  A digital health twin can be defined as a virtual model of a physical person,
in this specific case, a patient. This virtual model is constituted by
multidimensional data that can host from clinical, molecular and therapeutic
parameters to sensor data and living conditions. Given that in computational
pathology, it is very important to have the information from image donors to
create computational models, the integration of digital twins in this field
could be crucial. However, since these virtual entities collect sensitive data
from physical people, privacy safeguards must also be considered and
implemented. With these data safeguards in place, health digital twins could
integrate digital clinical trials and be necessary participants in the
generation of real-world evidence, which could positively change both fields.
