Predict drug-target interactions, optimize lead selection, and identify repurposing opportunities.
Generate novel molecular structures tailored for specific biological targets. AI-driven de novo molecule design, compound refinement, and safety optimization.
AI-driven simulations model patient-specific responses to drug compounds - for patient response simulations and biomarker-driven precision medicine.
AI continuously refines molecular properties based on efficacy and safety predictions.
Patient recruitment is one of the biggest hurdles in clinical trials. ScienOps' AI solutions ensure precision-driven, diverse patient matching and faster enrollments.
Predicts adverse events, drug interactions, and real-world safety risks.
AI analyzes millions of compounds, ranking the most promising candidates.
Predict drug-target interactions, optimize molecular design, and accelerate lead discovery.
Predictive modeling reduces protocol deviations and enhances adherence.
RAG & RPA for Regulatory Compliance – AI-driven automation for document processing, adverse event detection, and compliance tracking.
Real-world data replaces placebo groups, reducing patient burden.