Many participants in the consultation process are excited about the possible opportunities provided by the Digital Patient initiative, based on their own personal experience. Many of these opportunities are quite novel, and indicate the potential of the Digital Patient on the clinical, research and industrial sectors.
Medical Education: VPH models, and computational tools could be used to enrich medical student education. Firstly, the models, if sufficiently mature, can allow students to explore the mechanisms behind disease, and to study the effects of different aspects of disease on clinical end-points and patient well-being. Secondly, the introduction of computational tools at this early stage in training could help future adoption of VPH paradigms, and allow students to familiarise themselves with the state-of-the-art in computational bioengineering research.
Unifying patient data: The possibility of combining data on a patient from various diagnostic sources, and crucially, to be able to quickly and easily access the data, could help improve diagnosis. This will require an infrastructure in which the maximum level of detailed data is available to the medical practitioner, but is managed and interfaced-with in such a way that he/she is not overloaded with information.
From risk-factors to biomarkers: The use of mechanistic models can allow us to move away from empirical risk-factors for disease towards more mechanistic and relevant markers for disease. As an example, instead of using ventricle size as a surrogate measure of heat function, a haemodynamic analysis can provide information directly on the hydraulic performance of the heart (blood flow rate, pressure, etc.).
As a tool for understanding: Similar to its use in medical education, an individualised model could help clinicians understand the effects of intervention on patient well-being. Particularly in long-term and complex diseases, it may be difficult to predict the effects interventions such as lifestyle changes will have.