This company utilizes a machine learning platform integrating genomics, transcriptomics, and proteomics to identify novel, druggable protein targets across the entire human genome. Their methodology discovers noncanonical proteins previously overlooked by conventional drug discovery, offering new therapeutic avenues for over 1300 human diseases. The resulting target portfolio provides a substantial, validated resource for developing treatments against complex and difficult-to-treat conditions.
Funding
Funding not disclosed
IAFounders
Product
Problem
Current therapies target only a small fraction (1-2%) of the human genome, limiting the discovery of novel therapeutic targets for many diseases. The remaining 98%, often referred to as the "dark genome," is largely unexplored, potentially overlooking critical proteins and disease mechanisms. This narrow focus contributes to the lack of cures for numerous human diseases.
Solution
NonExomics leverages a proprietary platform that integrates genomics, transcriptomics, proteomics, and machine learning to identify druggable noncanonical proteins encoded by the entire human genome. This platform has identified and validated over 250,000 previously undiscovered proteins and associated approximately 3,000 novel targets with over 1,300 human diseases. By querying the entire genome, NonExomics aims to expand the landscape of potential drug targets and address diseases currently considered untreatable. The company's approach challenges the conventional focus on a small portion of the genome, opening up new avenues for therapeutic intervention.
Target Audience
The primary audience includes pharmaceutical companies, research institutions, and drug developers seeking novel therapeutic targets and innovative approaches to drug discovery.
Features
- Integrated platform combining genomics, transcriptomics, proteomics, and AI-based methodologies
- Identification of noncanonical proteins derived from the entire human genome
- Discovery of novel therapeutic targets associated with a wide range of human diseases
- Machine learning algorithms for target identification and validation
- Experimental validation of target druggability and clinical significance
- Growing patent portfolio covering targets associated with 1,365 human diseases