The rise of AI is revolutionizing medical technology, but it presents a unique challenge for regulators. How does the FDA approve a device that is designed to change and learn over time? This episode of MedTech Global Insights dives deep into the FDA's framework for AI-powered medical software, offering a clear guide for innovators. We break down the essentials of the premarket submission process, moving beyond traditional models. We explore the critical concept of the Predetermined Change Control Plan (PCCP), the FDA's innovative solution that allows AI devices to evolve post-market without constant re-submissions, and discuss the documentation required to demonstrate safety and effectiveness from day one through the entire product lifecycle. Case Study Spotlight: A startup develops a groundbreaking AI algorithm that predicts sepsis risk in ICU patients. They face a critical dilemma: their algorithm's performance improves with more data, but traditional FDA approval would 'lock' its initial version, making it obsolete quickly. This regulatory roadblock could delay market entry, waste R&D investment, and prevent patients from benefiting from the most advanced version of their life-saving technology. What You'll Learn: 1. What is a Predetermined Change Control Plan (PCCP) and why is it a game-changer for AI MedTech? 2. How does the FDA classify my AI software, and how does that impact my submission pathway? 3. What are the biggest mistakes companies make when preparing the technical dossier for an AI device? 4. How do I prove the safety and effectiveness of a 'learning' algorithm to regulators? 5. What kind of data and validation evidence does the FDA expect to see for AI/ML models? 6. Beyond the initial submission, what are my obligations for post-market surveillance of an AI device? 7. How can I design my AI development process from day one to align with FDA expectations? Contact us at [email protected] or visit https://pureglobal.com/ for more.