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Cells sense information encoded in extracellular ligand concentrations and process it using intracellular signalling cascades. Using mathematical modelling and high-throughput imaging of individual cells, we studied how a transient extracellular growth factor signal is sensed by the epidermal growth factor receptor system, processed by downstream signalling, and transmitted to the nucleus. We found that transient epidermal growth factor signals are linearly translated into an activated epidermal growth factor receptor integrated over time. This allows us to generate a simplified model of receptor signaling where the receptor acts as a perfect sensor of extracellular information, while the nonlinear input–output relationship of EGF-EGFR triggered signalling is a consequence of the downstream MAPK cascade alone.

Cancer therapy benefits today from the availability of new promising classes of drugs such as therapeutic proteins. Due to their ability to specifically bind targets in the body they allow to modulate specific chemical reactions and ultimately to modify the functional response of the cell, such as cell growth or cell division. Targeting receptor systems by competitive inhibition is the objective of various protein drugs in development and on the market. Many targeted receptor systems also constitute a degradation mechanism for the drug via endocytosis and a thorough understanding of the complex interplay between the drug's pharmacokinetics and its effect, is largely missing. For complex diseases such as cancer, systems biology models of therapeutically relevant cellular processes have proven valuable for identifying potent drug targets. So far, such information about the dynamics of the targeted system is neglected in later stages of the drug development process when pharmacokinetic modeling is used to guide dose finding and analyze preclinical or clinical in vivo data. This is especially critical for therapeutic proteins where, due to the degradation mediated by the targeted receptor, drug effect and pharmacokinetics are inherently interdependent. This thesis combines the points of view of systems biology and pharmacokinetics. We present a detailed mechanistic model of the targeted cellular system that explicitly takes into account receptor binding and trafficking inside the cell and that is used to derive reduced models of drug degradation which retain a mechanistic interpretation. By integrating cell-level models with established pharmacokinetic models, we translate biophysical properties of protein drugs into a transient drug effect in vivo. We illustrate the approach for antibodies against the epidermal growth factor receptor used in cancer therapy. The cell-level pharmacokinetic/pharmacodynamic model identifies options and limits for future therapeutic antibod

In drug discovery, the potential of cytochrome P450 inhibition of new chemical entities (NCEs) is frequently quantified in terms of IC50 values. In early drug discovery a risk-classification into low, medium or high potential inhibitors is often sufficient for ranking and prioritizing of compounds. While often six or more inhibitor concentrations are used to determine the IC50 value, the question arises whether it is possible to predict the risk-class based on fewer inhibitor concentrations with comparable reliability. In the present article we propose a new integrated twopoint method with inhibitor concentrations chosen in accordance with the risk-classification. We analyse its predictive power and the feasibility to not only classify the compounds into different risk classes but also rank those compounds that have been binned into the middle risk class. The proposed integrated two point method is thus highly suitable for automation. Altogether it maintains the quality of the prediction while considerably reducing time and cost. The proposed method is applicable to other IC50 assays and risk classifications.