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AI Audit checklist for GxP system

1. Governance and Compliance

Ensure alignment with regulatory requirements (FDA, EMA, etc.)

Define roles and responsibilities for AI oversight

Establish a governance framework for AI usage

Review and update policies related to AI and data management

Maintain documentation for compliance with GxP regulations

2. Risk Management

Conduct a risk assessment specific to AI applications

Identify potential risks associated with AI algorithms and data sources

Implement risk mitigation strategies and controls

Establish a process for continuous risk monitoring

Ensure traceability and accountability for AI decisions

3. Data Management

Assess data quality, integrity, and suitability for AI training

Validate data sources and ensure compliance with data privacy regulations

Implement data governance practices for AI-related datasets

Ensure proper data handling and storage procedures are in place

Establish protocols for data access and sharing

4. Validation and Verification

Develop a validation plan specific to AI systems

Conduct functional and non-functional testing of AI applications

Document validation results and address any discrepancies

Establish procedures for ongoing validation and continuous improvement

Ensure traceability of AI model development and changes

5. Model Management

Evaluate model selection processes and criteria

Monitor model performance and establish key performance indicators (KPIs)

Implement change control procedures for AI model updates

Ensure proper model documentation and version control

Conduct periodic reviews and audits of AI models

6. Training and Competence

Define training requirements for personnel involved with AI systems

Ensure ongoing training and skill development for staff

Assess the competency of personnel in GxP compliance and AI technologies

Foster a culture of awareness regarding AI risks and compliance

Maintain training records and documentation

7. Incident Management

Establish an incident reporting and management process for AI-related issues

Define criteria for incident escalation and resolution

Conduct root cause analysis for AI failures or incidents

Implement corrective and preventive actions (CAPA) as necessary

Review incident trends and integrate learnings into practices

8. Continuous Improvement

Establish a process for regular review and improvement of AI systems

Gather feedback from users and stakeholders on AI performance

Monitor industry trends and advancements in AI technologies

Engage in benchmarking against best practices in the industry

Document lessons learned and integrate them into future projects

This structured checklist should help organizations ensure compliance and quality in their AI applications within GxP systems.

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