Closed-loop deep learning in early-stage drug discovery - cloud platform for targeted protein degradation: CelerisTx - Celeris One Platform

Programme(s): HORIZON.3.1 - The European Innovation Council (EIC)

Topic(s): HORIZON-EIC-2022-ACCELERATORCHALLENGES-01 - EIC Accelerator Challenge: Technologies for
Open Strategic Autonomy

Call for proposal: HORIZON-EIC-2022-ACCELERATOR-01

Funding Scheme: EIC-ACC - EIC-ACC

Grant agreement ID: 190126641

Objective:
Celeris Therapeutics is a deep learning company that uses innovative, in-silico methods such as geometric deep learning and graph neural networks to degrade currently undruggable targets (pathogenic proteins). The platform shall make a broad impact by addressing currently incureable diseases such as Alzheimer's, Parkinson's, and different types of cancer like breast and prostate cancer.

Celeris Therapeutics' technical solution is the web application (orchestration platform) Celeris One.
It consists of three modules: Hades (target ID), Xanthos (predicting biomolecular interactions and ligand design), Hephaistos (automated synthesize and validate).
The addressed market is in the early-stage drug discovery and users are pharmaceutical and biotech companies with a focus on Targeted Protein Degradation.
The targeted customers are med. and comp. chemists, that currently rely on docking, which is computationally intensive, slow and inaccurate compared to CelerisTx deep learning methods.