Overview:
FDA
has always prioritized the risk management of medical devices, adhering to its
regulations while also endorsing the use of ISO 14971. The complexity of risk
management escalates with software as a medical device (SaMD) and software in a
medical device (SiMD), especially when machine learning (ML) is involved.
The
issuance of BS/AAMI 34971:2023, "Guidance on the application of ISO 14971
to AI and ML," represents a significant development. This document, a
joint effort by the BSI and AAMI, has been recognized by the FDA and offers
comprehensive guidelines tailored for AI and ML technologies in medical
devices.
This
webinar aims to demystify the ISO 14971 risk management process, highlighting
the unique challenges posed by ML. We will delve into Hazard Analysis as
outlined in ISO 14971, a pivotal risk management technique assessing risks
during normal operation and fault conditions.
Participants will gain insights into conducting a thorough hazard analysis, with a clear explanation of terms such as “hazard,” “hazardous situation,” “harm,” “causative event,” “ALARP,” and “risk index.” The session will guide attendees through the risk analysis process step by step, using examples to illustrate hazards and hazardous situations, including those specific to ML technologies.
This
session is not a programming or technical coding workshop but rather focuses on
guiding manufacturers, quality assurance professionals, and regulatory affairs
specialists through the landscape of BS/AAMI 34971:2023 and ISO 14971
compliance.
Areas
covered during the session:
- Hazard
analysis terminology
- The
process of conducting a hazard analysis
- Quality
control (QC) of datasets and ML algorithm updating
- The
significance of "explainability" in ML models
- Cybersecurity
considerations in the context of ML medical devices
Why
should you attend?
With
the evolving landscape of medical device regulation and the integration of
advanced technologies like AI and ML, staying abreast of the latest guidance is
crucial. BS/AAMI 34971:2023 offers a framework for managing the risks
associated with these innovations. This webinar will equip you with the
knowledge to navigate these complexities, ensuring compliance and the safety of
medical devices.
Who
should attend?
- Medical
Device Manufacturers and Developers
- Quality
Assurance and Regulatory Affairs Specialists
- Risk
Management Professionals
- Clinical
Engineers and Healthcare Technology Managers
- Software
Engineers and Developers in the Medical Sector
- Compliance
Officers and Legal Advisors
- R&D
Personnel
- Product
Managers
- Healthcare
Providers
This webinar is designed to provide attendees with a understanding of the latest standards and best practices in risk management for medical devices, with a special focus on the complexities introduced by machine learning and artificial intelligence.
Edwin Waldbusser is a consultant retired from industry after 20 years in management of development of medical devices (5 patents). He has been consulting in the US and internationally in the areas of design control, risk analysis and software validation for the past 11 years.
Mr.
Waldbusser has a BS in Mechanical Engineering and an MBA. He is a Lloyds of
London certified ISO 9000 Lead Auditor and a member of the Thomson Reuters
Expert Witness network.
Enrollment Options
Tags: ISO 14971, BS/AAMI 34971:2023, Machine Learning Medical Devices, Risk Management Healthcare, AI Medical Device Safety, Medical Device Software Compliance, Cybersecurity in Healthcare, Medical Dataset Quality Control, Regulatory Compliance Webinar, AI Explainability in Healthcare, Edwin, Waldbusser, February 2024