Advances at the interface of biomedicine and IT are leading to rapid growth in the amount of data available – genomics and other omics data, data from hospitals, primary care, biobanks or self-tracking health data (generated by individuals themselves). Personalized health uses this data to identify disease risks at an earlier stage, to tailor medical treatments to characteristics of individual patient groups and to develop public health strategies.
Personalized or precision medicine relies on big data to optimize healthcare for individual patients – from prevention to diagnosis, treatment and rehabilitation. The aims of personalized health are more far-reaching: data-driven findings should benefit not only individuals, but also the entire population, e.g. by enabling early identification of disease risks and the development of appropriate health strategies for those concerned.
For science and society
The increasing amount of data offers major opportunities for medical research and public health. However, the collection, storage and analysis of data raise numerous questions regarding data quality, -security and sovereignty, as well as the key issues of data comparability and interoperability.
Within this context, the Swiss Confederation launched a national initiative in 2017 to promote personalized medicine. The State Secretariat for Education, Research, and Innovation (SERI) and the Federal Office of Public Health (FOPH) commissioned the SAMS and the Swiss Institute for Bioinformatics (SIB) to establish the organizational framework for a Swiss network for personalized health. This led to the initiation of the Swiss Personalized Health Network (SPHN).