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.

28.5KDrugs 2,000DiseaseCausing Traits 12KDiseases 22 MillionHuman Genomes 1 Million ComputationalExperiments/Day on the Cloud

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.

Simbec OrionImmunGeneticsNucleomeApollo Health VenturesEternygenSamsara TherapeuticsImmu PharmaAtriva TherapeuticsGalileo Biotech3-ZAlfa IntesRefoxy Pharma

Pipeline