Digital Twins for Personalized Healthcare: Application to Radiopharmaceutical Therapies

Abstract

Abstract

There is significant interest and value in utilizing digital twins (DTs) to extend healthcare from ‘one-size-fits-all’ to personalized therapies. Radiopharmaceutical therapies (RPTs), which represent very powerful developments in the battle against cancer, are no exceptions to this. In fact, theranostic digital twins (TDTs), which we elaborate in this work, present viable and feasible approaches to personalize RPTs. TDTs are computational representations of the human body that, unlike images, are operable; i.e. virtual trials can be conducted on them to propose optimal therapies for individual patients. TDTs can be built using physiologically based pharmacokinetic (PBPK) models. This work elaborates that TDTs can be developed in static, dynamic and interactive modes towards routine use in future clinical settings. TDTs will open a new area of theranostics research and development in terms of new radiopharmaceutical designs, synthesis and enabling of more optimal therapies.