Drug discovery and development is associated with high attrition rates largely due to a lack of efficacy and unexpected safety concerns of new drugs. An important question is therefore how to improve the prediction of drug efficacy and safety.

The mechanism-based PK-PD modeling platform 2.0 aims at the development of novel mechanism-based PK-PD modeling concepts for stationary and non-stationary biological systems and builds on the mechanism-based PK-PD modeling platform 1.0. The research program is a systems pharmacology approach which focuses on the development and application of novel mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling concepts. The developed mechanism-based PK-PD models contain expressions to describe, in a quantitative manner, processes on the causal path between plasma concentration and effect. To this end mechanism-based PK-PD modeling utilizes concepts from physiologically-based pharmacokinetic modeling, receptor theory, dynamical systems analysis and disease systems analysis. This research program will yield a mechanism-based PK-PD model library and database which can be used for 1) drug candidate selection, 2) design and evaluation of early 'proof of concept' studies in man, 3) optimization of phase-3 clinical trials, and 4) prediction of long-term outcome of drug treatment. In addition to the generation of models the platform educates a new generation of PK-PD modelers.

Fast facts
Full project title: PK-PD platform 2.0
Start date: 1 November 2012
End date: 1 November 2017
Goal: Develop a mechanism-based PK-PD model library together with a knowledge-based management system to securely store preclinical, clinical and epidemiological data and to support future model-based research in drug discovery and development
Principal investigator: Meindert Danhof
Project size: 9 FTE Partners: Astellas, Erasmus MC, Janssen, Leiden University, Takeda, MSD Oss, University of Groningen

“What TI Pharma can deliver from collaborations is more efficient healthcare, faster time to market and quicker patient benefit.”

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