Integrative Approaches in Immune Modeling: Bridging Scales for Personalized Medicine

The field of systems biology has experienced significant growth since the early 20th century, influencing various branches of biomedicine like systems physiology and systems immunology. Despite the insightful theoretical publications that highlight the immense potential of a systems approach, its practical integration into real-world biomedicine remains scarce. One major hurdle impeding this integration is the multifactorial complexity, particularly the mathematical and computational challenges involved in creating and applying integrative models that accurately represent the multiscale, multi-physics nature of biological systems. The recent COVID-19 pandemic has accelerated efforts to form research consortia tackling key questions such as virus-host interactions and immune responses. This has underscored the necessity for general mathematical and computational frameworks capable of addressing both theoretical and practical issues, including model calibration and uncertainty quantification. There's an urgent need for innovative numerical techniques to solve both the single class models (initial-boundary value problems, agent-based models, etc.) as well as hybrid systems and to construct holistic models that can assimilate diverse data types, paving the way for breakthrough advancements in personalized medicine.

This Research Topic aims to develop integrative models that seamlessly connect molecular, cellular, and systemic levels of immune response. By leveraging cutting-edge technologies like high-throughput data analysis and advanced algorithms, the goal is to unlock new insights into immune cell behavior and its implications for personalized medicine. The exploration of these advanced models will focus on their potential to forecast therapeutic outcomes, optimize treatment strategies, and increase the efficacy of immune-based therapies.

To gather further insights within this dynamic area of research, we welcome articles addressing, but not limited to, the following themes:

- Theoretical frameworks for developing multi-scale immune models
- Computational methods for uncertainty quantification in model predictions
- Applications of integrative models in forecasting therapeutic outcomes
- Innovations in high-throughput data integration for personalized medicine
- Case studies on successful applications of multi-scale modeling in immunology

We invite contributions in various formats, including research articles, review articles, method papers, case reports, and perspective pieces.