Dynamic aspects such as transient phenomena after a therapeutic intervention are often not systematically investigated by clinical trials. Clinical research in general is faced with the limited accessibility to time resolved data needed for determination of time constants or identification of characteristic dynamic patterns. This may be a reason for the widely dominating and somewhat static view to disease as a result of a pathological mechanism instead to illness as a manifestation of dynamic (mis-) interactions. Since biological systems are characterised by a high degree of plasticity, the term of (dynamic) process instead of mechanism or (molecular) machinery seems to be more adequate.

One implication of this wording is the idea of considering cells, tissues, organs or organisms as systems with a dynamic network structure, were the influence of a single signalling pathway could be very limited or in some cases neglected due to evolved stability (by the system acquired strategies to maintain functionality). In this context, we demonstrated in recent research projects the usefulness of top-down approaches to cover relevant dynamic interactions leading to observable biological phenomena. Since the development of systems theory and computational methods offer the access to complex, non-linear dynamic systems, we started to transfer this knowledge to the planning of clinical trials, model-based data analysis clinical, pre-clinical or experimental biological data or to the design of medical devices.