFETY PLATFORM
Drug safety
engineered,
not discovered.
Cytocast maps the mechanistic chain from compound to clinical side effect, pathway by pathway, so drug teams see not just what will fail but which off-target causes it.
From compound to clinical insight
- CompoundStructure-based input
- Off-targetBinding predictions across 7,700+ proteins
- Perturbed pathwayPropagation through protein complexes and pathways
- Tissue effectSimulated across 15 human tissues
- Predicted side effect1,200+ side-effect endpoints
WHY IT MATTERS
Drug teams see fragments of safety risk. We connect them.
Disconnected safety evidence can leave critical liabilities unresolved during development.
Substantial time and money may therefore be invested before clinically relevant side effects emerge, sometimes only after compounds reach patients.
We add the missing piece: predicted clinical side effects to reduce cost, time, unnecessary animal studies, and patient harm.
HOW IT WORKS
From structure to adverse event.
Every step grounded in biology.
Every prediction connected to a mechanism.
02
MECHANISTIC SIMULATION
Model biological effects across 15 tissues
Predicted interactions are propagated through tissue-specific protein complexes, signaling networks, and biological pathways to simulate downstream effects.
03
SIDE-EFFECT MAPPING
Connect perturbed mechanisms to clinical outcomes
Changes in protein complexes and pathways are mapped to 1,200+ clinically defined side-effect endpoints.
Explore the digital twin architecture
Compound information, protein interactions, and clinical side-effect data connect through the Cytocast Digital Twin Platform.
Select the diagram to view it full size
PRODUCT
One platform for every critical safety decision.
Cytocast supports compound selection from early discovery to preclinical nomination, adapting the depth of analysis to each development stage.
Hit to lead
Cytocast
Screener
Identify early side-effect signals across large compound sets and eliminate weaker candidates before committing significant resources.
Lead optimization
Cytocast
Optimizer
Rank candidates by predicted safety profile and understand the protein interactions, pathways, and tissue effects behind their differences.
Preclinical & IND-enabling
Cytocast
Nominator
Build a decision-grade safety profile combining clinically relevant side-effect predictions with traceable biological mechanisms to support candidate advancement.
1,200+
Other AI and simulation tools focus on a handful of toxicity endpoints. Cytocast predicts over 1,200 clinically relevant side effects across the full body.
300+
Our performance on the 300+ best predictable side effects outperforms translation accuracy from animal models.
Research-first
Built by professors in systems biology and computational biology, our platform is grounded in world-class science and led by a research-first team.