FDA - AI based SaMD
HomeDocumentationGet started
  • FDA - AI based SaMD
  • Data Governance (DG)
    • DG01 - Define Sets
    • DG02 - Dataset Governance Policies
    • DG03 - Dataset Design Choices
    • DG04 - Dataset Source Information
    • DG05 - Dataset Annotations Information
    • DG06 - Dataset Labels Information
    • DG07 - Dataset Cleaning
    • DG08 - Dataset Enrichment
    • DG09 - Dataset Aggregation
    • DG10 - Dataset Description, Assumptions and Purpose
    • DG11 - Dataset Transformation Rationale
    • DG12 - Dataset Bias Identification
    • DG13 - Dataset Bias Mitigation
    • DG14 - Dataset Bias Analysis Action and Assessment
    • DG15 - Dataset Gaps and Shortcomings
    • DG16 - Dataset Bias Monitoring - Ongoing
    • DG17 - Dataset Bias Special/Protected Categories
  • Technical Documentation (TD)
    • TD01 - Technical Documentation Generated
    • TD02 - Additional Technical Documentation
    • TD03 - Technical Details
    • TD04 - Development steps and methods
    • TD05 - Pre-trained or Third party tools/systems
    • TD06 - Design specification
    • TD07 - System Architecture
    • TD08 - Computational Resources
    • TD09 - Data Requirements
    • TD10 - Human Oversight Assessment
    • TD11 - Pre Determined Changes
    • TD12 - Continuous Compliance
    • TD13 - Validation and Testing
    • TD14 - Monitoring, Function and Control
    • TD15 - Risk Management System
    • TD16 - Changes
    • TD17 - Other Technical Standards
    • TD18 - Ongoing Monitoring System
    • TD19 - Reports Signed
  • Transparency and Provision of Information to Users (TPI)
    • TPI01 - Transparency of the AI System
    • TPI02 - Instructions for Use
  • Human Oversight (HO)
    • HO01 - Human Oversight Mechanism
    • HO02 - Human Oversight Details
    • HO03 - Human Oversight - Biometric Identification Systems
  • Accuracy, Robustness and Cybersecurity (ARC)
    • ARC01 - Accuracy Levels
    • ARC02 - Robustness Assessment
    • ARC03 - Continuous Learning Feedback Loop Assessment
    • ARC04 - Cyber Security Assessment
  • Managing SaMD Lifecycle Support Process - Record Keeping (RK)
    • RK01 - Logging Capabilities
    • RK02 - Logging Traceability
    • RK03 - Logging - Situations that May Cause AI Risk
    • RK04 - Logging - Biometric systems requirements
    • RK05 - Details of Off-the-Shelf Components
    • RK06 - Evaluation Process of Off-the-Shelf Components
    • RK07 - Quality Control Process of Off-the-Shelf Components
    • RK08 - Internal Audit Reports
  • Risk Management System (RMS)
    • RMS01 - Risk Management System in Place
    • RMS02 - Risk Management System Capabilities and Processes
    • RMS03 - Risk Management Measures
    • RMS04 - Testing
    • RMS05 - Residual Risks
    • RMS06 - Full Track of Mitigation Measures
  • Quality Management Principles (QMP)
    • QMP01 - Quality Management System in Place
    • QMP02 - Compliance Strategy stated
    • QMP03 - Design processes
    • QMP04 - Development and QA (Quality Assurance) processes
    • QMP05 - Test and Validation Procedures
    • QMP06 - Technical Standards
    • QMP07 - Data Management Procedures
    • QMP08 - Risk Management System
    • QMP09 - Ongoing Monitoring System
    • QMP10 - Incident Reporting Procedures
    • QMP11 - Communications with Competent Authorities
    • QMP12 - Record Keeping Procedures
    • QMP13 - Resource Management Procedures
    • QMP14 - Accountability Framework
  • Post Market Monitoring System (PMS)
    • PMS01 - Post Market Monitoring System in Place
    • PMS02 - Data Collection Assessment
    • PMS03 - Post Market Monitoring Plan
Powered by GitBook
On this page

Quality Management Principles (QMP)

PreviousRMS06 - Full Track of Mitigation MeasuresNextQMP01 - Quality Management System in Place

Last updated 2 years ago

This control contains details of the requirements for the Quality Management System (QMS) in place for AI/ML based SaMD.

This category supports the principles stated in section 5 of the IMDRF/SaMD N23.

Medical device QMS principles allow for scaling of activities depending on the type of medical device; risk of the product to patients; size of the organization; technology or automation used to manufacture; and other factors that are determined by the manufacturer to control quality and maintain the safe and effective performance of the medical device.

The manufacturing of SaMD, which is a software-only product, is primarily based on the development lifecycle activities often supported by the use of automated software development tools (build automation, use of source code management tools, etc.). These automated activities may in some cases replace discrete or deliberate activities (e.g., transfer of design to production) typically found in the manufacturing of hardware products. However, the principles in a QMS that provide structure and support to the lifecycle processes and activities are still applicable and important to control the quality of SaMD.

An effective QMS for SaMD should include the following principles:

  • An organizational structure that provides leadership, accountability, and governance with adequate resources to assure the safety, effectiveness, and performance of SaMD;

  • A set of SaMD lifecycle support processes that are scalable for the size of the organization and are applied consistently across all realization and use processes; and

  • A set of realization and use processes that are scalable for the type of SaMD2 and the size of the organization; and that takes into account important elements required for assuring the safety, effectiveness, and performance of SaMD (innermost circle in Figure 1).

In addition, the governance should include activities for systematically verifying the effectiveness of the established quality management system, such as undertaking QMS internal audits. Management review of the results of the QMS audits is a tool to ensure that the established QMS is suitable, adequate, and effective and that any necessary adjustments may be made as a result.

Similarly, according to the FDA AI/ML discussion paper:

The FDA expects every medical device manufacturer to have an established quality system that is geared towards developing, delivering, and maintaining high-quality products throughout the lifecycle that conforms to the appropriate standards and regulations. Similarly, for AI/ML-based SaMD, we expect that SaMD developers embrace the excellence principles of culture of quality and organizational excellence.

This compliance category supports the following controls/checks:

QMP01 - Quality Management System in Place
QMP02 - Compliance Strategy Stated
QMP03 - Design Processes
QMP04 - Development and QA (Quality Assurance) Processes
QMP05 - Test and Validation Procedures
QMP06 - Technical Standards
QMP07 - Data Management Procedures
QMP08 - Risk Management System
QMP09 - Ongoing Monitoring System
QMP10 - Incident Reporting Procedures
QMP11 - Communications with Competent Authorities
QMP12 - Record Keeping Procedures
QMP13 - Resource Management Procedures
QMP14 - Accountability Framework