The medical world model for drug development
Emular Labs is building an AI trained on millions of real-world health records and drug biology to simulate how people's health evolves under different treatments.
What is a medical world model?
A world model learns how a system changes over time, so it can predict what happens next under different actions. Ours does this for human health: given a patient and a treatment, it predicts how that patient's health is likely to change over the months and years ahead. It helps pharma and biotech teams test drugs virtually, optimise trials and de-risk development before enrolling real patients.
How the medical world model works
Select a step to explore it.
structure
targets
knowledge
- Candidate drug
- Standard of care
- No treatment
Illustrative example, not model output.
Learns dynamics, not correlations
In routine care, sicker patients tend to receive stronger treatments, so the outcomes that follow reflect both the drug and who received it. The model learns how a patient's state changes under a treatment over time, using a causal training design that adjusts for why each treatment was given. It also captures how differently patients respond.
Products for clinical development teams
Assess a trial, optimise it, or find where else a drug could help.
Trial Assessment
Will this trial succeed in the patients it will actually enrol?
Before the go/no-go decision, predict the drug's effect against standard of care, with uncertainty, and surface early safety signals in the eligible population.
Trial Optimization
How can the trial be smaller, faster and better powered?
Create digital twins of patients to give a trial more statistical power or a smaller control arm.
Indication Expansion
Where else could this drug deliver clinical benefit?
Look across the drug's life and rank new indications by predicted benefit, to inform lifecycle and partnering decisions.
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