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Dynamical modeling of drug effect using hybrid systems

Xiangfang Li1*, Lijun Qian2 and Edward R Dougherty134

Author Affiliations

1 Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA

2 Department of Electrical and Computer Engineering, Prairie View A&M University, Prairie View, TX 77446, USA

3 Computational Biology Division, Translational Genomics Research Institution, Phoenix, AZ 85004, USA

4 Department of Bioinformatics and Computational Biology, University of Texas M.D. Anderson Cancer Center, Houston, TX 77030, USA

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EURASIP Journal on Bioinformatics and Systems Biology 2012, 2012:19  doi:10.1186/1687-4153-2012-19

Published: 26 December 2012


Drug discovery today is a complex, expensive, and time-consuming process with high attrition rate. A more systematic approach is needed to combine innovative approaches in order to lead to more effective and efficient drug development. This article provides systematic mathematical analysis and dynamical modeling of drug effect under gene regulatory network contexts. A hybrid systems model, which merges together discrete and continuous dynamics into a single dynamical model, is proposed to study dynamics of the underlying regulatory network under drug perturbations. The major goal is to understand how the system changes when perturbed by drugs and give suggestions for better therapeutic interventions. A realistic periodic drug intake scenario is considered, drug pharmacokinetics and pharmacodynamics information being taken into account in the proposed hybrid systems model. Simulations are performed using MATLAB/SIMULINK to corroborate the analytical results.

Drug effect; Hybrid systems; PK/PD; Gene regulatory network (GRN); Dosing regimens