Prediction grounded in biology you can trace
A mechanistic, causal modeling platform that represents the cause-and-effect biology of the patient and the drug, then sharpens it on clinical data - so every prediction is traceable to the biology that drove it.
We engineer the biology -
then let the data sharpen it
Simaya builds a mechanistic model of the patient and the drug - grounded in the drug's known mechanism of action - and calibrates it on clinical data under controlled, leakage-aware validation.
Patient biology
How the drug works
Clinical data
signals propagate through the network
Responder / Non-responder
Toxicity level
Dose optimization
Three predictions per patient
For each patient-drug pair, the platform returns the three estimates that inform whether a therapy advances in your program - and who to enroll in your trial.
Will they respond?
A response probability for this patient and this drug, with the biological drivers behind it.
What's the risk?
A predicted toxicity-risk level, so risk is visible during cohort design, before dosing.
How much?
A model-estimated dose range tuned to this patient's biology, not a population average - to support, not replace, dose decisions.
Where Simaya fits in your pipeline
Trial design
Define enrollment criteria informed by which patients are predicted to respond.
Patient selection
Rank and prioritize trial candidates by predicted response and toxicity risk.
Dose justification
Support dose decisions with mechanistic, per-patient, inspectable evidence.
Bring your program. We'll model it.
Walk through your indication with our team and see the platform applied to your data - handled under defined privacy, security, and IP controls.