Agentic AI for advanced therapies when every batch serves a unique patient
Agentic AI has crossed from slideware into live pharma operations. But the operating model that works for demand forecasting or procurement does not transfer cleanly to advanced therapies.
In autologous cell therapy and radiopharmaceuticals, every batch or dose belongs to one named patient. A single scheduling decision can carry clinical, manufacturing, quality, logistics and regulatory weight at once, making isolated optimization risky as conditions change.
Advanced therapies therefore require a different design principle. Specialist agents need to reason from a shared, patient-linked state, with orchestration determining when decisions can remain local and when they must be coordinated across the patient journey.
This white paper explores how advanced therapy organizations can build agentic AI around coordination first, automation second, while preserving the guardrails and human judgment needed in regulated operations.
Download the paper to learn:
- Why patient-specific therapies make isolated agent decisions risky
- How a shared patient-linked state can keep specialist agents coordinated across the patient journey
- Where business process model and notation guardrails and human oversight belong as autonomy scales
- How clinical- and commercial-stage organizations can build toward controlled autonomy safely
