Part of the FDA's action plan includes support for the development of machine learning best practices to evaluate and improve ML algorithms for topics such as data management, interpretability and documentation, as well as advancing real-world performance monitoring pilots. The FDA also noted that the action plan would continue to evolve to stay current with developments in the field of AI/ML-based software as a medical device (SaMD). As the agency pointed out in an April 2019 discussion paper, the potential power of AI/ML-based SaMD lies within its ability to continuously learn, where the adaptation or change to the algorithm is realized after the SaMD is distributed for use and has learned from real-world experience. READ MORE: AI can increase efficiency in healthcare, even in a pandemic. In turn, the autonomous and adaptive nature of these tools requires a new, total product lifecycle regulatory approach that supports a rapid cycle of product improvement, allowing SaMD to continually improve.