Detecting toxicity
before human test
We treat cells as dynamic systems.
Toxicity prediction
Our solution enable drug developpers to get key safety risk information early in the development to avoid costly R&D faillure
Personnalized output
The tool is designed to fit your difference. The output is adapted from your drug type to offer the most insightful result.
Facilitated integration
Facilitated Integration thanks to compatibility with industry standard software to facilitate data input and output analysis.
Solution system
We build computational models that simulate human cellular response to biologic therapeutics at single-cell resolution.
By combining foundation-model embeddings with self-supervised learning on large-scale perturbation atlases, we predict cytokine release, immune activation, viability shifts, and toxicity pathways before you run the experiment.
Drug settings
Cell type
Subliminal 1
Output
Pathway Impact
Toxicity risk
Immune response
Cell labels
Subliminal 1,
A world model for cell
Trained self-supervised on millions of single-cell perturbation profiles, Subliminal learns the intrinsic structure of cellular state how cells exist, transition, and respond to intervention. Without biological labels, the model discovers emergent properties: cell identity, pathway activation, mutation signatures.
We treat cells as dynamic systems. Our models factorize cell state into identity, cell-cycle position, and drug-induced response, enabling predictions that generalize across cell types, patient backgrounds, and experimental conditions
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