Description

As artificial intelligence becomes integrated into GMP operations, organizations must ensure that AI does not replace appropriate human judgment, accountability, or quality oversight. A Human-in-the-Loop (HITL) approach establishes defined points where qualified personnel review, challenge, approve, or override AI-generated recommendations.

This webinar explains how HITL can be incorporated into GMP systems to support data integrity, risk management, validation, and inspection readiness.

Learning Objectives:-

Participants will learn how to:

• Define Human-in-the-Loop in a GMP environment.
• Determine when human review of AI output is necessary.
• Establish clear authority to accept, reject, or override AI recommendations.
• Document human decisions and AI-assisted actions.
• Apply HITL controls using a risk-based and lifecycle approach.
• Maintain data integrity and traceability when AI supports GMP decisions.
• Generate inspection-ready evidence demonstrating effective human oversight.

Key Points:-

• What Human-in-the-Loop Means in GMP
  • AI supports rather than automatically replaces critical human decisions.
  • Qualified personnel retain responsibility for GMP decisions.
  • Human intervention points should be predefined.
• Risk-Based Human Oversight
  • Higher-risk AI decisions require stronger human controls.
  • Define which outputs require review or approval.
  • Establish escalation criteria for uncertain or abnormal AI outputs.
• Human Review and Override
  • Personnel must be able to challenge AI recommendations.
  • Override authority and responsibilities should be clearly defined.
  • Overrides should be documented and traceable.
• Data Integrity
  • Maintain traceability between AI output and the final human decision.
  • Preserve relevant inputs, outputs, approvals, changes, and overrides.
  • Ensure audit trails support reconstruction of significant decisions.
• Lifecycle Monitoring
  • Monitor AI performance after implementation.
  • Periodically assess whether human oversight remains effective.
  • Review deviations, overrides, unexpected outputs, and performance trends.
  • Reassess controls when the AI system, data, intended use, or risk changes.
• Inspection-Ready Evidence
• Organizations should be able to demonstrate:
  • Who reviewed the AI output.
  • What information was reviewed.
  • When the review occurred.
  • What decision was made.
  • Why an AI recommendation was accepted or overridden when justification is required.
  • How AI performance and human oversight are monitored over time.

Why Should You Attend:-

Human-in-the-Loop is not simply having a person present. Effective HITL requires meaningful human oversight, defined decision authority, documented intervention, traceability, and lifecycle monitoring proportional to GMP risk.

Who Should Attend:-

• Quality Assurance and Quality Control
• Validation and Computer System Validation personnel
• Manufacturing and Operations
• Data Integrity professionals
• Regulatory Affairs
• IT and Digital Transformation teams
• AI/ML system owners
• Compliance and auditing personnel.