Averages hide responders
Patients with the same diagnosis often respond very differently to the same therapy. Population averages hide the subgroups that benefit, and the ones that do not.
EndoVia Therapeutics
Mechanistic precision oncology for drug developers
We combine functional tumor-model data, molecular profiling and mechanistic modeling to explain and predict treatment response.
The challenge
The same treatment. Different biology. Different response.
Single-layer readouts
Viability alone shows that a tumor model responds, not why. Without signaling and molecular context, a response cannot be explained or transferred.
Trial-and-error development
Without mechanistic insight, compounds and combinations are tested one by one, and clinical trials can fail even when a responder subgroup exists.
We turn biological differences into better development decisions.
Our platform runs as a closed loop. Every experiment improves the model, and every model output points to the next experiment.
Laboratory ↔ Model
Profile
Characterize tumor models by functional drug response, signaling and molecular profiles.
characterize tumor models by functional drug response, signaling and molecular profiles.
connect these measurements in mechanistic models, supported by machine learning and AI.
generate testable predictions of sensitivity, resistance and combination effects.
test predictions in the lab and feed the results back into the model.
define biologically meaningful subgroups for development decisions.
Experimental findings feed back into the model. Prediction and validation develop together.
One platform, three layers
Biologically diverse tumor models
cancer cell lines and patient-derived models that capture patient-like differences.
Integrated response data
functional response, signaling and molecular profiles measured on the same models.
Predictive model
mechanistic modeling and machine learning that link drug targets to response.
Built for development decisions
Responder biology
which tumors respond, and why?
Biomarker hypotheses
what distinguishes responders?
Compound and formulation prioritization
which candidate goes next?
Combination opportunities
what works together, and how?
Reduce trial risk
which patients are most likely to respond, before the trial starts?
Support safer treatment
which adverse effects and interactions can we anticipate early?
Starting with cannabinoids
Cannabinoids show broad anticancer activity in the lab, yet clinical results remain inconsistent. That makes them the ideal first test for our approach. Through PRECISION-ECS, funded by the European Innovation Council, we are building the evidence in melanoma.
See our programs →
Partners and funders
Frequently asked questions
View all FAQs →What does EndoVia do?
We help drug developers understand which tumors respond to a treatment and why, by combining laboratory testing, molecular profiling and predictive modeling.
Is the platform limited to cannabinoids?
No. Cannabinoids are our first application. The approach works for any compound whose targets can be mapped to signaling pathways.
How can we work together?
Most collaborations start with a focused pilot on one defined question. Scope and timing are agreed per project.
Have a response question in your oncology program?
Tell us about your compound and the decision ahead. A short, non-confidential description is enough to start.
Discuss a project