Predict a drug's effect.
Design the trial that proves it.
Emular predicts how a drug will affect patients, so pharma and biotech teams can pick the right candidate and find the protocol most likely to read out.
AI made candidates cheap. Choosing between them did not get easier.
Molecule design has come down from four to six years to twelve to eighteen months, and the pipeline is now flooded with AI-assisted candidates. But cheap candidates have not changed the low success rate, or the cost of testing them in humans. The bottleneck is deciding which candidate to advance.
A world model that reasons about cause, not correlation.
Four capabilities on one causal engine.
Effect, not disease severity
In health records, the patients who get a drug are usually the sickest. A correlation model sees that, links the drug to worse outcomes, and concludes it is harmful when it is really picking up how ill those patients were. Emular reasons about the same patient with and without the drug, and recovers the treatment effect itself.
Find the protocol most likely to read out
Emular runs a proposed trial across its patient population and predicts the outcome. Because it runs at scale, you can vary eligibility criteria, subgroups, endpoints and dose to see who benefits, and settle the design before the protocol is locked.
Replaying trials the model never saw
We take completed randomised trials that were never part of training, run them through the model, and check whether it reproduces the published result. Reproducing a real trial is direct evidence that the causal predictions hold.
The model never learns a drug by its name.
It learns the molecule, the targets it binds and the pathways those targets perturb. A candidate that has never been given to a patient still has all three, so the model can reason about drugs it has never seen, and carry that reasoning up from chemistry to a trial readout.
Molecule
The compound and its structure
Target
The proteins it binds
Pathway
The physiology those targets perturb
Patient
One trajectory, with and without the drug
Trial
The outcome across a whole trial population
One model, three products.
Built for pharma and biotech, priced to the decision each one de-risks.
Trial Design
Simulate many protocols and pick the one most likely to succeed. Delivered as a protocol-level readout before first patient in.
Asset Diligence
Judge an in-licensing candidate before the deal. An independent, model-based read on the asset, on deal timelines.
Platform
Run any trial design through the simulation and fine-tune the model on your own data. Continuous access across the portfolio.
Interested in Emular?
We work with clinical development, business development and portfolio teams at pharma and biotech companies, and with investors diligencing clinical-stage assets. Pilots, research collaborations and investment enquiries are all welcome.
Please include your organisation and a brief description of what you would like to discuss. We normally reply within two business days.
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