Human-in-the-loop constructs for agentic workflows in healthcare and life sciences

This article explains four practical approaches to implementing human-in-the-loop (HITL) constructs for AI agents in healthcare and life sciences using AWS services, addressing regulatory compliance, patient safety, and audit requirements.

• Agentic Loop Interrupt: Uses Strands Agent Framework hooks to intercept and approve tool calls before execution
• Tool Context Interrupt: Embeds approval logic directly within tools for fine-grained, role-based access control
• Remote Tool Interrupt: Uses AWS Step Functions and Amazon SNS for asynchronous external approvals via email
• MCP Elicitation: Leverages Model Context Protocol's elicitation protocol for real-time interactive approvals
• All patterns deployed on Amazon Bedrock AgentCore Runtime for serverless scalability and session isolation
• Code examples available in public GitHub repository for adaptation to specific use cases

These HITL patterns enable compliant, production-ready AI agent deployments in healthcare by balancing automation efficiency with necessary human oversight at critical decision points.