Ivan De Weber
CEO
CD
Cortex Discovery
Cortex Discovery offers an AI-powered drug discovery platform that predicts molecule properties for various therapeutic areas, rivaling lab experiments in accuracy. Their services cover preclinical drug development, including virtual screening, ADMET predictions, and lead optimization, to accelerate the identification of promising drug candidates.
- Artificial Intelligence
- Biotechnology
- Software Only
Updated 6 months ago
Funding
Funding rounds are not available yet.
Founders
Product
Problem
Traditional drug discovery methods are time-consuming, expensive, and often yield limited results due to the vast chemical space and complex biological interactions involved. Identifying promising drug candidates requires extensive experimental screening and validation, leading to high failure rates in preclinical and clinical stages.
Solution
Cortex Discovery offers an AI-powered platform that accelerates preclinical drug discovery by accurately predicting molecule properties and biological activities. Their deep-learning models are trained on a vast database of biological experiments, enabling rapid virtual screening, ADMET profiling, and lead optimization. By simulating therapeutic and off-target effects, the platform identifies high-quality compounds with increased chances of success, reducing the need for extensive lab experiments and streamlining the drug development pipeline. The AI-driven approach allows for efficient exploration of chemical spaces, identification of novel hits, and optimization of drug candidates for various therapeutic areas, including longevity and age-related disorders.
Target Audience
The primary target audience includes pharmaceutical companies, biotech firms, and academic research institutions involved in preclinical drug discovery and development across various therapeutic areas.
Features
- AI-driven virtual screening of compound libraries, including billions of molecules
- Prediction of ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties
- Virtual off-target screening to enhance the safety profiles of therapeutic candidates
- AI-driven genetic algorithm for hit analog generation and de novo compound design
- Prediction of protein affinity, pathway activation/inhibition, and other biochemical interactions
- Integration of AI with molecular docking and quantum molecular simulations for accurate binding pose and affinity predictions
- In-house visualization tool (_Retina_) for molecular analysis
- Customizable ADMET prediction reports with confidence level assessment