Application of the SBTOOLBOX2 in drug discovery and development
K. Zhudenkov (1), G. Helmlinger (2), H. Schmidt (3)
(1) Novartis Pharma, Moscow, Russia; (2) Novartis Institute for Biomedical Research, Cambridge, MA; (3) Novartis Pharma, Basel, Switzerland
Objectives: In modern Drug discovery and Development, mechanistic physiologically based and more traditional PKPD models all play an important role. The practical handling of mathematical drug and disease models and their analysis require powerful and flexible, yet user-friendly computational tools. The Systems Biology Toolbox 2 (SBTOOLBOX2, [1]), is a publicly available, open-source tool aiming at simplifying the required modeling and simulation workflow (can be freely downloaded from - http://www.sbtoolbox2.org). At Novartis the SBTOOLBOX2 is used together with the SBPOP, to enable a link to population modeling approaches in Monolix® (Lixoft, France). Currently, the SBPOP extension is not generally available.
Methods: The SBTOOLBOX2 is a Matlab toolbox. It uses multiple features available in Matlab® (The MathWorks, USA) and provides additional specific technical features for Drug development and Discovery. The Systems Biology platform consists of linked packages: 1) The SBTOOLBOX2 is used for model development; 2) The Systems Biology Parameter Determination (SBPD) is used for project-level representations.
Results: Within the SBTOOLBOX2 project, model coding is very easy. Model syntax can be ODE-based or biochemical reactions-based. The latter is most intuitive and simple. Automatic C-code generation while processing projects is useful for speeding up simulations, in a seamless manner to the user. By using the SBPD, the project simulation is very fast (30-200 times faster than normal Matlab Simulation).
Here we present a drug monoclonal Antibody (mAb) - target binding model [2], as an example developed in the SBTOOLBOX2. Model describes mAb concentration in physiologically sized plasma and tissue compartments. Key aim is to assess dose-response relation for different assumptions on which gaps in knowledge exist and to test different properties of the mAb to support its design (estimation of KD with respect to dose regime and target half-life).
Conclusions: The SBTOOLBOX2 gives the user high flexibility and relative simplicity to work on PKPD and PBPK modeling activities, as compared to different popular software packages like Berkeley Madonna® (University of California at Berkeley, USA), CellDesigner® (Systems Biology Institute, Japan), etc. The SBTOOLBOX2 is easy to use, well documented and easily extensible. These qualities make the SBTOOLBOX2 a potential tool for Training and Education in the field of Systems biology and Drug Discovery and Development.
References:
[1] Schmidt H. and Jirstrand M.: Systems Biology Toolbox for MATLAB: a computational platform for research in systems biology. Bioinformatics 22 (4): 514-515, 2006;
[2] Roskos L.: Handbook of Therapeutic Antibodies. 2008.
