  Software of Unknown Provenance, SOUP, refers to a software component that is
already developed and widely available from a 3rd party, and that has not been
developed, to be integrated into a medical device. From regulatory perspective,
SOUP software requires special considerations, as the developers' obligations
related to design and implementation are not applied to it. In this paper, we
consider the implications of extending the concept of SOUP to machine learning
(ML) models. As the contribution, we propose practical means to manage the
added complexity of 3rd party ML models in regulated development.
