A computational systems biology software platform for multiscale modeling and simulation: Integrating whole-body physiology, disease biology, and molecular reaction networks

• Main Authors: Thomas eEissing, Lars eKuepfer, Corina eBecker, Michael eBlock, Katrin eCoboeken, Thomas eGaub, Linus eGoerlitz, Juergen eJaeger, Roland eLoosen, Bernd eLudewig, Michaela eMeyer, Christoph eNiederalt, Michael eSevestre, Hans-Ulrich eSiegmund, Juri eSolodenko, Kirstin eThelen, Ulrich eTelle, Wolfgang eWeiss, Thomas eWendl, Stefan eWillmann, Joerg eLippert
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2011-02-01
• Series: Frontiers in Physiology
• Subjects: Signal Transduction; Software; Systems Biology; simulation; modeling; PBPK
• Online Access: http://journal.frontiersin.org/Journal/10.3389/fphys.2011.00004/full

Today, in silico studies and trial simulations already complement experimental approaches in pharmaceutical R&D and have become indispensable tools for decision making and communication with regulatory agencies. While biology is multi-scale by nature, project work and software tools usually focus on isolated aspects of drug action, such as pharmacokinetics at the organism scale or pharmacodynamic interaction on the molecular level. We present a modeling and simulation software platform consisting of PK-Sim® and MoBi® capable of building and simulating models that integrate across biological scales. A prototypical multiscale model for the progression of a pancreatic tumor and its response to pharmacotherapy is constructed and virtual patients are treated with a prodrug activated by hepatic metabolization. Tumor growth is driven by signal transduction leading to cell cycle transition and proliferation. Free tumor concentrations of the active metabolite inhibit Raf kinase in the signaling cascade and thereby cell cycle progression. In a virtual clinical study, the individual therapeutic outcome of the chemotherapeutic intervention is simulated for a large population with heterogeneous genomic background. Thereby, the platform allows efficient model building and integration of biological knowledge and prior data from all biological scales. Experimental in vitro model systems can be linked with observations in animal experiments and clinical trials. The interplay between patients, diseases, and drugs and topics with high clinical relevance such as the role of pharmacogenomics, drug-drug or drug-metabolite interactions can be addressed using this mechanistic, insight driven multiscale modeling approach.