Revilico provides an integrated Operating System that unifies computational drug discovery engines like Docking, Molecular Dynamics, and Generative Chemistry. This platform centralizes multi-omic datasets and uses AI agents to automate workflows from Target ID through Preclinical Development. The system accelerates R&D cycles, significantly improves hit rates, and reduces IND costs by integrating simulation with Virtual Cell predictions.
Funding
$145K 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.
FVFounders
Product
Problem
Traditional high-throughput screening (HTS) in drug discovery is time-consuming and expensive, often involving the screening of millions of compounds with limited success in identifying promising drug candidates. This inefficiency hinders the revitalization of abandoned drugs and the creation of novel small molecules for therapeutic development.
Solution
Revilico offers an AI-driven drug discovery platform that accelerates the identification of potential therapeutic candidates. The platform leverages generative chemistry and advanced AI models to screen billions of compounds, significantly reducing the time and cost associated with traditional HTS. By integrating computational target identification, intelligent compound discovery, and precision-driven candidate refinement, Revilico optimizes the early stages of drug development, enabling faster and more efficient discovery of new therapeutics.
Target Audience
Revilico's platform is designed for pharmaceutical companies, biotechnology firms, and research institutions involved in drug discovery and development, particularly those focused on oncology and other therapeutic areas.
Features
- AI-driven computational target identification to uncover precise drug targets.
- High-speed AI screening of compounds through bioinformatics and generative chemistry.
- Data-driven refinement of drug candidates combining biological insights.
- Scalable data pipeline capable of handling industry-grade computation for millions of molecules and biologics.
- ISO-grade data security and compliance to protect sensitive research data.
- Proprietary AI models trained on a vast library of molecules and biologics.
- Streamlined workflow for seamless transition from computational predictions to wet lab validation.