Digital CMC.
Powered by AI.
Strengthen and accelerate CMC with Genedata Vico™, a purpose-built AI-native solution. Automatically create and manage domain-specific data products, apply specialized agentic AI, and use leading AI models to guide confident, dynamic decisions in development and manufacturing. Continuously improve the accuracy and relevance of analytical results with a closed learning loop, while maintaining security, compliance, and end-to-end traceability.
With Genedata Vico, we shift from a document-centric to a decision-centric approach. Now we can quickly access and analyze our data, run AI/ML models, and move faster toward IND.
Ismael Velasco
Director Global Data & Insights TRD
CMC Data and AI.
At Scale.
- Manage CMC digital assets at enterprise scale, connecting data and models across small- and large-molecule drug development and manufacturing
- Turn experimental, process analytical technology (PAT), manufacturing, and quality data into governed, CMC‑specific data products that preserve scientific context and lineage
- Achieve scalable AI in GxP by connecting experiments, data, models, and decisions into governed, unified workflows
- Enable proactive process decisions with complete, consistent, traceable data
Ask. Analyze.
Decide.
- Use CMC-specific agentic AI to search, analyze, interrogate, and visualize data
- Support human-in-the-loop decision making, ensuring scientific oversight and confidence
- Identify root causes and key drivers of quality attributes at scale
- Combine AI insights with clear data lineage and human oversight, so outcomes stay explainable and defensible
Closed-Loop Learning.
Better Decisions.
- Capture and apply CMC knowledge through a closed, learning AI loop
- Feed results from experiments and manufacturing runs back into models to improve future decisions
- Perform AI-guided design of experiments (DoE) based on historical data — not trial and error
- Detect and anticipate process deviations earlier, using AI-augmented PAT
Many CMC Use Cases.
One Platform.
- De‑risk tech transfer and scale up by reusing traceable process knowledge, models, and decision logic across programs and manufacturing sites
- Prioritize chemical synthesis routes using historical process data and closed‑loop AI to improve cost, scalability, and speed
- Optimize formulation stability and performance by learning from development, scale‑up, and manufacturing outcomes across sites
- Improve inventory and shipment planning by integrating manufacturing, quality, and supply data for proactive, data‑driven decisions
Unified Data and AI
Connecting data, context, and AI across the drug lifecycle
Decision-Ready Data
Context-rich, traceable data products for review‑ready decisions
Interoperability
Across development, tech transfer, and manufacturing — without breaking traceability
GxP Compliance
Governed, auditable AI for enterprise science
Speed to Insight
Understanding process behavior and identifying risk — faster and at scale