One of the major challenges of transplant medicine is to optimise immunosuppression to reduce drug toxicity and infection incidence while maintaining adequate immunosuppression to prevent graft rejection. Reliable markers that reflect the functional extent of immunosuppression and allow individualised therapy management are still lacking. The aim of the ChilSFree study is to define immune markers that can act as a proxy for the functional degree of immunosuppression after liver transplantation. However, this is complicated by the complex data properties of immune monitoring data, which make it difficult to analyse their predictive potential in an efficient and easily applicable way. Challenges include the high-dimensional nature of the immune monitoring parameters, the longitudinal data structure, the combination of longitudinal biomarker measurements and a time-to-event outcome, the translation of this statistical concept into a dynamic predictive model and, finally, changes in immunosuppressive treatment over the observation period.