Pharmaceutical companies are required to comply with stringent FDA/GCP guidelines, and their facilities are subject to inspections. The traditional preparation for these inspections involves a manual review of extensive documentation and adherence to constantly evolving compliance requirements. This manual process is also difficult to scale to multiple sites. To address these challenges, a GenAI-driven audit copilot system has been developed. This system leverages a unique agentic workflow using LLMs to automate the audit preparation process, making companies inspection-ready, improving compliance, and reducing the risk of production halts due to failed audits.

Companies face several challenges in maintaining compliance and preparing for FDA/GCP inspections due to:

• Constantly evolving compliance requirements
• The need for thorough and timely documentation review
• High risk of production halts if inspections are failed
• Manual processes that are time-consuming and prone to errors
• The necessity for both corrective and preventive actions to maintain compliance

Build a GenAI-driven audit copilot system that utilizes a network of LLM agents to automate and streamline your audit preparation process. This system includes:

1. Audit master agent: The central hub that orchestrates the workflow, receiving audit requests and managing specialized agents.
2. Specialized agents:
   Agent 1 (Informed Consent): Understands relevant policies, generates questions, identifies data sources, and generates findings related to audit site review area Informed Consent.
   
   Agent 2 (Protocol Deviation): Undertake similar operations to Agent 1 to flag protocol discrepancies or deviations.
   
   Agent 3 (Patient Visits & Labs): Gathers and analyzes patient data, including visit history and lab results.
3. Additional agents: Handle specific tasks within the audit process as needed.

The system understands applicable policies, processes questions, responds accordingly, and ensures inspection readiness by analyzing data and generating reports. It also allows for corrective and preventive actions based on identified issues.

1. Audit master agent: Central hub managing the workflow.
2. Specialized agents: Handle specific aspects of the audit process, including roles, protocol deviations, and patient data.
3. Automated reports: Inspection readiness and audit findings are automated.
4. Corrective and preventive actions: The system ensures readiness and suggests actions to maintain compliance.

• GPT-4 Turbo (or other proprietary LLM) for building the LLM agents.
• Azure (or similar secure hosting environment) for the prototype.

The GenAI-driven audit copilot system significantly enhances compliance readiness and streamlines the inspection process for companies. By automating the preparation for FDA/GCP inspections, the system saves time, ensures compliance, and reduces the risk of production halts. With its ability to provide actionable insights and facilitate corrective and preventive actions, companies can maintain a high level of compliance and be better prepared for unannounced inspections.