Regulatory Challenges of Real-World Artificial Intelligence (AI) and Machine Learning (ML)

Product Id : FDA252
Instructor : Angela Bazigos
Apr 23, 2020 1:00 PM ET | 12:00 PM CT | 10:00 AM PT | 90 Minutes


In April, the US Food & Drug Administration (FDA) published a request for comments on new proposals for the regulation of medical devices which employ artificial intelligence (AI) and machine learning (ML) components. This continues a trend over recent years of the FDA recognizing that regulation of software as medical devices (SaMD) must be different to how regulation has applied in the past.

We believe the FDA’s AI/ML regulation proposals are an excellent start, uniting well-established risk management principles and best-practice guidance while also recognizing the challenges and opportunities developing and managing complex AI/ML products. The FDA has also coherently integrated existing SaMD regulatory principles into their new proposals. More broadly, the FDA’s proposals encapsulate many established industry and academic best practices in AI/ML implementation and management – so will be familiar to anyone who has worked on such systems in other sectors.

Why should you attend:

This session will engage professionals looking to understand the regulatory challenges of software as a medical device (SaMD) with special focus on AI/Machine Learning (ML). This session will provide insights on moving from the traditional regulatory strategies for mature technologies to the new regulatory strategies for novel uses of AI and ML while engaging FDA and/or Notified Bodies in the effort. The IMDRF, US and EU perspectives on what’s next for AI and ML as SaMD will be explored.

Areas Covered in the Session:

  • Describe actual and future AI applications that are changing patient treatment and healthcare delivery through the exploration of real-world examples (across different diagnostic/therapeutic and technology areas)
  • Demonstrate knowledge of US and EU perspectives on current developments and challenges stemming from the development and implementation of AI/ML in development of regulatory strategies
  • Develop and execute regulatory strategies that meet real-world needs posed by AI and ML

Who will benefit:

  • VP of IT
  • Director of IT
  • Quality Managers
  • Project Managers (for DATA INTEGRITY / IT)
  • Validation Specialists
  • Database Administrators
  • System Administrators
  • Directors / Senior Directors of Discovery
  • Directors / Senior Directors of Development
  • Directors / Senior Directors of Commercialization
  • Document Managers
  • Training Managers
  • Consultants
  • Data Managers
  • Safety Managers
  • Doctors
  • Nurses
  • Regulatory Affairs
  • Quality Assurance
  • Regulatory Authority Inspectors
  • Clinical Safety Personnel
  • Clinical Data Management Personnel
  • IT personnel working on Clinical Systems
Speaker Profile:

Angela Bazigos is the CEO of Touchstone Technologies Inc. She has degrees in Microbiology and Computing and 40 years of experience in the Life Sciences, Healthcare & Public Health Services. Experience combines Quality Assurance, Regulatory Compliance, Business Administration, Information Technology, Project Management, Clinical Lab Science, Microbiology, Food Safety & Turnarounds. Past employers / clients include Royal Berkshire Hospital, Roche, Novartis, Genentech, PriceWaterhouseCoopers & Stanford Hospital. Positions include Chief Compliance Officer :, Director of QA and MIS Director.  Co-authored & prototyped 21 CFR 11 guidance with FDA.  Co-authored Computerized Systems in Clinical Research w/ FDA & DIA: Patent on speeding up software compliance

Recently quoted in Wall Street Journal for using training to bring regulatory compliance to the Boardroom :

Includes training for Society of Quality Assurance. Comments / collaborates with FDA on new guidance documents,Former President of Pacific Regional Chapter of Society of Quality Assurance. Stanford’s Who’s Who for LifeSciences:  

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