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Open-Source MOdeling framework for automated quality control and management of complex life Science systEms modelS (OSMOSES)

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OSMOSES

The Open-Source MOdeling framework for automated quality control and management of complex life Science systEms modelS (OSMOSES) is a project funded by the German Federal Ministry of Education and Research (project site).

The aim of the project is to solve the two major challenges in physiologically-based pharmacokinetics (PBPK) and complex systems modeling & simulation with the Open Systems Pharmacology Software (OSPS), namely 1) the requirement for continuous (re-)qualification of models throughout their life-cycle and 2) handling the growing complexity of the developed models.

  1. Model Qualification: The objective is to develop and implement a technical solution for automated requalification of selected (i.e. “officially released” or “OSP certified”) scenario types. This will allow convenient and quality controlled (re-)qualification of models for their intended use, which is required once changes in the software platform (e.g. adjusted or extended model structure, changed parameterization of a model, etc.) have been made e.g. for a new release. Scenario types would be a set of simulations of either PBPK or PB-QSP models to qualify: a certain drug PK, drug-drug interactions (e.g. CYP3A4 inhibition), pediatric scaling in primarily renally cleared drugs, multiple biomarkers of disease progression, etc.
  2. Model Management: Modular modeling concepts and infrastructure (“Platform Modularization”): While the software allows the implementation of any type of complex systems-biology sub-models, or “modules”, it lacks functionality to conveniently manage or change between and to share (e.g. in the open source community) different modules for hypothesis testing and model extension. We want to develop a flexible modularity-based concept for efficient handling of sub-models for the implementation of comprehensive disease model platforms for the software that allows quality controlled and performance-optimized use-case specific adaptation of the PB-QSP platform.

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