The starting point for our research are clinical studies showing that partial and total meniscectomies lead to prevalence of premature osteoarthritis in knee joints. Accordingly, substantial efforts are being made towards finding adequate regenerative tissue for meniscus replacement. In collaboration with partners from the Institute of Orthopaedic Research and Biomechanics at the University Ulm we work in parallel on an experimental study based on nonwoven scaffolds that enables in-vitro investigations and on an in-silico approach that is used to better understand and optimize the processes within the scaffolds. The presentation will first discuss the mathematical model that we have established so far and that forms a coupled system of reaction-diffusion-taxis equations where cell densities play a dominant role. The main focus will then be placed on the numerical challenges, along with a summary on the computational results that we have obtained so far and their validation with respect to experimental data. Also, recent results on an extension to porous media effects in the scaffold and their coupling with the cell dynamics model will be described. Last but not least, we report on current work on the parameter identification problem, along with statistical methods for computing parameter sensitivities. References: Surulescu, Christina, et al.: An in-silico approach to meniscus tissue regeneration: Modeling, numerical simulation, and experimental analysis, Applied Mathematical Modelling 151 116535 (2026) doi.org/10.1016/j.apm.2025.116535 Grosjean, Elise, and Bernd Simeon: The non-intrusive reduced basis two-grid method applied to sensitivity analysis, ESAIM: Mathematical Modelling and Numerical Analysis 59.1 101-135 (2025) doi.org/10.1051/m2an/2024044