
Relation Therapeutics
Using machine learning to improve drug discovery.
Date | Investors | Amount | Round |
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- | investor | €0.0 | round |
N/A | €0.0 | round | |
investor investor investor investor investor investor investor investor | €0.0 | round | |
N/A | €0.0 | round | |
* | $15.0m | Growth Equity VC | |
Total Funding | 000k |
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RelationRx is a biotechnology startup that operates in the drug discovery market. The company aims to address the critical bottleneck in drug discovery, which is the poor understanding of the biology underlying diseases. This lack of understanding often leads to the failure of many drug candidates in trials and leaves numerous devastating diseases untreated. RelationRx's solution to this problem is a radically different approach that uses machine learning to better understand the biology of disease and discover new therapeutics rationally.
The company's platform leverages ActiveGraph ML, a machine learning technology that has been successfully used by tech companies to solve problems in computer vision and product recommendations. However, RelationRx is the first to use this technology in drug discovery at such a large scale. With ActiveGraph ML, the company can understand the vast number of combinatorial functional relationships between genes, proteins, and drugs.
RelationRx is also pioneering a "Lab-in-the-Loop" approach that integrates active learning at every step of drug discovery, from predicting cell states to validating new targets. The company uses real cells from proprietary biobanks to generate genomic data, providing direct insights into critical biological relationships. This data is then fed into the machine learning systems, which request new experiments to improve their predictive ability.
The company's business model revolves around using its platform to discover new therapeutics. It generates revenue by licensing its discoveries to pharmaceutical companies for further development and commercialization.
In summary, RelationRx is a biotech startup that uses machine learning to revolutionize drug discovery. Its innovative approach could potentially lead to the discovery of treatments for diseases that are currently untreatable.
Keywords: Biotechnology, Startup, Drug Discovery, Machine Learning, ActiveGraph ML, Lab-in-the-Loop, Genomic Data, Therapeutics, Pharmaceutical Companies, Proprietary Biobanks.