Celeris Therapeutics utilizes an AI-driven closed-loop engine, CelerisTx One, to design proximity-inducing compounds that target and degrade proteins by leveraging endogenous cellular mechanisms. The company's drug pipeline focuses on addressing unmet medical needs in CNS and oncology through machine learning-driven interaction predictions and generative design.
Funding
$9.8M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Developing effective drugs for central nervous system (CNS) disorders and cancer is challenging due to the difficulty of targeting specific proteins and the limitations of traditional drug discovery methods. Identifying compounds that can selectively degrade disease-causing proteins using the body's own mechanisms remains a significant hurdle.
Solution
Celeris Therapeutics is developing a platform, CelerisTx One, that uses artificial intelligence to design proximity-inducing compounds. These compounds are designed to selectively target and degrade proteins by leveraging endogenous cellular mechanisms. The platform aims to accelerate drug discovery and development by predicting protein interactions and generating novel compounds with improved efficacy and specificity. This approach allows for the development of targeted therapies for diseases with unmet medical needs.
Target Audience
The primary target audience includes pharmaceutical companies and research institutions focused on developing novel therapies for CNS disorders and cancer.
Features
- AI-driven closed-loop engine for compound design
- Machine learning-driven interaction predictions
- Generative design of proximity-inducing compounds
- Focus on targeted protein degradation
- Drug pipeline targeting CNS disorders and oncology