Experience AI-Powered Drug Discovery

Watch our autonomous AI Scientists platform accelerate research from months to minutes

  • Real-time demonstration of AI agents in action
  • Target identification in minutes, not months
  • Comprehensive insights from 11 biomedical databases
  • Autonomous research with zero human intervention

Drug Discovery Stages

Target Identification

Understanding disease mechanisms and identifying drug targets using AI-powered analysis of biological data and pathways

2 Available Solutions

Drug Design / Optimization

Design and optimize drugs through AI-driven molecular modeling, structure prediction, and virtual screening

Coming Soon

Clinical Development

Evaluating safety and efficacy of drugs in clinical trials with AI-assisted protocol design and patient recruitment

Coming Soon

Available Now

Production-ready AI solutions for drug discovery

No products available at this time.

AI Capabilities Roadmap

Expanding our platform to cover the entire drug discovery pipeline

In Development

Autonomous Antibody Design Agent (AADA)

Future Outlook

Clinical Trials Prediction
Clinical Trial Protocol Writing
Small Molecule Drug Design
mRNA/siRNA Drug Design
Digital Twin & Virtual Cells
Intervention Recommendation

Latest News & Insights

Stay updated with the latest developments in AI-powered drug discovery

Research

AI-Driven Target Identification Breakthrough

New machine learning models achieve high accuracy in identifying novel drug targets for oncology research.

Read More

Our Team

World-class experts in AI, drug discovery, and computational biology

Wenliang Zhang

Wenliang Zhang

Daitor

As a seasoned data scientist with over a decade of research experience in immuno-oncology and infectious diseases, I am committed to leveraging data to make meaningful contributions at the intersection of computer science and biology. With a Master's degree in Computer Science and a PhD in Infectious Diseases, I possess a diverse skill set that includes expertise in data analytics, engineering, machine learning, and software development. I am passionate about utilizing data to develop and enhance software tools, build data pipelines and machine learning models, and extract valuable insights from complex data sets. My enthusiasm for machine learning extends to designing and implementing end-to-end MLOps architectures to accelerate and scale ML into production. I am excited to apply my skills and experience to drive innovation in the field of machine learning and contribute to cutting-edge research initiatives.

Powered by Advanced AI Architecture

Enterprise-grade platform combining multi-agent systems with comprehensive data integration

Deep Agent Architecture

Multi-agent system with specialized AI agents for target identification, hypothesis generation, and novelty verification with human-in-the-loop oversight

MCP Services Integration

Standardized Model Context Protocol (MCP) services enable seamless tool use and separation of concerns across the platform

Multi-Database Access

Unified access to 11 leading biomedical databases through standardized interfaces for literature, clinical trials, genomics, and drug interactions

AI-Powered Analysis

Advanced machine learning models for target validation, pathway analysis, and automated scientific report generation

Integrated Data Sources

PubMed
ClinicalTrials.gov
UniProt
ChEMBL
GTEx
OpenFDA
OpenTargets
DGIdb
AIRR Data Commons
iReceptor Gateway
PanKgraph
View Platform Architecture

Transform Your Drug Discovery Workflow

Join leading pharmaceutical and biotech companies accelerating research with AI

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