SUMMARYModeling and simulation in pharmacokinetics has 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 of significantly increasing insight into pharmacokinetic processes. To adequately support in silico methodology, software tools need to be user-friendly and, at the same time, flexible. In brief, the software has to allow the realization of modeling ideas that are beyond current knowledge -in the form of a virtual lab. We present and discuss the necessary design principles and concepts. These have been implemented in the software package MEDICI-PK to demonstrate its feasibility and advantages. PHARMACOKINETICS IN DRUG DISCOVERYThe medical benefits of a drug depend not only on its biological effect at the target protein, but also on its "life cycle" within the organism -from its absorption into the blood, distribution to tissue and its eventual breakdown or excretion by the liver and kidneys. Pharmacokinetics is the study of the drug-organism interaction, in particular the investigation of absorption, distribution, metabolism, and excretion (ADME) processes [1,2]. Studying ADME profiles is widely used in drug discovery to understand the properties necessary to convert leads into good medicines [3,4].As a result of studies in the late 1990s, indicating that poor pharmacokinetics (PK) and toxicity were important causes of costly late-stage failures in drug development, it has

Two different approaches to parameter estimation (PE) in the context of polymerization are introduced, refined, combined, and applied. The first is classical PE where one is interested in finding parameters which minimize the distance between the output of a chemical model and experimental data. The second is Bayesian PE allowing for quantifying parameter uncertainty caused by experimental measurement error and model imperfection. Based on detailed descriptions of motivation, theoretical background, and methodological aspects for both approaches, their relation are outlined. The main aim of this article is to show how the two approaches complement each other and can be used together to generate strong information gain regarding the model and its parameters. Both approaches and their interplay in application to polymerization reaction systems are illustrated. This is the first part in a two-article series on parameter estimation for polymer reaction kinetics with a focus on theory and methodology while in the second part a more complex example will be considered.

Abstract. A powerful new software concept to physiologically based pharmacokinetic (PBPK) modelling of drug disposition is presented. It links the inherent modular understanding in pharmacology with orthogonal design principles from software engineering. This concept allows for flexible and user-friendly design of pharmacokinetic whole body models, data analysis, hypotheses testing or extrapolation. The typical structure of physiologically-based pharmacokinetic models is introduced. The resulting requirements from a modelling and software engineering point of view and its realizations in the software tool MEDICI-PK are described. Finally, an example in the context of drug-drug interaction studies is given, that demonstrates the advantage of defining a whole-body pharmacokinetic model in terms of the underlying physiological processes quite impressively: A system of 162 ODEs is automatically compiled based on the specification of 7 local physiological processes only.