Regulatory oversight and ethical concerns surrounding software as medical device (SaMD) and digital twin technology in healthcare

Abstract

The goal of precision medicine is to provide tailored therapy to each patient with considering therapeutic benefits and risks. Strides toward this goal have been made by harnessing the benefits of big data, the development of mathematical and data-based computational models, and the use of artificial intelligence (AI) and machine learning (ML) algorithms (1-3). The currently available mathematical models lack fidelity, are unable to represent changes in real-time, and are far from being the optimal tools to provide robust predictive enrichment that can be of use in clinical medicine. In their article, Liu et al. (4) performed an exhaustive bibliometric analysis of the currently available applications, specifically in the arena of individualized diagnosis and treatment of the critically ill patients. There has been an increasing number of articles published over the past decade, however, the clinical relevance and real-world application remains debatable. To circumvent these issues, the construction of digital twin models based on research data and physiological properties has been proposed.