AI-driven analytics across the drug development lifecycle
Accelerating discovery, optimizing trials, and supporting seamless translation from research to clinical impact.
Key Capabilities
Pre-Clinical Analytics
- Accelerated drug discovery with machine learning on genomic/proteomic data.
- De novo compound design leveraging advanced AI models.
- Automated toxicity prediction for rapid risk assessment.
Clinical Development Solutions
- Generative AI in operational plan management—secure data, role management, and workflow automation.
- Document management, review, and collaboration for R&D teams.
Integrated Data Pipeline
- Continuous flow of information from pre-clinical through post-market stages for better decision-making and R&D efficiency.
Thought Leadership Insights
De-novo Compound Design
Generative AI proposing novel molecules with optimized efficacy and safety.
Predictive Toxicology
Automated risk pipelines to flag high-risk candidates early.
Synthetic Data
Privacy-preserving datasets enhancing model training without PHI exposure.
AI-Driven Trials
Optimizing recruitment, remote consent, and real-time monitoring to accelerate studies.
Regulatory Intelligence
NLP extraction and summarization of guidelines for audit-ready submissions.
Personalized Insights
Integrating EMR, claims, and lab data to forecast patient journeys.
Key Differentiators
Domain-Adapted AI Models
Proprietary LLMs and vision models fine-tuned on biomedical literature and lab data for unmatched prediction accuracy.
Real-Time Trial Optimization
Dynamic patient cohort re-balancing and adaptive protocol adjustments powered by continuous data ingestion.
End-to-End Compliance Automation
Built-in regulatory-grade audit trails, eCTD packaging, and submission workflows to streamline global approvals.