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Modeling and Simulation Tools: From Systems Biology to Systems Medicine
Brett G Olivier1, Maciej J Swat2, Martijn J Moné3,4
1Systems Bioinformatics, VU University Amsterdam, Amsterdam, The Netherlands. b.g.olivier@vu.nl.
Methods in Molecular Biology (Clifton, N.J.)
|December 18, 2015
Summary
This study compares Systems Biology and Pharmacometrics software tools for Systems Medicine. It highlights the need for standardized exchange formats, like SBML and a new Pharmacometrics format, to improve drug discovery and development efficiency.
Area of Science:
- Computational Biology
- Systems Medicine
- Pharmacometrics
Background:
- Modeling is crucial in modern biology and Systems Medicine.
- Software tools are essential for biological modeling and drug development.
- Two key methodologies, Systems Biology and Pharmacometrics, have distinct software development approaches.
Purpose of the Study:
- To compare software tools for Systems Biology and Pharmacometrics in the context of Systems Medicine.
- To explore the implications of "Software as a Medical Device" for research simulation software.
- To address the need for standardized exchange formats in computational drug discovery and development.
Main Methods:
- Comparative analysis of software development and characteristics in Systems Biology and Pharmacometrics.
- Examination of the "Software as a Medical Device" concept.
- Introduction of a new exchange format for Pharmacometrics, complementing existing standards like SBML.
Main Results:
- Systems Biology utilizes "Software as a Medical Device" concepts for research software migration.
- Hundreds of computational tools are used in drug discovery, necessitating standardized exchange formats.
- A new Pharmacometrics exchange format addresses the lack of standardization in clinical study population analysis.
Conclusions:
- Interfacing Systems Biology (SBML) and new Pharmacometrics exchange formats can cover the entire domain of computational modeling.
- Standardized formats streamline model exchange, minimize errors, and reduce development time.
- This integration facilitates seamless data flow from research to clinical applications in Systems Medicine.
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