AI Sustainability Maturity Framework for Pharma Manufacturing

AI is rapidly transforming pharmaceutical manufacturing, but scaling AI responsibly requires more than selecting the right LLM. This session explores how Pharma/life sciences organizations can build a sustainable and resilient AI foundation that balances innovation, regulatory compliance, operational performance, and environmental impact.

Drawing on practical perspectives from pharma manufacturing, the session examines the emerging AI maturity journey—from fragmented data and infrastructure to governed, validated and scalable AI operations. Data Centers are now been explored in Space, under water and relation to carbon-aware AI infrastructure, workload optimization, model selection, regulated data pipelines, validated MLOps, and the importance of connecting AI with manufacturing systems.

A particular focus will be the combination of Unified Namespace (UNS) and Model Context Protocol (MCP) as a potential bridge between AI intelligence and the regulated manufacturing environment.

The session will conclude with practical points on sustainability considerations for building AI capabilities that are scalable not be Fake Green (true sutainable) and compliant.