_______________________________________________________________________________________________________ π 2026 | π 11 AM Eastern Time US | π 3 PM GMT | β³ 90 Minutes
This course helps device teams distinguish among FDA submission pathways and evaluate how classification, risk, clinical evidence, newer technologies, and available submission programs affect regulatory planning and market authorization.
Medical devices entering the U.S. market, or undergoing substantial changes, may require different FDA pathways depending on classification, risk, intended use, and the evidence needed for review. The 510(k), De Novo, and PMA processes address different market authorization circumstances, while an Investigational Device Exemption (IDE) supports investigational device use before submission when clinical data are required. Selecting and understanding the applicable pathway directly affects development and submission planning.
This webinar examines practical considerations across the 510(k), De Novo, PMA, and IDE processes, including substantial equivalence, higher-risk devices requiring clinical evidence, and recent 510(k) modifications intended to accommodate newer technology or increased safety. The discussion also addresses the Q-Submission process, Breakthrough and STeP considerations, Machine Learning and Artificial Intelligence features that can add submission complexity, and post-market requirements. The focus is on understanding how device classification and evidence requirements influence FDA review and U.S. market authorization.
Distinguish the Appropriate FDA Submission Pathway
Develop a clearer basis for distinguishing among 510(k), De Novo, PMA, and IDE pathways based on device classification, risk, substantial equivalence, and clinical evidence considerations. Understanding these distinctions helps regulatory and product teams recognize how the applicable route affects submission planning and FDA review before commercialization in the United States.
Account for Newer Technologies and Submission Options
Strengthen awareness of factors that can complicate or modify traditional submission planning, including newer technology, increased safety, Q-Sub interactions, Breakthrough and STeP considerations, and Machine Learning or Artificial Intelligence features. This perspective helps teams evaluate how evolving device characteristics may affect the pathway and supporting evidence presented to FDA.