AI driven causal
modeling at scale
Efficacy prediction for drug
discovery & development
Causal modeling is a proven method to predict success in clinical trials. It rests upon the same theoretical framework as the Randomized Controlled Trial (RTC). Over 40,000 peer-reviewed publications demonstrate the importance of this methodology in contemporary scientific research.
Causal mapping of the human genome
Our proprietary causal genome dataset maps every locus on the genome to its downstream effects on biomarker levels and disease risk.
We screen biomarkers, accurately predict efficacy, and identify the top indications for every drug asset we discover.
Customers
Biopharma
Our causal models based on large-scale human genetic data have led to successful series A and B funding rounds for our biopharma partners where pre-clinical and animal data failed to move the needle.
CROs
We have enabled our strategic partner, CRO Simbec-Orion, to close several deals for clinical trials.
Pharma licensing
Most recently we have used our technology and data for drug and target discovery. We have out-licensed six drug assets.
Pipeline
Discovery
Outlicensed
Preclinical
Clinical
Commercial
Oncology (3 assets)
CNS (3 assets)
T2D (22 assets)
Repurposed Drug
New Molecular Entity