Qubigen combines federated AI technology with virtual screening and AI drug design to create a global proprietary dataset for drug development. This approach enhances the efficiency of drug discovery by enabling secure data collaboration across clinics and research institutions without compromising patient privacy.
Funding
$4.3M 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.
JCSIFounders
Product
Problem
Traditional drug discovery processes are slow and inefficient, often hampered by limited datasets and the inability to securely collaborate across different research institutions due to patient privacy concerns. This lack of data sharing and collaboration hinders the development of new and effective treatments.
Solution
Qubigen leverages federated AI technology combined with virtual screening and AI drug design to accelerate drug discovery. The company enables secure data collaboration across clinics and research institutions, creating a global proprietary dataset without compromising patient privacy. By using federated learning, Qubigen allows multiple parties to train AI models on their local data without directly exchanging sensitive information. This approach enhances the efficiency of drug discovery by providing a larger, more diverse dataset for training AI models, leading to better predictions and more effective drug candidates.
Target Audience
Qubigen's primary customers are pharmaceutical companies, research institutions, and clinics involved in drug discovery and development.
Features
- Federated AI technology for secure, privacy-preserving data collaboration
- Virtual screening capabilities to identify promising drug candidates
- AI-driven drug design tools to optimize molecular structures
- Global proprietary dataset for training AI models