AI System (Artificial intelligence systems ) Qualification as per GAMP 5

 

In the context of GAMP 5 (Good Automated Manufacturing Practice), AI system qualification refers to the process of ensuring that artificial intelligence (AI) systems used in the pharmaceutical industry meet predefined requirements for their intended use. Here's a breakdown of how AI system qualification aligns with GAMP 5 principles:

 

1. Risk Management :- GAMP 5 emphasizes a risk-based approach to validation and qualification. AI systems are typically complex and can introduce unique risks related to data integrity, algorithm performance, and regulatory compliance. Qualification involves identifying these risks and implementing controls to mitigate them effectively.

 

2. Supplier Assessment : - GAMP 5 requires thorough assessment of suppliers and their systems. For AI technologies, this involves evaluating the capabilities of AI vendors, understanding their development methodologies, and ensuring their systems comply with regulatory requirements and industry standards.

 

3. User Requirements Specification (URS) :-  The URS document defines the functional and operational requirements that the AI system must fulfill. This includes performance criteria, such as accuracy, reliability, and scalability, which are crucial for AI systems in pharmaceutical applications where precise decision-making and data integrity are paramount.

 

4. Installation Qualification (IQ) :- IQ verifies that the AI system has been installed correctly and according to specifications. This may include hardware installation, software installation, network configuration, and initial system setup.

 

5. Operational Qualification (OQ) :- OQ ensures that the AI system operates as intended in its operational environment. This phase involves testing the functionality and performance of the AI algorithms, data handling processes, and integration with other systems to ensure they meet predefined requirements.

 

6. Performance Qualification (PQ):- PQ demonstrates that the AI system consistently performs according to predefined specifications and requirements over an extended period. For AI systems, this may involve testing the robustness of machine learning models, evaluating performance under different data conditions, and validating outputs against expected results.

 

7. Change Control and Management :- GAMP 5 emphasizes the importance of change control throughout the lifecycle of the AI system. Changes to AI models, algorithms, or software configurations should be managed through a formal change control process to ensure that they do not adversely affect system performance or compliance.

 

8. Documentation and Reporting :- Comprehensive documentation is essential throughout the qualification process to provide evidence that the AI system meets regulatory requirements. This includes documenting validation protocols, test results, deviations, and corrective actions taken.

 

In summary, AI system qualification in accordance with GAMP 5 principles ensures that AI technologies used in pharmaceutical manufacturing and related processes are validated to operate reliably, accurately, and in compliance with regulatory standards. It involves a structured approach to risk management, documentation, testing, and validation to ensure the integrity and effectiveness of AI systems in supporting critical decision-making and operations within the pharmaceutical industry.

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