Model reduction in pharmacology and systems biology
Molecular biology generates gigantic amounts of in vitro data, which contains detailed information on disease mechanisms, ADME processes (pharmacokinetics) and on drug effects (pharmacodynamics). The derived information, however, relates to processes observed in isolation. In vivo derived data reflects the impact of a drug on the entire individual, however, only a fraction of relevant parameters can be measured.
Typically, in vivo data is analyzed and interpreted in terms of minimal models, whereas complex, mechanistic models are used to integrate in vitro data. We want to facilitate a continuous model development and enable the utilization of all available data and information. We use model reduction techniques to derive so called “core-models”, which can be parameterized by in vivo data. Back-transformation of these models enables to derive in vivo information on the molecular processes of interest.
The project is funded through the German Ministry of Education an Research (BMBF).
- von Kleist, M., Huisinga W.(2007) Physiologically based pharmacokinetic modelling: a sub-compartmentalized model of tissue distribution. J Pharmacokinet Pharmacodyn., 34(6):789-806
- von Kleist, M. and Kloft, Ch. and Huisinga, W. (2007) Combining Systems Biology with Physiologically Based Pharmacokinetics to Support the Understanding of Drug Effects. In: Proceedings of the 2nd Foundations of Systems Biology in Engineering Conference, FOSBE 2007, 09.-12.09.2007, Stuttgart, Germany.
<Patend application in process>
Max von Kleist