Description: he integration of Artificial Intelligence (AI) into In Vitro Diagnostic Medical Devices (IVD) promises transformative advances in patient care and diagnostics and is believed to bear the potential to revolutionize healthcare diagnostics by enhancing accuracy, efficiency, and personalized patient outcomes. However, these innovations must navigate a complex web of regulatory challenges to ensure safety, efficacy, and compliance. Successful implementation of AI will require a collaborative effort by all stakeholders involved in development and conformity assessment.
This educational session will delve deep into the regulatory aspects of incorporating AI technologies into IVDs and will explore key topics such as:
* Regulatory Framework
Overview: An in-depth look at the regulatory landscape governing IVDs and AI, including the FDA's action plan, CE marking, and relevant standards, guidances and best practices. * Risk Classification: Understanding how AI-powered IVDs are categorized based on risk, and the implications for pre-market submissions, quality control, and post-market surveillance. * Design Control: Implementation of AI development into the design control process to demonstrate compliance with standards and regulatory requirements. * Clinical Evidence: The critical role of clinical data in obtaining regulatory approvals, and strategies for designing robust studies to demonstrate AI-powered IVD safety and efficacy. * Quality Management Systems: Developing and maintaining quality systems to ensure compliance with ISO 13485 and other relevant standards in the context of AI. * Conformity
Assessment: On the basis of examples of IVD AI devices the intersection of IVDR and AI will be discussed including approaches for demonstrating conformity and risks to be considered related to the usage of AI. * Future Regulatory Trends: Exploring the potential changes and adaptations in IVD regulation as AI technologies continue to advance.
Attendees will gain valuable insights into the regulatory challenges and opportunities associated with AI in IVDs, equipping them with the knowledge and tools needed to successfully navigate this complex terrain. This session aims to foster a collaborative dialogue among regulatory professionals to ensure safe and effective AI-driven IVDs are brought to market, ultimately benefiting patients worldwide.
Learning Objectives:
list the different aspects of AI based on capability, functionality and branches
describe how machine learning models are implemented into the design control process compliant with ISO 13485 and IEC 62304
highlight the key elements of good machine learning practice for medical devices
describe the tremendous potential of Artificial Intelligence in the In Vitro Diagnostic Medical Device area.
list challenges related to the regulatory compliance and the ensuring of the safety and effectiveness of IVD(R) AI devices.
use approaches for demonstrating compliance and considering risks related to IVD AI devices.