The Digital Mouse: why computational modelling of mouse models of disease can improve translation

Computational models can be used to study the mechanistic phenomena of disease. Current mechanistic computer simulation models mainly focus on (patho)physiology in humans. However, often data and experimental findings from preclinical studies are used as input to develop such models. Biological processes underlying age-related chronic diseases are studied in animal models. The translation of these observations to clinical applications is not trivial. As part of a group of international scientists working in the COST Action network MouseAGE, we argue that in order to boost the translation of pre-clinical research we need to develop accurate in silico counterparts of the in vivo animal models. The Digital Mouse is proposed as framework to support the development of evidence-based medicine, for example to develop geroprotectors, which are drugs that target fundamental mechanisms of ageing. Highlights Computational modelling of human (patho)physiology is advancing rapidly, often using and extrapolating experimental findings from preclinical disease models. The lack of in silico models to support in vivo modelling in mice is a missing link in current approaches to study complex, chronic diseases. The development of mechanistic computational models to simulate disease in mice can boost the discovery of novel therapeutic interventions. The ‘Digital Mouse’ is proposed as a framework to implement this ambition. The development of a Digital Mouse Frailty Index (DM:FI) to study aging and age-related diseases is provided as an example.