Project
Systems medicine aims at translating systems biological knowledge into diagnostic, predictive and therapeutic applications taking account of individual differences among patients. While individualized medicine is more or less still orientated towards single biomarkers, systems medicine is grounded on mathematical models integrating heterogeneous data from different sources and levels. The project investigates how these data on biological systems are translated into medically relevant knowledge and which factors do impede these processes.
Our research guiding hypotheses are:
(1) The integration of data as well as translation of resulting knowledge into clinical practice are complex, interdisciplinary processes.
(2) They involve epistemic and technical as well as social and organizational questions and challenges.
(3) These challenges can create terminological, pragmatic and social differences and problems which impede the utilization of systems biological knowledge and its translation into clinical application.
A profound understanding of such integration and translation processes is a necessary precondition for overcoming potential hurdles generated by their complexity and interdisciplinarity. In order to contribute to their detailed understanding, the goal of the project is to empirically analyse the discourses, processes and practices of integration and translation in the context of systems medicine. From the perspective of Actor Network Theory (ANT), we will explore the ‘interface’ between research and clinical practice in which discourses, processes and practices of integration and translation are interrogated. As the components and the dynamics of integration and translation processes are so far rudimentary reflected and barely examined on an empirical basis, we will use exploratory empirical methods, in particular document analysis and interviews with scientists from involved disciplines comparing two fields of study in systems medicine (cancer and mental disorders).