Healx
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
Publications
14 July 2022
Discovery of multiple clinical candidates for treatment of Fragile X Syndrome using AI-Enabled drug discovery
Discovery of multiple clinical candidates for treatment of Fragile X Syndrome using AI-Enabled drug discovery
21 April 2022
BioNLP Workshop 2022
Slot Filling for Biomedical Information Extraction
25 June 2020
AKBC SciNLP Workshop 2020
Data augmented relation extraction (DARE) with GPT-2
20 April 2020
Reference Module in Biomedical Science
Drug combination modeling
1 November 2019
EMNLP DeepLo Workshop 2019
Deep bidirectional transformers for relation extraction without supervision
1 November 2019
EMNLP DeepLo Workshop 2019
Reasoning over paths via knowledge base completion
1 October 2018
Nature Reviews Drug Discovery
Drug repurposing: progress, challenges and recommendations
1 June 2018
Human Molecular Genetics
The antidepressant tianeptine reverts synaptic AMPA receptor defects caused by deficiency of CDKL5
1 February 2016
Nature Reviews Drug Discovery
Antibiotic resistance breakers: can repurposed drugs fill the antibiotic discovery void?
1 February 2016
Drug discovery today
Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives
1 February 2016
Journal of Medicinal Chemistry
Prediction of antibiotic interactions using descriptors derived from compound molecular structure
1 October 2018
Frontiers in Pharmacology
Using machine learning to predict synergistic antimalarial compound combinations with novel structures
1 March 2019
Neuropharmacology
Repurposing available drugs for neurodevelopmental disorders: the fragile X experience
30 August 2018
Bioinformatics
Understanding and predicting disease relationships through similarity fusion