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Technology

Pioneering the next generation of drug discovery

Prediction to patient

It isn’t effective to start with a single target in mind.

Rare diseases are often not well studied and there is a limited understanding of many of the aspects necessary to support a drug discovery programme. Our AI platform overcomes these challenges by analysing millions of drug and disease data points to find novel connections that could be turned into new treatment opportunities. By applying frontier technologies across the discovery and development pipeline, we can run multiple stages in parallel and at scale.

 

This isn't traditional drug discovery

One disease, one target, one drug: it's an overly simple model, yet it's the one used by nearly all pharmaceutical companies.

The next generation of drug discovery is AI-powered, parallel and hypothesis-free. Bringing together the key three drug discovery paradigms.

Our approach

Biomedical literature and other texts

Curated biological disease data

Commercial and biochemical information

Equiv. to
300+
years of reading

100M
high confidence
relationships

1B
extracted
entities

Genetics

Transcriptomics

Orphan drug designations

Compound gene associations

in vitro/ in vivo models

AI-reasoning predictions and knowledge graph to identify novel disease-compound relationships

Drug discovery expert analysis

These predictions are reviewed by our team of experts and progressed to lab testing.

 

Lab testing and
drug-bioactivity relationships

Monotherapies
Combination therapies
Enhanced molecules

Clinical trials