## 7 In Vivo Predictive Value and Experimental Validation of Cell Biomechanics and Flow Models  
1. **Helfrich Model + Phase Field Approach ([PERSON] et al. )**[23]  
This model effectively captures RBC deformation under Poiseuille flow and shear stress, aligning with typical microvascular conditions. By integrating with Navier-Stokes equations, it bridges single-cell mechanics with whole-blood hemodynamics. The model is primarily validated in vitro, aided by advanced microfluidic platforms. While these replicate physiologic flow profiles, true in vivo complexity (e.g., endothelial interactions, plasma composition) remains underrepresented. The approach displays strong mechanistic insight and numerical reliability but requires further in vivo correlation to confirm its translational relevance, particularly under pathological conditions. 2. **Multiphysics Microfluidic Modeling ([PERSON] et al. [37])**  
This framework integrates hydrodynamic, optical, electromagnetic, and acoustic forces--mimicking the diverse stimuli present in vascular environments. These models are validated in vitro within microfluidic systems, which closely approximate capillary-scale flows. However, real cell-endothelium interactions, immune signaling, and biochemical gradients are largely absent. This approach is promising for developing diagnostic lab-on-a-chip platforms, but current implementations serve more as biophysical proxies than direct in vivo predictors. 3. **Adhesion Models of Leukocytes and Platelets ([PERSON] et al. [55])**  
The in vivo predictive power of this model is high. These models incorporate both intravital microscopy (true in vivo) and in vitro flow chamber studies, enabling robust comparisons. This area is one of the few with extensive in vivo validation. The multi-step adhesion cascade--tethering, rolling, activation, firm adhesion--is well established through live animal imaging and has been reproduced in microfluidic systems. This approach represents a well-validated biomechanical framework, supported by both real-time in vivo imaging and controlled flow-based experimentation. Additionally, it offers strong predictive value for vascular inflammation and thrombosis. 4. **Leukocyte Deformation Models ([PERSON] et al. [49])**  
The in vivo predictive power is limited. The physical models (liquid drop, non-Newtonian, and tensegrity) help interpret deformation and recovery behaviors, but mainly under static or simplified dynamic conditions. While grounded in dynamic testing, the tensegrity model, for instance, is more applicable to adherent cells than circulating leukocytes. The lack of detailed internal structural data hampers full biological fidelity. These models are valuable for theoretical understanding and isolated cell studies, but not yet predictive of leukocyte biomechanics in dynamic, inflamed vasculature. The approach needs further refinement and correlation with live-cell and intravital data. 5. **FE/BE Immersed Boundary Simulations ([PERSON] et al. [57])**  
The in vivo predictive power of the model is high. The approach accounts for bending energy, membrane elasticity, and tank-treading motion--all key RBC behaviors observed in microcapillaries. The model is quantitatively validated against experimental data, showing good agreement. The simulations mimic RBC dynamics through constricted capillaries, a hallmark of in vivo microcirculation. This is among the most reliable computational methods, with strong in vitro-in vivo translation. It is particularly relevant for the modeling of pathologies involving altered RBC deformability, such as sickle cell disease. An overall assessment of the in vivo predictive value and experimental validation of cell biomechanics and flow models shows that the strongest in vivo validation is foundin studies on cell adhesion under flow conditions ([PERSON] et al. [55]) and RBC deformation in capillaries (FE/BE IBM modeling).