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Mechanistic Modeling of Genome Scale Molecular Interaction Networks

Wed, April 26th 2017
On-Demand Webinar
YouTube video

Physiologically-based Pharmacokinetic (PBPK) modeling has become the industry standard for predicting drug-drug interactions, formulation effects, and pharmacokinetics in human populations. As a bottom-up, literature-based, mechanistic computer simulation approach, it shares general methodology with the computational systems biology, where molecular biology knowledge is assimilated into molecular network models. In particular, reconstruction of Genome Scale Metabolic Networks (GSMNs) has led to mechanistic models incorporating a whole set of metabolic enzymes expressed in human tissues. Moreover, dynamic models of the expression of key drug metabolism enzymes are available.

Currently, PBPK models account for about 20 genes involved in drug metabolism. Integrating PBPK with GSMN and gene regulation models can extend the scope of mechanistic pharmacokinetic modeling to thousands of genes as well as the complex interactions of drug metabolism enzymes with endogenous metabolites such as cortisol. In this webinar, Dr. Andrzej Kierzek will demonstrate how integrating human hepatocyte GSMN, gene regulation of CYP3A4, and a basic PBPK model can identify genes influencing the production of toxic metabolites and simulate kinetics of this metabolite as a function of cortisol and Pregnane X receptor (PXR) ligands.

About Our Speaker

Andrzej Kierzek graduated with an undergraduate degree in molecular biology from the University of Warsaw and received a PhD in biophysics from Polish Academy of Sciences in 1999. Since 2004, he has been working at University of Surrey, UK and became Professor of Systems Biology in 2011. In April 2016, he moved to Certara QSP as Head of Systems Modeling. He is still a visiting Professor of Systems Biology at Surrey. Andrzej has more than 20 years of experience in computational biology. He has been working in computational systems biology for over 15 years. He published models and software for analysis of molecular network dynamics and constraint-based modeling of genome scale metabolic networks, including metabolic reprogramming in cancer. Currently, his research focus is on immune-oncology and immunogenicity.

Physiologically-based Pharmacokinetic (PBPK) modeling has become the industry standard for predicting drug-drug interactions, formulation effects, and pharmacokinetics in human populations. As a bottom-up, literature-based, mechanistic computer simulation approach, it shares general methodology with the computational systems biology, where molecular biology knowledge is assimilated into molecular network models. In particular, reconstruction of Genome Scale Metabolic Networks (GSMNs) has led to mechanistic models incorporating a whole set of metabolic enzymes expressed in human tissues. Moreover, dynamic models of the expression of key drug metabolism enzymes are available.

Currently, PBPK models account for about 20 genes involved in drug metabolism. Integrating PBPK with GSMN and gene regulation models can extend the scope of mechanistic pharmacokinetic modeling to thousands of genes as well as the complex interactions of drug metabolism enzymes with endogenous metabolites such as cortisol. In this webinar, Dr. Andrzej Kierzek demonstrated how integrating human hepatocyte GSMN, gene regulation of CYP3A4, and a basic PBPK model can identify genes influencing the production of toxic metabolites and simulate kinetics of this metabolite as a function of cortisol and Pregnane X receptor (PXR) ligands.