Building Validated AI Systems: Risk-Based Approaches to GxP Compliance
AI is transforming life sciences, but navigating GxP compliance, regulatory validation, and audit readiness remains a challenge. Join us for an interactive workshop designed for AI, data science, and complaince leaders at pharma and biotech companies who are working on AI-powered initiatives in personalized medicine, clinical trials, pharmacovigilance, and manufacturing.
Through expert-led sessions, simulations, and real-world case studies, you’ll learn how to:
- Apply risk-based validation strategies to AI-driven GxP applications
- Ensure AI audit readiness with explainability and traceability best practices
- Streamline validation processes to accelerate AI adoption and regulatory approval
- Balance innovation and compliance in AI-powered GxP applications and operations
Agenda
Enjoy coffee, bagels, and meet fellow industry leaders.
- The latest FDA, EMA, and global regulations for AI in life sciences
- Key challenges in GxP compliance for AI-powered solutions
- Pathways to validate non-deterministic models
- Ensuring AI systems are interpretable for regulators and auditors
- How leading pharma companies balance AI innovation with compliance
- Case studies in AI validation and regulatory approval
Guided by industry experts, attendees will participate in a real-world AI validation simulation. Teams will be given an AI-powered system and use case in life sciences. Working together, teams will identify and classify risks, build a risk-based validation framework, validate an AI model under GxP compliance constraints, and prove its audit-ready
- Agile validation and CSA vs. traditional CSV for AI-driven systems
- Case study: How an enterprise went from 1 year to 2-week release cycles for its FDA-approved AI/ML in 6 months.
- How platforms and platform teams will make validated AI scale-proof
- Explore costs and cost-savings for implementation
Enjoy a catered lunch while connecting with peers and industry experts.
Speakers
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Erez is passionate about improving patient care and health outcomes with software solutions. Over the last decade, Erez worked in industries including computational mathematics, biotech, and energy, helping build monitoring systems for pharmaceutical equipment and AI for medication management. Before Ketryx, Erez worked with Amgen, the world’s largest biotechnology company, as the head of AI/ML for their medical device division and with Wolfram Research, the builders of Mathematica and Wolfram|Alpha. Erez holds a Master of Science in Electrical Engineering and Computer Science and a Master of Business Administration from the Massachusetts Institute of Technology.
