- 1:30 PM

Computer Aided Modelling in Pharmacokinetics as a Topical Issue

Michael Wulkow and Regina Telgmann. CiT GmbH, Oldenburger Str. 200, Rastede, 26180, Germany

Modelling and simulation in pharmacokinetics has turned into the focus of pharmaceutical companies, driven by the emerging consensus that in silico predictions, combined with in vitro data, have the potential to significantly increase insight into pharmacokinetic processes. Pharmacokinetics is the study of the time course of drug and metabolite levels in different fluids, tissues, and excreta of the body. This includes the investigation and understanding of the processes of absorption, distribution, metabolism and excretion (ADME). The pharmacokinetic profile of a drug strongly influences its delivery to biological targets, thereby affecting its efficacy and potential side effects. To support in silico methodology adequately, software tools are needed which do not only facilitate the solving of equations but also take over the ballast of repeated implementation of known and structurally equal working steps without preventing the input of open modelling ideas. In fact, such software (that does not mean purely equation based standard solvers) has to allow the modelling of ideas that go beyond the current knowledge otherwise it would not be called innovative. In this talk a powerful new concept to physiologically based pharmacokinetic (PBPK) modelling of drug disposition is presented linking the inherent modular understanding in pharmacology to orthogonal design principles from software engineering. The necessary design principles and concepts required to do this are discussed. They have been implemented in the software package MEDICI-PK, demonstrating its feasibility and advantages. The approach is illustrated on examples from drug-drug interaction studies in a body model with more than a dozen compartments leading to several hundred differential equations. It is demonstrated how changes of list of compartments (organs), topology and modelling of physiological phenomena can easily be realized. Even parameter identification can be applied to such openly defined models.