From digital control to digital twins in medicine: A brief review and future perspectives

Abstract

The last few decades have been dominated by the need for digital control of various processes in biology and medicine. Advances in artificial intelligence (AI) over the last few years, and data being generated at extremely high rates and being analyzed and interpreted with the help of AI, have led to new approaches in medicine that include also optimization and real-time control algorithms. In particular, digital twins (i.e., digital replicas of biological systems: cells, tissues, organs, systems) have seen a fulminant rise over the last few years. We start this review by discussing briefly the use of digital control applied to various medical problems: from diabetes to anesthesia. Then, we focus on the extension of the digital control concept to the digital twins concept to improve not only the process control, but also to improve biomedical design, virtual testing of personalized therapies, and optimization of therapies (including drug delivery). We discuss the applications of such digital twins to preclinical research as well as clinical research. We conclude this review by outlining some benefits as well as ethical concerns surrounding the digital twins.