p38α has multi-functional mechanisms of action. This has enabled GEn1E to build its unique AI/ML-based technology platform creating a beachhead in inflammatory diseases, which currently do not have effective treatment. Our Machine Learning models that trained using this data span the entire process chain from drug discovery to clinical trials. This enables us to accelerate the drug development cycle, create cost efficiencies and take multiple shots at the goal.
Continuously and efficiently expand of our pipeline of novel compounds
Select best indications by mapping inflammatory biomarkers of our NextGen p38 compounds with disease biomarkers
Increase likelihood of success in clinical studies
Our AI/ML Platform is Full-Chain and spans entire process from Discovery to Clinical Studies enabling efficient Drug Development. We have designed Machine Learning models that uses disease mapping databases to identify other indications for the drugs we have discovered, allowing us to broaden the scope of diseases which could be treated with our drugs. Neural Networks, Gradient Boosting Methods and Hidden Markov Models are being used to accelerate drug development.
Gene expression analyses show that GEn1E drugs are selective, immunomodulating and protect the anti-inflammatory pathways.
This leads to safe and effective treatments for inflammatory diseases. Each inflammatory disease has its own unique signature as expressed with multiple biomarkers.
GEn1E matches its drug’s unique signature with the inflammatory disease signature to select the best match of the drug for the disease.
The key building blocks of our platform include a curated database, a mapper and a machine learning engine which connects the dots between genes, pathways, proteins, diseases, and our compounds.
This includes proprietary data for GEn1E drugs as well as data for inflammatory diseases
Each inflammatory disease has its own unique signature as expressed with multiple biomarkers. The platform matches our drug’s unique signature with the inflammatory disease signature to select the best match of our drug for the disease
We utilize a continuous feedback loop across the entire process from discovery to clinical studies.
Neural Networks, Gradient Boosting Methods and Hidden Markov Models are used to accelerate drug development
