gms | German Medical Science

51. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (gmds)

10. - 14.09.2006, Leipzig

Mathematical modeling in pharmacokinetics: a modular, physiologically-based approach

Meeting Abstract

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  • Wilhelm Huisinga - Freie Universität Berlin & DFG-Forschungszentrum MATHEON, Berlin

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (gmds). 51. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. Leipzig, 10.-14.09.2006. Düsseldorf, Köln: German Medical Science; 2006. Doc06gmds209

The electronic version of this article is the complete one and can be found online at:

Published: September 1, 2006

© 2006 Huisinga.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Pharmacokinetic studies have turned into the focus of pharmaceutical companies, after studies manifested that the major reason for attrition is due to poor pharmacokinetics [1]. As a consequence, considerable effort has been put on the development of in silico models to predict and understand the pharmacokinetics of new compounds, in particular in early drug discovery. Meanwhile, considerable progress has been made with the use of physiologically based pharmacokinetic models such that nowadays modeling and simulation is possible prior to any in vivo experiments, solely based on in vitro data [2].

Physiologically based pharmacokinetic modeling approaches offer the advantage of incorporating experimental animal data as well as in vitro and in silico derived data into a coherent framework, from which meaningful and reliable assessments can be made. Many data on physicochemical properties and specific absorption, distribution, metabolism, excretion (ADME) processes are already available at early stages of the drug discovery process. Along the drug discovery process more refined and detailed data are generated, based on which more accurate predictions and analysis can be made.

In the talk, we present the concepts of a hierarchical, modular and physiologically-based approach supporting in silico modeling and simulation in pharmacokinetics/dynamics that is especially tailored to serve the needs in drug discovery. The approach is illustrated in application to the pharmacokinetics of a first-generation sulfonylurea. The different models have been realized in the virtual lab MEDICI-PK [3], a joint cooperation with Computing in Technology (CiT), Rastede/Germany.


Waterbeemd H, van Gifford E. ADMET in silico modelling: towards prediction paradise? Nature 2. 2003; p. 192-204
Poulin P, Theil FP. Prediction of Pharmacokinetics prior to In Vivo Studies. II. Generic Physiologically Based Pharmacokinetic Models of Drug Disposition. J Pharm Sci. 2002;91:1358-1370.
Huisinga W, Telgmann R, Wulkow M. The Virtual Lab Approach to Pharmacokinetics: Design Principles and Concepts, submitted. 2006.