Clinical pharmacometrics to optimize immunosuppressive therapy in kidney transplantation

Abstract

This thesis was aimed at optimizing immunosuppressive therapy in kidney transplant recipients using pharmacometric models. Kidney transplantation comprises the preferred treatment strategy for patients with end-stage kidney disease. Its clinical success is challenged by graft rejection, necessitating lifelong immunosuppressive therapy to accommodate host-graft adaptation. Herein, achievement of balanced immunosuppression is vital for optimal outcomes, but is complicated by pharmacokinetic variability of the immunosuppressants. Currently, therapeutic drug monitoring (TDM)-guided dose individualization is conducted in an effort to achieve immunosuppressant exposure with adequate rejection prophylaxis and minimal toxicity. However, TDM target attainment rates are low and graft rejection and toxicity are observed in patients with on-target immunosuppressant exposure, indicating a need for further improvement. Pharmacometrics harnesses options to modernize this endeavor, allowing for model-based prediction of individual pharmacokinetic behavior and dosage requirements from patient characteristics and pharmacokinetic observations. We reviewed the current state of pharmacometrics in kidney transplantation, developed pharmacometric models for alemtuzumab and iohexol, externally evaluated a model-based dosing tool for everolimus, and combined pharmacometrics with microsampling to enable remote monitoring of immunosuppressant exposure and kidney function, simultaneously. Our research underlines the broad applicability of pharmacometrics and provides an impulse for future research to further optimize immunosuppressive therapy in kidney transplantation.