Web-based workflow planning platform supporting the design and execution of complex multiscale cancer models.

Area of Science:

• Computational biology
• Oncology
• Systems biology

Background:

• Virtual Physiological Human (VPH) initiatives have focused on cancer modeling for personalized therapy.
• Current efforts in computational oncology and systems biology are fragmented, hindering clinical translation.
• Developing realistic in silico predictive models requires integrating diverse, specialized models.

Purpose of the Study:

• To propose an intelligent graphical workflow planning system for building complex cancer models.
• To facilitate the integration of fragmented systems biology and computational oncology efforts.
• To enable the creation of reliable and reproducible cancer models for clinical application.

Main Methods:

• Developed an intelligent graphical workflow planning system.
• Exploited the multiscale and modular nature of cancer for model construction.
• Integrated and extended current standardization efforts, tools, and infrastructure.

Main Results:

• The system allows intuitive linking and interchanging of specialized cancer models.
• Facilitates the creation of complex, multiscale cancer simulations.
• Aims to build a pool of reliable and reproducible computational models.

Conclusions:

• The proposed system supports the development of personalized cancer simulations.
• It addresses the need for synergistic approaches in computational oncology.
• Demonstrates potential for clinical translation of in silico cancer modeling technologies.