Personalised disease prevention
Diseases develop as a consequence of inherited susceptibilities and environmental exposure. Earlier intervention could clearly reduce the costs and the disease burden with major societal impacts in health and life-style. With modern science and technology including rapid evolving fields such as genomics, proteomics, and metabolomics, the ability to predict events and interfere before damage occurs is possible. Individuals will be evaluated to determine their baseline risk for various diseases, their current health status, and the likelihood of their developing specific clinical problems given their risks. In order for this to be possible one must acquire the tools like predictive biomarkers. These biomarkers would be identified and tracked over time to determine whether the individual’s likelihood of developing any particular disease is increasing or decreasing. For individuals that are identified to be high risk they will undergo extensive surveillance to track the disease as much as possible and to provide therapeutic support, such as with breast cancer. With any disease for personalized prevention and early intervention, it is necessary to predict baseline risks, provide surveillance for early detection, and facilitate optimal individualized therapy if disease develops. The first solutions are likely to emerge in specific areas where conventional treatments are not sufficient and there are first clinical applications. It is possible that this happens both through public sector financed initiatives and in the private markets.
The institutionalisation of the approach in healthcare would require the development of math models and data collection as a guideline to help standardize care. The models can then be used to identify risk prediction factors for particular diseases and a specific person’s profile.
The development of models and the collection of data require wide healthcare sector collaboration. Breakthroughs in such more personalised prevention have potentially far reaching economic and social impacts that would justify investments in coordinated European R&D efforts and market deployment. Increased predictive power is likely to attract the health insurance companies and subsequently also raise several data privacy issues that need to be addressed in a coordinated manner, in which European institutions and programmes could be in a relevant role.