On Regulating AI in Medical Products (OnRAMP)

Medical AI products require certification before deployment in most jurisdictions. To date, clear pathways for regulating medical AI are still under development. I present a methodological guide to the development of a regulatory package which will form part of a certification process. This approach is predicated on the translation between a statistical risk perspective, typical of medical device regulators, and a deep understanding of machine learning methodologies. This work of translation envisages the statistician as the key negotiator between medical device regulators and machine learning experts, allowing them to communicate more clearly, and thus lead to the development of standardised pathways for medical AI regulation.