Computational drug discovery
Medicines that start at the cause.
Etiova begins with the causal biology of disease — the genetic loci and mechanisms that drive it — and finds the drugs and targets that act on them, ranked by network, structural, and machine-learning evidence.
Approach
From the cause of disease to medicine
Human biology tells us what causes a disease. Our job is to turn those causes into candidates worth testing, then carry the strongest forward.
Start at the cause
Every programme begins from the causal biology of the disease — the loci and mechanisms that drive it, not a favourite target.
Rank the evidence
Network proximity, structural prediction, and machine learning score which approved and clinical-stage drugs reach those causes.
Carry the best forward
The candidates where independent evidence converges become the shortlist for validation and partnering.
First programme
IgA nephropathy
The leading cause of kidney failure across much of Asia, with a well-mapped causal biology and no therapy that reverses fibrosis. It is where our method has the most to say, and where we started.
Using only data that predates each approval, the pipeline recovers known IgAN drugs blind: atrasentan at roughly the 1st percentile before its 2025 approval, and sibeprenlimab's target years before it reached patients.
Get in touch
For partners, clinicians, and investors
If you are developing in a genetically-anchored disease, or evaluating an asset, we would like to talk.
hanif@etiova.com