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Activity Number: 400 - Challenges and Opportunities for the Principled Calibration and QA/QC Assessments of AI and Machine Learning Methods Within Medical Device Applications
Type: Invited
Date/Time: Wednesday, August 10, 2022 : 10:30 AM to 12:20 PM
Sponsor: Section on Medical Devices and Diagnostics
Abstract #320405
Title: Advancing Regulatory Science for Medical Devices and Medical Software Through Collaboration
Author(s): Jithesh Veetil, PhD*
Companies: MDIC
Keywords: MDIC; Devices; Diagnostics; regulatory science; digital health; AI/ML

Digital health technologies including AI/ML is revolutionizing medical device development and is being leveraged in applications ranging from wellness products to in vitro diagnostics to sophisticated robotic surgery devices. Although it is expected that the number of digital health products will increase exponentially in the future, the global regulatory framework is still evolving. For example, currently no suitable regulatory framework for addressing the iterative improvements that can occur post-launch for AI/ML-enabled medical devices, while ensuring their safety and effectiveness for their intended use. Such a framework would need to take into account numerous factors, such as the potential use of Real World Data (RWD), and the appropriate metrics to use to address the unique challenges posed by AI/ML applications used as software in a medical device (SiMD) and/or software as a medical device (SaMD). In this session we will highlight how the Medical Device innovation Consortium (MDIC), a public-private partnership is bringing stakeholders together through pre-competitive regulatory science initiatives to provide solutions to challenges faced in digital health technologies

Authors who are presenting talks have a * after their name.

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