Computational Models of the Foreign Body Response: A Focus on Biomaterial Properties

The foreign body response (FBR) is the main biological process governing the long-term performance and safety of implantable biomaterials. As the FBR is complex, multifactorial, and unfolds over extended time scales, making in vitro replication challenging, standard biological evaluation frameworks continue to rely primarily on in vivo testing In this context, computational modeling offers a promising strategy to improve the fundamental understanding of FBR mechanisms, support biomaterial design, and reduce dependency on animal experimentation. Existing approaches, including ordinary differential equation (ODE), partial differential equation (PDE), and agent-based (AB) models, have provided important insights into inflammatory signaling, macrophage dynamics, fibrosis progression, and capsule formation. However, most computational models still treat the FBR in a simplified way and rarely integrate material-dependent effects in a quantitative manner, despite the well-established role of surface chemistry, topography, stiffness, and other properties in shaping host responses. This review summarizes the current state of the art in computational models of the FBR, including both mechanistic and data-driven methods, with a particular focus on how material properties are represented. We discuss the main limitations of current modeling approaches as well as the scarcity of standardized experimental data suitable for calibration and validation, and highlight the need for closer interplay between hybrid predictive models and experimental data, with a digital twin (DT) of the FBR representing the ultimate objective of these efforts.